Journal ArticleDOI
Adaptive Critic Design Based Neuro-Fuzzy Controller for a Static Compensator in a Multimachine Power System
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TLDR
In this article, a nonlinear optimal controller for a static compensator (STATCOM) connected to a power system, using artificial neural networks and fuzzy logic, is presented, which is capable of dealing with actual rather than deviation signals.Abstract:
This paper presents a novel nonlinear optimal controller for a static compensator (STATCOM) connected to a power system, using artificial neural networks and fuzzy logic. The action dependent heuristic dynamic programming, a member of the adaptive Critic designs family, is used for the design of the STATCOM neuro-fuzzy controller. This neuro-fuzzy controller provides optimal control based on reinforcement learning and approximate dynamic programming. Using a proportional-integrator approach the proposed controller is capable of dealing with actual rather than deviation signals. The STATCOM is connected to a multimachine power system. Two multimachine systems are considered in this study: a 10-bus system and a 45-bus network (a section of the Brazilian power system). Simulation results are provided to show that the proposed controller outperforms a conventional PI controller in large scale faults as well as small disturbancesread more
Citations
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Journal ArticleDOI
Adaptive Dynamic Programming: An Introduction
TL;DR: Some recent research trends within the field of adaptive/approximate dynamic programming (ADP), including the variations on the structure of ADP schemes, the development of ADPs algorithms and applications, and many recent papers have provided convergence analysis associated with the algorithms developed.
Journal ArticleDOI
Optimal Home Energy Management Under Dynamic Electrical and Thermal Constraints
Francesco De Angelis,Matteo Boaro,Danilo Fuselli,Stefano Squartini,Francesco Piazza,Qinglai Wei +5 more
TL;DR: An approach based on the mixed-integer linear programming paradigm, which is able to provide an optimal solution in terms of tasks power consumption and management of renewable resources, is developed and yields an optimal task scheduling under dynamic electrical constraints.
Journal ArticleDOI
Reinforcement Learning for Electric Power System Decision and Control: Past Considerations and Perspectives
TL;DR: In this paper, the authors review past and very recent research considerations in using reinforcement learning (RL) to solve electric power system decision and control problems, and analyse the perspectives of RL approaches in light of the emergence of new generation, communications, and instrumentation technologies currently in use, or available for future use, in power systems.
Journal ArticleDOI
Reinforcement learning algorithms with function approximation: Recent advances and applications
Xin Xu,Lei Zuo,Zhenhua Huang +2 more
TL;DR: A comprehensive survey is given on recent developments in RL algorithms with function approximation, including the convergence and feature representation of RL algorithms and their performance in several benchmark learning prediction and learning control tasks.
Journal ArticleDOI
An Event-Triggered Approach for Load Frequency Control With Supplementary ADP
TL;DR: In this paper, a novel ETC architecture design for load frequency control (LFC) with supplementary adaptive dynamic programming (ADP) is presented, where the primary proportional-integral (PI) controller uses different proportional and integral thresholds for updating the actions, while the supplementary ADP controller is updated in an aperiodic manner.
References
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Book
Neural Networks: A Comprehensive Foundation
TL;DR: Thorough, well-organized, and completely up to date, this book examines all the important aspects of this emerging technology, including the learning process, back-propagation learning, radial-basis function networks, self-organizing systems, modular networks, temporal processing and neurodynamics, and VLSI implementation of neural networks.
Journal ArticleDOI
Fuzzy identification of systems and its applications to modeling and control
T. Takagi,Michio Sugeno +1 more
TL;DR: A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented and two applications of the method to industrial processes are discussed: a water cleaning process and a converter in a steel-making process.
Book
Dynamic Programming and Optimal Control
TL;DR: The leading and most up-to-date textbook on the far-ranging algorithmic methododogy of Dynamic Programming, which can be used for optimal control, Markovian decision problems, planning and sequential decision making under uncertainty, and discrete/combinatorial optimization.
Book
Understanding FACTS: Concepts and Technology of Flexible AC Transmission Systems
TL;DR: The Flexible AC Transmission System (FACTS)—a new technology based on power electronics—offers an opportunity to enhance controllability, stability, and power transfer capability of ac transmission systems.