Wind Power Forecasting to Minimize the Effects of Overproduction
Wind power generation increases very rapidly in the past few years. The available wind energy is random due to the intermittency and variability of the wind speed. This poses difficulty in the energy dispatched and cause costs, as the wind energy is not accurately scheduled in advance. This paper presents a short-term wind speed forecasting that uses a Kalman filter approach to predict the power production of wind farms. The prediction uses wind speed values measured over a year in a site, on the case study of Portugal. A method to group wind speeds by their similarity in clusters is developed together with a Kalman filter model that uses each cluster as an input to perform the wind power forecasting.
KeywordsClustering Kalman Filter Wind Power Forecasting
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- 1.Silva, B.: China e Índia fazem consumo mundial de energia disparar 40%. Diário Económico, 22–23 (2010)Google Scholar
- 2.Lange, M., Waldl, H.-P.: Assessing the uncetiainty of wind power predictions with regard to specific weather situations. In: Proc. of the 2001 European Wind Energy Association Conference, EWEC’UI, Copenhagen (Denmark), July 2-6, pp. 695–698 (2001)Google Scholar
- 4.Fonte, P.M., Quadrado, J.C.: ANN approach to WECS power forecast. In: 10th IEEE Conference on Emerging Technologies and Factory Automation, September 19-22, vol. 1, pp. 1069–1072 (2005)Google Scholar
- 6.Giebel, G., Brownsword, R., Kariniotakis, G., Denhard, M., Draxl, C.: The State-Of-The-Art in Short-Term Prediction of Wind Power: A Literature Overview, 2nd edn. ANEMOS.plus (2011)Google Scholar
- 7.REN - Rede Eléctrica Nacional, S.A. Caracterização da Rede Nacional de Transporte para efeitos de acesso à rede em 31 de Dezembro de 2010 (2011) Google Scholar
- 8.REN - Rede Eléctrica Nacional, S.A. A Energia Eólica em Portugal 2010 (2011) Google Scholar
- 9.OMEL Mercados A. V. Preços da tarifa de electricidade entre Espanha e Portugal, http://www.omel.es/files/flash/ResultadosMercado.swf (accessed in May 2, 2011)
- 10.Xu, R., Wunsch II, D.: Survey of clustering algorithms. IEEE Transactions on Neural Networks, 645–678 (2005)Google Scholar