基于改進(jìn)螢火蟲算法的分布式電源的選址和定容

史吏 李先棟 張濤 許強(qiáng) 賈軒

摘? ?要：針對(duì)分布式電源的選址定容問題，提出了基于自適應(yīng)遺傳機(jī)制的螢火蟲算法。首先，設(shè)計(jì)了以各節(jié)點(diǎn)電壓、可接入最大功率及線路電流作為約束條件，以配電網(wǎng)網(wǎng)損最小作為目標(biāo)的配電網(wǎng)優(yōu)化模型，其次，改進(jìn)了遺傳算法中交叉、變異算子公式，并提出了改進(jìn)的高斯擾動(dòng)方法，將兩者應(yīng)用到螢火蟲算法中，提高了螢火蟲算法全局尋優(yōu)能力和收斂速度。最后，借助于MATLAB軟件，以IEEE33節(jié)點(diǎn)系統(tǒng)為例進(jìn)行了測(cè)試，仿真結(jié)果與自適應(yīng)遺傳算法進(jìn)行了比較，證明了本方法的有效性和優(yōu)越性。

關(guān)鍵詞：分布式電源;螢火蟲算法;自適應(yīng)遺傳機(jī)制

中圖分類號(hào)：TM731? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?文獻(xiàn)標(biāo)識(shí)碼：A

Siting and Sizing of Distributed Generation Based

on Improved Firefly Algorithm

SHI? Li LI? Xian-dong，ZHANG Tao，XU Qiang，JIA Xuan

（State Grid Liaocheng Electric Power Supply Company，Liaocheng，Shangdong 252000，China）

Abstract：In order to solve siting and sizing of distributed generation，the firefly algorithm based on adaptive genetics mechanism is presented. Firstly，regarding each node voltage，accessible maximum power，and line currents as constraints，the distribution network's minimum loss as objective function，designing the optimization model of distribution network;Secondly，the improved firefly algorithm is presented，adding to improved crossover and mutation operations of? genetic algorithm and improved Gauss perturbation，improves the global optimization ability and the convergence speed. Finally，experiments are conducted on IEEE33 node by means of MATLAB . Compared with the adaptive genetic algorithm，the results show that the improved algorithm is effective and superior.

Key words：distributed generation;firefly algorithm;adaptive genetics mechanism