基于储能惯量支撑的受端电网频率优化控制方法

doi:10.19595/j.cnki.1000-6753.tces.230466

Abstract
Figure/Table
References (0)
Related Citation (15)

Download: PDF (451 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract

In view of the problem that the equivalent inertia and frequency modulation capability of the receiving power grid are constantly reduced due to large-scale renewable energy access, and the frequency stability of the receiving power grid is seriously affected, this paper proposes an optimal control method for frequency stability of the receiving power grid considering energy storage support. Firstly, the frequency response characteristics of multi-source energy storage in the receiving power grid are analyzed. Secondly, the relationship between multi-energy energy coordination and frequency change based on multi-source energy storage is analyzed, a frequency support characteristic model considering multi-energy energy storage sup-port is established, and the equivalent model of the frequency response of the receiving-end power grid based on multi-energy coordination is modified. Then, the frequency change speed index and frequency drop index of the receiving power grid are established as the frequency stability index, and an optimal control method for frequency stability of the receiving-end power grid based on multi-source energy storage support is proposed. Finally, a simulation model is established by taking an actual receiving-end power grid as an example. The results of the example verify the validity of the model in this paper. Based on the multi-energy energy storage support, the frequency stability performance of the receiving-end power grid can be improved.
The innovations of this paper are as follows :
(1) In this paper, the response characteristics of multi-source energy storage equipment to frequency through virtual inertia control are analyzed, and the frequency control model of multi-source energy storage inertia support is established.
(2) The internal response considers the response of the prime mover and the governor when the active power adjustment is considered, and the external response is equivalent using the parameter identification method. On this basis, a frequency response model of receiving-end power grid considering multi-source energy storage support is established.
(3) Taking the frequency change speed index and frequency drop index of the receiving-end power grid as the frequency stability index, the frequency stability optimization control method of the receiving-end power grid based on multi-source energy storage support is proposed. An improved quantum particle swarm optimization algorithm is proposed to solve the frequency stability control of the receiving-end power grid. Finally, the simulation model is established by taking the actual receiving-end power grid in East China as an example. The results of the example verify the effectiveness of the model in this paper.
The following conclusions can be drawn from the simulation analysis: (1) The characteristics of multi-energy storage in the receiving-end power grid are analyzed, and the frequency control response models of electric vehicles, P2H, P2G equipment and electric vehicles are analyzed. (2) The support characteristics of the system based on multi-energy energy coordination and multi-source energy storage are analyzed. The frequency response model of the receiving-end power grid considering multi-source energy storage is proposed, and the frequency stability optimization control model of multi-source energy storage is established. (3) A frequency stability index is established, which is composed of the frequency change speed index and the frequency drop index of the receiving power grid, and the virtual inertia control of multi-source energy storage is used for frequency regulation. The simulation results show that the model can effectively improve the frequency characteristics of the receiving end power grid, and the proposed frequency response model has high accuracy. (4) The frequency modulation optimization control method based on multi-source energy storage in this paper can make full use of the rotor kinetic energy, reasonably adjust the system inertia, and improve the frequency modulation ability of the receiving end system.

Key words： energy storage receiving end grid frequency stability optimal control

Received: 08 April 2023

PACS:

TM614

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Zhang Yijing
	Zhi Li
	Shi Yanqiang
	Ding Haoyin
	Zhang Wenchao

Cite this article:

Zhang Yijing,Zhi Li,Shi Yanqiang等. Optimal Frequency Control Method of Receiving Power Grid Based on Energy Storage Inertia Support[J]. Transactions of China Electrotechnical Society, 0, (): 230466-.

URL:

https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.230466 OR https://dgjsxb.ces-transaction.com/EN/Y0/V/I/230466

