Soft Computing Applications in Modern Power and Energy Systems

Name: Soft Computing Applications in Modern Power and Energy Systems | Select Proceedings of EPREC 2023, Volume 4
Brand: Springer
Price: 128.39 EUR
Availability: OnlineOnly

Select Proceedings of EPREC 2023, Volume 4

Om Hari Gupta Narayana Prasad Padhy Sukumar Kamalasadan(Editor)

Springer (Publisher)

1st Edition

Published on 17. February 2024

X, 360 pages

E-Book

PDF with digital watermarking

System requirements

978-981-99-8007-9 (ISBN)

€128.39incl. 7% vat

System requirements

for PDF with digital watermarking

E-Book Single Licence

Available for download

Description

More details

Other editions

Persons

Om Hari Gupta received B.Tech. degree in electrical and electronics engineering from UP Technical University, Lucknow, Uttar Pradesh, India in 2007 and the M.Tech. degree in power electronics & ASIC design from Motilal Nehru National Institute of Technology, Allahabad, Prayagraj, Uttar Pradesh, India, in 2011 and the Ph.D. degree in electrical engineering from Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India, in 2017. He is an awardee of the Canadian Queen Elizabeth II Diamond Jubilee Scholarship for research visiting Canada and from March 2017 to June 2017, he was a visiting Researcher at the Ontario Tech University, Canada. Since 2018, Dr. Gupta has been an Assistant Professor with the Department of Electrical Engineering, National Institute of Technology Jamshedpur, Jharkhand, India. He is one of the founding organizing secretaries of the conference series "Electric Power and Renewable Energy Conference - EPREC". Dr. Gupta is the author of four books and has morethan 70 publications including 25 journal papers. He is a senior member of IEEE and a reviewer of many reputed journals like IEEE Transactions on Power Delivery, IET Generation and Transmission, Electric Power Systems Research, Electric Power Components and Systems, and International Journal of Electrical Power and Energy Systems. His research interests include power system protection, microgrid, renewable-based distributed generation, and electric power quality.
Narayana Prasad Padhy, Director, MNIT Jaipur and Director, IIIT Kota, is a Professor (HAG) of Electrical Engineering and has served as Dean of Academic Affairs, IIT Roorkee, Founder Head Mehta Family School of Data Science and Artificial Intelligence, Professor In-Charge Training and Placement, NEEPCO, and Institute Chair Professor at IIT Roorkee. Dr. Padhy is a prolific researcher in the area of Power Systems Engineering and Smart Grid. He has contributed significantly to the domain by way of securing research grants, supervising scholars, publishing research articles, writing books, securing patents, laboratory development and developing online NPTEL courses. Dr. Padhy has held visiting positions at eminent international universities and established research engagements and institutional tie-ups with these universities. He has collaborated with top industries and government agencies for research, laboratory development, and as a knowledge partner. He is well recognised in international and national professional bodies and has actively contributed in various capacities towards their growth. He also represents the country at various international research platforms.
Dr. Padhy is a well awarded and honoured scholarly professional at the national and international levels. Sukumar Kamalasadan is a Duke Energy Distinguished Professor of electric power engineering at the University of North Carolina at Charlotte (UNCC) and the Director of power energy and intelligent systems lab (PEISL) within the Energy Production and Infrastructure Center (EPIC) at UNCC. He received his Ph.D. degree in electrical engineering from the University of Toledo, OH in 2004. His research interests include data-driven approaches to power grid modernization, smart grid, microgrid, power system operation and optimization, power system dynamics, stability and control and renewable-energy-based distributed generation. Prof. Kamalasadan is an Associate Editor and paper review chair of the IEEE Transactions on Industry Applications, Editor of IEEE Transactions on Vehicular Technologies, and Editor of Elsevier Electrical Engineering Journal. He is a recipient of several awards, including the National Science Foundation Faculty Early CAREER Award in 2008, best paper awards from IEEE in 2015, 2018, and 2021, outstanding teaching awards in 2004, and Duke Energy Professorship in 2019. He is a Senior Member of the IEEE. Prof. Kamalasadan is the past chair of the IEEE Lifelong Learning Subcommittee (LLLSC),and Inaugural Chair of Selection and Quality Control Subcommittee which selects all the webinars and tutorials of IEEE Power and Energy Society (PES). He is a member of PES University Chairs, a group that designs and monitors IEEE PES University. He is also a member of IEEE PES oscillation location taskforce committee, co-chair for subtask under the oscillation location task force, a member of dynamic equivalent systems taskforce, member of working groups in Power System Relaying Committee, Member of IEEE PES distribution subcommittee and Energy storage and DER interconnection Taskforce. Past chair of IEEE IAS Industrial Automation and Control Committee, Chair of IEEE PES Power and Energy Education Committee, and past chair for IEEE PES Charlotte section. He has delivered more than 30 lectures/panels and keynotes in more than 10 countries. He is supervising/has supervised more than 25 M.S. and 30 Ph.D. level research students. He is the author of more than 200 archival type technicalpublications including a book (monograph type) and 4 patents.

