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Sequential and comprehensive BESSs placement in unbalanced active distribution networks considering the impacts of BESS dual attributes on sensitivity

Su, X., Zhang, Z., Liu, Y., Fu, Y., Shahnia, F.ORCID: 0000-0002-8434-0525, Zhang, C. and Dong, Z. (2021) Sequential and comprehensive BESSs placement in unbalanced active distribution networks considering the impacts of BESS dual attributes on sensitivity. IEEE Transactions on Power Systems . Early Access.

Link to Published Version: https://doi.org/10.1109/TPWRS.2021.3051629
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Abstract

The placement of battery energy storage system (BESS) determines whether its capabilities can be effectively exploited. However, existing BESS placement studies are commonly based on a balanced network model while practical distribution networks are essentially unbalanced. Besides, the power injection-based loss sensitivities are widely used to reduce the computation and memory burdens for complicated placement applications, which nevertheless cannot fully consider the impacts of both the BESS charging and discharging attributes and tends to generate less cost-effective clustered solutions. To address the challenges above, this study firstly proposes a multi-objective BESS placement optimization model for unbalanced active distribution networks, considering the time-varying load and renewable profiles as well as electricity prices, to minimize the cost of primary investment and operation/maintenance while maximizing the saving by loss reduction and load shifting. Then, a sequential BESS placement strategy is presented, based on the definition of a comprehensive loss sensitivity index (CLSI) considering the dual attributes of BESS charging and discharging, for more cost-effective and reasonable placement solutions. Finally, the proposed CLSI based sequential BESS placement is tested by detailed simulations on a real Australian distribution network of high PV penetrations.

Item Type: Journal Article
Murdoch Affiliation(s): School of Engineering and Information Technology
Publisher: IEEE
Copyright: © 2021 IEEE
URI: http://researchrepository.murdoch.edu.au/id/eprint/59487
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