基于改进多目标海樽群算法的电力系统优化调度  

A improved multi-objective salp swarm algorithm for optimization dispatch of power system

作　　者：夏爱明 伍雪冬[1] Xia Aiming;Wu Xuedong(School of Electronic Information,Jiangsu University of Science and Technology,Zhenjiang 212000,Jiangsu,China)

机构地区：[1]江苏科技大学电子信息学院,江苏镇江212000

出　　处：《电测与仪表》2023年第7期77-82,共6页Electrical Measurement & Instrumentation

基　　金：国家自然科学基金资助项目(61671222)。

摘　　要：文中提出了一种新的多目标海樽群优化算法,将其与等式约束修正技术和可行解占优约束处理技术相结合,用于求解高度约束的电力系统环境经济优化调度问题。该算法采用高斯采样策略和变异操作增强其寻优性能;通过一种改进的基于动态拥挤距离的非支配排序方法获得分布均匀的帕累托最优前沿;应用模糊集理论为决策者提供最佳折中解。在IEEE 30节点6机组标准测试系统上进行算例仿真,并与其它优化算法进行了对比。结果表明,所提算法在求解电力系统环境经济调度问题时具有更好的优化效果。A novel multi-objective salp swarm optimization algorithm is proposed in this paper,which is combined with equality constraint modification technology and feasible solution dominant constraint processing technology to solve the highly constrained environmental economic optimization dispatch problem of power system.A Gauss sampling strategy and a mutation operator are adopted to enhance the optimization performance of the suggested algorithm;a non-dominated sorting method based on improved dynamic crowding distance is adopted to obtain a uniformly distributed Pareto-optimal front;a fuzzy set theory is applied to provide the best compromise solution for decision makers.Simulations are carried out on the IEEE 30-bus 6-unit standard test system and compared with other optimization algorithms.The results show that the proposed algorithm has better optimization effect in solving environmental economic dispatch problem of power system.

关 键 词：环境经济调度 多目标海樽群算法 约束处理方法 最佳折中解 

分 类 号：TM734[电气工程—电力系统及自动化]