This paper proposes a two-stage robust optimal scheduling method for the integrated community energy system (ICES) with flexible heating loads of buildings. At the first stage, consumers in buildings optimize their heating loads to minimize their heating costs. The thermal dynamics of buildings with controllable indoor radiators are modeled using the Resistor-Capacitor thermal network. At the second stage, the ICES operator seeks to maximize its profit by optimizing the schedules of energy generation and supply. Moreover, a robust optimization is used at the second stage to cope with the energy prices uncertainties from the energy markets. Numerical studies show that the proposed optimal scheduling method can reduce the heating costs of consumers in buildings while ensuring the ICES’s profit under energy prices uncertainties.
Keywords Buildings, integrated community energy system, prices uncertainties, resistor-capacitor thermal network, robust optimization