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

• Published in: Energies (Basel) Vol. 12; no. 14; p. 2712
• Main Authors: Elkazaz, Mahmoud, Sumner, Mark, Thomas, David
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 16.07.2019
• Subjects: Abbreviations; adaptive autoregression forecasting algorithm; adaptive neuro-fuzzy system; Adaptive systems; Algorithms; Alternative energy sources; Artificial intelligence; Augmented reality; Autoregressive processes; Carbon dioxide; Controller area network; Controllers; Demand; Distributed generation; Electric vehicles; Electricity; Electricity consumption; Electricity distribution; Energy charge; Energy management; Energy resources; Energy sources; Energy storage; Forecasting; Forecasting techniques; Fuzzy systems; Genetic algorithms; Integer programming; Linear programming; microgrid energy management system; mixed integer linear programming; Neural networks; Operating costs; Optimization; Photovoltaics; Real time; real-time predictive controller; Regression analysis; Short term; short term energy forecasting; Spring (season); State of charge; Tariffs; Time of use; White noise; United Kingdom > UK; Istanbul Turkey; Turkey
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en12142712

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.