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Intelligent Coordinated Control of Complex Uncertain Systems for Power Distribution and Network Reliability discusses the important topics revolving around the control of complex uncertain systems using the intelligent coordination control mechanism, a topic that has become the research focus of current control and computer fields. The book provides theoretical guidance for power distribution network reliability analysis, focusing on practical problems and algorithms within the field.
- Provides effective solutions for complex control systems
- Presents theoretical guidance for power distribution network reliability analysis
- Focuses on practical problems and algorithms
The book will be an essential reading material for practicing engineers, researchers, technicians, and advanced undergraduate and graduate students in electrical power industries.
- Chapter 1: Introduction
- 1.1. Background and significance of intelligent coordinated control of complex uncertainty system
- 1.2. Background of distribution network security control
- 1.3. Relationship between the safety and stability of distribution network and vulnerability of the system
- 1.4. Research status of power grid security control
- 1.5. Main content of the book
- Chapter 2: Theoretical Basis for Intelligent Coordinated Control
- 2.1. Multiagent system
- 2.2. Reinforcement learning of multiagent system
- 2.3. Ant colony algorithm
- 2.4. BP neural network
- 2.5. Particle swarm optimization
- Chapter 3: Power Grid Vulnerability Early-Warning Indicators
- 3.1. Introduction
- 3.2. Power grid vulnerability and influence factors
- 3.3. Early-warning indicators of power grid safety
- 3.4. Advantages and disadvantages of each indicator and scope of application
- Chapter 4: Derivation of Distribution Network Vulnerability Indicators Based on Voltage Stability
- 4.1. Introduction
- 4.2. Overview of voltage stability
- 4.3. Evaluation indicator L of voltage stability in the power grid
- 4.4. The model for indicator calculation
- 4.5. Example analysis
- Chapter 5: Vulnerability Assessment of the Distribution Network Based on Quantum Multiagent
- 5.1. Introduction
- 5.2. Reinforcement learning of the multiagent system based on quantum theory
- 5.3. The design of distribution network vulnerability analysis system based on Q-MAS
- 5.4. The realization of primary vulnerability assessment function
- 5.5. The realization of comprehensive vulnerability assessment function of the distribution network
- Chapter 6: Low-Voltage Risk Assessment of the Distribution Network Based on Vulnerability Information Coordination Among Buses
- 6.1. Introduction
- 6.2. Low-voltage risk analysis of isolated buses
- 6.3. Quantitative calculation of interrelationship of vulnerabilities between buses
- 6.4. Comprehensive indicator of low-voltage vulnerability in the distribution network
- 6.5. Example analysis
- Chapter 7: Direction-Coordinating Based Ant Colony Algorithm and its Application in Distribution Network Reconfiguration
- 7.1. Introduction
- 7.2. Improved ant colony algorithm based on directional pheromone
- 7.3. Application of direction-coordinating ant colony algorithm in distribution network reconfiguration
- Chapter 8: Optimization and Solution of Unit Maintenance Scheduling Models
- 8.1. Introduction
- 8.2. Establishing the optimization model of unit maintenance plan
- 8.3. The solution of unit maintenance plan based on improved ant colony algorithm
- 8.4. Example analysis
- No. of pages:
- © Elsevier 2016
- 19th November 2015
- Paperback ISBN:
- eBook ISBN:
Xiangping Meng is a full professor at school of electrical and information engineering, the Changchun Institute of Technology. Also, she is a research professor and director at Jilin province universities distribution automation engineering research center. Her areas of research are intelligent control, power system optimal operation and control, power distribution network reliability control, power system voltage stability, power quality analysis and control. She was elected as the Jilin provincial high-level experts, the Jilin provincial outstanding young scholar, and the Changchun outstanding contributions experts.
School of Electrical and Information Engineering Changchun Institute of Technology, China
Associate Professor, College of Information Science and Engineering, Shenyang Ligong University, China
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