Online Monitoring Method for Inertial Support Capacity of Point-to-Grid in New Power Systems

doi:10.16183/j.cnki.jsjtu.2023.029

Abstract

Abstract:

An accurate and timely monitoring for the inertia support capability of the point of interconnection of aggregated sources to the grid in a low-inertia new power system is crucial for the safety, stability, and economic operation of the system. In order to explain the basic idea of the online point-to-grid inertia monitoring method, the definition of inertia of power system based on the swing equation and existing online monitoring methods are analyzed. Then, in order to improve the accuracy of the existing online inertia monitoring method, an equivalent inertia constant identification method based on the regression method is developed. Combining the proposed inertia constant identification method with the online inertia monitoring method, a systematic method for online monitoring of the inertia support capacity of point-to-grid in new power system is developed based on synchronous phasor measurement units. Finally, the simulation analysis of a modified New England 10-machine 39-bus system proves the accuracy and the feasibility of the developed real-time inertia monitoring method for the new power system.

Key words: new power system, inertia monitoring, virtual synchronous generator, equivalent inertia constant

CLC Number:

TM712

DENG Xiaoyu, LIU Muyang, CHANG Xiqiang, NAN Dongliang, MO Ruo, CHEN Junru. Online Monitoring Method for Inertial Support Capacity of Point-to-Grid in New Power Systems[J]. Journal of Shanghai Jiao Tong University, 2024, 58(9): 1390-1399.

