Determination of the output power of wind generators is always associated with some uncertainties due to wind speed and other weather parameters variation, and accurate short-term forecasts are essential for their efficient operation. This can efficiently support transmission and distribution system operators and schedulers to improve the power network control and management. In this paper, we ...

In this paper, a new approach is proposed in order to select an optimal membership function for inputs of wind speed prediction system. Then using a fuzzy method and the stochastic characteristics of wind speed in the previous year, the wind speed modeling is performed and the wind speed for the future year will be predicted. In this proposed method, the average and the standard deviation of in...

Wind energy has been part of the fastest growing renewable energy sources that is clean and pollution-free, which has been increasingly gaining global attention, and wind speed forecasting plays a vital role in the wind energy field, however, it has been proven to be a challenging task owing to the effect of various meteorological factors. This paper proposes a hybrid forecasting model, which c...

The scope of this paper is to forecast wind speed. Wind speed, temperature, wind direction, relative humidity, precipitation of water content and air pressure are the main factors make the wind speed forecasting as a complex problem and neural network performance is mainly influenced by proper hidden layer neuron units. This paper proposes new criteria for appropriate hidden layer neuron unit’s...

This paper considers the effect of nonlinear atmospheric disturbances on wind power prediction. A Lorenz system is introduced as an atmospheric disturbance model. Three new improved wind forecasting models combined with a Lorenz comprehensive disturbance are put forward in this study. Firstly, we define the form of the Lorenz disturbance variable and the wind speed perturbation formula. Then, d...

In this paper an ARIMA model is used for time-series forecast involving wind speed measurements. Results are compared with the performance of a back propagation type NNT. Results show that ARIMA model is better than NNT for short time-intervals to forecast (10 minutes, 1 hour, 2 hours and 4 hours). Data was acquired from a unit located in Southern Andalusia (Peñaflor, Sevilla), with a soft orog...

Wind energy has been well recognized as renewable resource in electricity generation. In this paper, a novel hybrid approach is proposed for wind speed forecasting in a Rostamabad in Iran, from 2002 to 2004. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system (PSO-ANFIS). The 10-minute average wind speed data from Ro...

Wind farms are producing a considerable portion of the world renewable energy. Since the output power of any wind farm is highly dependent on the wind speed, the power extracted from a wind park is not always a constant value. In order to have a non-disruptive supply of electricity, it is important to have a good scheduling and forecasting system for the energy output of any wind park. In this ...

In the recent years there is a lot of research happening to predict wind speed with several mathematical methods and biologically inspired computing techniques to reduce the prediction error. A new strategy in wind speed prediction is proposed in this paper and the Adaptive Neuro-Fuzzy Inference System (ANFIS) is applied to forecast the speed of wind. ANFIS can forecast very well of the next va...