Smart Grids for Smart Cities, Volume 1
Description
Written and edited by a team of experts in the field, this first volume in a two-volume set focuses on an interdisciplinary perspective on the financial, environmental, and other benefits of smart grid technologies and solutions for smart cities.
What makes a regular electric grid a "smart" grid? It comes down to digital technologies that enable two-way communication between a utility and its customers, as opposed to the traditional electric grid, where power flows in one direction. Based on statistics and available research, smart grids globally attract the largest investment venues in smart cities. Smart grids and city buildings that are connected in smart cities contribute to significant financial savings and improve the economy. The smart grid has many components, including controls, computers, automation, and new technologies and equipment working together. These technologies cooperate with the electrical grid to respond digitally to our quickly changing electric demand.
The investment in smart grid technology also has certain challenges. The interconnected feature of smart grids is valuable, but it tremendously increases their susceptibility to threats. It is crucial to secure smart grids wherein many technologies are employed to increase real-time situational awareness and the ability to support renewables, as well as system automation to increase the reliability, efficiency, and safety of the electric grid.
This exciting new volume covers all of these technologies, including the basic concepts and the problems and solutions involved with the practical applications in the real world. Whether for the veteran engineer or scientist, the student, or a manager or other technician working in the field, this volume is a must-have for any library.
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O.V. Gnana Swathika, PhD, earned her PhD in electrical engineering from VIT University, Chennai, Tamil Nadu, India. She completed her postdoc at the University of Moratuwa, Sri Lanka in 2019. Her current research interests include microgrid protection, power system optimization, embedded systems, and photovoltaic systems.
K. Karthikeyan is an electrical and electronics engineering graduate with a master's in personnel management from the University of Madras. He has two decades of experience in electrical design. He is Chief Engineering Manager in Electrical Designs for Larsen & Toubro Construction.
Sanjeevikumar Padmanaban, PhD, Department of Electrical Engineering, IT and Cybernetics, University of South-Eastern Norway, Porsgrunn-Norway. He received his PhD in electrical engineering from the University of Bologna, Italy. He has almost ten years of teaching, research, and industrial experience and is an associate editor for a number of international scientific refereed journals. He has published more than 750 research papers and has won numerous awards for his research and teaching.
Content
Preface xvii
1 Carbon-Free Fuel and the Social Gap: The Analysis 1
Saravanan Chinnusamy, Milind Shrinivas Dangate and Nasrin I. Shaikh
1.1 Introduction 2
1.2 Objectives 3
1.3 Study Areas 3
1.3.1 Community A 4
1.3.2 Community B 4
1.3.3 community c 5
1.3.4 Community d 5
1.4 Data Collection 6
1.5 Data Analysis 9
1.6 Conclusion 10
References 13
2 Opportunities of Translating Mobile Base Transceiver Station (BTS) for EV Charging Through Energy Management Systems in DC Microgrid 15
A. Matheswaran, P. Prem, C. Ganesh Babu and K. Lakshmi
2.1 Introduction 16
2.1.1 Telecom Sector in India 16
2.1.2 Overview of Base Transceiver Station (BTS) 17
2.1.3 Electric Vehicle in India 19
2.1.4 Evolution of EV Charging Station 21
2.2 Translating Mobile Base Transceiver Station (BTS) for EV Charging 21
2.2.1 Mobile Base Transceiver Station (BTS) for EV Charging - A Substitute or Complementary Solution? 21
2.2.2 Proposed Methodology 23
