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Lookup NU author(s): Dr Anurag Sharma
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2021 The AuthorsBoth global climate change and the decreasing cost of lithium-ion batteries are enablers of electric vehicles as an alternative form of transportation in the private sector. However, a high electric vehicle penetration in urban distribution grids leads to challenges, such as line over loading for the grid operator. In such a case installation of grid integrated storage systems represent an alternative to conventional grid reinforcement. This paper proposes a method of coordinated control for multiple battery energy storage systems located at electrical vehicle charging parks in a distribution grid using linear optimization in conjunction with time series modeling. The objective is to reduce the peak power at the point of common coupling in existing distribution grids with a high share of electric vehicles. An open source simulation tool has been developed that aims to couple a stand alone power flow model with a model of a stand alone battery energy storage system. This combination of previously disjointed tools enables more realistic simulation of the effects of storage systems in different operating modes on the distribution grid. Further information is derived from a detailed analysis of the storage system based on six key characteristics. The case study involves three charging parks with various sizes of coupled storage systems in a test grid in order to apply the developed method. By operating these storage systems using the coordinated control strategy, the maximum peak load can be reduced by 44.9%. The rise in peak load reduction increases linearly with small storage capacities, whereas saturation behavior can be observed above 800kWh.
Author(s): Kucevic D, Englberger S, Sharma A, Trivedi A, Tepe B, Schachler B, Hesse H, Srinivasan D, Jossen A
Publication type: Article
Publication status: Published
Journal: Applied Energy
Print publication date: 01/08/2021
Online publication date: 30/04/2021
Acceptance date: 04/04/2021
Date deposited: 02/06/2023
ISSN (print): 0306-2619
Publisher: Elsevier Ltd
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