Short-Term PV Power Forecasts Based on a Real-Time Irradiance Monitoring Network

被引:0
|
作者
Lorenzo, Antonio T. [1 ]
Holmgren, William F. [2 ]
Leuthold, Michael [3 ]
Kim, Chang Ki [3 ]
Cronin, Alexander D. [2 ]
Betterton, Eric A. [3 ]
机构
[1] Univ Arizona, Coll Opt Sci, Tucson, AZ 85721 USA
[2] Univ Arizona, Dept Phys, Tucson, AZ 85721 USA
[3] Univ Arizona, Dept Atmospher Sci, Tucson, AZ USA
来源
2014 IEEE 40TH PHOTOVOLTAIC SPECIALIST CONFERENCE (PVSC) | 2014年
关键词
data analysis; forecasting; real-time systems; sensors; solar energy; UC SAN-DIEGO; SKY IMAGER; SOLAR;
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
We built an irradiance sensor network that we are now using to make operational, real-time, intra-hour forecasts of solar power at key locations. We developed reliable irradiance sensor hardware platforms to enable these sensor network forecasts. Using 19 of the 55 irradiance sensors we have throughout Tucson, we make retrospective forecasts of 26 days in April and evaluate their performance. We find that that our network forecasts outperform a persistence model for 1 to 28 minute time horizons as measured by the root mean squared error. The sensor hardware, our network forecasting method, error statistics, and future improvements to our forecasts are discussed.
引用
收藏
页码:75 / 79
页数:5
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