Gastón Romeo, Martín

Profile Picture

Email Address

person.page.identifierURI

https://academica-e.unavarra.es/handle/2454/49134

Birth Date

Job Title

Last Name

Gastón Romeo

First Name

Martín

person.page.departamento

Estadística, Informática y Matemáticas

person.page.instituteName

ISC. Institute of Smart Cities

ORCID

0000-0001-5175-9381

person.page.observainves

751015

person.page.upna

4616

Name

Filters

20171
Reset filters

Settings

Author: León, Teresa × Subject: Energy forecasting accuracy ×

Search Results

Now showing 1 - 1 of 1
  • Thumbnail Image
    PublicationOpen Access
    Assessing energy forecasting inaccuracy by simultaneously considering temporal and absolute errors
    (Elsevier, 2017-04-17) Frías Paredes, Laura; Mallor Giménez, Fermín; Gastón Romeo, Martín; León, Teresa; Estadística e Investigación Operativa; Estatistika eta Ikerketa Operatiboa; Institute of Smart Cities - ISC
    Recent years have seen a growing trend in wind and solar energy generation globally and it is expected that an important percentage of total energy production comes from these energy sources. However, they present inherent variability that implies uctuations in energy generation that are dicult to forecast. Thus, forecasting errors have a considerable role in the impacts and costs of renewable energy integration, management, and commercialization. This study presents an important advance in the task of analyzing prediction models, in particular, in the timing component of prediction error, which improves previous pioneering results. A new method to match time series is dened in order to assess energy forecasting accuracy. This method relies on a new family of step patterns, an essential component of the algorithm to evaluate the temporal distortion index (TDI). This family minimizes the mean absolute error (MAE) of the transformation with respect to the reference series (the real energy series) and also allows detailed control of the temporal distortion entailed in the prediction series. The simultaneous consideration of temporal and absolute errors allows the use of Pareto frontiers as characteristic error curves. Real examples of wind energy forecasts are used to illustrate the results.