Multi-time scale optimal scheduling of integrated electricity and district heating systems considering thermal comfort of users: An enhanced-interval optimization method

Due to the high integration of renewable energy, renewable energy curtailment has become a key issue that needs to be solved urgently. Aiming at the areas with the characteristics of curtailed wind energy and strong thermal demand, a multi-time scale optimal scheduling model for improving the wind power integration in heating seasons was proposed. In the framework, the enhanced-interval optimization method (EIOM) was applied, by considering the uncertainties of wind power and loads in an integrated electricity and district heating system. Considering the dynamic characteristics of the heating network and the thermal inertia of building, the factors affecting users comfort are analyzed. Then the comfort model parameters based on different user types are designed. The EIOM was reformulated by decomposing into two sub-models. A test system including a 30-node electric network and two 15-node heating networks was used to apply the proposed model. The simulation proves that the EIOM can solve the impact of load uncertainty and obtain the optimal operation cost.