Title :
Short-term wind power forecasting using a hybrid evolutionary intelligent approach
Author :
Catalão, J. P S ; Osório, G.J. ; Pousinho, H.M.I.
Author_Institution :
Univ. of Beira Interior, Covilha, Portugal
Abstract :
This paper presents a hybrid evolutionary intelligent approach, based on a combination of evolutionary particle swarm optimization (EPSO) with an adaptive-network-based fuzzy inference system (ANFIS), for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses challenges due to its intermittency and volatility. Hence, good forecasting tools are important for tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated, reporting the numerical results from a real-world case study.
Keywords :
fuzzy reasoning; load forecasting; particle swarm optimisation; power engineering computing; power grids; wind power plants; ANFIS; EPSO; Portugal; adaptive-network-based fuzzy inference system; electric grid; evolutionary particle swarm optimization; hybrid evolutionary intelligent approach; short-term wind power forecasting; Accuracy; Artificial neural networks; Forecasting; Power systems; Predictive models; Wind forecasting; Wind power generation; Forecasting; evolutionary programming; neurofuzzy; particle swarm optimization; wind power;
Conference_Titel :
Intelligent System Application to Power Systems (ISAP), 2011 16th International Conference on
Conference_Location :
Hersonissos
Print_ISBN :
978-1-4577-0807-7
Electronic_ISBN :
978-1-4577-0808-4
DOI :
10.1109/ISAP.2011.6082234