New Type Power System and the Integrated Energy

Inertial Control Strategy for Wind Farm with Distributed Energy Storage System Based on Model Predictive Control

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  • 1. Electric Power Scientific Research Institute, State Grid Hunan Electric Power Co., Ltd., Changsha 410000, China
    2. College of Electrical and Information Engineering, Hunan University, Changsha 410082, China

Received date: 2020-06-30

  Online published: 2022-05-19

Abstract

Distributed energy storage (DES) wind turbine is an effective means to solve the problem of system frequency stability caused by large-scale wind power connection. In this paper, an inertial control method for DES wind farms based on model predictive control (MPC) is proposed.First, the linearized prediction model of the DES wind farm is established. Then, on this basis, in combination with the control framework of MPC, an optimization model and strategy of MPC inertial control are proposed considering the cost of energy storage loss and the balanced change of wind turbine rotor speed,in order to achieve the balanced change of wind turbine rotor speed during inertia control. The simulation results show that the proposed control strategy can effectively coordinate the active power output of the wind power generation unit and the energy storage system unit in the DES wind turbine, reduce the cost of charging and discharging loss of the energy storage system, and ensure that the rotational speed of all wind turbines in the wind farm tends to be average during the inertial control period, avoiding the problem of wind turbines exiting frequency regulation due to excessive reduction of the rotational speed of wind turbines. The inertial control strategy of the DES wind farm is beneficial to improve the frequency stability of the power grid, which is of great significance to ensure the safe operation of the power grid.

Cite this article

SHEN Yangwu, SONG Xingrong, LUO Ziren, SHEN Feifan, HUANG Sheng . Inertial Control Strategy for Wind Farm with Distributed Energy Storage System Based on Model Predictive Control[J]. Journal of Shanghai Jiaotong University, 2022 , 56(10) : 1285 -1293 . DOI: 10.16183/j.cnki.jsjtu.2022.134

References

[1] 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.
[2] 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.
[2] 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.
[3] REZA M. Power electronic interfaced DG units: Impact of control strategy on power system transient stability[C]//3rd IEE International Conference on Reliability of Transmission and Distribution Networks. London, UK: IEE, 2005: 179-182.
[4] 付媛, 王毅, 张祥宇, 等. 基于多端直流联网的风电功率协调控制[J]. 高电压技术, 2014, 40(2): 611-619.
[4] FU Yuan, WANG Yi, ZHANG Xiangyu, et al. Coordinated control of wind power in multi-terminal DC transmission system[J]. High Voltage Engineering, 2014, 40(2): 611-619.
[5] LIU F, LIU Z W, MEI S W, et al. ESO-based inertia emulation and rotor speed recovery control for DFIGs[J]. IEEE Transactions on Energy Conversion, 2017, 32(3): 1209-1219.
[6] WANG D X, GAO X D, MENG K, et al. Utilisation of kinetic energy from wind turbine for grid connections: A review paper[J]. IET Renewable Power Ge-neration, 2018, 12(6): 615-624.
[7] 苗福丰, 唐西胜, 齐智平. 风储联合调频下的电力系统频率特性分析[J]. 高电压技术, 2015, 41(7): 2209-2216.
[7] MIAO Fufeng, TANG Xisheng, QI Zhiping. Analysis of frequency characteristics of power system based on wind farm-energy storage combined frequency re-gulation[J]. High Voltage Engineering, 2015, 41(7): 2209-2216.
[8] BAO W Y, WU Q W, DING L, et al. Synthetic inertial control of wind farm with BESS based on model predictive control[J]. IET Renewable Power Generation, 2020, 14(13): 2447-2455.
[9] FANG J Y, ZHANG R Q, LI H C, et al. Frequency derivative-based inertia enhancement by grid-connected power converters with a frequency-locked-loop[J]. IEEE Transactions on Smart Grid, 2019, 10(5): 4918-4927.
[10] 刘巨, 姚伟, 文劲宇, 等. 一种基于储能技术的风电场虚拟惯量补偿策略[J]. 中国电机工程学报, 2015, 35(7): 1596-1605.
[10] LIU Ju, YAO Wei, WEN Jinyu, et al. A wind farm virtual inertia compensation strategy based on energy storage system[J]. Proceedings of the CSEE, 2015, 35(7): 1596-1605.
[11] WU Z P, GAO D W, ZHANG H G, et al. Coordinated control strategy of battery energy storage system and PMSG-WTG to enhance system frequency regulation capability[J]. IEEE Transactions on Sustainable Energy, 2017, 8(3): 1330-1343.
[12] JIANG Q Y, GONG Y Z, WANG H J. A battery energy storage system dual-layer control strategy for mitigating wind farm fluctuations[J]. IEEE Transactions on Power Systems, 2013, 28(3): 3263-3273.
[13] ZHAO H R, WU Q W, GUO Q L, et al. Optimal active power control of a wind farm equipped with energy storage system based on distributed model predictive control[J]. IET Generation, Transmission & Distribution, 2016, 10(3): 669-677.
[14] 付红军, 陈惠粉, 赵华, 等. 高渗透率下风电的调频技术研究综述[J]. 中国电力, 2021, 54(1): 104-115.
[14] FU Hongjun, CHEN Huifen, ZHAO Hua, et al. Review on frequency regulation technology with high wind power penetration[J]. Electric Power, 2021, 54(1): 104-115.
[15] ZHAO H R, WU Q W, GUO Q L, et al. Distributed model predictive control of a wind farm for optimal active power control—Part I: Clustering-based wind turbine model linearization[J]. IEEE Transactions on Sustainable Energy, 2015, 6(3): 831-839.
[16] GUO Y F, GAO H L, WU Q W, et al. Enhanced voltage control of VSC-HVDC-connected offshore wind farms based on model predictive control[J]. IEEE Transactions on Sustainable Energy, 2018, 9(1): 474-487.
[17] 刘淼. 参与电网调频的风电场有功功率控制方法研究[D]. 成都: 电子科技大学, 2018.
[17] LIU Miao. Wind farm active power control method in power system frequency regulation[D]. Chengdu: University of Electronic Science and Technology of China, 2018.
[18] WANG S Q, TOMSOVIC K. A novel active power control framework for wind turbine generators to improve frequency response[J]. IEEE Transactions on Power Systems, 2018, 33(6): 6579-6589.
[19] HUANG S, WU Q W, GUO Y F, et al. Hierarchical active power control of DFIG-based wind farm with distributed energy storage systems based on ADMM[J]. IEEE Transactions on Sustainable Energy, 2020, 11(3): 1528-1538.
[20] HUANG S, WU Q W, GUO Y F, et al. Bi-level decentralised active power control for large-scale wind farm cluster[J]. IET Renewable Power Generation, 2018, 12(13): 1486-1492.
[21] ANDERSON P M, BOSE A. Stability simulation of wind turbine systems[J]. IEEE Transactions on Power Apparatus and Systems, 1983, 102(12): 3791-3795.
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