Journal of Energy Markets

Risk.net

Statistical analysis of photovoltaic and wind power generation

Noor ’Adilah Ibrahim

  • Deterministic behavior of PV and wind can be explained by sun intensity and trigonometric function, respectively.
  • Autoregressive process of order two is suffcient to explain short term fluctuation of all production.
  • Residuals of PV and wind are weakly anticorrelated.
  • No copula pattern detected in transformed residuals of PV and wind, but there is seasonality in dependency.

In this paper, we do a comparison between maximal and daily average production of photovoltaic (PV) and wind energy based on a transmission system operator in Germany using statistical analysis with different seasonality functions. We adopt sun intensity as a seasonal function for PV and a trigonometric function for wind, while the deseasonalized data is modeled by an autoregressive process. The stochastic component of both energies is relatively well captured by a skew normal distribution. Further, a weak anticorrelation between residuals of PV and wind is found, which leads to the complexity of balancing supply of renewable energy. No clear copula pattern is detected between transformed residuals, but it exhibits seasonality in the dependence. We can exploit this feature as a risk management strategy, such as quanto options, for nonrenewable energy producers to hedge against high renewable energy generation.

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