Multi-scenario flexibility assessment of power systems considering renewable energy output uncertainty

Autor: Qing Ai, Jianqiang Xiang, Yaolin Liu, Luguang Qu, Jinchao Cao, Xiangnan Li, Yingge Wang
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Frontiers in Energy Research, Vol 12 (2024)
Druh dokumentu: article
ISSN: 2296-598X
DOI: 10.3389/fenrg.2024.1359233
Popis: The widespread adoption of renewable energy sources presents a significant challenge to the flexibility of power system. To assess the flexibility of the power system in scenarios with uncertain renewable energy output, it is crucial to quantify it quantitatively. This evaluation plays a vital role in planning flexible regulatory resources and dispatching resources for both the energy source and load. This study introduces a novel flexibility assessment model tailored for power grids with high renewable energy penetration, specifically addressing uncertainty associated with wind and PV. By analyzing the impact of wind and PV uncertainty on system flexibility, the paper proposes an improved cohesive hierarchical cluster analysis method, incorporating reliability considerations based on the Davies-Bouldin classification reliability index. Additionally, the study develops models for flexibility resources and demands within high renewable energy power systems, along with quantitative assessment indicators across three key aspects. Through a structured flexibility assessment process accounting for wind and PV uncertainty, the effectiveness of the proposed approach is validated using real-world data from a renewable energy power grid in Shandong province. A set of typical renewable energy output scenarios with uncertainty is constructed using the improved hierarchical cluster analysis method. The study then analyses the impact of different wind and PV penetration rates and the proportion of energy storage units on system flexibility by the flexibility assessment model to validate the proposed method's effectiveness.
Databáze: Directory of Open Access Journals