Battery Degradation Modeling and Optimal Usage in a Microgrid using Markov Decision Process
With a focus of reducing emission due to power production from fossil fuels, emphasis on renewable energy based resources are gaining more importance in recent years. Photovoltaic power generation systems with battery backup has the need to use a battery backup as due to the intermittent nature of the solar energy. A framework based on Markov Decision Process (MDP) to schedule the battery has been presented in this work with the battery degradation modeled. The objective is to reduce the overall cost of the power production. The algorithm is also equipped with solar and load forecasting based on regression and time series model respectively. The battery degradation modeling is based on the battery chemistry for which an equivalent mathematical model is created and incorporated inside the MDP algorithm. The discussed control algorithm is tested on a system comprising of a grid, a photovoltaic generation, local loads and a battery energy storage system.
V. R. Chowdhury et al., "Battery Degradation Modeling and Optimal Usage in a Microgrid using Markov Decision Process," Proceedings of the 51st North American Power Symposium (2019, Wichita, KS), Institute of Electrical and Electronics Engineers (IEEE), Oct 2019.
The definitive version is available at https://doi.org/10.1109/NAPS46351.2019.9000375
51st North American Power Symposium, NAPS 2019 (2019: Oct. 13-15, Wichita, KS)
Mechanical and Aerospace Engineering
Electrical and Computer Engineering
Keywords and Phrases
Battery Degradation Modeling; Load Forecasting; Markov Decision Process (MDP); Solar Forecasting
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Oct 2019