Dynamic vulnerability assessment and intelligent control for sustainable power systems / edited by Professor Jose L. Rueda Torres, Professor Francisco Gonzalez-Longatt.

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Material type: Text

TextPublisher: Hoboken, New Jersey : Wiley, 2018Distributor: [Piscataqay, New Jersey] : IEEE Xplore, [2018]Edition: First editionDescription: 1 PDF (448 pages)Content type:

text

Media type:

electronic

Carrier type:

online resource

ISBN:

9781119214984

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Genre/Form:

Electronic books.

Additional physical formats: Print version:: No titleDDC classification:

621.31/7

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Also available in print.

Contents:

The role of wide area monitoring systems in dynamic vulnerability assessment -- Steady state security -- Probabilistic indicators for the assessment of reliability and security of future power systems -- An enhanced WAMS-based power system oscillation analysis approach -- Pattern-recognition-based approach for dynamic vulnerability status prediction -- Performance-indicator-based real-time vulnerability assessment -- Challenges ahead risk-based AC optimal power flow under uncertainty for smart, sustainable power systems -- Modelling preventive and corrective actions using linear formulations -- Model-based predictive control for damping electromechanical oscillations in power systems -- Voltage stability enhancement by computational intelligence methods -- Knowledge-based primary and optimization-based secondary control of multi-terminal HVDC grids -- Model based voltage/reactive control in sustainable distribution systems -- Multi-agent-based approach for intelligent control of reactive power injection in transmission systems -- Operation of distribution systems within secure limits using real-time model predictive control -- Enhancement of transmission system voltage stability through local control of distribution networks -- Electric power network splitting considering frequency dynamics and transmission overloads constraints -- High-speed transmission line protection based on empirical orthogonal functions -- Implementation of a real phasor based vulnerability assessment and control scheme : the ecuadorian wampac system.

Summary: Identifying, assessing, and mitigating electric power grid vulnerabilities is a growing focus in short-term operational planning of power systems. Through illustrated application, this important guide surveys state-of-the-art methodologies for the assessment and enhancement of power system security in short-term operational planning and real-time operation. The methodologies employ advanced methods from probabilistic theory, data mining, artificial intelligence, and optimization, to provide knowledge-based support for monitoring, control (preventive and corrective), and decision making tasks. Key features: . Introduces behavioural recognition in wide-area monitoring and security constrained optimal power flow for intelligent control and protection and optimal grid management.. Provides in-depth understanding of risk-based reliability and security assessment, dynamic vulnerability assessment methods, supported by the underpinning mathematics.. Develops expertise in mitigation techniques using intelligent protection and control, controlled islanding, model predictive control, and multi-agent and distributed control systems.. Illustrates implementation in smart grid and self-healing applications with examples and real-world experience from the WAMPAC (Wide Area Monitoring Protection and Control) scheme. Dynamic Vulnerability Assessment and Intelligent Control for Sustainable Power Systems is a valuable reference for postgraduate students and researchers in power system stability as well as practicing engineers working in power system dynamics, control, and network operation and planning.

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Identifying, assessing, and mitigating electric power grid vulnerabilities is a growing focus in short-term operational planning of power systems. Through illustrated application, this important guide surveys state-of-the-art methodologies for the assessment and enhancement of power system security in short-term operational planning and real-time operation. The methodologies employ advanced methods from probabilistic theory, data mining, artificial intelligence, and optimization, to provide knowledge-based support for monitoring, control (preventive and corrective), and decision making tasks. Key features: . Introduces behavioural recognition in wide-area monitoring and security constrained optimal power flow for intelligent control and protection and optimal grid management.. Provides in-depth understanding of risk-based reliability and security assessment, dynamic vulnerability assessment methods, supported by the underpinning mathematics.. Develops expertise in mitigation techniques using intelligent protection and control, controlled islanding, model predictive control, and multi-agent and distributed control systems.. Illustrates implementation in smart grid and self-healing applications with examples and real-world experience from the WAMPAC (Wide Area Monitoring Protection and Control) scheme. Dynamic Vulnerability Assessment and Intelligent Control for Sustainable Power Systems is a valuable reference for postgraduate students and researchers in power system stability as well as practicing engineers working in power system dynamics, control, and network operation and planning.