2.2.3 System Description 24
2.2.3.1 Solar PV Array 24
2.2.3.2 DC-DC Boost Converter 25
2.2.3.3 Rectifier 25
2.2.3.4 Battery Backup System 26
2.2.3.5 Charge Controller 27
2.2.3.6 Bidirectional Converter 28
2.3 Implementation of Energy Management System in Base Transceiver Station (BTS) 29
2.3.1 Introduction 29
2.3.2 Control Strategies 30
2.3.2.1 MPPT Control 31
2.3.2.2 Charge Controller Control 31
2.3.2.3 Bidirectional Converter Control 32
2.3.3 Power Supervisory and Control Algorithm (PSCA) 33
2.3.3.1 Grid Available Mode 33
2.3.3.2 Grid Fault Mode 33
2.3.4 Results and Discussions 35
2.3.4.1 Grid Available Mode 35
2.3.4.2 Grid Failure Mode 35
2.4 Conclusion 35
References 38
3 A Review on Advanced Control Techniques for Multi-Input Power Converters for Various Applications 41
Kodada Durga Priyanka and Abitha Memala Wilson Duraisamy
3.1 Introduction 42
3.2 Multi-Input Magnetically Connected Power Converters 46
3.2.1 Dual-Source Power DC to DC Converter with Buck-Boost Arrangement 46
3.2.2 Bidirectional Multi-Input Arrangement 47
3.2.3 Full-Bridge Boost DC-DC Converter Formation 48
3.2.4 Multi-Input Power Converter with Half-Bridge and Full Bridge Configuration 49
3.3 Electrically Coupled Multi-Input Power DC-DC Converters 50
3.3.1 Combination of Electrically Linked Multi-Input DC/DC Power Converter 50
3.3.2 Multi-Input Power Converters in Series or Parallel Connection 51
3.3.3 Multi-Input DC/DC Fundamental Power Converters 52
3.3.4 Multiple-Input Boost Converter for RES 53
3.3.5 Multi-Input Buck-Boost/Buck/Boost-Boost Based Converter 54
3.3.6 Multi-Input Buck-Boost/Buck/Boost-Boost Based Converter 55
3.3.7 Multi-Input DC/DC Converter Using ZVS (Zero Voltage Switching) 57
3.3.8 Multi-Input DC-DC Converter Based Three Switches Leg 57
3.3.9 Multi-Input Converter Constructed on Switched Inductor/Switched Capacitor/Diode Capacitor 58
3.3.10 High/Modular VTR Multi-Input Converters 59
3.3.11 Multi/Input and Multi/Output (MIMO) Power Converter 60
3.4 Electro Magnetically Coupled Multi-Input Power DC/DC Converters 61
3.4.1 Direct Charge Multi-Input DC/DC Power Converter 61
3.4.2 Boost-Integrated Full-Bridge DC-DC Power Converter 62
3.4.3 Isolated Dual-Port Power Converter for Immediate Power Management 63
3.4.4 Dual Port Converter with Non-Isolated and Isolated Ports 63
3.4.5 Multi-Port ZVS And ZCS DC-DC Converter 64
3.4.6 Combined DC-Link and Magnetically Coupled DC/DC Power Converter 65
3.4.7 Three-Level Dual-Input DC-DC Converter 65
3.4.8 Half-Bridge Tri-Modal DC-DC Converter 66
3.4.9 Bidirectional Converter with Various Collective Battery Storage Input Sources 75
3.5 Different Control Methods Used in Multi-Input DC-DC Power Converters 75
3.5.1 Proportional Integral Derivation Controller (PID) 76
3.5.2 Model Predictive Control Method (MPC) 77
3.5.3 State Space Modelling (SSM) 78
3.5.4 Fuzzy Logic Control (FLC) 79
3.5.5 Sliding Mode Control (SMC) 80
3.6 Comparison and Future Scope of Work 82
3.6.1 Comparison and Discussion 82
3.7 Conclusion 85
References 86
4 Case Study: Optimized LT Cable Sizing for an IT Campus 101
O.V. Gnana Swathika, K. Karthikeyan, Umashankar Subramaniam and K.T.M.U. Hemapala
Abbreviations 102
4.1 Introduction 102
4.2 Methodology 103
4.2.1 Algorithm for Cable Sizing 103
4.3 Results and Discussion 103
4.3.1 Feeder Schedule 104
4.3.2 Design Consideration for LT Power Cable 104
4.3.3 Cable Sizing & Voltage Drop Calculation 107
4.4 Conclusion 114
References 114
5 Advanced Control Architecture for Interlinking Converter in Autonomous AC, DC and Hybrid AC/DC Micro Grids 115
M. Padma Lalitha, S. Suresh and A. Viswa Pavani
5.1 Introduction 116
5.2 Prototype Model of IC 117
5.3 Implemented Photo Voltaic System 118
5.4 Highly Reliable and Efficient (HRE) Configurations 120
5.5 MATLAB Simulink Results 122
5.6 Conclusion 127
References 127
6 Optimal Power Flow Analysis in Distributed Grid Connected Photovoltaic Systems 131
Neenu Thomas, T.N.P. Nambiar and Jayabarathi R.
