The series model applied to predict the wind power energy production
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Wind power, via wind turbine, transforms mechanical energy to electrical energy. It is an alternative to burning fossil fuels, it is plentiful, renewable, widely distributed, clean, produces no greenhouse gas emissions during operation, consumes no water, and uses little surface of land. The net effects on the environment are far less problematic than those of fossil fuel sources. This paper proposes a forecasting model based on time series technique for wind power energy generation. The increasing use of renewable energy from solar and wind sources has gained acceptance and is being increasingly used. The main problems with these energies sources are the dependence of power output on the environmental parameters and the circadian variation. In order to obtain a continuous time series, average daily specific power records, W/m2, are used and moving average and exponential smoothing were tested to evidence the trend and seasonal patterns. The resulting data were correlated in mathematical models which were in good agreement with data collected from a Romanian wind power energy plant.
time series technique, wind energy generation, forecasting model, probabilistic forecasting