Content

Intro
Contents
About the Editors
Coordinated Design of Damping Controllers for Power System Stability
1 Introduction
2 System Description
2.1 SMIB System
2.2 Power System Stabilizer (PSS)
2.3 Static Synchronous Series Compensator (SSSC)
3 Problem Formulation
4 Proposed Method
5 Results and Discussions
5.1 Nominal Loading (NL) Condition
5.2 Light Loading (LL) Condition
5.3 Heavy Loading (HL) Condition
6 Conclusion
References
The Effect of Electric Vehicle Charging Stations on Distribution Systems While Minimizing the Placement Cost and Maximizing Voltage Stability Index
1 Introduction
2 Objective Problem Formulation
2.1 Objective Function 1
2.2 Objective Function 2
2.3 Constraint Used
3 Optimization Technique Used
4 Numerical Analysis
5 Conclusion
References
SFO Based Economic Load Dispatch with FACTS Devices for DC Link Placement Problem
1 Introduction
2 Problem Statement with FACTS Devices and Solution Process
2.1 Representation of Decision Variables
3 Results and Discussions
4 Summary and Future Research
References
Selection of Batteries for Electric Vehicle Applications
1 Introduction
2 Methodology
2.1 For Charging
2.2 For Discharging
3 Battery Specifications
4 Results and Discussion
5 Conclusion
References
Issues and Solutions for Optimum Overcurrent Relays Co-Ordination in Medium Voltage Radial Distribution System
1 Introduction
2 Problem Formulation
2.1 Constraint Set I-Coordination Criteria
2.2 Constraint Set II-Bounds on Relay Operating Time
2.3 Constraint Set III-Bounds on the TMS of Relays
2.4 Constraint Set IV-Bounds on the Plug Setting (PS) of Relays
2.5 Constraint Set V-Relay Characteristic
3 Distribution Network
4 Results and Discussions
5 Conclusion
References
Powering Electric Vehicles with Solar Panels with Both the G2V and V2G Charging Modes
1 Introduction
2 History of Electric Vehicle Technologies
2.1 EV's Developing History
2.2 Battery
2.3 PV System
3 EV Circuit Configuration and Design
4 Simulation Results and Discussions
4.1 Mode 1: Solar PV Used for Charge the EV Battery and Supply the DC Load
4.2 Mode 2: Grid to Vehicle Mode with Solar PV
4.3 Mode 3: Vehicle to Grid Mode with Solar PV
5 Conclusion
References
Ultrasonic Analysis of Lorentz Force for Gas Density Monitoring Using EMAT Sensor
1 Introduction
2 Methodology
2.1 Mathematical Model
2.2 Geometric Analysis for Designing the Sensor
2.3 Generation of Eddy Current from Coil
2.4 Simulation of Dynamic Characteristics of the EMAT
3 Results
3.1 Quantitative Analysis of the Simulated Sensor
3.2 Parametric Analysis
4 Discussion
5 Conclusion
References
WSN Based Energy-Efficient Protocols for Smart Grid: A State-of-Art Review
1 Introduction
2 Energy Efficiency
3 Routing Protocol
4 Literature Review
4.1 LEACH: Low Energy Adaptive Cluster Head Protocol
4.2 PEGASIS: Power Efficient Gathering in Sensor Information System
4.3 TEEN: Threshold Sensitive Energy Efficient Sensor Network Protocol
4.4 APTEEN: Adaptive Periodic Threshold Energy Efficient Network Protocol
4.5 Energy Efficient Distributing Clustering
4.6 Additional Cluster Based Protocols Network
5 Conclusion
References
Wireless Sensor Network for Condition Monitoring of Axel Counter Device in Railways
1 Introduction
2 Requirements for Remote Supervision
3 Literature Review on Condition Monitoring
4 Basic Working Principle of an Axel Counter
5 Proposed Architecture Wireless Sensor Network
6 Advantages of Proposed System
6.1 Low Construction Cost
6.2 Error Free Signalling Data
6.3 Low Down Time of Train
6.4 Low Demand of Block Period
6.5 Energy Efficient system
6.6 Ease of Installation and Maintenance
7 Conclusion
References
PID Based Optimal Neural Control of Single Wheel Robot (SWR)
1 Introduction
2 Mathematical Model and Simulink of SWR
