集群光伏电站频率主动支撑自校正控制方法

doi:10.11930/j.issn.1004-9649.202112014

中国电力 ›› 2022, Vol. 55 ›› Issue (9): 156-162.DOI: 10.11930/j.issn.1004-9649.202112014

集群光伏电站频率主动支撑自校正控制方法

刘刚¹, 陈海东¹, 孙睿哲², 彭佩佩³

1. 国网宁夏电力有限公司调度控制中心，宁夏银川 750001;
2. 东南大学电气工程学院，江苏南京 210096;
3. 中国电力科学研究院有限公司，江苏南京 210037

收稿日期:2021-12-10 修回日期:2022-04-28 发布日期:2022-09-20
作者简介:刘刚（1988—），男，硕士，高级工程师，从事电力系统调度控制管理工作，E-mail：648082444@qq.com;陈海东（1986—），男，硕士，高级工程师，从事电力系统调度控制管理工作，E-mail：18995258968@163.com;孙睿哲（1997—），男，通信作者，硕士研究生，从事新能源并网控制技术研究，E-mail：seu_ruizhe@163.com;彭佩佩（1984—），女，工程师，从事新能源发电技术研究，E-mail：pengpeipei@epri.sgcc.com.cn
基金资助:
国家重点研发计划资助项目（可再生能源与火力发电耦合集成与灵活运行控制技术，2019YFB1505400）

Self-tuning Control Method of Active Frequency Support of Clustering Photovoltaic Power Plants

LIU Gang¹, CHEN Haidong¹, SUN Ruizhe², PENG Peipei³

1. Dispatching & Control Center, State Grid Ningxia Electric Power Co., Ltd., Yinchuan 750001, China;
2. School of Electrical Engineering, Southeast University, Nanjing 210096, China;
3. China Electric Power Research Institute, Nanjing 210037, China

Received:2021-12-10 Revised:2022-04-28 Published:2022-09-20
Supported by:
This work is supported by National Key R&D Program of China (Renewable Energy and Thermal Power Generation Coupling Integration and Flexible Operation Control Technology, No.2019YFB1505400).

摘要/Abstract

摘要： 现有光伏电站通过检测频率变化，采用下垂控制调节出力抑制源侧随机无规则出力波动，调频过程存在时间滞后性。基于自校正控制，提出一种可平滑光伏秒级出力波动的光伏电站频率主动支撑控制策略，根据受扰光伏电站光照波动情况，通过前馈补偿主动校正自身有功参考值，重新自适应分配各光伏电站有功给定值，实现在频率明显变化前主动补偿受扰电站的出力波动。基于Matlab/Simulink搭建仿真算例，仿真结果表明：相较下垂控制，自校正控制在扰动下可将频率最低点提高约0.04 Hz，并使得平均频率变化率降低约26.06%，有效提升了系统频率性能。

关键词: 光伏电站, 自校正控制, 出力平滑, 主动支撑, 频率

Abstract: As existing photovoltaic power plants implement droop control to adjust output and thereby suppress random and irregular output fluctuations on the supply side after detecting frequency changes, a time lag occurs in the frequency modulation process. On the basis of self-tuning control, this paper proposes a control strategy of active frequency support that can smooth second-level output fluctuations of photovoltaic power for photovoltaic power plants. According to the light fluctuation at the disturbed photovoltaic power plant, the reference active power is automatically corrected through feedforward compensation, and the active power setpoint of each photovoltaic power plant is redistributed adaptively. The output fluctuation at the disturbed power plant is thereby actively compensated before the frequency changes significantly. A simulation example is built with Matlab/Simulink. The simulation results show that compared with droop control, the proposed self-tuning control effectively improves the frequency performance of the system by elevating the lowest frequency point by about 0.04 Hz under disturbances and reducing the average frequency change rate by about 26.06%.

Key words: photovoltaic power plant, self-tuning control, output smoothing, active support, frequency

刘刚, 陈海东, 孙睿哲, 彭佩佩. 集群光伏电站频率主动支撑自校正控制方法[J]. 中国电力, 2022, 55(9): 156-162.

