Short-Term Load Forecasting 2019

• Andere auteurs: Gabaldón, Antonio (Redacteur), Ruiz-Abellón, Dr. María Carmen (Redacteur), Fernández-Jiménez, Luis Alfredo (Redacteur)
• Formaat: Elektronisch Hoofdstuk
• Taal: Engels
• Gepubliceerd in: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Onderwerpen: History of engineering & technology; short-term load forecasting; demand-side management; pattern similarity; hierarchical short-term load forecasting; feature selection; weather station selection; load forecasting; special days; regressive models; electric load forecasting; data preprocessing technique; multiobjective optimization algorithm; combined model; Nordic electricity market; electricity demand; component estimation method; univariate and multivariate time series analysis; modeling and forecasting; deep learning; wavenet; long short-term memory; demand response; hybrid energy system; data augmentation; convolution neural network; residential load forecasting; forecasting; time series; cubic splines; real-time electricity load; seasonal patterns; Load forecasting; VSTLF; bus load forecasting; DBN; PSR; distributed energy resources; prosumers; building electric energy consumption forecasting; cold-start problem; transfer learning; multivariate random forests; random forest; electricity consumption; lasso; Tikhonov regularization; load metering; preliminary load; short term load forecasting; performance criteria; power systems; cost analysis; day ahead; feature extraction; deep residual neural network; multiple sources; electricity
• Online toegang: DOAB: download the publication; DOAB: description of the publication

Short-term load forecasting (STLF) plays a key role in the formulation of economic, reliable, and secure operating strategies (planning, scheduling, maintenance, and control processes, among others) for a power system and will be significant in the future. However, there is still much to do in these...