Cloud Motion Forecasting and Cloud Base Height Estimation Using Two Low-Cost Sky Cameras

被引:0
|
作者
Zhang, Can [1 ]
Du, Yang [1 ]
Chen, Xiaoyang [1 ]
Lim, Eng Gee [1 ]
机构
[1] Xian Jiaotong Liverpool Univ, Dept Elect & Elect Engn, Suzhou, Peoples R China
来源
2018 2ND IEEE CONFERENCE ON ENERGY INTERNET AND ENERGY SYSTEM INTEGRATION (EI2) | 2018年
基金
中国国家自然科学基金;
关键词
cloud motion vector tracking; cloud base height estimation; solar power ramp-rate control; ultra short-time forecasting; SOLAR-RADIATION; SYSTEM;
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
Passing cloud results in rapid irradiance changes. The intermittency of PV output power has drawn serious concern as the PV system installation increases. Consequently, power ramp-rate control (PRRC) is introduced as the regulation to limit significant power fluctuations. These requirements are driving an increasing demand for ultra short-term PV power forecasting. Sky imager has been used as an effective tool to predict the cloud motion, then to forecast the PV power. However, the high cost of sky imager system and low update frequency are still hindering its application in PRRC. The estimation of cloud base height (CBH) is also a challenging using sky imager. In this paper, a low-cost cloud motion tracking system has been developed. Ultra short-term cloud motion forecasting has been achieved in seconds level which can be used in PRRC application. The proposed cloud tracking method improves the forecasting accuracy by multiple cloud centroid tracking. Secondly, a novel sky camera based CBH estimation method is proposed. The effectiveness of the proposed CBH estimation method has been verified by experiment results.
引用
收藏
页数:6
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