基于遗传膜算法的含风电机组和电动汽车的配电网分时段动态重构

Membrane Computing Based Genetic Algorithm for Dynamic Reconfiguration of Distribution Network with Dividing Time and Considering Electric Vehicles and Wind Turbines

在新能源不断接入配电网的环境下,配电网分时段动态重构变得越来越重要。配电网分时段动态重构模型中考虑了电力公司从风电机组的购电成本、随机波动性成本、电动汽车充放电成本和网络损耗成本等。在满足各时段配电网安全运行等约束条件下,以配网经济性最优为目标函数确定最终的开关组合,该模型反映了风电机组和不同类型电动汽车对电网经济性的影响。为克服重构中产生大量重复解,提出等份交叉概率选择法,并提出一种膜计算与改进遗传算法相结合的遗传膜算法对上述模型进行求解,该算法克服了基本遗传算法的"早熟"问题。实验验证了上述模型和方法的正确性和有效性。

Dynamic reconfiguration with dividing time is becoming more and more important in the distribution network with more new energy. The dynamic reconfiguration model of distribution network with dividing time is established for electric power company, considering the costs of purchasing electricity from wind turbines, stochastic volatility, electric vehicle charging and discharging, and network loss. The final switch combination can be decided by minimum network cost with safe operation in each period. The model reflects the comprehensive effect of wind turbines and different kinds of electric vehicles on grid economy. Equal sections crossover probability selection method is used to overcome a large amount of duplicate solutions in the reconfiguration, and the improved algorithm based on the genetic membrane algorithm （GMA） is presented. The global searching capability of the algorithm is improved. Finally, the effectiveness and correctness of the proposed model and method are verified.