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Optimal operation of a smart railway station based on a multi-energy hub structure considering environmental perspective and regenerative braking utilization
Energy Science & Engineering ( IF 3.8 ) Pub Date : 2021-06-30 , DOI: 10.1002/ese3.937
Saeed Akbari 1 , Seyed Saeed Fazel 1 , Shahram Jadid 2
Affiliation  

This paper presents a stochastic bi-objective model to reduce the operation cost and the carbon emission of a smart railway station along with dependent commercial buildings, according to a multi-energy hub system's structure. The proposed energy hub system (EHS) includes a power, heating, and cooling subenergy hub. The recovered energy obtained from the regenerative braking (RB) during train deceleration is utilized to supply the load of EHS. To calculate the recovered energy, the motion of trains is simulated in MATLAB software. Furthermore, a demand response program (DRP) is integrated into the model to improve the flexibility of the EHS. Also, the uncertainty related to the photovoltaic generation and the power obtained from RB is considered. GAMS software is used to solve the bi-objective model with the ɛ-constraint approach. Then, to select the best possible solution, a fuzzy technique is engaged. Seven case studies are considered investigating the effect of exerting the DRP, utilizing the recovered energy, and employing the energy storage on operation cost and carbon emission. The simulation results demonstrate a significant improvement in operating cost and the carbon emission for the proposed EHS.

中文翻译:

考虑环境视角和再生制动利用的基于多能源枢纽结构的智能火车站优化运行

根据多能源枢纽系统的结构,本文提出了一个随机双目标模型,以降低智能火车站及其附属商业建筑的运营成本和碳排放。拟议的能源中心系统 (EHS) 包括一个电力、加热和冷却子能源中心。在列车减速期间从再生制动 (RB) 获得的回收能量用于供应 EHS 的负载。为了计算回收的能量,在 MATLAB 软件中模拟了火车的运动。此外,将需求响应程序 (DRP) 集成到模型中以提高 EHS 的灵活性。此外,还考虑了与光伏发电和从 RB 获得的功率相关的不确定性。GAMS 软件用于通过 ɛ 约束方法求解双目标模型。然后,为了选择最佳解决方案,采用了模糊技术。考虑了七个案例研究来调查应用 DRP、利用回收的能源和使用储能对运营成本和碳排放的影响。模拟结果表明,拟议 EHS 的运营成本和碳排放量显着改善。
更新日期:2021-09-02
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