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Lookup NU author(s): Dr Adib Allahham, Dr David Greenwood, Professor Haris Patsios
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
A receding horizon controller for optimal, adaptive scheduling of a battery energy storage system is proposed. Batteries degrade as a function of their operation and age; operation also affects battery energy storage system efficiency. Many state-of-the-art energy management techniques simplify the relationship between state of charge (SoC) and degradation, assume the efficiency to be constant, and neglect the impact of state of health and variable efficiency on the SoC progression used to quantify the degradation. This results in significant deviations from optimal operation, over-estimates of remaining capacity, and inaccuracies in the calculation of further degradation. The controller developed in this paper adapts the operating schedule of a battery energy storage system to its age, condition, and state of charge. This is achieved by identifying the factors which affect the degradation processes and efficiency in lithium-ion battery systems and quantifying their impacts, resulting in a system-level model which incorporates all the pertinent parameters. Integrating the developed model into the problem formulation of the receding horizon controller enables online evaluation of age and operation-dependant efficiency and degradation, which allows the controller to make adaptive decisions, minimising operating costs. The proposed controller was tested using data from a real-world case study and the results show the controller outperforms two existing energy management techniques, whilst delivering the same network services.
Author(s): Allahham A, Greenwood D, Patsios C, Taylor P
Publication type: Article
Publication status: Published
Journal: Electric Power Systems Research
Year: 2022
Volume: 209
Print publication date: 01/08/2022
Online publication date: 29/03/2022
Acceptance date: 16/03/2022
Date deposited: 20/06/2023
ISSN (electronic): 0378-7796
Publisher: Elsevier
URL: https://doi.org/10.1016/j.epsr.2022.107936
DOI: 10.1016/j.epsr.2022.107936
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