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Simplified Markov Chain Models for Generation of Synthetic Time Series of Wind Speed and Direction

https://doi.org/10.1109/pmaps53380.2022.9810593
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.apenergy.2011.04.051openalex-snapshot
Influence of local wind speed and direction on wind power dynamics – Application to offshore very short-term forecasting
inferredcites →https://doi.org/10.1016/j.energy.2004.05.026openalex-snapshot
First and second order Markov chain models for synthetic generation of wind speed time series
inferredcites →https://doi.org/10.1016/j.epsr.2014.12.025openalex-snapshot
Markov chain modeling for very-short-term wind power forecasting
inferredcites →https://doi.org/10.1016/j.jweia.2015.11.011openalex-snapshot
Simulation of non-stationary wind speed and direction time series
inferredcites →https://doi.org/10.1016/s0167-6105(00)00081-7openalex-snapshot
First-order Markov chain approach to wind speed modelling
inferredcites →https://doi.org/10.1049/iet-rpg.2020.0113openalex-snapshot
Evaluation of wind turbine power outputs with and without uncertainties in input wind speed and wind direction data
inferredcites →https://doi.org/10.1109/iccep.2019.8890086openalex-snapshot
On the Importance of Correlating Wind Speed and Wind Direction for Evaluating Uncertainty in Wind Turbine Power Output
inferredcites →https://doi.org/10.1109/pmaps47429.2020.9183446openalex-snapshot
First Order Non-homogeneous Markov Chain Model for Generation of Wind Speed and Direction Synthetic Time Series
inferredcites →https://doi.org/10.1109/tste.2017.2675445openalex-snapshot
Non-Homogeneous Markov Wind Speed Time Series Model Considering Daily and Seasonal Variation Characteristics
inferredcites →https://doi.org/10.3390/en12050826openalex-snapshot
Including Wind Power Generation in Brazil’s Long-Term Optimization Model for Energy Planning

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4509452openalex-extracted
inferred← citeshttps://doi.org/10.1016/j.rser.2024.114420openalex-snapshot
Investigation of the effects of synthetic wind speed parameters and wind speed distribution on system size and cost in hybrid renewable energy system design
inferred← citeshttps://doi.org/10.1109/iccep65222.2025.11143749openalex-snapshot
Long-term scenario generation of heterogeneous random variables based on Markov chains for smart road tunnels planning
inferred← citeshttps://doi.org/10.1109/pmaps61648.2024.10667103openalex-snapshot
New High Efficiency Models for Generation of Synthetic Time Series of Wind Speed and Direction
inferred← citeshttps://doi.org/10.1186/s40537-024-00924-7openalex-snapshot
Evaluation is key: a survey on evaluation measures for synthetic time series
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