An improved PSO approach to short-term economic dispatch of cascaded hydropower plants
An improved PSO approach to short-term economic dispatch of cascaded hydropower plants
复制标题
梯级水电站短期经济调度的改进PSO方法
DOI：
10.1108/03684921011063664
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发表时间：
2010-01-01
期刊：
影响因子：
2.5
通讯作者：
Yuan, Xiaohui
中科院分区：
文献类型：
--
作者：
Yuan, Yanbin;Yuan, Xiaohui
目的--建立梯级水电站短期经济调度优化模型并求解。设计/方法/途径--提出一种改进的粒子群优化算法（IPSO）求解梯级水电站短期经济调度。该方法考虑了梯级水库间的输水延迟时间，易于处理梯级水电站实际运行中难以处理的水力和功率耦合约束。结果-仿真结果表明，该方法可以防止早熟收敛到很高的程度，并保持快速的收敛速度。研究限制/影响-在所提出的方法中的参数的最优值是主要的限制，该方法将被应用于水电站的经济运行。工厂。实际影响-本文提出了有益的建议，短期经济运行的水电厂。提出了一种新的求解短期发电优化调度问题的优化方法。在整个调度时间为水电厂operation.Originality/值-IPSO方法是通过保持高多样性的群体在优化过程中，防止过早收敛的最佳发电功率和水排放。
Purpose - The purpose of this paper is to establish the optimization model and solve the short-term economic dispatch of cascaded hydro-plants.Design/methodology/approach - An improved particle swarm optimization (IPSO) approach is proposed to solve the short-term 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 limitations/implications - 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 hydro-plant.Practical implications The paper presents useful advice for short-term economic operations of the hydro-plant. A new optimization method to solve the short-term optimal generation scheduling is proposed. The optimal generation power and water discharge during the whole dispatching time for hydro-plant operation can be obtained.Originality/value - The IPSO method is realized by maintaining high diversity of the swarm during the optimization process and preventing premature convergence.