A Novel Battery Wear Model for Energy Management in Microgrids

• Published in: IEEE access Vol. 10; pp. 30405 - 30413
• Main Authors: Izumida Martins, Marcos Aurelio, Rhode, Lucas B., De Almeida, Adriano Batista De
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Batteries; Battery management systems; Costs; Data models; Diesel generators; Discharges (electric); Distributed generation; Electric vehicles; Energy consumption; Energy management; Energy storage; Lead acid batteries; microgrids; Photovoltaic cells; State of charge; US Department of Defense; Vehicle-to-grid; Wear
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2022.3160239

This paper proposes a novel battery wear model for microgrid (MG) energy management applications. This model is based on a popular battery wear model originally proposed for vehicle-to-grid (V2G) applications. The presented model can be easily parameterized to fit the cycle life data of almost any battery and yields the wear cost of a charge/discharge event as function of the variation in the state of charge (SoC) of the battery. This wear model is incorporated into an energy management algorithm to optimize the operation of a grid-connected MG using a day-ahead planning strategy. To test the model, four simulated scenarios are considered in and MG composed of a diesel generator (DG), a photovoltaic (PV) system, a residential load and, naturally, a battery storage system (battery energy storage system (BESS)). The inclusion of the battery wear model leads the optimizer to be more selective about battery usage, cycling the battery at SoC levels that minimized battery wear, effectively prolonging its lifespan.