自适应多种群果蝇算法在配电网重构中的应用

Application of Adaptive Multiple-population Fruit Fly Optimization Algorithm for Reconfiguration in Distribution Network

针对有源配电网对安全可靠性的要求较高,而现有的配电网重构算法精度低、速度低的问题,提出了一种基于自适应多种群果蝇优化算法,以网络损耗、负荷均衡度和电压偏差为目标函数建立配电网多目标重构数学模型。为克服标准果蝇算法的缺陷,引入自适应步长调整策略提高算法的局部搜索能力,进一步采用多种群策略和切比雪夫混沌映射提高算法的全局搜索能力和寻优速度,达到平衡全局与局部搜索的效果。通过对含DG的典型IEEE33节点系统为例进行仿真分析,系统接入DG后的重构结果显示三项指标分别下降了9.56%、23.34%和37.29%,同时,改进后的果蝇算法比标准果蝇算法在平均收敛代数方面降低了43.39%,验证了所提方法的有效性与高效性。

Existing optimizations have low precision and slow speed for reconfiguration of distribution network.In order to improve the safety and reliability of distribution network with distributed generation,a distribution network reconfiguration model with diferent DC is established,this paper presents a multi-objective reconfiguration model of active distribution network based on the adaptive multiple-population fruit fly optimization algorithm.To over-come the defect of standard fruit fly al-gorithm and achieve the ffet of balancing global search and local search,an adaptive step strategy is used to promote the local search ability of the algorithm,furthermore,multiple-popu-lation strategy and Chebyshev chaotic mapping are used to improve search speed and global search capability of the algorithm.Through the typical IEEE33 node distribution system simulation,the experimental results show that the three indexes of reducing network loss,maintaining load balance and reducing voltage deviation after DC access de-creased respectively by 9.56%,23.34%and 37.29%compared with the econstruction method without DG ac-cess,meanwhile,the AMFOA reduces the average convergence algebra by 43.39%compared with the standard FOA,which verifies effectiveness and eficiency of the proposed method.