Neural network – genetic algorithm optimization of a hybrid renewable energy system (HRES) for a primary school in a rural area

  • سال انتشار: 1401
  • محل انتشار: سی امین همایش سالانه بین المللی انجمن مهندسان مکانیک ایران
  • کد COI اختصاصی: ISME30_223
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 307
دانلود فایل این مقاله

نویسندگان

Masoomeh Shahafve

M.Sc. Student, School of Mechanical Engineering, College of Engineering, University of Tehran;

Ali Izadi

M.Sc. Student, School of Mechanical Engineering, College of Engineering, University of Tehran;

Behrang Sajadi

Associate Professor, School of Mechanical Engineering, College of Engineering, University of Tehran;

Pouria Ahmadi

Assistant Professor, School of Mechanical Engineering, College of Engineering, University of Tehran;

چکیده

The main attention of the present paper is producing the energy demand of a primary school located in a remote area of the eastern province of Iran, Zabol. As remote districts have less access to the grid electricity, the energy demand of the primary school has been generated through renewable resources. Therefore, a hybrid renewable energy system (HRES) comprising of PV panels, wind turbines, as the generator of energy, hydrogen energy storage system, as energy storage, and batteries, as backup energy storage, is proposed. Afterward, an artificial neural network (ANN) has been trained based on simulated HRES to predict required grid energy and loss of power supply probability (LPSP). Then, trained ANN has been optimized with the genetic algorithm to find the lowest Life cycle cost (LCC), highest LPSP, and lowest grid power. The results indicated that system configuration which is comprised of ۸۴۸ PV panels, ۶۸ wind turbines, ۳۰ batteries, a ۱۵۲.۲۱۵ kWh electrolyzer can have the most optimum LCC, LPSP and grid power. The mentioned system has LPSP of ۷۷.۲۹ %.

کلیدواژه ها

Hybrid Renewable Energy System, Neural Network, Genetic Algorithm, Hydrogen Energy Storage, Battery

مقالات مرتبط جدید

اطلاعات بیشتر در مورد COI

COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.

کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.