RESEARCH ARTICLE
Intelligent Services for Building Information Modeling - Assessing Variable Input Weather Data for Building Simulations
Constantinos A. Balaras*, Simon Kontoyiannidis, Elena G. Dascalaki, Kaliopi G. Droutsa
Article Information
Identifiers and Pagination:
Year: 2013Volume: 7
First Page: 138
Last Page: 145
Publisher ID: TOBCTJ-7-138
DOI: 10.2174/1874836820131022005
Article History:
Received Date: 6/09/2013Revision Received Date: 16/10/2013
Acceptance Date: 17/10/2013
Electronic publication date: 31/10/2013
Collection year: 2013
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Building Information Modeling (BIM) for optimizing the total lifecycle cost of buildings is a challenge even today. Inadequate software interoperability, high costs as a result of the fragmented nature of the building industry, lack of standardization, inconsistent technology adoption among stakeholders are just some of the obstacles that architects and engineers face. However, optimization requires a structured procedure that enables continuous changes in design variables and assessment on energy consumption. A holistic building design and construction are already introduced in Europe through the energy performance of buildings directive (EPBD). The requirements have been strengthened by the EPBD recast for achieving cost optimal building designs for the life cycle of the building, moving towards nearly zero energy buildings by the end of the decade. BIM and intelligent services could play a crucial role in these efforts with improved visualization and productivity due to easy retrieval of information, increased coordination of data and exchange of information, all leading to a reduced cost for the design of energy efficient buildings. An ongoing European research project aims to contribute to these needs by developing a Virtual Energy Laboratory that will support building energy performance simulations taking into account the stochastic nature of input parameters and processes. This will be supported by information communication technology features utilizing the necessary computational power through cloud computing. This paper presents an overview of the ongoing efforts and focuses on results for assessing the impact of different input weather and climate data that are pertinent in building load and energy performance calculations.
