Real-Time Energy Management for a Small Scale PV-Battery Microgrid: Modeling, Design, and Experimental Verification

被引:10
作者
Elkazaz, Mahmoud [1 ,2 ]
Sumner, Mark [1 ]
Thomas, David [1 ]
机构
[1] Univ Nottingham, Dept Elect & Elect Engn, Nottingham NG7 2RD, England
[2] Tanta Univ, Dept Elect Power & Machines Engn, Tanta 31527, Egypt
关键词
microgrid energy management system; mixed integer linear programming; adaptive neuro-fuzzy system; short term energy forecasting; real-time predictive controller; adaptive autoregression forecasting algorithm; RENEWABLE ENERGY; COMMUNITY ENERGY; SYSTEM; OPTIMIZATION; STORAGE; IMPLEMENTATION; ALGORITHM;
D O I
10.3390/en12142712
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
A new energy management system (EMS) is presented for small scale microgrids (MGs). The proposed EMS focuses on minimizing the daily cost of the energy drawn by the MG from the main electrical grid and increasing the self-consumption of local renewable energy resources (RES). This is achieved by determining the appropriate reference value for the power drawn from the main grid and forcing the MG to accurately follow this value by controlling a battery energy storage system. A mixed integer linear programming algorithm determines this reference value considering a time-of-use tariff and short-term forecasting of generation and consumption. A real-time predictive controller is used to control the battery energy storage system to follow this reference value. The results obtained show the capability of the proposed EMS to lower the daily operating costs for the MG customers. Experimental studies on a laboratory-based MG have been implemented to demonstrate that the proposed EMS can be implemented in a realistic environment.
引用
收藏
页数:26
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