A Markov-chain probability distribution mixture approach to the clear-sky index

@article{Munkhammar2018AMP,
  title={A Markov-chain probability distribution mixture approach to the clear-sky index},
  author={Joakim Munkhammar and Joakim Wid{\'e}n},
  journal={Solar Energy},
  year={2018}
}
View via Publisher
18 Citations
Background Citations
1
Methods Citations
5

18 Citations

An N-state Markov-chain mixture distribution model of the clear-sky index
A spatiotemporal Markov-chain mixture distribution model of the clear-sky index
Probabilistic forecasting of the clear-sky index using Markov-chain mixture distribution and copula models
TLDR
Two probabilistic forecasting models for the clear-sky index, based on the Markov-chain mixture distribution (MCM) and copula clear-Sky index generators, are presented and evaluated and show that the copula model generally outperforms the PeEn, while the MCM and QR models are superior in all tested aspects.
Probabilistic forecasting of high-resolution clear-sky index time-series using a Markov-chain mixture distribution model
Solar Radiation Nowcasting Using a Markov Chain Multi-Model Approach
Solar energy has found increasing applications in recent years, and the demand will continue to grow as society redirects to a more renewable development path. However, the required high-frequency…
Assessing Evidence for Weather Regimes Governing Solar Power Generation in Kuwait
With electricity representing around 20% of the global energy demand, and increasing support for renewable sources of electricity, there is also an escalating need to improve solar forecasts to…
Generation Data of Synthetic High Frequency Solar Irradiance for Data-Driven Decision-Making in Electrical Distribution Grids
In this paper, we introduce a model representing the key characteristics of high frequency variations of solar irradiance and photovoltaic (PV) power production based on Clear Sky Index (CSI) data.…
A Nested MCMC Method Incorporated With Atmospheric Process Decomposition for Photovoltaic Power Simulation
TLDR
A nested Markov chain Monte Carlo (MCMC) method incorporated with atmospheric process decomposition (APD) for PV power simulation is proposed and the results validate the proposed method's accuracy over previous ones in reproducing PV power characteristics.
A generative hidden Markov model of the clear-sky index
Clear-sky index (CSI) generative models are of paramount importance in, e.g., studying the integration of solar power in the electricity grid. Several models have recently been proposed with method…
Probabilistic solar forecasting benchmarks on a standardized dataset at Folsom, California
...
...

References

SHOWING 1-10 OF 27 REFERENCES
A three-state model for the probability distribution of instantaneous solar radiation, with applications
On the properties of aggregate clear-sky index distributions and an improved model for spatially correlated instantaneous solar irradiance
An autocorrelation-based copula model for generating realistic clear-sky index time-series
Synthetic generation of high temporal resolution solar radiation data using Markov models
Cloud cover effect of clear-sky index distributions and differences between human and automatic cloud observations
Simple procedure for generating sequences of daily radiation values using a library of Markov transition matrices
A probability density function for the clearness index, with applications
A copula method for simulating correlated instantaneous solar irradiance in spatial networks
The probability density and autocorrelation of short-term global and beam irradiance
Polynomial probability distribution estimation using the method of moments
TLDR
A procedure for estimating Nth degree polynomial approximations to unknown (or known) probability density functions (PDFs) based on N statistical moments from each distribution based on the method of moments is suggested.
...
...