An adaptive decision‐making approach for transmission expansion planning considering risk assessment of renewable energy extreme scenarios
-
Published:2023-08-29
Issue:18
Volume:17
Page:4107-4118
-
ISSN:1751-8687
-
Container-title:IET Generation, Transmission & Distribution
-
language:en
-
Short-container-title:IET Generation Trans & Dist
Author:
Zhao Pengfei1ORCID,
Xu Xinzhi2,
Dong Xiaochong1,
Gao Yi2,
Sun Yingyun1ORCID
Affiliation:
1. School of Electrical and Electronic Engineering North China Electric Power University Beijing China
2. Global Energy Interconnection Group Co., Ltd. Beijing China
Abstract
AbstractThe extreme power output scenarios of renewable energy sources (RES) proposed new challenges to the safe and stable operation of the power system. Transmission expansion planning (TEP) with large‐scale RES grid integration needs considering the risk of extreme scenarios. In this paper, an adaptive decision‐making approach for the TEP problem based on planning‐risk assessment‐replanning iterative process is proposed. The method obtains massive temporal and spatial correlated wind‐photovoltaic (PV) power output scenarios by generalizing the historical data to describe the uncertainties. A data‐driven load loss risk assessment model (RAM) based on the power system's actual operating state is built, referring to the degree of extreme scenario risks on the balance of supply and demand, and the probability of extreme scenario occurrence. The planning decision is progressively revised according to the risk assessment result. The Garver's 6‐bus system and the IEEE RTS 24‐bus system are adopted as simulation cases. The results show that the optimal expansion plans achieve a balance between the economy and robustness, which verifies the effectiveness of the proposed method.
Publisher
Institution of Engineering and Technology (IET)
Subject
Electrical and Electronic Engineering,Energy Engineering and Power Technology,Control and Systems Engineering
Reference34 articles.
1. International Renewable Energy Agency (IRENA): Renewable Energy Capacity Statistics(2023)
2. Review of restoration technology for renewable‐dominated electric power systems
3. A Review of Power System Flexibility With High Penetration of Renewables
4. Texas electric power crisis of 2021 warns of a new blackout mechanism;Zhang G.;CSEE J Power Energy Syst.,2022
5. Low‐carbon transformation of electric system against power shortage in China;Wang B.;Policy Optimization. Energies.,2022
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. An Extreme Scenario Reduction Algorithm for Multi-time Scale Net-Load;2023 IEEE 7th Conference on Energy Internet and Energy System Integration (EI2);2023-12-15