LIU Gang, CHEN Haidong, SUN Ruizhe, PENG Peipei. Self-tuning Control Method of Active Frequency Support of Clustering Photovoltaic Power Plants[J]. Electric Power, 2022, 55(9): 156-162.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202112014

https://www.electricpower.com.cn/CN/Y2022/V55/I9/156

参考文献

[1] 国家能源局. 10亿千瓦可再生能源装机意味着什么[EB/OL]. (2021-12-03) [2021-12-09]. http://www.nea.gov.cn/2021-12/03/c_1310350120.htm.
[2] 于腾凯,董靓媛,杜晓东,等. 考虑机会约束的配电网光伏并网容量分布鲁棒优化方法[J]. 电力系统保护与控制, 2021, 49(10): 43–50
YU Tengkai, DONG Liangyuan, DU Xiaodong, et al. Distributionally robust optimization method of PV grid-connected capacity in a distribution network considering chance constraints[J]. Power System Protection and Control, 2021, 49(10): 43–50
[3] 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
[4] 汪宁渤, 马明, 强同波, 等. 高比例新能源电力系统的发展机遇、挑战及对策[J]. 中国电力, 2018, 51(1): 29–35,50
WANG Ningbo, MA Ming, QIANG Tongbo, et al. High-penetration new energy power system development: challenges, opportunities and countermeasures[J]. Electric Power, 2018, 51(1): 29–35,50
[5] 苏宜强, 刘盛松. 静态安全域约束的多区域大规模新能源接纳能力研究与应用[J]. 中国电力, 2021, 54(9): 165–175
SU Yiqiang, LIU Shengsong. Research and application of multi-area large-scale new energy integration capability with steady-state security region constraints[J]. Electric Power, 2021, 54(9): 165–175
[6] 张义, 胡正阳, 彭佩佩, 等. 基于极点配置的新能源并网附加阻尼控制策略[J]. 中国电力, 2021, 54(10): 217–222
ZHANG Yi, HU Zhengyang, PENG Peipei, et al. Pole assignment based auxiliary damping control for renewable generation integrated into power system[J]. Electric Power, 2021, 54(10): 217–222
[7] 刘洋, 邵广惠, 张弘鹏, 等. 新能源参与系统一次调频分析及参数设置[J]. 电网技术, 2020, 44(2): 683–689
LIU Yang, SHAO Guanghui, ZHANG Hongpeng, et al. Analysis of renewable energy participation in primary frequency regulation and parameter setting scheme of power grid[J]. Power System Technology, 2020, 44(2): 683–689
[8] 万天虎,李华,唐浩,等. 基于多主站协调控制的光伏电站一次调频应用研究[J]. 智慧电力, 2021, 49(4): 37–43
WAN Tianhu, LI Hua, TANG Hao, et al. Application & research on primary frequency modulation of photovoltaic power station based on multi-muster coordinated control[J]. Smart Power, 2021, 49(4): 37–43
[9] 蔡乾, 王晶, 耿天翔, 等. 考虑新能源资源及出力特性的全局备用容量优化方法[J]. 中国电力, 2021, 54(2): 90–97
CAI Qian, WANG Jing, GENG Tianxiang, et al. Global reserve optimization method considering resources and output characteristics of renewable energy[J]. Electric Power, 2021, 54(2): 90–97
[10] 张振宇, 孙骁强, 万筱钟, 等. 基于统计学特征的新能源纳入西北电网备用研究[J]. 电网技术, 2018, 42(7): 2047–2054
ZHANG Zhenyu, SUN Xiaoqiang, WAN Xiaozhong, et al. Research on reserve of northwest power grid considering renewable energy based on statistical characteristics[J]. Power System Technology, 2018, 42(7): 2047–2054
[11] 陶仁峰, 李凤婷, 李燕青, 等. 基于系统频率响应特征的电网广义旋转备用优化配置[J]. 电力系统自动化, 2019, 43(9): 82–91
TAO Renfeng, LI Fengting, LI Yanqing, et al. Optimal configuration of generalized spinning reverse for power grid based on characteristics of system frequency response[J]. Automation of Electric Power Systems, 2019, 43(9): 82–91
