An intelligent energy management system to optimise demand response in Smart Micro Grids

Sandip Chanda, A. De
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引用次数: 1

Abstract

This paper proposes the development of an intelligent Energy Management System (EMS) at consumer end to utilize the sensitivities of the local renewable generation, battery backup and Plug In Electric Vehicle resources to the changes in grid power input and price of electricity for utility and Demand Response optimization in Smart Micro Grids. In Demand Response usually the price elasticity of demand is considered as per statistical data. In this work the development of an optimized Demand Response(DR) has been depicted for reliable and efficient operation of Micro grids with Smart Communication facility. A housing complex, in the proposed work has been viewed as a future micro-grid and it has been demonstrated that the EMS developed can be effectively programmed to minimize the consumer payment by efficient utility and load management with the assistance of pricing signals from the Smart Grid. The choice of Particle Swarm Optimization(PSO) was compelling for the nonlinear nature of the optimization surface. The results obtained from simulation looked promising from context of future Smart Micro Grids.
优化智能微电网需求响应的智能能源管理系统
本文提出在用户端开发智能能源管理系统(EMS),以利用当地可再生能源发电、备用电池和插电式电动汽车资源对电网输入电力和电价变化的敏感性,实现智能微电网的公用事业和需求响应优化。在需求响应中,通常根据统计数据来考虑需求的价格弹性。在这项工作中,描述了优化需求响应(DR)的发展,以实现具有智能通信设施的微电网的可靠和高效运行。在拟议的工作中,一个住宅综合体被视为未来的微电网,并且已经证明,在智能电网的定价信号的帮助下,通过有效的公用事业和负荷管理,可以有效地对开发的EMS进行编程,以最大限度地减少消费者的支付。考虑到优化曲面的非线性特性,选择粒子群优化算法(PSO)是很有必要的。从未来智能微电网的背景下,仿真结果看起来很有希望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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