A stochastic response surface method for probabilistic assessment of ATC in wind power integrated system

被引:0
|
作者
Luo Gang [1 ]
Wu Xiaoshan [1 ]
Wu Guobing [1 ]
Yang Yinguo [1 ]
Qian Feng [1 ]
机构
[1] Guangdong Power Grid Corp Ltd, Power Dispatch Control Ctr, Guangzhou, Guangdong, Peoples R China
关键词
Available transfer capability; correlation; polynomial normal transformation; stochastic response surface; wind farm; FLOW;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
With the increasing integration of large-scale wind farms, modification of current tools for evaluating and managing power systems such as available transfer capability (ATC) becomes an important issue. This paper presents a computationally accurate and efficient approach based on stochastic response surface method (SRSM) for probabilistic assessment of ATC. The uncertainties of load, wind power and component failure were considered in the model. Polynomial normal transformation combined with orthogonal transformation technique was used to deal with the correlated continuous input random variables with unknown probability distribution functions. The discrete input random variables were simulated by Monte Carlo simulation. The case studies, with the IEEE Reliability Test System, illustrate the advantages of the proposed method that largely reduces the computation burden under the premise of ensuring its accuracy. The results also verify the enhancement of component failure and spatially correlated wind power on the volatility of ATC.
引用
收藏
页数:5
相关论文
共 50 条
  • [1] Probabilistic power flow calculation of power system considering wind power based on improved stochastic response surface method
    Su H.
    Dong X.
    [J]. Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2021, 42 (06): : 289 - 296
  • [2] A stochastic response surface method for probabilistic evaluation of the voltage stability considering wind power
    Bao, Haibo
    Wei, Hua
    [J]. Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2012, 32 (13): : 77 - 85
  • [3] A Fast Probabilistic Voltage Assessment Method for Distribution System Integrated with Wind Power Generation
    Chen, Can
    Zhang, Boming
    Wu, Wenchuan
    [J]. TENCON 2012 - 2012 IEEE REGION 10 CONFERENCE: SUSTAINABLE DEVELOPMENT THROUGH HUMANITARIAN TECHNOLOGY, 2012,
  • [4] Stochastic Response Surface Method Addressing Correlated Wind Power for Probabilistic Evaluation of Voltage Stability
    Bao, Haibo
    Wei, Hua
    Guo, Xiaoxuan
    [J]. 2016 IEEE PES ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), 2016, : 1660 - 1664
  • [5] Probabilistic risk assessment of ATC based on reflective slice sampling for power system with wind farm
    Zhang X.
    Jia L.
    Wang K.
    Zhang L.
    Chen W.
    [J]. Dianli Zidonghua Shebei/Electric Power Automation Equipment, 2017, 37 (07): : 25 - 31
  • [6] Probabilistic Power Flow Analysis Based on the Stochastic Response Surface Method
    Ren, Zhouyang
    Li, Wenyuan
    Billinton, Roy
    Yan, Wei
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2016, 31 (03) : 2307 - 2315
  • [7] Probabilistic Power Flow Analysis Based on the Stochastic Response Surface Method
    Ren, Zhouyang
    Li, Wenyuan
    Billinton, Roy
    Yan, Wei
    [J]. 2016 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING (PESGM), 2016,
  • [8] A STOCHASTIC PROGRAMMING METHOD FOR UNIT COMMITMENT OF WIND INTEGRATED POWER SYSTEM
    Shao Jian
    Zhang Buhan
    Deng Weisi
    Zhang Kaimin
    Jin Binjie
    Ge Tengyu
    [J]. THERMAL, POWER AND ELECTRICAL ENGINEERING, PTS 1 AND 2, 2013, 732-733 : 1390 - 1395
  • [9] Probabilistic assessment of available transfer capability considering spatial correlation in wind power integrated system
    Luo Gang
    Chen Jinfu
    Cai Defu
    Shi Dongyuan
    Xianzhong, Duan
    [J]. IET GENERATION TRANSMISSION & DISTRIBUTION, 2013, 7 (12) : 1527 - 1535
  • [10] Wind Farm Dynamic Equivalent Modeling Method for Power System Probabilistic Stability Assessment
    Wang, Peng
    Zhang, Zhenyuan
    Huang, Qi
    Lee, Wei-Jen
    [J]. 2019 IEEE INDUSTRY APPLICATIONS SOCIETY ANNUAL MEETING, 2019,