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The recent development of the Energy Internet has urged the conventional inefficient utilization of single energy to change towards the more developed energy usage of optimal dispatch of the integrated energy system. In this context, the joint optimization scheduling framework of integrated energy system is established based on the energy hub. Then a typical integrated energy system model is developed considering carbon emission and energy supply costs with valve point effect. To solve this non-linear problem with non-convex, discontinuously differentiable characteristic, the cascaded algorithm combined with the knowledge transfer based Q-learning algorithm and interior point method is applied on the model. Meanwhile, the efficiency is greatly improved by knowledge transfer. Case studies have been carried out on a 33energy hubs test system to verify the effectiveness of the proposed model and algorithm.

A Cascaded Algorithm Incorporating Knowledge Transfer Q-learning and Interior Point Method for Coordinated Operation of Integrated Energy System