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https://hdl.handle.net/11000/31226
Use of Available Daylight to Improve Short-Term Load Forecasting Accuracy
Título : Use of Available Daylight to Improve Short-Term Load Forecasting Accuracy |
Autor : López García, Miguel VALERO, SERGIO Sans Treserras, Carlos Senabre, Carolina |
Editor : MDPI |
Fecha de publicación: 2020-12-26 |
URI : https://hdl.handle.net/11000/31226 |
Resumen :
This paper introduces a new methodology to include daylight information in short-term
load forecasting (STLF) models. The relation between daylight and power consumption is obvious
due to the use of electricity in lighting in general. Nevertheless, very few STLF systems include
this variable as an input. In addition, an analysis of one of the current STLF models at the Spanish
Transmission System Operator (TSO), shows two humps in its error profile, occurring at sunrise
and sunset times. The new methodology includes properly treated daylight information in STLF
models in order to reduce the forecasting error during sunrise and sunset, especially when daylight
savings time (DST) one-hour time shifts occur. This paper describes the raw information and the
linearization method needed. The forecasting model used as the benchmark is currently used at
the TSO’s headquarters and it uses both autoregressive (AR) and neural network (NN) components.
The method has been designed with data from the Spanish electric system from 2011 to 2017 and
tested over 2018 data. The results include a justification to use the proposed linearization over other
techniques as well as a thorough analysis of the forecast results yielding an error reduction in sunset
hours from 1.56% to 1.38% for the AR model and from 1.37% to 1.30% for the combined forecast.
In addition, during the weeks in which DST shifts are implemented, sunset error drops from 2.53%
to 2.09%.
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Palabras clave/Materias: daylight load forecasting power demand |
Área de conocimiento : CDU: Ciencias aplicadas: Ingeniería. Tecnología: Ingeniería mecánica en general. Tecnología nuclear. Electrotecnia. Maquinaria |
Tipo documento : application/pdf |
Derechos de acceso: info:eu-repo/semantics/openAccess Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
DOI : https://dx.doi.org/10.3390/en14010095 |
Aparece en las colecciones: Artículos Ingeniería Mecánica y Energía
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La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.