Interval optimal scheduling method of integrated energy system with ground source heat pump based on quantum derivative algorithm

To better consume new energy and make full use of new energy, an interval optimal scheduling method of integrated energy system considering wind power uncertainty is proposed. Interval mathematics is used to characterize the uncertainty of wind power output. Taking the system operation cost and wind curtailment cost as the optimization objectives, the interval optimization of integrated energy system and related optimization models are constructed. The model after uncertainty transformation is solved by allele quantum derivative algorithm to further improve the optimization accuracy. Combined with Copula distribution and K-means clustering, the typical scenario combination of source and load is generated. The simulation results show that the proposed interval optimization scheduling method can effectively reduce the operation cost of integrated energy system and improve the utilization of new energy.