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Article summary:
1. A two-stage scheduling method for integrated community energy systems (ICES) is proposed based on a hybrid mechanism and data-driven model.
2. The hybrid-driven dynamic energy hub (DEH) model is used to accurately extract nonlinear characteristics of equipment efficiency.
3. A rolling optimization (RO) strategy is adopted to address the uncertainties of equipment efficiency and load demand.
Article analysis:
The article provides a detailed overview of a two-stage scheduling method for integrated community energy systems (ICES). The proposed method combines a hybrid mechanism and data-driven model to accurately extract nonlinear characteristics of equipment efficiency, as well as a rolling optimization (RO) strategy to address the uncertainties of equipment efficiency and load demand. The article appears to be reliable in its presentation of the proposed method, providing sufficient detail on the various components involved in the scheduling process. However, there are some potential biases that should be noted. For example, the article does not explore any counterarguments or alternative methods that could be used for ICES scheduling, nor does it provide any evidence for the claims made about the effectiveness of the proposed method. Additionally, there is no discussion of possible risks associated with using this method or how it might affect other aspects of ICES operations. Finally, while the article does present both sides equally in terms of describing the proposed method and its components, it does not provide an equal amount of detail on each side which could lead to partiality in its conclusions.