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Power System Transition with Multiple Flexibility Resources: A Data-Driven Approach

delete2022-02-24
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OA
AI
H
Hao Li
乔颖 cover
乔颖 (Ying Qiao)
鲁宗相 cover
鲁宗相 (Zongxiang Lu) *
B
Baosen Zhang *
DOI:10.3390/su14052656delete
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Abstract

Abstract

En 中文
Power systems are transitioning toward having high shares of variable renewable energy (VRE) with the help of flexibility resources. However, multiple flexibility resources on the generation, storage and demand sides introduce multiple technical and economic uncertainties, making the transition hard to predict. Moreover, the benefit of these resources in the transition is unclear. To fill these gaps, this paper proposes a data-driven approach to explore the transition to a high VRE share-oriented power system with multiple flexibility resources. This approach generates a wealth of possible transition paths under multiple uncertainties and then uses them to quantitatively analyze the transition. Specifically, the proposed method includes principal component analysis-based path visualization, multiple index-based transition milestone identification, cluster and distance calculation-based key influential factor identification, marginal index-based flexibility resource benefit comparison and Pareto frontier-based path recommendation. Case studies based on the Northwest China power system, which involves wind, photovoltaics and concentrated solar plants, validate the effectiveness of the proposed approach and further indicate that flexibility resources increase rapidly with the growth of the VRE share. Of the multiple flexibility resources, storage contributes the most. Key influential factors include the capital cost of VRE and storage along with coal price. These factors should be the focus in a low-cost and low-carbon transition.
Keywords:
power system transition
flexibility resources
multiple uncertainties
data-driven
high renewable penetration

Journal

Sustainability cover
Sustainability
IF:
3.3
Papers:
10.5W
Citations:
28.4W

Organization

T
tsinghua university
Scholars:
11.8W
Papers: 10.0W
Citations: 137
U
University of Washington
Scholars:
8.0W
Papers: 7.0W
Citations: 12.5W