Artificial Neural Network-Based Development of an Efficient Energy Management Strategy for Office Building

作     者：Payal Soni J.Subhashini 

作者机构：Department of ECESRMISTKattankulathurChennai603203India 

出 版 物：《Intelligent Automation & Soft Computing》 (智能自动化与软计算（英文）)

年 卷 期：2023年第37卷第7期

页      面：1225-1242页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：HVAC ANN demand response power consumption smart grid Weather and temperature occupancy EMS 

摘      要：In the current context,a smart grid has replaced the conventional grid through intelligent energy management,integration of renewable energy sources(RES)and two-way communication infrastructures from power gen-eration to *** management from the distribution side is a critical problem for balancing load demand.A unique energy manage-ment strategy(EMS)is being developed for office building *** includes renewable energy integration,automation,and control based on the Artificial Neural Network(ANN)system using Matlab *** strategy reduces electric power consumption and balances the load demand of the traditional *** strategy is developed by taking inputs from an office building electricity consumption behavior study,a power generation study of a solar photovoltaic system,and the supply pattern of a grid in peak and non-peak *** this is done in consideration of the Indian scenario,where real-time data of month-wise ANN-based intelligent switching has been established for intermittent renewable sources and peak load reduction,as well as average load reduction,has been demonstrated along with the power control loop without the battery system.