Approach for modelling stochastically dependent renewable energy-based generators using diagonal band copula

Abstract

This study presents a novel algorithm for modelling stochastically dependent renewable energy-based generators. To examine and model the stochastic dependence between renewable energy power outputs and system demand, all different random variables corresponding to wind speeds, solar irradiance and system demand are transformed to a common domain 'the rank/uniform domain' by applying the cumulative distribution function transformation. The rank correlation is first used to examine stochastic dependence and then, diagonal band copula is employed for considering the multivariate stochastic dependence. Finally, Monte Carlo method is utilised to accurately obtain the most likelihood values of the wind power, photovoltaic power and system demand. The rationale behind the proposed model is to include the probabilistic model into deterministic planning problems. The proposed algorithm is implemented in MATLAB environment and the results and comparisons show the accuracy of the proposed modelling algorithm.