کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
771796 1462872 2015 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Historical trends and current state of heating and cooling degree days in Italy
ترجمه فارسی عنوان
روند تاریخی و وضعیت فعلی درجه حرارت و درجه حرارت در ایتالیا
کلمات کلیدی
تقاضای انرژی، ساختمان، روزهای تحصیلی روند آب و هوا، پیش بینی مصرف
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی (عمومی)
چکیده انگلیسی


• A comparison among methods for calculating heating degree-days (HDD) is provided.
• ASHRAE method is used for analyze the historical trends of HDD and CDD in Italy.
• The HDD historical profile for Rome is decomposed in its characterizing components.

Degree days (DD) represent a versatile climatic indicator which is commonly used in the analysis of building energy performance, as e.g. (i) to perform energetic assessment of existent and new buildings, (ii) to analyze the territory energy consumption, (iii) to develop scenario analyses in terms of energy consumption forecasting, and so on.Different methods can be used for determining the DD values, depending on the available climatic data of each location. In the present paper, the simplified methods based on reduced climatic data set have been compared assuming the mean daily degree-hours method (MDDH) as reference. Hourly temperature profiles recorded by the meteorological station located at the University of Genoa have been used for these analyses.In the second part of the present work, the ASHRAE method has been selected to calculate heating (HDD) and cooling (CDD) degree days for several Italian cities. In particular, daily meteorological data of several Italian cities (covering the whole climatic conditions which occur in Italy) have been used to calculate heating and cooling degree days in the period 1978–2013, in order to analyze their trends in the last years. Finally, the historical profiles of Rome and Milan have been treated as time-series and analyzed in the frequency domain, performing a decomposition of the original data set into different characterizing components. This simplified approach permits to deeply analyze the historical profile of DD and represents a simple starting point method for future analyses with forecasting perspectives.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy Conversion and Management - Volume 90, 15 January 2015, Pages 323–335
نویسندگان
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