This paper investigates the potential for systematic errors in the Energy Information Administration’s (EIA) widely used Annual Energy Outlook, focusing on the near- to midterm projections of energy demand as measured in physical quantities. Overall, based on an analysis of the EIA’s 22-year...

The paper deals with a modeling procedure which aims to predict the power output of wind farm electricity generators. The following modeling steps are proposed: factor selection, raw data pretreatment, model evaluation and optimization. Both heuristic and formal methods are combined to construct...

Forecasting of electricity demand has assumed a lot of importance to provide sustainable solutions to the electricity problems. LEAP has been used to forecast electricity demand for the target year 2030, for the state of Maharashtra (India). Holt’s exponential smoothing method has been used to...

The prediction of wind speed is one of the most important aspects when dealing with renewable energy. In this paper we show a new nonparametric model, based on semi-Markov chains, to predict wind speed and the energy produced by a commercial blade. Particularly, we use an indexed semi-Markov...

In 2013, American Meteorological Society Committees on AI (artificial intelligence) Applications organized a short-term solar energy prediction competition aiming at predicting total daily solar energy received at 98 solar farms based on the outputs of various weather patterns of a numerical...

This paper discusses the building process and models used by Red Eléctrica de España (REE), the Spanish system operator, in short-term electricity load forecasting. REE's forecasting system consists of one daily model and 24 hourly models with a common structure. There are two types of...