Power Grid Voltage Phasor Trajectory Fitting and Transient Stability Evaluation Index Construction Based on Alternate Direction Multiplier Method

doi:10.12204/j.issn.1000-7229.2023.12.012

Abstract

Abstract:

The quantitative assessment of the transient stability of a power system constitutes the basis of the online security defense of a large power grid, and the construction of a transient stability prediction index based on the dynamic trajectory information of the power grid is key. The grid voltage phasor trajectory information contains richer stable behavior characteristics. In this study, using a dual-machine system as an example, the evolution law between the transient energy conversion of the generator and the voltage phase trajectory is first analyzed from the perspective of trajectory geometry. The reasoning is based on the EEAC. Thus, the universality of the multi-machine system is verified. To realize the fast prediction of transient stability, a trajectory fitting method based on the alternating direction multiplier method is proposed, which has obvious advantages in fitting accuracy and speed. Based on the arc length distance of the voltage phasor trajectory fitting curve as the data support, a fast prediction index of transient stability is constructed. Finally, the evaluation accuracy of the proposed method is verified using the simulation data of a 10-machine, 39-node system in New England and a provincial power grid as examples.

Key words: voltage phasor trajectory, trajectory fitting, transient stability, evaluation index

CLC Number:

TM712

MA Haibin, LIU Daowei, ZHAO Gaoshang, YANG Hongying, YUAN Fei, GAO Shen. Power Grid Voltage Phasor Trajectory Fitting and Transient Stability Evaluation Index Construction Based on Alternate Direction Multiplier Method[J]. ELECTRIC POWER CONSTRUCTION, 2023, 44(12): 136-147.

