Intelligent Computing Techniques for Smart Energy Systems
Proceedings of ICTSES 2018
1st Edition
Published on 16. December 2019
XVIII, 1046 pages
978-981-15-0214-9 (ISBN)
Description
The book compiles the research works related to smart solutions concept in context to smart energy systems, maintaining electrical grid discipline and resiliency, computational collective intelligence consisted of interaction between smart devices, smart environments and smart interactions, as well as information technology support for such areas. It includes high-quality papers presented in the International Conference on Intelligent Computing Techniques for Smart Energy Systems organized by Manipal University Jaipur. This book will motivate scholars to work in these areas. The book also prophesies their approach to be used for the business and the humanitarian technology development as research proposal to various government organizations for funding approval.
More details
Series
Language
English
Place of publication
Singapore
Singapore
Publishing group
Springer Singapore
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
XVIII, 1046 p. 585 illus., 416 illus. in color.
File size
45,63 MB
ISBN-13
978-981-15-0214-9 (9789811502149)
DOI
10.1007/978-981-15-0214-9
Schweitzer Classification
Other editions
Additional editions
Akhtar Kalam | Khaleequr Rehman Niazi | Amit Soni
Intelligent Computing Techniques for Smart Energy Systems
Proceedings of ICTSES 2018
Book
02/2020
Springer
€353.09
Shipment within 3-4 weeks
Persons
Akhtar Kalam has been at Victoria University (VU) since 1985. He is a former Deputy Dean of the Faculty of Health, Engineering and Science and Head of Engineering of the College of Engineering and Science. Currently, he is the Head of External Engagement. He is also the current Chair of the Academic Board in the Engineering Institute of Technology, Perth, Australia, and the Editor in Chief of Australian Journal of Electrical & Electronics Engineering. Also, he has a Distinguished Professorship position at the University of New South Wales, Sydney, Australia, three Indian and five Malaysian universities. Professor Kalam has conducted research, provided industrial consultancy and published more than 542 publications on his area of expertise. He has written 26-plus books in the area. More than 35 PhD students have graduated under his supervision He received his B.Sc. and B.Sc. Engineering degrees from University of Calcutta and the Aligarh Muslim University, India. He completed his MS and Ph.D degrees at the University of Oklahoma, USA and the University of Bath, UK respectively. He provides consultancy for major electrical utilities, manufacturers and other industry bodies in his field of expertise. He is a Fellow of EA, IET, AIE, a life member of IEEE and a member CIGRE AP B5 Study Committee.
Khaleequr Rehman Niazi has over 29 years of teaching and research experience. Currently he is a Professor in the Department of Electrical Engineering and Dean of Academic affairs of MNIT Jaipur. He has vast administrative experience. He has worked as Head, Electrical Engineering Department, Advisor- Estate, Chief Vigilance Officer, Chairman- Senate Undergraduate committee, Member Board of Governors of MNIT, Professor In-Charge - Training & Placement, Nodal Officer-TEQIP, etc at MNIT, Jaipur. He has published over 200 papers in International journals and conferences. He has also published a book. He has so far supervised 16 Ph.Ds and many PG dissertations and carried out many sponsored R&D projects. He has diversified research interests in the areas of conventional power and renewable energy systems, smart grid, distribution network reconfiguration, flexible AC transmission systems (FACTS), and application of AI and ANN techniques to power systems. He has been visiting professor of Taibah University, Kingdom of Saudi Arabia. He was also nominated by DST India for International Training on "Electrical Power system automation Technology and applications" at Wuhan China. He is presently Associate Editor of RPG IET journal of UK, Senior Member IEEE, USA and life member ISTE, India.
Amit Soni Amit Soni has 18 years of teaching and research experience and is presently working as Professor & Head of Department of Electrical Engineering, Manipal University Jaipur, Jaipur. He has completed PhD (2012) and M. Tech. (2005) in "Power Systems" both from M.N.I.T. Jaipur. He has worked in various administrativecapacities such as Director, RTU affiliated Engineering College, Head, Electrical Department, Coordinator and Chairman for various Academic Committees at both undergraduate and postgraduate levels. He has published more than 50 research papers in repute SCI indexed journals and conferences. He has supervised 3 Ph.Ds and many PG students under his guidance. Currently, he is working on DST SERB funded research project in collaboration with MLSU, Udaipur and NIT Uttarakhand. Students from all levels i.e. UG, PG and Ph.D. are working under his supervision on different areas. He has also published book on "Power System Engineering" for RTU affiliated institutions. Currently, he is working on Solar PV Materials & its applications, Photovoltaics, Renewable Energy Systems and Power System. He is life member of Solar Energy Society of India, Member ISTE, India and IEEE, USA.
Shahbaz Ahmed Siddiqui is Associate Professor and Head in Department of Mechatronics Engineering, Manipal University, Jaipur India. He completed his Ph.D and M. Tech. from M.N.I.T., Jaipur in Power Systems. He is teaching undergraduate and post graduate courses and his areas of research interests include artificial intelligence applications to power system operation and control, operation and control of microgrid, and synthesization and fabrication of solar cells. He has published more than 50 papers in International Journals and Conferences. He is life member of ISTE, India and member of IEEE, USA.
Ankit Mundra is working as Assistant Professor in the Department of Information Technology, Faculty of Engineering, Manipal University Jaipur. He is pursuing PhD from M.N.I.T., Jaipur in Internet of Things. His area of research expertise is Network Security, Wireless Networks, Online Fraud Detection. He has published more than 25 research articles in International Journals and Conferences. He has been the editor of two international books published by Springer Nature.
Khaleequr Rehman Niazi has over 29 years of teaching and research experience. Currently he is a Professor in the Department of Electrical Engineering and Dean of Academic affairs of MNIT Jaipur. He has vast administrative experience. He has worked as Head, Electrical Engineering Department, Advisor- Estate, Chief Vigilance Officer, Chairman- Senate Undergraduate committee, Member Board of Governors of MNIT, Professor In-Charge - Training & Placement, Nodal Officer-TEQIP, etc at MNIT, Jaipur. He has published over 200 papers in International journals and conferences. He has also published a book. He has so far supervised 16 Ph.Ds and many PG dissertations and carried out many sponsored R&D projects. He has diversified research interests in the areas of conventional power and renewable energy systems, smart grid, distribution network reconfiguration, flexible AC transmission systems (FACTS), and application of AI and ANN techniques to power systems. He has been visiting professor of Taibah University, Kingdom of Saudi Arabia. He was also nominated by DST India for International Training on "Electrical Power system automation Technology and applications" at Wuhan China. He is presently Associate Editor of RPG IET journal of UK, Senior Member IEEE, USA and life member ISTE, India.
Amit Soni Amit Soni has 18 years of teaching and research experience and is presently working as Professor & Head of Department of Electrical Engineering, Manipal University Jaipur, Jaipur. He has completed PhD (2012) and M. Tech. (2005) in "Power Systems" both from M.N.I.T. Jaipur. He has worked in various administrativecapacities such as Director, RTU affiliated Engineering College, Head, Electrical Department, Coordinator and Chairman for various Academic Committees at both undergraduate and postgraduate levels. He has published more than 50 research papers in repute SCI indexed journals and conferences. He has supervised 3 Ph.Ds and many PG students under his guidance. Currently, he is working on DST SERB funded research project in collaboration with MLSU, Udaipur and NIT Uttarakhand. Students from all levels i.e. UG, PG and Ph.D. are working under his supervision on different areas. He has also published book on "Power System Engineering" for RTU affiliated institutions. Currently, he is working on Solar PV Materials & its applications, Photovoltaics, Renewable Energy Systems and Power System. He is life member of Solar Energy Society of India, Member ISTE, India and IEEE, USA.
Shahbaz Ahmed Siddiqui is Associate Professor and Head in Department of Mechatronics Engineering, Manipal University, Jaipur India. He completed his Ph.D and M. Tech. from M.N.I.T., Jaipur in Power Systems. He is teaching undergraduate and post graduate courses and his areas of research interests include artificial intelligence applications to power system operation and control, operation and control of microgrid, and synthesization and fabrication of solar cells. He has published more than 50 papers in International Journals and Conferences. He is life member of ISTE, India and member of IEEE, USA.
Ankit Mundra is working as Assistant Professor in the Department of Information Technology, Faculty of Engineering, Manipal University Jaipur. He is pursuing PhD from M.N.I.T., Jaipur in Internet of Things. His area of research expertise is Network Security, Wireless Networks, Online Fraud Detection. He has published more than 25 research articles in International Journals and Conferences. He has been the editor of two international books published by Springer Nature.
Content
1 - Preface [Seite 6]
2 - Contents [Seite 8]
3 - About the Editors [Seite 18]
4 - LED Driver Design and Thermal Management [Seite 20]
4.1 - 1 Introduction [Seite 20]
4.1.1 - 1.1 Experimental Setup [Seite 21]
4.2 - 2 Conclusion [Seite 26]
4.3 - References [Seite 26]
5 - Automatic Generation Control of Interconnected Power Systems Using Elephant Herding Optimization [Seite 28]
5.1 - 1 Introduction [Seite 28]
5.2 - 2 Modelling of Interconnected Three-Area Power System [Seite 29]
5.3 - 3 Proposed Elephant Herding Optimization (EHO) Based Strategy for LFC [Seite 31]
5.3.1 - 3.1 Clan Updating Operator [Seite 31]
5.3.2 - 3.2 Separating Operator [Seite 32]
5.4 - 4 Control Strategy [Seite 32]
5.5 - 5 Results and Discussions [Seite 33]
5.6 - 6 Conclusion [Seite 33]
5.7 - References [Seite 36]
6 - Use of Ti-Doped Hafnia in Photovoltaic Devices: Ab Initio Calculations [Seite 38]
6.1 - 1 Introduction [Seite 38]
6.2 - 2 FP-LAPW Theory [Seite 39]
6.3 - 3 Results and Discussion [Seite 40]
6.4 - 4 Conclusions [Seite 42]
6.5 - References [Seite 42]
7 - Electronic and Optical Response of Photovoltaic Semiconductor ZrSxTe2-x [Seite 43]
7.1 - 1 Introduction [Seite 43]
7.2 - 2 FP-LAPW Method [Seite 44]
7.3 - 3 Results and Discussion [Seite 44]
7.3.1 - 3.1 Electronic Structure [Seite 44]
7.4 - 4 Conclusions [Seite 46]
7.5 - References [Seite 47]
8 - Investigation of Optical Response of Silver Molybdate for Photovoltaic [Seite 48]
8.1 - 1 Introduction [Seite 48]
8.2 - 2 Methodology [Seite 49]
8.2.1 - 2.1 Experiment [Seite 49]
8.2.2 - 2.2 Theory [Seite 49]
8.3 - 3 Results and Discussion [Seite 50]
8.3.1 - 3.1 Electronic Response [Seite 50]
8.3.2 - 3.2 Compton Profile [Seite 51]
8.3.3 - 3.3 Optical Response [Seite 51]
8.4 - 4 Conclusions [Seite 53]
8.5 - References [Seite 53]
9 - Comparative Analysis of Conventional and Meta-heuristic Algorithm Based Control Schemes for Single Link Robotic Manipulator [Seite 55]
9.1 - 1 Introduction [Seite 55]
9.2 - 2 Control of a Single Link Manipulator [Seite 56]
9.3 - 3 Conventional Control Techniques [Seite 58]
9.3.1 - 3.1 PID Control [Seite 58]
9.3.2 - 3.2 FOPID Control [Seite 58]
9.3.3 - 3.3 Tuning of Controller Using GA [Seite 58]
9.4 - 4 Results [Seite 59]
9.5 - 5 Conclusion [Seite 61]
9.6 - References [Seite 61]
10 - Synthesis of Antenna Array Pattern Using Ant Lion Optimization Algorithm for Wide Null Placement and Low Dynamic Range Ratio [Seite 63]
10.1 - 1 Introduction [Seite 63]
10.2 - 2 Problem Formulation [Seite 64]
10.2.1 - 2.1 Wide Null Placement with Reduced SLL [Seite 65]
10.2.2 - 2.2 Dynamic Range Ratio (DRR) Constraint-Based Peak Side Lobe Level (PSLL) Minimization [Seite 66]
10.3 - 3 Results and Discussion [Seite 67]
10.3.1 - 3.1 Wide Null Placement with Reduced SLL [Seite 67]
10.3.2 - 3.2 Dynamic Range Ratio (DRR) Constraint-Based Peak Side Lobe Level (PSLL) Minimization [Seite 69]
10.4 - 4 Conclusion [Seite 71]
10.5 - References [Seite 72]
11 - Design and Analysis of a Hybrid Non-volatile SRAM Cell for Energy Autonomous IoT [Seite 73]
11.1 - 1 Introduction [Seite 74]
11.2 - 2 Background [Seite 75]
11.3 - 3 Proposed NV-SRAM Cell [Seite 76]
11.3.1 - 3.1 Cell Design Concept [Seite 76]
11.4 - 4 Results [Seite 79]
11.5 - 5 Conclusion [Seite 80]
11.6 - References [Seite 80]
12 - Bandgap Engineering of AgGaS2 for Optoelectronic Devices: First-Principles Computational Technique [Seite 82]
12.1 - 1 Introduction [Seite 82]
12.2 - 2 Computational Details [Seite 83]
12.3 - 3 Structural Information [Seite 84]
12.4 - 4 Results and Discussion [Seite 85]
12.4.1 - 4.1 Electronic Properties [Seite 85]
12.4.2 - 4.2 Optical Properties [Seite 87]
12.5 - 5 Conclusion [Seite 88]
12.6 - References [Seite 88]
13 - Intelligent Power Sharing Control for Hybrid System [Seite 90]
13.1 - 1 Introduction [Seite 90]
13.2 - 2 System Description and Modeling [Seite 91]
13.3 - 3 Control Strategy [Seite 92]
13.4 - 4 Proposed Intelligent Control [Seite 93]
13.5 - 5 Results and Discussion [Seite 95]
13.5.1 - 5.1 Steady-State Response [Seite 95]
13.5.2 - 5.2 Dynamic Response [Seite 96]
13.6 - 6 Conclusion [Seite 98]
13.7 - References [Seite 99]
14 - Comparative Analysis of Various Classifiers for Gesture Recognition [Seite 100]
14.1 - 1 Introduction [Seite 101]
14.2 - 2 Related Work [Seite 101]
14.2.1 - 2.1 Detection of Target [Seite 102]
14.2.2 - 2.2 Recognition of Target [Seite 102]
14.3 - 3 Proposed Work [Seite 103]
14.4 - 4 Result [Seite 104]
14.5 - 5 Conclusion and Future Development [Seite 107]
14.6 - References [Seite 108]
15 - Artificial Intelligence Based Optimization Techniques: A Review [Seite 110]
15.1 - 1 Introduction [Seite 110]
15.2 - 2 Genetic Algorithm [Seite 111]
15.3 - 3 Particle Swarm Optimization [Seite 112]
15.4 - 4 Ant Colony Optimization (ACO) [Seite 113]
15.5 - 5 BAT Algorithm [Seite 114]
15.5.1 - 5.1 Random Fly [Seite 114]
15.5.2 - 5.2 Local Random Walk [Seite 115]
15.6 - 6 Elephant Herding Optimization [Seite 115]
15.6.1 - 6.1 Clan Updating Operator [Seite 115]
15.6.2 - 6.2 Separating Operator [Seite 116]
15.7 - 7 Conclusion [Seite 117]
15.8 - References [Seite 117]
16 - Optimal Location and Sizing of Microgrid for Radial Distribution Systems [Seite 119]
