IEEE Access (Jan 2023)

Bi-Level Optimizing Model for Microgrids With Fast Lithium Battery Energy Storage Considering Degradation Effect

  • Jiyong Li,
  • Xiaoshuai Xu,
  • Yasai Wang,
  • Ran Chen,
  • Chengye Liu

DOI
https://doi.org/10.1109/ACCESS.2023.3264563
Journal volume & issue
Vol. 11
pp. 34643 – 34658

Abstract

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The nonlinear degradation effect of the fast lithium battery energy storage system (FLBESS) and the time-scale variability of peak shaving and frequency regulation both make the optimal operation of the microgrid more challenging. Therefore, this paper presents a bi-level optimization model to balance the degradation cost of lithium battery and the benefit of peak shaving and frequency regulation and improve the utilization of FLBESS while dealing with the multiple time scales optimization problems. The upper-level model mainly optimizes the day-ahead hourly power to minimize the power purchase cost and wind and solar power curtailment cost while calculating the internal parameters of the FLBESS to supply the lower-level model for the solution. The lower model optimizes the intra-hour economic cost and coordinates the frequency regulation benefit and lithium battery degradation cost. Finally, case studies are conducted using a regional microgrid to verify that the model solution satisfies the requirements for optimal system operation. In contrast, the model has the advantages of lower economic cost, more significant life extension effect, and higher energy storage utilization rate. The results show that the annual costs were reduced by 14.9%, and the battery life was increased by 19.0% than without considering degradation.

Keywords