Probabilistic Power System Expansion Planning with Renewable Energy Resources and Energy Storage Systems: (IEEE Press Series on Power and Energy Systems)

Probabilistic Power System Expansion Planning with Renewable Energy Resources and Energy Storage Systems Discover how modern techniques have shaped complex power system expansion planning with this one-stop resource from two experts in the field Probabilistic Power System Expansion Planning with Renewable Energy Resources and Energy Storage Systems delivers a comprehensive collection of innovative approaches to the probabilistic planning of generation and transmission systems under uncertainties. The book includes renewables and energy storage calculations when using probabilistic and deterministic reliability techniques to assess system performance from a long-term expansion planning viewpoint. Divided into two sections, the book first covers topics related to Generation Expansion Planning, with chapters on cost assessment, methodology and optimization, and more. The second and final section provides information on Transmission System Expansion Planning, with chapters on reliability constraints, probabilistic production cost simulation, and more. Probabilistic Power System Expansion Planning compares the optimization and methodology across dynamic, linear, and integer programming and explores the branch and bound algorithm. Along with case studies to demonstrate how the techniques described within have been applied in complex power system expansion planning problems, readers will enjoy: A thorough discussion of generation expansion planning, including cost assessment, methodology and optimization, and probabilistic production cost An exploration of transmission system expansion planning, including the branch and bound algorithm, probabilistic production cost simulation for TEP, and TEP with reliability constraints An examination of fuzzy decision making applied to transmission system expansion planning A treatment of probabilistic reliability-based grid expansion planning of power systems including wind turbine generators Perfect for power and energy systems designers, planners, operators, consultants, practicing engineers, software developers, and researchers, Probabilistic Power System Expansion Planning with Renewable Energy Resources and Energy Storage Systems will also earn a place in the libraries of practicing engineers who regularly deal with optimization problems.

Table of Contents:
Author Biographies xvii Preface xix Acknowledgments xxv Part I Generation Expansion Planning 1 1 Introduction 3 1.1 Electricity Outlook 3 1.2 Renewables 8 1.3 Power System Planning 12 2 Background on Generation Expansion Planning 15 2.1 Methodology and Issues 15 2.2 Formulation of the Least-Cost Generation Expansion Planning Problem 18 3 Cost Assessment and Methodologies in Generation Expansion Planning  21 3.1 Basic Cost Concepts 21 3.1.1 Annual Effective Discount Rate 22 3.1.2 Present Value 23 3.1.3 Relationship Between Salvage Value and Depreciation Cost 24 3.2 Methodologies 26 3.2.1 Dynamic Programming 26 3.2.2 Linear Programming 27 3.2.2.1 Investment Cost (Capital Cost) 27 3.2.2.2 Operating Cost 27 3.2.2.3 LP Formula 28 3.2.3 Integer Programming 28 3.2.4 Multi-objective Linear Programming 28 3.2.5 Genetic Algorithm 29 3.2.6 Game Theory 30 3.2.7 Reliability Worth 32 3.2.8 Maximum Principle 32 3.3 Conventional Approach for Load Modeling 34 3.3.1 Load Duration Curve 34 4 Load Model and Generation Expansion Planning 39 4.1 Introduction 39 4.2 Analytical Approach for Long-Term Generation Expansion Planning 40 4.2.1 Representation of Random Load Fluctuations 41 4.2.2 Available Generation Capacities 43 4.2.3 Expected Plant Outputs 44 4.2.4 Expected