Figures/Tables 10

Fig.1

Fig.2

Fig.3

Fig.4

Tab.1

Tab.2

Fig.5

Fig.6

Fig.7

Tab.3

References 33

[1]	巩伟峥, 许凌, 姚寅. 计及风速分布与机组惯量转化不确定性的风电场可用惯量估计[J]. 上海交通大学学报, 2021, 55 (Sup.2): 51-59.
	GONG Weizheng, XU Ling, YAO Yin. Estimation of wind farm available inertia considering uncertainty of wind speed distribution and unit Inertia transformation[J]. Journal of Shanghai Jiao Tong University, 2021, 55 (Sup.2): 51-59.
[2]	孙华东, 王宝财, 李文锋, 等. 高比例电力电子电力系统频率响应的惯量体系研究[J]. 中国电机工程学报, 2020, 40(16): 5179-5192.
	SUN Huadong, WANG Baocai, LI Wenfeng, et al. Research on inertia system of frequency response for power system with high penetration electronics[J]. Proceedings of the CSEE, 2020, 40(16): 5179-5192.
[3]	文云峰, 杨伟峰, 汪荣华, 等. 构建100%可再生能源电力系统述评与展望[J]. 中国电机工程学报, 2020, 40(6): 1843-1856.
	WEN Yunfeng, YANG Weifeng, WANG Ronghua, et al. Review and prospect of toward 100% renewable energy power systems[J]. Proceedings of the CSEE, 2020, 40(6): 1843-1856.
[4]	刘中建, 周明, 李昭辉, 等. 高比例新能源电力系统的惯量控制技术与惯量需求评估综述[J]. 电力自动化设备, 2021, 41(12): 1-11.
	LIU Zhongjian, ZHOU Ming, LI Zhaohui, et al. Review of inertia control technology and requirement evaluation in renewable-dominant power system[J]. Electric Power Automation Equipment, 2021, 41(12): 1-11.
[5]	陈亦平, 卓映君, 刘映尚, 等. 高比例可再生能源电力系统的快速频率响应市场发展与建议[J]. 电力系统自动化, 2021, 45(10): 174-183.
	CHEN Yiping, ZHUO Yingjun, LIU Yingshang, et al. Development and recommendation of fast frequency response market for power system with high proportion of renewable energy[J]. Automation of Electric Power Systems, 2021, 45(10): 174-183.
[6]	邵昊舒, 蔡旭. 大型风电机组惯量控制研究现状与展望[J]. 上海交通大学学报, 2018, 52(10): 1166-1177. doi: 10.16183/j.cnki.jsjtu.2018.10.004
	SHAO Haoshu, CAI Xu. Research status and prospect of inertia control for large scale wind turbines[J]. Journal of Shanghai Jiao Tong University, 2018, 52(10): 1166-1177.
[7]	赵珊珊, 周勤勇, 赵强, 等. 计及频率约束的风电最大接入比例研究[J]. 中国电机工程学报, 2018, 38 (Sup.1): 24-31.
	ZHAO Shanshan, ZHOU Qinyong, ZHAO Qiang, et al. Study on the maximum access ratio of wind power considering frequency constraint[J]. Proceedings of the CSEE, 2018, 38 (Sup.1): 24-31.
[8]	吕志鹏, 盛万兴, 刘海涛, 等. 虚拟同步机技术在电力系统中的应用与挑战[J]. 中国电机工程学报, 2017, 37(2): 349-360.
	LÜ Zhipeng, SHENG Wanxing, LIU Haitao, et al. Application and challenge of virtual synchronous machine technology in power system[J]. Proceedings of the CSEE, 2017, 37(2): 349-360.
[9]	CHEN J R, LIU M Y, MILANO F, et al. 100% Converter-interfaced generation using virtual synchronous generator control: A case study based on the Irish system[J]. Electric Power Systems Research, 2020, 187: 106475.
[10]	李少林, 王伟胜, 张兴, 等. 基于频率响应区间划分的风电机组虚拟惯量模糊自适应控制[J]. 电网技术, 2021, 45(5): 1658-1665.
	LI Shaolin, WANG Weisheng, ZHANG Xing, et al. Fuzzy adaptive virtual inertia control strategy of wind turbines based on system frequency response interval division[J]. Power System Technology, 2021, 45(5): 1658-1665.
[11]	钟庆昌. 虚拟同步机与自主电力系统[J]. 中国电机工程学报, 2017, 37(2): 336-349.
	ZHONG Qingchang. Virtual synchronous machines and autonomous power systems[J]. Proceedings of the CSEE, 2017, 37(2): 336-349.
[12]	文云峰, 杨伟峰, 林晓煌. 低惯量电力系统频率稳定分析与控制研究综述及展望[J]. 电力自动化设备, 2020, 40(9): 211-222.
	WEN Yunfeng, YANG Weifeng, LIN Xiaohuang. Review and prospect of frequency stability analysis and control of low-inertia power systems[J]. Electric Power Automation Equipment, 2020, 40(9): 211-222.
[13]	柯贤波, 张文朝, 李朋旺, 等. 高风电渗透率系统的模糊自适应虚拟惯量控制[J]. 电网技术, 2020, 44(6): 2127-2136.
	KE Xianbo, ZHANG Wenchao, LI Pengwang, et al. Fuzzy adaptive virtual inertia control for high wind power penetration system[J]. Power System Technology, 2020, 44(6): 2127-2136.
[14]	任凯奇, 张东英, 黄越辉, 等. 基于新能源出力比例的大规模系统惯量估计[J]. 电网技术, 2022, 46(4): 1307-1315.
	REN Kaiqi, ZHANG Dongying, HUANG Yuehui, et al. Large-scale system inertia estimation based on new energy output ratio[J]. Power System Technology, 2022, 46(4): 1307-1315.
[15]	李美依, 黄文焘, 邰能灵, 等. 频率扰动下虚拟同步电机控制型分布式电源自适应惯性控制策略[J]. 电网技术, 2020, 44(4): 1525-1533.
