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Volume 11
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Article

Optimal Battery Dispatch Using Finite-Input Set Non-Linear Model Predictive Control: Algorithm Development and Case Study

by
Fathi Abugchem
,
Michael Short
*,
Chris Ogwumike
and
Huda Dawood
Centre for Sustainable Engineering, School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK
*
Author to whom correspondence should be addressed.
Electronics 2022, 11(1), 101; https://doi.org/10.3390/electronics11010101
Submission received: 14 December 2021 / Revised: 25 December 2021 / Accepted: 26 December 2021 / Published: 29 December 2021
(This article belongs to the Special Issue Condition Monitoring and Diagnostics of Energy Storage Systems Components)
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Abstract

The advancement in battery manufacturing has played a significant role in the use of batteries as a cost-effective energy storage system. This paper proposes an optimal charging and discharging strategy for the battery energy storage system deployed for economic dispatch and supply/demand balancing services in the presence of intermittent renewables such as solar photovoltaic systems. A decision-making strategy for battery charge/discharge operations in a discrete-time rolling horizon framework is developed as a finite-input set non-linear model predictive control instances and a dynamic programming procedure is proposed for its real-time implementation. The proposed scheme is tested on controllable loads and a photovoltaic generation scenario in the premises of a sports centre, as a part of a pilot demonstration of the inteGRIDy EU-funded project. The test results confirm that the implemented stacking of the battery and optimal decision-making algorithm can enhance net saving in the electricity bill of the sports centre, and lead to corresponding CO2 reductions.
Keywords: battery management systems; smart energy solution; PV generation; non-linear optimization; optimal charging and discharging; dynamic programming battery management systems; smart energy solution; PV generation; non-linear optimization; optimal charging and discharging; dynamic programming

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MDPI and ACS Style

Abugchem, F.; Short, M.; Ogwumike, C.; Dawood, H. Optimal Battery Dispatch Using Finite-Input Set Non-Linear Model Predictive Control: Algorithm Development and Case Study. Electronics 2022, 11, 101. https://doi.org/10.3390/electronics11010101

AMA Style

Abugchem F, Short M, Ogwumike C, Dawood H. Optimal Battery Dispatch Using Finite-Input Set Non-Linear Model Predictive Control: Algorithm Development and Case Study. Electronics. 2022; 11(1):101. https://doi.org/10.3390/electronics11010101

Chicago/Turabian Style

Abugchem, Fathi, Michael Short, Chris Ogwumike, and Huda Dawood. 2022. "Optimal Battery Dispatch Using Finite-Input Set Non-Linear Model Predictive Control: Algorithm Development and Case Study" Electronics 11, no. 1: 101. https://doi.org/10.3390/electronics11010101

APA Style

Abugchem, F., Short, M., Ogwumike, C., & Dawood, H. (2022). Optimal Battery Dispatch Using Finite-Input Set Non-Linear Model Predictive Control: Algorithm Development and Case Study. Electronics, 11(1), 101. https://doi.org/10.3390/electronics11010101

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