3 Designing of PID Based ANN Controller for SWR
4 Results and Comparison
5 Conclusion
References
Impact of Instrument Transformer Secondary Connections on Performance of Protection System-Analysis of Field Events from Indian Power Sector
1 Introduction
2 Fundamental Concepts and Review of Relevant IEEE Standards
2.1 Neutral Connection and Grounding of Instrument Transformer Secondary Circuits
2.2 Cable Selection for Instrument Transformer Connection
3 Commissioning and Retrofitting Philosophies of Powergrid
4 Analysis of Field Events
4.1 Problem in VT Selection Relay Leads to Tripping of Bus Reactor
4.2 400/220 kV 500MVA Auto Transformer Tripped on Differential Protection After Closing of Tie Circuit Breaker of HV Side
4.3 Line Tripped on Single Line to Ground Fault but the Phase to Neutral Voltage Were not the True Representation of Single Line to Ground Fault
4.4 Line Tripped on Operation of Over-Voltage During Planned Bus Shutdown at 765 kV Substation Due to Wiring Error.
4.5 Line Tripped Due to Faulty CT Cable on Detection of Phase-To-Phase Fault in the Distance Relay During Phase to Ground Fault on the Transmission Line
4.6 Auto Transformer Tripped on Operation of REF Protection Due to Damaged CT Lug
4.7 Auto Transformer Tripped on Operation of Differential Protection Due to Incorrect CT Ratio
4.8 Shunt Reactor Tripped on Operation of REF Protection Due to Problem in CT Wiring
4.9 Incorrect Direction Determination by Directional Overcurrent Protection Because of Missing CVT Neutral and Leads to Tripping of Auto Transformer
4.10 Phase-phase Fault in One of the 400 kV Line, One Out of the Two Protection Relay Declares Fuse Fail and Blocked the Distance Protection. The Problem was Due to Multiple Grounding of CVT Secondaries at Switchyard MB as well as at relay/control Panel
5 Instrument Transformer Secondary Connection and Cvt Transients
6 Conclusion
References
Reducing the Burden on the Utility Grid by Implementing the Demand Response Strategy with Home Loads and Solar PV Using TLBO Technique
1 Introduction
2 Home Load Energy Management System Model
2.1 Home Appliances
2.2 Solar Photo-Voltaic
3 Problem Formulation
4 Teaching Learning Based Optimization (TLBO) for HLEM
5 Results and Discussion
5.1 Scheduling with Traditional Structure
5.2 Scheduling with TLBO Optimization
6 Conclusion
References
Automatic Generation Control of Multi Area Power Systems Using BELBIC
1 Introduction
2 Mathematical Modelling of LFC
3 Concepts for Designing a Control System
4 Research Gaps and Challenges
4.1 Improvement of AI Optimization Techniques Over Conventional PI Controllers
5 Proposed Control Strategy
5.1 BELBIC Controller
6 Simulation Results and Discussion
7 Conclusion
References
Chaotic Quasi-Oppositional Differential Search Algorithm for Transient Stability Constraint Optimal Power Flow Problem
1 Introduction
2 Formulation of Mathematical Problems
2.1 Objective Function
2.2 Transient Stability Assessment
2.3 Constraints
3 Differential Search Algorithm (DSA)
3.1 Inspiration of DSA
3.2 Modelling of DSA Mathematically
4 Quasi-Oppositional Based Learning (Q-OBL)
4.1 Opposite Numbers
4.2 Opposite Pointing
4.3 Quasi-Opposite Number and Quasi-Opposite Point
4.4 Chaotic DSA
5 CQODSA Steps for OPF Problem
6 Simulation Results and Discussions
6.1 Test System-I (WSCC 3-Machine 9-Bus System)
6.2 Test System II (New England 10-Machine 39-Bus System)
7 Conclusion
References
Chaotic Quasi-Oppositional Moth Flame Optimization for Radial Distribution Network Reconfiguration with DG Allocation
1 Introduction
2 Mathematical Formulation
2.1 Intended Purpose
2.2 Modelling of Load
2.3 Constraints
3 Optimization Technique
3.1 Moth Flame Optimization
