Distributed Linear Programming Models in a Smart Grid

Name: Distributed Linear Programming Models in a Smart Grid
Author: Prakash Ranganathan

Gebonden Engels 2017 9783319526164

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This book showcases the strengths of Linear Programming models for Cyber Physical Systems (CPS), such as the Smart Grids. Cyber-Physical Systems (CPS) consist of computational components interconnected by computer networks that monitor and control switched physical entities interconnected by physical infrastructures. A fundamental challenge in the design and analysis of CPS is the lack of understanding in formulating constraints for complex networks. We address this challenge by employing collection of Linear programming solvers that models the constraints of sub-systems and micro grids in a distributed fashion.
The book can be treated as a useful resource to adaptively schedule resource transfers between nodes in a smart power grid. In addition, the feasibility conditions and constraints outlined in the book will enable in reaching optimal values that can help maintain the stability of both the computer network and the physical systems. It details the collection of optimization methods that are reliable for electric-utilities to use for resource scheduling, and optimizing their existing systems or sub-systems. The authors answer to key questions on ways to optimally allocate resources during outages, and contingency cases (e.g., line failures, and/or circuit breaker failures), how to design de-centralized methods for carrying out tasks using decomposition models; and how to quantify un-certainty and make decisions in the event of grid failures.

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ISBN13:9783319526164

Taal:Engels

Bindwijze:gebonden

Uitgever:Springer International Publishing

Serie:Power Electronics and Power Systems

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<div>Abstract</div><div>Acknowledgments</div><div>List of Tables </div><div>List of Figures</div><div>List of Abbreviations</div><div>Chapter 1. Introduction</div><div> Objectives of the Book</div><div>Chapter 2. Literature Review</div><div> Linear Programming in Practice</div><div> Development of a Distributed Linear Programming Model</div><div>Chapter 3. Energy Reallocation in a Smart Grid</div><div> Introduction</div><div> Problem Statement</div><div> Physical Infrastructure Issues</div><div> Smart Grid Modeling</div><div> Smart Grid Simulation</div><div> Conclusions</div><div>Chapter 4.  Resource Allocation Using Branch and Bound</div><div> Distributed Energy Resources in Smart Grid</div><div>        Related Work</div><div>        Assigning DER to RUA Formulation</div><div> Branch-and-Bound (BB) Strategy</div><div> Conclusions</div><div>Chapter 5. Resource Allocation Using DW Decomposition</div><div> Why Decompose?</div> Objective Function and Illustration of DW Algorithm</div><div> LP Formulation of the IEEE 14-BUS System</div><div> Decomposing the IEEE 14-Bus System into Two Regions</div><div> Formulating the IEEE 30-Bus System’s Constraints</div><div>Chapter 6. Implementation and Testing of DW Procedure</div><div> Overview of Modeling in AMPL and Results</div><div> Lagrangian Relaxation Procedure</div><div> Computational Results of IEEE Bus System</div><div>Chapter 7. Remarks on DW</div><div>Chapter 8. A Linear Classifier for Decision Support in a Smart Grid</div><div>Chapter 9. PMU Placement Problem Using Linear Programming</div><div>Chapter 10. Unbiased Optimum Power Flow in Power Systems Using Linear Programming with Wind Generation Models</div><div>Chapter 11. Smart Grid Optimization Using a Capacitated Transshipment Problem Solver</div><div>Chapter 12. Decomposition of Microgrids in Large Scale Electric Test Beds for Economic Dispatch Optimization</div>References</div><div><br></div>

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