智能电网环境下住宅用电需求侧管理的自然启发策略

Ravindrakumar Yadav, P. N. Hrishikesha, V. Bhadoria
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引用次数: 4

摘要

全球电力消费的很大一部分是由住宅部门完成的。负荷变化的性质具有高度的不确定性,已成为控制的一个挑战,从而对电力公司造成了很大的峰值负荷负担。然而,需求侧管理(DSM)的概念使公用事业公司能够在智能电网环境中管理住宅部门的负荷。智能电网中的DSM概念能够促进客户和公用事业公司之间的信息流动,从而帮助重建曲线。本文提出了一种基于人类行为的算法,通过管理居民扇区负荷来改变负荷曲线。本文提出的算法用Python编码进行了测试,结果令人满意。临界峰值定价方案(CPP)可以显著降低峰值负荷,同时增加公用事业收益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Nature Inspired Strategy for Demand Side Management in Residential Sector with Smart Grid Environment
A major portion of global electricity consumption is done by residential sector. The nature of load variation is highly uncertain and has become a challenge to control thereby contributes a lot in peak load burden on utility. However, the concept of demand side management (DSM) enables the utility to manage the residential sector load in smart grid environment. The concept of DSM in the smart grid enables the ability to facilitate the flow of information between customers and utility that helps to rebuild the curve. In this paper, human behavior-based algorithm is developed to alter the load curve by managing residential sector load. The proposed algorithm is tested with Python coding and offers satisfactory results. The considerable reduction in peak load with increased utility earning is noticed with critical peak pricing scheme (CPP).
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