Identification of the Worst-Case Static Voltage Stability Margin Interval of AC/DC Power System Considering Uncertainty of Renewables

IF 6.9 2区 工程技术 Q2 ENERGY & FUELS CSEE Journal of Power and Energy Systems Pub Date : 2023-09-08 DOI:10.17775/CSEEJPES.2022.06390
Wanbin Liu;Shunjiang Lin;Yuerong Yang;Mingbo Liu;Qifeng Li
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Abstract

Calculation of static voltage stability margin (SVSM) of AC/DC power systems with lots of renewable energy sources (RESs) integration requires consideration of uncertain load growth and renewable energy generation output. This paper presents a bi-level optimal power flow (BLOPF) model to identify the worst-case SVSM of an AC/DC power system with line commutation converter-based HVDC and multi-terminal voltage sourced converter-based HVDC transmission lines. Constraints of uncertain load growth's hypercone model and control mode switching of DC converter stations are considered in the BLOPF model. Moreover, uncertain RES output fluctuations are described as intervals, and two three-level optimal power flow (TLOPF) models are established to identify interval bounds of the system worst-case SVSM. The two TLOPF models are both transformed into max-min bi-level optimization models according to independent characteristics of different uncertain variables. Then, transforming the inner level model into its dual form, max-min BLOPF models are simplified to single-level optimization models for direct solution. Calculation results on the modified IEEE-39 bus AC/DC case and an actual large-scale AC/DC case in China indicate correctness and efficiency of the proposed identification method.
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考虑可再生能源不确定性的交直流电力系统最坏情况下静态电压稳定裕度区间的确定
计算集成大量可再生能源(RES)的交直流电力系统的静态电压稳定裕度(SVSM)需要考虑不确定的负荷增长和可再生能源发电输出。本文提出了一种双电平最优功率流(BLOPF)模型,用于确定基于线路换向换流器的高压直流和基于多终端电压源换流器的高压直流输电线路的交直流电力系统的最坏情况 SVSM。BLOPF 模型考虑了不确定负荷增长的超锥模型和直流换流站控制模式切换的约束。此外,将不确定的可再生能源输出波动描述为区间,并建立了两个三级优化功率流(TLOPF)模型,以确定系统最坏情况 SVSM 的区间边界。根据不同不确定变量的独立特性,将两个 TLOPF 模型都转化为最大最小双级优化模型。然后,将内层模型转化为对偶形式,将 max-min BLOPF 模型简化为单层优化模型,以便直接求解。对修改后的 IEEE-39 母线交直流案例和中国实际大型交直流案例的计算结果表明,所提出的识别方法是正确和有效的。
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来源期刊
CiteScore
11.80
自引率
12.70%
发文量
389
审稿时长
26 weeks
期刊介绍: The CSEE Journal of Power and Energy Systems (JPES) is an international bimonthly journal published by the Chinese Society for Electrical Engineering (CSEE) in collaboration with CEPRI (China Electric Power Research Institute) and IEEE (The Institute of Electrical and Electronics Engineers) Inc. Indexed by SCI, Scopus, INSPEC, CSAD (Chinese Science Abstracts Database), DOAJ, and ProQuest, it serves as a platform for reporting cutting-edge theories, methods, technologies, and applications shaping the development of power systems in energy transition. The journal offers authors an international platform to enhance the reach and impact of their contributions.
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