Bi-Level Optimization Framework for Buildings to Heating Grid Integration in Integrated Community Energy Systems

This paper proposes a bi-level optimization framework for buildings to heating grid (B2HG) integration in integrated heating/electricity community energy systems. The proposed B2HG framework enables buildings to carry out heating demand response to the integrated community energy systems (ICES). In upper level, ICES operator with energy conversion equipment devotes to maximizing its profits by optimizing the energy generation/supply schedules and the sale heating price. In lower level, a detailed physical model of the building with adjustable indoor radiators is developed while considering the building thermal dynamics. Consumers minimize their heating costs by adjusting the flow rates of their radiators according to the heating price provided by the upper level. Then, the proposed bi-level optimization problem is converted into a mixed-integer linear programming using Karush-Kuhn-Tucker conditions and strong duality theorem. The piecewise linearization is used to eliminate the nonlinearity of heating network constraints. Numerical results show that consumers can provide heating demand response to ICES operator by considering the thermal dynamics. With the multiple energy conversion equipment, the ICES operator can unlock the flexibility from the supply side. Moreover, the proposed bi-level optimization method can combine the flexibility from both the supply and demand side, and benefits both the ICES operator and building consumers.