16.1 - 1 Introduction [Seite 120]
16.2 - 2 Problem Formulation [Seite 121]
16.2.1 - 2.1 Objective Function [Seite 121]
16.2.2 - 2.2 Constraints [Seite 121]
16.3 - 3 Methodology [Seite 122]
16.3.1 - 3.1 Proposed Algorithm [Seite 122]
16.4 - 4 Case Study [Seite 123]
16.5 - 5 Conclusion [Seite 126]
16.6 - References [Seite 126]
17 - Constraint Tariff Model to Reduce the Amount of Cross Subsidy Incorporated in Electricity Tariff Using Iterative Optimization Technique [Seite 128]
17.1 - 1 Introduction [Seite 128]
17.2 - 2 Basic Model and Recommended Modifications [Seite 129]
17.3 - 3 Optimization Problem Formulation [Seite 130]
17.3.1 - 3.1 The Objective Function [Seite 130]
17.3.2 - 3.2 The Operating Constraints [Seite 130]
17.3.3 - 3.3 The Bounds [Seite 131]
17.4 - 4 Algorithm Developed [Seite 131]
17.5 - 5 Availability of Data and Assumptions [Seite 133]
17.6 - 6 Results and Discussion [Seite 134]
17.7 - 7 Conclusion [Seite 135]
17.8 - References [Seite 136]
18 - Titration Machine: A New Approach Using Arduino [Seite 137]
18.1 - 1 Introduction [Seite 137]
18.2 - 2 Motivation [Seite 138]
18.3 - 3 Experimental Setup [Seite 138]
18.4 - 4 Working and Flowchart [Seite 139]
18.5 - 5 Circuit Diagram of Arduino with Motor Shield [Seite 139]
18.6 - 6 A Glimpse of the Titration Machine [Seite 140]
18.7 - 7 Results [Seite 142]
18.8 - 8 Conclusions [Seite 143]
18.9 - References [Seite 143]
19 - Hybrid Method for Cluster Analysis of Big Data [Seite 144]
19.1 - 1 Introduction [Seite 144]
19.2 - 2 Related Work [Seite 145]
19.3 - 3 Proposed Work [Seite 146]
19.3.1 - 3.1 The Proposed Model [Seite 146]
19.3.2 - 3.2 Workflow of the Algorithm [Seite 146]
19.4 - 4 Results and Discussion [Seite 147]
19.5 - 5 Conclusions [Seite 149]
19.6 - References [Seite 150]
20 - A New Radio Frequency Harvesting System [Seite 151]
20.1 - 1 Introduction [Seite 151]
20.2 - 2 Overview of the System [Seite 152]
20.2.1 - 2.1 Rectenna [Seite 153]
20.2.2 - 2.2 Power Converter [Seite 153]
20.2.3 - 2.3 Flyback Converter [Seite 154]
20.3 - 3 Methodology [Seite 155]
20.3.1 - 3.1 Conceptual Frame Work and Simulations [Seite 156]
20.4 - 4 Results [Seite 160]
20.5 - 5 Conclusion [Seite 161]
20.6 - References [Seite 162]
21 - Backpropagation Algorithm-Based Approach to Mitigate Soiling from PV Module [Seite 163]
21.1 - 1 Introduction [Seite 164]
21.2 - 2 Factors Influencing Dust Settlement [Seite 164]
21.3 - 3 Training and Modeling of ANN [Seite 166]
21.4 - 4 Results and Discussion [Seite 168]
21.5 - 5 Conclusion [Seite 170]
21.6 - References [Seite 171]
22 - Real-Time Low-Frequency Oscillations Monitoring and Coherency Determination in a Wind-Integrated Power System [Seite 172]
22.1 - 1 Introduction [Seite 172]
22.2 - 2 Problem Formulation [Seite 174]
22.2.1 - 2.1 Damping Index (DI) [Seite 174]
22.2.2 - 2.2 Coherent Groups Determination [Seite 175]
22.3 - 3 Proposed Methodology [Seite 175]
22.3.1 - 3.1 Optimal PMU Placement [Seite 175]
22.3.2 - 3.2 Wind Site Selection [Seite 175]
22.3.3 - 3.3 Proposed PMU-ANN Based Method [Seite 176]
22.4 - 4 Results [Seite 177]
22.4.1 - 4.1 Optimal PMU Placement [Seite 178]
22.4.2 - 4.2 Proposed Real-Time Monitoring [Seite 178]
22.5 - 5 Conclusion [Seite 180]
22.6 - References [Seite 180]
23 - Design and Performance Analysis of Different Structures of MEMS PVDF-Based Low-Frequency Piezoelectric Energy Harvester [Seite 182]
23.1 - 1 Introduction [Seite 183]
23.2 - 2 Mathematical Modeling [Seite 184]
23.3 - 3 Design Parameters of Cantilever Beam [Seite 185]
23.3.1 - 3.1 Design Parameters for the Straight T-Shaped Cantilever Structure [Seite 186]
23.3.2 - 3.2 Designing Parameters of the Pi-Shaped Cantilever Structure [Seite 186]
23.4 - 4 Results and Discussion [Seite 187]
23.4.1 - 4.1 Modal Analysis [Seite 187]
23.4.2 - 4.2 Dynamic Analysis [Seite 189]
23.4.3 - 4.3 Piezoelectric Analysis [Seite 189]
23.4.4 - 4.4 Stress Analysis [Seite 189]
23.5 - 5 Conclusion [Seite 189]
23.6 - References [Seite 190]
24 - Designing and Implementation of Overhead Conductor Altitude Measurement System Using GPS for Sag Monitoring [Seite 192]
24.1 - 1 Introduction [Seite 193]
24.2 - 2 Designing of Overhead Conductor Altitude Measurement System [Seite 194]
24.2.1 - 2.1 Field Test [Seite 195]
24.3 - 3 Accuracy Enhancement Techniques [Seite 197]
24.4 - 4 Results [Seite 198]
24.4.1 - 4.1 Error Analysis [Seite 200]
24.5 - 5 Sag Estimation [Seite 201]
24.6 - 6 Conclusion [Seite 201]
24.7 - References [Seite 202]
25 - Risk-Averse G2V Scheduling of Electric Vehicle Aggregator for Improved Market Operations [Seite 204]
25.1 - 1 Introduction [Seite 204]
25.2 - 2 Risk Controlling in Stochastic Optimization [Seite 206]
25.3 - 3 Scenario Generation and Reduction [Seite 206]
25.4 - 4 Risk-Aversive Formulation of Stochastic Programming Problem [Seite 207]
25.5 - 5 Simulation Results of Risk-Constrained Stochastic Scheduling [Seite 209]
25.6 - 6 Conclusion [Seite 211]
25.7 - References [Seite 211]
26 - Optical Gain Tuning in Type-I Al0.45Ga0.55As/GaAs0.84P0.16/Al0.45Ga0.55As Nano-heterostructure [Seite 213]
26.1 - 1 Introduction [Seite 214]
26.2 - 2 Theoretical Background [Seite 214]
26.3 - 3 Simulation Results [Seite 215]
26.4 - 4 Conclusions [Seite 217]
26.5 - References [Seite 218]
27 - Semantic Similarity Computation Among Hindi Words Using Hindi Lexical Ontology [Seite 219]
27.1 - 1 Introduction [Seite 219]
27.2 - 2 Theoretical Background of Hindi Ontology [Seite 220]
27.2.1 - 2.1 The Structure for Indo WordNet [Seite 221]
27.3 - 3 Proposed Semantic Similarity Method [Seite 221]
27.4 - 4 Experiments and Analysis [Seite 222]
27.5 - 5 Conclusion [Seite 225]
27.6 - References [Seite 226]
28 - A Dual-Band Microstrip Patch Antenna for Wireless Applications [Seite 227]
28.1 - 1 Introduction [Seite 227]
28.2 - 2 Antenna Geometry [Seite 228]
28.3 - 3 Results and Discussion [Seite 229]
28.4 - 4 Conclusion [Seite 230]
28.5 - References [Seite 233]
29 - Analysis of Energy Consumption and Implementation of R-Statistical Programming for Load Forecasting in Presence of Solar Generation [Seite 234]
29.1 - 1 Introduction [Seite 234]
29.2 - 2 Details of the Installed System [Seite 235]
29.3 - 3 Advanced Metering Infrastructure (AMI) Architecture [Seite 235]
29.3.1 - 3.1 Smart Energy Meters [Seite 236]
29.3.2 - 3.2 Communication Network [Seite 236]
29.3.3 - 3.3 Smart Grid Control Center [Seite 236]
29.4 - 4 Advanced Data Analysis Using Smart Meter Data [Seite 236]
29.4.1 - 4.1 Signature of Monthly Energy Consumption of the House [Seite 237]
29.4.2 - 4.2 Signature of Daily Energy Consumption of the House [Seite 237]
29.5 - 5 Impact of Renewable Integration [Seite 238]
29.5.1 - 5.1 Grid-Connected Solar PV System Without Battery Backup [Seite 239]
29.5.2 - 5.2 Grid-Connected Solar PV System with Battery Backup for Partial Load [Seite 240]
29.5.3 - 5.3 Comparison of Monthly Consumption Pattern [Seite 240]
29.6 - 6 Forecasting of Consumer Energy Consumption [Seite 241]
29.6.1 - 6.1 ARIMA Forecasting Model [Seite 241]
29.6.2 - 6.2 Simple Exponential Smoothing Forecasting Model [Seite 242]
29.7 - 7 Results [Seite 243]
29.8 - 8 Conclusion [Seite 244]
29.9 - References [Seite 245]
30 - A Comprehensive Analysis of Delta and Adaptive Delta Modulated Modular Multilevel Converter [Seite 246]
30.1 - 1 Introduction [Seite 246]
30.2 - 2 Delta Modulation [Seite 248]
30.3 - 3 Adaptive Delta Modulation [Seite 248]
30.4 - 4 Results and Discussion [Seite 248]
30.5 - 5 Conclusion [Seite 252]
30.6 - References [Seite 253]
31 - Speed Control of PMSM Drive Using Jaya Optimization Based Model Reduction [Seite 254]
31.1 - 1 Introduction [Seite 254]
31.2 - 2 Mathematical Modeling of PMSM Drive and Control [Seite 255]
31.2.1 - 2.1 PMSM Drive [Seite 256]
31.3 - 3 Order Reduction and Controller Design for PMSM [Seite 257]
31.3.1 - 3.1 Jaya Optimization Algorithm [21, 22] [Seite 257]
31.3.2 - 3.2 Current Control Loop [Seite 257]
31.3.3 - 3.3 Speed Control Loop [Seite 259]
31.3.4 - 3.4 Tuning of PI Controller Using Optimization Algorithm [Seite 260]
31.4 - 4 Conclusion [Seite 262]
31.5 - References [Seite 262]
32 - Jaya Optimization-Based PID Controller for Z-Source Inverter Using Model Reduction [Seite 264]
32.1 - 1 Introduction [Seite 264]
32.2 - 2 Z-Source Inverter [Seite 266]
32.3 - 3 Jaya Optimization Algorithm [Seite 268]
32.4 - 4 Simulation and Results [Seite 271]
32.5 - 5 Conclusion [Seite 273]
32.6 - References [Seite 273]
33 - Stability Analysis of an Offshore Wind and Marine Current Farm in Grid Connected Mode Using SMES [Seite 275]
33.1 - 1 Introduction [Seite 275]
33.2 - 2 Configuration of the Studied Systems [Seite 276]
33.2.1 - 2.1 Modeling of OWF [Seite 276]
33.2.2 - 2.2 DFIG Modeling [Seite 277]
33.2.3 - 2.3 Marine Current Turbine [Seite 278]
33.2.4 - 2.4 SCIG Modeling [Seite 279]
33.3 - 3 SMES Modeling [Seite 279]
33.4 - 4 H-Infinity Controller of SMES [Seite 280]
33.5 - 5 Simulation Results and Discussion [Seite 282]
33.6 - 6 Conclusion [Seite 283]
33.7 - References [Seite 284]
34 - Modeling and Simulation of Proton Exchange Membrane Fuel Cell Hybrid Electric Vehicle [Seite 286]
34.1 - 1 Introduction [Seite 286]
34.2 - 2 Architecture of Fuel Cell Hybrid Electric Vehicle [Seite 288]
34.2.1 - 2.1 Fuel Cell [Seite 288]
34.2.2 - 2.2 Unidirectional DC-DC Converter [Seite 288]
34.2.3 - 2.3 Bidirectional DC-DC Converter [Seite 289]
34.2.4 - 2.4 Energy Storage System (ESS) [Seite 289]
34.3 - 3 Simulation Results and Discussion [Seite 290]
34.3.1 - 3.1 Case Study 1 (Cold Start Mode) [Seite 290]
34.3.2 - 3.2 Case Study-2 (Normal Operating Mode) [Seite 290]
34.3.3 - 3.3 Case Study 3 (Acceleration Mode) [Seite 291]
34.3.4 - 3.4 Case Study 4 (Deceleration Mode) [Seite 292]
34.4 - 4 Conclusion [Seite 293]
34.5 - References [Seite 294]
35 - Optimum Performance of Carbon Nanotube Field-Effect Transistor Based Sense Amplifier D Flip-Flop Circuits [Seite 297]
35.1 - 1 Introduction [Seite 297]
35.2 - 2 Theoretical Analysis and Design Consideration of Existing D Flip-Flop Topologies (CNFET) [Seite 298]
35.3 - 3 Carbon Nanotube Field-Effect Transistor (CNFET) [Seite 300]
35.3.1 - 3.1 Diameter of CNFET (DCNT) [Seite 300]
35.3.2 - 3.2 Threshold Voltage (Vth) [Seite 301]
35.3.3 - 3.3 Width of CNTFET [Seite 301]
35.3.4 - 3.4 On Off Current Ratio [Seite 301]
35.3.5 - 3.5 Transconductance (gm) [Seite 302]
35.4 - 4 Simulated Results of Various High-Performance D Flip-Flop Designs [Seite 302]
35.5 - 5 Conclusion [Seite 304]
35.6 - References [Seite 304]
36 - Flower Pollination Based Solar PV Parameter Extraction for Double Diode Model [Seite 306]
36.1 - 1 Introduction [Seite 307]
36.2 - 2 Modeling of Solar PV [Seite 308]
36.3 - 3 Problem Formulation [Seite 309]
36.4 - 4 Flower Pollination Algorithm [Seite 310]
36.5 - 5 Simulation Results and Discussions [Seite 312]
36.6 - 6 Conclusion [Seite 314]
36.7 - References [Seite 314]
37 - Cost-Benefit Calculation Using AB2X4 (A = Zn, Cd [Seite 316]
37.1 - 1 Introduction [Seite 316]
37.2 - 2 Theoretical Methodology [Seite 317]
37.3 - 3 Result Discussion [Seite 317]
37.3.1 - 3.1 Method Overview [Seite 318]
37.3.2 - 3.2 PV Module Cost Calculation [Seite 318]
37.4 - 4 Conclusion [Seite 320]
37.5 - References [Seite 320]
38 - Detection and Analysis of Power System Faults in the Presence of Wind Power Generation Using Stockwell Transform Based Median [Seite 321]
38.1 - 1 Introduction [Seite 322]
38.2 - 2 Test System Used for the Proposed Study [Seite 323]
38.3 - 3 Proposed Methodology [Seite 324]
38.3.1 - 3.1 Proposed Fault Index [Seite 324]
38.3.2 - 3.2 Stockwell Transform [Seite 324]
38.4 - 4 S-Transform Based Simulation Results with Discussion [Seite 325]
38.4.1 - 4.1 Line to Ground Fault [Seite 325]
38.4.2 - 4.2 Double Line Fault [Seite 326]
38.4.3 - 4.3 Double Line to Ground Fault [Seite 327]
38.4.4 - 4.4 Three-Phase Fault Involving Ground [Seite 328]
38.4.5 - 4.5 Comparative Study [Seite 329]
38.5 - 5 Conclusion [Seite 330]
38.6 - References [Seite 330]
39 - A Directional Relaying Scheme for Microgrid Protection [Seite 332]
39.1 - 1 Introduction [Seite 332]
39.2 - 2 Test Microgrid [Seite 334]
39.3 - 3 Directional Relaying Algorithm [Seite 334]
39.3.1 - 3.1 Detectors for the Directional Approach [Seite 334]
39.3.2 - 3.2 Proposed Technique [Seite 336]
39.4 - 4 Simulation Results [Seite 336]
39.4.1 - 4.1 Faults During Grid-Connected Mode [Seite 337]
39.4.2 - 4.2 Results for Fault During Islanded Mode [Seite 338]
39.4.3 - 4.3 Results for Load Switching [Seite 338]
39.4.4 - 4.4 Results for High-Impedance Fault (HIF) in Islanding Mode [Seite 339]
39.5 - 5 Conclusion [Seite 340]
39.6 - References [Seite 340]
40 - Wavefunctions and Optical Gain in In0.24Ga0.76N/GaN Type-I Nano-heterostructure Under External Uniaxial Strain [Seite 342]
40.1 - 1 Introduction [Seite 342]
40.2 - 2 Device Structure and Modeling [Seite 343]
40.3 - 3 Results and Discussion [Seite 345]
40.4 - 4 Conclusions [Seite 349]
40.5 - References [Seite 349]
41 - Cost-Benefit Analysis in Distribution System of Jaipur City After DG and Capacitor Allocation [Seite 351]
41.1 - 1 Introduction [Seite 351]
41.2 - 2 Problem Formulation [Seite 352]
41.3 - 3 Proposed Technique [Seite 353]
41.4 - 4 Results [Seite 354]
41.4.1 - 4.1 69 Bus Test System [Seite 354]
41.4.2 - 4.2 130 Bus (Jaipur City) System [Seite 356]
41.5 - 5 Conclusion [Seite 357]
41.6 - References [Seite 358]
42 - Comparative Simulation Study of Dual-Axis Solar Tracking System on Simulink Platform [Seite 359]
42.1 - 1 Introduction [Seite 359]
42.2 - 2 Developed Solar Tracking System [Seite 360]
42.3 - 3 Characteristics of PV Cell [Seite 361]
42.3.1 - 3.1 Simulink Block Diagram [Seite 362]
42.4 - 4 Simulation Results and Discussion [Seite 364]
42.4.1 - 4.1 Elevated Tracking Results [Seite 364]
42.4.2 - 4.2 Azimuthal Tracking Results [Seite 364]
42.5 - 5 Conclusion [Seite 365]
42.6 - References [Seite 365]
43 - Performance Evaluation and Quality Analysis of Line and Node Based Voltage Stability Indices for the Determination of the Voltage Instability Point [Seite 366]
43.1 - 1 Introduction [Seite 366]
43.2 - 2 Existing Line and Node Based Voltage Stability Indices [Seite 367]
43.2.1 - 2.1 Maximum Loadability Index (MLI) [Seite 367]
43.2.2 - 2.2 Loadability Index (Lp) [Seite 368]
43.2.3 - 2.3 Line Loadability Index (Ls) [Seite 368]
43.2.4 - 2.4 Line Stability Index (Lmn) [Seite 368]
43.2.5 - 2.5 Line Stability Factor (LQP) [Seite 369]
43.2.6 - 2.6 Fast Voltage Stability Index (FVSI) [Seite 369]
43.2.7 - 2.7 Line Collapse Proximity Index (LCPI) [Seite 369]
43.2.8 - 2.8 L-Index [Seite 369]
43.3 - 3 Illustrative Example [Seite 370]
43.3.1 - 3.1 With One Fictitious Bus in the Middle of the Transmission Line [Seite 371]
43.3.2 - 3.2 With One Fictitious Bus at (3/4)th Length of the Transmission Line [Seite 373]
43.4 - 4 Conclusion [Seite 374]
43.5 - References [Seite 374]
44 - Channel Estimation in Massive MIMO with Spatial Channel Correlation Matrix [Seite 376]
44.1 - 1 Introduction [Seite 376]
44.2 - 2 System Model for Uplink Pilot Transmission [Seite 377]
44.3 - 3 MMSE Channel Estimation [Seite 378]
44.4 - 4 Spatial Channel Correlation and Pilot Contamination [Seite 379]
