Electric Power ›› 2025, Vol. 58 ›› Issue (12): 73-85.DOI: 10.11930/j.issn.1004-9649.202502060

• Key Technologies for Resilient Urban Energy Systems Integrating Massive Distributed Flexible Resources • Previous Articles     Next Articles

Collaborative Configuration of Multi-temporal and Spatial Flexible Resources in New Distribution Systems Considering Operational Risks

JIA Dongli1(), LIU Jiajing1(), ZHAN Huiyu1(), WANG Huanchang1,2(), BU Qiangsheng3()   

  1. 1. China Electric Power Research Institute, Beijing 100192, China
    2. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
    3. State Grid Jiangsu Electric Power Co., Ltd. Research Institute, Nanjing 211103, China
  • Received:2025-02-25 Revised:2025-11-06 Online:2025-12-27 Published:2025-12-28
  • Supported by:
    This work is supported by Science and Technology Project of SGCC (No.5400-202355555A-3-2-ZN).

Abstract:

The high proportion of renewable energy integration and diversified load connections have exacerbated the operational risks of high operating costs and high voltage deviations in new distribution systems. To address the issue that the current new distribution system does not consider the operational risks and the collaborative configuration of multi-temporal and spatial flexible resources across multiple time scales during the configuration phases, this paper proposes a collaborative configuration model for multi-temporal and spatial flexible resources considering operational risks. Firstly, a source-load scenario set is generated using Monte Carlo sampling and the K-means clustering algorithm, and the multi-scale morphological algorithm is employed to decompose the source-load curve waveforms at multiple scales. Then, based on the conditional value at risk (CVaR) theory, a quantitative assessment of the multi-temporal operational risks in the distribution system is conducted. On this basis, a bi-level configuration model for multi-temporal and spatial flexible resources considering operational risks is established. In this model, the upper level aims to minimize the annual total cost of the distribution system for collaborative configuration of the multi-temporal and spatial flexible resources, while the lower level focuses on minimizing the expected loss value and the CVaR-based operational risk value for system optimization. Finally, an improved IEEE 33-node system is used for case study, validating the proposed method can effectively reduce the operational risks related to high operating costs and voltage deviations in the distribution systems.

Key words: flexible resources, multi-time scale, new distribution system, operational risk, morphological algorithm