کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1730817 1521441 2016 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Cross-domain feature selection and coding for household energy behavior
ترجمه فارسی عنوان
انتخاب ویژگی های متقابل دامنه و برنامه نویسی برای رفتار انرژی خانوار
کلمات کلیدی
رفتار انرژی خانوار، عوامل جمعیت شناختی، طبقه بندی مشتری، انتخاب ویژگی و برنامه نویسی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی (عمومی)
چکیده انگلیسی


• A cross-domain feature selection and coding method for household energy behavior is proposed.
• The method extracts and connects customers' features from smart metering data and demographic data.
• The results show that employment status and internet usage are highly correlated with household energy behavior in Ireland.

Household energy behavior is a key factor that dictates energy consumption, efficiency and conservation. In the past, household energy behavior was typically unknown because conventional meters only recorded the total amount of energy consumed for a household over a significant period of time. The rollout of smart meters enabled real-time household energy consumption to be recorded and analyzed. This paper uses smart meter readings from more than 5000 Irish households to identify energy behavior indicators through a cross-domain feature selection and coding approach. The idea is to extract and connect customers' features from energy domain and demography domain, i.e., smart metering data and household information. Smart metering data are characterized by typical energy spectral patterns, whereas household information is encoded as the energy behavior indicator. The results show that employment status and internet usage are highly correlated with household energy behavior in Ireland because employment status and internet usage have an important effect on lifestyle, including when to work, play, and rest, and hence yield a difference in electricity use style. The proposed approach offers a simple, transparent and effective alternative to a challenging cross-domain matching problem with massive smart metering data and energy behavior indicators.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy - Volume 107, 15 July 2016, Pages 9–16
نویسندگان
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