Solar Irradiance Ramp Forecasting Based on All-Sky Imagers
Logothetis, Stavros-Andreas; Salamalikis, Vasileios; Nouri, Bijan; Remund, Jan; Zarzalejo, Luis F.; Xie, Yu; Wilbert, Stefan; Ntavelis, Evangelos; Nou, Julien; Hendrikx, Niels; Visser, Lennard; Sengupta, Manajit; Pó, Mário; Chauvin, Remi; Grieu, Stéphane; Blum, Niklas; Sark, Wilfried van; Kazantzidis, Andreas
(2022) Energies, volume 15, issue 17, pp. 1 - 17
(Article)
Abstract
Solar forecasting constitutes a critical tool for operating, producing and storing generated power from solar farms. In the framework of the International Energy Agency’s Photovoltaic Power Systems Program Task 16, the solar irradiance nowcast algorithms, based on five all-sky imagers (ASIs), are used to investigate the feasibility of ASIs to
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foresee ramp events. ASIs 1–2 and ASIs 3–5 can capture the true ramp events by 26.0–51.0% and 49.0–92.0% of the cases, respectively. ASIs 1–2 provided the lowest (
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Keywords: all-sky imagers, solar irradiance ramp event forecasting, ramp events, forecasting
ISSN: 1996-1073
Publisher: MDPI AG
Note: Funding Information: This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH—CREATE—INNOVATE (project code: T1EDK-00681). We acknowledge support of this work by the project “PANhellenic infrastructure for Atmospheric Composition and climatE change” (MIS 5021516) which is implemented under the Action “Reinforcement of the Research and Innovation Infrastructure”, funded by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014-2020) and co-financed by Greece and the European Union (European Regional Development Fund). DLR’s contribution to the study benchmarking experiment was funded by the German Federal Ministry of for Economic Affairss and Technology Climate Action within the WOBAS A project (Grant Agreement no. 0324307A) while the contributions on the definition of evaluation metrics were funded within the Solrev project (Grant Agreement no. 03EE1010C). Niels Hendrikx, Lennard Visser and Wilfried van Sark acknowledge support from the Dutch Research Council NWO in the framework of the Energy Systems Integration & Big Data programme, project eNErgy intrAneTs (NEAT). This work constitutes the main contribution of several experts to activity 3.4 of the Task 16 IEA-PVPS. Publisher Copyright: © 2022 by the authors.
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