44.4.1 - 4.1 Impact of Spatial Correlation on Channel Estimation [Seite 380]
44.4.2 - 4.2 Impact of Pilot Contamination on Channel Estimation [Seite 380]
44.5 - 5 EW-MMSE and LS Estimation Schemes [Seite 380]
44.5.1 - 5.1 Element-Wise MMSE Channel Estimator [Seite 380]
44.5.2 - 5.2 Least-Square Channel Estimator [Seite 381]
44.6 - 6 Simulation Results [Seite 381]
44.7 - 7 Conclusion [Seite 382]
44.8 - References [Seite 383]
45 - A New Array Reconfiguration Scheme for Solar PV Systems Under Partial Shading Conditions [Seite 385]
45.1 - 1 Introduction [Seite 385]
45.2 - 2 System Description [Seite 387]
45.2.1 - 2.1 Modeling of a Total Cross Tied TCT Connection [Seite 387]
45.3 - 3 Methodology [Seite 388]
45.4 - 4 Simulation Results and Discussion [Seite 389]
45.4.1 - 4.1 Pattern 1-Short Wide [Seite 389]
45.4.2 - 4.2 Pattern 2-Long Wide [Seite 392]
45.5 - 5 Conclusion [Seite 393]
45.6 - References [Seite 394]
46 - Adaptability Analysis of Particle Swarm Optimization Variants in Maximum Power Tracking for Solar PV Systems [Seite 395]
46.1 - 1 Introduction [Seite 395]
46.2 - 2 System Description [Seite 396]
46.3 - 3 Modelling of PV Cell [Seite 396]
46.3.1 - 3.1 Characteristics of PV Module [Seite 398]
46.3.2 - 3.2 Characteristics of PV Array Under Partial Shading Conditions [Seite 399]
46.4 - 4 Particle Swarm Optimization: Outline of PSO [Seite 399]
46.4.1 - 4.1 Neighbourhood Selection Scheme [Seite 401]
46.5 - 5 Simulation and Results Discussion [Seite 402]
46.6 - 6 Conclusion [Seite 403]
46.7 - References [Seite 407]
47 - Fault Location Methods in HVDC Transmission System-A Review [Seite 408]
47.1 - 1 Introduction [Seite 408]
47.2 - 2 Literature Review on Fault Location Techniques [Seite 412]
47.3 - 3 Conclusion [Seite 415]
47.4 - References [Seite 415]
48 - Optimal Reactive Power Dispatch Through Minimization of Real Power Loss and Voltage Deviation [Seite 417]
48.1 - 1 Introduction [Seite 419]
48.2 - 2 Problem Formulation [Seite 420]
48.2.1 - 2.1 Objective Function [Seite 420]
48.2.2 - 2.2 System Constraints [Seite 420]
48.2.3 - 2.3 General Formulation of the Objective Function [Seite 421]
48.3 - 3 Solution Methodology [Seite 421]
48.4 - 4 Simulation Result [Seite 422]
48.5 - 5 Conclusion [Seite 425]
48.6 - References [Seite 425]
49 - IoT Enabled Intelligent Energy Management and Optimization Scheme with Controlling and Monitoring Approach in Modern Classroom Applications [Seite 427]
49.1 - 1 Introduction [Seite 428]
49.2 - 2 Related Works [Seite 428]
49.3 - 3 Contextual Analysis/Background Survey [Seite 429]
49.4 - 4 Energy Management in Campus: Challenges [Seite 430]
49.5 - 5 Existing System [Seite 431]
49.6 - 6 Methodology [Seite 431]
49.6.1 - 6.1 Design Criteria [Seite 431]
49.6.2 - 6.2 Device Configuration and Working Principles [Seite 431]
49.7 - 7 Testing and Evaluation of Project Implementation [Seite 432]
49.8 - 8 Future Scope and Conclusion [Seite 435]
49.9 - References [Seite 435]
50 - High Power Density Parallel LC-Link PV Inverter for Stand-alone and Grid Mode of Operation [Seite 437]
50.1 - 1 Introduction [Seite 438]
50.2 - 2 Operation Principle Under Different Modes [Seite 439]
50.2.1 - 2.1 Configuration [Seite 439]
50.2.2 - 2.2 Principle of Operation [Seite 440]
50.3 - 3 Parameter Design Procedure [Seite 441]
50.4 - 4 Zero Voltage Switching Operation (ZVS) [Seite 444]
50.5 - 5 Simulation Results [Seite 445]
50.6 - 6 Conclusions [Seite 448]
50.7 - References [Seite 449]
51 - A Hybrid Forecasting Model Based on Artificial Neural Network and Teaching Learning Based Optimization Algorithm for Day-Ahead Wind Speed Prediction [Seite 450]
51.1 - 1 Introduction [Seite 450]
51.2 - 2 Working Principle of Hybrid Forecasting Model [Seite 451]
51.3 - 3 Forecasting Results and Discussions [Seite 453]
51.4 - 4 Conclusion [Seite 458]
51.5 - References [Seite 458]
52 - Risk Averse Energy Management for Grid Connected Microgrid Using Information Gap Decision Theory [Seite 459]
52.1 - 1 Introduction [Seite 460]
52.2 - 2 Information Gap Decision Theory [Seite 461]
52.3 - 3 Problem Formulation [Seite 462]
52.3.1 - 3.1 Deterministic MG Energy Management [Seite 462]
52.3.2 - 3.2 IGDT Based MG Energy Management [Seite 462]
52.4 - 4 Numerical Simulation [Seite 463]
52.5 - 5 Conclusions [Seite 466]
52.6 - References [Seite 466]
53 - Power Quality Improvement of Microgrid Using Double Bridge Shunt Active Power Filter (DBSAPF) [Seite 468]
53.1 - 1 Introduction [Seite 468]
53.2 - 2 Shunt Active Power Filter [Seite 469]
53.3 - 3 Hysteresis Control Technique [Seite 470]
53.4 - 4 Proposed Double Bridge SAPF [Seite 471]
53.5 - 5 Simulation Results [Seite 472]
53.5.1 - 5.1 Case Study 1 [Seite 473]
53.5.2 - 5.2 Case Study 2 [Seite 474]
53.6 - 6 Conclusion [Seite 475]
53.7 - References [Seite 476]
54 - Opposition Theory Enabled Intelligent Whale Optimization Algorithm [Seite 477]
54.1 - 1 Introduction [Seite 477]
54.2 - 2 Whale Optimization Algorithm [Seite 479]
54.2.1 - 2.1 Girdling Prey [Seite 479]
54.2.2 - 2.2 Bubble-Net Attacking Method (Exploitation Phase) [Seite 480]
54.2.3 - 2.3 Prey Search (Exploration Phase) [Seite 480]
54.3 - 3 Opposition Theory Enabled Intelligent Whale Optimization Algorithm [Seite 481]
54.3.1 - 3.1 Implementation of OBL on OIWOA [Seite 481]
54.3.2 - 3.2 Implementation of Sinusoidal Function [Seite 482]
54.3.3 - 3.3 Implementation of Crossover [Seite 482]
54.4 - 4 Results and Discussions [Seite 482]
54.5 - 5 Conclusions [Seite 484]
54.6 - References [Seite 484]
55 - Adaptive Inertia-Weighted Firefly Algorithm [Seite 486]
55.1 - 1 Introduction [Seite 486]
55.2 - 2 Firefly Algorithm [Seite 488]
55.3 - 3 Improved Firefly Algorithm [Seite 489]
55.4 - 4 Simulation Results and Discussions [Seite 491]
55.4.1 - 4.1 Results on Uni-modal Functions [Seite 491]
55.4.2 - 4.2 Results on Multi-modal and Fixed Dimension Multi-modal Functions [Seite 492]
55.5 - 5 Conclusions [Seite 492]
55.6 - References [Seite 493]
56 - A Review of Scheduling Techniques and Communication Protocols for Smart Homes Capable of Implementing Demand Response [Seite 495]
56.1 - 1 Introduction [Seite 495]
56.2 - 2 Scheduling Techniques [Seite 496]
56.2.1 - 2.1 Rule-Based Scheduling Techniques [Seite 496]
56.2.2 - 2.2 Training-Based Artificial Intelligent Techniques [Seite 497]
56.2.3 - 2.3 Heuristic and Meta-Heuristic AI Techniques [Seite 497]
56.3 - 3 Communication [Seite 498]
56.3.1 - 3.1 Wired Communication Protocols [Seite 498]
56.3.2 - 3.2 Wireless-Based Communication [Seite 499]
56.3.3 - 3.3 Hybrid and Integrated Protocols [Seite 499]
56.4 - 4 Conclusion [Seite 500]
56.5 - References [Seite 500]
57 - A Robust Open-Loop Frequency Estimation Method for Single-Phase Systems [Seite 504]
57.1 - 1 Introduction [Seite 504]
57.2 - 2 Even Harmonics Generation [Seite 505]
57.3 - 3 Filtering Requirements [Seite 506]
57.3.1 - 3.1 DC-Offset Rejection [Seite 506]
57.3.2 - 3.2 Extraction of Fundamental Orthogonal Components [Seite 507]
57.3.3 - 3.3 Elimination of Higher Order Harmonics [Seite 508]
57.4 - 4 Frequency Estimation [Seite 509]
57.4.1 - 4.1 Simulation Setup and Results [Seite 509]
57.5 - 5 Conclusion [Seite 512]
57.6 - References [Seite 512]
58 - Demand-Side Load Management for Peak Shaving [Seite 514]
58.1 - 1 Introduction [Seite 514]
58.2 - 2 Demand-Side Load Management [Seite 515]
58.3 - 3 Modeling and Simulation [Seite 517]
58.3.1 - 3.1 Modeling [Seite 517]
58.3.2 - 3.2 Simulation Process [Seite 518]
58.4 - 4 Simulation Results [Seite 520]
58.5 - 5 Conclusions [Seite 523]
58.6 - References [Seite 523]
59 - A New Line Voltage Stability Index (NLVSI) For Voltage Stability Assessment [Seite 524]
59.1 - 1 Introduction [Seite 524]
59.2 - 2 Existing Line Based Voltage Stability Indices [Seite 526]
59.2.1 - 2.1 Line Stability Index (Lmn) [Seite 526]
59.2.2 - 2.2 Fast Voltage Stability Index (FVSI) [Seite 526]
59.2.3 - 2.3 Line Stability Factor (LQP) [Seite 526]
59.2.4 - 2.4 Line Voltage Reactive Power Index (VQIline) [Seite 527]
59.2.5 - 2.5 New Voltage Stability Index (NVSI) [Seite 527]
59.3 - 3 Effect of Delta on Voltage [Seite 527]
59.4 - 4 Proposed Index Formulation [Seite 529]
59.5 - 5 Representation of ZIP Load Model [Seite 531]
59.6 - 6 Test Case Results [Seite 531]
59.6.1 - 6.1 When Conventional (i.e. Constant Power) Load is Used [Seite 532]
59.6.2 - 6.2 When ZIP Load Model is Used [Seite 534]
59.6.3 - 6.3 Results Comparison Between Conventional Load and ZIP Load Model [Seite 534]
59.7 - 7 Conclusion [Seite 536]
59.8 - References [Seite 537]
60 - A Comprehensive Comparative Economic Analysis of ACO and CS Technique for Optimal Operation of Stand-alone HES [Seite 538]
60.1 - 1 Introduction [Seite 540]
60.2 - 2 Mathematical Formulation [Seite 541]
60.2.1 - 2.1 Modeling of System Components [Seite 542]
60.2.2 - 2.2 Operation Strategy [Seite 545]
60.2.3 - 2.3 Objective Function [Seite 546]
60.2.4 - 2.4 Constraints [Seite 546]
60.3 - 3 Ant Colony Optimization [Seite 547]
60.4 - 4 Cuckoo Search Technique [Seite 548]
60.4.1 - 4.1 Levy Flights Technique [Seite 548]
60.4.2 - 4.2 Random Walk Technique [Seite 549]
60.5 - 5 Comparative Analysis [Seite 549]
60.6 - 6 Conclusion [Seite 552]
60.7 - References [Seite 553]
61 - Demand Response in Distribution Systems: A Comprehensive Review [Seite 554]
61.1 - 1 Introduction [Seite 554]
61.2 - 2 Background and Classification of DRPs [Seite 555]
61.3 - 3 An Overview of DR [Seite 557]
61.4 - 4 Conclusion [Seite 560]
61.5 - References [Seite 560]
62 - Stochastic Operational Management of Grid-Connected Microgrid Under Uncertainty of Renewable Resources and Load Demand [Seite 562]
62.1 - 1 Introduction [Seite 562]
62.2 - 2 Stochastic Modeling of Renewable Generation and System Load [Seite 563]
62.2.1 - 2.1 Stochastic Modeling of Wind Power Generation [Seite 563]
62.2.2 - 2.2 Stochastic Modeling of PV Power Generation [Seite 564]
62.2.3 - 2.3 Stochastic Modeling of System Load Demand [Seite 565]
62.2.4 - 2.4 Combined Stochastic Modeling of the System [Seite 565]
62.2.5 - 2.5 Tournament Selection Based Scenarios Sampling [Seite 565]
62.3 - 3 Problem Formulation [Seite 565]
62.3.1 - 3.1 Objective Function [Seite 565]
62.3.2 - 3.2 Constraints [Seite 566]
62.4 - 4 Solution Methodology [Seite 567]
62.5 - 5 Simulation Results and Discussion [Seite 567]
62.6 - 6 Conclusion [Seite 569]
62.7 - References [Seite 570]
63 - Real-Time High-Speed Novel Data Acquisition System Based on ZYNQ [Seite 571]
63.1 - 1 Introduction [Seite 572]
63.2 - 2 Overview of the Hardware Platform and Contemporary Solutions [Seite 572]
63.3 - 3 Firmware Design of Data Acquisition System [Seite 573]
63.4 - 4 Software Interface for Data Acquisition System [Seite 574]
63.5 - 5 Results and Discussion [Seite 576]
63.6 - 6 Conclusion [Seite 577]
63.7 - References [Seite 578]
64 - Exergetic Analysis of Glazed Photovoltaic Thermal (Single-Channel) Module Using Whale Optimization Algorithm and Genetic Algorithm [Seite 579]
64.1 - 1 Introduction [Seite 580]
64.2 - 2 System Description [Seite 582]
64.3 - 3 Tool Used for Optimization [Seite 582]
64.4 - 4 Result and Discussion [Seite 583]
64.5 - 5 Conclusion [Seite 587]
64.6 - Appendix: Optimized Value of Parameters [Seite 587]
64.7 - References [Seite 588]
65 - An 8-Bit Charge Redistribution SAR ADC [Seite 589]
65.1 - 1 Introduction [Seite 589]
65.2 - 2 8-Bit SAR ADC Architecture [Seite 591]
65.3 - 3 Implementation of Inner Blocks [Seite 593]
65.3.1 - 3.1 S/H Circuit [Seite 593]
65.3.2 - 3.2 Comparator [Seite 594]
65.4 - 4 Simulation Results [Seite 595]
65.5 - 5 Conclusion [Seite 597]
65.6 - References [Seite 597]
66 - Analysis of Triple-Threshold Technique for Power Optimization in SRAM Bit-Cell for Low-Power Applications at 45 Nm CMOS Technology [Seite 598]
66.1 - 1 Introduction [Seite 598]
66.2 - 2 Approach [Seite 600]
66.3 - 3 Analysis and Result [Seite 600]
66.3.1 - 3.1 Data Stability [Seite 600]
66.3.2 - 3.2 Read Noise Margin [Seite 600]
66.3.3 - 3.3 Write Noise Margin [Seite 601]
66.3.4 - 3.4 Average Power and Leakage Power [Seite 602]
66.4 - 4 Conclusion [Seite 604]
66.5 - References [Seite 604]
67 - Low Power Adder Circuits Using Various Leakage Reduction Techniques [Seite 606]
67.1 - 1 Introduction [Seite 606]
67.2 - 2 Literature Review [Seite 607]
67.2.1 - 2.1 Sleep Transistor Technique [Seite 607]
67.2.2 - 2.2 Stack Transistor Technique [Seite 608]
67.2.3 - 2.3 Super Cutoff (SCCMOS) Technique [Seite 609]
67.3 - 3 Implementation of Adder Circuit [Seite 610]
67.3.1 - 3.1 1-Bit Full Adder [Seite 610]
67.3.2 - 3.2 4-Bit Ripple Carry Adder [Seite 612]
67.4 - 4 Simulation and Analysis [Seite 612]
67.5 - 5 Conclusion [Seite 614]
67.6 - References [Seite 615]
68 - A Nature-Inspired Metaheuristic Swarm Based Optimization Technique BFOA Based Optimal Controller for Damping of SSR [Seite 617]
68.1 - 1 Introduction [Seite 617]
68.2 - 2 System Configuration [Seite 618]
68.3 - 3 Development of Overall System Model [Seite 619]
68.4 - 4 Application of Optimal Control Theory [Seite 619]
68.5 - 5 Optimal Parameter Selection Using BFOA [Seite 619]
68.5.1 - 5.1 A Brief Overview of BFOA [Seite 619]
68.6 - 6 Results and Discussions [Seite 620]
68.6.1 - 6.1 Case Study with 60% Series Compensation [Seite 620]
68.7 - 7 Conclusion [Seite 622]
68.8 - References [Seite 624]
69 - New Fuzzy Divergence Measures, Series, Its Bounds and Applications in Strategic Decision-Making [Seite 626]
69.1 - 1 Introduction [Seite 626]
69.2 - 2 New Information Divergence Measures [Seite 627]
69.3 - 3 Series of Fuzzy Divergence Measures [Seite 628]
69.4 - 4 Some New Other Fuzzy Information Divergence Measures [Seite 632]
69.5 - 5 New Information Divergence and Their Relation with Other Well-Known Divergence Measures [Seite 633]
69.6 - 6 Application of Proposed Series of Fuzzy Divergence Making in Strategic Decision-Making [Seite 635]
69.7 - 7 Conclusion [Seite 638]
69.8 - References [Seite 638]
70 - Mutual Coupling Reduction of Biconvex Lens Shaped Patch Antenna for 5G Application [Seite 639]
70.1 - 1 Introduction [Seite 639]
70.2 - 2 Design of the Proposed Antenna [Seite 640]
70.2.1 - 2.1 Rotman Lens Equations and Proposed Modification [Seite 640]
70.2.2 - 2.2 Design of the Perturbed Strip [Seite 641]
70.3 - 3 Design and Simulation of Proposed Antenna [Seite 641]
70.3.1 - 3.1 Substrate Material and Height [Seite 641]
70.3.2 - 3.2 Design of the Proposed Antenna [Seite 642]
70.3.3 - 3.3 Results from Simulation of the Proposed Antenna [Seite 642]
70.4 - 4 Conclusion [Seite 644]
70.5 - References [Seite 646]
71 - Analysis of Anti-Islanding Protection Methods Integrated in Distributed Generation [Seite 647]
71.1 - 1 Introduction [Seite 647]
71.2 - 2 Passive Methods [Seite 648]
71.3 - 3 Active Methods [Seite 650]
71.4 - 4 Simulation Results [Seite 652]
71.5 - 5 Conclusion [Seite 654]
71.6 - References [Seite 654]
72 - Color Image Watermarking with Watermark Hashing [Seite 656]
72.1 - 1 Introduction [Seite 656]
72.2 - 2 Background [Seite 657]
72.2.1 - 2.1 Singular Value Decomposition (SVD) [Seite 657]
72.2.2 - 2.2 Discrete Wavelet Transform (DWT) [Seite 658]
72.3 - 3 Hashing Techniques [Seite 658]
72.4 - 4 Experiments and Results [Seite 659]
72.5 - 5 Conclusions [Seite 662]
72.6 - References [Seite 663]
