Ramp rate constrained unit commitment by improved priority list and augmented Lagrange Hopfield network

This paper proposes an improved priority list (IPL) and augmented Hopfield Lagrange neural network (ALH) for solving ramp rate constrained unit commitment (RUC) problem. The proposed IPL-ALH minimizes the total production cost subject to the power balance, 15 min spinning reserve response time const...

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Vydané v:	Electric power systems research Ročník 78; číslo 3; s. 291 - 301
Hlavní autori:	Dieu, Vo Ngoc, Ongsakul, Weerakorn
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier B.V 01.03.2008 Elsevier
Predmet:	Applied sciences Augmented Lagrange Hopfield neural network Electrical engineering. Electrical power engineering Electrical power engineering Exact sciences and technology Heuristic search Improved priority list Miscellaneous Operation. Load control. Reliability Power networks and lines Unit commitment Augmented Lagrange Hopfield neural network Improved priority list Heuristic search Unit commitment Dispatching problem Energy function Optimization method Power distribution planning Lagrange multiplier Relaxation method IEEE standards Lagrangian method Hopfield model Stopping time Priority Neural network Search algorithm Electrical network Heuristic method Production cost Economic aspect Economic impact Reliability Spinning Production unit
ISSN:	0378-7796, 1873-2046
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Abstract	This paper proposes an improved priority list (IPL) and augmented Hopfield Lagrange neural network (ALH) for solving ramp rate constrained unit commitment (RUC) problem. The proposed IPL-ALH minimizes the total production cost subject to the power balance, 15 min spinning reserve response time constraint, generation ramp limit constraints, and minimum up and down time constraints. The IPL is a priority list enhanced by a heuristic search algorithm based on the average production cost of units, and the ALH is a continuous Hopfield network whose energy function is based on augmented Lagrangian relaxation. The IPL is used to solve unit scheduling problem satisfying spinning reserve, minimum up and down time constraints, and the ALH is used to solve ramp rate constrained economic dispatch (RED) problem by minimizing the operation cost subject to the power balance and new generator operating frame limits. For hours with insufficient power due to ramp rate or 15 min spinning reserve response time constraints, repairing strategy based on heuristic search is used to satisfy the constraints. The proposed IPL-ALH is tested on the 26-unit IEEE reliability test system, 38-unit and 45-unit practical systems and compared to combined artificial neural network with heuristics and dynamic programming (ANN-DP), improved adaptive Lagrangian relaxation (ILR), constraint logic programming (CLP), fuzzy optimization (FO), matrix real coded genetic algorithm (MRCGA), absolutely stochastic simulated annealing (ASSA), and hybrid parallel repair genetic algorithm (HPRGA). The test results indicate that the IPL-ALH obtain less total costs and faster computational times than some other methods.
AbstractList	This paper proposes an improved priority list (IPL) and augmented Hopfield Lagrange neural network (ALH) for solving ramp rate constrained unit commitment (RUC) problem. The proposed IPL-ALH minimizes the total production cost subject to the power balance, 15 min spinning reserve response time constraint, generation ramp limit constraints, and minimum up and down time constraints. The IPL is a priority list enhanced by a heuristic search algorithm based on the average production cost of units, and the ALH is a continuous Hopfield network whose energy function is based on augmented Lagrangian relaxation. The IPL is used to solve unit scheduling problem satisfying spinning reserve, minimum up and down time constraints, and the ALH is used to solve ramp rate constrained economic dispatch (RED) problem by minimizing the operation cost subject to the power balance and new generator operating frame limits. For hours with insufficient power due to ramp rate or 15 min spinning reserve response time constraints, repairing strategy based on heuristic search is used to satisfy the constraints. The proposed IPL-ALH is tested on the 26-unit IEEE reliability test system, 38-unit and 45-unit practical systems and compared to combined artificial neural network with heuristics and dynamic programming (ANN-DP), improved adaptive Lagrangian relaxation (ILR), constraint logic programming (CLP), fuzzy optimization (FO), matrix real coded genetic algorithm (MRCGA), absolutely stochastic simulated annealing (ASSA), and hybrid parallel repair genetic algorithm (HPRGA). The test results indicate that the IPL-ALH obtain less total costs and faster computational times than some other methods.
Author	Ongsakul, Weerakorn Dieu, Vo Ngoc
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Keywords	Augmented Lagrange Hopfield neural network Improved priority list Heuristic search Unit commitment Dispatching problem Energy function Optimization method Power distribution planning Lagrange multiplier Relaxation method IEEE standards Lagrangian method Hopfield model Stopping time Priority Neural network Search algorithm Electrical network Heuristic method Production cost Economic aspect Economic impact Reliability Spinning Production unit
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SubjectTerms	Applied sciences Augmented Lagrange Hopfield neural network Electrical engineering. Electrical power engineering Electrical power engineering Exact sciences and technology Heuristic search Improved priority list Miscellaneous Operation. Load control. Reliability Power networks and lines Unit commitment
Title	Ramp rate constrained unit commitment by improved priority list and augmented Lagrange Hopfield network
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