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Optimal Energy Scheduling of Renewable-based Smart Homes in thePresence of Electric Vehicles and Demand Response Programs

عنوان مقاله: Optimal Energy Scheduling of Renewable-based Smart Homes in thePresence of Electric Vehicles and Demand Response Programs
شناسه ملی مقاله: EESCONF09_011
منتشر شده در نهمین کنفرانس بین المللی مهندسی برق ،الکترونیک و شبکه های هوشمند در سال 1401
مشخصات نویسندگان مقاله:

Zohreh Salmani - Department of Electrical Engineering, Shahid Beheshti University, Iran
Abolfazl pirayesh - Department of Electrical Engineering, Shahid Beheshti University, Iran

خلاصه مقاله:
With the expansion of distributed generation units, the technological advancement of energy storage systems (ESS), and a rise in the use of electric vehicles (EV) in smart homes, more study is required to understand how to manage the energy from these types of sources. The goal of the smart house operator is to run the structure as efficiently as possible. The usage of household appliances will be properly regulated by this system, which will also control the electricity produced by renewable sources and regulate the charging and discharging of ESS and EVs. In order to reduce the overall running expenses of the house, this research proposes a unique idea for scheduling EVs and ESS in tandem while taking demand response programms (DRP) into consideration. According to prosumer preferences, the impact of DRP collaboration and the best scheduling of EVs and energy storages on operational costs, power transactions with the main grid, and hourly distributed generation management has been investigated. The numerical findings show that the suggested approach may cut operational and billing costs by ۳۷.۴۲% while also lowering risk levels in the provision of critical loads by up to ۹.۸۵%. Additionally, EVs and different energy storage technologies used to their full potential lower operating costs by ۱۲.۸۳%.

کلمات کلیدی:
Smart home, electric vehicles, demand response, energy storage

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1603131/