Optimal Scheduling of Multi Vector Energy Networks Considering Resiliency Improvement

سال انتشار: 1403
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 212

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شناسه ملی سند علمی:

JR_IJE-37-10_011

تاریخ نمایه سازی: 23 تیر 1403

چکیده مقاله:

Present study investigates the effects of managing a mobile energy storage system's (MESS) charging and discharging within a multi vector energy network (MVEN) to improve resilience, self-adequacy, load restoration capabilities, and cost-efficiency. It integrates renewable sources like photovoltaics and wind, with energy demands met via the grid, combined heat and power (CHP) systems, and renewables. The electrical and gas networks primarily meet electrical and heating demands, with gas fueling CHP and boiler units. The model also features gas and heat storage to balance demands and uses probability distributions function to account for uncertainties paramaters such as renewable outputs and loads. It tests the system's robustness against power disruptions from natural disasters, examining four case studies and three electric vehicle (EV) charging main scenarios, including a demand response program (DRP). The simulation results validate the effectiveness of the proposed approach in lowering energy costs and improving system resilience. The strategy of coordinated charging and discharging of EVs, combined with the use of DRP, results in significant cost savings and a more stable energy supply. Furthermore, the model's ability to scale and adapt to larger networks is highlighted, showcasing its potential for application in more complex energy systems.

کلیدواژه ها:

Electrical vehicle ، Multi Vector Energy Network ، demand response ، resiliency

نویسندگان

B. Beram

Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran

A. Sheikholeslami

Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran

M. Marzband

Faculty of Electrical Engineering, Islamic Azad University,Branch of Lahijan, Iran

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