6.1 Introduction 131
6.2 System Development and Design Parameters 132
6.3 Proposed Algorithm 138
6.4 Results and Discussion 138
6.5 Conclusion 141
References 141
7 Reliability Assessment for Solar and Wind Renewable Energy in Generation System Planning 143
S. Vinoth John Prakash and P.K. Dhal
7.1 Introduction 144
7.2 Generation & Load Model 146
7.2.1 Generation Model-RBTS 146
7.2.2 Wind Power Generation Model 147
7.2.2.1 Wind Speed and Wind Turbine Output Model 147
7.2.3 Solar Power Generation Model 150
7.2.3.1 Solar Radiation and Solar Power Output Model 150
7.2.4 Load Model 152
7.3 Results and Analysis 152
7.3.1 Reliability Indices Evaluation for Different Scenario 153
7.4 Conclusion 155
References 156
8 Implementation of Savonius Blad Wind Tree Structure by Super Lift Luo Converter for Smart Grid Applications and Benefits to Smart City 159
Jency Joseph J., Anitha Mary X., Josh F. T., Vinoth Kumar K. and Vinodha K.
8.1 Introduction 160
8.2 Savonius Wind Turbine - Performance Design 160
8.3 Design Modules 163
8.4 Results and Discussion 167
8.5 Positive Output Super Lift Luo Converter 170
8.6 Conclusion 171
References 172
9 Analysis: An Incorporation of PV and Battery for DC Scattered System 175
M. Karuppiah, P. Dineshkumar, A. Arunbalaj and S. Krishnakumar
9.1 Introduction 176
9.2 Block Diagram of Proposed System 179
9.2.1 Determine the Load Profile 180
9.2.2 Duration of Autonomy and Recharge 180
9.2.3 Select the Battery Rating 181
9.2.4 Sizing the PV Array 182
9.2.5 Analysis of Boost Converter 184
9.2.5.1 To Select a Proper Inductor Value 187
9.2.5.2 To Select a Proper Capacitor Value 187
9.3 Proposed System Simulations 188
9.4 Conclusion 192
References 193
10 Dead Time Compensation Scheme Using Space Vector PWM for 3Ø Inverter 195
Sreeramula Reddy, Ravindra Prasad, Harinath Reddy and Suresh Srinivasan
10.1 Introduction 195
10.2 Concept of Space Vector PWM 197
10.3 Proteus Simulation 200
10.4 Hardware Setup 201
10.4.1 Total Harmonic Distortion 206
10.4.2 Hardware Configuration 209
10.5 Conclusion 210
References 211
11 Transformer-Less Grid Connected PV System Using TSRPWM Strategy with Single Phase 7 Level Multi-Level Inverter 213
S. Sruthi, K. Karthikumar, D. Narmitha, P. Chandra Sekhar and K. Karthi
11.1 Introduction 214
11.2 Proposed System 215
11.3 DC-DC Influence Converter 216
11.4 Controlling of 7-Level Inverter 218
11.5 Controlling for Boost Converter and Inverter 221
11.6 MATLAB Simulation Results 221
11.7 Conclusion 224
References 225
12 An Enhanced Multi-Level Inverter Topology for HEV Applications 227
Premkumar E. and Kanimozhi G.
12.1 Introduction 227
12.2 E-MLI Topology 228
12.2.1 Switching Operation of the E-MLI Topology 229
12.2.2 Diode-Clamped Multi-Level Inverter (DC-MLI) 232
12.3 PWM for the E-MLI Topology 233
12.3.1 SPWM Based Switching for the E-MLI Topology 234
12.3.2 Phase Opposition Disposition (POD) Scheme for DC-MLI 234
12.4 Simulation Results & Discussions 236
12.5 Conclusion 249
References 249
13 Improved Sheep Flock Heredity Algorithm-Based Optimal Pricing of RP 253
P. Booma Devi, Booma Jayapalan and A.P. Jagadeesan
13.1 Introduction 254
13.2 RP Flow Tracing 257
13.2.1 Intent Function 257
13.2.1.1 System's Price Loss After RP Compensation 257
13.2.1.2 SVC Support Price for RP 258
13.2.1.3 Diesel Generator RP Production Price 258
13.2.1.4 Minimization Function 258
13.3 Existing Methodologies 259
13.3.1 Particle Swarm Optimization (PSO) 259
13.3.1.1 PSO Parameter Settings 259
13.3.2 Hybrid Particle Swarm Optimization (HPSO) 260
13.3.2.1 Flowchart for HPSO 260
13.4 Proposed Methodology 261
13.4.1 Improved Sheep Flock Heredity Algorithm 261
13.4.2 ISFHA Algorithm 263
13.5 Case Study 263
13.5.1 Realistic Seventy-Five Bus Indian System Wind Farm 263
13.6 Conclusion 266
References 267
14 Dual Axis Solar Tracking with Weather Monitoring System by Using IR and LDR Sensors with Arduino UNO 269
Rajesh Babu Damala and Rajesh Kumar Patnaik
14.1 Introduction 269
