遗传算法的阶梯电价用电需求管理方案

用电需求管理是智能电网中的重要部分，能让消费者根据自己的用电量做出合适的决策，帮助供电者减少峰值负载，让负载的时空分布更为均衡，从而增加智能电网的可持续性，并减少运营成本和碳排放量。一种基于负载转移技术的用电需求管理方案可以满足对大量、多种设备的调节需求。用电需求管理的解决方案使用改进的遗传算法，并引入了一个新的算子，模拟测试的结果显示通过改进的算法获得的方案节省了可观的成本，并且在使用阶梯式电价的情况下，减少了智能电网的峰值负载。

Demand side management strategy on multistep electricity price using Genetic Algo-rithm

Demand side management plays an important role in smart grid business, which allows consumers to choose a suitable electricity consuming strategy according to their demand, lowers the peak load in smart grid, and makes the load curve even. These characteristics lead to a more sustainable, economical smart grid, and a reduction on carbon emission. A demand side management strategy based on a load-shifting technique is proposed, which will be able to manage the demand that comes from large quantities and types of devices. The strategy is carried out with an improved genetic algorithm which imports a new operator. Simulation shows that the resulting strategy generated by the proposed algorithm saves appreciable cost, and reduces the peak load of the smart grid when involving a multistep electricity price.