Modelling the impacts of building regulations and a property bubble on residential space and water heating

被引:31
作者
Dineen, D. [1 ]
Gallachoir, B. P. O. [2 ]
机构
[1] Natl Univ Ireland Univ Coll Cork, Environm Res Inst, Cork, Ireland
[2] Natl Univ Ireland Univ Coll Cork, Dept Civil & Environm Engn, Cork, Ireland
关键词
Energy demand model; Residential sector; Bottom up; Archetype; USE ENERGY-CONSUMPTION;
D O I
10.1016/j.enbuild.2010.09.004
中图分类号
TU [建筑科学];
学科分类号
081407 [建筑环境与能源工程];
摘要
This paper develops a bottom-up model of space and water heating energy demand for new build dwellings in the Irish residential sector This is used to assess the impacts of measures proposed in Ireland s National Energy Efficiency Action Plan (NEEAP) The impact of the housing construction boom which resulted in 23% of occupied dwellings in 2008 having been built since 2002 and the subsequent bust are also assessed The model structure treats separately new dwellings added to the stock after 2007 and pre-existing occupied dwellings The former is modelled as a set of archetype dwellings with energy end use affected by the relevant set of building regulations that apply during construction Energy demand of existing dwellings is predicted by a simpler top down method based on historical energy use trends The baseline scenario suggests residential energy demand will grow by 19% from 3206 ktoe in 2007 to 3810 ktoe in 2020 The results indicate that 2008 and 2010 building regulations will lead to energy savings of 305 ktoe (80%) in 2020 Had the 2008 building regulations been introduced in 2002 at the start of the boom there would be additional savings of 238 ktoe (6 7%) in 2020 (C) 2010 Elsevier B V All rights reserved
引用
收藏
页码:166 / 178
页数:13
相关论文
共 30 条
[1]
ADEME, 2007, ADEME EV EN EFF EU 1
[2]
Aigner DJ, 1984, The Energy Journal, V5
[3]
[Anonymous], 2008, 13790 ISO
[4]
[Anonymous], EU EN TRANSP FIG STA
[5]
Modeling of the space and domestic hot-water heating energy-consumption in the residential sector using neural networks [J].
Aydinalp, M ;
Ugursal, VI ;
Fung, AS .
APPLIED ENERGY, 2004, 79 (02) :159-178
[6]
Comparison of neural network, conditional demand analysis, and engineering approaches for modeling end-use energy consumption in the residential sector [J].
Aydinalp-Koksal, Merih ;
Ugursal, V. Ismet .
APPLIED ENERGY, 2008, 85 (04) :271-296
[7]
BARRETT A, 2009, ESRI RES B, V91
[8]
Defining the rebound effect [J].
Berkhout, PHG ;
Muskens, JC ;
Velthuijsen, JW .
ENERGY POLICY, 2000, 28 (6-7) :425-432
[9]
CANES ME, 2002, EC MODELLING CLIMATE
[10]
Dennehy E., 2009, Energy Efficiency in Ireland