14.2 Associated Hardware Components Details 270
14.2.1 Arduino Uno 270
14.2.2 L293D Motor Driver 271
14.2.3 LDR Sensor 272
14.2.4 Solar Panel 273
14.2.5 RPM 10 Motor 274
14.2.6 Jumper Wires 274
14.2.7 16×2 LCD (Liquid Crystal Display) Module with I2C 275
14.2.8 DTH11 Sensor 276
14.2.9 Rain Drop Sensor 276
14.3 Methodology 277
14.3.1 Dual Axis Solar Tracking System Working Model 277
14.3.2 Dual Axis Solar Tracking System Schematic Diagram 279
14.4 Results and Discussion 279
14.5 Conclusion 281
References 282
15 Missing Data Imputation of an Off-Grid Solar Power Model for a Small-Scale System 285
Aadyasha Patel, Aniket Biswal and O.V. Gnana Swathika
Abbreviations and Nomenclature 286
15.1 Overview 286
15.2 Literature Review 287
15.3 AI/ML for Imputation of Missing Values 288
15.3.1 Cbr 288
15.3.2 Mice 290
15.3.3 Results and Discussion 291
15.3.3.1 Data Collection 291
15.3.3.2 Error Metrics 292
15.3.3.3 Comparison Between CBR and MICE 293
15.4 Applications of MICE in Imputation 296
15.5 Summary 296
References 297
16 Power Theft in Smart Grids and Microgrids: Mini Review 299
P. Tejaswi and O.V. Gnana Swathika
16.1 Introduction 299
16.2 Smart Grids/Microgrids Security Threats and Challenges 300
16.2.1 Security Threats to Smart Grid/Microgrid by Classification of Sources 301
16.2.1.1 Smart Grid/Microgrid Threats Sources in Technical Point of View 302
16.2.2 Sources of Smart Grids/Microgrids Threats in Non-Technical Point of View 304
16.2.2.1 Security of Environment 304
16.2.2.2 Regulatory Policies of Government 304
16.3 Conclusion 304
References 304
17 Isolated SEPIC-Based DC-DC Converter for Solar Applications 309
Varun Mukesh Lal, Pranay Singh Parihar and Kanimozhi. G
17.1 Introduction 309
17.2 Converter Operation and Analysis 311
17.2.1 Mode A 311
17.2.2 Mode B 313
17.3 Design Equations 314
17.4 Simulation Results 316
17.5 Conclusion 321
References 321
18 Hybrid Converter for Stand-Alone Solar Photovoltaic System 323
R.R. Rubia Gandhi and C. Kathirvel
18.1 Introduction 324
18.2 Review on Converter Topology 324
18.3 Block Diagram 325
18.4 Existing Converter Topology 326
18.5 Proposed Tapped Boost Hybrid Converter 326
18.5.1 Novelty in the Circuit 327
18.5.2 Converter Modes of Operation 327
18.6 Derivation Part of Tapped Boost Hybrid Converter 327
18.6.1 Voltage Gain 328
18.6.2 Modulation Index 328
18.7 Design Specification of the Converter 329
18.8 Simulation Results for Both DC and AC Power Conversion 330
18.9 Hardware Results 330
18.10 TBHC Parameters for Simulation 332
18.11 Conclusion 334
References 334
19 Analysis of Three-Phase Quasi Switched Boost Inverter Based on Switched Inductor-Switched Capacitor Structure 337
P. Sriramalakshmi, Vachan Kumar, Pallav Pant and Reshab Kumar Sahoo
19.1 Introduction 337
19.1.1 Conventional Inverter (VSI) 339
19.1.2 Z-Source Inverter (ZSI) 339
19.1.3 SBI Based on SL-SC Structure 340
19.2 Working Modes of Three-Phase SL-SC Circuit 341
19.2.1 Shoot-Through State 341
19.2.2 Non-Shoot-Through State 342
19.3 Design of Three-Phase SL-SC Based Quasi Switched Boost Inverter 342
19.3.1 Steady State Analysis of SL-SC Topology 342
19.3.2 Design of Passive Elements 344
19.3.3 Design Equations 344
19.3.4 Design Specifications 344
19.4 Simulation Results and Discussions 344
19.4.1 Simulation Diagram of SBC PWM Technique 344
19.4.2 SBC PWM Technique 345
19.4.3 Switching Pulse Generated for the Power Switches 347
19.4.4 Expanded Switching Pulse 348
19.4.5 Input Current 348
19.4.6 Current in Inductor L 1 349
19.4.7 Current in Inductor L 2 349
19.4.8 Capacitor Voltage VC 2 350
19.4.9 dc Link Voltage 350
19.4.10 Output Load Voltage 351
19.4.11 Output Load Current 351
19.5 Performance Analysis 351
19.6 Conclusion 353
References 354
20 Power Quality Improvement and Performance Enhancement of Distribution System Using D-STATCOM 357
M. Sai Sandeep, N. Balaji, Muqthiar Ali and Suresh Srinivasan
20.1 Introduction 358
20.2 Distribution Static Synchronous Compensator (d-statcom) 360
20.3 Modelling of Distribution System 361
