A Novel Reliability Evaluation Method of AC/DC Hybrid Power System with the Injection of Wind Power

被引:0
|
作者
Wang, Can [1 ]
Xie, Haipeng [1 ]
Liu, Shiyu [1 ]
Bie, Zhaohong [1 ]
机构
[1] Xi An Jiao Tong Univ, State Key Lab Elect Insulat & Power Equipment, Shaanxi Prov Key Lab Smart Grid, Xian, Shaanxi, Peoples R China
来源
2017 IEEE ELECTRICAL POWER AND ENERGY CONFERENCE (EPEC) | 2017年
基金
中国国家自然科学基金;
关键词
AC/DC hybrid power system; HVDC; wind power; BP neural network; Monte-Carlo method;
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 rapid development of HVDC projects and renewable energy, reliability of AC/DC hybrid power system with wind power draws more and more attention. To depict the uncertainty of wind power, this paper proposes the wind power BP neural network model to fit the probability distribution of actual wind speed. Compared with traditional wind power models such as Weibull distribution model, the BP neural network model is closer to the actual probability distribution of wind speed according to numerical results. By using Monte Carlo method, the AC/DC hybrid system states are obtained. Then considering the interaction between AC and DC system, a novel minimum load shedding model of hybrid system with HVDC is proposed. IEEE-RTS 96 system is testified with actual Northern China wind data, which illustrates a more accurate wind power modeling as well as a comprehensive reliability evaluation on AC/DC hybrid power system integrated with wind power.
引用
收藏
页码:225 / 230
页数:6
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