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DSM and Optimization of Multihop Smart Grid Based on Genetic Algorithm

机译:基于遗传算法的DSM与多跳智能电网优化

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摘要

Multihop smart grid is built on the basis of an integrated and high-speed communication network. Through the application of advanced sensing and measurement technology, equipment technology, control method, and advanced decision support system technology, the goal of reliable, safe, economic, efficient, environment-friendly, and safe use of the power grid is realized. In order to solve the problem of excessive demand for power supply, new energy power generation and demand response are proposed. According to the above background, the demand side economic scheduling problem is a complex optimization problem, which is difficult to be solved by ordinary algorithms. The adaptive global search algorithm based on a genetic algorithm can better solve complex optimization problems. The genetic algorithm proposed in this paper can effectively manage a large number of controllable loads in the selected area. The algorithm minimizes the cost and peak to the average ratio by changing the load. Home users can arrange their maximum load when the price is low. The peak load of residential buildings decreased from 98.5 kw/h to 90 kw/h, and the peak load decreased by about 7.53. Through appropriate load dispatching, users minimize the daily electricity charge, which is reduced from 1352 yuan to 1245 yuan per day, and the daily electricity charge is reduced by about 7.25. In addition, the advanced measurement, communication, and control means under the framework of the smart grid also play a key role in promoting all aspects of demand side management (DSM).
机译:多跳智能电网建立在集成的高速通信网络的基础上。通过应用先进的传感测量技术、装备技术、控制方法和先进的决策支持系统技术,实现电网可靠、安全、经济、高效、环保、安全使用的目标。为解决电力供应需求过剩的问题,提出了新能源发电和需求响应。根据上述背景,需求侧经济调度问题是一个复杂的优化问题,是普通算法难以求解的。基于遗传算法的自适应全局搜索算法可以更好地求解复杂的优化问题。本文提出的遗传算法能够有效地管理所选区域的大量可控载荷。该算法通过改变负载来最小化成本和峰值与平均值的比率。家庭用户可以在价格低廉时安排最大负载。住宅建筑峰值负荷由98.5 kw/h下降到90 kw/h,峰值负荷下降约7.53%。通过适当的负荷调度,使用户每天的电费降到最低,从每天1352元减少到1245元,每天电费减少约7.25%。此外,智能电网框架下的先进测量、通信和控制手段在促进需求侧管理(DSM)的各个方面也发挥着关键作用。

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