In this paper, a robust optimization framework is proposed for solving the energy hub operation problem in the presence of renewable energy resources (RERs) and three electrical, cooling and thermal storage systems. The study hub is a real case study in a hospital building in Hamedan, Iran. All the input parameters are obtained from real data by connecting a dw-6095 Lutron power analyzer to the hub equipment. Furthermore, the study problem is modeled as a mixed-integer non-linear programming (MINLP) problem and is solved in the form of 8 different case studies using the DICOPT solver in GAMS software. Our analysis of the simulation results reveals that considering the uncertainties led to a 6.41% increase in the total operation costs. The results also indicate that storage systems increased flexibility and reduced the operation costs by 0.87%. Moreover, the problem was solved with three different time resolutions, and the results mirrored an increase in the accuracy and solution time due to the increase in the resolution. Finally, the hub performance is assessed under three contingency events, and the results show that the exclusion of the boiler leads to about 5563.3 kWh of energy not served (ENS).

在本文中，提出了一种鲁棒的优化框架，用于解决存在可再生能源 (RER) 和三个电力、冷却和热存储系统的能源枢纽运行问题。该研究中心是伊朗哈马丹一所医院大楼的真实案例研究。所有输入参数均通过将 dw-6095 Lutron 功率分析仪连接到集线器设备从真实数据中获得。此外，研究问题被建模为混合整数非线性规划 (MINLP) 问题，并使用 GAMS 软件中的 DICOPT 求解器以 8 个不同案例研究的形式解决。我们对仿真结果的分析表明，考虑到不确定性导致总运营成本增加了 6.41%。结果还表明，存储系统提高了灵活性，并将运营成本降低了 0.87%。此外，该问题是用三种不同的时间分辨率解决的，结果反映了由于分辨率的增加而导致的精度和求解时间的增加。最后，在三个意外事件下评估集线器性能，结果表明，排除锅炉导致约 5563.3 kWh 的能源未提供 (ENS)。