Computer Engineering and Applications ›› 2014, Vol. 50 ›› Issue (21): 264-270.

Previous Articles    

Demand side management strategy on multistep electricity price using Genetic Algorithm

YANG Xihua1, HU Xiaomin2   

  1. 1.School of Information Science and Technology, Sun Yat-sen University, Guangzhou 510006, China
    2.School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
  • Online:2014-11-01 Published:2014-10-28

遗传算法的阶梯电价用电需求管理方案

杨曦华1,胡晓敏2   

  1. 1.中山大学 信息科学与技术学院,广州 510006
    2.中山大学 公共卫生学院,广州 510080

Abstract: 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.

Key words: smart grid, Genetic Algorithm(GA), multistep electricity price, demand side management, load shifting

摘要: 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。

关键词: 智能电网, 遗传算法, 阶梯电价, 用电需求管理, 负载转移