Assessment Method of Regional Equivalent Inertia of New Energy Power System Based on Measured Data
Ma Yanfeng1, Li Jinyuan1, Wang Zijian1, Zhao Shuqiang1, Guo Runsheng2
1. Key Laboratory of Distributed Energy Storage and Microgrid in Hebei Province North China Electric Power University Baoding 071003 China; 2. State Grid Shuozhou Electric Power Company Shuozhou 036002 China
Abstract：The high proportion of new energy connected to the grid makes the problem of low inertia of the power system increasingly prominent, and the frequency problem more frequency problem is more serious. In order to improve the stable operation ability of the new energy power system, it is necessary to evaluate the level of system inertia and analyze the influence of new energy power generation type, permeability and virtual inertia control mode on the real-time inertia of the system At present, the most widely used evaluation methods have the problem of a large number of measurement data and difficulty in obtaining them. The evaluation accuracy is affected by the selection of frequency sampling points, measurement devices, and the processing methods of measurement data. To address these issues, this paper proposes a method for assessing the regional equivalent inertia of new energy system based on measured data. The active power, frequency, and voltage data are used to accurately calculate the inertia, measurement data are few and easy to obtain, which reduces the data processing steps and is still applicable when the internal parameters of the new energy units are unknown. Firstly, the virtual inertia response characteristics of wind power and photovoltaic power and their influence on the frequency stability of the system are analyzed. Secondly, on the basis of analyzing the principle of regional equivalent inertia assessment, the expression of regional equivalent inertia of new energy system is derived by considering the load voltage characteristics. Finally, in order to reduce the error caused by the frequency distribution characteristics, the selection of sampling points and the calculation method of regional frequency are proposed from the perspective of weighted average. Sampling points are determined according to the real-time inertia monitoring results of the SCADA system, which saves the installation cost of PMUs (phasor measurement units) and avoids large amount of calculations. In addition, the low-pass filter and sliding window technology are used to process the measurement data, which improves the accuracy of the inertia assessment results. The simulation results show that the proposed method can accurately assess the regional equivalent inertia of both traditional and new energy power system. Wind power system with additional frequency control can provide virtual inertia much larger than the actual inertia, but due to the limitation of actual speed and output, its virtual inertia response time is short, and the support power can be limited. The virtual inertia response time of the PV system controlled by VSG (virtual synchronous generators) is fast, and can provide support power according to the dispatching needs, but it needs to be equipped with large energy storage devices. The following conclusions can be drawn from the simulation analysis: (1) Changing the new energy output and virtual inertia control parameters will cause a change in the equivalent inertia and results. (2) The PV virtual inertia control using VSG has a long response time, more flexible output, and better frequency regulation effect, but it requires large-capacity energy storage, the economic benefits are not good. The wind power system with additional frequency control does not need energy storage, and the primary investment is small, but with the recovery of rotor speed, it is possible to cause a secondary reduction in system frequency. (3) From the perspective of technical economy, when the system inertia is insufficient, the power support brought by dispatching means should be considered first, if new energy power is used to provide power support, priority should be given to the use of wind turbine rotor kinetic energy control, when the actual output and rotor speed do not meet the requirements, then consider the configuration of energy storage for photovoltaic or wind turbine. Therefore, how to balance the economy and the output of new energy is a problem that needs further research.
马燕峰, 李金媛, 王子建, 赵书强, 郭润生. 基于量测数据的新能源电力系统区域等效惯量评估方法[J]. 电工技术学报, 2024, 39(17): 5406-5421.
Ma Yanfeng, Li Jinyuan, Wang Zijian, Zhao Shuqiang, Guo Runsheng. Assessment Method of Regional Equivalent Inertia of New Energy Power System Based on Measured Data. Transactions of China Electrotechnical Society, 2024, 39(17): 5406-5421.
