Proposed Metric for Evaluation of Solar Forecasting Models
By Ricardo Marquez, Carlos F. M. Coimbra. 2013
162 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Management Science and Operations Research, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/dfb9d908c18a01935d808f0c78e9865ee9697488
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Carlos F. M. Coimbra
- Ricardo Marquez
- F. J. Martínez-de-Pisón
- Fernando Antoñanzas-Torres
- Javier Antoñanzas
- R. Escobar
- Rubén Urraca
- N. Osório
In Management Science and Operations Research
In Renewable Energy, Sustainability and the Environment
Citations in the corpus
- Review of photovoltaic power forecasting (2016, background): “Marquez and Coimbra (2013) defined those two terms, which have been adapted here for PV power, (30) and (31).”
- Intra-hour DNI forecasting based on cloud tracking image analysis (2013, methodology): “For 1-h ahead forecasting, Perez et al. (2010) obtained 8–10% improvement over persistence using cloud motion forecasts from satellite images; Marquez and Coimbra (2013) obtained 12–20% using a ANNs; and Martin et al. (2010) obtained 10–15% also using ANNs.”
- Benefits of solar forecasting for energy imbalance markets (2016, unknown): “Forecast skill is a measure to compare the performance of the proposed model against the benchmark model [37].”