1.现代电力系统仿真控制与绿色电能新技术教育部重点实验室(东北电力大学),吉林省吉林市132012
2.国网电力科学研究院有限公司(南瑞集团有限公司),江苏省南京市211106
郄朝辉(1985—),男,博士研究生,正高级工程师,主要研究方向:电力系统安全稳定分析控制及低频减载、故障解列、备自投等安全自动装置的研发。E-mail:qiezhaohui@139.com
付麟博(1996—),女,博士研究生,主要研究方向:微电网能量管理与交易。E-mail:fulinbo123@aliyun.com
姜涛(1983—),男,通信作者,博士,教授,博士生导师,主要研究方向:电力系统安全性与稳定性、可再生能源集成、综合能源系统。E-mail:electricpowersys@163.com
收稿:2025-11-01,
修回:2026-02-12,
网络首发:2026-04-27,
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郄朝辉,付麟博,姜涛等.计及时序特征的电力系统高风险运行方式在线辨识[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20251101005.
QIE Zhaohui,FU Linbo,JIANG Tao,et al.Online Identification of High-risk Operation Modes for Power Systems Considering Temporal Features[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20251101005.
郄朝辉,付麟博,姜涛等.计及时序特征的电力系统高风险运行方式在线辨识[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20251101005. DOI:
QIE Zhaohui,FU Linbo,JIANG Tao,et al.Online Identification of High-risk Operation Modes for Power Systems Considering Temporal Features[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20251101005. DOI:
面向高比例新能源并网电力系统强时序耦合与高不确定性的特点,传统在线风险辨识方法保守且难以捕捉时序关联风险,提出一种计及时序特征的电力系统高风险运行方式在线辨识方法,辨识时序关联与系统稳定风险。在时序风险辨识方面,基于机组分段爬坡速率动态构建系统爬坡能力,结合净负荷不确定性域,提出爬坡不足引发时序高风险运行方式的识别方法。在稳定风险辨识方面,提出“离线构建-在线检查”的凸包策略,利用样本子集与增量式Quickhull算法进行稳定运行方式安全区域的离线构建,通过线性约束的在线检查,快速识别高风险运行方式。实际电网算例验证表明,所提方法能有效识别系统爬坡不足的时序高风险运行方式,显著提升了输电断面模糊区的辨识精度,在样本偏态情况下仍具有泛化鲁棒性,为电力系统的安全经济运行提供了技术支撑。
Facing the features of strong temporal coupling and high uncertainty in power systems with integration of high proportion of renewable energy
traditional online risk identification methods are conservative and difficult to capture temporal correlation risks
an online identification method of high-risk operation modes for power systems considering temporal features is proposed to identify temporal correlation and system stability risks. In terms of temporal risk identification
based on unit segmented ramp rates
system ramp capability is dynamically constructed
combined with net load uncertainty region
an identification method for temporal high-risk operation modes caused by insufficient ramp is proposed. In terms of stability risk identification
a "offline construction - online inspection" convex hull strategy is proposed
which uses sample subsets and incremental Quickhull algorithm to offline construct the safe region of stable operation modes
through online inspection of linear constraints
high-risk operation modes are quickly identified. Actual power grid case verification shows that the proposed method can effectively identify temporal high-risk operation modes caused by insufficient system ramp
significantly improve the identification accuracy of the fuzzy region of transmission sections
still have generalization robustness under sample skewness conditions
and provide technical support for safe and economic operation of power systems.
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