20.3.1 Single Machine System 361
20.3.2 Modeling of IEEE 14 Bus System 362
20.4 Simulation Results & Discussions 363
20.4.1 Power Flow Analysis on Single Machine System 363
20.4.2 Different Modes of Operation of D-STATCOM on Single Machine System 365
20.4.3 Step Change in Reference Value of dc Link Voltage 368
20.5 IEEE-14 Bus Systems 370
20.6 Conclusion 374
References 374
Index 377
1
Carbon-Free Fuel and the Social Gap: The Analysis
Saravanan Chinnusamy1, Milind Shrinivas Dangate1* and Nasrin I. Shaikh2┼
1 Chemistry Division, School of Advanced Sciences, Vellore Institute of Technology, Chennai, Tamilnadu, India
2 Department of Chemistry, Nowrosjee Wadia College, Pune, Maharashtra, India
Abstract
Many consider utility-scale photovoltaic solar power to be an essential component of decarbonizing the Indian power sector and mitigating climate change. This technology is well accepted by the public in general surveys, yet often faces local resistance during project siting. This phenomenon is known as the "social gap." Using social gap theory from the wind energy literature as a foundation, this study examines the causes of and offers recommendations for addressing the solar social gap in Maharashtra. The study relied on 33 semi-structured interviews with citizens, government officials, and developers across four Maharashtra communities, each facing a prospective utility-scale solar project. Through thematic analysis, the study shows that the solar social gap can be attributed to both a vocal minority that dominated community sentiment and project proposals that failed to meet the community's standards for acceptable development. The gap was exacerbated by the presence of organized opposition groups as well as decision-makers relying on ineffective public processes to engage citizens. This research makes it clear that government officials and developers need to adopt practices that enhance community representation, process transparency, and decision-influence. Though decisionmaking strategies are not the only factor that affects community acceptance, implementing improved procedures could help close the solar social gap.
Keywords: Renewable energy, carbon-free fuel, smart cities, solar cells, communication gap
1.1 Introduction
Solar PV is undoubtedly a key player in the future of energy [1]. This technology continues to see cost reductions and is significantly contributing to new additions in generation capacity [2]. Utility-scale solar projects, i.e., ground-mounted systems that produce 50 MW of power or more for consumption by utility-users have a distinct competitive edge. As solar PV becomes increasingly attractive in the market, there will likely be a surge in development of large-scale solar arrays on what has been termed "subprime land" or land lacking one or more of the three prime requirements for development: solar resource potential, aesthetic buffers or distance from communities, and necessary grid capacity [3]. Maharashtra may already be experiencing this trend.
Additionally, there is high national public acceptance for solar energy; over 80% of India supports its development, although, as we have learned from wind, favorable survey results do not always adequately reflect what is happening in reality. There has been documentation of community disapproval of solar developments in southern India; one researcher has even identified the solar social gap in that area [4]. These utility-scale solar farms have been scrutinized for intermittency, aesthetics, socioeconomic impacts, wildlife hazards, human health hazards, and cultural infringement [5]. This response may provide a glimpse into what is to come as large-scale solar farm proposals expand beyond the Sun Belt. Therefore, there is a need to study how the deployment of utility-scale solar farms in unprecedented areas are received by the public compared to hypothetical circumstances, i.e., the unfolding of a midwestern solar social gap.
