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.

Meeting Name

51st North American Power Symposium, NAPS 2019 (2019: Oct. 13-15, Wichita, KS)


Mechanical and Aerospace Engineering

Second Department

Electrical and Computer Engineering

Research Center/Lab(s)

Center for Research in Energy and Environment (CREE)

Second Research Center/Lab

Center for High Performance Computing Research


This work was supported by the National Science Foundation under award 1610396.

Keywords and Phrases

Battery Degradation Modeling; Load Forecasting; Markov Decision Process (MDP); Solar Forecasting

International Standard Book Number (ISBN)


Document Type

Article - Conference proceedings

Document Version


File Type





© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Oct 2019