2085 KB89 KB201420202020Dragan, DejanHammad, Mahmoud A.Jereb, BorutRosi, Bojanletnik:11številka:iss. 1str. 51-76DOI:10.2478/jlst-2020-0004ISSN:2232-4968COBISSID_HOST:513089597URN:URN:NBN:SI:doc-P3QUKHD1enDe Gruyter PolandFakulteta za logistikoLogistics and sustainable transportelectric load forecastingelectricity industryelektrične obremenitveelektroenergetska industrijalogisticslogistikamethodsmetodemodelimodeling electricity loadsmodeliranje električnih obremenitevmodelsnapovedovanje obremenitev z električno energijopower managementupravljanje električne energijeMethods and models for electric load forecasting| a comprehensive review|Electric load forecasting (ELF) is a vital process in the planning of the electricity industry and plays a crucial role in electric capacity scheduling and power systems management and, therefore, it has attracted increasing academic interest. Hence, the accuracy of electric load forecasting has great importance for energy generating capacity scheduling and power system management. This paper presents a review of forecasting methods and models for electricity load. About 45 academic papers have been used for the comparison based on specified criteria such as time frame, inputs, outputs, the scale of the project, and value. The review reveals that despite the relative simplicity of all reviewed models, the regression analysis is still widely used and efficient for long-term forecasting. As for short-term predictions, machine learning or artificial intelligence-based models such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Fuzzy logic are favoredTEXTznanstveno časopisjejournalsSlovenian National E-content AggregatorNational and University Library of SloveniaUniverza v Mariboru, Fakulteta za logistiko