in this paper the maximum power point tracking (mppt) algorithms for wind energy systems arereviewed. as the amounts of power produced in wind power plants is changing due to theinstantaneous changing nature of the wind, it is desirable to determine the one optimal generatorspeed that ensures maximum energy yield. thus, it is important to include a controller that cantrack the maximum peak rega...

Wind energy is rapidly increasing and it is becoming a significant contributor to the electricity grid. Wind speed is an important factor in wind power production and integration. This paper presents a wind speed forecasting using feature selection method and bagging neural network. Feature selection plays an essential role in the machine learning environment and especially in the prediction ta...

The renewable wind power generation spreads over. The application of wind turbines requires wind prediction and nation wide production control. The generation forecasts are based on measurements, models and wind turbine characteristics. In this paper we introduce the validation of the characteristics through the definition of the relationship between the real measurements. We found that the pur...

Iran is a country completely dependent on fossil fuel resources. In order to obtain a diversity of energy sources, it requires other resources, especially renewable energy. Utilization of wind energy appears to be one of the most efficient ways of achieving sustainable development. The quantification of wind potential is a pivotal and essential initial step while developing strategies for the de...

Full scale measurements of the propulsion power, ship speed, wind speed and direction, sea and air temperature, from four different loading conditions has been used to train a neural network for prediction of propulsion power. The network was able to predict the propulsion power with accuracy between 0.8-2.8%, which is about the same accuracy as for the measurements. The methods developed are i...

Abstract. From small farms to electricity markets the interest and importance of wind power production is continuously increasing. This interest is mainly caused by the fact that wind is a continuous resource of clean energy. To take full advantage of the potential of wind power production it is crucial to have tools that accurately forecast the expected wind speed. However, forecasting the win...

To address the static voltage stability issue and suppress the voltage fluctuation caused by the increasing integration of wind farms and solar photovoltaic (PV) power plants, a two-tier reactive power and voltage control strategy based on ARMA power forecasting models for wind and solar plants is proposed in this paper. Firstly, ARMA models are established to forecast the output of wind farms ...

It is important to improve the accuracy of wind speed forecasting for wind parks management and wind power utilization. In this paper, a novel hybrid approach known as WTT-TNN is proposed for wind speed forecasting. In the first step of the approach, a wavelet transform technique (WTT) is used to decompose wind speed into an approximate scale and several detailed scales. In the second step, a t...

In this paper, a wind prediction system for the wind power generation using ensemble of multiple complex extreme learning machines (C-ELM) is proposed. The extreme learning machines is a single layer feed forward neural network having a fast learning and better generalization ability than the gradient-based learning methods. C-ELM is chosen as base classifier because it is very suitable for pro...