Affiliation:
1. State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing University Chongqing China
Abstract
AbstractPower system unreliability tracing model allocates the system's reliability index to individual components, identifying potential weaknesses. This study expands its scope by considering the impact of storage resources. Unreliable factors leading to load shedding are categorized into two groups: objective factors inherent to the component and insufficient storage resources. The latter requires a retrospective analysis of other components that caused unreliability previously. When allocating responsibility for load shedding at a certain time, it begins by allocating it among components based on differences between fixed expected output and actual supply. Expected output insufficiency is considered as the unreliable factor. This insufficiency due to insufficient storage resources is then decomposed into segments, each caused by excessive output in earlier instances of the same component. The expected output excess is attributed to the expected output insufficiency of other components in previous times, for which responsibility has been allocated to each component. Consequently, the expected output insufficiency at a particular time can be traced back based on a temporal recursive model, with the load shedding further allocated to components before that time. Case studies based on several systems demonstrate that the proposed model's allocation results are reasonable and more accurate than the traditional model.
Funder
National Natural Science Foundation of China
Publisher
Institution of Engineering and Technology (IET)
Reference32 articles.
1. IRENA:Renewable capacity statistics 2024. The International Renewable Energy Agency.https://www.irena.org/Publications/2024/Mar/Renewable‐capacity‐statistics‐2024(2024). Accessed 9 April 2024
2. Low‐carbon generation expansion planning considering flexibility requirements for hosting wind energy
3. Integrated risk measurement and control for stochastic energy trading of a wind storage system in electricity markets;Xiao D.;Prot. Control Mod. Power Syst.,2023
4. Magness B.:Review of February 2021 Extreme Cold Weather Event – ERCOT Presentation. ERCOT.https://docs.house.gov/meetings/IF/IF02/20210324/111365/HHRG‐117‐IF02‐20210324‐SD007.pdf(2021)
5. Impact of Operational Flexibility on Electricity Generation Planning With Renewable and Carbon Targets