Intro; Preface; Acknowledgments; Contents; About the Authors; Chapter 1: Introduction to Information Gap Decision Theory Method; 1.1 Motivation; 1.1.1 Application of IGDT for Modeling Uncertainties of Renewables, Demands, and Energy Tariffs in Systematic Analysis; 1.1.2 Risk-Aversion and Risk-Seeker Decisions in Energy and Reserve Markets Using IGDT; 1.2 Mathematical Modeling of Uncertain Parameter Using IGDT; 1.2.1 Objective Function; 1.2.2 Implementation Requirement; 1.2.3 Uncertainty Formulation; 1.2.4 Implementing Risk-Aversion and Robust Decision-Making Strategy
1.2.5 Implementing Risk-Seeker and Opportunistic Design Making Strategy1.3 Conclusion and Future Trend; References; Chapter 2: Information-Gap Decision Theory: Principles and Fundamentals; 2.1 Introduction; 2.1.1 Applications; 2.1.2 Summary; 2.2 Challenges of IGDT; 2.2.1 Pros of IGDT; 2.2.2 Cons of IGDT; 2.2.3 Future Development; 2.3 Statistics Related to Documents; 2.4 Information-Gap Decision Theory Modeling; 2.4.1 System Model; 2.4.2 Uncertainty Modeling; 2.4.2.1 Energy-Bound Model; 2.4.2.2 Envelope-Bound Model; 2.4.3 Performance Requirements; 2.4.3.1 Robustness Function
3.3.3 Limitations of gas and water networks3.3.4 Objective Function Without Uncertainty; 3.3.5 IGDT-Based Optimal Performance of Hub Energy; 3.3.5.1 Uncertainty Model; 3.3.5.2 Robustness Function; 3.3.5.3 Opportunity Function; 3.4 Simulation and Results; 3.4.1 Input Data; 3.4.2 Results; 3.4.2.1 Result of Robustness Function; 3.4.2.2 Result of Opportunity Function; 3.4.2.3 Uncertainty-Based Operation of Various Sections in the Hub System; 3.5 Conclusions; References; Chapter 4: Risk-Constrained Scheduling of a Solar Ice Harvesting System Using Information Gap Decision Theory; 4.1 Introduction
4.2 Proposed Methodology4.2.1 Ice Storage System; 4.2.2 Information Gap Decision Theory; 4.2.2.1 Objective Function; 4.2.2.2 Implementation Requirement; 4.2.2.3 Uncertainty Formulation; 4.2.2.4 Implementing Risk-Aversion and Robust Decision-Making Strategy; 4.2.2.5 Implementing Risk-Seeker and Opportunistic Design-Making Strategy; 4.3 Simulation Result and Discussions; 4.3.1 Ice Making System Without IGDT; 4.3.2 Ice Making Cycle with Risk-Averse and Risk-Seeker Decisions Using IGDT; 4.4 Concluding Remarks; References; Chapter 5: Robust Unit Commitment Using Information Gap Decision Theory
Profit MaximizationCost Minimization; 2.4.3.2 Opportunity Function; Profit Maximization; Cost Minimization; 2.5 Conclusion; References; Chapter 3: Optimization Framework Based on Information Gap Decision Theory for Optimal Operation of Multi-energy Systems; 3.1 Introduction; 3.1.1 Literature Review; 3.1.2 Contributions and Novelties; 3.1.3 Structure of Chapter; 3.2 Information Gap Decision Theory (IGDT); 3.2.1 System Model; 3.2.2 Operation Requirements; 3.2.3 Uncertainty Modeling; 3.3 Problem Formulation; 3.3.1 Electrical Limitations; 3.3.2 Thermal Limitations
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This book discusses the recent developments in robust optimization (RO) and information gap design theory (IGDT) methods and their application for the optimal planning and operation of electric energy systems. Chapters cover both theoretical background and applications to address common uncertainty factors such as load variation, power market price, and power generation of renewable energy sources. Case studies with real-world applications are included to help undergraduate and graduate students, researchers and engineers solve robust power and energy optimization problems and provide effective and promising solutions for the robust planning and operation of electric energy systems.
Springer Nature
com.springer.onix.9783030042967
Robust Optimal Planning and Operation of Electrical Energy Systems.