Nowadays, the high penetration of renewable energy sources (RESs) with non-uniformly distributed patterns has created unprecedented challenges for regional power systems to maintain system flexibility and reliability. These technical challenges obligate power system operators to curtail part of the produced renewable energy at various scheduling intervals. Motivated by these challenges, grid-connected energy hubs are seen as a way forward to boost system flexibility, decrease the rate of renewable power curtailment, and increase energy efficiency. However, simplified models may significantly affect the performance of the grid-connected energy hubs in practice. Hence, this paper proposes a holistic structure to determine the optimal coordinated operation of the grid-connected energy hubs and the regional power system by relying on the high penetration of wind power. In this regard, various fundamental challenges that have not yet been addressed in an integrated manner, including the $C{O}_2$ emission rate and the amount of curtailed renewable energy along with total operating costs of the integrated energy system, are among the main objectives of the optimization problem. The proposed structure is developed in the form of tractable mixed-integer nonlinear programming (MINLP) problem to handle the day-ahead security-constrained unit commitment (SCUC). The information-gap decision theory (IGDT)-based robust model is used for accurate modeling of wind power uncertainty. The characteristics of the proposed IGDT-based robust SCUC model and its benefits are investigated through several technical case studies conducted on the modified 6-bus and 24-bus test systems. The simulation results validate the effectiveness and feasibility of the proposed structure. According to the obtained results for the 6-bus test system, networked energy hubs can help the system operator to reduce the total operating cost, wind power curtailment cost, and $C{O}_2$ emission cost by 16.62%, 100%, and 30.44%, respectively, through utilizing up-to-date energy conversion facilities and energy storage systems as well as managing energy demands. It can be seen that the proposed strategy is a very effective step towards achieving a 100% renewable energy system.

如今，具有不均匀分布模式的可再生能源（RES）的高普及率给区域电力系统保持系统灵活性和可靠性带来了前所未有的挑战。这些技术挑战迫使电力系统运营商必须在各种调度间隔内削减部分生产的可再生能源。受这些挑战的推动，并网能源枢纽被视为提高系统灵活性，降低可再生能源削减率和提高能源效率的一种方式。但是，简化的模型在实践中可能会严重影响并网的能源枢纽的性能。因此，本文提出了一种整体结构，以依靠风力的高渗透性来确定并网的能源枢纽和区域电力系统的最佳协调运行。在这方面，尚未以综合方式解决的各种基本挑战，包括$C{Ø}_2$排放率和减少的可再生能源数量以及综合能源系统的总运营成本，是优化问题的主要目标。提出的结构以可处理的混合整数非线性规划（MINLP）问题的形式开发，以处理日趋安全的约束单位承诺（SCUC）。基于信息鸿沟决策理论（IGDT）的鲁棒模型用于对风电不确定性进行精确建模。通过对改进的6总线和24总线测试系统进行的几个技术案例研究，研究了基于IGDT的鲁棒SCUC模型的特点及其优势。仿真结果验证了所提结构的有效性和可行性。根据6总线测试系统获得的结果，$C{Ø}_2$通过利用最新的能源转换设施和储能系统以及管理能源需求，分别减少了16.62％，100％和30.44％的排放成本。可以看出，所提出的策略是实现100％可再生能源系统的非常有效的步骤。