[1] 习近平.在第七十五届联合国大会一般性辩论上的讲话[N].人民日报,2020-09-23(003).
Xi Jinping.Add at the general debate of the seventy-fifth United Nations General Assembly [N].People's Daily,2020-09-23(003).
[2] Ratnam K S, Palanisamy K, Yang Guangya.Future low-inertia power systems: requirements, issues, and solutions - A review[J]. Renewable and Sustainable Energy Reviews, 2020, 124: 109773.
[3] 李帅虎, 向丽珍, 向振宇, 等. 用于改善VSG频率响应的模型预测控制方法[J]. 高电压技术, 2021, 47(8): 2856-2864.
Li Shuaihu, Xiang Lizhen, Xiang Zhenyu, et al.MPC control method for improving VSG frequency response[J]. High Voltage Engineering, 2021, 47(8): 2856-2864.
[4] 李忠文, 吴龙, 程志平, 等. 光储系统参与微电网频率调节的模糊自适应滑模控制[J]. 高电压技术, 2022, 48(6): 2065-2076.
Li Zhongwen, Wu Long, Cheng Zhiping, et al.Fuzzy adaptive sliding mode control of photovoltaic and storage systems for providing frequency regulation of microgrid[J]. High Voltage Engineering, 2022, 48(6): 2065-2076.
[5] 滕云, 孙鹏, 张明理, 等. 基于农村新型产业结构的“能源-环境-经济”鲁棒优化模型[J]. 中国电机工程学报, 2022, 42(2): 614-631.
Teng Yun, Sun Peng, Zhang Mingli, et al.Robust optimization model of “energy-environment-economy” based on the new rural industrial structure[J]. Proceedings of the CSEE, 2022, 42(2): 614-631.
[6] 娄源媛, 蒋若蒙, 钱峰, 等. 考虑负荷特性的解列后受端电网频率控制策略[J]. 电网技术, 2019, 43(1): 213-220.
Lou Yuanyuan, Jiang Ruomeng, Qian Feng, et al.Frequency control strategy after receiving-end power grid splitting considering load characteristics[J]. Power System Technology, 2019, 43(1): 213-220.
[7] 黎静华, 骆怡辰, 杨舒惠, 等. 可再生能源电力不确定性预测方法综述[J]. 高电压技术, 2021, 47(4): 1144-1157.
Li Jinghua, Luo Yichen, Yang Shuhui, et al.Review of uncertainty forecasting methods for renewable energy power[J]. High Voltage Engineering, 2021, 47(4): 1144-1157.
[8] 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.
[9] Syed M H, Guillo-Sansano E, Mehrizi-Sani A, et al.Load frequency control in variable inertia systems[J]. IEEE Transactions on Power Systems, 2020, 35(6): 4904-4907.
[10] 邢鹏翔, 付立军, 王刚, 等. 改善微电网频率动态响应的虚拟同步发电机强化惯量控制方法[J]. 高电压技术, 2018, 44(7): 2346-2353.
Xing Pengxiang, Fu Lijun, Wang Gang, et al.Control strategy of virtual synchronous generator with enhanced inertia for improving dynamic frequency response of microgrid[J]. High Voltage Engineering, 2018, 44(7): 2346-2353.
[11] Sun Peng, Teng Yun, Chen Zhe.Robust coordinated optimization for multi-energy systems based on multiple thermal inertia numerical simulation and uncertainty analysis[J]. Applied Energy, 2021, 296: 116982.
[12] 金红洋, 滕云, 冷欧阳, 等. 基于源荷不确定性状态感知的无废城市多能源协调储能模型[J]. 电工技术学报, 2020, 35(13): 2830-2842.
Jin Hongyang, Teng Yun, Leng Ouyang, et al.Multi-energy coordinated energy storage model in zero-waste cities based on situation awareness of source and load uncertainty[J]. Transactions of China Electrotechnical Society, 2020, 35(13): 2830-2842.
[13] 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.
[14] 滕云, 吴磊, 冷欧阳, 等. 考虑垃圾处理与多源储能协调的多能源微网优化运行模型[J]. 电工技术学报, 2020, 35(19): 4120-4130.
Teng Yun, Wu Lei, Leng Ouyang, et al.Multi-energy microgrid optimization operation model considering waste disposal and multi-source coordinated energy storage[J]. Transactions of China Electrotechnical Society, 2020, 35(19): 4120-4130.
[15] 王晶晶, 廖思阳, 姚良忠, 等. 基于一致性算法的直流受端电网分布式调频资源协同频率控制[J]. 电网技术, 2022, 46(3): 888-900.
Wang Jingjing, Liao Siyang, Yao Liangzhong, et al.Coordinated frequency control strategy for DC receiving-end power grid with distributed frequency regulation resources using consensus algorithm[J]. Power System Technology, 2022, 46(3): 888-900.
