A simulation and optimisation methodology for choosing energy efficiency measures in non-residential buildings

被引:29
|
作者
Ceballos-Fuentealba, Irlanda [1 ]
Alvarez-Miranda, Eduardo [2 ,5 ]
Torres-Fuchslocher, Carlos [2 ,4 ]
Luisa del Campo-Hitschfeld, Maria [3 ,4 ]
Diaz-Guerrero, John [4 ]
机构
[1] Univ Talca, Fac Engn, Dept Ind Engn, MSc Programme Operat Management, Campus Curico, Talca, Chile
[2] Univ Talca, Fac Engn, Dept Ind Engn, Campus Curico, Talca, Chile
[3] Univ Talca, Fac Engn, Dept Construct Engn & Management, Campus Curico, Talca, Chile
[4] Univ Talca, Fac Engn, Ctr Tecnol Kipus, Campus Curico, Talca, Chile
[5] Inst Sistemas Complejos Ingn, Santiago, Chile
关键词
Building energy simulation; Building retrofit; Energy efficiency; SYSTEM INTELLIGENCE; SOLAR-RADIATION; MODEL; DESIGN; AUTOMATION; STRATEGIES; INCIDENT;
D O I
10.1016/j.apenergy.2019.113953
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The global stock of buildings account for more than 40% of global energy consumption. Improving their energy behaviour thus offers tremendous potential for promoting sustainable development. While new buildings can be benefited from new construction methods and techniques for ensuring a sustainable operation, a sustainable operation of existing buildings is only possible by retrofitting. However, the later represent the larger portion of the total stock, so effective retrofitting is fundamental for global improvement of energy efficiency. This article develops a methodological framework for predicting (i) the energy consumed in heating and cooling an existing commercial or institutional building, and (ii) the potential impact of different energy conservation measures that could be implemented on a given building. The proposed tool incorporates a simulation model and an algorithm strategy for parameter optimization. The framework is implemented in the JAVA programming language and evaluated in a case study of a 500 [m(2)] institutional building located in Puerto Montt, Chile. The results of this implementation show that the tool is competitive with the state-of-the art commercial simulation tool DesignBuilder. More importantly, it successfully estimated the savings obtained from different combinations of energy conservation measures for the building and proved to be computationally efficient, the algorithm requiring only 2.5 h to complete the simulation.
引用
收藏
页数:19
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