Figures/Tables 22

Fig.1 Generator voltage phase trajectory

Fig.2 Two-generator system model

Fig.3 Power angle time domain curve

Fig.4 Simulation curve of voltage trajectory in steady state

Fig.5 Simulation curve of voltage trajectory in unstable state

Fig.6 Schematic diagram of track under steady state

Fig.7 Schematic diagram of track under unstable state

Fig.8 Equivalent schematic diagram of two clusters

Fig.9 Schematic diagram of voltage change

Fig.10 SVR schematic diagram of voltage trace

Fig.11 Transient assessment method

Fig.12 39-node system diagram

Fig.13 Comparison of power angle curves during transient stability

Fig.14 Voltage phasor trajectories at different cut-off times

Fig.15 Comparison of evaluation results under different resection times

Fig.16 Relative power angle curve

Fig.17 Comparison diagram of fitting curve

Fig.18 Fitting time comparison chart

Fig.19 Power angle and voltage phase trajectory curve of No. 3 power plant

Fig.20 Evaluation index of No. 3 power plant

Fig.21 Power angle and voltage phase trajectory curve of No.18 power plant

Fig.22 Evaluation index of No.18 power plant

References 32

[1]	吕鹏飞. 交直流混联电网下直流输电系统运行面临的挑战及对策[J]. 电网技术, 2022, 46(2): 503-510.
	LÜ Pengfei. Research on HVDC operation characteristics under influence of hybrid AC/DC power grids[J]. Power System Technology, 2022, 46(2): 503-510.
[2]	张勋奎. 以新能源为主体的新型电力系统发展路线图[J]. 分布式能源, 2021, 6(6): 1-8.
	ZHANG Xunkui. A roadmap for developing a new power system with new energy as the main body[J]. Distributed Energy, 2021, 6(6): 1-8.
[3]	刘道伟, 张东霞, 孙华东, 等. 时空大数据环境下的大电网稳定态势量化评估与自适应防控体系构建[J]. 中国电机工程学报, 2015, 35(2): 268-276.
	LIU Daowei, ZHANG Dongxia, SUN Huadong, et al. Construction of stability situation quantitative assessment and adaptive control system for large-scale power grid in the spatio-temporal big data environment[J]. Proceedings of the CSEE, 2015, 35(2): 268-276.
[4]	李柏青, 刘道伟, 秦晓辉, 等. 信息驱动的大电网全景安全防御概念及理论框架[J]. 中国电机工程学报, 2016, 36(21): 5796-5805, 6022.
	LI Baiqing, LIU Daowei, QIN Xiaohui, et al. Concept and theory framework of panoramic security defense for bulk power system driven by information[J]. Proceedings of the CSEE, 2016, 36(21): 5796-5805, 6022.
[5]	王继业, 刘道伟, 马世英, 等. 信息驱动的全球能源互联网全景安全防御系统[J]. 电力信息与通信技术, 2016, 14(3): 13-19.
	WANG Jiye, LIU Daowei, MA Shiying, et al. An information-driven panoramic security defense system for global energy interconnection[J]. Electric Power Information and Communication Technology, 2016, 14(3): 13-19.
[6]	王伟胜, 林伟芳, 何国庆, 等. 美国得州2021年大停电事故对我国新能源发展的启示[J]. 中国电机工程学报, 2021, 41(12): 4033-4043.
	WANG Weisheng, LIN Weifang, HE Guoqing, et al. Enlightenment of 2021 texas blackout to the renewable energy development in China[J]. Proceedings of the CSEE, 2021, 41(12): 4033-4043.
[7]	滕苏郸, 宫一玉, 张璞, 等. 2019年8月9日英国大停电事故分析及对北京电网安全稳定运行的启示[J]. 电力勘测设计, 2020(2): 5-8.
	TENG Sudan, GONG Yiyu, ZHANG Pu, et al. Analysis of blackout accident in Britain on August 9, 2019 and its enlightenment to the safe and stable operation of Beijing power grid[J]. Electric Power Survey & Design, 2020(2): 5-8.
[8]	胡秦然, 丁昊晖, 陈心宜, 等. 美国加州2020年轮流停电事故分析及其对中国电网的启示[J]. 电力系统自动化, 2020, 44(24): 11-18.
	HU Qinran, DING Haohui, CHEN Xinyi, et al. Analysis on rotating power outage in California, USA in 2020 and its enlightenment to power grid of China[J]. Automation of Electric Power Systems, 2020, 44(24): 11-18.