[1] 滕贤亮, 谈超, 昌力, 等. 高比例新能源电力系统有功功率与频率控制研究综述及展望[J]. 电力系统自动化, 2023, 47(15): 12-35. Teng Xianliang, Tan Chao, Chang Li, et al.Review and prospect of research on active power and frequency control in power system with high proportion of renewable energy[J]. Automation of Electric Power Systems, 2023, 47(15): 12-35. [2] 曾辉, 孙峰, 李铁, 等. 澳大利亚“9·28”大停电事故分析及对中国启示[J]. 电力系统自动化, 2017, 41(13): 1-6. Zeng Hui, Sun Feng, Li Tie, et al.Analysis of “9·28” blackout in South Australia and its enlightenment to China[J]. Automation of Electric Power Systems, 2017, 41(13): 1-6. [3] 樊陈, 姚建国, 张琦兵, 等. 英国“8·9”大停电事故振荡事件分析及思考[J]. 电力工程技术, 2020, 39(4): 34-41. Fan Chen, Yao Jianguo, Zhang Qibing, et al.Reflection and analysis for oscillation of the blackout event of 9 August 2019 in UK[J]. Electric Power Engineering Technology, 2020, 39(4): 34-41. [4] 贾焦心, 颜湘武, 李铁成, 等. 基于改进RoCoF测量方法的储能辅助光伏机组快速调频策略[J]. 电工技术学报, 2022, 37(增刊1): 93-105. Jia Jiaoxin, Yan Xiangwu, Li Tiecheng, et al.Fast frequency regulation strategy of PV power system assisted by energy storage based on improved measurement method of RoCoF[J]. Transactions of China Electrotechnical Society, 2022, 37(S1): 93-105. [5] 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. [6] 李兆伟, 方勇杰, 吴雪莲, 等. 频率紧急控制中动作时延和措施量对低惯量系统控制有效性的影响分析[J/OL]. 电工技术学报, 2023: 1-13. https://doi.org/10.19595/j.cnki.1000-6753.tces.231175. Li Zhaowei, Fang Yongjie, Wu Xuelian, et al. Influence of action delay and amount on the control effectiveness of low inertia systems in frequency emergency control[J/OL]. Transactions of China Electrotechnical Society, 2023: 1-13. https://doi.org/10.19595/j.cnki.1000-6753.tces.231175. [7] 李东东, 张佳乐, 徐波, 等. 考虑频率分布特性的新能源电力系统等效惯量评估[J]. 电网技术, 2020, 44(8): 2913-2921. Li Dongdong, Zhang Jiale, Xu Bo, et al.Equivalent inertia assessment in renewable power system considering frequency distribution properties[J]. Power System Technology, 2020, 44(8): 2913-2921. [8] 曾辉, 苏安龙, 葛延峰, 等. 考虑负荷特性的区域电网在线转动惯量快速估计算法[J]. 电网技术, 2023, 47(2): 423-436. Zeng Hui, Su Anlong, Ge Yanfeng, et al.Fast estimation algorithm for on-line moment of inertia of regional power grid considering load characteristics[J]. Power System Technology, 2023, 47(2): 423-436. [9] 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. [10] 刘方蕾, 毕天姝, 闫家铭, 等. 基于PMU同步测量的分区惯量估计方法[J]. 华北电力大学学报(自然科学版), 2020, 47(3): 19-26. Liu Fanglei, Bi Tianshu, Yan Jiaming, et al.Area inertia estimation based on PMU synchronous measurements[J]. Journal of North China Electric Power University (Natural Science Edition), 2020, 47(3): 19-26. [11] 曾繁宏, 张俊勃. 电力系统惯性的时空特性及分析方法[J]. 中国电机工程学报, 2020, 40(1): 50-58, 373. Zeng Fanhong, Zhang Junbo.Temporal and spatial characteristics of power system inertia and its analysis method[J]. Proceedings of the CSEE, 2020, 40(1): 50-58, 373. [12] 李东东, 郭天洋, 刘庆飞, 等. 计及光伏发电的新能源电力系统惯量评估[J]. 太阳能学报, 2021, 42(5): 174-179. Li Dongdong, Guo Tianyang, Liu Qingfei, et al.Inertia estimation of renewable power system considering photovoltaics[J]. Acta Energiae Solaris Sinica, 2021, 42(5): 174-179. [13] 李世春, 宋秋爽, 薛臻瑶, 等. 