73 - Global Neighbourhood Algorithm Based Event-Triggered Automatic Generation Control [Seite 665]
73.1 - 1 Introduction [Seite 665]
73.2 - 2 AGC System Modelling [Seite 667]
73.3 - 3 Problem Formulation [Seite 668]
73.3.1 - 3.1 Objective Function [Seite 668]
73.3.2 - 3.2 Global Neighbourhood Algorithm (GNA) [Seite 668]
73.3.3 - 3.3 Delay/Sampling Time Dependent Stability [Seite 668]
73.4 - 4 Case Study [Seite 670]
73.4.1 - 4.1 Case I [Seite 670]
73.4.2 - 4.2 Case II [Seite 672]
73.5 - 5 Conclusions [Seite 673]
73.6 - References [Seite 673]
74 - A Review on Voltage and Frequency Control of Micro Hydro System [Seite 675]
74.1 - 1 Introduction [Seite 675]
74.2 - 2 Voltage and Frequency Regulation in Micro Hydro System [Seite 677]
74.3 - 3 Classification of ELC on the Basis of Loading [Seite 679]
74.4 - 4 Discussion [Seite 681]
74.5 - 5 Conclusion [Seite 682]
74.6 - References [Seite 682]
75 - Performance Analysis of Solar and Plug-in Electric Vehicle's Integration to the Power System with Automatic Generation Control [Seite 684]
75.1 - 1 Introduction [Seite 684]
75.2 - 2 Proposed System Study [Seite 685]
75.3 - 3 Selection of Controller and Objective Function [Seite 686]
75.4 - 4 Jaya Optimization Technique [Seite 687]
75.5 - 5 Result and Analysis [Seite 688]
75.6 - 6 Conclusion [Seite 691]
75.7 - 7 Appendix [Seite 691]
75.8 - References [Seite 691]
76 - A Bibliographical View on Research and Developments of Photovoltaic and Thermal Technologies as a Combined System: PV/T System [Seite 693]
76.1 - 1 Introduction [Seite 694]
76.2 - 2 PV/T Air Collector [Seite 695]
76.2.1 - 2.1 Effect of Glazing [Seite 696]
76.2.2 - 2.2 Effect of Adding Thin Metallic Sheets (TMS) and Fins [Seite 696]
76.2.3 - 2.3 Effect of Packing Factor [Seite 697]
76.3 - 3 PV/T Water [Seite 697]
76.4 - 4 PV/T Combi [Seite 698]
76.5 - 5 Modelling of PV/T Collector [Seite 699]
76.6 - 6 Optimization Using Soft Computing [Seite 700]
76.7 - 7 Conclusion [Seite 701]
76.8 - References [Seite 701]
77 - UPM-NoC: Learning Based Framework to Predict Performance Parameters of Mesh Architecture in On-Chip Networks [Seite 703]
77.1 - 1 Introduction [Seite 704]
77.2 - 2 Related Work [Seite 705]
77.2.1 - 2.1 Learning Models Used in Different Aspects of NoC [Seite 705]
77.3 - 3 Design Strategy [Seite 706]
77.3.1 - 3.1 Detailed Layout of Unified Performance Model [Seite 706]
77.3.2 - 3.2 Data Collection Using Booksim Simulator [Seite 707]
77.3.3 - 3.3 Generation of Dataset [Seite 708]
77.4 - 4 Results and Discussion [Seite 708]
77.4.1 - 4.1 Experimental Results [Seite 708]
77.4.2 - 4.2 Validation [Seite 710]
77.4.3 - 4.3 Runtime Comparison [Seite 711]
77.5 - 5 Conclusion [Seite 712]
77.6 - References [Seite 712]
78 - Comparison of Performance Analysis of Optimal Controllers for Frequency Regulation of Three-Area Power System [Seite 714]
78.1 - 1 Introduction [Seite 714]
78.2 - 2 Three-Area System Under Study [Seite 716]
78.3 - 3 Optimization of Controller Gains [Seite 717]
78.4 - 4 Results and Discussion [Seite 718]
78.5 - 5 Conclusion [Seite 721]
78.6 - References [Seite 721]
79 - Optimal DG Allocation in a Microgrid Using Droop-Controlled Load Flow [Seite 723]
79.1 - 1 Introduction [Seite 723]
79.2 - 2 Problem Formulation [Seite 725]
79.3 - 3 Methodology [Seite 726]
79.3.1 - 3.1 Droop-Controlled Load Flow (DCLF) [Seite 726]
79.3.2 - 3.2 Non-Dominated Sorted Genetic Algorithm [Seite 727]
79.3.3 - 3.3 Fuzzy Satisfying Method [Seite 727]
79.4 - 4 Results and Discussions [Seite 727]
79.5 - 5 Conclusion [Seite 728]
79.6 - References [Seite 729]
80 - A Comparative Study of Classification Algorithms for Predicting Liver Disorders [Seite 731]
80.1 - 1 Introduction [Seite 731]
80.2 - 2 Literature Review [Seite 732]
80.3 - 3 Methodology [Seite 734]
80.3.1 - 3.1 Data Collection [Seite 734]
80.3.2 - 3.2 Data Preprocessing [Seite 734]
80.3.3 - 3.3 Applying Different Classification Algorithms [Seite 734]
80.3.4 - 3.4 Predicting the Test Set Results [Seite 735]
80.3.5 - 3.5 Comparison of Models [Seite 735]
80.4 - 4 Results and Discussion [Seite 735]
80.5 - 5 Conclusion and Future Work [Seite 737]
80.6 - References [Seite 737]
81 - Performance Analysis of Fabricated Buck-Boost MPPT Charge Controller [Seite 739]
81.1 - 1 Introduction [Seite 739]
81.2 - 2 Experimental Setup [Seite 740]
81.3 - 3 Experimental Result [Seite 741]
81.4 - 4 Conclusion [Seite 745]
81.5 - References [Seite 745]
82 - Performance Improvement of Cycloconverter Fed Induction Machine Using Shunt Active Power Filter [Seite 747]
82.1 - 1 Introduction [Seite 747]
82.2 - 2 Input Current of Cycloconverter [Seite 748]
82.2.1 - 2.1 Harmonic Analysis of Input Current [Seite 749]
82.3 - 3 Harmonic Analysis of Input Current of Cycloconverter Fed Induction Machine [Seite 749]
82.4 - 4 Design Shunt Active Power Filter [Seite 751]
82.4.1 - 4.1 Voltage Source Converter [Seite 751]
82.4.2 - 4.2 Fuzzy Logic Based Controller [Seite 752]
82.4.3 - 4.3 Hysteresis Band Current Control Technique [Seite 754]
82.4.4 - 4.4 Simulation of Cycloconverter Fed Induction Machine with Shunt Active Power Filter [Seite 754]
82.5 - 5 Conclusion [Seite 757]
82.6 - References [Seite 758]
83 - Comparative Analysis of Speaker Recognition System Based on Voice Activity Detection Technique, MFCC and PLP Features [Seite 759]
83.1 - 1 Introduction [Seite 759]
83.2 - 2 Methodology [Seite 760]
83.2.1 - 2.1 Voice Activity Detection (VAD) [Seite 761]
83.2.2 - 2.2 MFCC [Seite 762]
83.2.3 - 2.3 Vector Quantization [Seite 762]
83.2.4 - 2.4 Perceptual Linear Predictive (PLP) [Seite 763]
83.2.5 - 2.5 Database [Seite 763]
83.3 - 3 Results and Discussion [Seite 764]
83.4 - 4 Conclusions [Seite 765]
83.5 - References [Seite 765]
84 - Nonintrusive Load Monitoring: Making Smart Meters Smarter [Seite 766]
84.1 - 1 Introduction [Seite 766]
84.1.1 - 1.1 Need for NILM in Smart Meters [Seite 766]
84.2 - 2 Working of NILM and Challenges with It [Seite 767]
84.2.1 - 2.1 Data Acquisition [Seite 768]
84.3 - 3 Proposal [Seite 768]
84.3.1 - 3.1 Security Feature to Safeguard Consumer as Well as Appliance [Seite 768]
84.3.2 - 3.2 NILM to Predict Appliance Health [Seite 770]
84.4 - 4 Conclusion [Seite 770]
85 - Stabilization of Chaotic Systems Using Robust Optimal Controller [Seite 772]
85.1 - 1 Introduction [Seite 772]
85.2 - 2 Problem Statement [Seite 773]
85.3 - 3 Optimal Controller Design [Seite 774]
85.4 - 4 Design of Sliding Mode Controller [Seite 775]
85.5 - 5 Simulation Results [Seite 777]
85.6 - 6 Conclusion [Seite 779]
85.7 - References [Seite 779]
86 - Jaya Algorithm Based Optimal Allocation of Distributed Energy Resources [Seite 781]
86.1 - 1 Introduction [Seite 781]
86.2 - 2 Problem Description [Seite 783]
86.2.1 - 2.1 Boundary Limit of Node Voltage [Seite 783]
86.2.2 - 2.2 Power Balance [Seite 784]
86.2.3 - 2.3 Distribution Thermal Limit [Seite 784]
86.2.4 - 2.4 DERs Generation [Seite 784]
86.3 - 3 Description of the Jaya Algorithm [Seite 784]
86.4 - 4 Simulation Results [Seite 786]
86.4.1 - 4.1 Test System 1:33 Bus Radial Distribution Network [Seite 787]
86.4.2 - 4.2 Test System 2: 69 Bus Radial Distribution Network [Seite 787]
86.5 - 5 Conclusion [Seite 789]
86.6 - References [Seite 789]
87 - Bayesian Game Model: Demand Side Management for Residential Consumers with Electric Vehicles [Seite 791]
87.1 - 1 Introduction [Seite 791]
87.2 - 2 System Model [Seite 792]
87.2.1 - 2.1 Energy Consumption Cost Model [Seite 793]
87.2.2 - 2.2 Payoff Model for EV's [Seite 794]
87.3 - 3 Bayesian Game for Household Consumers [Seite 795]
87.4 - 4 Simulation Results [Seite 796]
87.5 - 5 Conclusion [Seite 798]
87.6 - References [Seite 798]
88 - Classification of Power System Disturbances Using Support Vector Machine in FPGA [Seite 800]
88.1 - 1 Introduction [Seite 800]
88.2 - 2 Support Vector Machine [Seite 801]
88.2.1 - 2.1 Linear SVM [Seite 801]
88.2.2 - 2.2 Nonlinear SVM [Seite 802]
88.3 - 3 Power System Transient [Seite 804]
88.4 - 4 SVM Implementation [Seite 805]
88.4.1 - 4.1 Software Simulation of SVM in MATLAB [Seite 805]
88.4.2 - 4.2 Hardware Co-simulation of SVM in FPGA [Seite 806]
88.5 - 5 Simulation Result [Seite 808]
88.6 - 6 Conclusion [Seite 809]
88.7 - References [Seite 809]
89 - Designing a Smart System for Air Quality Monitoring and Air Purification [Seite 811]
89.1 - 1 Introduction [Seite 811]
89.2 - 2 Filters and Sensors [Seite 812]
89.2.1 - 2.1 Filters [Seite 812]
89.2.2 - 2.2 Comparison of Various Filters Used in the Air Purifiers [Seite 814]
89.2.3 - 2.3 Sensors [Seite 814]
89.3 - 3 Proposed Model [Seite 815]
89.4 - 4 Results [Seite 816]
89.5 - 5 Conclusion [Seite 816]
89.6 - 6 Future Scope [Seite 817]
89.7 - References [Seite 817]
90 - Activation Map Networks with Deep Graphical Model for Semantic Segmentation [Seite 819]
90.1 - 1 Introduction [Seite 820]
90.2 - 2 Context Deep CRFs [Seite 820]
90.3 - 3 Pairwise Potential Functions [Seite 821]
90.4 - 4 Prognostic Process [Seite 822]
90.5 - 5 Prognostic Consummation Phase [Seite 823]
90.6 - 6 Practical Experiments with Validation Set on Matlab Contextual Modeling [Seite 823]
90.7 - 7 Conclusion [Seite 823]
90.8 - References [Seite 825]
91 - Grey Wolf Optimized PI Controller for Hybrid Power System Using SMES [Seite 827]
91.1 - 1 Introduction [Seite 827]
91.2 - 2 Hybrid Power System [Seite 828]
91.2.1 - 2.1 Mathematical Modelling of HPS [Seite 828]
91.3 - 3 Grey Wolf Optimization [Seite 830]
91.4 - 4 Simulation Results and Analysis [Seite 831]
91.5 - 5 Conclusion [Seite 834]
91.6 - References [Seite 835]
92 - JAYA-Evaluated Frequency Control Design for Hydroelectric Power System Using RFB and UPFC [Seite 836]
92.1 - 1 Introduction [Seite 837]
92.2 - 2 Studied Model [Seite 838]
92.3 - 3 JAYA-Optimized LFC Designs [Seite 838]
92.4 - 4 Result Analysis [Seite 841]
92.5 - 5 Conclusion [Seite 842]
92.6 - References [Seite 844]
93 - A Human Face-Shaped Microstrip Patch Antenna for Ultra-Wideband Applications [Seite 845]
93.1 - 1 Introduction [Seite 845]
93.2 - 2 Antenna Geometry [Seite 846]
93.3 - 3 Simulation Results [Seite 847]
93.4 - 4 Conclusion [Seite 849]
93.5 - References [Seite 851]
94 - Scheduling Energy Storage to Provide Balancing During Line Contingency at High Wind Penetration [Seite 853]
94.1 - 1 Introduction [Seite 855]
94.2 - 2 Problem Formulation [Seite 856]
94.2.1 - 2.1 Objective Function [Seite 856]
94.2.2 - 2.2 Operating Constraints [Seite 856]
94.2.3 - 2.3 Wind Generation Constraints [Seite 857]
94.2.4 - 2.4 Storage Constraints [Seite 857]
94.2.5 - 2.5 Power Balance [Seite 858]
94.3 - 3 Data and Result Analysis [Seite 858]
94.3.1 - 3.1 Data [Seite 858]
94.3.2 - 3.2 Result Analysis [Seite 858]
94.4 - 4 Conclusion [Seite 861]
94.5 - References [Seite 861]
95 - Multilevel Inverter Topologies in Renewable Energy Applications [Seite 863]
95.1 - 1 Introduction [Seite 864]
95.2 - 2 Classical MLI Topologies [Seite 865]
95.2.1 - 2.1 Neutral Point Clamped MLI (NPC MLI) [Seite 865]
95.2.2 - 2.2 Flying Capacitor MLI (FC MLI) [Seite 866]
95.2.3 - 2.3 Cascaded H-Bridge MLI (CHB MLI) [Seite 867]
95.3 - 3 RCC Topologies for LV Applications [Seite 867]
95.3.1 - 3.1 Developed Cascaded MLI (DC MLI) [Seite 867]
95.3.2 - 3.2 Cascaded Sub-multilevel Inverter (CSMLI) [Seite 867]
95.3.3 - 3.3 Multilevel DC-Link Inverter (MLDCLI) [Seite 869]
95.4 - 4 MLIs in Renewable Energy Applications [Seite 869]
95.4.1 - 4.1 Photovoltaic Systems [Seite 869]
95.4.2 - 4.2 Wind Energy Conversion System (WECS) [Seite 870]
95.4.3 - 4.3 Battery Storage Energy Systems (BSES) [Seite 870]
95.5 - 5 Conclusion [Seite 871]
95.6 - References [Seite 871]
96 - A Review on Demand Side Management Forecasting Models for Smart Grid [Seite 875]
96.1 - 1 Introduction [Seite 875]
96.2 - 2 Load Forecasting [Seite 877]
96.2.1 - 2.1 Traditional Forecasting Method [Seite 877]
96.2.2 - 2.2 Modern Forecasting Method [Seite 879]
96.3 - 3 Comparative Study of Forecasting Techniques [Seite 880]
96.4 - 4 Challenges and Conclusion [Seite 881]
96.5 - References [Seite 881]
97 - Detection of Suspicious Activity in ATM Booth [Seite 883]
97.1 - 1 Introduction [Seite 883]
97.1.1 - 1.1 Video Surveillance [Seite 884]
97.1.2 - 1.2 Overview [Seite 884]
97.2 - 2 Related Work [Seite 884]
97.3 - 3 Background [Seite 885]
97.3.1 - 3.1 Automated Teller Machine [Seite 885]
97.3.2 - 3.2 Suspicious Activities in ATM Booth [Seite 886]
97.4 - 4 Multiple Object Detection [Seite 886]
97.4.1 - 4.1 Viola-Jones Algorithm [Seite 886]
97.4.2 - 4.2 Approach Used for Multiple Person Detection [Seite 888]
97.5 - 5 Helmet Detection [Seite 888]
97.5.1 - 5.1 Circle Hough Transformation [Seite 888]
97.5.2 - 5.2 Approach Used for Helmet Detection [Seite 891]
97.6 - 6 Results Analysis [Seite 891]
97.7 - 7 Conclusion [Seite 895]
97.8 - References [Seite 896]
98 - Mitigation of Power Quality for Wind Energy Using Transmission Line Based on D-STATCOM [Seite 898]
98.1 - 1 Introduction [Seite 898]
98.2 - 2 Proposed Work [Seite 899]
98.3 - 3 Result and Discussion [Seite 900]
98.4 - 4 Conclusion [Seite 904]
98.5 - References [Seite 905]
99 - Performance Evaluation of Solar Power Plant [Seite 907]
99.1 - 1 Introduction [Seite 907]
99.2 - 2 Methodology and Input Parameters [Seite 908]
99.3 - 3 Result and Discussion [Seite 909]
99.4 - 4 Conclusion [Seite 909]
99.5 - References [Seite 911]
100 - GWO Based PID Controller Optimization for Robotic Manipulator [Seite 913]
100.1 - 1 Introduction [Seite 913]
100.2 - 2 Modeling of Robotic Manipulator [Seite 914]
100.3 - 3 Trajectory for Manipulator [Seite 916]
100.4 - 4 PID Controller [Seite 916]
100.5 - 5 Optimization Technique [Seite 917]
100.5.1 - 5.1 GWO Optimization [Seite 917]
100.6 - 6 Simulation and Result Analysis [Seite 918]
100.7 - 7 Conclusion [Seite 920]
100.8 - References [Seite 921]
101 - A 26 W Power Supply Based on Luo Converter with Improved Power Factor and Total Harmonic Distortion [Seite 922]
101.1 - 1 Introduction [Seite 922]
101.2 - 2 Proposed Model: A Power Factor Corrected (PFC) Power Supply Based on Luo Converter [Seite 923]
101.3 - 3 Components Selection of Power Supply [Seite 924]
101.4 - 4 System Loop Gain Analysis [Seite 924]
101.5 - 5 Model Stability Without Controller in Feedback [Seite 926]
101.6 - 6 Controller Design and Analysis of Stability System with Compensation Network [Seite 926]
101.6.1 - 6.1 Proportional Integral (PI) Controller [Seite 927]
101.6.2 - 6.2 Compensator's Component Design [Seite 928]
101.6.3 - 6.3 Model with Proposed Compensated Network: Stability Analysis [Seite 928]
101.7 - 7 Simulated Circuit Diagram and Analysis [Seite 929]
101.8 - 8 Results Analysis [Seite 929]
101.9 - 9 Conclusions [Seite 931]
101.10 - References [Seite 931]
102 - Optimal Strategic Bidding Using Intelligent Gravitational Search Algorithm for Profit Maximization of Power Suppliers in an Emerging Power Market [Seite 932]
102.1 - 1 Introduction [Seite 932]
102.2 - 2 Problem Formulation [Seite 934]
102.3 - 3 Intelligent GSA [Seite 935]
102.3.1 - 3.1 Opposition Phenomenon in GSA [Seite 936]
102.3.2 - 3.2 Update Mode of Gravity Constant [Seite 936]
102.4 - 4 Results and Discussion [Seite 936]
102.5 - 5 Conclusion [Seite 939]
102.6 - References [Seite 939]