[12] 龚莺飞, 鲁宗相, 乔颖, 等. 光伏功率预测技术[J]. 电力系统自动化, 2016, 40(4): 140–151
GONG Yingfei, LU Zongxiang, QIAO Ying, et al. An overview of photovoltaic energy system output forecasting technology[J]. Automation of Electric Power Systems, 2016, 40(4): 140–151
[13] 王哲, 张嘉英, 张彦振. 基于机器学习的光伏输出功率预测方法研究[J]. 计算机仿真, 2020, 37(4): 71–75,163
WANG Zhe, ZHANG Jiaying, ZHANG Yanzhen. Research on photovoltaic output power prediction method based on machine learning[J]. Computer Simulation, 2020, 37(4): 71–75,163
[14] 马原, 张雪敏, 甄钊, 等. 基于修正晴空模型的超短期光伏功率预测方法[J]. 电力系统自动化, 2021, 45(11): 44–51
MA Yuan, ZHANG Xuemin, ZHEN Zhao, et al. Ultra-short-term photovoltaic power prediction method based on modified clear-sky model[J]. Automation of Electric Power Systems, 2021, 45(11): 44–51
[15] 陈志宝, 李秋水, 程序, 等. 基于地基云图的光伏功率超短期预测模型[J]. 电力系统自动化, 2013, 37(19): 20–25
CHEN Zhibao, LI Qiushui, CHENG Xu, et al. A very short-term prediction model for photovoltaic power based on ground-based cloud images[J]. Automation of Electric Power Systems, 2013, 37(19): 20–25
[16] 柴闵康, 夏飞, 张浩, 等. 基于云图特征自识别的光伏超短期预测模型[J]. 电网技术, 2021, 45(3): 1023–1035
CHAI Minkang, XIA Fei, ZHANG Hao, et al. Ultra-short-term prediction of self-identifying photovoltaic based on sky cloud chart[J]. Power System Technology, 2021, 45(3): 1023–1035
[17] 吴振威, 蒋小平, 马会萌, 等. 用于混合储能平抑光伏波动的小波包–模糊控制[J]. 中国电机工程学报, 2014, 34(3): 317–324
WU Zhenwei, JIANG Xiaoping, MA Huimeng, et al. Wavelet packet-fuzzy control of hybrid energy storage systems for PV power smoothing[J]. Proceedings of the CSEE, 2014, 34(3): 317–324
[18] 颜晨煜, 樊艳芳, 姚波. 采用自适应变分模态分解的混合储能平滑光伏出力波动控制策略[J]. 高电压技术, 2019, 45(6): 1898–1906
YAN Chenyu, FAN Yanfang, YAO Bo. Strategy for smoothing photovoltaic power fluctuation of hybrid energy storage system using self-adaptive variational mode decomposition[J]. High Voltage Engineering, 2019, 45(6): 1898–1906
[19] 马晓伟, 徐海超, 刘鑫, 等. 适用于西北送端大电网新能源场站快速频率响应功能的入网试验方法[J]. 电网技术, 2020, 44(4): 1384–1391
MA Xiaowei, XU Haichao, LIU Xin, et al. A test method for fast frequency response function of renewable energy stations in northwest power grid[J]. Power System Technology, 2020, 44(4): 1384–1391
[20] 孙骁强, 刘鑫, 程林, 等. 基于多调频资源协调控制的西北送端大电网新能源快速频率响应参数设置方案[J]. 电网技术, 2019, 43(5): 1760–1765
SUN Xiaoqiang, LIU Xin, CHENG Lin, et al. Parameter setting of rapid frequency response of renewable energy sources in northwest power grid based on coordinated control of multi-frequency regulation resources[J]. Power System Technology, 2019, 43(5): 1760–1765
[21] 徐湘元. 自适应控制与预测控制[M]. 北京: 清华大学出版社, 2017.
[22] ABE C F, DIAS J B, NOTTON G, et al. Computing solar irradiance and average temperature of photovoltaic modules from the maximum power point coordinates[J]. IEEE Journal of Photovoltaics, 2020, 10(2): 655–663.
[23] 高晖胜, 辛焕海, 黄林彬, 等. 新能源电力系统的共模频率分析及其特征量化[J]. 中国电机工程学报, 2021, 41(3): 890–900
GAO Huisheng, XIN Huanhai, HUANG Linbin, et al. Characteristic analysis and quantification of common mode frequency in power systems with high penetration of renewable resources[J]. Proceedings of the CSEE, 2021, 41(3): 890–900