Annual Energy 47 4.2.5 Reliability Measures 47 4.2.5.1 Expected Annual Unserved Energy 47 4.2.5.2 Annual Loss-of-Load Probability 47 4.2.6 Expected Annual Cost 48 4.2.7 Expected Marginal Values 49 4.3 Optimal Utilization of Hydro Resources 50 4.3.1 Introduction 50 4.3.2 Conventional Peak-Shaving Operation and its Problems 51 4.3.3 Peak-Shaving Operation Based on Analytical Production Costing Model 52 4.3.3.1 Basic Concept 52 4.3.3.2 Peak-Shaving Operation Problem 53 4.3.4 Optimization Procedure for Peak-Shaving Operation 53 4.4 Long-Range Generation Expansion Planning 56 4.4.1 Statement of Long-Range Generation Expansion Planning Problem 56 4.4.1.1 Master Problem and Basic Subproblems 57 4.4.1.2 Hydro Subproblem 58 4.4.2 Optimization Procedures 59 4.5 Case Studies 60 4.5.1 Test for Accuracy of Formulas 60 4.5.2 Test for Solution Convergence and Computing Efficiency 62 4.6 Conclusion 65 5 Probabilistic Production Simulation Model 67 5.1 Introduction 67 5.2 Effective Load Distribution Curve 67 5.3 Case Studies 71 5.3.1 Case Study I: Sample System I With One 30MW Generator Only 71 5.3.2 Case Study II: Sample System II With One 10MW Generator Only 75 5.3.3 Case Study III: Sample System III With Two Generators – 30 and 10MW 78 5.4 Probabilistic Production Simulation Algorithm 82 5.4.1 Hartley Transform 82 5.5 Supply Reserve Rate 90 6 Decision Maker’s Satisfaction Using Fuzzy Set Theory 95 6.1 Introduction 95 6.2 Fuzzy Dynamic Programming 96 6.3 Best Generation Mix 97 6.3.1 Problem Statement 97 6.3.2 Objective Functions 97 6.3.3 Constraints 99 6.3.4 Membership Functions 100 6.3.5 The Proposed Fuzzy Dynamic Programming-Based Solution Procedure 101 6.4 Case Study 102 6.4.1 Results and Discussion 104 6.5 Conclusion 108 7 Best Generation Mix Considering Air Pollution Constraints 111 7.1 Introduction 111 7.2 Concept of Flexible Planning 111 7.3 LP Formulation of the Best Generation Mix 112 7.3.1 Problem Statement 112 7.3.2 Objective Functions 113 7.4 Fuzzy LP Formulation of Flexible Generation Mix 116 7.4.1 The Optimal Decision Theory by Fuzzy Set Theory 116 7.4.2 The Function of Fuzzy Linear Programming 117 7.5 Case Studies 118 7.5.1 Results by Non-Fuzzy Model 120 7.5.2 Results by Fuzzy Model 122 7.6 Conclusion 124 8 Generation System Expansion Planning with Renewable Energy 127 8.1 Introduction 127 8.2 LP Formulation of the Best Generation Mix 128 8.2.1 Problem Statement 128 8.2.2 Objective Function and Constraints 129 8.3 Fuzzy LP Formulation of Flexible Generation Mix 132 8.3.1 The Optimal Decision Theory by Fuzzy Set Theory 132 8.3.2 The Function of Fuzzy Linear Programming 133 8.4 Case Studies 134 8.4.1 Test Results 134 8.4.2 Sensitivity Analysis 134 8.4.2.1 Capacity Factor of WTG and SCG 134 8.5 Conclusion 140 9 Reliability Evaluation for Power System Planning with Wind Generators and Multi-Energy Storage Systems 141 9.1 Introduction 141 9.2 Probabilistic Reliability Evaluation by Monte Carlo Simulation 143 9.2.1 Probabilistic Operation Model of Generator 1 143 9.2.2 Probabilistic Operation Model of Generator 2 144 9.3 Probabilistic Output Prediction Model of WTG 145 9.4 Multi-Energy Storage System Operational Model 147 9.4.1 Constraints of ESS control (EUi,k) 149 9.5 Multi-ESS Operation Rule 150 9.5.1 Discharging Mode 150 9.5.2 Charging Mode 151 9.6 Reliability Evaluation with Energy Storage System 151 9.7 Case Studies 152 9.7.1 Power System of Jeju Island 152 9.7.2 Reliability Evaluation of Single-ESS 156 9.7.3 Reliability Evaluation of Multi-ESS 159 9.7.4 Comparison of System A and System B 162 9.8 Conclusion 163 9.A Appendices 164 9.A.1 Single-ESS Model 164 9.A.2 Multi-ESS Model 167 9.A.3 Operation of Multi-ESS Models 168 Method 1: Energy Rate Dispatch Method (ERDM) 173 Method 2: Maximum