[16] 边晓燕, 张菁娴, 丁炀, 等. 基于DFIG虚拟惯量的微电网双维自适应动态频率优化控制[J]. 高电压技术, 2020, 46(5): 1476-1485.
Bian Xiaoyan, Zhang Jingxian, Ding Yang, et al.Double layer adaptive dynamic frequency optimization control of microgrid based on DFIG virtual inertia[J]. High Voltage Engineering, 2020, 46(5): 1476-1485.
[17] 孙玉树, 杨敏, 师长立, 等. 储能的应用现状和发展趋势分析[J]. 高电压技术, 2020, 46(1): 80-89.
Sun Yushu, Yang Min, Shi Changli, et al.Analysis of application status and development trend of energy storage[J]. High Voltage Engineering, 2020, 46(1): 80-89.
[18] 张祥宇, 朱正振, 付媛. 风电并网系统的虚拟同步稳定分析与惯量优化控制[J]. 高电压技术, 2020, 46(8): 2922-2932.
Zhang Xiangyu, Zhu Zhengzhen, Fu Yuan.Virtual synchronous stability analysis and optimized inertia control for wind power grid-connected system[J]. High Voltage Engineering, 2020, 46(8): 2922-2932.
[19] 颜湘武, 王德胜, 杨琳琳, 等. 直驱风机惯量支撑与一次调频协调控制策略[J]. 电工技术学报, 2021, 36(15): 3282-3292.
Yan Xiangwu, Wang Desheng, Yang Linlin, et al.Coordinated control strategy of inertia support and primary frequency regulation of PMSG[J]. Transactions of China Electrotechnical Society, 2021, 36(15): 3282-3292.
[20] 赵冬梅, 王闯, 谢家康, 等. 考虑惯量中心频率偏移的自编码器暂态稳定评估[J]. 电网技术, 2022, 46(2): 662-670.
Zhao Dongmei, Wang Chuang, Xie Jiakang, et al.Transient stability assessment of auto encoder considering frequency shift of inertia center[J]. Power System Technology, 2022, 46(2): 662-670.
[21] 赵晋泉, 汤建军, 吴迪, 等. 直流馈入受端电网暂态电压与频率稳定紧急协调控制策略[J]. 电力系统自动化, 2020, 44(22): 45-53.
Zhao Jinquan, Tang Jianjun, Wu Di, et al.Emergency coordination control strategy for transient voltage and transient frequency stability in HVDC infeed receiving-end power grid[J]. Automation of Electric Power Systems, 2020, 44(22): 45-53.
[22] 孙鹏, 滕云, 回茜, 等. 考虑异质能流输运特性的多能源系统惯量极限优化[J]. 中国电机工程学报, 2022, 42(10): 3642-3656.
Sun Peng, Teng Yun, Hui Qian, et al.Inertia limit optimization of multi-energy system considering the transport characteristics of heterogeneous energy flow[J]. Proceedings of the CSEE, 2022, 42(10): 3642-3656.
[23] 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.
[24] 王博, 杨德友, 蔡国伟. 大规模风电并网条件下考虑动态频率约束的机组组合[J]. 电网技术, 2020, 44(7): 2513-2519.
Wang Bo, Yang Deyou, Cai Guowei.Dynamic frequency constraint unit commitment in large-scale WindPower grid connection[J]. Power System Technology, 2020, 44(7): 2513-2519.
[25] 周雷, 田蓓, 卓谷颖, 等. 考虑多能互补的多区域交直流系统频率稳定联合控制模型[J]. 可再生能源, 2021, 39(5): 681-686.
Zhou Lei, Tian Bei, Zhuo Guying, et al.Multi-zone AC/DC system frequency stability joint control model considering multi-energy complementation[J]. Renewable Energy Resources, 2021, 39(5): 681-686.
[26] 林恒先, 侯凯元, 陈磊, 等. 高比例风电电力系统考虑频率安全约束的机组组合[J]. 电网技术, 2021, 45(1): 1-13.
Lin Hengxian, Hou Kaiyuan, Chen Lei, et al.Unit commitment of power system with high proportion of wind power considering frequency safety constraints[J]. Power System Technology, 2021, 45(1): 1-13.
[27] Cheng Xueyang, Lee W J, Sahni M, et al.Dynamic equivalent model development to improve the operation efficiency of wind farm[J]. IEEE Transactions on Industry Applications, 2016, 52(4): 2759-2767.
[28] 胡石阳, 刘国荣. 基于虚拟同步机的新能源并网智能控制研究[J]. 电气技术, 2022, 23(10): 10-17.
Hu Shiyang, Liu Guorong.Research on intelligent control of grid connected new energy based on virtual synchronous machine[J]. Electrical Engineering, 2022, 23(10): 10-17.