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

Mahmoud Elkazaz, Mark Sumner and David Thomas
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Mahmoud Elkazaz: Department of Electrical & Electronic Engineering, The University of Nottingham, Nottingham NG7 2RD, UK
Mark Sumner: Department of Electrical & Electronic Engineering, The University of Nottingham, Nottingham NG7 2RD, UK
David Thomas: Department of Electrical & Electronic Engineering, The University of Nottingham, Nottingham NG7 2RD, UK

Energies, 2019, vol. 12, issue 14, 1-26

Abstract: 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.

Keywords: microgrid energy management system; mixed integer linear programming; adaptive neuro-fuzzy system; short term energy forecasting; real-time predictive controller; adaptive autoregression forecasting algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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