First Priority Method (MFPM) 173 9.A.4 A Comparative Analysis of Single-ESS and Multi-ESS Models 175 10 Genetic Algorithm for Generation Expansion Planning and Reactive Power Planning 177 10.1 Introduction 177 10.2 Generation Expansion Planning 178 10.3 The Least-Cost GEP Problem 179 10.4 Simple Genetic Algorithm 180 10.4.1 String Representation 181 10.4.2 Genetic Operations 181 10.5 Improved GA for the Least-Cost GEP 182 10.5.1 String Structure 182 10.5.2 Fitness Function 182 10.5.3 Creation of an Artificial Initial Population 183 10.5.4 Stochastic Crossover, Elitism, and Mutation 185 10.6 Case Studies 186 10.6.1 Test Systems’ Description 186 10.6.2 Parameters for GEP and IGA 187 10.6.3 Numerical Results 189 10.6.4 Summary 192 10.7 Reactive Power Planning 192 10.8 Decomposition of Reactive Power Planning Problem 194 10.8.1 Investment-Operation Problem 194 10.8.2 Benders Decomposition Formulation 195 10.9 Solution Algorithm for VAR Planning 196 10.10 Simulation Results 198 10.10.1 The 6-bus System 198 10.10.2 IEEE 30-bus System 199 10.10.3 Summary 200 10.11 Conclusion 201 References 203 Part II Transmission System Expansion Planning 213 11 Transmission Expansion Planning Problem 215 11.1 Introduction 215 11.2 Long-Term Transmission Expansion Planning 216 11.3 Yearly Transmission Expansion Planning 218 11.3.1 Power Flow Model 218 11.3.2 Optimal Operation Cost Model 220 11.3.3 Probability of Line Failures 222 11.3.4 Expected Operation Cost 223 11.3.5 Annual Expected Operation Cost 224 11.4 Long-Term Transmission Planning Problem 224 11.4.1 Long-Term Transmission Planning Model 225 11.4.2 Solution Technique for the Planning Problem 226 11.5 Case Study 227 11.6 Conclusion 232 12 Models and Methodologies 235 12.1 Introduction 235 12.2 Transmission System Expansion Planning Problem 235 12.3 Cost Evaluation for TEP Considering Electricity Market 236 12.4 Model Development History for TEP Problem 237 12.5 General DC Power Flow-Based Formulation of TEP Problem 238 12.5.1 Linear Programming 239 12.5.2 Dynamic Programming 240 12.5.3 Integer Programming (IP) 242 12.5.4 Genetic Algorithm by Mixed Integer Programming (MIP) 245 12.6 Branch and Bound Algorithm 246 12.6.1 Branch and Bound Algorithm and Flow Chart 246 12.6.2 Sample System Study by Branch and Bound 248 13 Probabilistic Production Cost Simulation for TEP 257 13.1 Introduction 257 13.2 Modeling of Extended Effective Load for Composite Power System 259 13.3 Probability Distribution Function of the Synthesized Fictitious Equivalent Generator 263 13.4 Reliability Evaluation and Probabilistic Production Cost Simulation at Load Points 265 13.5 Case Studies 266 13.5.1 Numerical Calculation of a Simple Example 266 13.5.2 Case Study: Modified Roy Billinton Test System 274 13.6 Conclusion 288 14 Reliability Constraints 291 14.1 Deterministic Reliability Constraint Using Contingency Constraints 291 14.1.1 Introduction 291 14.1.2 Transmission Expansion Planning Problem 292 14.1.3 Maximum Flow Under Contingency Analysis for Security Constraint 297 14.1.4 Alternative Types of Contingency Criteria 298 14.1.5 Solution Algorithm 299 14.1.6 Case Studies 300 14.1.7 Conclusion 316 Appendix 319 14.2 Deterministic Reliability Constraints 322 14.2.1 Introduction 322 14.2.2 Transmission System Expansion Planning Problem 323 14.2.3 Maximum Flow Under Contingency Analysis for Security Constraint 325 14.2.4 Solution Algorithm 325 14.2.5 Case Studies 326 14.2.6 Conclusion 331 14.3 Probabilistic Reliability Constraints 333 14.3.1 Introduction 333 14.3.2 Transmission System Expansion Planning Problem 338 14.3.3 Composite Power System Reliability Evaluation 340 14.3.4 Solution Algorithm 343 14.3.5 Case Study 344 14.3.6 Conclusion 357 14.4 Outage Cost Constraints 357 14.4.1 