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