Hour-ahead wind power prediction for power systems using Hidden Markov Models and Viterbi Algorithm
作者： S Jafarzadeh , S Fadali , C Y Evrenosoglu , H Livani
关键词: Simulation 、 Power (physics) 、 Markov process 、 Hidden Markov model 、 Viterbi algorithm 、 Electric power system 、 Algorithm 、 Statistical analysis 、 Wind power 、 Wind speed 、 Engineering
摘要: This paper presents a new stochastic method for very short-term (1 hour) wind prediction in electrical power systems. The utilizes Hidden Markov Models (HMM) and the Viterbi Algorithm (VA). Past farm production data are required to develop HMM model. accuracy of predictions improves drastically if hourly weather forecast used as pseudo-measurements. Computer simulations using Northwestern recordings from Bonneville Power Administration (BPA) website show good correlation between our actual data.
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