Electric Power ›› 2024, Vol. 57 ›› Issue (11): 129-138.DOI: 10.11930/j.issn.1004-9649.202401117

• New Energy • Previous Articles     Next Articles

Risk Analysis of Insufficient Flexibility from Regulation Resources in High Proportion Renewable Energy Power Systems

Jing XU1(), Tiejun ZHAO1(), Xiaogang GAO1, Ju YE1, Lingling SUN2()   

  1. 1. Qinhuangdao Power Supply Company, State Grid Jibei Electric Power Company Limited, Qinhuangdao 066000, China
    2. Key Lab of Power Electronics for Energy Conservation and Motor Drive of Hebei Province (Yanshan University), Qinhuangdao 066004, China
  • Received:2024-01-26 Accepted:2024-04-25 Online:2024-11-23 Published:2024-11-28
  • Supported by:
    This work is supported by the National Natural Science Foundation of China (Research on Collaborative Optimization Allocation Strategy of power quality management resource partition in Active Distribution Network, No.51877186), Science and Technology Project of State Grid Jibei Electric Power Limited (No.5201041900VX).

Abstract:

High-penetration renewable energy power systems introduce significant volatility and uncertainty, exposing the power system to operational risks associated with inadequate flexibility. Assessing the risk of insufficient flexibility under uncertain conditions is crucial for controlling the operational risk levels of power systems and evaluating the merits of planning scenarios. This study explores quantitative assessment methods for the risk of inadequate flexibility in renewable energy power system regulation resources and proposes a risk evaluation index system for this risk. Firstly, a data-driven modeling approach for source-load uncertainty is introduced based on kernel density estimation and order optimization theory. To enhance the adequacy of source-load sample data in power systems, a reconstruction method for low-probability risk sample sets in power systems based on cloud modeling is proposed, enabling cost-free and flexible acquisition of training samples. Secondly, a quantitative assessment method for the risk of inadequate flexibility in renewable energy power system regulation resources is developed from two aspects: ramping capability and regulation depth. Finally, case studies validate the effectiveness and feasibility of the proposed methods.

Key words: high penetration renewable energy grid, regulate resource flexibility, risk assessment indicators, data-driven modeling, reconstruction of risk samples