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Use of Available Daylight to Improve Short-Term Load Forecasting Accuracy


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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%.
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



Creative Commons La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.