Chance-constrained Optimal Schedule of Battery Energy Storage Considering the Uncertainties of Renewable Generation

Zhi Li¹Dawei Xie¹Haifeng Ye¹Yujun Li¹Jinzhong Li¹Yichi Chen²Yue Yang^2*

• ¹State Grid Anhui Electric Power Co. Ltd., Tongling, Anhui Province, China
• ²Hefei University of Technology, Hefei, China

Since the renewable energy generation has strong uncertainty and the pure conventional unit dispatch schemes are limited by unit-operating capacity, such scheduling mode becomes inapplicable for power systems with high proportion of renewable energy sources (RES). This paper proposes an optimal scheduling model for Battery Energy Storage Systems (BESS) considering the uncertainties of RES. The probability distribution of RES generation is characterized using a Gaussian Mixture Model (GMM), which effectively captures the stochastic nature of renewable generation. To enhance system security, chance constraints are incorporated into the dispatch model, ensuring sufficient reserve capacity to mitigate fluctuations in RES output. These constraints are transformed into deterministic ones using quantile-based methods for solution. Case studies on two systems demonstrate the proposed model's ability to improve system security and economic efficiency. The results indicate that incorporating BESS can significantly reduce system risk probability and operational costs, particularly under high RES penetration scenarios. The model also highlights the trade-offs between BESS capacity and system risk levels, constraint settings and economic benefits, providing valuable insights for practical applications. Future work will focus on extending the model to include the impact of BESS on branch power transmission risks.