A PV Power Time Series Generating Method Considering Correlation Characteristics Based on Multi Markov Chain Monte Carlo Method
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National Key R&D Program of China,China Scholarship Council Program

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    Abstract:

    The existing power system planning and operation mainly considers the uncertainty of the single renewable energy output,and there are few studies considering the correlation between renewable energy outputs.In this paper,a multi Markov Chain Monte Carlo method is proposed to predict the PV power time series.This method establishes several Markov chains that obey the complete conditional distribution to each other to simulate the random variation of the atmosphere over the PV plants.These Markov chains can fully retain the correlation between the PV plants.This paper simulates the time series of three sets of PV plants with different correlation levels using multi MCMC method.It is proved that this method can inherit the general statistical characteristics of historical sequences more accurately than the original MCMC method and can more effectively reflect the characteristics of the interaction between PV power plants.The multi MCMC method is more suitable for future power electrical system planning and operation design.

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History
  • Received:July 09,2018
  • Revised:August 14,2018
  • Adopted:August 02,2018
  • Online: November 28,2018
  • Published: November 28,2018