差分进化算法在三峡电站厂内经济运行中的应用

Application of Differential Evolution in In-plant Economical Operation of Three Gorges Hydropower Station

差分进化算法是一种基于群体进化的算法,具有记忆个体最优解和种群内信息共享的特点,即通过种群内个体间的合作与竞争来实现对优化问题的求解,其本质是一种基于实数编码的具有保优思想的贪婪遗传算法。本文将差分进化算法用于求解三峡电站厂内经济运行问题,同时又将该算法与标准遗传算法相比较,结果显示差分进化算法优化效果明显优于标准遗传算法,差分进化算法的全局的收敛性比标准遗传算法强,差分进化算法是求解大型水电站经济运行问题的有效方法。

Differential Evolution （DE） is an optimization algorithm based on evolution of the population, which has the ability of memorizing the best individuals and features of sharing information of population. Optimization problem can be solved by DE through cooperation and competi- tion of individuals in population, which essentially is a greedy genetic algorithm having the thought of memorizing the best solution based on real coding. DE was applied in solving the problem of load dispatch of units in the Three Gorges hydropower station. Meanwhile, the simulation results were compared with that of SGA. Differential Evolution obtains better simulation results than SGA which has a strong global convergent ability. Differential Evolution is an excellent method in solving in-plant economic operation problem of large-scale hydropower station with huge installation.