103 - Synchrophasor Measurements Assisted Naïve Bayes Classification Based Real-Time Transient Stability Prediction of Power System [Seite 941]
103.1 - 1 Introduction [Seite 941]
103.2 - 2 Naïve Bayes Classifier [Seite 942]
103.3 - 3 Proposed Methodology [Seite 943]
103.3.1 - 3.1 Optimal PMU Placement Formulation [Seite 944]
103.3.2 - 3.2 Data Generation [Seite 944]
103.3.3 - 3.3 Feature Selection and Target Assignment [Seite 944]
103.3.4 - 3.4 Training, Testing and New Data [Seite 945]
103.3.5 - 3.5 Proposed Synchrophasor Measurement Assisted Naïve Bayes Classifier [Seite 945]
103.4 - 4 Simulation and Results [Seite 945]
103.4.1 - 4.1 Optimal PMU Placement [Seite 945]
103.4.2 - 4.2 PMU-Naïve Bayes Based Real-Time Transient Stability Prediction [Seite 946]
103.5 - 5 Conclusion [Seite 947]
103.6 - References [Seite 947]
104 - Device Modeling and Characteristics of Solution Processed Perovskite Solar Cell at Ambient Conditions [Seite 949]
104.1 - 1 Introduction [Seite 949]
104.2 - 2 Methodology [Seite 951]
104.2.1 - 2.1 Materials [Seite 951]
104.2.2 - 2.2 Preparation of Layers [Seite 952]
104.2.3 - 2.3 Device Fabrication [Seite 952]
104.3 - 3 Characterization [Seite 954]
104.3.1 - 3.1 I-V Measurement [Seite 954]
104.3.2 - 3.2 UV-Visible Analysis [Seite 954]
104.4 - 4 Summary [Seite 955]
104.5 - References [Seite 956]
105 - Control and Remote Sensing of an Irrigation System Using ZigBee Wireless Network [Seite 957]
105.1 - 1 Introduction [Seite 958]
105.2 - 2 Materials and Methods [Seite 959]
105.2.1 - 2.1 Conceptual System Design [Seite 959]
105.2.2 - 2.2 Sensor-Based In-field Station [Seite 960]
105.2.3 - 2.3 Irrigation Control Station [Seite 961]
105.2.4 - 2.4 Base Station [Seite 962]
105.2.5 - 2.5 Graphical User Interface (Gui) [Seite 962]
105.2.6 - 2.6 Mail Transfer [Seite 964]
105.3 - 3 Application and Observations [Seite 964]
105.4 - 4 Limitation [Seite 965]
105.5 - 5 Conclusion and Future Work [Seite 965]
105.6 - References [Seite 966]
106 - Analysis and Classification of Maximum Power Point Tracking (MPPT) Techniques: A Review [Seite 967]
106.1 - 1 Introduction [Seite 967]
106.2 - 2 Introduction to MPPT Techniques [Seite 968]
106.3 - 3 Types of MPPT Techniques [Seite 969]
106.3.1 - 3.1 Conventional Methods [Seite 969]
106.3.2 - 3.2 Soft Computing Methods [Seite 972]
106.3.3 - 3.3 Comparative Study [Seite 974]
106.4 - 4 Conclusion [Seite 975]
106.5 - References [Seite 975]
107 - A Study and Comprehensive Overview of Inverter Topologies for Grid-Connected Photovoltaic Systems (PVS) [Seite 977]
107.1 - 1 Introduction [Seite 978]
107.2 - 2 Evolution of Grid-Connected Inverter Topologies for PVS [Seite 978]
107.2.1 - 2.1 Centralized Inverters [Seite 981]
107.2.2 - 2.2 String Inverters and AC-Modules [Seite 981]
107.2.3 - 2.3 Multi-string Inverters and Cascaded Inverters [Seite 982]
107.3 - 3 Power Processing Stages-Based Inverters [Seite 982]
107.3.1 - 3.1 SSI: Single-Stage Inverter [Seite 982]
107.3.2 - 3.2 MSI: Multiple-Stage Inverter [Seite 983]
107.4 - 4 Conclusion [Seite 983]
107.5 - References [Seite 984]
108 - IOT Based Smart Writer [Seite 986]
108.1 - 1 Technical Details of the Paper [Seite 987]
108.1.1 - 1.1 Origin of Idea [Seite 987]
108.1.2 - 1.2 Definition of the Problem [Seite 987]
108.2 - 2 Objectives [Seite 987]
108.2.1 - 2.1 Printing [Seite 987]
108.2.2 - 2.2 Android/IOS Development [Seite 988]
108.2.3 - 2.3 App to Machine Communication [Seite 988]
108.2.4 - 2.4 Speech to Text Conversion [Seite 988]
108.2.5 - 2.5 Signature Printing and Encryption [Seite 988]
108.3 - 3 Workplan [Seite 988]
108.3.1 - 3.1 Literature Survey [Seite 988]
108.3.2 - 3.2 Writer Installation [Seite 988]
108.3.3 - 3.3 Arduino Programming [Seite 989]
108.3.4 - 3.4 Mobile App Development [Seite 989]
108.3.5 - 3.5 Paper Representation [Seite 989]
108.4 - 4 Methodology [Seite 989]
108.5 - 5 Organization of the Work Elements [Seite 990]
108.6 - 6 Time Schedule Chart [Seite 991]
108.7 - 7 Technologies Used [Seite 991]
108.8 - 8 Conclusion [Seite 991]
108.9 - References [Seite 991]
109 - Design and Implementation of Arduino Based Control System for Power Management of Household Utilities [Seite 992]
109.1 - 1 Introduction [Seite 992]
109.2 - 2 Environmental Impact of Conventional Energy Resources [Seite 993]
109.3 - 3 Solar Power and Scope in India [Seite 993]
109.4 - 4 Experimental Setup [Seite 994]
109.5 - 5 Results and Discussion [Seite 995]
109.6 - 6 Conclusion [Seite 998]
109.7 - References [Seite 998]
110 - Interfacing Python with DIgSILENT Power Factory: Automation of Tasks [Seite 999]
110.1 - 1 Python Interpreter [Seite 999]
110.2 - 2 Python Power Factory Module [Seite 1000]
110.3 - 3 Python Power Factory Module Usage [Seite 1000]
110.4 - 4 Conclusion [Seite 1002]
110.5 - References [Seite 1003]
111 - Recent Development in Perovskite Solar Cell Based on Planar Structures [Seite 1004]
111.1 - 1 Introduction [Seite 1004]
111.2 - 2 Planar Structure [Seite 1006]
111.3 - 3 The Inverted Planar Structure [Seite 1007]
111.4 - 4 Summary [Seite 1009]
111.5 - References [Seite 1009]
2 - Contents [Seite 8]
3 - About the Editors [Seite 18]
4 - LED Driver Design and Thermal Management [Seite 20]
4.1 - 1 Introduction [Seite 20]
4.1.1 - 1.1 Experimental Setup [Seite 21]
4.2 - 2 Conclusion [Seite 26]
4.3 - References [Seite 26]
5 - Automatic Generation Control of Interconnected Power Systems Using Elephant Herding Optimization [Seite 28]
5.1 - 1 Introduction [Seite 28]
5.2 - 2 Modelling of Interconnected Three-Area Power System [Seite 29]
5.3 - 3 Proposed Elephant Herding Optimization (EHO) Based Strategy for LFC [Seite 31]
5.3.1 - 3.1 Clan Updating Operator [Seite 31]
5.3.2 - 3.2 Separating Operator [Seite 32]
5.4 - 4 Control Strategy [Seite 32]
5.5 - 5 Results and Discussions [Seite 33]
5.6 - 6 Conclusion [Seite 33]
5.7 - References [Seite 36]
6 - Use of Ti-Doped Hafnia in Photovoltaic Devices: Ab Initio Calculations [Seite 38]
6.1 - 1 Introduction [Seite 38]
6.2 - 2 FP-LAPW Theory [Seite 39]
6.3 - 3 Results and Discussion [Seite 40]
6.4 - 4 Conclusions [Seite 42]
6.5 - References [Seite 42]
7 - Electronic and Optical Response of Photovoltaic Semiconductor ZrSxTe2-x [Seite 43]
7.1 - 1 Introduction [Seite 43]
7.2 - 2 FP-LAPW Method [Seite 44]
7.3 - 3 Results and Discussion [Seite 44]
7.3.1 - 3.1 Electronic Structure [Seite 44]
7.4 - 4 Conclusions [Seite 46]
7.5 - References [Seite 47]
8 - Investigation of Optical Response of Silver Molybdate for Photovoltaic [Seite 48]
8.1 - 1 Introduction [Seite 48]
8.2 - 2 Methodology [Seite 49]
8.2.1 - 2.1 Experiment [Seite 49]
8.2.2 - 2.2 Theory [Seite 49]
8.3 - 3 Results and Discussion [Seite 50]
8.3.1 - 3.1 Electronic Response [Seite 50]
8.3.2 - 3.2 Compton Profile [Seite 51]
8.3.3 - 3.3 Optical Response [Seite 51]
8.4 - 4 Conclusions [Seite 53]
8.5 - References [Seite 53]
9 - Comparative Analysis of Conventional and Meta-heuristic Algorithm Based Control Schemes for Single Link Robotic Manipulator [Seite 55]
9.1 - 1 Introduction [Seite 55]
9.2 - 2 Control of a Single Link Manipulator [Seite 56]
9.3 - 3 Conventional Control Techniques [Seite 58]
9.3.1 - 3.1 PID Control [Seite 58]
9.3.2 - 3.2 FOPID Control [Seite 58]
9.3.3 - 3.3 Tuning of Controller Using GA [Seite 58]
9.4 - 4 Results [Seite 59]
9.5 - 5 Conclusion [Seite 61]
9.6 - References [Seite 61]
10 - Synthesis of Antenna Array Pattern Using Ant Lion Optimization Algorithm for Wide Null Placement and Low Dynamic Range Ratio [Seite 63]
10.1 - 1 Introduction [Seite 63]
10.2 - 2 Problem Formulation [Seite 64]
10.2.1 - 2.1 Wide Null Placement with Reduced SLL [Seite 65]
10.2.2 - 2.2 Dynamic Range Ratio (DRR) Constraint-Based Peak Side Lobe Level (PSLL) Minimization [Seite 66]
10.3 - 3 Results and Discussion [Seite 67]
10.3.1 - 3.1 Wide Null Placement with Reduced SLL [Seite 67]
10.3.2 - 3.2 Dynamic Range Ratio (DRR) Constraint-Based Peak Side Lobe Level (PSLL) Minimization [Seite 69]
10.4 - 4 Conclusion [Seite 71]
10.5 - References [Seite 72]
11 - Design and Analysis of a Hybrid Non-volatile SRAM Cell for Energy Autonomous IoT [Seite 73]
11.1 - 1 Introduction [Seite 74]
11.2 - 2 Background [Seite 75]
11.3 - 3 Proposed NV-SRAM Cell [Seite 76]
11.3.1 - 3.1 Cell Design Concept [Seite 76]
11.4 - 4 Results [Seite 79]
11.5 - 5 Conclusion [Seite 80]
11.6 - References [Seite 80]
12 - Bandgap Engineering of AgGaS2 for Optoelectronic Devices: First-Principles Computational Technique [Seite 82]
12.1 - 1 Introduction [Seite 82]
12.2 - 2 Computational Details [Seite 83]
12.3 - 3 Structural Information [Seite 84]
12.4 - 4 Results and Discussion [Seite 85]
12.4.1 - 4.1 Electronic Properties [Seite 85]
12.4.2 - 4.2 Optical Properties [Seite 87]
12.5 - 5 Conclusion [Seite 88]
12.6 - References [Seite 88]
13 - Intelligent Power Sharing Control for Hybrid System [Seite 90]
13.1 - 1 Introduction [Seite 90]
13.2 - 2 System Description and Modeling [Seite 91]
13.3 - 3 Control Strategy [Seite 92]
13.4 - 4 Proposed Intelligent Control [Seite 93]
13.5 - 5 Results and Discussion [Seite 95]
13.5.1 - 5.1 Steady-State Response [Seite 95]
13.5.2 - 5.2 Dynamic Response [Seite 96]
13.6 - 6 Conclusion [Seite 98]
13.7 - References [Seite 99]
14 - Comparative Analysis of Various Classifiers for Gesture Recognition [Seite 100]
14.1 - 1 Introduction [Seite 101]
14.2 - 2 Related Work [Seite 101]
14.2.1 - 2.1 Detection of Target [Seite 102]
14.2.2 - 2.2 Recognition of Target [Seite 102]
14.3 - 3 Proposed Work [Seite 103]
14.4 - 4 Result [Seite 104]
14.5 - 5 Conclusion and Future Development [Seite 107]
14.6 - References [Seite 108]
15 - Artificial Intelligence Based Optimization Techniques: A Review [Seite 110]
15.1 - 1 Introduction [Seite 110]
15.2 - 2 Genetic Algorithm [Seite 111]
15.3 - 3 Particle Swarm Optimization [Seite 112]
15.4 - 4 Ant Colony Optimization (ACO) [Seite 113]
15.5 - 5 BAT Algorithm [Seite 114]
15.5.1 - 5.1 Random Fly [Seite 114]
15.5.2 - 5.2 Local Random Walk [Seite 115]
15.6 - 6 Elephant Herding Optimization [Seite 115]
15.6.1 - 6.1 Clan Updating Operator [Seite 115]
15.6.2 - 6.2 Separating Operator [Seite 116]
15.7 - 7 Conclusion [Seite 117]
15.8 - References [Seite 117]
16 - Optimal Location and Sizing of Microgrid for Radial Distribution Systems [Seite 119]
16.1 - 1 Introduction [Seite 120]
16.2 - 2 Problem Formulation [Seite 121]
16.2.1 - 2.1 Objective Function [Seite 121]
16.2.2 - 2.2 Constraints [Seite 121]
16.3 - 3 Methodology [Seite 122]
16.3.1 - 3.1 Proposed Algorithm [Seite 122]
16.4 - 4 Case Study [Seite 123]
16.5 - 5 Conclusion [Seite 126]
16.6 - References [Seite 126]
17 - Constraint Tariff Model to Reduce the Amount of Cross Subsidy Incorporated in Electricity Tariff Using Iterative Optimization Technique [Seite 128]
17.1 - 1 Introduction [Seite 128]
17.2 - 2 Basic Model and Recommended Modifications [Seite 129]
17.3 - 3 Optimization Problem Formulation [Seite 130]
17.3.1 - 3.1 The Objective Function [Seite 130]
17.3.2 - 3.2 The Operating Constraints [Seite 130]
17.3.3 - 3.3 The Bounds [Seite 131]
17.4 - 4 Algorithm Developed [Seite 131]
17.5 - 5 Availability of Data and Assumptions [Seite 133]
17.6 - 6 Results and Discussion [Seite 134]
17.7 - 7 Conclusion [Seite 135]
17.8 - References [Seite 136]
18 - Titration Machine: A New Approach Using Arduino [Seite 137]
18.1 - 1 Introduction [Seite 137]
18.2 - 2 Motivation [Seite 138]
18.3 - 3 Experimental Setup [Seite 138]
18.4 - 4 Working and Flowchart [Seite 139]
18.5 - 5 Circuit Diagram of Arduino with Motor Shield [Seite 139]
18.6 - 6 A Glimpse of the Titration Machine [Seite 140]
18.7 - 7 Results [Seite 142]
18.8 - 8 Conclusions [Seite 143]
18.9 - References [Seite 143]
19 - Hybrid Method for Cluster Analysis of Big Data [Seite 144]
19.1 - 1 Introduction [Seite 144]
19.2 - 2 Related Work [Seite 145]
19.3 - 3 Proposed Work [Seite 146]
19.3.1 - 3.1 The Proposed Model [Seite 146]
19.3.2 - 3.2 Workflow of the Algorithm [Seite 146]
19.4 - 4 Results and Discussion [Seite 147]
19.5 - 5 Conclusions [Seite 149]
19.6 - References [Seite 150]
20 - A New Radio Frequency Harvesting System [Seite 151]
20.1 - 1 Introduction [Seite 151]
20.2 - 2 Overview of the System [Seite 152]
20.2.1 - 2.1 Rectenna [Seite 153]
20.2.2 - 2.2 Power Converter [Seite 153]
20.2.3 - 2.3 Flyback Converter [Seite 154]
20.3 - 3 Methodology [Seite 155]
20.3.1 - 3.1 Conceptual Frame Work and Simulations [Seite 156]
20.4 - 4 Results [Seite 160]
20.5 - 5 Conclusion [Seite 161]
20.6 - References [Seite 162]
21 - Backpropagation Algorithm-Based Approach to Mitigate Soiling from PV Module [Seite 163]
21.1 - 1 Introduction [Seite 164]
21.2 - 2 Factors Influencing Dust Settlement [Seite 164]
21.3 - 3 Training and Modeling of ANN [Seite 166]
21.4 - 4 Results and Discussion [Seite 168]
21.5 - 5 Conclusion [Seite 170]
21.6 - References [Seite 171]
22 - Real-Time Low-Frequency Oscillations Monitoring and Coherency Determination in a Wind-Integrated Power System [Seite 172]
22.1 - 1 Introduction [Seite 172]
22.2 - 2 Problem Formulation [Seite 174]
22.2.1 - 2.1 Damping Index (DI) [Seite 174]
22.2.2 - 2.2 Coherent Groups Determination [Seite 175]
22.3 - 3 Proposed Methodology [Seite 175]
22.3.1 - 3.1 Optimal PMU Placement [Seite 175]
22.3.2 - 3.2 Wind Site Selection [Seite 175]
22.3.3 - 3.3 Proposed PMU-ANN Based Method [Seite 176]
22.4 - 4 Results [Seite 177]
22.4.1 - 4.1 Optimal PMU Placement [Seite 178]
22.4.2 - 4.2 Proposed Real-Time Monitoring [Seite 178]
22.5 - 5 Conclusion [Seite 180]
22.6 - References [Seite 180]
23 - Design and Performance Analysis of Different Structures of MEMS PVDF-Based Low-Frequency Piezoelectric Energy Harvester [Seite 182]
23.1 - 1 Introduction [Seite 183]
23.2 - 2 Mathematical Modeling [Seite 184]
23.3 - 3 Design Parameters of Cantilever Beam [Seite 185]
23.3.1 - 3.1 Design Parameters for the Straight T-Shaped Cantilever Structure [Seite 186]
23.3.2 - 3.2 Designing Parameters of the Pi-Shaped Cantilever Structure [Seite 186]
23.4 - 4 Results and Discussion [Seite 187]
23.4.1 - 4.1 Modal Analysis [Seite 187]
23.4.2 - 4.2 Dynamic Analysis [Seite 189]
23.4.3 - 4.3 Piezoelectric Analysis [Seite 189]
23.4.4 - 4.4 Stress Analysis [Seite 189]
23.5 - 5 Conclusion [Seite 189]
23.6 - References [Seite 190]
24 - Designing and Implementation of Overhead Conductor Altitude Measurement System Using GPS for Sag Monitoring [Seite 192]
24.1 - 1 Introduction [Seite 193]
24.2 - 2 Designing of Overhead Conductor Altitude Measurement System [Seite 194]
24.2.1 - 2.1 Field Test [Seite 195]
24.3 - 3 Accuracy Enhancement Techniques [Seite 197]
24.4 - 4 Results [Seite 198]
24.4.1 - 4.1 Error Analysis [Seite 200]
24.5 - 5 Sag Estimation [Seite 201]
24.6 - 6 Conclusion [Seite 201]
24.7 - References [Seite 202]
25 - Risk-Averse G2V Scheduling of Electric Vehicle Aggregator for Improved Market Operations [Seite 204]
25.1 - 1 Introduction [Seite 204]
25.2 - 2 Risk Controlling in Stochastic Optimization [Seite 206]
25.3 - 3 Scenario Generation and Reduction [Seite 206]
25.4 - 4 Risk-Aversive Formulation of Stochastic Programming Problem [Seite 207]
25.5 - 5 Simulation Results of Risk-Constrained Stochastic Scheduling [Seite 209]
25.6 - 6 Conclusion [Seite 211]
25.7 - References [Seite 211]
