Wind speed and energy forecasting at different time scales: A nonparametric approach

D’Amico, Guglielmo, Filippo Petroni () and Flavio Prattico

Physica A: Statistical Mechanics and its Applications, 2014, vol. 406, issue C, 59-66

Abstract: 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 model, that reproduces accurately the statistical behavior of wind speed. The model is used to forecast future wind speed and the energy produced through a 10 kW Aircon wind turbine. We forecast one step ahead and for different time scales. In order to check the main features of the model we show, as indicator of goodness, the root mean square error between real data and predicted ones. We compare our forecasting results with those of a persistence model and of an autoregressive model.

Keywords: Wind speed; Forecasting model; Indexed semi-Markov chains; Energy forecasting; Persistence model; Autoregressive model (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:406:y:2014:i:c:p:59-66

DOI: 10.1016/j.physa.2014.03.034

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