[9]	马晨霄, 戴则梅, 胡超凡, 等. 应对严重自然灾害的省级高压网架增强辅助策略[J]. 电力建设, 2022, 43(6): 119-127. doi: 10.12204/j.issn.1000-7229.2022.06.013
	MA Chenxiao, DAI Zemei, HU Chaofan, et al. Strengthening auxiliary strategy of provincial high-voltage power grid in response to severe natural disasters[J]. Electric Power Construction, 2022, 43(6): 119-127. doi: 10.12204/j.issn.1000-7229.2022.06.013
[10]	薛禹胜. EEAC与直接法的机理比较(一): 受扰程度函数[J]. 电力系统自动化, 2001, 25(11): 6-11.
	XUE Yusheng. A critical comparison of various methods for transient stability assessment part one disturbed-measure functions[J]. Automation of Electric Power Systems, 2001, 25(11): 6-11.
[11]	薛禹胜. EEAC与直接法的机理比较(三)定性判稳与定量分析[J]. 电力系统自动化, 2001, 25(13): 1-5, 25.
	XUE Yusheng. A critical comparison of variousmethodsfor transient stability assessment part three qualitative criterion and quantitative analysis[J]. Automation of Electric Power Systems, 2001, 25(13): 1-5, 25.
[12]	梁卓航, 时纯, 李岩松, 等. 换相失败下STATCOM助增暂态过电压机理与优化策略[J]. 电力建设, 2022, 43(6): 66-74. doi: 10.12204/j.issn.1000-7229.2022.06.007
	LIANG Zhuohang, SHI Chun, LI Yansong, et al. Mechanism of STATCOM assisting transient voltage under commutation failure at weak sending end system and its optimization strategy[J]. Electric Power Construction, 2022, 43(6): 66-74. doi: 10.12204/j.issn.1000-7229.2022.06.007
[13]	任俊谕. 数据驱动的电力系统暂态稳定分析及预防控制研究[D]. 武汉: 华中科技大学, 2002.
	REN Junyu. Research on data-driven transient stability analysis and preventive control of power system[D]. Wuhan: Huazhong University of Science and Technology, 2002.
[14]	刘光萌. 基于数据驱动的电力系统直接法暂态稳定分析研究[D]. 北京: 华北电力大学, 2022.
	LIU Guangmeng. Research on direct transient stability analysis of power system based on data driving[D]. Beijing: North China Electric Power University, 2022.
[15]	李峰. 数据-物理驱动的电网暂态稳定评估方法研究[D]. 南京: 东南大学, 2021.
	LI Feng. Research on data-physical-driven transient stability evaluation method of power grid[D]. Nanjing: Southeast University, 2021.
[16]	汪小明, 刘涤尘, 吴军, 等. 基于能量函数法的电网暂态稳定性分析[J]. 电网技术, 2011, 35(8): 114-118.
	WANG Xiaoming, LIU Dichen, WU Jun, et al. Energy function-based power system transient stability analysis[J]. Power System Technology, 2011, 35(8): 114-118.
[17]	周二专, 冯东豪, 严剑峰, 等. 秒级响应电网在线分析软件平台[J]. 电网技术, 2020, 44(9): 3474-3480.
	ZHOU Erzhuan, FENG Donghao, YAN Jianfeng, et al. A software platform for second-order responsiveness power grid online analysis[J]. Power System Technology, 2020, 44(9): 3474-3480.
[18]	孙树明, 谢昶, 吕颖, 等. 电力系统在线安全稳定分析应用模式[J]. 电网技术, 2015, 39(10): 2875-2881.
	SUN Shuming, XIE Chang, LÜ Ying, et al. Power system online security and stability analysis application modes[J]. Power System Technology, 2015, 39(10): 2875-2881.
[19]	范新凯, 杨松浩, 赵一铭, 等. 基于相轨迹凹凸性的暂态失稳判据准确性验证[J]. 电力自动化设备, 2021, 41(1): 159-165, 171, 166.
	FAN Xinkai, YANG Songhao, ZHAO Yiming, et al. Accuracy verification of transient instability criterion based on concavity and convexity of phase trajectory[J]. Electric Power Automation Equipment, 2021, 41(1): 159-165, 171, 166.
[20]	杨松浩, 王怀远, 苏福, 等. 基于相轨迹凹凸性的暂态不稳定性判别方法的分析比较[J]. 电力自动化设备, 2017, 37(9): 193-198.
	YANG Songhao, WANG Huaiyuan, SU Fu, et al. Analysis and comparison of transient instability detection methods based on convexity and concavity of phase trajectory[J]. Electric Power Automation Equipment, 2017, 37(9): 193-198.
[21]	褚云龙, 谢欢. 基于相图凸凹性和系统辨识理论的暂态稳定性快速预测方法[J]. 电网技术, 2008, 32(5): 59-65.
