کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6775086 | 1432007 | 2018 | 21 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Modeling the electrical energy consumption profile for residential buildings in Iran
ترجمه فارسی عنوان
مدل سازی پروفایل مصرف برق برای ساختمان های مسکونی در ایران
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
مدل سازی بار، مصرف انرژی مسکونی، روش پایین آمدن، ضریب همبستگی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی
The development of smart grid, especially using the demand side management (DSM) programs in order to control the consumption pattern and optimize the energy consumption is severely growing. The consumers' behavior intensively influences the resources and demand control in the power grid. Hence, proper understanding and modeling the behavioral pattern of the demand side is a fundamental step for smart grid development and achieving sustainable energy systems. On the other hand, the energy consumption information is necessary for planning and management of distribution networks and the resources allocation. Thus, achieving a model to predict the energy consumption in the level of subscribers is a basic step and it can be used for different studies. In this paper, in order to study the random behavior of the residential subscribers, a bottom-up method is developed with a one-minute resolution and with considering the number of residents and the way of using different equipment in order to obtain the consumption profile for the residential subscribers. The results represent the effectiveness of the proposed model and compatibleness of the obtained consumption profile with the real measured values.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Sustainable Cities and Society - Volume 41, August 2018, Pages 481-489
Journal: Sustainable Cities and Society - Volume 41, August 2018, Pages 481-489
نویسندگان
Mohammad Sepehr, Reza Eghtedaei, Ali Toolabimoghadam, Younes Noorollahi, Mohammad Mohammadi,