Sustainable Distribution Network Planning for Enhancing PV Accommodation: A Source–Network–Storage Coordinated Stochastic Approach

Jing Wang, Chenzhang Chang, Jian Le (), Xiaobing Liao and Weihao Wang
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Jing Wang: School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Chenzhang Chang: School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen 518172, China
Jian Le: School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Xiaobing Liao: College of Electrical and Electronic Engineering, Wuhan Institute of Technology, Wuhan 430073, China
Weihao Wang: School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China

Sustainability, 2025, vol. 17, issue 12, 1-32

Abstract: To address the impacts of source load temporal–spatial uncertainties on distribution network planning considering the global transition towards sustainable energy systems with high-penetration photovoltaic (PV) integration, this paper proposes a source–network–storage coordinated stochastic planning method. A temporal–spatial correlation probability model for PV output and load demand is constructed based on Copula theory. Scenario generation and efficient reduction are achieved through Monte Carlo sampling and K-means clustering, extracting representative daily scenarios that preserve the temporal–spatial characteristics. A coordinated planning model targeting the minimization of comprehensive costs is established to holistically optimize PV deployment, energy storage system (ESS) configuration, and network expansion schemes. Simulations on typical distribution network systems demonstrate that the proposed method, by integrating temporal–spatial correlation modeling and multi-element collaborative decision-making, significantly improves PV accommodation capacity and reduces planning costs while improving the overall economic efficiency of distribution network planning. This study provides a robust technical pathway for developing economically viable and resilient distribution networks capable of integrating large-scale renewable energy, thereby contributing to the decarbonization of the power sector and advancing the goals of sustainable energy development.

Keywords: sustainable energy system; source–network–storage collaborative planning; PV accommodation; Copula theory; stochastic scenarios (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:12:p:5324-:d:1675156

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