In order to reduce carbon emissions and improve the absorption capacity of new energy, this paper considers three kinds of demand-side response loads that can be reduced, transferred and replaced. Then, including a carbon trading mechanism, a day-ahead optimization scheduling model of wind-opto-electric-gas-storage integrated energy distribution network system is established with the comprehensive optimization objectives of the least carbon emission, the lowest comprehensive operation cost, the least amount of wind and light abandoning and the lowest network loss. To minimize the fluctuation of wind power and photovoltaic power generation prediction error, model predictive control theory is used to feed back and correct the prediction error of wind and photovoltaic power generation, and an intra-day rolling optimization scheduling model of an integrated energy distribution network system is established. Simulation experiments on the modified 33-node and 20-node distribution networks have verified that the proposed model could effectively reduce carbon emissions, improve the absorption capacity of wind power and photovoltaic, smooth the load curve, and reduce the comprehensive operating cost of the system.

The work is supported by the Key Research and Development Program of Science and Technology Department of Sichuan Province (No. 2017GZ0054).