Review of photovoltaic power forecasting

被引:811
作者
Antonanzas, J. [1 ]
Osorio, N. [2 ]
Escobar, R. [2 ,3 ]
Urraca, R. [1 ]
Martinez-de-Pison, F. J. [1 ]
Antonanzas-Torres, F. [1 ]
机构
[1] Univ La Rioja, Dept Mech Engn, EDMANS Grp, Logrono, Spain
[2] Ctr Solar Energy Technol, Av Vicuna Mackenna 4860, Santiago, Chile
[3] Pontificia Univ Catolica Chile, Av Vicuna Mackenna 4860, Santiago, Chile
关键词
Solar energy; Solar power forecasting; Value of forecasting; Grid integration; ARTIFICIAL NEURAL-NETWORK; STATISTICAL REGRESSION METHODS; SOLAR POWER; ENERGY GENERATION; CLOUD MOTION; BASE-LINE; OUTPUT; PREDICTION; IRRADIANCE; MODELS;
D O I
10.1016/j.solener.2016.06.069
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
Variability of solar resource poses difficulties in grid management as solar penetration rates rise continuously. Thus, the task of solar power forecasting becomes crucial to ensure grid stability and to enable an optimal unit commitment and economical dispatch. Several forecast horizons can be identified, spanning from a few seconds to days or weeks ahead, as well as spatial horizons, from single site to regional forecasts. New techniques and approaches arise worldwide each year to improve accuracy of models with the ultimate goal of reducing uncertainty in the predictions. This paper appears with the aim of compiling a large part of the knowledge about solar power forecasting, focusing on the latest advancements and future trends. Firstly, the motivation to achieve an accurate forecast is presented with the analysis of the economic implications it may have. It is followed by a summary of the main techniques used to issue the predictions. Then, the benefits of point/regional forecasts and deterministic/probabilistic forecasts are discussed. It has been observed that most recent papers highlight the importance of probabilistic predictions and they incorporate an economic assessment of the impact of the accuracy of the forecasts on the grid. Later on, a classification of authors according to forecast horizons and origin of inputs is presented, which represents the most up-to-date compilation of solar power forecasting studies. Finally, all the different metrics used by the researchers have been collected and some remarks for enabling a fair comparison among studies have been stated. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:78 / 111
页数:34
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