集群光伏电站频率主动支撑自校正控制方法

Self-tuning Control Method of Active Frequency Support of Clustering Photovoltaic Power Plants

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	吴云锐, 张建坡, 田新成, 应恺锋, 陈忠. 计及频率适应和快速稳定特性的多端直流电网改进协调控制策略[J]. 中国电力, 2025, 58(3): 31-42.
[2]	沈舒仪, 王国腾, 但扬清, 孙飞飞, 黄莹, 徐政. 频率偏差与电压刚度约束下多馈入直流优化调度方法[J]. 中国电力, 2025, 58(3): 132-141.
[3]	沃建栋, 潘武略, 李跃辉, 吴佳毅. 基于综合谐波驱动的光伏场站集电线路保护新方案[J]. 中国电力, 2025, 58(2): 133-139.
[4]	王雪, 刘林, 卓庆东, 张海鹏, 杨苓, 许方园, 曹雨晨. 基于虚拟惯量控制的新型电力系统功率差前馈振荡抑制方法[J]. 中国电力, 2024, 57(4): 68-76.
[5]	周于清, 李大虎, 姚伟, 宗启航, 周泓宇, 文劲宇. 受端近区光伏电站对LCC-HVDC系统稳定性影响分析[J]. 中国电力, 2024, 57(3): 170-182.
[6]	覃海, 陈胜, 张洪略, 夏天, 马覃峰, 段展宇, 颜伟. 并网光伏电站关口无功调节能力的分时段等值方法[J]. 中国电力, 2024, 57(2): 27-33.
[7]	黄堃, 付明, 梁加本. 基于融合专家知识DDPG的孤岛微电网频率调节策略[J]. 中国电力, 2024, 57(2): 194-201.
[8]	张江丰, 柯松, 陈文进, 王天宇, 郑可轲, 杨军. 光伏电站自备用可调的虚拟同步控制调频策略[J]. 中国电力, 2024, 57(11): 108-118.
[9]	于琳琳, 严格, 晏昕童, 毛玉宾, 陈姝彧, 李甜甜, 文云峰. 考虑电网支撑能力约束的直流落点及定容优化规划[J]. 中国电力, 2023, 56(8): 175-185.
[10]	赵晶晶, 杜明, 刘帅, 李梓博, 马闻鹤. 基于模型预测控制的双馈风电机组调频与转子转速恢复策略[J]. 中国电力, 2023, 56(6): 11-17.
[11]	鞠玲, 黄怿. 基于EFPI的数字配电网超声检测传感器[J]. 中国电力, 2023, 56(6): 194-201.
[12]	苏开元, 董文凯, 邱银锋, 魏澈, 谢小荣. 分散式风储一体化系统提升海上油田群电网频率稳定性研究[J]. 中国电力, 2023, 56(5): 163-171.
[13]	李振垚, 甘德强, 栾某德, 何国庆. 基于全状态模型的自同步电压源并网系统频率稳定分析[J]. 中国电力, 2023, 56(5): 182-192.
[14]	项颂, 苏鹏, 吴坚, 刘鑫, 马继涛. 基于多源储能协同的交直流送端系统惯量优化控制模型[J]. 中国电力, 2023, 56(4): 68-76.
[15]	李建华, 曹路, 杨仁炘, 邓桢彦, 李征, 蔡旭. 华东沿海风电场群电网主动频率支撑策略[J]. 中国电力, 2023, 56(11): 49-58, 112.

模态框（Modal）标题

集群光伏电站频率主动支撑自校正控制方法

Self-tuning Control Method of Active Frequency Support of Clustering Photovoltaic Power Plants

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics