Review of photovoltaic power forecasting

  1. Antonanzas, J. 2
  2. Osorio, N. 1
  3. Escobar, Rodrigo A . 13
  4. Urraca, R. 2
  5. Martinez-de-Pison, F.J. 2
  6. Antonanzas-Torres, F. 2
  1. 1 Center for Solar Energy Technologies, Av. Vicuña Mackenna 4860, Macul, Santiago, Chile
  2. 2 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

  3. 3 Pontificia Universidad Católica de Chile
    info

    Pontificia Universidad Católica de Chile

    Santiago de Chile, Chile

    ROR https://ror.org/04teye511

Revista:
Solar Energy

ISSN: 0038-092X

Año de publicación: 2016

Volumen: 136

Páginas: 78-111

Tipo: Artículo

DOI: 10.1016/J.SOLENER.2016.06.069 SCOPUS: 2-s2.0-84977650217 WoS: WOS:000383004200009 GOOGLE SCHOLAR

Otras publicaciones en: Solar Energy

Resumen

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. © 2016 Elsevier Ltd