Real-time prediction intervals for intra-hour DNI forecasts

被引:86
作者
Chu, Yinghao
Li, Mengying
Pedro, Hugo T. C.
Coimbra, Carlos F. M. [1 ]
机构
[1] Univ Calif San Diego, Dept Mech & Aerosp Engn, Ctr Excellence Renewable Resource Integrat, Jacobs Sch Engn, La Jolla, CA 92093 USA
基金
美国国家科学基金会;
关键词
Solar forecasting; Prediction intervals; Sky imaging; Support vector machines; Artificial neural networks; SUPPORT VECTOR MACHINES; SOLAR-RADIATION; CLOUD DETECTION; PROBABILISTIC FORECASTS; WIND POWER; IRRADIANCE; MODEL; SKY; CLASSIFICATION; METHODOLOGY;
D O I
10.1016/j.renene.2015.04.022
中图分类号
X [环境科学、安全科学];
学科分类号
083001 [环境科学];
摘要
We develop a hybrid, real-time solar forecasting computational model to construct prediction intervals (Pis) of one-minute averaged direct normal irradiance for four intra-hour forecasting horizons: five, ten, fifteen, and 20 min. This hybrid model, which integrates sky imaging techniques, support vector machine and artificial neural network sub-models, is developed using one year of co-located, high-quality irradiance and sky image recording in Folsom, California. We validate the proposed model using six-month of measured irradiance and sky image data, and apply it to construct operational PI forecasts in real-time at the same observatory. In the real-time scenario, the hybrid model significantly outperforms the reference persistence model and provides high performance PIs regardless of forecast horizon and weather condition. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:234 / 244
页数:11
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