一种基于遗传算法的智能电网调度方法

随着智慧电网的发展，调度控制系统中的数据规模和种类呈指数型上升并且处理复杂度较高。为了更好地进行电力调度，给予电力系统相应的决策支持和更好地为客户服务，满足用户在不同时段的电力需求，本文基于遗传算法提出一种多种类型可控电器的G-DSM算法，将负荷调度问题定义为成本最小化问题，并用遗传算法求解；结合从用户侧获取的电力大数据对用户的电力需求进行规划，降低了用户的花销以及峰值电力负荷，从而避免电力资源的浪费，提高了电网的工作效率。实验结果表明，该算法具有较好的可行性，并在实际操作中易于实现。

A Scheduling Method of Smart Grid Based on Genetic Algorithm

With the development of smart grid, the scale and types of data obtained from dispatch control systems increase exponentially, and dealing with these data is relatively complex. In order to better perform power dispatching to provide corresponding decision support for power system and better serve customers to meet the users power needs at different times, this paper proposes a G-DSM algorithm based on genetic algorithm, which can control server appliances. In the algorithm, the load scheduling problem is defined as cost minimization problem and solved by genetic algorithm. The algorithm combines with the large amount of power big data obtained from the user side to plan the users power demand, reduces the users cost and peak power load, thereby avoiding the waste of power resources and improving the work efficiency of the power grid. Experimental results show that the algorithm has good feasibility and is easy to implement in actual operation.