26 - Optical Gain Tuning in Type-I Al0.45Ga0.55As/GaAs0.84P0.16/Al0.45Ga0.55As Nano-heterostructure [Seite 213]
26.1 - 1 Introduction [Seite 214]
26.2 - 2 Theoretical Background [Seite 214]
26.3 - 3 Simulation Results [Seite 215]
26.4 - 4 Conclusions [Seite 217]
26.5 - References [Seite 218]
27 - Semantic Similarity Computation Among Hindi Words Using Hindi Lexical Ontology [Seite 219]
27.1 - 1 Introduction [Seite 219]
27.2 - 2 Theoretical Background of Hindi Ontology [Seite 220]
27.2.1 - 2.1 The Structure for Indo WordNet [Seite 221]
27.3 - 3 Proposed Semantic Similarity Method [Seite 221]
27.4 - 4 Experiments and Analysis [Seite 222]
27.5 - 5 Conclusion [Seite 225]
27.6 - References [Seite 226]
28 - A Dual-Band Microstrip Patch Antenna for Wireless Applications [Seite 227]
28.1 - 1 Introduction [Seite 227]
28.2 - 2 Antenna Geometry [Seite 228]
28.3 - 3 Results and Discussion [Seite 229]
28.4 - 4 Conclusion [Seite 230]
28.5 - References [Seite 233]
29 - Analysis of Energy Consumption and Implementation of R-Statistical Programming for Load Forecasting in Presence of Solar Generation [Seite 234]
29.1 - 1 Introduction [Seite 234]
29.2 - 2 Details of the Installed System [Seite 235]
29.3 - 3 Advanced Metering Infrastructure (AMI) Architecture [Seite 235]
29.3.1 - 3.1 Smart Energy Meters [Seite 236]
29.3.2 - 3.2 Communication Network [Seite 236]
29.3.3 - 3.3 Smart Grid Control Center [Seite 236]
29.4 - 4 Advanced Data Analysis Using Smart Meter Data [Seite 236]
29.4.1 - 4.1 Signature of Monthly Energy Consumption of the House [Seite 237]
29.4.2 - 4.2 Signature of Daily Energy Consumption of the House [Seite 237]
29.5 - 5 Impact of Renewable Integration [Seite 238]
29.5.1 - 5.1 Grid-Connected Solar PV System Without Battery Backup [Seite 239]
29.5.2 - 5.2 Grid-Connected Solar PV System with Battery Backup for Partial Load [Seite 240]
29.5.3 - 5.3 Comparison of Monthly Consumption Pattern [Seite 240]
29.6 - 6 Forecasting of Consumer Energy Consumption [Seite 241]
29.6.1 - 6.1 ARIMA Forecasting Model [Seite 241]
29.6.2 - 6.2 Simple Exponential Smoothing Forecasting Model [Seite 242]
29.7 - 7 Results [Seite 243]
29.8 - 8 Conclusion [Seite 244]
29.9 - References [Seite 245]
30 - A Comprehensive Analysis of Delta and Adaptive Delta Modulated Modular Multilevel Converter [Seite 246]
30.1 - 1 Introduction [Seite 246]
30.2 - 2 Delta Modulation [Seite 248]
30.3 - 3 Adaptive Delta Modulation [Seite 248]
30.4 - 4 Results and Discussion [Seite 248]
30.5 - 5 Conclusion [Seite 252]
30.6 - References [Seite 253]
31 - Speed Control of PMSM Drive Using Jaya Optimization Based Model Reduction [Seite 254]
31.1 - 1 Introduction [Seite 254]
31.2 - 2 Mathematical Modeling of PMSM Drive and Control [Seite 255]
31.2.1 - 2.1 PMSM Drive [Seite 256]
31.3 - 3 Order Reduction and Controller Design for PMSM [Seite 257]
31.3.1 - 3.1 Jaya Optimization Algorithm [21, 22] [Seite 257]
31.3.2 - 3.2 Current Control Loop [Seite 257]
31.3.3 - 3.3 Speed Control Loop [Seite 259]
31.3.4 - 3.4 Tuning of PI Controller Using Optimization Algorithm [Seite 260]
31.4 - 4 Conclusion [Seite 262]
31.5 - References [Seite 262]
32 - Jaya Optimization-Based PID Controller for Z-Source Inverter Using Model Reduction [Seite 264]
32.1 - 1 Introduction [Seite 264]
32.2 - 2 Z-Source Inverter [Seite 266]
32.3 - 3 Jaya Optimization Algorithm [Seite 268]
32.4 - 4 Simulation and Results [Seite 271]
32.5 - 5 Conclusion [Seite 273]
32.6 - References [Seite 273]
33 - Stability Analysis of an Offshore Wind and Marine Current Farm in Grid Connected Mode Using SMES [Seite 275]
33.1 - 1 Introduction [Seite 275]
33.2 - 2 Configuration of the Studied Systems [Seite 276]
33.2.1 - 2.1 Modeling of OWF [Seite 276]
33.2.2 - 2.2 DFIG Modeling [Seite 277]
33.2.3 - 2.3 Marine Current Turbine [Seite 278]
33.2.4 - 2.4 SCIG Modeling [Seite 279]
33.3 - 3 SMES Modeling [Seite 279]
33.4 - 4 H-Infinity Controller of SMES [Seite 280]
33.5 - 5 Simulation Results and Discussion [Seite 282]
33.6 - 6 Conclusion [Seite 283]
33.7 - References [Seite 284]
34 - Modeling and Simulation of Proton Exchange Membrane Fuel Cell Hybrid Electric Vehicle [Seite 286]
34.1 - 1 Introduction [Seite 286]
34.2 - 2 Architecture of Fuel Cell Hybrid Electric Vehicle [Seite 288]
34.2.1 - 2.1 Fuel Cell [Seite 288]
34.2.2 - 2.2 Unidirectional DC-DC Converter [Seite 288]
34.2.3 - 2.3 Bidirectional DC-DC Converter [Seite 289]
34.2.4 - 2.4 Energy Storage System (ESS) [Seite 289]
34.3 - 3 Simulation Results and Discussion [Seite 290]
34.3.1 - 3.1 Case Study 1 (Cold Start Mode) [Seite 290]
34.3.2 - 3.2 Case Study-2 (Normal Operating Mode) [Seite 290]
34.3.3 - 3.3 Case Study 3 (Acceleration Mode) [Seite 291]
34.3.4 - 3.4 Case Study 4 (Deceleration Mode) [Seite 292]
34.4 - 4 Conclusion [Seite 293]
34.5 - References [Seite 294]
35 - Optimum Performance of Carbon Nanotube Field-Effect Transistor Based Sense Amplifier D Flip-Flop Circuits [Seite 297]
35.1 - 1 Introduction [Seite 297]
35.2 - 2 Theoretical Analysis and Design Consideration of Existing D Flip-Flop Topologies (CNFET) [Seite 298]
35.3 - 3 Carbon Nanotube Field-Effect Transistor (CNFET) [Seite 300]
35.3.1 - 3.1 Diameter of CNFET (DCNT) [Seite 300]
35.3.2 - 3.2 Threshold Voltage (Vth) [Seite 301]
35.3.3 - 3.3 Width of CNTFET [Seite 301]
35.3.4 - 3.4 On Off Current Ratio [Seite 301]
35.3.5 - 3.5 Transconductance (gm) [Seite 302]
35.4 - 4 Simulated Results of Various High-Performance D Flip-Flop Designs [Seite 302]
35.5 - 5 Conclusion [Seite 304]
35.6 - References [Seite 304]
36 - Flower Pollination Based Solar PV Parameter Extraction for Double Diode Model [Seite 306]
36.1 - 1 Introduction [Seite 307]
36.2 - 2 Modeling of Solar PV [Seite 308]
36.3 - 3 Problem Formulation [Seite 309]
36.4 - 4 Flower Pollination Algorithm [Seite 310]
36.5 - 5 Simulation Results and Discussions [Seite 312]
36.6 - 6 Conclusion [Seite 314]
36.7 - References [Seite 314]
37 - Cost-Benefit Calculation Using AB2X4 (A = Zn, Cd [Seite 316]
37.1 - 1 Introduction [Seite 316]
37.2 - 2 Theoretical Methodology [Seite 317]
37.3 - 3 Result Discussion [Seite 317]
37.3.1 - 3.1 Method Overview [Seite 318]
37.3.2 - 3.2 PV Module Cost Calculation [Seite 318]
37.4 - 4 Conclusion [Seite 320]
37.5 - References [Seite 320]
38 - Detection and Analysis of Power System Faults in the Presence of Wind Power Generation Using Stockwell Transform Based Median [Seite 321]
38.1 - 1 Introduction [Seite 322]
38.2 - 2 Test System Used for the Proposed Study [Seite 323]
38.3 - 3 Proposed Methodology [Seite 324]
38.3.1 - 3.1 Proposed Fault Index [Seite 324]
38.3.2 - 3.2 Stockwell Transform [Seite 324]
38.4 - 4 S-Transform Based Simulation Results with Discussion [Seite 325]
38.4.1 - 4.1 Line to Ground Fault [Seite 325]
38.4.2 - 4.2 Double Line Fault [Seite 326]
38.4.3 - 4.3 Double Line to Ground Fault [Seite 327]
38.4.4 - 4.4 Three-Phase Fault Involving Ground [Seite 328]
38.4.5 - 4.5 Comparative Study [Seite 329]
38.5 - 5 Conclusion [Seite 330]
38.6 - References [Seite 330]
39 - A Directional Relaying Scheme for Microgrid Protection [Seite 332]
39.1 - 1 Introduction [Seite 332]
39.2 - 2 Test Microgrid [Seite 334]
39.3 - 3 Directional Relaying Algorithm [Seite 334]
39.3.1 - 3.1 Detectors for the Directional Approach [Seite 334]
39.3.2 - 3.2 Proposed Technique [Seite 336]
39.4 - 4 Simulation Results [Seite 336]
39.4.1 - 4.1 Faults During Grid-Connected Mode [Seite 337]
39.4.2 - 4.2 Results for Fault During Islanded Mode [Seite 338]
39.4.3 - 4.3 Results for Load Switching [Seite 338]
39.4.4 - 4.4 Results for High-Impedance Fault (HIF) in Islanding Mode [Seite 339]
39.5 - 5 Conclusion [Seite 340]
39.6 - References [Seite 340]
40 - Wavefunctions and Optical Gain in In0.24Ga0.76N/GaN Type-I Nano-heterostructure Under External Uniaxial Strain [Seite 342]
40.1 - 1 Introduction [Seite 342]
40.2 - 2 Device Structure and Modeling [Seite 343]
40.3 - 3 Results and Discussion [Seite 345]
40.4 - 4 Conclusions [Seite 349]
40.5 - References [Seite 349]
41 - Cost-Benefit Analysis in Distribution System of Jaipur City After DG and Capacitor Allocation [Seite 351]
41.1 - 1 Introduction [Seite 351]
41.2 - 2 Problem Formulation [Seite 352]
41.3 - 3 Proposed Technique [Seite 353]
41.4 - 4 Results [Seite 354]
41.4.1 - 4.1 69 Bus Test System [Seite 354]
41.4.2 - 4.2 130 Bus (Jaipur City) System [Seite 356]
41.5 - 5 Conclusion [Seite 357]
41.6 - References [Seite 358]
42 - Comparative Simulation Study of Dual-Axis Solar Tracking System on Simulink Platform [Seite 359]
42.1 - 1 Introduction [Seite 359]
42.2 - 2 Developed Solar Tracking System [Seite 360]
42.3 - 3 Characteristics of PV Cell [Seite 361]
42.3.1 - 3.1 Simulink Block Diagram [Seite 362]
42.4 - 4 Simulation Results and Discussion [Seite 364]
42.4.1 - 4.1 Elevated Tracking Results [Seite 364]
42.4.2 - 4.2 Azimuthal Tracking Results [Seite 364]
42.5 - 5 Conclusion [Seite 365]
42.6 - References [Seite 365]
43 - Performance Evaluation and Quality Analysis of Line and Node Based Voltage Stability Indices for the Determination of the Voltage Instability Point [Seite 366]
43.1 - 1 Introduction [Seite 366]
43.2 - 2 Existing Line and Node Based Voltage Stability Indices [Seite 367]
43.2.1 - 2.1 Maximum Loadability Index (MLI) [Seite 367]
43.2.2 - 2.2 Loadability Index (Lp) [Seite 368]
43.2.3 - 2.3 Line Loadability Index (Ls) [Seite 368]
43.2.4 - 2.4 Line Stability Index (Lmn) [Seite 368]
43.2.5 - 2.5 Line Stability Factor (LQP) [Seite 369]
43.2.6 - 2.6 Fast Voltage Stability Index (FVSI) [Seite 369]
43.2.7 - 2.7 Line Collapse Proximity Index (LCPI) [Seite 369]
43.2.8 - 2.8 L-Index [Seite 369]
43.3 - 3 Illustrative Example [Seite 370]
43.3.1 - 3.1 With One Fictitious Bus in the Middle of the Transmission Line [Seite 371]
43.3.2 - 3.2 With One Fictitious Bus at (3/4)th Length of the Transmission Line [Seite 373]
43.4 - 4 Conclusion [Seite 374]
43.5 - References [Seite 374]
44 - Channel Estimation in Massive MIMO with Spatial Channel Correlation Matrix [Seite 376]
44.1 - 1 Introduction [Seite 376]
44.2 - 2 System Model for Uplink Pilot Transmission [Seite 377]
44.3 - 3 MMSE Channel Estimation [Seite 378]
44.4 - 4 Spatial Channel Correlation and Pilot Contamination [Seite 379]
44.4.1 - 4.1 Impact of Spatial Correlation on Channel Estimation [Seite 380]
44.4.2 - 4.2 Impact of Pilot Contamination on Channel Estimation [Seite 380]
44.5 - 5 EW-MMSE and LS Estimation Schemes [Seite 380]
44.5.1 - 5.1 Element-Wise MMSE Channel Estimator [Seite 380]
44.5.2 - 5.2 Least-Square Channel Estimator [Seite 381]
44.6 - 6 Simulation Results [Seite 381]
44.7 - 7 Conclusion [Seite 382]
44.8 - References [Seite 383]
45 - A New Array Reconfiguration Scheme for Solar PV Systems Under Partial Shading Conditions [Seite 385]
45.1 - 1 Introduction [Seite 385]
45.2 - 2 System Description [Seite 387]
45.2.1 - 2.1 Modeling of a Total Cross Tied TCT Connection [Seite 387]
45.3 - 3 Methodology [Seite 388]
45.4 - 4 Simulation Results and Discussion [Seite 389]
45.4.1 - 4.1 Pattern 1-Short Wide [Seite 389]
45.4.2 - 4.2 Pattern 2-Long Wide [Seite 392]
45.5 - 5 Conclusion [Seite 393]
45.6 - References [Seite 394]
46 - Adaptability Analysis of Particle Swarm Optimization Variants in Maximum Power Tracking for Solar PV Systems [Seite 395]
46.1 - 1 Introduction [Seite 395]
46.2 - 2 System Description [Seite 396]
46.3 - 3 Modelling of PV Cell [Seite 396]
46.3.1 - 3.1 Characteristics of PV Module [Seite 398]
46.3.2 - 3.2 Characteristics of PV Array Under Partial Shading Conditions [Seite 399]
46.4 - 4 Particle Swarm Optimization: Outline of PSO [Seite 399]
46.4.1 - 4.1 Neighbourhood Selection Scheme [Seite 401]
46.5 - 5 Simulation and Results Discussion [Seite 402]
46.6 - 6 Conclusion [Seite 403]
46.7 - References [Seite 407]
47 - Fault Location Methods in HVDC Transmission System-A Review [Seite 408]
47.1 - 1 Introduction [Seite 408]
47.2 - 2 Literature Review on Fault Location Techniques [Seite 412]
47.3 - 3 Conclusion [Seite 415]
47.4 - References [Seite 415]
48 - Optimal Reactive Power Dispatch Through Minimization of Real Power Loss and Voltage Deviation [Seite 417]
48.1 - 1 Introduction [Seite 419]
48.2 - 2 Problem Formulation [Seite 420]
48.2.1 - 2.1 Objective Function [Seite 420]
48.2.2 - 2.2 System Constraints [Seite 420]
48.2.3 - 2.3 General Formulation of the Objective Function [Seite 421]
48.3 - 3 Solution Methodology [Seite 421]
48.4 - 4 Simulation Result [Seite 422]
48.5 - 5 Conclusion [Seite 425]
48.6 - References [Seite 425]
49 - IoT Enabled Intelligent Energy Management and Optimization Scheme with Controlling and Monitoring Approach in Modern Classroom Applications [Seite 427]
49.1 - 1 Introduction [Seite 428]
49.2 - 2 Related Works [Seite 428]
49.3 - 3 Contextual Analysis/Background Survey [Seite 429]
49.4 - 4 Energy Management in Campus: Challenges [Seite 430]
49.5 - 5 Existing System [Seite 431]
49.6 - 6 Methodology [Seite 431]
49.6.1 - 6.1 Design Criteria [Seite 431]
49.6.2 - 6.2 Device Configuration and Working Principles [Seite 431]
49.7 - 7 Testing and Evaluation of Project Implementation [Seite 432]
49.8 - 8 Future Scope and Conclusion [Seite 435]
49.9 - References [Seite 435]
50 - High Power Density Parallel LC-Link PV Inverter for Stand-alone and Grid Mode of Operation [Seite 437]
50.1 - 1 Introduction [Seite 438]
50.2 - 2 Operation Principle Under Different Modes [Seite 439]
50.2.1 - 2.1 Configuration [Seite 439]
50.2.2 - 2.2 Principle of Operation [Seite 440]
50.3 - 3 Parameter Design Procedure [Seite 441]
50.4 - 4 Zero Voltage Switching Operation (ZVS) [Seite 444]
50.5 - 5 Simulation Results [Seite 445]
50.6 - 6 Conclusions [Seite 448]
50.7 - References [Seite 449]
51 - A Hybrid Forecasting Model Based on Artificial Neural Network and Teaching Learning Based Optimization Algorithm for Day-Ahead Wind Speed Prediction [Seite 450]
51.1 - 1 Introduction [Seite 450]
51.2 - 2 Working Principle of Hybrid Forecasting Model [Seite 451]
51.3 - 3 Forecasting Results and Discussions [Seite 453]
51.4 - 4 Conclusion [Seite 458]
51.5 - References [Seite 458]
52 - Risk Averse Energy Management for Grid Connected Microgrid Using Information Gap Decision Theory [Seite 459]
52.1 - 1 Introduction [Seite 460]
52.2 - 2 Information Gap Decision Theory [Seite 461]
52.3 - 3 Problem Formulation [Seite 462]
52.3.1 - 3.1 Deterministic MG Energy Management [Seite 462]
52.3.2 - 3.2 IGDT Based MG Energy Management [Seite 462]
52.4 - 4 Numerical Simulation [Seite 463]
52.5 - 5 Conclusions [Seite 466]
52.6 - References [Seite 466]
53 - Power Quality Improvement of Microgrid Using Double Bridge Shunt Active Power Filter (DBSAPF) [Seite 468]
53.1 - 1 Introduction [Seite 468]
53.2 - 2 Shunt Active Power Filter [Seite 469]
53.3 - 3 Hysteresis Control Technique [Seite 470]
53.4 - 4 Proposed Double Bridge SAPF [Seite 471]
53.5 - 5 Simulation Results [Seite 472]
53.5.1 - 5.1 Case Study 1 [Seite 473]
53.5.2 - 5.2 Case Study 2 [Seite 474]
53.6 - 6 Conclusion [Seite 475]
53.7 - References [Seite 476]
54 - Opposition Theory Enabled Intelligent Whale Optimization Algorithm [Seite 477]
54.1 - 1 Introduction [Seite 477]
54.2 - 2 Whale Optimization Algorithm [Seite 479]
54.2.1 - 2.1 Girdling Prey [Seite 479]
54.2.2 - 2.2 Bubble-Net Attacking Method (Exploitation Phase) [Seite 480]
