An improved PSO approach to shortterm economic dispatch of cascaded hydropower plants

Purpose The purpose of this paper is to establish the optimization model and solve the shortterm economic dispatch of cascaded hydroplants. Designmethodologyapproach An improved particle swarm optimization IPSO approach is proposed to solve the shortterm economic dispatch of cascaded hydroelectric p...

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Veröffentlicht in:Kybernetes 2010-08, Vol.39 (8), p.1359-1365
Hauptverfasser: Yuan, Yanbin, Yuan, Xiaohui
Format: Artikel
Sprache:eng
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Zusammenfassung:Purpose The purpose of this paper is to establish the optimization model and solve the shortterm economic dispatch of cascaded hydroplants. Designmethodologyapproach An improved particle swarm optimization IPSO approach is proposed to solve the shortterm economic dispatch of cascaded hydroelectric plants. The water transport delay time between connected reservoirs is taken into account and it is easy in dealing with the difficult hydraulic and power coupling constraints using the proposed method in practical cascaded hydroelectric plants operation. The feasibility of the proposed method is demonstrated for actual cascaded hydroelectric plant. Findings The simulation results show that this approach can prevent premature convergence to a high degree and keep a rapid convergence speed. Research limitationsimplications The optimal values of parameters in the proposed method are the main limitations where the method will be applied to the economic operation of the hydroplant. Practical implications The paper presents useful advice for shortterm economic operations of the hydroplant. A new optimization method to solve the shortterm optimal generation scheduling is proposed. The optimal generation power and water discharge during the whole dispatching time for hydroplant operation can be obtained. Originalityvalue The IPSO method is realized by maintaining high diversity of the swarm during the optimization process and preventing premature convergence.
ISSN:0368-492X
DOI:10.1108/03684921011063664