Electric Power ›› 2025, Vol. 58 ›› Issue (3): 55-64.DOI: 10.11930/j.issn.1004-9649.202403093

• Coordinated Control and Optimal Operation of High Proportion of New Energy Integrating Power Grid • Previous Articles     Next Articles

Bi-level Capacity Optimization for Battery/Thermal Energy Storage System in Multi-energy Complementary Power Generation System

Pai LI1(), Hui LU1(), Chi LI1(), Hongbo DU2   

  1. 1. State Key Laboratory of Renewable Energy Grid-Integration (China Electric Power Research Institute), Beijing 100192, China
    2. Guo Ke Optimization Technology Ltd., Beijing 100089, China
  • Received:2024-03-22 Accepted:2024-06-20 Online:2025-03-23 Published:2025-03-28
  • Supported by:
    This work is supported by Research and Development Project of China Electric Power Research Institute (Research on Flexible Resource Optimization Planning Method Integrating Deep Learning and Optimization Decision Algorithm, No.NY83-21-006).

Abstract:

Multi-energy complementary power generation system can fully utilize the complementary advantages of wind-PV-thermal-battery sources and improve energy efficiency. It is of great significance for the construction of low-carbon new power system. Capacity coordinated optimization of battery/thermal energy storage in multi-energy complementary power generation system can reduce the investment costs of power system, and improve the utilization rate of renewable energy and continuous power supply. In this paper, multi-energy complementary power generation system with wind-PV-thermal-battery sources is studied, and a bi-level capacity coordinated optimization model of this system is established. The upper-level model optimizes the capacity of battery/thermal energy storage with the maximum annual net income of this system. The lower-level model optimizes the power shortage in this system, and optimize the generation operation status of this system by considering the constraints such as continuous power supply, wind-PV-thermal-battery sources operation, utilization rate of renewable energy, etc. To solve this bi-level model, a linearization method for nonlinear constraints model is proposed, and a heuristic algorithm based on the combination of value function and branch-bound is designed to obtain the efficient solution. Based on a typical example of multi-energy complementary power generation system, the experimental results verify the effectiveness of the proposed bi-level model and algorithm.

Key words: multi-energy complementary power generation system, battery/thermal energy storage, capacity optimization, bi-level, heuristic algorithm