Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.9/1941
Título: On the use of Markov chain models for the analysis of wind power time-series
Autor: Lopes, Vitor V.
Scholz, Teresa
Estanqueiro, Ana
Novais, Augusto Q.
Palavras-chave: Discrete Markov chain models
Wind power
Variability
Persistence
Data: 2012
Editora: IEEE - Institute of Electrical and Electronics Engineers
Citação: Lopes, Vitor V.; Scholz, Teresa; Estanqueiro, Ana; Novais, Augusto Q. On the use of Markov chain models for the analysis of wind power time-series. In: EEEIC - 11th International Conference on Environment and Electrical Engineering, Venice, Italy, 18-25 May, 2012, p. 770-775
Resumo: Wind energy is becoming a top contributor to the renewable energy mix, which raises potential reliability issues for the grid due to the fluctuating and intermittent nature of its source. This paper explores the use of Markov chain models for the analysis of wind power time-series. The proposed Markov chain model is based on a 2yr dataset collected from a wind turbine located in Portugal. The wind speed, direction and power variables are used to define the states and the transition matrix is determined using a maximum likelihood estimator based on multi-step transition data. The Markov chain model is analyzed by comparing the theoretically derived properties with their empirically determined analogues. Results show that the proposed model is capable of describing the observed statistics, such as wind speed and power probability density as well as the persistence statistics. It is demonstrated how the application of the Markov chain model can be used for the short-term prediction of wind power.
URI: http://hdl.handle.net/10400.9/1941
Versão do Editor: http://dx.doi.org/10.1109/EEEIC.2012.6221479
Aparece nas colecções:UMOSE - Comunicações em actas de encontros científicos internacionais

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