Application of short term energy consumption forecasting for household energy management system

K. Ahmed, M. Al- Amin, M. T. Rahman
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引用次数: 7

Abstract

In the context of the smart grid, energy management systems at household level has a vital impact on distribution grid. PV based energy systems at household level become more popular day-by-day. Thus scheduling residential energy storage device is necessary to optimize technical and market integration of distributed energy resources (DERs), especially the ones based on renewable energy. The first step of electricity consumption forecasting at individual household level is used to achieve proper scheduling of the storage devices. Then an intelligent agent based controlling technique is proposed to make sure the financial benefits of end-user as a part of energy management system. In this paper the forecasting ability of Artificial Neural Network (ANN) is evaluated to capture the daily electricity consumption profile of an individual household.
短期能耗预测在家庭能源管理系统中的应用
在智能电网的背景下,家庭级能源管理系统对配电网的运行有着至关重要的影响。家用光伏能源系统日益普及。因此,对分布式能源,特别是基于可再生能源的分布式能源进行技术和市场整合优化是必要的。第一步是对单个家庭的用电量进行预测,以实现对存储设备的合理调度。然后提出了一种基于智能体的控制技术,作为能源管理系统的一部分,以确保最终用户的经济效益。本文评估了人工神经网络(ANN)的预测能力,以捕捉单个家庭的日常用电量。
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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