含风电虚拟惯性响应的新能源电力系统惯量估计[J]. 电力工程技术, 2023, 42(2): 84-93. Li Shichun, Song Qiushuang, Xue Zhenyao, et al.Inertia estimation of new energy power system with virtual inertia response of wind power[J]. Electric Power Engineering Technology, 2023, 42(2): 84-93. [14] 李世春, 徐松林, 李惠子, 等. 风电场等效虚拟惯量快速估计方法[J]. 电网技术, 2021, 45(12): 4683-4692. Li Shichun, Xu Songlin, Li Huizi, et al.Rapid estimation of equivalent virtual inertia of wind farm[J]. Power System Technology, 2021, 45(12): 4683-4692. [15] 安军, 盛帅, 周毅博, 等. 基于量测数据的风电场等效虚拟惯量评估方法[J]. 电网技术, 2023, 47(5): 1819-1829. An Jun, Sheng Shuai, Zhou Yibo, et al.Evaluation of equivalent virtual inertia of wind farm based on measured data[J]. Power System Technology, 2023, 47(5): 1819-1829. [16] 王博, 杨德友, 蔡国伟. 高比例新能源接入下电力系统惯量相关问题研究综述[J]. 电网技术, 2020, 44(8): 2998-3007. Wang Bo, Yang Deyou, Cai Guowei.Review of research on power system inertia related issues in the context of high penetration of renewable power generation[J]. Power System Technology, 2020, 44(8): 2998-3007. [17] 张祥宇, 胡剑峰, 付媛, 等. 风储联合系统的虚拟惯量需求与协同支撑[J]. 电工技术学报, 2024, 39(3): 672-685. Zhang Xiangyu, Hu Jianfeng, Fu Yuan, et al.Virtual inertia demand and collaborative support of wind power and energy storage system[J]. Transactions of China Electrotechnical Society, 2024, 39(3): 672-685. [18] 张冠锋, 杨俊友, 王海鑫, 等. 基于虚拟同步机技术的风储系统协调调频控制策略[J]. 电工技术学报, 2022, 37(增刊1): 83-92. Zhang Guanfeng, Yang Junyou, Wang Haixin, et al.Coordinated frequency modulation control strategy of wind farm-storage system based on virtual synchronous generator technology[J]. Transactions of China Electrotechnical Society, 2022, 37(S1): 83-92. [19] 胡正阳, 高丙团, 张磊, 等. 风电机组双向支撑能力分析与自适应惯量控制策略[J]. 电工技术学报, 2023, 38(19): 5224-5240. Hu Zhengyang, Gao Bingtuan, Zhang Lei, et al.Bidirectional support capability analysis and adaptive inertial control strategy of wind turbine[J]. Transactions of China Electrotechnical Society, 2023, 38(19): 5224-5240. [20] 王科, 秦文萍, 张宇, 等. 双馈风机等效惯量控制比例系数对系统功角首摆稳定的影响机理分析[J]. 电工技术学报, 2023, 38(3): 741-753. Wang Ke, Qin Wenping, Zhang Yu, et al.Mechanism analysis of effect of equivalent proportional coefficient of inertia control of DFIG on stability of first swing of power angle[J]. Transactions of China Electrotechnical Society, 2023, 38(3): 741-753. [21] 张旭, 陈云龙, 岳帅, 等. 风电参与电力系统调频技术研究的回顾与展望[J]. 电网技术, 2018, 42(6): 1793-1803. Zhang Xu, Chen Yunlong, Yue Shuai, et al.Retrospect and prospect of research on frequency regulation technology of power system by wind power[J]. Power System Technology, 2018, 42(6): 1793-1803. [22] 陈宇航, 王刚, 侍乔明, 等. 一种新型风电场虚拟惯量协同控制策略[J]. 电力系统自动化, 2015, 39(5): 27-33. Chen Yuhang, Wang Gang, Shi Qiaoming, et al.A new coordinated virtual inertia control strategy for wind farms[J]. Automation of Electric Power Systems, 2015, 39(5): 27-33. [23] 王鑫, 杨德健. 基于变系数PI控制的双馈风电机组自适应转速恢复策略[J]. 