Optimization in the Energy Industry (eBook)

Preface 6
Contents 10
List of Contributors 13
Conventions and Abbreviations 19
Part I Challenges and Perspectives of Optimization in the Energy Industry 20
1 Current and Future Challenges for Production Planning Systems 21
1.1 Introduction 21
1.2 Production Planning – History and Present 22
1.3 The Coming Challenge: Handling Uncertainty 24
1.4 Requirements for Future Production Planning Systems 27
1.5 Conclusion 32
References 33
2 The Earth Warming Problem: Practical Modeling in Industrial Enterprises 34
2.1 Introduction 34
2.2 Management: What Changes will Affect the Planning Work? 35
2.3 Modeling: How to Make a Practical Model for the Earth Warming Problem? 36
2.4 Problems When Applying to Real World 39
2.5 Conclusion 40
References 40
Part II Deterministic Methods 41
3 Trading Hubs Construction for Electricity Markets 42
3.1 Introduction 42
3.2 Hedging in the Electricity Markets and Hubs Usage 44
3.3 Problem Formulations 51
3.4 Heuristics for Construction of Given Number of Hubs 57
3.5 Solving the Single Hub Selection Problem 62
3.6 Conclusion 67
References 67
Appendix 69
4 A Decision Support System to Analyze the Influence of Distributed Generation in Energy Distribution Networks 71
4.1 Introduction 71
4.2 Methodology 73
4.3 Simulation Study 76
4.4 Computational Results 78
4.5 Conclusions 87
References 88
5 New Effective Methods of Mathematical Programming and Their Applications to Energy Problems 90
5.1 Introduction 90
5.2 Polynomial-Time Algorithms in Convex Programming 91
5.3 Solution of Energy Problems by Polynomial-Time Algorithms 120
5.4 Conclusion 138
References 139
6 Improving Combustion Performance by Online Learning 142
6.1 Introduction 142
6.2 High Dimensional Combustion Data Streams 145
6.3 Virtual Age of a Boiler 146
6.4 Stream Clustering 147
6.5 Determining the Best Centroid 150
6.6 Industrial Case Study 151
6.7 Conclusion 157
References 157
7 Critical States of Nuclear Power Plant Reactors and Bilinear Modeling 160
7.1 Introduction 160
7.2 System-Theoretical Description of Nuclear Reactor Dynamics 162
7.3 Bilinear Logic-Dynamical Models 163
7.4 Versal Models of Critical States 165
7.5 Bilinear Model of the Thermal-Hydraulic Systems 170
7.6 Bilinear Simulation of Reactor Core Accidents 172
7.7 Conclusions 174
References 175
8 Mixed-Integer Optimization for Polygeneration Energy Systems Design 177
8.1 An Overview of Polygeneration Energy Systems 177
8.2 Studies and Existing Problems 181
8.3 Superstructure Representation 182
8.4 Mathematical Model 185
8.5 A Polygeneration Plant for Electricity and Methanol – A Case Study 193
8.6 Conclusions 197
References 198
Appendix A – Nomenclature 199
9 Optimization of the Design and Partial-Load Operation of Power Plants Using Mixed-Integer Nonlinear Programming 202
9.1 Introduction 202
9.2 Model of a Cogeneration Power Plant 204
9.3 Solution of the MINLP 212
9.4 Optimization Results 218
9.5 Conclusions 224
References 225
10 Optimally Running a Biomass-Based Energy Production Process 230
10.1 Introduction 230
10.2 Modeling the Production Process 231
10.3 A Real-World Application 235
10.4 Model Improvements 238
10.5 Conclusion 240
References 241
11 Mathematical Modeling of Batch, Single Stage, Leach Bed Anaerobic Digestion of Organic Fraction of Municipal Solid Waste 242
11.1 Introduction 243
11.2 Characteristics of Municipal Solid Waste 245
11.3 Metabolic Processes in Anaerobic Digestion 247
11.4 Model Description 249
