Guo / Fang / Khargonekar Stochastic Optimization for Distributed Energy Resources in Smart Grids

1. Auflage 2017
ISBN: 978-3-319-59529-0
Verlag: Springer Nature Switzerland
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 84 Seiten

Reihe: SpringerBriefs in Electrical and Computer Engineering

This brief focuses on stochastic energy optimization for distributed energy resources in smart grids. Along with a review of drivers and recent developments towards distributed energy resources, this brief presents research challenges of integrating millions of distributed energy resources into the grid. The brief then proposes a novel three-level hierarchical architecture for effectively integrating distributed energy resources into smart grids. Under the proposed hierarchical architecture, distributed energy resource management algorithms at the three levels (i.e., smart home, smart neighborhood, and smart microgrid) are developed in this brief based on stochastic optimization that can handle the involved uncertainties in the system.

Autoren/Hrsg.

Guo, Yuanxiong

Fang, Yuguang

Khargonekar, Pramod P.

Inhaltsverzeichnis

1;Preface;6
2;Contents;8
3;Acronyms;10
4;1 Hierarchical Architecture for Distributed Energy Resource Management;11
4.1;1.1 Introduction to DERs;11
4.2;1.2 Research Challenges for Integrating DERs;12
4.3;1.3 A Novel Hierarchical Architecture for DER Management;13
4.4;1.4 Related Work;14
4.5;References;15
5;2 Optimal Energy Management for Smart Homes;19
5.1;2.1 System Model;19
5.1.1;2.1.1 Renewable Energy Generation;19
5.1.2;2.1.2 Energy Storage;20
5.1.3;2.1.3 Electricity Market;21
5.1.4;2.1.4 Control Objective;21
5.2;2.2 Inelastic Energy Demand;22
5.2.1;2.2.1 Relaxed Problem;23
5.2.2;2.2.2 Our Proposed Algorithm;25
5.2.3;2.2.3 Algorithmic Properties;26
5.3;2.3 Elastic Energy Demand;27
5.3.1;2.3.1 Relaxed Problem;29
5.3.2;2.3.2 Delay-Aware Virtual Queue;30
5.3.3;2.3.3 Our Proposed Algorithm;30
5.3.4;2.3.4 Algorithmic Properties;31
5.4;2.4 Performance Evaluation;33
5.4.1;2.4.1 Simulation Setup;33
5.4.2;2.4.2 Results and Analysis;34
5.5;Appendix;36
5.5.1;Proof of Theorem 2.1;36
5.5.2;Proof of Lemma 3.1;39
5.5.3;Proof of Theorem 2.2;40
5.6;References;44
6;3 Decentralized Coordination of Energy Consumption for Smart Neighborhoods;45
6.1;3.1 System Model;45
6.1.1;3.1.1 Load Serving Entity;45
6.1.2;3.1.2 Energy Loads;46
6.1.3;3.1.3 Energy Storage;47
6.1.4;3.1.4 Renewable Distributed Generation;48
6.2;3.2 Problem Formulation;49
6.3;3.3 Online Distributed Algorithm;50
6.3.1;3.3.1 Relaxed Problem;50
6.3.2;3.3.2 Delay-Aware Virtual Queue;51
6.3.3;3.3.3 The Lyapunov Approach;52
6.3.4;3.3.4 Distributed Algorithm;55
6.4;3.4 Performance Analysis;57
6.5;3.5 Performance Evaluation;60
6.5.1;3.5.1 Simulation Setup;60
6.5.2;3.5.2 Results and Analysis;61
6.6;Appendix;64
6.6.1;The Worst-case Delay for Buffered Elastic Loads;64
6.7;References;65
7;4 Risk-Constrained Optimal Energy Management for SmartMicrogrids;66
7.1;4.1 System Model;66
7.1.1;4.1.1 Combined Heat and Power;67
7.1.2;4.1.2 Deferrable Load;69
7.1.3;4.1.3 Electrical and Thermal Storage;69
7.1.4;4.1.4 Heat Supply and Balance;70
7.1.4.1;4.1.4.1 Linearized Power Flow Equations;71
7.1.4.2;4.1.4.2 Network Constraints;72
7.1.5;4.1.5 Electricity Market;72
7.2;4.2 Problem Formulation;73
7.2.1;4.2.1 Conditional Value at Risk;73
7.2.2;4.2.2 Objective Function;74
7.3;4.3 Solution Approach;75
7.4;4.4 Case Study;76
7.4.1;4.4.1 Numerical Settings;76
7.4.2;4.4.2 Simulation Results;77
7.4.2.1;4.4.2.1 Stochastic Approach Versus Deterministic Approach;77
7.4.2.2;4.4.2.2 Expected Operating Cost and CVaR;78
7.4.2.3;4.4.2.3 Voltage Regulation Tests;78
7.4.2.4;4.4.2.4 Sensitivity Analysis;79
7.5;References;81
8;5 Conclusion;83
8.1;5.1 Concluding Remarks;83
8.2;5.2 Future Work;84