A New Control Methodology of Wind Farm using Short-Term Ahead Wind Speed Prediction for Load Frequency Control of Power System

被引：5

作者：

Senjyu, Tomonobu ^{[1
]}

Tokudome, Motoki ^{[1
]}

Uehara, Akie ^{[1
]}

Kaneko, Toshiaki ^{[1
]}

Yona, Atsushi ^{[1
]}

Sekine, Hideomi ^{[2
]}

Kim, Chul-Hwan ^{[3
]}

机构：

[1] Univ Ryukyus, Dept Elect & Elect Engn, Nakagami, Japan

[2] Univ Ryukyus, Dept Educ Technol, Nakagami, Japan

[3] Sungkyunkwan Univ, Sch Elect & Comp Engn, Suwon, South Korea

来源：

2008 IEEE 2ND INTERNATIONAL POWER AND ENERGY CONFERENCE: PECON, VOLS 1-3 | 2008年

关键词：

Coordination Control; Disturbance Observer; Load Frequency Control; Power System; Wind Farm; Wind Speed Prediction;

D O I：

10.1109/PECON.2008.4762513

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Currently, there are several published reports on wind power detailing various researches based on such subjects as pitch angle control, variable speed wind turbines, energy storage systems, and so on. These reports propose output power leveling to reduce the adverse effects of power system frequency deviation. In this context, it is desirable to decrease frequency deviations of power systems by output power control of wind turbine generator that has potential of effective utilization. This paper presents an output power control methodology for wind farm which can decrease frequency deviations of a power system using load power estimation. Load power is estimated by a disturbance observer and, output power command for wind farm is determined according to estimated load. Besides, each wind turbine generator can also be controlled well during wind turbulence since the power command is determined by considering short-term ahead predicted wind speed. In order to verify the proposed method, simulation results are presented to show the effectiveness of considering wind turbulence and sudden load variation.

引用

页码：425 / +

页数：2

共 50 条

[1] A New Control Strategy for Smoothing of Wind Farm Output using Short-Term Ahead Wind Speed Prediction and Flywheel Energy Storage System [J].

Islam, Farzana ;

Hasanien, Hany. ;

Al-Durra, Ahmed ;

Muyeen, S. M. .

2012 AMERICAN CONTROL CONFERENCE (ACC), 2012, :3026-3031

[2] Short-term Prediction Models for Wind Speed and Wind Power [J].

Bai, Guangxing ;

Ding, Yanwu ;

Yildirim, Mehmet Bayram ;

Ding, Yan-Hong .

2014 2ND INTERNATIONAL CONFERENCE ON SYSTEMS AND INFORMATICS (ICSAI), 2014, :180-185

[3] A Frequency Control Method by Wind Farm & Battery using Load Estimation in Isolated Power System [J].

Uehara, Akie ;

Senjyu, Tomonobu ;

Yona, Atsushi ;

Funabashi, Toshihisa .

INTERNATIONAL JOURNAL OF EMERGING ELECTRIC POWER SYSTEMS, 2010, 11 (02)

[4] Very Short-term Wind Speed Prediction of a Wind Farm Based on Artificial Neural Network [J].

Ma, Rui ;

Hu, Shuju ;

Xu, Honghua .

PROGRESS IN RENEWABLE AND SUSTAINABLE ENERGY, PTS 1 AND 2, 2013, 608-609 :677-682

[5] A new control methodology of wind turbine generators for frequency control of power system in isolated island [J].

Kaneko, Toshiaki ;

Uehara, Akie ;

Yona, Atsushi ;

Senjyu, Tomonobu ;

Kim, Chul-Hwan .

WIND ENERGY, 2011, 14 (03) :407-423

[6] A Fuzzy-Based Output Power Smoothing of WECS using Short-Term Ahead Prediction of Wind Speed [J].

Izumi, Yuya ;

Pratap, Alok ;

Kinjyo, Yoshihisa ;

Uehara, Akie ;

Yona, Atsushi ;

Senjyu, Tomonobu ;

Funabashi, Toshihisa ;

Muhando, Endusa Billy .

IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ 2011), 2011, :2414-2419

[7] Wind farm virtual inertia coordinated control technology based on wind speed prediction [J].

Wang Z. ;

Gao J. ;

Zhao B. ;

Ding L. ;

Cao Y. .

Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2022, 43 (10) :138-143

[8] Short-Term Wind Speed Forecasting of Lelystad Wind Farm by using ANN Algorithms [J].

Sahay, Kishan Bhushan ;

Srivastava, Shwetank .

2018 6TH INTERNATIONAL ELECTRICAL ENGINEERING CONGRESS (IEECON), 2018,

[9] Short-Term Wind Speed and Wind Power Prediction Based on Meteorological Model Modification [J].

Liu, Tianze ;

Zhao, Yan ;

Sun, Gang ;

Ma, Yanjuan .

PROCEEDINGS OF 2020 IEEE 9TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS CONFERENCE (DDCLS'20), 2020, :742-747

[10] Adaptive wind farm frequency response control considering uneven wind speed [J].

Wang K. ;

Wan T. ;

Li H. ;

Huang K. ;

Kou P. .

Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2022, 43 (03) :366-372

← 1 2 3 4 5 →