Stochastic modeling for daily clearness index sequence in Can Tho city

Tran Van Ly *

* Corresponding author (tvly@ctu.edu.vn)

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Received: 08 Aug 2015
Revised: 30 Sep 2015
Accepted: 19 Feb 2016
Published: 28 Feb 2016
DOI: 10.22144/ctu.jen.2016.005
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How to Cite
Tran, V. L. (2016). Stochastic modeling for daily clearness index sequence in Can Tho city. CTU Journal of Innovation and Sustainable Development , (02), 90-99. https://doi.org/10.22144/ctu.jen.2016.005
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No. 02 (2016)

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Abstract

A stochastic model for daily clearness index sequence in Can Tho city has been proposed. This model based on a pair of stochastic processes, called the state process and the observation process. The random dynamic of meteorological regimes in random medium will be modellized by the state process, a hidden homogeneous Markov chain. The observation process, which represent the daily clearness index sequences, will be formed by a real valued function whose values are corrupted by Gaussian noise. Model parameters are estimated from the real data using Maximum Likelihood estimation via Expectation Maximization algorithm. The simulated data will be used to estimate the experimental distribution of daily clearness index sequences.
Keywords: hidden Markov model, maximum likelihood estimation, expectation maximization algorithm, filter, clear index, solar radiation

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