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June 1, 2026Smart Energy0 citationsOpen Access

Optimization Design of an Energy Storage-Electric Vehicle Collaborative Multi-energy Complementary Modular Energy Supply System for High Photovoltaic Penetration

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WJWang JialingWZWang ZhiyongZYZhang Yueyuan

Key Points

  • This study aims to quantify the benefits of energy storage and electric vehicles in optimizing energy supply in high photovoltaic areas.
  • Developed an optimization model for energy storage and EV coordinated system
  • Utilized typical days and multiple weather scenarios to assess PV variability
  • Conducted a case study in a building cluster in western Inner Mongolia.
  • PV utilization rate reached 99.51%, compared to 93.69% and 91.90% in non-coordinated scenarios
  • System net present cost was 33,856.71×104 ¥, lower than benchmarks by 279.62×104 ¥ and 617.08×104 ¥
  • Carbon emissions were reduced by 14,903.05 t and 13,946.70 t.

Abstract

The increasing penetration of photovoltaic (PV) generation has intensified the temporal mismatch between energy supply and demand in park-level energy systems. However, the coordinated planning value of energy storage and electric vehicles (EVs) in high-PV building clusters, especially the trade-off between system and user costs, remains insufficiently quantified. This study develops an optimization model for an energy storage–EV coordinated multi-energy complementary modular energy supply system considering PV output uncertainty. Typical days and multiple weather scenarios are used to describe PV variability, and a bi-objective framework is formulated to minimize the system net present cost (NPC) and EV user NPC while jointly optimizing equipment capacities and hourly operation. EVs are aggregated as a bidirectional virtual storage unit through vehicle-to-grid to enhance flexibility against PV fluctuations. A case study of a building cluster in western Inner Mongolia is conducted. The results show that the coordinated scenario improves regulation capability and PV utilization. The PV utilization rate reaches 99.51%, compared with 93.69% and 91.90% in two non-coordinated benchmarks. The system NPC is 33,856.71×104 ¥, which is 279.62×104 ¥ and 617.08×104 ¥ lower than the benchmarks, respectively. Carbon emissions are reduced by 14,903.05 t and 13,946.70 t.

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Cite This Study

Jialing et al. (2026) studied this question.

synapsesocial.com/papers/6a1d21e502fbce9130637c65https://doi.org/10.1016/j.segy.2026.100253
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