Distributed Energy Storage Control for Dynamic Load Impact Mitigation


The future uptake of electric vehicles (EV) in low-voltage distribution networks can cause increased voltage violations and thermal overloading of network assets, especially in networks with limited headroom at times of high or peak demand. To address this problem, this paper proposes a distributed battery energy storage solution, controlled using an additive increase multiplicative decrease (AIMD) algorithm. The improved algorithm (AIMD+) uses local bus voltage measurements and a reference voltage threshold to determine the additive increase parameter and to control the charging, as well as discharging rate of the battery. The used voltage threshold is dependent on the network topology and is calculated using power flow analysis tools, with peak demand equally allocated amongst all loads. Simulations were performed on the IEEE LV European Test feeder and a number of real U.K. suburban power distribution network models, together with European demand data and a realistic electric vehicle charging model. The performance of the standard AIMD algorithm with a fixed voltage threshold and the proposed AIMD+ algorithm with the reference voltage profile are compared. Results show that, compared to the standard AIMD case, the proposed AIMD+ algorithm further improves the network’s voltage profiles, reduces thermal overload occurrences and ensures a more equal battery utilisation.

Publication DOI: https://doi.org/10.3390/en9080647
Divisions: College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
Additional Information: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Publication ISSN: 1996-1073
Last Modified: 29 Apr 2024 07:33
Date Deposited: 02 Aug 2019 14:13
Full Text Link:
Related URLs: http://www.mdpi ... 96-1073/9/8/647 (Publisher URL)
PURE Output Type: Article
Published Date: 2016-08-17
Accepted Date: 2016-08-04
Authors: Zangs, Maximilian
Adams, Peter
Yunusov, Timur
Holderbaum, William (ORCID Profile 0000-0002-1677-9624)
Potter, Ben



Version: Published Version

License: Creative Commons Attribution

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