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Because of a large demand for building operation and its flexibility, building energy systems have considerable energy-saving potential, which provides a technical path toward the national strategic goal of “peak carbon dioxide emissions and carbon neutrality.” However, building energy management may face challenges such as the complicated interaction between the occupants' requirements and system demand, multiscale spatiotemporal coupling and energy balance among multiple energy media, and high computational complexity caused by the curse of dimensionality. Therefore, to overcome these challenges, in this paper, we develop a cyber-physical energy system model by proposing a node and traffic model to formulate the building energy management problem with supply–demand coordination, which captures the interaction between the information network and the physical network of electricity, heating, and cooling, and supports the edge-cloud computing framework by integrating the local data collection and computation. Furthermore, we develop an edge-cloud framework-based distributed algorithm to solve the problem and show the optimality of the developed algorithm. The performance of the method proposed in this paper is demonstrated using six case studies with different problem scales. The results show that the proposed method has good performance in accuracy and computational efficiency, which is particularly suitable for solving large-scale problems.
徐 et al. (Mon,) studied this question.