基于新型分数阶粒子群优化算法的分布式电源选址定容  

Distributed Generation’s Location and Capacity Optimization Using a Novel Fractional Particle Swarm Algorithm

作　　者：张江[1] 王福绵 ZHANG Jiang;WANG Fu-mian(School of Computer Science and Artificial Intelligence,Hefei Normal University,Hefei 230601,China;College of Energy and Electrical Engineering,Hohai University,Nanjing 211100,China)

机构地区：[1]合肥师范学院计算机与人工智能学院,安徽合肥230601 [2]河海大学能源与电气学院,江苏南京211100

出　　处：《安徽师范大学学报（自然科学版）》2023年第5期425-432,共8页Journal of Anhui Normal University(Natural Science)

基　　金：国家自然科学基金项目(51777058).

摘　　要：大规模分布式电源并网带来巨大的经济效益和环境效益的同时也会对电网的稳定性造成威胁。为使配电网可以消纳更高比例的分布式电源,需要对分布式电源接入电网的位置及容量进行优化。首先,建立了风速、光照强度、负荷的不确定性分析模型,构建了以年综合费用最低为目标函数的分布式电源选址定容规划模型;然后,提出新型分数阶粒子群优化算法,测试了算法在复杂优化问题上的性能。最后,IEEE-33节点配电网算例的仿真结果验证了所建立模型的合理性与所提算法的有效性。Large-scale distributed generation grid connection brings huge economic and environmental benefits,but also threatens the stability of the grid.To undertake a higher penetration of distributed generation,it is necessary to optimize the location and capacity of the distributed generation connected to the grid.Firstly,the uncertainty analysis model of wind speed,light intensity,and load is established.Then,a planning model with the lowest annual comprehensive cost as the objective function is constructed.Secondly,a novel fractional particle swarm optimization algorithm is proposed,and the performance of the algorithm on complex optimization problems is tested.Finally,the simulation results of the IEEE-33 distribution network example verify the rationality of the established model and the effectiveness of the proposed algorithm.

关 键 词：不确定性 机会约束 选址定容 分数阶粒子群优化 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]