Optimization of Distributed Photovoltaic Energy Storage System Double-Layer Planning in Low-Carbon Parks Considering Variable Operating Conditions and Complementary Synergy of Energy Storage Devices

Ziquan Wang, Yaping Gao and Yan Gao ()
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Ziquan Wang: Beijing Key Lab of Heating, Gas Supply, Ventilating and Air Conditioning Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Yaping Gao: School of Architecture and Urban Planning, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Yan Gao: Collaborative Innovation Center of Energy Conservation & Emission Reduction and Sustainable Urban-Rural Development in Beijing, Beijing University of Civil Engineering and Architecture, Beijing 100044, China

Energies, 2025, vol. 18, issue 8, 1-35

Abstract: Reasonable planning and scheduling in low-carbon parks is conducive to coordinating and optimizing energy resources, saving total system costs, and improving equipment utilization efficiency. In this paper, the optimization study of a distributed photovoltaic energy storage system considers the synergistic effects of the planning and operation phases. On the basis of the variable operating characteristics of the unit equipment and the complementary synergistic characteristics of the energy storage equipment, a two-layer optimization model combining planning and operation is adopted, with the minimum total cost and the minimum carbon emission content in the whole life cycle of the system as the optimization objectives and the upper layer of the planning equipment capacity and the configured capacity of each equipment in the system as the optimization variables, which are solved by using the multi-objective no-dominated-sorting genetic algorithm. The lower layer is the optimized operation mode, and the time-by-time operating capacity of each item of equipment is the optimization variable, which is solved by the interior point method. The upper layer optimization results are used as the constraint boundary conditions for optimization of the lower layer, and the lower layer optimization results provide feedback correction to the upper layer optimization results, which ultimately determine the energy system optimization scheme. The optimization results reflect that photovoltaic green power should be arranged in large quantities as a priority, and the synergistic effect of power and cold storage equipment on the system’s economy and low-carbon performance is positive. At the same time, by setting up four control scenarios of only cold storage, only electricity storage, no energy storage, and no two-tier optimization, the impacts of cold storage and electricity storage on the economic and environmental aspects of the system and the positive effect of mutual synergy are investigated, which concretely proves the validity of the two-tier optimization strategy, taking into account the operating characteristics of the equipment.

Keywords: low carbon; distributed photovoltaic; energy storage; two-tier programming (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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