混合量子进化算法在110kV变电站规划中的应用

Hybrid quantum-inspired evolutionary algorithm for 110 kV substations optimization planning

针对城市电网中110 kV变电站规划这一组合优化问题,给出一种基于混合量子进化算法的变电站规划优化方法。该方法融合了量子进化算法收敛速度快,擅长全局搜索的优点和贪婪随机自适应算法局部搜索能力强的长处。将此方法应用到四川某县110 kV变电站容量规划中,计算结果表明该方法很好地完成了对该县变电站数量、主变容量的优化规划。结果符合该地区电力需求和未来电网建设形势,对该县电网下一步规划建设有重要参考意义,表明了方法的有效性。

The paper presents a substations optimization planning method based on hybrid quantum-inspired evolutionary algorithm （HQIEA） for the 110 kV substations combinational optimization. The method integrates the advantages of quantum evolutionary algorithm （QIEA） and the greedy random adaptive search algorithm （GRASP）. The QIEA has the advantage of quick convergence rate and powerful ability of global search. The GRASP is good at the local search. The method is applied to 110 kV substations planning of a county in Sichuan. The result shows that it can optimize the number and capacity of substations. The results comply with current power demand and substations construction trend of the county, and have important reference value for the current power grid planning construction planning. It shows the effectiveness of the method.