Optimal operation of multi-reservoir system by multi-elite guide particle swarm optimization

► A multi-elite guide particle swarm optimization is proposed in this paper. ► Archive set is employed to provide multiple flying directions for particles. ► An effective constrain handling method is proposed to deal with OMRS problem. ► Simulation results prove MGPSO get better solutions with small...

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Veröffentlicht in:International journal of electrical power & energy systems 2013-06, Vol.48, p.58-68
Hauptverfasser: Zhang, Rui, Zhou, Jianzhong, Ouyang, Shuo, Wang, Xuemin, Zhang, Huifeng
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container_title International journal of electrical power & energy systems
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creator Zhang, Rui
Zhou, Jianzhong
Ouyang, Shuo
Wang, Xuemin
Zhang, Huifeng
description ► A multi-elite guide particle swarm optimization is proposed in this paper. ► Archive set is employed to provide multiple flying directions for particles. ► An effective constrain handling method is proposed to deal with OMRS problem. ► Simulation results prove MGPSO get better solutions with smaller energy deficit. With increasingly scarce of fossil fuel resources required for energy demand, hydropower has become one of the most important energy resources. As a renewable and sustainable energy, hydropower system has developed rapidly during recent decades. The unprecedented rate of expansion and development scale of hydropower has posed a challenge to the operation of multi-reservoir system (OMRS). The optimal operation of multi-reservoir system is a large-scaled, non-linear and multi-stage problem which subject to a series of hydraulic constraints. The main objective of OMRS is to find out the optimal hourly water discharge rate of each hydro station in the multi-reservoir system to minimize the power deficit and distribute the uniformly deficit if any. In order to solve OMRS problem effectively, in this paper, a multi-elite guide particle swarm optimization (MGPSO) is proposed by introducing archive set into standard particle swarm optimization. External archive set which can preserve elite solutions along the evolution process is employed to provide multi-elite flying directions for particles. Meanwhile, an effective constrain handling method is proposed to handle the operational constraints of OMRS problem. This proposed method is applied to a multi-reservoir system consisting of 10 cascaded hydro plants for case study. Compared with several previous methods, the simulation results of MGPSO can get better solutions with smaller energy deficit, which proves it is an alternative method to deal with OMRS problem.
doi_str_mv 10.1016/j.ijepes.2012.11.031
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With increasingly scarce of fossil fuel resources required for energy demand, hydropower has become one of the most important energy resources. As a renewable and sustainable energy, hydropower system has developed rapidly during recent decades. The unprecedented rate of expansion and development scale of hydropower has posed a challenge to the operation of multi-reservoir system (OMRS). The optimal operation of multi-reservoir system is a large-scaled, non-linear and multi-stage problem which subject to a series of hydraulic constraints. The main objective of OMRS is to find out the optimal hourly water discharge rate of each hydro station in the multi-reservoir system to minimize the power deficit and distribute the uniformly deficit if any. In order to solve OMRS problem effectively, in this paper, a multi-elite guide particle swarm optimization (MGPSO) is proposed by introducing archive set into standard particle swarm optimization. External archive set which can preserve elite solutions along the evolution process is employed to provide multi-elite flying directions for particles. Meanwhile, an effective constrain handling method is proposed to handle the operational constraints of OMRS problem. This proposed method is applied to a multi-reservoir system consisting of 10 cascaded hydro plants for case study. Compared with several previous methods, the simulation results of MGPSO can get better solutions with smaller energy deficit, which proves it is an alternative method to deal with OMRS problem.</description><identifier>ISSN: 0142-0615</identifier><identifier>EISSN: 1879-3517</identifier><identifier>DOI: 10.1016/j.ijepes.2012.11.031</identifier><identifier>CODEN: IEPSDC</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Applied sciences ; Constraint handling ; Electric power plants ; Electrical engineering. 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With increasingly scarce of fossil fuel resources required for energy demand, hydropower has become one of the most important energy resources. As a renewable and sustainable energy, hydropower system has developed rapidly during recent decades. The unprecedented rate of expansion and development scale of hydropower has posed a challenge to the operation of multi-reservoir system (OMRS). The optimal operation of multi-reservoir system is a large-scaled, non-linear and multi-stage problem which subject to a series of hydraulic constraints. The main objective of OMRS is to find out the optimal hourly water discharge rate of each hydro station in the multi-reservoir system to minimize the power deficit and distribute the uniformly deficit if any. In order to solve OMRS problem effectively, in this paper, a multi-elite guide particle swarm optimization (MGPSO) is proposed by introducing archive set into standard particle swarm optimization. External archive set which can preserve elite solutions along the evolution process is employed to provide multi-elite flying directions for particles. Meanwhile, an effective constrain handling method is proposed to handle the operational constraints of OMRS problem. This proposed method is applied to a multi-reservoir system consisting of 10 cascaded hydro plants for case study. Compared with several previous methods, the simulation results of MGPSO can get better solutions with smaller energy deficit, which proves it is an alternative method to deal with OMRS problem.</description><subject>Applied sciences</subject><subject>Constraint handling</subject><subject>Electric power plants</subject><subject>Electrical engineering. 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subjects Applied sciences
Constraint handling
Electric power plants
Electrical engineering. Electrical power engineering
Electrical power engineering
Exact sciences and technology
Hydroelectric power plants
Hydropower generation
Multi-elite guide
Multi-reservoir system
Optimal operation
Particle swarm optimization
title Optimal operation of multi-reservoir system by multi-elite guide particle swarm optimization
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