摘要
基于逐步最优化原理和遗传算法相结合 ,提出了水、火电力系统优化调度算法 .该方法主要优点在于占用内存少 ,不需要优化问题具有凸性、连续性和可微性 .与单点最优算法相比 ,该方法为多点寻优 ,单调收敛 ,可获得全局最优解和用于长、短期或实时优化调度 .
This paper presents a method (POGA) based on the principle of progressive optimality with a genetic algorithm for determining the optimal scheduling of a hydrothermal power system. Its main advantages lie in great robustness and less memory space. The usual. assumptions about problem convexity, continuity or existence of derivatives are no longer necessary. The algorithm uses a population of points at a time in contrast to the single point approach by traditional optimization methods. The convergence is monotonic and a global solution is obtained. The algorithm can be used in the generation of long term or short term scheduling activities in real time operation. A case study is presented.
出处
《水电能源科学》
2000年第2期69-72,共4页
Water Resources and Power
关键词
电力系统
水库
遗传算法
调度
power system
reservoir optimal scheduling
genetic algorithm
