Refined ramp event characterisation for wind power ramp control using energy storage system

被引:8
作者
Liu, Wenlong [1 ]
Gong, Yuzhong [2 ]
Geng, Guangchao [1 ]
Jiang, Quanyuan [1 ]
机构
[1] Zhejiang Univ, Coll Elect Engn, Hangzhou, Zhejiang, Peoples R China
[2] Univ Saskatchewan, Dept Elect & Comp Engn, Saskatoon, SK, Canada
关键词
wind power plants; energy storage; power generation control; optimisation; ESS; refined ramp event characterisation; continuous wind power ramp control; wind power ramp event prediction; anticipated ramp events; ramp requirement; wind energy curtailment; energy storage system; bidirectional charge-discharge; energy storage reserve; optimisation model; active adjustment strategy; wind farm; expected charging-discharging energy; power; 100; 0; MW; BATTERY;
D O I
10.1049/iet-rpg.2018.5064
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
With the advantages of fast response and bidirectional charge/discharge, an energy storage system (ESS) plays a promising role in wind power ramp control. In this study, an optimisation model based on refined ramp event characterisation is proposed to achieve continuous wind power ramp control using ESS. Firstly, four kinds of ramp scenarios are characterised considering both the wind power ramp event prediction and the charge/discharge state of ESS. State of charge of ESS is managed within its limits during ramp control, based on the classified ramp scenarios. Secondly, for the classified ramp scenarios, an active adjustment strategy is proposed to decide the expected charging/discharging energy of ESS according to the conditions of wind power and ESS. Thus, an appropriate energy storage reserve can be determined for anticipated ramp events. Refined ramp event characterisation is able to achieve better control performance with higher satisfaction of ramp requirement, less wind energy curtailment as well as promising adaptability to different ramp event predictions, wind conditions and changes of ESS parameters. The effectiveness of the proposed method is verified through case studies with real-world data from a 100 MW wind farm in China.
引用
收藏
页码:1731 / 1740
页数:10
相关论文
共 50 条
  • [31] Optimal allocation of energy storage coordinated with thermal power units for ramp events considering the correlation among offshore wind farms
    Yu, Xinyi
    Bian, Xiaoyan
    Yin, Zhiang
    Lin, Yi
    Tang, Yuchen
    Sun, Fengzhou
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2025, 19 (01)
  • [32] Wind Ramp Event Prediction with Parallelized Gradient Boosted Regression Trees
    Gupta, Saurav
    Shrivastava, Nitin Anand
    Khosravi, Abbas
    Panigrahi, Bijaya Ketan
    2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2016, : 5296 - 5301
  • [33] Optimal active power control of a wind farm equipped with energy storage system based on distributed model predictive control
    Zhao, Haoran
    Wu, Qiuwei
    Guo, Qinglai
    Sun, Hongbin
    Xue, Yusheng
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2016, 10 (03) : 669 - 677
  • [34] Solar Power Ramp Event Forewarning with Limited Historical Observations
    Zhu, Wenli
    Zhang, Li
    Yang, Ming
    Wang, Bo
    2019 IEEE/IAS 55TH INDUSTRIAL AND COMMERCIAL POWER SYSTEMS TECHNICAL CONFERENCE (I&CPS), 2019, : 161 - 168
  • [35] Control of a Flywheel Energy Storage System for Power Smoothing in Wind Power Plants
    Diaz-Gonzalez, Francisco
    Bianchi, Fernando D.
    Sumper, Andreas
    Gomis-Bellmunt, Oriol
    IEEE TRANSACTIONS ON ENERGY CONVERSION, 2014, 29 (01) : 204 - 214
  • [36] Ramp rate abatement for wind power plants: A techno-economic analysis
    Frate, G. F.
    Cherubini, P.
    Tacconelli, C.
    Micangeli, A.
    Ferrari, L.
    Desideri, U.
    APPLIED ENERGY, 2019, 254
  • [37] Grid-Connected Wind Farm Power Control using VRB-based Energy Storage System
    Wang, Wenliang
    Ge, Baoming
    Bi, Daqiang
    Sun, Dongsen
    2010 IEEE ENERGY CONVERSION CONGRESS AND EXPOSITION, 2010, : 3772 - 3777
  • [38] Comparative Study of Ramp-Rate Control Algorithms for PV with Energy Storage Systems
    Martins, Joao
    Spataru, Sergiu
    Sera, Dezso
    Stroe, Daniel-Ioan
    Lashab, Abderezak
    ENERGIES, 2019, 12 (07)
  • [39] Data Mining for Prediction of Wind Farm Power Ramp Rates
    Kusiak, Andrew
    Zheng, Haiyang
    2008 IEEE INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY TECHNOLOGIES (ICSET), VOLS 1 AND 2, 2008, : 1099 - 1103
  • [40] Modelling and simulation of a storage system connected to a wind farm under ramp-rate limitation
    D'Amico, Guglielmo
    Petroni, Filippo
    Vergine, Salvatore
    INTERNATIONAL JOURNAL OF MODELLING AND SIMULATION, 2023, 43 (06) : 1021 - 1040