The empirical mode decomposition (EMD) is well known for predicting wind speed.However, but the joint application of relevance vector machine (RVM) and empirical mode decomposition in wind speed forecasting is seldom found in the field. This paper proposes a relevance vector machine model based on empirical mode decomposition to predict the wind speed. Before the wind speed forecasting with RVM...

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...

Many models have been developed to forecast wind farm power output. It is generally difficult to determine whether the performance of one model is consistently better than that of another model under all circumstances. Motivated by this finding, we aimed to integrate groups of models into an aggregated model using fuzzy theory to obtain further performance improvements. First, three groups of l...

Modern variable-speed wind turbines, although decoupled from the system frequency, can respond to significant power imbalances through power electronic controls as synthetic inertial or governor-like droop responses. However, frequency response capabilities from wind power plant cannot be considered a direct replacement for traditional frequency responsive services. Before such capabilities sho...

We discuss the accuracy of the prediction of the aggregated power output of wind farms distributed over given regions. Our forecasting procedure provides the expected power output for a time horizon up to 48 hours ahead. It is based on the large scale wind field prediction which is generated operationally by the German weather service. Our investigation focuses on the statistical analysis of th...

Sustainability is of great importance due to increasing demands and limited resources. Many problem classes in sustainable energy systems are data mining, optimization, and control tasks. In this work we demonstrate how techniques from computational intelligence can help in solving important tasks in sustainable energy systems. We will show how statistically sound wind models can be estimated w...

A microgrid can be operated in on-grid or off-grid, mode using distributed energy resources (DER), among which combined heat power can play an important role in increasing the total energy efficiency. This paper reports the total solutions to the problem of scheduling DER including CHP and their dispatch, called a generation application package. To increase the accuracy of forecasting, this pap...

Having an accurate model of the power curve of a wind turbine allows us to better monitor its operation and planning of storage capacity. Since wind speed and direction is of a highly stochastic nature, the forecasting of the power generated by the wind turbine is of the same nature as well. In this paper, a method for obtaining a robust confidence band containing the power curve of a wind turb...

We consider the operation of a wind turbine and a connected local battery or other electrical storage device, taking into account varying wind speed, with the goal of maximizing the total energy generated while respecting limits on the time derivative (gradient) of power delivered to the grid. We use the turbine inertia as an additional energy storage device, by varying its speed over time, and...