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

机译:短期能耗预测在家庭能源管理系统中的应用

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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.
机译:在智能电网的背景下,家庭一级的能源管理系统对配电网具有至关重要的影响。家用级别的基于PV的能源系统日益流行。因此,安排住宅储能设备对于优化分布式能源(DER)(尤其是基于可再生能源的分布式能源)的技术和市场整合是必要的。单个家庭级别的用电量预测的第一步用于实现对存储设备的正确调度。然后提出了一种基于智能代理的控制技术,以确保作为能源管理系统一部分的最终用户的经济利益。在本文中,对人工神经网络(ANN)的预测能力进行了评估,以捕获单个家庭的日常用电量。

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