电工技术学报, 2023, 38(15): 4120-4129. Wang Xin, Yang Dejian.Adaptive speed recovery strategy of doubly-fed induction generator based on variable PI control coefficient[J]. Transactions of China Electrotechnical Society, 2023, 38(15): 4120-4129. [24] 蔡葆锐, 杨蕾, 黄伟. 基于惯性/下垂控制的变速型风电机组频率协调控制方法[J]. 电力系统保护与控制, 2021, 49(15): 169-177. Cai Baorui, Yang Lei, Huang Wei.Frequency coordination control of a variable speed wind turbine based on inertia/droop control[J]. Power System Protection and Control, 2021, 49(15): 169-177. [25] 陈文倩, 辛小南, 程志平. 基于虚拟同步发电机的光储并网发电控制技术[J]. 电工技术学报, 2018, 33(增刊2): 538-545. Chen Wenqian, Xin Xiaonan, Cheng Zhiping.Control of grid-connected of photovoltaic system with storage based on virtual synchronous generator[J]. Transactions of China Electrotechnical Society, 2018, 33(S2): 538-545. [26] 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. [27] 杨晓楠, 李洋, 史梁, 等. 光-储虚拟同步机多模式运行控制与改善储能系统寿命的选择性投退策略[J]. 太阳能学报, 2022, 43(4): 66-74. Yang Xiaonan, Li Yang, Shi Liang, et al.Multi-mode operating control of optical-storage virtual synchronizer and selectively plug in/out strategy for improving energy storage system lifetime[J]. Acta Energiae Solaris Sinica, 2022, 43(4): 66-74. [28] 秦晓辉, 苏丽宁, 迟永宁, 等. 大电网中虚拟同步发电机惯量支撑与一次调频功能定位辨析[J]. 电力系统自动化, 2018, 42(9): 36-43. Qin Xiaohui, Su Lining, Chi Yongning, et al.Functional orientation discrimination of inertia support and primary frequency regulation of virtual synchronous generator in large power grid[J]. Automation of Electric Power Systems, 2018, 42(9): 36-43. [29] Kundur P, Balu N J, Lauby M G.Power system stability and control[M]. New York: McGraw-Hill, 1994. [30] Cepeda J C, Rueda J L, Colomé D G, et al.Real-time transient stability assessment based on centre-of-inertia estimation from phasor measurement unit records[J]. IET Generation, Transmission & Distribution, 2014, 8(8): 1363-1376. [31] 王宝财, 孙华东, 李文锋, 等. 考虑动态频率约束的电力系统最小惯量评估[J]. 中国电机工程学报, 2022, 42(1): 114-127. Wang Baocai, Sun Huadong, Li Wenfeng, et al.Minimum inertia estimation of power system considering dynamic frequency constraints[J]. Proceedings of the CSEE, 2022, 42(1): 114-127. [32] Wall P, Terzija V.Simultaneous estimation of the time of disturbance and inertia in power systems[J]. IEEE Transactions on Power Delivery, 2014, 29(4): 2018-2031. [33] Morren J, Pierik J, de Haan S W H. Inertial response of variable speed wind turbines[J]. Electric Power Systems Research, 2006, 76(11): 980-987. [34] 叶畅, 柳丹, 杨欣宜, 等. 基于最小惯量评估的高比例新能源电力系统优化运行策略[J]. 电网技术, 2023, 47(2): 502-516. Ye Chang, Liu Dan, Yang Xinyi, et al.Optimal operation strategy of high proportion new energy power system based on minimum inertia evaluation[J]. Power System Technology, 2023, 47(2): 502-516. [35] 唐西胜, 苗福丰, 齐智平, 等. 风力发电的调频技术研究综述[J]. 中国电机工程学报, 2014, 34(25): 4304-4314. Tang Xisheng, Miao Fufeng, Qi Zhiping, et al.Survey on frequency control of wind power[J]. Proceedings of the CSEE, 2014, 34(25): 4304-4314.
2024, Vol. 39 
