基于遗传算法的移动储能车调度方案优化及应用

随着移动储能车技术的发展,移动储能车的应用快速增长。当移动储能车应用于台区变减载时,需考虑储能车的充放电时间点。因此,提出了一种基于遗传算法的移动储能车调度优化方案。算法的适应函数以经济效益最大化为目标,将满足台区变减载电量的约束为罚函数计入适应度计算中。在编码时,考虑生成个体的可行性,合理设置参数的范围和意义,提高优化效率。算例分析表明,该方案可提高减载能力,达到最优调度效果。

Scheduling Scheme Optimization and Application of Mobile Energy Storage Vehicle Based on Genetic Algorithm

With the development of mobile energy storage vehicle technology, the application of mobile energy storage vehicle is growing rapidly. When the mobile energy storage vehicle is applied to substation transformer load shedding, the charging and discharging time points of the energy storage vehicle should be considered. Therefore, the paper proposes a scheduling optimization scheme based on genetic algorithm for mobile energy storage vehicle. The fitness function of the algorithm takes the maximum economic benefit as the goal and constraints that meet the substation transformer as the penalty function and include it in the adaptability calculation. When coding, the feasibility of individual generation is considered to set the scope and significance of parameters reasonably and improve the optimization efficiency. The example shows that the scheme can improve the load reduction capacity and achieve the optimal scheduling effect.