54.2.3 - 2.3 Prey Search (Exploration Phase) [Seite 480]
54.3 - 3 Opposition Theory Enabled Intelligent Whale Optimization Algorithm [Seite 481]
54.3.1 - 3.1 Implementation of OBL on OIWOA [Seite 481]
54.3.2 - 3.2 Implementation of Sinusoidal Function [Seite 482]
54.3.3 - 3.3 Implementation of Crossover [Seite 482]
54.4 - 4 Results and Discussions [Seite 482]
54.5 - 5 Conclusions [Seite 484]
54.6 - References [Seite 484]
55 - Adaptive Inertia-Weighted Firefly Algorithm [Seite 486]
55.1 - 1 Introduction [Seite 486]
55.2 - 2 Firefly Algorithm [Seite 488]
55.3 - 3 Improved Firefly Algorithm [Seite 489]
55.4 - 4 Simulation Results and Discussions [Seite 491]
55.4.1 - 4.1 Results on Uni-modal Functions [Seite 491]
55.4.2 - 4.2 Results on Multi-modal and Fixed Dimension Multi-modal Functions [Seite 492]
55.5 - 5 Conclusions [Seite 492]
55.6 - References [Seite 493]
56 - A Review of Scheduling Techniques and Communication Protocols for Smart Homes Capable of Implementing Demand Response [Seite 495]
56.1 - 1 Introduction [Seite 495]
56.2 - 2 Scheduling Techniques [Seite 496]
56.2.1 - 2.1 Rule-Based Scheduling Techniques [Seite 496]
56.2.2 - 2.2 Training-Based Artificial Intelligent Techniques [Seite 497]
56.2.3 - 2.3 Heuristic and Meta-Heuristic AI Techniques [Seite 497]
56.3 - 3 Communication [Seite 498]
56.3.1 - 3.1 Wired Communication Protocols [Seite 498]
56.3.2 - 3.2 Wireless-Based Communication [Seite 499]
56.3.3 - 3.3 Hybrid and Integrated Protocols [Seite 499]
56.4 - 4 Conclusion [Seite 500]
56.5 - References [Seite 500]
57 - A Robust Open-Loop Frequency Estimation Method for Single-Phase Systems [Seite 504]
57.1 - 1 Introduction [Seite 504]
57.2 - 2 Even Harmonics Generation [Seite 505]
57.3 - 3 Filtering Requirements [Seite 506]
57.3.1 - 3.1 DC-Offset Rejection [Seite 506]
57.3.2 - 3.2 Extraction of Fundamental Orthogonal Components [Seite 507]
57.3.3 - 3.3 Elimination of Higher Order Harmonics [Seite 508]
57.4 - 4 Frequency Estimation [Seite 509]
57.4.1 - 4.1 Simulation Setup and Results [Seite 509]
57.5 - 5 Conclusion [Seite 512]
57.6 - References [Seite 512]
58 - Demand-Side Load Management for Peak Shaving [Seite 514]
58.1 - 1 Introduction [Seite 514]
58.2 - 2 Demand-Side Load Management [Seite 515]
58.3 - 3 Modeling and Simulation [Seite 517]
58.3.1 - 3.1 Modeling [Seite 517]
58.3.2 - 3.2 Simulation Process [Seite 518]
58.4 - 4 Simulation Results [Seite 520]
58.5 - 5 Conclusions [Seite 523]
58.6 - References [Seite 523]
59 - A New Line Voltage Stability Index (NLVSI) For Voltage Stability Assessment [Seite 524]
59.1 - 1 Introduction [Seite 524]
59.2 - 2 Existing Line Based Voltage Stability Indices [Seite 526]
59.2.1 - 2.1 Line Stability Index (Lmn) [Seite 526]
59.2.2 - 2.2 Fast Voltage Stability Index (FVSI) [Seite 526]
59.2.3 - 2.3 Line Stability Factor (LQP) [Seite 526]
59.2.4 - 2.4 Line Voltage Reactive Power Index (VQIline) [Seite 527]
59.2.5 - 2.5 New Voltage Stability Index (NVSI) [Seite 527]
59.3 - 3 Effect of Delta on Voltage [Seite 527]
59.4 - 4 Proposed Index Formulation [Seite 529]
59.5 - 5 Representation of ZIP Load Model [Seite 531]
59.6 - 6 Test Case Results [Seite 531]
59.6.1 - 6.1 When Conventional (i.e. Constant Power) Load is Used [Seite 532]
59.6.2 - 6.2 When ZIP Load Model is Used [Seite 534]
59.6.3 - 6.3 Results Comparison Between Conventional Load and ZIP Load Model [Seite 534]
59.7 - 7 Conclusion [Seite 536]
59.8 - References [Seite 537]
60 - A Comprehensive Comparative Economic Analysis of ACO and CS Technique for Optimal Operation of Stand-alone HES [Seite 538]
60.1 - 1 Introduction [Seite 540]
60.2 - 2 Mathematical Formulation [Seite 541]
60.2.1 - 2.1 Modeling of System Components [Seite 542]
60.2.2 - 2.2 Operation Strategy [Seite 545]
60.2.3 - 2.3 Objective Function [Seite 546]
60.2.4 - 2.4 Constraints [Seite 546]
60.3 - 3 Ant Colony Optimization [Seite 547]
60.4 - 4 Cuckoo Search Technique [Seite 548]
60.4.1 - 4.1 Levy Flights Technique [Seite 548]
60.4.2 - 4.2 Random Walk Technique [Seite 549]
60.5 - 5 Comparative Analysis [Seite 549]
60.6 - 6 Conclusion [Seite 552]
60.7 - References [Seite 553]
61 - Demand Response in Distribution Systems: A Comprehensive Review [Seite 554]
61.1 - 1 Introduction [Seite 554]
61.2 - 2 Background and Classification of DRPs [Seite 555]
61.3 - 3 An Overview of DR [Seite 557]
61.4 - 4 Conclusion [Seite 560]
61.5 - References [Seite 560]
62 - Stochastic Operational Management of Grid-Connected Microgrid Under Uncertainty of Renewable Resources and Load Demand [Seite 562]
62.1 - 1 Introduction [Seite 562]
62.2 - 2 Stochastic Modeling of Renewable Generation and System Load [Seite 563]
62.2.1 - 2.1 Stochastic Modeling of Wind Power Generation [Seite 563]
62.2.2 - 2.2 Stochastic Modeling of PV Power Generation [Seite 564]
62.2.3 - 2.3 Stochastic Modeling of System Load Demand [Seite 565]
62.2.4 - 2.4 Combined Stochastic Modeling of the System [Seite 565]
62.2.5 - 2.5 Tournament Selection Based Scenarios Sampling [Seite 565]
62.3 - 3 Problem Formulation [Seite 565]
62.3.1 - 3.1 Objective Function [Seite 565]
62.3.2 - 3.2 Constraints [Seite 566]
62.4 - 4 Solution Methodology [Seite 567]
62.5 - 5 Simulation Results and Discussion [Seite 567]
62.6 - 6 Conclusion [Seite 569]
62.7 - References [Seite 570]
63 - Real-Time High-Speed Novel Data Acquisition System Based on ZYNQ [Seite 571]
63.1 - 1 Introduction [Seite 572]
63.2 - 2 Overview of the Hardware Platform and Contemporary Solutions [Seite 572]
63.3 - 3 Firmware Design of Data Acquisition System [Seite 573]
63.4 - 4 Software Interface for Data Acquisition System [Seite 574]
63.5 - 5 Results and Discussion [Seite 576]
63.6 - 6 Conclusion [Seite 577]
63.7 - References [Seite 578]
64 - Exergetic Analysis of Glazed Photovoltaic Thermal (Single-Channel) Module Using Whale Optimization Algorithm and Genetic Algorithm [Seite 579]
64.1 - 1 Introduction [Seite 580]
64.2 - 2 System Description [Seite 582]
64.3 - 3 Tool Used for Optimization [Seite 582]
64.4 - 4 Result and Discussion [Seite 583]
64.5 - 5 Conclusion [Seite 587]
64.6 - Appendix: Optimized Value of Parameters [Seite 587]
64.7 - References [Seite 588]
65 - An 8-Bit Charge Redistribution SAR ADC [Seite 589]
65.1 - 1 Introduction [Seite 589]
65.2 - 2 8-Bit SAR ADC Architecture [Seite 591]
65.3 - 3 Implementation of Inner Blocks [Seite 593]
65.3.1 - 3.1 S/H Circuit [Seite 593]
65.3.2 - 3.2 Comparator [Seite 594]
65.4 - 4 Simulation Results [Seite 595]
65.5 - 5 Conclusion [Seite 597]
65.6 - References [Seite 597]
66 - Analysis of Triple-Threshold Technique for Power Optimization in SRAM Bit-Cell for Low-Power Applications at 45 Nm CMOS Technology [Seite 598]
66.1 - 1 Introduction [Seite 598]
66.2 - 2 Approach [Seite 600]
66.3 - 3 Analysis and Result [Seite 600]
66.3.1 - 3.1 Data Stability [Seite 600]
66.3.2 - 3.2 Read Noise Margin [Seite 600]
66.3.3 - 3.3 Write Noise Margin [Seite 601]
66.3.4 - 3.4 Average Power and Leakage Power [Seite 602]
66.4 - 4 Conclusion [Seite 604]
66.5 - References [Seite 604]
67 - Low Power Adder Circuits Using Various Leakage Reduction Techniques [Seite 606]
67.1 - 1 Introduction [Seite 606]
67.2 - 2 Literature Review [Seite 607]
67.2.1 - 2.1 Sleep Transistor Technique [Seite 607]
67.2.2 - 2.2 Stack Transistor Technique [Seite 608]
67.2.3 - 2.3 Super Cutoff (SCCMOS) Technique [Seite 609]
67.3 - 3 Implementation of Adder Circuit [Seite 610]
67.3.1 - 3.1 1-Bit Full Adder [Seite 610]
67.3.2 - 3.2 4-Bit Ripple Carry Adder [Seite 612]
67.4 - 4 Simulation and Analysis [Seite 612]
67.5 - 5 Conclusion [Seite 614]
67.6 - References [Seite 615]
68 - A Nature-Inspired Metaheuristic Swarm Based Optimization Technique BFOA Based Optimal Controller for Damping of SSR [Seite 617]
68.1 - 1 Introduction [Seite 617]
68.2 - 2 System Configuration [Seite 618]
68.3 - 3 Development of Overall System Model [Seite 619]
68.4 - 4 Application of Optimal Control Theory [Seite 619]
68.5 - 5 Optimal Parameter Selection Using BFOA [Seite 619]
68.5.1 - 5.1 A Brief Overview of BFOA [Seite 619]
68.6 - 6 Results and Discussions [Seite 620]
68.6.1 - 6.1 Case Study with 60% Series Compensation [Seite 620]
68.7 - 7 Conclusion [Seite 622]
68.8 - References [Seite 624]
69 - New Fuzzy Divergence Measures, Series, Its Bounds and Applications in Strategic Decision-Making [Seite 626]
69.1 - 1 Introduction [Seite 626]
69.2 - 2 New Information Divergence Measures [Seite 627]
69.3 - 3 Series of Fuzzy Divergence Measures [Seite 628]
69.4 - 4 Some New Other Fuzzy Information Divergence Measures [Seite 632]
69.5 - 5 New Information Divergence and Their Relation with Other Well-Known Divergence Measures [Seite 633]
69.6 - 6 Application of Proposed Series of Fuzzy Divergence Making in Strategic Decision-Making [Seite 635]
69.7 - 7 Conclusion [Seite 638]
69.8 - References [Seite 638]
70 - Mutual Coupling Reduction of Biconvex Lens Shaped Patch Antenna for 5G Application [Seite 639]
70.1 - 1 Introduction [Seite 639]
70.2 - 2 Design of the Proposed Antenna [Seite 640]
70.2.1 - 2.1 Rotman Lens Equations and Proposed Modification [Seite 640]
70.2.2 - 2.2 Design of the Perturbed Strip [Seite 641]
70.3 - 3 Design and Simulation of Proposed Antenna [Seite 641]
70.3.1 - 3.1 Substrate Material and Height [Seite 641]
70.3.2 - 3.2 Design of the Proposed Antenna [Seite 642]
70.3.3 - 3.3 Results from Simulation of the Proposed Antenna [Seite 642]
70.4 - 4 Conclusion [Seite 644]
70.5 - References [Seite 646]
71 - Analysis of Anti-Islanding Protection Methods Integrated in Distributed Generation [Seite 647]
71.1 - 1 Introduction [Seite 647]
71.2 - 2 Passive Methods [Seite 648]
71.3 - 3 Active Methods [Seite 650]
71.4 - 4 Simulation Results [Seite 652]
71.5 - 5 Conclusion [Seite 654]
71.6 - References [Seite 654]
72 - Color Image Watermarking with Watermark Hashing [Seite 656]
72.1 - 1 Introduction [Seite 656]
72.2 - 2 Background [Seite 657]
72.2.1 - 2.1 Singular Value Decomposition (SVD) [Seite 657]
72.2.2 - 2.2 Discrete Wavelet Transform (DWT) [Seite 658]
72.3 - 3 Hashing Techniques [Seite 658]
72.4 - 4 Experiments and Results [Seite 659]
72.5 - 5 Conclusions [Seite 662]
72.6 - References [Seite 663]
73 - Global Neighbourhood Algorithm Based Event-Triggered Automatic Generation Control [Seite 665]
73.1 - 1 Introduction [Seite 665]
73.2 - 2 AGC System Modelling [Seite 667]
73.3 - 3 Problem Formulation [Seite 668]
73.3.1 - 3.1 Objective Function [Seite 668]
73.3.2 - 3.2 Global Neighbourhood Algorithm (GNA) [Seite 668]
73.3.3 - 3.3 Delay/Sampling Time Dependent Stability [Seite 668]
73.4 - 4 Case Study [Seite 670]
73.4.1 - 4.1 Case I [Seite 670]
73.4.2 - 4.2 Case II [Seite 672]
73.5 - 5 Conclusions [Seite 673]
73.6 - References [Seite 673]
74 - A Review on Voltage and Frequency Control of Micro Hydro System [Seite 675]
74.1 - 1 Introduction [Seite 675]
74.2 - 2 Voltage and Frequency Regulation in Micro Hydro System [Seite 677]
74.3 - 3 Classification of ELC on the Basis of Loading [Seite 679]
74.4 - 4 Discussion [Seite 681]
74.5 - 5 Conclusion [Seite 682]
74.6 - References [Seite 682]
75 - Performance Analysis of Solar and Plug-in Electric Vehicle's Integration to the Power System with Automatic Generation Control [Seite 684]
75.1 - 1 Introduction [Seite 684]
75.2 - 2 Proposed System Study [Seite 685]
75.3 - 3 Selection of Controller and Objective Function [Seite 686]
75.4 - 4 Jaya Optimization Technique [Seite 687]
75.5 - 5 Result and Analysis [Seite 688]
75.6 - 6 Conclusion [Seite 691]
75.7 - 7 Appendix [Seite 691]
75.8 - References [Seite 691]
76 - A Bibliographical View on Research and Developments of Photovoltaic and Thermal Technologies as a Combined System: PV/T System [Seite 693]
76.1 - 1 Introduction [Seite 694]
76.2 - 2 PV/T Air Collector [Seite 695]
76.2.1 - 2.1 Effect of Glazing [Seite 696]
76.2.2 - 2.2 Effect of Adding Thin Metallic Sheets (TMS) and Fins [Seite 696]
76.2.3 - 2.3 Effect of Packing Factor [Seite 697]
76.3 - 3 PV/T Water [Seite 697]
76.4 - 4 PV/T Combi [Seite 698]
76.5 - 5 Modelling of PV/T Collector [Seite 699]
76.6 - 6 Optimization Using Soft Computing [Seite 700]
76.7 - 7 Conclusion [Seite 701]
76.8 - References [Seite 701]
77 - UPM-NoC: Learning Based Framework to Predict Performance Parameters of Mesh Architecture in On-Chip Networks [Seite 703]
77.1 - 1 Introduction [Seite 704]
77.2 - 2 Related Work [Seite 705]
77.2.1 - 2.1 Learning Models Used in Different Aspects of NoC [Seite 705]
77.3 - 3 Design Strategy [Seite 706]
77.3.1 - 3.1 Detailed Layout of Unified Performance Model [Seite 706]
77.3.2 - 3.2 Data Collection Using Booksim Simulator [Seite 707]
77.3.3 - 3.3 Generation of Dataset [Seite 708]
77.4 - 4 Results and Discussion [Seite 708]
77.4.1 - 4.1 Experimental Results [Seite 708]
77.4.2 - 4.2 Validation [Seite 710]
77.4.3 - 4.3 Runtime Comparison [Seite 711]
77.5 - 5 Conclusion [Seite 712]
77.6 - References [Seite 712]
78 - Comparison of Performance Analysis of Optimal Controllers for Frequency Regulation of Three-Area Power System [Seite 714]
78.1 - 1 Introduction [Seite 714]
78.2 - 2 Three-Area System Under Study [Seite 716]
78.3 - 3 Optimization of Controller Gains [Seite 717]
78.4 - 4 Results and Discussion [Seite 718]
78.5 - 5 Conclusion [Seite 721]
78.6 - References [Seite 721]
79 - Optimal DG Allocation in a Microgrid Using Droop-Controlled Load Flow [Seite 723]
79.1 - 1 Introduction [Seite 723]
79.2 - 2 Problem Formulation [Seite 725]
79.3 - 3 Methodology [Seite 726]
79.3.1 - 3.1 Droop-Controlled Load Flow (DCLF) [Seite 726]
79.3.2 - 3.2 Non-Dominated Sorted Genetic Algorithm [Seite 727]
79.3.3 - 3.3 Fuzzy Satisfying Method [Seite 727]
79.4 - 4 Results and Discussions [Seite 727]
79.5 - 5 Conclusion [Seite 728]
79.6 - References [Seite 729]
80 - A Comparative Study of Classification Algorithms for Predicting Liver Disorders [Seite 731]
80.1 - 1 Introduction [Seite 731]
80.2 - 2 Literature Review [Seite 732]
80.3 - 3 Methodology [Seite 734]
80.3.1 - 3.1 Data Collection [Seite 734]
80.3.2 - 3.2 Data Preprocessing [Seite 734]
80.3.3 - 3.3 Applying Different Classification Algorithms [Seite 734]
80.3.4 - 3.4 Predicting the Test Set Results [Seite 735]
80.3.5 - 3.5 Comparison of Models [Seite 735]
80.4 - 4 Results and Discussion [Seite 735]
80.5 - 5 Conclusion and Future Work [Seite 737]
80.6 - References [Seite 737]
81 - Performance Analysis of Fabricated Buck-Boost MPPT Charge Controller [Seite 739]
81.1 - 1 Introduction [Seite 739]
81.2 - 2 Experimental Setup [Seite 740]
81.3 - 3 Experimental Result [Seite 741]
81.4 - 4 Conclusion [Seite 745]
81.5 - References [Seite 745]
82 - Performance Improvement of Cycloconverter Fed Induction Machine Using Shunt Active Power Filter [Seite 747]
82.1 - 1 Introduction [Seite 747]
82.2 - 2 Input Current of Cycloconverter [Seite 748]
82.2.1 - 2.1 Harmonic Analysis of Input Current [Seite 749]
82.3 - 3 Harmonic Analysis of Input Current of Cycloconverter Fed Induction Machine [Seite 749]
82.4 - 4 Design Shunt Active Power Filter [Seite 751]
82.4.1 - 4.1 Voltage Source Converter [Seite 751]
82.4.2 - 4.2 Fuzzy Logic Based Controller [Seite 752]
82.4.3 - 4.3 Hysteresis Band Current Control Technique [Seite 754]