	LI Meiyi, HUANG Wentao, TAI Nengling, et al. Adaptive inertial control strategy for inverter interfaced distributed generator based on virtual synchronous generator under frequency disturbances[J]. Power System Technology, 2020, 44(4): 1525-1533.
[16]	张武其, 文云峰, 迟方德, 等. 电力系统惯量评估研究框架与展望[J]. 中国电机工程学报, 2021, 41(20): 6842-6856.
	ZHANG Wuqi, WEN Yunfeng, CHI Fangde, et al. Research framework and prospect on power system inertia estimation[J]. Proceedings of the CSEE, 2021, 41(20): 6842-6856.
[17]	CAI G W, WANG B, YANG D Y, et al. Inertia estimation based on observed electromechanical oscillation response for power systems[J]. IEEE Transactions on Power Systems, 2019, 34(6): 4291-4299.
[18]	YOU S T, LIU Y, KOU G F, et al. Non-invasive identification of inertia distribution change in high renewable systems using distribution level PMU[J]. IEEE Transactions on Power Systems, 2018, 33(1): 1110-1112.
[19]	刘方蕾, 胥国毅, 王凡, 等. 基于差值计算法的系统分区惯量评估方法[J]. 电力系统自动化, 2020, 44(20): 46-53.
	LIU Fanglei, XU Guoyi, WANG Fan, et al. Assessment method of system partition inertia based on differential calculation method[J]. Automation of Electric Power Systems, 2020, 44(20): 46-53.
[20]	SCHIFFER J, ARISTIDOU P, ORTEGA R. Online estimation of power system inertia using dynamic regressor extension and mixing[J]. IEEE Transactions on Power Systems, 2019, 34(6): 4993-5001.
[21]	LIU M Y, CHEN J R, MILANO F. On-line inertia estimation for synchronous and non-synchronous devices[J]. IEEE Transactions on Power Systems, 2021, 36(3): 2693-2701.
[22]	MILANO F, ORTEGA Á. A method for evaluating frequency regulation in an electrical grid-part I: Theory[J]. IEEE Transactions on Power Systems, 2021, 36(1): 183-193.
[23]	ORTEGA Á, MILANO F. A method for evaluating frequency regulation in an electrical grid-part II: Applications to non-synchronous devices[J]. IEEE Transactions on Power Systems, 2021, 36(1): 194-203.
[24]	CHEN J R, LIU M Y, MILANO F, et al. Adaptive virtual synchronous generator considering converter and storage capacity limits[J]. CSEE Journal of Power & Energy Systems, 2020, 8(2): 580-590.
[25]	陈来军, 王任, 郑天文, 等. 基于参数自适应调节的虚拟同步发电机暂态响应优化控制[J]. 中国电机工程学报, 2016, 36(21): 5724-5731.
	CHEN Laijun, WANG Ren, ZHENG Tianwen, et al. Optimal control of transient response of virtual synchronous generator based on adaptive parameter adjustment[J]. Proceedings of the CSEE, 2016, 36(21): 5724-5731.
[26]	MILANO F, ORTEGA Á. Frequency divider[J]. IEEE Transactions on Power Systems, 2017, 32(2): 1493-1501.
[27]	韦钢. 电力系统分析基础[M]. 北京: 中国电力出版社, 2006.
	WEI Gang. Fundamentals of power system analysis[M]. Beijing: China Electric Power Press, 2006.
[28]	KUNDUR P, BALU N J, LAUBY M G. Power system stability and control[M]. New York: McGraw-Hill, 1994.
[29]	LIU J H, WANG C, BI T S, et al. Online estimation of POI-level aggregated inertia considering frequency spatial correlation[J]. IEEE Transactions on Power Systems, 2023, 38(4): 3232-3244.
[30]	AEMC. System security market frameworks review, final report[R]. Sydney: AEMC, 2017.
[31]	MILANO F. Power system scripting[M]//Power system modelling and scripting. Berlin, Heidelberg: Springer, 2010: 31-58.
[32]	MILANO F. A python-based software tool for power system analysis[C]//2013 IEEE Power & Energy Society General Meeting. Vancouver, Canada: IEEE, 2013: 1-5.
[33]	MILANO F, ZÁRATE-MIÑANO R. A systematic method to model power systems as stochastic differential algebraic equations[J]. IEEE Transactions on Power Systems, 2013, 28(4): 4537-4544.

母线序号	发电机编号	装机量/MW	有功出力/MW
33	4号VSG	1000	632
35	6号VSG	1000	650
37	1号WPP	606	540
38	2号WPP	900	830

编号	母线	发电机编号	等效惯性常数/ [MW·s·(MV·A)^-1]
1	39	1号G	100
2	31	2号G	60.6
3	32	3号G	71.6
4	34	5号G	52
5	36	7号G	52.8
6	33	4号VSG	120
7	35	6号VSG	100

VSG	时间窗口	H^*/[MW·s· (MV·A)^-1]	H/[MW·s· (MV·A^-1)]	ψ/%
4号	1	100.20	100.00	0.20
	2	70.33	70.00	0.48
6号	1	120.39	120.00	0.33
	2	150.63	150.00	0.42