Distributionally robust optimization for integrated energy distribution network considering vine Copula uncertainty of wind power, photovoltaic and demand side response
In order to adapt to the uncertainty of new energy, increase new energy consumption and reduce carbon emissions, an optimal scheduling model of integrated energy distribution network system is proposed based on vine Copula considering three uncertainties of wind power, photovoltaic and demand side response. The joint probability distribution of wind power, photovoltaic and demand response is established by using the vine structure of Copula function. The joint probability distribution is used as the reference probability distribution of the distributionally robust ambiguous set. A distributionally robust ambiguous set based on kullback-leibler (KL) divergence is established to deal with uncertainties. Taking the minimum scheduling cost of integrated energy distribution network system as the optimization objective, a distributionally robust optimization scheduling model is established and the solver is used. The simulation experiment on the modified integrated energy distribution network system model shows that the proposed distributionally robust optimization model can effectively improve new energy consumption capacity and reduce carbon emissions.