E3S Web Conf.
Volume 152, 20202019 International Conference on Power, Energy and Electrical Engineering (PEEE 2019)
|Number of page(s)||5|
|Section||Photovoltaic Power Generation System and Technology|
|Published online||14 February 2020|
Probabilistic reference model for hourly PV power generation forecasting
Department of Electrical Engineering, University of La Rioja, 26004 Logroño, Spain
* Corresponding author: firstname.lastname@example.org
This paper presents a new probabilistic forecasting model of the hourly mean power production in a Photovoltaic (PV) plant. It uses the minimal information and it can provide probabilistic forecasts in the form of quantiles for the desired horizon, which ranges from the next hours to any day in the future. The proposed model only needs a time series of hourly mean power production in the PV plant, and it is intended to fill a gap in international literature where hardly any model has been proposed as a reference for comparison or benchmarking purposes with other probabilistic forecasting models. The performance of the proposed forecasting model is tested, in a case study, with the time series of hourly mean power production in a PV plant with 1.9 MW capacity. The results show an improvement with respect to the reference probabilistic PV power forecasting models reported in the literature.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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