11.5 Selection of Parameters 259
11.6 Model Implementation and Simulation 264
11.7 Model Validation 266
11.8 Model Application 275
11.9 Conclusions 277
References 278
Appendix 281
12 Spatially Differentiated Trade of Permits for Multipollutant Electric Power Supply Chains 285
12.1 Introduction 285
12.2 The Electric Power Supply Chain Network Model with Multipollutant Tradable Permits 287
12.3 Algorithm and Examples 298
12.4 Summary and Conclusions 301
References 302
13 Applications of TRUST-TECH Methodology in Optimal Power Flow of Power Systems 305
13.1 Introduction 305
13.2 Optimal Power Flow 308
13.3 Overview of TRUST-TECH Methodology 309
13.4 Computational and Analytical Basis 312
13.5 Active-Set Quotient Gradient System 315
13.6 Stage II – IPM 318
13.7 Numerical Studies 320
13.8 Concluding Remarks 323
References 324
Part III Stochastic Programming: Methods and Applications 327
14 Scenario Tree Approximation and Risk Aversion Strategies for Stochastic Optimization of Electricity Production and Trading 328
14.1 Introduction 328
14.2 Mathematical Framework 330
14.3 Stability of Multistage Problems 331
14.4 Construction of Scenario Trees 335
14.5 Polyhedral Risk Functionals 340
14.6 Case Study 345
14.7 Conclusion 351
References 351
15 Optimization of Dispersed Energy Supply – Stochastic Programming with Recombining Scenario Trees 354
15.1 Introduction 354
15.2 Model Description 355
15.3 Decomposition Using Recombining Scenario Trees 359
15.4 Case Study 365
15.5 Numerical Results 365
15.6 Conclusions and Outlook 369
References 370
16 Stochastic Model of the German Electricity System 372
16.1 Introduction 372
16.2 Model 373
16.3 Scenarios 377
16.4 Conclusion and Outlook 391
References 392
17 Optimization of Risk Management Problems in Generation and Trading Planning 393
17.1 Introduction and Motivation 394
17.2 Analysis and Modeling 395
17.3 Optimization Method 402
17.4 Exemplary Results 408
17.5 Conclusions 412
References 413
18 Optimization Methods Application to Optimal Power Flow in Electric Power Systems 415
18.1 Introduction 415
18.2 Overview of Optimal Power Flow 416
18.3 Stochastic Methods for OPF 422
18.4 Numerical Application 432
18.5 Concluding Remarks 438
References 439
19 WILMAR: A Stochastic Programming Tool to Analyze the Large-Scale Integration of Wind Energy 443
19.1 Introduction 443
19.2 Existing Modeling Approaches 445
19.3 Markets and Unit Commitment 445
19.4 Key Model Equations 446
19.5 Key Model Features 453
19.6 Application 457
19.7 Final Remarks 461
References 461
Appendix: Symbols Used 463
Part IV Stochastic Programming in Pricing 465
20 Clean Valuation with Regard to EU Emission Trading 466
20.1 Introduction 466
20.2 Market Developments and Observations 468
20.3 Clean Valuation in a Multicommodity Context 471
20.4 Modeling Investment Planning and Power Generation 477
20.5 Conclusions 486
References 487
21 Efficient Stochastic Programming Techniques for Electricity Swing Options 489
21.1 Introduction 489
21.2 General Valuation Problem 491
21.3 Concrete Valuation Problem 497
21.4 Computational Experiments 500
21.5 Computational Results 501
21.6 Discussion 505
21.7 Conclusion 508
References 508
22 Delta-Hedging a Hydropower Plant Using Stochastic Programming 511
22.1 Introduction 511
22.2 The Nordic Power Market 512
22.3 Hedging of Power Production 514
22.4 Production Models – Theory and Implementation 516
22.5 Results 522
22.6 Discussion 525
22.7 Conclusion 526
References 527
Index 529