A framework for building energy management system with residence mounted photovoltaic

查看全文 作　　者：Chellaswamy [1]C;Ganesh Babu [2]R;Vanathi [3]A

机构地区：[1]Department of Electronics and Communication Engineering,Kings Engineering College,Chennai,India;[2]Department of Electronics and Communication Engineering,SRM TRP Engineering College,Tiruchirappalli,India;[3]Department of Electronics and Communication Engineering,Rajalakshmi Institute of Technology,Chennai,India

出　　处：《Building Simulation》索引2021年第14卷第4期,共16页

摘　　要：Efficient utilization of a residential photovoltaic (PV) array with grid connection is difficult due to power fluctuation and geographical dispersion. Reliable energy management and control system are required for overcoming these obstacles. This study provides a new residential energy management system (REMS) based on the convolution neural network (CNN) including PV array environment. The CNN is used in the estimation of the nonlinear relationship between the residence PV array power and meteorological datasets. REMS has three main stages for the energy management such as forecasting, scheduling, and real functioning. A short term forecasting strategy has been performed in the forecasting stage based on the PV power and the residential load. A coordinated scheduling has been utilized for minimizing the functioning cost. A real-time predictive strategy has been used in the actual functioning stage to minimize the difference between the actual and scheduled power consumption of the building. The proposed approach has been evaluated based on real-time power and meteorological data sets. 关键词：building energy management convolution neural network PHOTOVOLTAIC coordinated scheduling

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A framework for building energy management system with residence mounted photovoltaic

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耦合文献(9)

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