Abstract

AbstractThis 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.

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