电力市场环境下梯级水库发电优化调度的协进化粒子群算法应用研究  

Application of co-evolutionary particle swarm optimization to the optimized power generation operation of cascade reservoirs based on power market

作　　者：原文林[1] 吴泽宁[1] 黄强[2] 

机构地区：[1]郑州大学水利与环境学院,郑州450002 [2]西安理工大学水利水电学院,西安710048

出　　处：《水力发电学报》2011年第3期65-70,共6页Journal of Hydroelectric Engineering

基　　金：国家自然科学基金(50779053)

摘　　要：本文针对传统优化算法在求解高维、复杂的梯级水库发电优化调度时多约束条件难以处理、计算机时长、易陷入局部最优解等缺陷,结合电力市场环境下梯级水库发电优化调度的特点,提出了基于协进化的粒子群优化算法,并建立了相应罚因子的评价机制,在此基础上对协进化粒子群优化算法进行了改进。通过实际算例验证了该方法的合理性和可靠性,从而为市场环境下高维、复杂梯级水库发电优化调度提供了一种新的求解途径。The traditional optimization algorithms for high-dimensional and complex cascade reservoirs often meet difficulties in multi-constraint condition implementation,local optimal solution trapping and long computational time and have other defects.In this paper,a co-evolutionary particle swarm optimization algorithm is proposed and an evaluation mechanism of the penalty factors is established to improve the optimization algorithm.Application of this new method to the optimal operation of cascade reservoirs under the power market constraints shows its efficiency and reliability,thus it provides a new approach to solve the optimal operation problem for high-dimensional and complex cascade reservoirs.

关 键 词：电力市场 梯级水库 优化调度 协进化 粒子群算法 

分 类 号：TV7[水利工程—水利水电工程]