Generation of wind power time series to fit time-domain characteristics

被引：1
|
作者：
Li, Jinghua [1 ,3 ]
Wen, Jinyu [1 ]
Li, Jiaming [1 ]
Cheng, Shijie [1 ]
Yu, Peng [1 ]
Luo, Weihua [2 ]
机构：
[1] Huazhong Univ Sci & Technol, State Key Lab Adv Elect Engn & Technol, Sch Elect & Elect Engn, Wuhan 430074, Peoples R China
[2] Liaoning Elect Power Co Ltd, Shenyang 110006, Peoples R China
[3] Guangxi Univ, Guangxi Power Syst Optimizat & Energy Saving Tech, Nanning 530004, Peoples R China
来源：
ELECTRONICS LETTERS | 2014年 / 50卷 / 23期
基金：
中国国家自然科学基金;
关键词：
MIMO communication; wireless channels; space division multiplexing; precoding; spatial multiplexing; MIMO channels; open-loop precoder; feedback channel information; SM; transmit-correlated multiinput-multioutput channels; channel correlation; amplitude parameters; phase parameters; random phase correlation;
D O I：
10.1049/el.2014.1908
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The generation of wind power time series is important for electric power system planning and decision making. A method to generate a synthetic series of wind power outputs is proposed, considering the state transition, the duration time and the variation features of wind power. The simulation results using the proposed method for 25 wind farms at six different locations in different countries show that the wind power time series generated by the proposed method are able to reflect more comprehensive wind power characteristics than that generated by the conventional Markov chain Monte Carlo (MCMC) method.
引用
收藏
页码：1734 / 1735
页数：2
相关论文
共 50 条
  • [21] Time-domain characteristics of complex computer networks
    Holden, RA
    Thomas, RW
    NAVAL ENGINEERS JOURNAL, 1998, 110 (02) : 61 - 72
  • [22] Time-series-based maximization of distributed wind power generation integration
    Ochoa, Luis F.
    Padilha-Feltrin, Antonio
    Harrison, Gareth P.
    IEEE TRANSACTIONS ON ENERGY CONVERSION, 2008, 23 (03) : 968 - 974
  • [23] Prediction of Wind Power Generation Based on Time Series Wavelet Transform for Large Wind Farm
    Dong, Lei
    Wang, Lijie
    Liao, Xiaozhong
    Gao, Yang
    Li, Yili
    Wang, Zhiwei
    2009 3RD INTERNATIONAL CONFERENCE ON POWER ELECTRONICS SYSTEMS AND APPLICATIONS: ELECTRIC VEHICLE AND GREEN ENERGY, 2009, : 64 - 64
  • [24] ARIMA-Based Time Series Model of Stochastic Wind Power Generation
    Chen, Peiyuan
    Pedersen, Troels
    Bak-Jensen, Birgitte
    Chen, Zhe
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2010, 25 (02) : 667 - 676
  • [25] Evaluation of hybrid forecasting approaches for wind speed and power generation time series
    Shi, Jing
    Guo, Jinmei
    Zheng, Songtao
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2012, 16 (05): : 3471 - 3480
  • [26] Time-Domain Analysis of Power Quality Adverse Effects of Grid Interconnected Photovoltaic Generation
    Cisneros-Magana, Rafael
    Medina, Aurelio
    Fuerte-Esquivel, Claudio R.
    2019 51ST NORTH AMERICAN POWER SYMPOSIUM (NAPS), 2019,
  • [27] Photonic time-domain electromagnetic arbitrary waveform generation
    Weiner, AM
    McKinney, JD
    2005 Conference on Lasers & Electro-Optics (CLEO), Vols 1-3, 2005, : 866 - 867
  • [28] Error analysis and improved method of time-domain distance protection for wind power transmission lines
    Xie, Zhongrun
    Li, Bin
    He, Jiawei
    Shao, Mingyu
    Zhou, Bohao
    Wu, Tonghua
    Hong, Feng
    Wang, Haiji
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2024, 160
  • [29] A Novel Principle of Directional relay for Wind Power Integration Based on Model Recognition in Time-domain
    Wang, Chenqing
    Song, Guobing
    Zhang, Jinhua
    2016 IEEE PES ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), 2016, : 1851 - 1855
  • [30] Generating wind power time series based on its persistence and variation characteristics
    LI Jing Hua
    LI Jia Ming
    WEN Jin Yu
    CHENG Shi Jie
    XIE Hai Lian
    YUE Cheng Yan
    Science China(Technological Sciences), 2014, (12) : 2475 - 2486
12345