Short‐term deterministic solar irradiance forecasting considering a heuristics‐based, operational approach

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dc.article.number6005
dc.article.number120712
dc.catalogadordfo
dc.contributor.authorCastillejo Cuberos, Armando
dc.contributor.authorBoland, John
dc.contributor.authorEscobar Moragas, Rodrigo
dc.date.accessioned2023-10-10T20:08:12Z
dc.date.available2023-10-10T20:08:12Z
dc.date.issued2021
dc.description.abstractSolar energy is an economic and clean power source subject to natural variability, while energy storage might attenuate it, ultimately, effective and operationally feasible forecasting techniques for energy management are needed for better grid integration. This work presents a novel deterministic forecast method considering: irradiance pattern classification, Markov chains, fuzzy logic and an operational approach. The method developed was applied in a rolling manner for six years to a target location with no prior data to assess performance and its changes as new local data becomes available. Clearness index, diffuse fraction and irradiance hourly forecasts are analyzed on a yearly basis but also for 20 day types, and compared against smart persistence. Results show the proposed method outperforms smart persistence by ~10% for clearness index and diffuse fraction on the base case, but there are significant differences across the 20 day types analyzed, reaching up to +60% for clear days. Forecast lead time has the greatest impact in forecasting performance, which is important for any practical implementation. Seasonality in data gaps or rejected data can have a definite effect in performance assessment. A novel, comprehensive and detailed analysis framework was shown to present a better assessment of forecasters’ performance.
dc.description.funderCORFO
dc.description.funderPontificia Universidad Católica de Chile
dc.fechaingreso.objetodigital2023-10-10
dc.format.extent24 páginas
dc.fuente.origenORCID
dc.identifier.doi10.3390/en14186005
dc.identifier.eissn1996-1073
dc.identifier.issn1996-1073
dc.identifier.scopusidSCOPUS_ID:85115376407
dc.identifier.urihttps://www.mdpi.com/1996-1073/14/18/6005/pdf
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/75071
dc.information.autorucEscuela de Ingeniería ; Castillejo Cuberos Armando ; 0000-0002-0742-4661 ; 1050239
dc.information.autorucEscuela de Ingeniería ; Escobar Moragas Rodrigo Alfonso ; S/I ; 158663
dc.issue.numero18
dc.language.isoen
dc.nota.accesoContenido completo
dc.pagina.final24
dc.pagina.inicio1
dc.publisherMDPI
dc.relation.ispartofEnergies
dc.revistaEnergies
dc.rightsacceso abierto
dc.subjectFuzzy logic
dc.subjectHeuristics
dc.subjectMarkov chains
dc.subjectRenewable energy
dc.subjectSolar energy
dc.subjectSolar power forecasting
dc.subject.ddc620
dc.subject.deweyIngenieríaes_ES
dc.titleShort‐term deterministic solar irradiance forecasting considering a heuristics‐based, operational approach
dc.typeartículo
dc.volumen14
sipa.codpersvinculados1050239
sipa.codpersvinculados158663
sipa.indexSCOPUS
sipa.indexWOS
sipa.trazabilidadSCOPUS;21-03-2022
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