There are a limited number of studies that have examined the acceptance [1] of people living near large-scale solar farms or having experienced local solar development in the south. This may have been previously due to a lack of projects available to study; however, continued improvements are inviting more solar energy onto the grid which is creating new opportunities to capture the public's reaction. [6] were among one of the first to seize this research potential. They performed a content analysis of newspapers to understand reasons for citizens' support and opposition to solar projects in Gujarat and Rajasthan. My research will take a deeper dive into the Gujarat by using semi-structured interviews to examine community acceptance of and related decision-making processes for proposed utility-scale solar projects.
1.2 Objectives
The objectives of this research guided my inquiry and analysis to sufficiently identify and describe the various elements of the solar social gap. I attempted to set up the layout of my results and discussion to match the order of my objectives to demonstrate clear connections. The objectives of this research are as follows:
- Determine public support or opposition, attitudes, perceptions, and values associated with utility-scale solar projects.
- Analyze the solar social gap using [7] wind social gap determinants.
- Investigate how governmentand developer-led public engagement processes address or contribute to the solar social gap.
- Identify best practices for public engagement in utilityscale solar project siting to help diminish the solar social gap.
1.3 Study Areas
Four communities[8] in Maharashtra have been targeted to examine acceptance and procedures related to large-scale solar projects. The locations of these study sites are left unnamed to protect participants' privacy. Instead, I will refer to the four communities as Community A, B, C, and D. I also redacted the site-specific references (e.g., media sources, public records, project websites) from this report as a further discretionary precaution.
Site selection was based on what is already known about each community's public response to a solar farm proposal, zoning level, and estimated project size. According to online news articles and public records, Communities A and C have yet to report much, if any, controversy regarding their projects (Redacted 3; Redacted 4), while Communities B and D have experienced notably contentious development processes (Redacted 2; Redacted 6). Within both groupings, there is one township that is zoned locally and one that is (or was) zoned at the county level. See Figure 1.1 for a visual. This case selection was done to achieve a more accurate representation of the views on and approaches to utility-scale solar [9]. Additionally, at the time of this writing, these projects would be the largest solar farms in Maharashtra.
Figure 1.1 Matrix of study areas by zoning level and anticipated acceptance.
1.3.1 Community A
Community A consists of two townships, each housing less than 2,500 residents (Redacted 10; Redacted 12). Both townships are zoned at the county level. A special use permit was unanimously approved by the county planning commission to permit construction of a solar farm that will span over 1,000 acres and produce more than 200 MW of power.
Based on information from the developer's website, they worked closely with township residents to hear their thoughts and answer any questions that came up. They facilitated this discussion by hosting several community forums (Redacted 1). Overall, media accounts have claimed that the public has been receptive to this solar farm (Redacted 3). Even back when the project was first introduced to the area, there were few complaints from the residents (Redacted 5).
1.3.2 Community B
Community B is a single township and home to just over 2,800 people (Redacted 8). This area was formerly county zoned until the prospects of solar development were introduced. The county established a large-scale solar ordinance and a developer subsequently submitted a proposal to build a solar array shy of 1,000 acres on rural land primarily in Community B (Redacted 6). Many of the township residents were reportedly unenthusiastic about the idea of living next to a large solar farm (Redacted 6). Further, township officials claimed that the solar array was not in accordance with their master plan (Redacted 6). In response, Community B moved to execute their right to self-zone and created an interim ordinance that would temporary block any large-scale solar development. The township's actions caused the county to postpone consideration of the solar farm application [6]. The developer subsequently sued the township, and litigations are pending at the time of this writing. The proposed project will remain on hold until the township finalizes their zoning ordinance and settles matters in court.
1.3.3 Community C
Community C has an estimated population of just over 2,100 (Redacted 11). This self-zoned municipality unanimously passed a solar energy ordinance several years back and has since approved multiple utility-scale solar projects collectively exceeding 1,000 acres.
Both developers in Community C claimed to have used a similar public engagement approach as the developer in Community A (Redacted 7). Online news articles have not identified residents raising concerns or disapproval (Redacted 4).
1.3.4 Community D
Community D has a population of roughly 3,400 residents and is locally zoned (Redacted 9). The township board initially approved a solar ordinance from which a developer proposed a utility-scale project that would cover nearly 1,000 acres. However, due to some...
