Modelling of wind and photovoltaic power output considering dynamic spatio-temporal correlation

Zhongliang Wang, Hongyu Zhu, Dongdong Zhang, Hui Hwang Goh, Yunxuan Dong and Thomas Wu

Applied Energy, 2023, vol. 352, issue C, No S0306261923013120

Abstract: The simulation technology of wind and solar power output can provide data support for the planning of new energy stations and the optimization and scheduling of power systems. In order to solve the problem that the existing output models can not accurately describe the dynamic spatio-temporal dependence between wind and solar output, a dynamic spatiotemporal correlation model of wind and solar output based on Markov stochastic process and Copula function theory is proposed. Firstly, wind power and photovoltaic output are regarded as a stochastic process, and the time autocorrelation models of wind power and photovoltaic output are constructed based on a one-dimensional Markov chain and hybrid Copula function. Next, two one-dimensional Markov chains were coupled to form a two-dimensional Markov chain, and a spatial correlation model between wind and solar output was constructed using the dynamic SJC Copula function. Take the measured data of adjacent wind farms and photovoltaic power stations in Hami, Xinjiang as an example for simulation. The simulation results show that the proposed model can effectively reflect the spatio-temporal correlation of the original data and reflect the dynamic changes in the correlation between wind and solar energy.

Keywords: Spatio-temporal correlation; Dynamic correlation; Copula theory; Markov chain; Dynamic Copula function (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1016/j.apenergy.2023.121948

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