BPSO优化算法在含DG配电网中的故障诊断研究

针对含分布式电源(distributed generation,DG)的配电网故障检测,传统的故障检测方法容易出现检测精度低、适用性差、容错力低等问题;为此,提出了一种改进的二进制粒子群算法(binary particle swarm optimization,BPSO)进行故障检测,该算法是在BPSO算法的基础上,重新对自适应度值进行定义确保种群寻找到最为准确的最优解,解决BPSO算法容易陷入"早熟"的情况;通过IEEE33节点进行仿真分析,实验结果表明:采用改进的BPSO算法可以有效对故障区段进行定位,验证了改进的BPSO算法的有效性和正确性;同时,当存在信息畸变时,改进的BPSO算法比一般算法具有更强的容错能力。

BPSO Optimization Algorithm in distributed Distribution network with DG fault diagnosis research

Abstract: For fault detection of distribution network including Distributed Generation (DG), traditional fault detection methods are prone to problems such as low detection accuracy, poor applicability and low fault tolerance. An improved Binary Particle Swarm Optimization (BPSO) was proposed for fault detection. Based on THE BPSO algorithm, the self-adaptive value was redefined to ensure that the population could find the most accurate optimal solution and solve the problem that BPSO algorithm was prone to "premature". Through the simulation analysis of IEEE33 nodes, the experimental results show that the improved BPSO algorithm can effectively locate fault sections, which verifies the effectiveness and correctness of the improved BPSO algorithm. At the same time, when there is information distortion, the improved BPSO algorithm is more fault-tolerant than the general algorithm.