3.2 Quasi-Oppositional Based Learning
4 Chaotic Moth Flame
5 CQOMFO Applied to Reconfiguration Problem Along with DG
6 Results
6.1 Radial Distribution Network 33-Bus Demonstration
6.2 69-Bus Test Radial Distribution Network
7 Conclusion
References
Global Horizontal Irradiance Prediction Using Clustering and Artificial Neural Network
1 Introduction
2 Methodology
2.1 Problem Formulation
2.2 Artificial Neural Network (ANN)
2.3 Performance Metrics
3 Experiment
3.1 Data Description
3.2 Correlation Between Parameters
3.3 Seasonality
3.4 Data Pre-processing
4 Results and Discussion
5 Conclusion
References
Optimal Co-Ordination of Directional Overcurrent Relays in Distribution Network Using Whale Optimization Algorithm
1 Introduction
2 Optimization Problem Formulation
2.1 Objective Function
2.2 Constraints
2.3 Modified Objective Function
3 Whale Optimization Algorithm (WOA)
3.1 Prey Encircling
3.2 Bubble-Net Attacking
3.3 Prey Search
4 Results and Discussions
4.1 Case-1: 3-Bus Test Model
4.2 Case-2: 9-Bus Test Model
4.3 Case-3: 30-Bus Test Model
4.4 Discussions
5 Conclusions
References
Optimization and Comparative Analysis of Hybrid Renewable Energy Generation (Solar-Wind-Biomass) Using HOMER
1 Introduction
2 Methodology
2.1 Study Area
2.2 Load and Resource Assessment
3 Proposed System Simulation Model
3.1 System Configuration
3.2 PV Module
3.3 Wind Turbine
3.4 Bio-Generator
3.5 Battery
3.6 Converter
3.7 Grid
4 Optimization and Economic Analysis
4.1 Stand-Alone HRES
4.2 Grid Connected HRES
5 Comparative Analysis
6 Conclusion
References
A Review on Battery Management System
1 Introduction
2 Literature Review
3 Battery Management System
3.1 Types of Batteries in EVs
3.2 Function of BMS
3.3 BMS Topologies
3.4 BMS Architecture
4 Conclusion
References
Photovoltaic Faults Prediction by Neural Networks
1 Introduction
2 Problem Statement
3 Methodology
3.1 Building Model
4 Results
5 Conclusion
References
Neural Network-Based Approach for Islanding Detection in a PV Grid-Connected System
1 Introduction
2 Artificial Neural Network (ANN) Model
3 Voltage Phase-Jump Detection
4 Sequence Components of Voltage and Current at PCC
5 Proposed Islanding Detection Technique
6 Result and Discussion
7 Conclusion
References
An Investigation of Fault Detection in Electrical Distribution Systems Using Deep Neural Networks
1 Introduction
2 Discrete Wavelet Transform
3 Deep Learning
3.1 Generative Adversarial Networks (GANs)
3.2 Convolutional Neural Network (CNN)
3.3 Recurrent Neural Network (RNN)
3.4 Long Short-Term Memory Network (LSTM)
3.5 Deep Belief Networks (DBNs)
4 System Modeling
4.1 IEEE 33 Bus System
4.2 Fault Detection System Development
4.3 Results and Discussion
5 Future Scope
6 Conclusion
References
Solar Radiation Prediction Using Regression Methods
1 Introduction
2 Regression Methods
2.1 Multiple Linear Regression
2.2 Random Forest Regression
2.3 Gradient Boosting Regression
3 Methodology
3.1 Step of Prediction of Solar Irradiation
3.2 Evaluate Matrix
4 Result
5 Conclusion
References
Forecasting of Solar Power Generation Using Hybrid Empirical Mode Decomposition and Adaptive Neuro-Fuzzy Inference System
1 Introduction
2 Data Description/Case Study
2.1 Data Cleaning
2.2 Data Normalization
2.3 Feature Selection
3 Framework of Hybrid EMDANFIS Forecasting Model
3.1 Empirical Mode Decomposition (EMD)
3.2 Adaptive Neuro-Fuzzy Inference System (ANFIS)
3.3 Implementation of Hybrid EMDANFIS Network
4 Results and Discussion
5 Conclusions
References

System requirements

Save as PDF Copy link into clipboard

Schweitzer Fachinformationen

Soft Computing Applications in Modern Power and Energy Systems

Description

More details

Other editions

Additional editions

Persons

Content

System requirements