Introduction 357 14.4.2 The Objective Function 358 14.4.3 Constraints 359 14.4.4 Outage Cost Assessment of Transmission System 360 14.4.5 Reliability Evaluation of Transmission System 363 14.4.6 Outage Cost Assessment 363 14.4.7 Solution Algorithm 364 14.4.8 Case Study 365 14.4.9 Conclusion 369 14.5 Deterministic–Probabilistic (D–P) Criteria 373 15 Fuzzy Decision Making for TEP 375 15.1 Introduction 375 15.2 Fuzzy Transmission Expansion Planning Problem 377 15.3 Equivalent Crisp Integer Programming and Branch and Bound Method 379 15.4 Membership Functions 380 15.5 Solution Algorithm 381 15.6 Testing 382 15.6.1 Discussion of Results 384 15.6.2 Solution Sensitivity to Reliability Criterion 387 15.6.3 Sensitivity to Budget for Construction Cost 389 15.7 Case Study 390 15.8 Conclusion 396 15.A Appendix 396 15.A.1 Network Modeling of Power System 396 15.A.2 Definition 397 15.A.3 Fuzzy Integer Programming (FIP) 398 16 Optimal Reliability Criteria for TEP 401 16.1 Introduction 401 16.2 Probabilistic Optimal Reliability Criterion 401 16.2.1 Introduction 401 16.2.2 Optimal Reliability Criterion Determination 403 16.2.3 Optimal Composite Power System Expansion Planning 403 16.2.3.1 The Objective Function 403 16.2.3.2 Constraints 405 16.2.4 Composite Power System Reliability Evaluation and Outage Cost Assessment 406 16.2.4.1 Reliability Evaluation at HLI 406 16.2.4.2 Reliability Evaluation at HLII (Composite Power System) 407 16.2.4.3 Flow Chart of the Proposed Methodology for Optimal Reliability Criterion Determination in Transmission System Expansion Planning 409 16.2.5 Case Study 410 16.2.6 Conclusion 416 16.3 Deterministic Reliability Criterion for Composite Power System Expansion Planning 416 16.3.1 Introduction 416 16.3.2 Optimal Reliability Criterion Determination 419 16.3.3 Optimal Composite Power System Expansion Planning 419 16.3.3.1 Composite Power System Expansion Planning Formulation in CmExpP.For 419 16.3.3.2 Flow Chart 421 16.3.4 Composite Power System Reliability Evaluation 421 16.3.4.1 Reliability Indices at Load Points 422 16.3.4.2 Reliability Indices of the Bulk System 423 16.3.5 DMR Evaluation using Maximum Flow Method 424 16.3.6 Flow Chart of Optimal Reliability Criterion Determination 424 16.3.7 Case Study 425 16.3.7.1 Basic Input Data 425 16.3.7.2 Results of Construction Costs of Cases 428 16.3.7.3 Reliability Evaluation 428 16.3.8 Conclusion 431 17 Probabilistic Reliability-Based Expansion Planning with Wind Turbine Generators 433 17.1 Introduction 433 17.2 The Multistate Operation Model of WTG 434 17.2.1 WTG Power Output Model 434 17.2.2 Wind Speed Model 435 17.2.3 The Multistate Model of WTG using Normal ProbabilityDistribution Function 435 17.3 Reliability Evaluation of a Composite Power System with WTG 438 17.3.1 Reliability Indices at Load Buses 440 17.3.2 System Reliability Indices 440 17.4 Case Study 441 17.5 Conclusion 448 17.A Appendix 448 18 Probabilistic Reliability-Based HVDC Expansion Planning with Wind Turbine Generators 449 18.1 The Status of HVDC 449 18.2 HVDC Technology for Energy Efficiency and Grid Reliability 451 18.3 HVDC Impacts on Transmission System Reliabili ty 455 18.4 Case Study 455 References 465 Index 469

About the Author :
JAESEOK CHOI, PHD, is Full Professor at Gyeongsang National University and is a Fellow of the Korean Institute of Electrical Engineers. He is a senior member of the IEEE Power Engineering Society and participates in the Reliability, Risk, and Probability Applications Subcommittee. KWANG Y. LEE, PHD, is Professor and Chair of Electrical and Computer Engineering at Baylor University and a Life Fellow of IEEE. He is a member of the Intelligent Systems Subcommittee and Station Control Subcommittee of the IEEE Power and Energy Society.