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Regular Paper | Open Access

Adjustable Robust Sizing and Operation Co-optimization for Grid-connected LVDC Systems with Photovoltaic and Battery

Yangxin Qiu, Qing Zhong( ), Longjun Wang, Gang Wang
School of Electric Power, South China University of Technology, Guangzhou 510640, China
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Abstract

Low-voltage direct current (LVDC) systems that are connected to the grid present a viable way to achieve low-carbon growth. However, sizing grid-connected LVDC systems is made more difficult by the high cost of grid-connected converters and the erratic fluctuation of renewable energy. This work investigates the co-optimization of sizing and operation for grid-connected LVDC systems that include photovoltaic (PV) and batteries to bridge this gap. An adjustable robust sizing and operation model is proposed, considering the uncertainty of PV generations and loads. The proposed model comprehensively describes the main characteristics of LVDC systems, such as grid-connected converters and the flexible operation of batteries. The proposed model is a nonlinear trilevel min-max-min problem that is difficult to solve. Therefore, a novel solving method is proposed, including three main steps. Firstly, the proposed model is linearized by extending the feasible region while keeping the same optimal solutions. Secondly, a penalty function is added to improve the feasibility of the subproblem of the model. Finally, an approximately equivalent model is attained and solved by the classical column-and-constraint generation (C&CG) algorithm. The numerical results of the case study verify the feasibility and validity of the proposed model and solving method.

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CSEE Journal of Power and Energy Systems
Pages 1835-1846

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Cite this article:
Qiu Y, Zhong Q, Wang L, et al. Adjustable Robust Sizing and Operation Co-optimization for Grid-connected LVDC Systems with Photovoltaic and Battery. CSEE Journal of Power and Energy Systems, 2026, 12(4): 1835-1846. https://doi.org/10.17775/CSEEJPES.2022.03780

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Received: 07 January 2022
Revised: 03 September 2022
Accepted: 24 October 2022
Published: 19 September 2024
© 2022 CSEE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).