The role of renewable energy sources in the Polish power system is growing. highest share installed capacity goes to wind and solar energy. Both are characterized by high variability their output very low dispatchability. Taking into account nature system, it is, therefore, imperative predict future generation economically schedule use conventional generators. Considering above, this paper exam...

This paper elaborates on a problem of one-year ahead estimation of energy demand based on macroeconomic variables. To this end, two different Computational Intelligence approaches are herein evaluated: (1) a modified Harmony Search (HS) optimization algorithm with an exponential prediction model and (2) an Extreme Learning Machine (ELM). In the case of the HS, a feature selection of the best se...

This paper proposes an optimal ensemble method for one-day-ahead hourly wind power forecasting. The forecasting is the most common of meteorological Several different models are combined to increase accuracy. proposed has three stages. first stage uses k-means classify generation data into five distinct categories. In second stage, single prediction models, including a K-nearest neighbors (KNN)...

Due to the increasing proportion of wind power connected grid, day-ahead prediction plays a more and important role in operation system. This paper proposes short-term model based on deep learning (DWT_AE_BiLSTM). Firstly, discrete wavelet transform (DWT) is used denoise data, then an autoencoder (AE) technology extract data features, finally, bidirectional long memory (BiLSTM) for prediction. ...