To address the frequency random fluctuation caused by high-penetration wind power integrated with power system
a fast frequency regulation strategy was proposed based on moment generating function. Firstly
through collecting the local frequency data at connection points of each wind turbine in wind farm
and obtaining the frequency data by monitoring the dispatch center
the frequency deviation signal at current moment was obtained. Secondly
the probability density function (PDF) of frequency deviation was calculated with kernel density estimation
so as to establish a random distribution model of frequency deviation based on the moment generating function
and performance indicators for frequency control system. Thirdly
an analytical solution for frequency control was obtained after optimization solution
and the stability of frequency control system was analyzed. After which
simulation experiments were conducted on a domestic 1 100 MW wind-thermal hybrid power system. Results show that
under both of load and wind speed disturbance conditions
the proposed fast frequency control strategy can maintain the quasi-steady-state frequency deviation of the points of common coupling and each wind turbine within ±0.02 Hz
while the PDF of frequency deviation exhibits a sharp peak and remains a concentrated distribution around zero. Compared with the traditional droop control
the deviation range of quasi-steady-state frequency is reduced by over 80%
and the nadir of frequency is increased by about 0.05 Hz. Relevant results verify the effectiveness of the proposed strategy in mitigating the frequency fluctuation caused by wind speed and load disturbances.
关键词
Keywords
references
唐坚, 唐庆宏, 姚禹歌, 等. 风电调频能力的潜力分析[J]. 动力工程学报, 2022, 42(11): 1138-1145. TANG Jian, TANG Qinghong, YAO Yuge, et al. Potential analysis of frequency regulation ability of wind power in the view of energy[J]. Journal of Chinese Society of Power Engineering, 2022, 42(11): 1138-1145.
IRENA. Renewable capacity statistics 2024[R]. Abu Dhabi: International Renewable Energy Agency, 2024.
SAHA S, SALEEM M I, ROY T K. Impact of high penetration of renewable energy sources on grid frequency behaviour[J]. International Journal of Electrical Power & Energy Systems, 2023, 145: 108701.
姚路锦, 王玮, 蔡玮, 等. 提升风电调频性能的源储协同控制策略[J]. 动力工程学报, 2023, 43(2): 126-135, 193. YAO Lujin, WANG Wei, CAI Wei, et al. Cooperative control strategy of source and storage for improving frequency regulation performance of wind power[J]. Journal of Chinese Society of Power Engineering, 2023, 43(2): 126-135, 193.
宋子秋, 余照国, 胡阳, 等. 海上漂浮式风电场高比例并网一次调频控制策略研究[J]. 动力工程学报, 2023, 43(1): 92-101. SONG Ziqiu, YU Zhaoguo, HU Yang, et al. Research on primary frequency regulation control strategy of high-penetration offshore floating wind farm[J]. Journal of Chinese Society of Power Engineering, 2023, 43(1): 92-101.
RUAN Yimin, YAO Wei, ZONG Qihang, et al. Online assessment of frequency support capability of the DFIG-based wind farm using a knowledge and data-driven fusion Koopman method[J]. Applied Energy, 2025, 377: 124518.
YANG Dejian, YAN Gangui, ZHENG Taiying, et al. Fast frequency response of a DFIG based on variable power point tracking control[J]. IEEE Transactions on Industry Applications, 2022, 58(4): 5127-5135.
BJRK J, POMBO D V, JOHANSSON K H. Variable-speed wind turbine control designed for coordinated fast frequency reserves[J]. IEEE Transactions on Power Systems, 2022, 37(2): 1471-1481.
李想, 刘克天, 李军, 等. 基于风电机组转子动能的风电场一次调频功率分配优化[J]. 动力工程学报, 2023, 43(9): 1238-1246. LI Xiang, LIU Ketian, LI Jun, et al. Optimization of power distribution for primary frequency regulation of wind farm based on rotor kinetic energy of wind turbines[J]. Journal of Chinese Society of Power Engineering, 2023, 43(9): 1238-1246.
KHESHTI M, LIN Shuyue, ZHAO Xiaowei, et al. Gaussian distribution-based inertial control of wind turbine generators for fast frequency response in low inertia systems[J]. IEEE Transactions on Sustainable Energy, 2022, 13(3): 1641-1653.
ZHU Donghai, GUO Xiang, TANG Binwei, et al. Feedforward frequency deviation control in PLL for fast inertial response of DFIG-based wind turbines[J]. IEEE Transactions on Power Electronics, 2024, 39(1): 664-676.
CHEN Qian, BADESA L, CHU Zhongda, et al. Adaptive droop gain control for optimal kinetic energy extraction from wind turbines to support system frequency[J]. IEEE Access, 2024, 12: 120624-120637.
CHEN Wei, ZHENG Taiying, NIAN Heng, et al. Multi-objective adaptive inertia and droop control method of wind turbine generators[J]. IEEE Transactions on Industry Applications, 2023, 59(6): 7789-7799.
XU Mengtian, JIN Yuqing, MA Junchao, et al. Fuzzy frequency droop control of DFIG wind turbine generators adapted to continuous changes in wind speeds[J]. IEEE Access, 2023, 11: 115011-115024.
MA Shaokang, GENG Hua, YANG Geng, et al. Clustering-based coordinated control of large-scale wind farm for power system frequency support[J]. IEEE Transactions on Sustainable Energy, 2018, 9(4): 1555-1564.
ZHANG Yubo, HAO Zhiguo, YANG Songhao, et al. A system-view optimal additional active power control of wind turbines for grid frequency support[J]. IEEE Transactions on Power Systems, 2024, 39(2): 4323-4335.
YE Lin, ZHANG Cihang, TANG Yong, et al. Hierarchical model predictive control strategy based on dynamic active power dispatch for wind power cluster integration[J]. IEEE Transactions on power systems, 2019, 34(6): 4617-4629.
ZHANG Zhihao, KOU Peng, ZHANG Yuanhang, et al. Coordinated predictive control of offshore DC collection grid and wind turbines for frequency response: a scheme without secondary frequency drop[J]. IEEE Transactions on Sustainable Energy, 2023, 14(3): 1488-1503.
Short-term Wind Power Output Prediction Based on FeatureSimilarity Day and CNN-BiLSTM-Attention Model
Research Progress of Molten Salt Thermal Energy Storage Technology Under New Power System
Research on Trading Decision of Wind-Photovoltaic-Gas Combined System Participating in Day-ahead and Real-time Markets Considering Wind and Photovoltaic Uncertainty
Research on Multiaixal Creep Behavior and Failure Criteria of TP321 Stainless Steel at 650 ℃
Dual-channel Short-term Wind Power Forecasting Fusing Long- and Short-term Dependencies
Related Author
LUAN Fuming
ZHANG Heng
CHEN Haiping
高达
王峰
刘伟华
唐忠锋
Related Institution
School of Energy Power and Mechanical Engineering, North China Electric Power University
North China Electric Power Test and Research Institute, China DatangCorporation Science and Technology General Research Institute Co., Ltd.