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The multi-stage framework for optimal sizing and operation of hybrid electrical-thermal energy storage system

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  • He, Yi
  • Guo, Su
  • Zhou, Jianxu
  • Song, Guotao
  • Kurban, Aynur
  • Wang, Haowei

Abstract

In order to mitigate the intermittency of renewable energy, the paper proposes a hybrid electrical-thermal energy storage system, which complementarily utilizes the cost-effective two-tank direct molten salt thermal energy storage system and the flexible lead-acid battery. A multi-stage framework is further proposed for optimal sizing and operation of the hybrid energy storage system. First, the renewable energy capacity is optimized considering the minimization of total net load. Then, the typical net load profiles are selected by K-means clustering algorithm. Finally, a bi-level optimization model considers the minimization of levelized cost of storage (LCOS) and power deviation to optimize the sizing and operation strategy of the hybrid energy storage system, and the optimization problem is solved by meta-heuristic algorithm and mixed-integer linear programming. The case studies show that: (1) the hybrid energy storage system is more reliable than single thermal energy storage and more cost-effective than single battery; (2) the multi-stage framework outperforms the commonly-used rule-based operation strategy; (3) demand response strategy can effectively reduce the investment cost of the proposed system.

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  • He, Yi & Guo, Su & Zhou, Jianxu & Song, Guotao & Kurban, Aynur & Wang, Haowei, 2022. "The multi-stage framework for optimal sizing and operation of hybrid electrical-thermal energy storage system," Energy, Elsevier, vol. 245(C).
    • Handle: RePEc:eee:energy:v:245:y:2022:i:c:s0360544222001517
    DOI: 10.1016/j.energy.2022.123248
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    Cited by:

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    6. He, Yi & Guo, Su & Dong, Peixin & Wang, Chen & Huang, Jing & Zhou, Jianxu, 2022. "Techno-economic comparison of different hybrid energy storage systems for off-grid renewable energy applications based on a novel probabilistic reliability index," Applied Energy, Elsevier, vol. 328(C).
    7. Wang, Xiaojing & Han, Li & Wang, Chong & Yu, Hongbo & Yu, Xiaojiao, 2023. "A time-scale adaptive dispatching strategy considering the matching of time characteristics and dispatching periods of the integrated energy system," Energy, Elsevier, vol. 267(C).
    8. Olis, Walker & Rosewater, David & Nguyen, Tu & Byrne, Raymond H., 2023. "Impact of heating and cooling loads on battery energy storage system sizing in extreme cold climates," Energy, Elsevier, vol. 278(PB).
    9. Yan, Yixian & Huang, Chang & Guan, Junquan & Zhang, Qi & Cai, Yang & Wang, Weiliang, 2024. "Stochastic optimization of solar-based distributed energy system: An error-based scenario with a day-ahead and real-time dynamic scheduling approach," Applied Energy, Elsevier, vol. 363(C).
    10. Tassenoy, Robin & Couvreur, Kenny & Beyne, Wim & De Paepe, Michel & Lecompte, Steven, 2022. "Techno-economic assessment of Carnot batteries for load-shifting of solar PV production of an office building," Renewable Energy, Elsevier, vol. 199(C), pages 1133-1144.

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