一种优化遗传算法在配电网重构的应用研究

Application of optimized genetic algorithm in distribution network reconfiguration

针对配电网重构计算中存在回路和孤岛节点以及效率不高的问题,文中提出一种基于病态基因诊断恢复的优化遗传算法。该算法通过优化基因编码有效减少算法的计算量,并对标准遗传操作进行了优化改进,引入病态基因的诊断修复操作,有效维持算法种群的多样性,且使种群具有快速脱离不可行解区域迅速趋于最优解空间的能力。通过仿真测试证明了优化遗传算法在测试环境中能够有效降低重构后的网损,并具有优于其他遗传算法的计算速度。

Aiming at the existence of loops and island nodes in the reconfiguration of distribution network and its inefficiency,this paper presents an optimized genetic algorithm based on pathological diagnosis and restoration. The algorithm reduces the computational complexity of the algorithm by optimizing the genetic code,optimizes and improves the standard genetic operation,introduces the diagnostic and repair operation of the pathological gene,effectively maintains the diversity of the algorithm population,and quickly separates the population from the infeasible solution area. The ability to go to the optimal solution space reduces the probability of finding infeasible solutions and improves the convergence rate of the algorithm. The simulation test proves that the optimized genetic algorithm can effectively reduce the network loss in the test environment and has fast computational speed than other genetic algorithms.