基于自适应粒子群算法的梯级小水电群优化调度研究
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摘要
针对以发电为主的梯级小水电群,以各水库的发电引用流量为决策变量,建立了以发电量最大为目标的梯级小水电群优化调度数学模型;设计了PSO算法和APSO算法的工程实现方法,具体包括编码设计、迭代方法设计以及惯性权重设计等;通过一个具有两库串联的梯级小水电群实例,将PSO算法和APSO算法的仿真寻优过程进行了比较,结果显示两种算法是有效的,并且APSO算法具有更强、更快的全局搜索能力;将APSO算法的仿真结果与同一条件下的GA算法的仿真结果进行了比较,结果显示APSO算法的仿真结果更优,更能充分利用水能资源。
Optimization operation model is established for a cascaded samll hydropower stations,task of which is usually generating electricity.The objective of the model is maximal energy output,and the decision-making variable of the model is discharge of the hydropower stations.Realization method of PSO and APSO is designed including the code design,iterative algorithm design and inertia weight design,etc.By simulation operation of PSO and APSO for a two-cascaded small reservoir system,the optimization of searching process is compared,the arithmetic results are proved to be valid,moreover,the searching ability of APSO is better than PSO.Compared with the operation result of GA under the same conditions,the operation result of APSO is the better.
Optimization operation model is established for a cascaded samll hydropower stations,task of which is usually generating electricity.The objective of the model is maximal energy output,and the decision-making variable of the model is discharge of the hydropower stations.Realization method of PSO and APSO is designed including the code design,iterative algorithm design and inertia weight design,etc.By simulation operation of PSO and APSO for a two-cascaded small reservoir system,the optimization of searching process is compared,the arithmetic results are proved to be valid,moreover,the searching ability of APSO is better than PSO.Compared with the operation result of GA under the same conditions,the operation result of APSO is the better.
引文
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[4]Parsopoulos K E,Vrahatis M N.Recent Approaches to Global Optimization Problems Through Particle Swarm Optimization[J].NaturalComputing,2002,1(2-3):235~306.
[5]谢晓锋,张文俊,杨之廉.微粒群算法综述[J].控制与决策,2003,18(2):129~134.
[6]袁晓辉,王乘,张勇传,等.粒子群优化算法在电力系统中的应用[J].电网技术,2004,28(19):14~19.
[7]李崇浩,纪昌明,等.改进微粒群算法及其在水库优化调度中的应用[J].中国农村水利水电,2006,(2):54~56.
[8]杨道辉,马光文,严秉忠,等.粒子群算法在水电站日优化调度中的应用[J].水力发电,2006,32(3):73~75.
[9]王万良,周慕逊,管秋,罗云霞,等.基于遗传算法的小水电站优化调度方法的研究与实践[J].水力发电学报,2005,24(3):6~11.
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