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Computational Intelligence Applications In Smart Grids: Enabling Methodologies For Proactive And Self-organizing Power Systems [Hardback]

Edited by (Univ Of Sannio, Italy), Edited by (Brunel Univ, Uk)
  • Formāts: Hardback, 264 pages
  • Izdošanas datums: 24-Feb-2015
  • Izdevniecība: Imperial College Press
  • ISBN-10: 1783265876
  • ISBN-13: 9781783265879
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  • Hardback
  • Cena: 108,03 €
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  • Formāts: Hardback, 264 pages
  • Izdošanas datums: 24-Feb-2015
  • Izdevniecība: Imperial College Press
  • ISBN-10: 1783265876
  • ISBN-13: 9781783265879
Citas grāmatas par šo tēmu:
This book considers the emerging technologies and methodologies of the application of computational intelligence to smart grids.From a conceptual point of view, the smart grid is the convergence of information and operational technologies applied to the electric grid, allowing sustainable options to customers and improved levels of security. Smart grid technologies include advanced sensing systems, two-way high-speed communications, monitoring and enterprise analysis software, and related services used to obtain location-specific and real-time actionable data for the provision of enhanced services for both system operators (i.e. distribution automation, asset management, advanced metering infrastructure) and end-users (i.e. demand side management, demand response).In this context, a crucial issue is how to support the evolution of existing electrical grids from static hierarchal systems to self-organizing, highly scalable and pervasive networks. Modern trends are oriented toward the employment of computational intelligence techniques for deploying advanced control, protection and monitoring architectures that move away from the older centralized paradigm to systems distributed across the field with an increasing pervasion of intelligence devices. The large-scale deployment of computational intelligence technologies in smart grids could lead to a more efficient tasks distribution amongst energy resources and, consequently, to a sensible improvement of the electrical grid flexibility.
Preface vii
1 Wide-Area Monitoring, Protection and Control Needs, Applications, and Benefits 1(50)
Vahid Madani
Damir Novosel
Roger King
1.1 Introduction
1(1)
1.2 Grid Development History
2(13)
1.3 System Integrity Protection Schemes
15(5)
1.4 Synchronized Measurements
20(3)
1.5 Benefits and Roadmaps
23(2)
1.6 Selecting PMU Locations
25(10)
1.7 Integrated Phasor Measurement Network Subsystem and Energy Management System
35(5)
1.8 Proof of Concept (POC) Test Facility
40(4)
1.9 Data Mining and Cyber Security
44(1)
1.10 On-line Dimension Reduction of Synchrophasor Data
44(1)
1.11 Cyber Security Preparedness
45(1)
1.12 Conclusions
45(3)
References
48(3)
2 A MINLP Approach for Network Reconfiguration and Dispatch in Distribution Systems 51(26)
Sergio Bruno
Massimo La Scala
2.1 Introduction
51(3)
2.2 Optimal Reconfiguration Functions in Advanced DMS Scheme
54(8)
2.3 Test Results
62(11)
2.4 Conclusions
73(1)
References
74(3)
3 Multi-Objective Optimization Methods for Solving the Economic Emission Dispatch Problem 77(36)
Balusu Srinivasa Rao
Kanchapogu Vaisakh
3.1 Introduction
77(2)
3.2 Mathematical Formulation of the EED Problem
79(4)
3.3 Multi-Objective Optimization
83(4)
3.4 Particle Swarm Optimization (PSO)
87(5)
3.5 Differential Evolution (DE)
92(3)
3.6 Genetic Algorithm
95(4)
3.7 Clonal Selection Algorithm
99(3)
3.8 Simulation Results
102(4)
3.9 Conclusions
106(2)
References
108(5)
4 Voltage Security Assessment and Optimal Load Shedding Using the CBR Approach 113(28)
Narayan Prasad Patidar
4.1 Introduction
113(3)
4.2 Case-Based Reasoning
116(3)
4.3 Methodology
119(7)
4.4 Results and Discussion
126(11)
4.5 Conclusions
137(1)
References
138(3)
5 A Novel State Estimation Paradigm Based on Artificial Dynamic Models 141(24)
Francesco Torelli
Alfredo Vaccaro
5.1 Introduction
141(2)
5.2 Problem Formulation
143(3)
5.3 A Dynamic Computing Paradigm for SE
146(5)
5.4 Case Studies
151(9)
5.5 Conclusion
160(2)
References
162(3)
6 Improving Voltage Regulation in Smart Grids through Adaptive Fuzzy Agents 165(22)
Giovanni Acampora
Autilia Vitiello
6.1 Introduction
165(2)
6.2 Related Works
167(1)
6.3 Problem Formulation
168(1)
6.4 An Adaptive Fuzzy Multi-Agent System for Voltage Regulation
169(9)
6.5 Case Study and Experimental Results
178(5)
6.6 Conclusions
183(1)
References
184(3)
7 Smart Metering 187(54)
Daniele Gallo
Carmine Landi
Marco Landi
Mario Luiso
7.1 Introduction
187(7)
7.2 Research and Industrial Development
194(10)
7.3 Industrial Products
204(2)
7.4 Custom Solutions
206(29)
7.5 Final Remarks
235(1)
References
236(5)
Index 241