0000000000341127

AUTHOR

Laura Frías-paredes

0000-0001-7444-6388

showing 3 related works from this author

Assessing energy forecasting inaccuracy by simultaneously considering temporal and absolute errors

2017

Abstract 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 fluctuations in energy generation that are difficult 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 defined…

Mathematical optimizationWind powerSeries (mathematics)Renewable Energy Sustainability and the Environmentbusiness.industryComputer science020209 energyPareto principleEnergy Engineering and Power Technology02 engineering and technology021001 nanoscience & nanotechnologyRenewable energyFuel TechnologyElectricity generationNuclear Energy and EngineeringDistortion0202 electrical engineering electronic engineering information engineering0210 nano-technologybusinessEnergy sourceEnergy (signal processing)Energy Conversion and Management
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Dynamic mean absolute error as new measure for assessing forecasting errors

2018

Abstract Accurate wind power forecast is essential for grid integration, system planning, and electricity trading in certain electricity markets. Therefore, analyzing prediction errors is a critical task that allows a comparison of prediction models and the selection of the most suitable model. In this work, the temporal error and absolute magnitude error are simultaneously considered to assess the forecast error. The trade-off between both types of errors is computed, analyzed, and interpreted. Moreover, a new index, the dynamic mean absolute error, DMAE, is defined to measure the prediction accuracy. This index accounts for both error components: temporal and absolute. Real cases of wind …

Absolute magnitudeWind powerIndex (economics)Renewable Energy Sustainability and the EnvironmentComputer sciencebusiness.industry020209 energyWork (physics)Energy Engineering and Power Technology02 engineering and technology021001 nanoscience & nanotechnologyGridMeasure (mathematics)Fuel TechnologyNuclear Energy and EngineeringStatistics0202 electrical engineering electronic engineering information engineeringElectricity0210 nano-technologybusinessPredictive modellingEnergy Conversion and Management
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Introducing the Temporal Distortion Index to perform a bidimensional analysis of renewable energy forecast

2016

Abstract Wind has been the largest contributor to the growth of renewal energy during the early 21st century. However, the natural uncertainty that arises in assessing the wind resource implies the occurrence of wind power forecasting errors which perform a considerable role in the impacts and costs in the wind energy integration and its commercialization. The main goal of this paper is to provide a deeper insight in the analysis of timing errors which leads to the proposal of a new methodology for its control and measure. A new methodology, based on Dynamic Time Warping, is proposed to be considered in the estimation of accuracy as attribute of forecast quality. A new dissimilarity measure…

Measure (data warehouse)Dynamic time warpingIndex (economics)Wind powerComputer sciencebusiness.industry020209 energyMechanical Engineeringmedia_common.quotation_subjectWind power forecasting02 engineering and technologyBuilding and ConstructionPollutionIndustrial and Manufacturing EngineeringRenewable energyGeneral EnergyDistortion0202 electrical engineering electronic engineering information engineeringEconometricsQuality (business)Electrical and Electronic EngineeringbusinessCivil and Structural Engineeringmedia_commonEnergy
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