Optimal sizing of electricity supply components in an Iranian smart home considering load and power generation prediction by machine learning
محل انتشار: پنجمین کنفرانس ملی مهندسی برق و مکاترونیک ایران
سال انتشار: 1398
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 482
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شناسه ملی سند علمی:
ICELE05_310
تاریخ نمایه سازی: 26 بهمن 1398
چکیده مقاله:
Today, managing power systems alongside the renewable energy resources in order to minimize the cost and maximize the efficiency is increasingly noticed. In this way, Buildings which are known as end-users, play very important role in this sort of problems. In addition to smoothing the power system tension at the peak times, they can decrease their bill cost by optimal sizing the power supply components. Also, to obtain valuable results, a precise prediction of power production and consumption can be very effective. In this paper, a new model is discussed to gain optimal sizing of solar cells and batteries in corporation with power grid in an Iranian smart home. To forecast the hourly power consumption and the amount of photovoltaic generation, the benefits of machine learning have been applied. The results show that the proposed model has positive effects on the end-user’ electricity cost and power system tension reduction.
کلیدواژه ها:
نویسندگان
Hamzeh Asgharnezhad
Tabriz University
Mehdi Talebi
Bu-Ali Sina University