Based on Scene Classification Method of Wind-PV Output Coupling Mechanism

Abstract:

Load tracking and output forecast error are less researched in wind and photovoltaic (PV) systems synthetic of output coupling power in present time. This paper using the technology of data mining of according to the wind and PV output characteristics with different scenario data partitioning method to the Wind and PV resource rich region of the actual wind power and PV output data divides the scene under the typical scenario data of division of Wind and PV complementary output coupling characteristics are analyzed and studied the mechanism of synthesis of output tracking system load characteristics and improve the output prediction error problem. Studies have shown that Wind and PV complementary synthetic efforts to a certain extent, reduced the coupling characteristics of output volatility, the system load tracking degree reached 14.1%.

• Periodical: Applied Mechanics and Materials (Volumes 448-453)
• Pages: 1845-1850
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.448-453.1845
• Online since: October 2013
• Authors: Qing Luo*, Qin Chao, Yi Bo Wang, Jian Chun Luo, Gai Qian Liu
• Keywords: Scene Classification Method, Tracking the Load, Wind and PV Systems Synthetic Output Power

References

[1] Chong Ying Xiao, Ning Bo Wang, Jing Zhi, Kun Ding, Gansu Jiuquan wind power output characteristic analysis [J]. Power Systems, 2010, 9, 34 (17), P64-67, In Chinese.

[2] Xiaoqi Han, Xuan Kun Song, Chill Li, Qingru Qi. Changes in wind power output of the FM system [J]. Chinese power, 2010, 6, 43 (6), P26-29, In Chinese.

[3] Yilu Zhang, Yan Chang, Guoqin Yu, Dakang Zhu. Photovoltaic power plants and the impact on the power grid reliability [J]. East China Electric Power, 2010, 5, 38 (5), P0700-0706, In Chinese.

[4] Sun Chuanyong, Peng Youbing high Yuanyuan, YU Guang Liang, Jiang Ning, Wei Lei numerical model of the solar output Analysis Research [J]. Power System and Clean Energy, 2012, 8, 28 (8), P73-76, In Chinese.

[5] Chen Can, Wu Chuan, ZHANG Bo-ming, Qin Jianguang, Derek Kwok-based multi-scenario technology, active distribution network reliability assessment [J]. Proceeding of the CSEE, 201212, 32 (34), P67-73, In Chinese.

[6] Ye Hang governance. Wind power generation system design, operation and maintenance (first edition) [M]. Beijing: Electronic Industry Press, 2010: 90 - 94, 183 - 187, In Chinese.

[7] Ju Ping, Chen Qian, Xiongzhuan Ping, etc. Based on daily load curve load classification and integrated modeling [J]. Power Systems, 2006, 30 (16) : 6-9, In Chinese.

[8] Lu Jiping, Bai Shuhua. Scenery Hydrogen Joint-alone power system modeling and simulation [J]. Power System Technology, 2007, 11; 75-79, In Chinese.

[9] Dong-Jing Lee , Li Wang. Small-Signal Stability Analysis of an AutonomousHybrid Renewable Energy Power Generation/Energy Storage System Part I: Time-Domain Simulations. [J] IEEE Journals & Magazines, 2008, 311-320, In Chinese.

DOI: 10.1109/tec.2007.914309

[10] Cai Guowei, Ling country Yangde You, Pan Chao, Sun Zhenglong. Scale wind and solar hair modeling and operational characteristics of the system [J]. Power System Technology, 2012, 1; 65-71, In Chinese.

[11] ZHENG Kuan, ZHANG Jian-hua, LIU Wen-xia. Distribution Network Reliability Considering Complementary Distribution Generation with Wind and Photovoltaic Powers. [J] IEEE Conference Publications, 2010, 1-5.

DOI: 10.1109/cris.2010.5617519