82.4.4 - 4.4 Simulation of Cycloconverter Fed Induction Machine with Shunt Active Power Filter [Seite 754]
82.5 - 5 Conclusion [Seite 757]
82.6 - References [Seite 758]
83 - Comparative Analysis of Speaker Recognition System Based on Voice Activity Detection Technique, MFCC and PLP Features [Seite 759]
83.1 - 1 Introduction [Seite 759]
83.2 - 2 Methodology [Seite 760]
83.2.1 - 2.1 Voice Activity Detection (VAD) [Seite 761]
83.2.2 - 2.2 MFCC [Seite 762]
83.2.3 - 2.3 Vector Quantization [Seite 762]
83.2.4 - 2.4 Perceptual Linear Predictive (PLP) [Seite 763]
83.2.5 - 2.5 Database [Seite 763]
83.3 - 3 Results and Discussion [Seite 764]
83.4 - 4 Conclusions [Seite 765]
83.5 - References [Seite 765]
84 - Nonintrusive Load Monitoring: Making Smart Meters Smarter [Seite 766]
84.1 - 1 Introduction [Seite 766]
84.1.1 - 1.1 Need for NILM in Smart Meters [Seite 766]
84.2 - 2 Working of NILM and Challenges with It [Seite 767]
84.2.1 - 2.1 Data Acquisition [Seite 768]
84.3 - 3 Proposal [Seite 768]
84.3.1 - 3.1 Security Feature to Safeguard Consumer as Well as Appliance [Seite 768]
84.3.2 - 3.2 NILM to Predict Appliance Health [Seite 770]
84.4 - 4 Conclusion [Seite 770]
85 - Stabilization of Chaotic Systems Using Robust Optimal Controller [Seite 772]
85.1 - 1 Introduction [Seite 772]
85.2 - 2 Problem Statement [Seite 773]
85.3 - 3 Optimal Controller Design [Seite 774]
85.4 - 4 Design of Sliding Mode Controller [Seite 775]
85.5 - 5 Simulation Results [Seite 777]
85.6 - 6 Conclusion [Seite 779]
85.7 - References [Seite 779]
86 - Jaya Algorithm Based Optimal Allocation of Distributed Energy Resources [Seite 781]
86.1 - 1 Introduction [Seite 781]
86.2 - 2 Problem Description [Seite 783]
86.2.1 - 2.1 Boundary Limit of Node Voltage [Seite 783]
86.2.2 - 2.2 Power Balance [Seite 784]
86.2.3 - 2.3 Distribution Thermal Limit [Seite 784]
86.2.4 - 2.4 DERs Generation [Seite 784]
86.3 - 3 Description of the Jaya Algorithm [Seite 784]
86.4 - 4 Simulation Results [Seite 786]
86.4.1 - 4.1 Test System 1:33 Bus Radial Distribution Network [Seite 787]
86.4.2 - 4.2 Test System 2: 69 Bus Radial Distribution Network [Seite 787]
86.5 - 5 Conclusion [Seite 789]
86.6 - References [Seite 789]
87 - Bayesian Game Model: Demand Side Management for Residential Consumers with Electric Vehicles [Seite 791]
87.1 - 1 Introduction [Seite 791]
87.2 - 2 System Model [Seite 792]
87.2.1 - 2.1 Energy Consumption Cost Model [Seite 793]
87.2.2 - 2.2 Payoff Model for EV's [Seite 794]
87.3 - 3 Bayesian Game for Household Consumers [Seite 795]
87.4 - 4 Simulation Results [Seite 796]
87.5 - 5 Conclusion [Seite 798]
87.6 - References [Seite 798]
88 - Classification of Power System Disturbances Using Support Vector Machine in FPGA [Seite 800]
88.1 - 1 Introduction [Seite 800]
88.2 - 2 Support Vector Machine [Seite 801]
88.2.1 - 2.1 Linear SVM [Seite 801]
88.2.2 - 2.2 Nonlinear SVM [Seite 802]
88.3 - 3 Power System Transient [Seite 804]
88.4 - 4 SVM Implementation [Seite 805]
88.4.1 - 4.1 Software Simulation of SVM in MATLAB [Seite 805]
88.4.2 - 4.2 Hardware Co-simulation of SVM in FPGA [Seite 806]
88.5 - 5 Simulation Result [Seite 808]
88.6 - 6 Conclusion [Seite 809]
88.7 - References [Seite 809]
89 - Designing a Smart System for Air Quality Monitoring and Air Purification [Seite 811]
89.1 - 1 Introduction [Seite 811]
89.2 - 2 Filters and Sensors [Seite 812]
89.2.1 - 2.1 Filters [Seite 812]
89.2.2 - 2.2 Comparison of Various Filters Used in the Air Purifiers [Seite 814]
89.2.3 - 2.3 Sensors [Seite 814]
89.3 - 3 Proposed Model [Seite 815]
89.4 - 4 Results [Seite 816]
89.5 - 5 Conclusion [Seite 816]
89.6 - 6 Future Scope [Seite 817]
89.7 - References [Seite 817]
90 - Activation Map Networks with Deep Graphical Model for Semantic Segmentation [Seite 819]
90.1 - 1 Introduction [Seite 820]
90.2 - 2 Context Deep CRFs [Seite 820]
90.3 - 3 Pairwise Potential Functions [Seite 821]
90.4 - 4 Prognostic Process [Seite 822]
90.5 - 5 Prognostic Consummation Phase [Seite 823]
90.6 - 6 Practical Experiments with Validation Set on Matlab Contextual Modeling [Seite 823]
90.7 - 7 Conclusion [Seite 823]
90.8 - References [Seite 825]
91 - Grey Wolf Optimized PI Controller for Hybrid Power System Using SMES [Seite 827]
91.1 - 1 Introduction [Seite 827]
91.2 - 2 Hybrid Power System [Seite 828]
91.2.1 - 2.1 Mathematical Modelling of HPS [Seite 828]
91.3 - 3 Grey Wolf Optimization [Seite 830]
91.4 - 4 Simulation Results and Analysis [Seite 831]
91.5 - 5 Conclusion [Seite 834]
91.6 - References [Seite 835]
92 - JAYA-Evaluated Frequency Control Design for Hydroelectric Power System Using RFB and UPFC [Seite 836]
92.1 - 1 Introduction [Seite 837]
92.2 - 2 Studied Model [Seite 838]
92.3 - 3 JAYA-Optimized LFC Designs [Seite 838]
92.4 - 4 Result Analysis [Seite 841]
92.5 - 5 Conclusion [Seite 842]
92.6 - References [Seite 844]
93 - A Human Face-Shaped Microstrip Patch Antenna for Ultra-Wideband Applications [Seite 845]
93.1 - 1 Introduction [Seite 845]
93.2 - 2 Antenna Geometry [Seite 846]
93.3 - 3 Simulation Results [Seite 847]
93.4 - 4 Conclusion [Seite 849]
93.5 - References [Seite 851]
94 - Scheduling Energy Storage to Provide Balancing During Line Contingency at High Wind Penetration [Seite 853]
94.1 - 1 Introduction [Seite 855]
94.2 - 2 Problem Formulation [Seite 856]
94.2.1 - 2.1 Objective Function [Seite 856]
94.2.2 - 2.2 Operating Constraints [Seite 856]
94.2.3 - 2.3 Wind Generation Constraints [Seite 857]
94.2.4 - 2.4 Storage Constraints [Seite 857]
94.2.5 - 2.5 Power Balance [Seite 858]
94.3 - 3 Data and Result Analysis [Seite 858]
94.3.1 - 3.1 Data [Seite 858]
94.3.2 - 3.2 Result Analysis [Seite 858]
94.4 - 4 Conclusion [Seite 861]
94.5 - References [Seite 861]
95 - Multilevel Inverter Topologies in Renewable Energy Applications [Seite 863]
95.1 - 1 Introduction [Seite 864]
95.2 - 2 Classical MLI Topologies [Seite 865]
95.2.1 - 2.1 Neutral Point Clamped MLI (NPC MLI) [Seite 865]
95.2.2 - 2.2 Flying Capacitor MLI (FC MLI) [Seite 866]
95.2.3 - 2.3 Cascaded H-Bridge MLI (CHB MLI) [Seite 867]
95.3 - 3 RCC Topologies for LV Applications [Seite 867]
95.3.1 - 3.1 Developed Cascaded MLI (DC MLI) [Seite 867]
95.3.2 - 3.2 Cascaded Sub-multilevel Inverter (CSMLI) [Seite 867]
95.3.3 - 3.3 Multilevel DC-Link Inverter (MLDCLI) [Seite 869]
95.4 - 4 MLIs in Renewable Energy Applications [Seite 869]
95.4.1 - 4.1 Photovoltaic Systems [Seite 869]
95.4.2 - 4.2 Wind Energy Conversion System (WECS) [Seite 870]
95.4.3 - 4.3 Battery Storage Energy Systems (BSES) [Seite 870]
95.5 - 5 Conclusion [Seite 871]
95.6 - References [Seite 871]
96 - A Review on Demand Side Management Forecasting Models for Smart Grid [Seite 875]
96.1 - 1 Introduction [Seite 875]
96.2 - 2 Load Forecasting [Seite 877]
96.2.1 - 2.1 Traditional Forecasting Method [Seite 877]
96.2.2 - 2.2 Modern Forecasting Method [Seite 879]
96.3 - 3 Comparative Study of Forecasting Techniques [Seite 880]
96.4 - 4 Challenges and Conclusion [Seite 881]
96.5 - References [Seite 881]
97 - Detection of Suspicious Activity in ATM Booth [Seite 883]
97.1 - 1 Introduction [Seite 883]
97.1.1 - 1.1 Video Surveillance [Seite 884]
97.1.2 - 1.2 Overview [Seite 884]
97.2 - 2 Related Work [Seite 884]
97.3 - 3 Background [Seite 885]
97.3.1 - 3.1 Automated Teller Machine [Seite 885]
97.3.2 - 3.2 Suspicious Activities in ATM Booth [Seite 886]
97.4 - 4 Multiple Object Detection [Seite 886]
97.4.1 - 4.1 Viola-Jones Algorithm [Seite 886]
97.4.2 - 4.2 Approach Used for Multiple Person Detection [Seite 888]
97.5 - 5 Helmet Detection [Seite 888]
97.5.1 - 5.1 Circle Hough Transformation [Seite 888]
97.5.2 - 5.2 Approach Used for Helmet Detection [Seite 891]
97.6 - 6 Results Analysis [Seite 891]
97.7 - 7 Conclusion [Seite 895]
97.8 - References [Seite 896]
98 - Mitigation of Power Quality for Wind Energy Using Transmission Line Based on D-STATCOM [Seite 898]
98.1 - 1 Introduction [Seite 898]
98.2 - 2 Proposed Work [Seite 899]
98.3 - 3 Result and Discussion [Seite 900]
98.4 - 4 Conclusion [Seite 904]
98.5 - References [Seite 905]
99 - Performance Evaluation of Solar Power Plant [Seite 907]
99.1 - 1 Introduction [Seite 907]
99.2 - 2 Methodology and Input Parameters [Seite 908]
99.3 - 3 Result and Discussion [Seite 909]
99.4 - 4 Conclusion [Seite 909]
99.5 - References [Seite 911]
100 - GWO Based PID Controller Optimization for Robotic Manipulator [Seite 913]
100.1 - 1 Introduction [Seite 913]
100.2 - 2 Modeling of Robotic Manipulator [Seite 914]
100.3 - 3 Trajectory for Manipulator [Seite 916]
100.4 - 4 PID Controller [Seite 916]
100.5 - 5 Optimization Technique [Seite 917]
100.5.1 - 5.1 GWO Optimization [Seite 917]
100.6 - 6 Simulation and Result Analysis [Seite 918]
100.7 - 7 Conclusion [Seite 920]
100.8 - References [Seite 921]
101 - A 26 W Power Supply Based on Luo Converter with Improved Power Factor and Total Harmonic Distortion [Seite 922]
101.1 - 1 Introduction [Seite 922]
101.2 - 2 Proposed Model: A Power Factor Corrected (PFC) Power Supply Based on Luo Converter [Seite 923]
101.3 - 3 Components Selection of Power Supply [Seite 924]
101.4 - 4 System Loop Gain Analysis [Seite 924]
101.5 - 5 Model Stability Without Controller in Feedback [Seite 926]
101.6 - 6 Controller Design and Analysis of Stability System with Compensation Network [Seite 926]
101.6.1 - 6.1 Proportional Integral (PI) Controller [Seite 927]
101.6.2 - 6.2 Compensator's Component Design [Seite 928]
101.6.3 - 6.3 Model with Proposed Compensated Network: Stability Analysis [Seite 928]
101.7 - 7 Simulated Circuit Diagram and Analysis [Seite 929]
101.8 - 8 Results Analysis [Seite 929]
101.9 - 9 Conclusions [Seite 931]
101.10 - References [Seite 931]
102 - Optimal Strategic Bidding Using Intelligent Gravitational Search Algorithm for Profit Maximization of Power Suppliers in an Emerging Power Market [Seite 932]
102.1 - 1 Introduction [Seite 932]
102.2 - 2 Problem Formulation [Seite 934]
102.3 - 3 Intelligent GSA [Seite 935]
102.3.1 - 3.1 Opposition Phenomenon in GSA [Seite 936]
102.3.2 - 3.2 Update Mode of Gravity Constant [Seite 936]
102.4 - 4 Results and Discussion [Seite 936]
102.5 - 5 Conclusion [Seite 939]
102.6 - References [Seite 939]
103 - Synchrophasor Measurements Assisted Naïve Bayes Classification Based Real-Time Transient Stability Prediction of Power System [Seite 941]
103.1 - 1 Introduction [Seite 941]
103.2 - 2 Naïve Bayes Classifier [Seite 942]
103.3 - 3 Proposed Methodology [Seite 943]
103.3.1 - 3.1 Optimal PMU Placement Formulation [Seite 944]
103.3.2 - 3.2 Data Generation [Seite 944]
103.3.3 - 3.3 Feature Selection and Target Assignment [Seite 944]
103.3.4 - 3.4 Training, Testing and New Data [Seite 945]
103.3.5 - 3.5 Proposed Synchrophasor Measurement Assisted Naïve Bayes Classifier [Seite 945]
103.4 - 4 Simulation and Results [Seite 945]
103.4.1 - 4.1 Optimal PMU Placement [Seite 945]
103.4.2 - 4.2 PMU-Naïve Bayes Based Real-Time Transient Stability Prediction [Seite 946]
103.5 - 5 Conclusion [Seite 947]
103.6 - References [Seite 947]
104 - Device Modeling and Characteristics of Solution Processed Perovskite Solar Cell at Ambient Conditions [Seite 949]
104.1 - 1 Introduction [Seite 949]
104.2 - 2 Methodology [Seite 951]
104.2.1 - 2.1 Materials [Seite 951]
104.2.2 - 2.2 Preparation of Layers [Seite 952]
104.2.3 - 2.3 Device Fabrication [Seite 952]
104.3 - 3 Characterization [Seite 954]
104.3.1 - 3.1 I-V Measurement [Seite 954]
104.3.2 - 3.2 UV-Visible Analysis [Seite 954]
104.4 - 4 Summary [Seite 955]
104.5 - References [Seite 956]
105 - Control and Remote Sensing of an Irrigation System Using ZigBee Wireless Network [Seite 957]
105.1 - 1 Introduction [Seite 958]
105.2 - 2 Materials and Methods [Seite 959]
105.2.1 - 2.1 Conceptual System Design [Seite 959]
105.2.2 - 2.2 Sensor-Based In-field Station [Seite 960]
105.2.3 - 2.3 Irrigation Control Station [Seite 961]
105.2.4 - 2.4 Base Station [Seite 962]
105.2.5 - 2.5 Graphical User Interface (Gui) [Seite 962]
105.2.6 - 2.6 Mail Transfer [Seite 964]
105.3 - 3 Application and Observations [Seite 964]
105.4 - 4 Limitation [Seite 965]
105.5 - 5 Conclusion and Future Work [Seite 965]
105.6 - References [Seite 966]
106 - Analysis and Classification of Maximum Power Point Tracking (MPPT) Techniques: A Review [Seite 967]
106.1 - 1 Introduction [Seite 967]
106.2 - 2 Introduction to MPPT Techniques [Seite 968]
106.3 - 3 Types of MPPT Techniques [Seite 969]
106.3.1 - 3.1 Conventional Methods [Seite 969]
106.3.2 - 3.2 Soft Computing Methods [Seite 972]
106.3.3 - 3.3 Comparative Study [Seite 974]
106.4 - 4 Conclusion [Seite 975]
106.5 - References [Seite 975]
107 - A Study and Comprehensive Overview of Inverter Topologies for Grid-Connected Photovoltaic Systems (PVS) [Seite 977]
107.1 - 1 Introduction [Seite 978]
107.2 - 2 Evolution of Grid-Connected Inverter Topologies for PVS [Seite 978]
107.2.1 - 2.1 Centralized Inverters [Seite 981]
107.2.2 - 2.2 String Inverters and AC-Modules [Seite 981]
107.2.3 - 2.3 Multi-string Inverters and Cascaded Inverters [Seite 982]
107.3 - 3 Power Processing Stages-Based Inverters [Seite 982]
107.3.1 - 3.1 SSI: Single-Stage Inverter [Seite 982]
107.3.2 - 3.2 MSI: Multiple-Stage Inverter [Seite 983]
107.4 - 4 Conclusion [Seite 983]
107.5 - References [Seite 984]
108 - IOT Based Smart Writer [Seite 986]
108.1 - 1 Technical Details of the Paper [Seite 987]
108.1.1 - 1.1 Origin of Idea [Seite 987]
108.1.2 - 1.2 Definition of the Problem [Seite 987]
108.2 - 2 Objectives [Seite 987]
108.2.1 - 2.1 Printing [Seite 987]
108.2.2 - 2.2 Android/IOS Development [Seite 988]
108.2.3 - 2.3 App to Machine Communication [Seite 988]
108.2.4 - 2.4 Speech to Text Conversion [Seite 988]
108.2.5 - 2.5 Signature Printing and Encryption [Seite 988]
108.3 - 3 Workplan [Seite 988]
108.3.1 - 3.1 Literature Survey [Seite 988]
108.3.2 - 3.2 Writer Installation [Seite 988]
108.3.3 - 3.3 Arduino Programming [Seite 989]
108.3.4 - 3.4 Mobile App Development [Seite 989]
108.3.5 - 3.5 Paper Representation [Seite 989]
108.4 - 4 Methodology [Seite 989]
108.5 - 5 Organization of the Work Elements [Seite 990]
108.6 - 6 Time Schedule Chart [Seite 991]
108.7 - 7 Technologies Used [Seite 991]
108.8 - 8 Conclusion [Seite 991]
108.9 - References [Seite 991]
109 - Design and Implementation of Arduino Based Control System for Power Management of Household Utilities [Seite 992]
109.1 - 1 Introduction [Seite 992]
109.2 - 2 Environmental Impact of Conventional Energy Resources [Seite 993]
109.3 - 3 Solar Power and Scope in India [Seite 993]
109.4 - 4 Experimental Setup [Seite 994]
109.5 - 5 Results and Discussion [Seite 995]
109.6 - 6 Conclusion [Seite 998]
109.7 - References [Seite 998]
110 - Interfacing Python with DIgSILENT Power Factory: Automation of Tasks [Seite 999]
110.1 - 1 Python Interpreter [Seite 999]
110.2 - 2 Python Power Factory Module [Seite 1000]
110.3 - 3 Python Power Factory Module Usage [Seite 1000]
110.4 - 4 Conclusion [Seite 1002]
110.5 - References [Seite 1003]
111 - Recent Development in Perovskite Solar Cell Based on Planar Structures [Seite 1004]
111.1 - 1 Introduction [Seite 1004]
111.2 - 2 Planar Structure [Seite 1006]
111.3 - 3 The Inverted Planar Structure [Seite 1007]
111.4 - 4 Summary [Seite 1009]
111.5 - References [Seite 1009]
