考虑系统频率调节约束的电力系统动态优化调度

Dynamic optimal dispatch of power system considering system frequency regulation constraints

我国高比例可再生能源不断并网,增加了电力系统运行的不确定程度,传统电力系统安全运行面临更多挑战。为应对实际负荷的快速波动,文中构建了充分考虑系统频率调节约束的动态经济调度模型,使系统的爬坡速率满足实际连续波动的负荷需求,保障电力系统安全、可靠、经济运行。针对传统粒子群算法存在早熟收敛等问题,采用一种基于混沌的随机选取邻居的多智能体粒子群算法进行求解,通过随机邻居选择使每个多智能体获取更多有效信息,同时利用混沌系统的随机性、遍历性来优化搜索,避免陷入局部最优,提升算法全局寻优能力。通过对仿真算例进行分析,验证了该模型的有效性及算法的优越性。

The continuous grid connection of a high proportion of renewable energy in China increases the uncertainty of power system operation,and the safe operation of traditional power system faces more challenges.In order to deal with the rapid fluctuation of the actual load,this paper constructs a dynamic economic scheduling model fully considering the system frequency regulation constraint,so that the system climbing rate can meet the actual continuous fluctuating load demand and ensure the safe,reliable and economic operation of the power system.Aiming at the problems of premature convergence in the traditional particle swarm optimization algorithm,a multi-agent particle swarm optimization algorithm based on chaos is used to solve it.Through random neighbor selection,each multi-agent can obtain more effective information.At the same time,the randomness and ergodicityof chaotic system are used to optimize the search,avoiding fall into local optimization and improve the global optimization ability of the algorithm.Through the analysis of simulation examples,the effectiveness of the model and the superiority of the algorithm are verified.