Real-Coded Quantum Optimization-Based Bi-Level Dispatching Strategy of Integrated Power and Heat systems

To reduce the curtailment of renewable energy and improve energy efficiency, the integration of multi-energy systems, which is proven to be effective in reducing energy loss, has been extensively studied all over the world in recent years. Among all the coupled systems, the integrated electricity and heat system is comparatively mature and has been large-scale applied. However, the widely use of combined heat and power (CHP) units limits the flexibility of integrated systems due to the coupling of power and heat. This paper proposes a bi-level programming model to take full advantage of the flexibility of the heating system. The heat pumps (HP) are utilized to decouple the strong coupling constraints introduced by CHP units. The upper-level problem is the optimal power flow of power system which is composed of coal-fired units, wind turbines, and electric loads. The bottom level decision-maker is the district heating network (DHN) which contains CHP units, HP and heat loads. The upper and lower level problem are linked by price signals sent by the power system operator (PSO). A quantum optimization-based solution method combined with single-level reduction is proposed for solving the bi-level model. The simulation results show that the proposed model can reduce the curtailment of wind power and increase the profit of power system significantly according to the price signal.