	CHU Yunlong, XIE Huan. A method to fast predict power system transient stability based on concave-convex of phase diagram and system identification theory[J]. Power System Technology, 2008, 32(5): 59-65.
[22]	马世英, 朱存浩, 郑超, 等. 扩展相轨迹特征解析及暂态稳定判别方法研究[J]. 中国电机工程学报, 2020, 40(20): 6516-6527.
	MA Shiying, ZHU Cunhao, ZHENG Chao, et al. Analysis of extended phase trajectory characteristics and transient stability identification[J]. Proceedings of the CSEE, 2020, 40(20): 6516-6527.
[23]	马美玲, 王杰, 王子强, 等. 多机系统全局相轨线的暂态稳定性分析[J]. 中国电机工程学报, 2019, 39(15): 4385-4395.
	MA Meiling, WANG Jie, WANG Ziqiang, et al. Transient stability analysis of the global phase portraits in multi-machine system[J]. Proceedings of the CSEE, 2019, 39(15): 4385-4395.
[24]	刘道伟, 马世英, 李柏青, 等. 基于响应的电网暂态稳定态势在线量化评估方法[J]. 中国电机工程学报, 2013, 33(4): 85-95, 12.
	LIU Daowei, MA Shiying, LI Baiqing, et al. Quantitative method for on-line power system transient stability assessment based on response information[J]. Proceedings of the CSEE, 2013, 33(4): 85-95, 12.
[25]	邓晖, 赵晋泉, 吴小辰, 等. 基于受扰电压轨迹的电力系统暂态失稳判别: (一)机理与方法[J]. 电力系统自动化, 2013, 37(16): 27-32, 46.
	DENG Hui, ZHAO Jinquan, WU Xiaochen, et al. Transient instability detection of power system based on perturbed voltage trajectories part one theory and method[J]. Automation of Electric Power Systems, 2013, 37(16): 27-32, 46.
[26]	穆钢, 王仲鸿, 韩英铎, 等. 暂态稳定性的定量分析-轨迹分析法[J]. 中国电机工程学报, 1993, 13(3): 23-30.
	MU Gang, WANG Zhonghong, HAN Yingduo, et al. A new method for quantitative assessment of the transient stability of power systems-trajectory analysis method[J]. Proceedings of the CSEE, 1993, 13(3): 23-30.
[27]	阮佳程. 基于轨迹断面特征根的电力系统动态稳定评估[D]. 济南: 山东大学, 2022.
	RUAN Jiacheng. Dynamic stability assessment of power system based on characteristic root of trajectory section[D]. Jinan: Shandong University, 2022.
[28]	刘鸣, 王长江, 李斌, 等. 基于轨迹簇和MBLDA的受端电网暂态电压稳定评估[J]. 电力系统保护与控制, 2021, 49(19): 27-37.
	LIU Ming, WANG Changjiang, LI Bin, et al. Transient voltage stability evaluation of a receiving-end power grid based on a trajectory cluster and MBLDA[J]. Power System Protection and Control, 2021, 49(19): 27-37.
[29]	李宏浩. 基于深度强化学习的暂态稳定紧急控制研究[D]. 北京: 北京交通大学, 2022.
	LI Honghao. Research on emergency control of transient stability based on deep reinforcement learning[D]. Beijing: Beijing Jiaotong University, 2022.
[30]	梁俊宇, 杨洋, 李怡雪, 等. 基于迁移学习的电能替代节能量在线估计方法[J]. 电力建设, 2021, 42(8): 29-37. doi: 10.12204/j.issn.1000-7229.2021.08.004
	LIANG Junyu, YANG Yang, LI Yixue, et al. Online energy-saving estimation of electric energy substitution applying transfer learning[J]. Electric Power Construction, 2021, 42(8): 29-37. doi: 10.12204/j.issn.1000-7229.2021.08.004
[31]	王哲, 万宝, 凌天晗, 等. 基于谱聚类和LSTM神经网络的电动公交车充电负荷预测方法[J]. 电力建设, 2021, 42(6): 58-66. doi: 10.12204/j.issn.1000-7229.2021.06.006
	WANG Zhe, WAN Bao, LING Tianhan, et al. Electric bus charging load forecasting method based on spectral clustering and LSTM neural network[J]. Electric Power Construction, 2021, 42(6): 58-66. doi: 10.12204/j.issn.1000-7229.2021.06.006
[32]	李建宜, 李鹏, 徐晓春, 等. 基于综合概率模型与深度学习的智能电网功率-电压映射方法[J]. 电力建设, 2022, 43(2): 37-44. doi: 10.12204/j.issn.1000-7229.2022.02.005
	LI Jianyi, LI Peng, XU Xiaochun, et al. Power-voltage mapping method based on comprehensive probability model and deep learning for smart grid[J]. Electric Power Construction, 2022, 43(2): 37-44. doi: 10.12204/j.issn.1000-7229.2022.02.005