应用粒子群优化算法求解市场环境下的电力系统动态经济调度问题

在竞争性的电力市场环境下,为了获得最大化的社会利润,提出了基于竞价机制的动态经济调度模型,该模型综合考虑了发电机组的爬坡约束、输电线路的容量约束和污染气体排放量的约束。针对该模型,提出了一种新的求解方法:粒子群优化算法(PSO)。算例的结果表明,PSO算法能够有效地得到一个高性能的优化调度结果

Dynamic economic dispatch using particle swarm optimization algorithm in electricity market

This paper proposes a bid-based dynamic economic dispatch model to maximize the social profit in a competitive electricity market. The model synthetically considers various constraints such as ramp rates, transmission line capacity and emission constraints to obtain a physically feasible resource scheduling. Particle swarm optimization (PSO) is applied to solve the problem. Numerical simulation results show that the proposed PSO method is capable of obtaining higher quality dispatch solution efficiently, furthermore, the algorithm is versatile and robust.