Wind farms usually cluster in areas with abundant wind resources.Therefore,spatial dependence of wind speeds among nearby wind farms should be taken into account when modeling a power system with large-scale wind powe...Wind farms usually cluster in areas with abundant wind resources.Therefore,spatial dependence of wind speeds among nearby wind farms should be taken into account when modeling a power system with large-scale wind power penetration.This paper proposes a novel non-parametric copula method,multivariate Gaussian kernel copula(MGKC),to describe the dependence structure of wind speeds among multiple wind farms.Wind speed scenarios considering the dependence among different wind farms are sampled from the MGKC by the quasi-Monte Carlo(QMC)method,so as to solve the stochastic economic dispatch(SED)problem,for which an improved meanvariance(MV)model is established,which targets at minimizing the expectation and risk of fuel cost simultaneously.In this model,confidence interval is applied in the wind speed to obtain more practical dispatch solutions by excluding extreme scenarios,for which the quantile-copula is proposed to construct the confidence interval constraint.Simulation studies are carried out on a modified IEEE 30-bus power system with wind farms integrated in two areas,and the results prove the superiority of the MGKC in formulating the dependence among different wind farms and the superiority of the improved MV model based on quantilecopula in determining a better dispatch solution.展开更多
Copula method has been widely applied to model the correlation among underlying assets in financial market. In this paper, we propose to use the multivariate Frechet copula family presented in J. P. Yang et al. [Insur...Copula method has been widely applied to model the correlation among underlying assets in financial market. In this paper, we propose to use the multivariate Frechet copula family presented in J. P. Yang et al. [Insurance Math. Econom., 2009, 45：139 147] to price multivariate financial instruments whose payoffs depend on the k^th realization of the underlying assets and collateralized debt obligation （CDO）. The advantage of the multivariate Frechet copula is discussed. Empirical study shows that such copula family gives a better fitting to CDO＇s market price than Gaussian copula for some derivatives.展开更多
基金This research is supported by the Key-Area Research and Development Program of Guangdong Province(No.2020B010166004)the Fundamental Research Funds for the Central Universities,SCUT(No.2018ZD06).
文摘Wind farms usually cluster in areas with abundant wind resources.Therefore,spatial dependence of wind speeds among nearby wind farms should be taken into account when modeling a power system with large-scale wind power penetration.This paper proposes a novel non-parametric copula method,multivariate Gaussian kernel copula(MGKC),to describe the dependence structure of wind speeds among multiple wind farms.Wind speed scenarios considering the dependence among different wind farms are sampled from the MGKC by the quasi-Monte Carlo(QMC)method,so as to solve the stochastic economic dispatch(SED)problem,for which an improved meanvariance(MV)model is established,which targets at minimizing the expectation and risk of fuel cost simultaneously.In this model,confidence interval is applied in the wind speed to obtain more practical dispatch solutions by excluding extreme scenarios,for which the quantile-copula is proposed to construct the confidence interval constraint.Simulation studies are carried out on a modified IEEE 30-bus power system with wind farms integrated in two areas,and the results prove the superiority of the MGKC in formulating the dependence among different wind farms and the superiority of the improved MV model based on quantilecopula in determining a better dispatch solution.
文摘Copula method has been widely applied to model the correlation among underlying assets in financial market. In this paper, we propose to use the multivariate Frechet copula family presented in J. P. Yang et al. [Insurance Math. Econom., 2009, 45：139 147] to price multivariate financial instruments whose payoffs depend on the k^th realization of the underlying assets and collateralized debt obligation （CDO）. The advantage of the multivariate Frechet copula is discussed. Empirical study shows that such copula family gives a better fitting to CDO＇s market price than Gaussian copula for some derivatives.
