Optimal robust allocation of distributed modular energy storage system in distribution networks for voltage regulation
This paper addresses the optimal robust allocation (location and number) problem of distributed modular energy storage (DMES) in active low-voltage distribution networks (DNs) with the aim of reducing voltage deviations. In the proposed allocation problem, a novel centralized-local control framework...
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| Published in: | Applied energy Vol. 388; p. 125625 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier Ltd
15.06.2025
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| ISSN: | 0306-2619 |
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| Abstract | This paper addresses the optimal robust allocation (location and number) problem of distributed modular energy storage (DMES) in active low-voltage distribution networks (DNs) with the aim of reducing voltage deviations. In the proposed allocation problem, a novel centralized-local control framework (CLCF) is designed for DMES for voltage regulation, where the droop coefficients setting schedule are optimally determined. Besides, in order to address the uncertainties and correlation between active and reactive power injections, the proposed DMES allocation problems are formulated as robust optimization models under the novel correlated polyhedral uncertainty set (CPUS) to avoid over-conservatism of solutions. Moreover, to make the proposed nonlinear nonconvex allocation problem computationally trackable, it is decoupled into operation and planning (siting and sizing) optimization stages. The operation problem is relaxed into a mixed-integer second-order cone programming problem using mixed-integer reformulation, dual linear program and second-order cone program. In planning stage, a recursive algorithm is employed to determine the capacity boundaries to identify the optimal number of DMESs. Through case studies, the effectiveness and advantages of the optimal allocation methods was demonstrated in an actual rural low-voltage DN in China.
•Optimal robust allocation of distributed modular energy storage systems considering droop coefficients design is investigated to reduce voltage deviations.•A centralized-local (droop) control framework for voltage regulation is employed.•A correlated polyhedral uncertainty set considering the correlation between active and reactive power injection is proposed.•An efficient optimization algorithm is developed to solve optimal allocation problem.•Optimization can efficiently mitigate voltage deviation and over-conservatism. |
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| AbstractList | This paper addresses the optimal robust allocation (location and number) problem of distributed modular energy storage (DMES) in active low-voltage distribution networks (DNs) with the aim of reducing voltage deviations. In the proposed allocation problem, a novel centralized-local control framework (CLCF) is designed for DMES for voltage regulation, where the droop coefficients setting schedule are optimally determined. Besides, in order to address the uncertainties and correlation between active and reactive power injections, the proposed DMES allocation problems are formulated as robust optimization models under the novel correlated polyhedral uncertainty set (CPUS) to avoid over-conservatism of solutions. Moreover, to make the proposed nonlinear nonconvex allocation problem computationally trackable, it is decoupled into operation and planning (siting and sizing) optimization stages. The operation problem is relaxed into a mixed-integer second-order cone programming problem using mixed-integer reformulation, dual linear program and second-order cone program. In planning stage, a recursive algorithm is employed to determine the capacity boundaries to identify the optimal number of DMESs. Through case studies, the effectiveness and advantages of the optimal allocation methods was demonstrated in an actual rural low-voltage DN in China.
•Optimal robust allocation of distributed modular energy storage systems considering droop coefficients design is investigated to reduce voltage deviations.•A centralized-local (droop) control framework for voltage regulation is employed.•A correlated polyhedral uncertainty set considering the correlation between active and reactive power injection is proposed.•An efficient optimization algorithm is developed to solve optimal allocation problem.•Optimization can efficiently mitigate voltage deviation and over-conservatism. This paper addresses the optimal robust allocation (location and number) problem of distributed modular energy storage (DMES) in active low-voltage distribution networks (DNs) with the aim of reducing voltage deviations. In the proposed allocation problem, a novel centralized-local control framework (CLCF) is designed for DMES for voltage regulation, where the droop coefficients setting schedule are optimally determined. Besides, in order to address the uncertainties and correlation between active and reactive power injections, the proposed DMES allocation problems are formulated as robust optimization models under the novel correlated polyhedral uncertainty set (CPUS) to avoid over-conservatism of solutions. Moreover, to make the proposed nonlinear nonconvex allocation problem computationally trackable, it is decoupled into operation and planning (siting and sizing) optimization stages. The operation problem is relaxed into a mixed-integer second-order cone programming problem using mixed-integer reformulation, dual linear program and second-order cone program. In planning stage, a recursive algorithm is employed to determine the capacity boundaries to identify the optimal number of DMESs. Through case studies, the effectiveness and advantages of the optimal allocation methods was demonstrated in an actual rural low-voltage DN in China. |
| ArticleNumber | 125625 |
| Author | Liu, Youbo Xu, Xiao Tang, Zhiyuan Xu, Zirong Gao, Hongjun Chen, Yongdong |
| Author_xml | – sequence: 1 givenname: Zirong surname: Xu fullname: Xu, Zirong – sequence: 2 givenname: Zhiyuan surname: Tang fullname: Tang, Zhiyuan email: tangzhiyuan@scu.edu.cn – sequence: 3 givenname: Yongdong surname: Chen fullname: Chen, Yongdong – sequence: 4 givenname: Youbo surname: Liu fullname: Liu, Youbo – sequence: 5 givenname: Hongjun surname: Gao fullname: Gao, Hongjun – sequence: 6 givenname: Xiao surname: Xu fullname: Xu, Xiao |
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| Cites_doi | 10.1109/TPWRS.2016.2598186 10.1109/TSTE.2021.3080311 10.1016/j.solener.2017.02.047 10.1016/j.apenergy.2017.03.123 10.1016/j.cie.2015.12.006 10.1016/j.apenergy.2017.03.118 10.1016/j.est.2019.01.023 10.1016/j.est.2020.102158 10.1109/TPWRS.2015.2404533 10.1016/j.apenergy.2022.119253 10.1109/TPWRD.2018.2868158 10.1109/61.19266 10.1016/j.apenergy.2019.113468 10.1109/TSTE.2019.2946371 10.1109/TPWRS.2019.2897948 10.1016/j.apenergy.2017.05.048 10.1109/TSG.2016.2602480 10.1109/TPWRS.2020.3029532 10.1007/s10107-003-0396-4 10.1109/TPWRS.2018.2847400 10.1016/j.est.2021.102263 10.1109/TSG.2016.2562672 10.1109/TSG.2013.2282504 10.1109/TPWRS.2017.2735379 10.1287/moor.23.4.769 10.1016/j.apenergy.2020.115768 10.1109/TPWRS.2017.2751043 10.1016/j.neucom.2011.10.037 10.1016/j.epsr.2018.12.001 10.1109/TSG.2014.2313724 10.1109/TSG.2013.2245926 10.1109/TPWRS.2017.2716407 |
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| Keywords | Distributed modular energy storage Correlated polyhedral uncertainty set Local droop control Optimal robust allocation Distribution networks Voltage regulation |
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| SubjectTerms | algorithms China Correlated polyhedral uncertainty set Distributed modular energy storage Distribution networks electric potential difference linear programming Local droop control Optimal robust allocation uncertainty Voltage regulation |
| Title | Optimal robust allocation of distributed modular energy storage system in distribution networks for voltage regulation |
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