A multi-objective decision model for the improvement of energy efficiency in buildings
Kostas Kalaitzakis and
Energy, 2010, vol. 35, issue 12, 5483-5496
Improving energy efficiency in buildings is a major priority worldwide. The measures employed to save energy vary in nature, and the decision maker is required to establish an optimal solution, taking into account multiple and usually competitive objectives such as energy consumption, financial costs, environmental performance, etc. In other words, the decision maker is facing the challenge to solve a multi-objective optimization problem, although the common practice usually employs other methods like simulation and multiple criteria decision analysis techniques that exploit possibly many but in any case limited alternative options. The multi-objective decision model, presented herein, aims to overcome this limitation by allowing the examination of a potentially infinite number of alternative measures, evaluated according to a set of criteria, which include the annual primary energy consumption of the building, the annual carbon dioxide emissions and the initial investment cost. These criteria are adjusted to the decision maker’s preferences and are optimized with the aid of compromise programming, which is a well-established multi-objective solution methodology. A simple case study is used to demonstrate the functionality of the proposed decision model. The results verify the feasibility of the approach, thus encouraging further improvements and extensions.
Keywords: Building energy efficiency; Energy efficiency improvement; Multi-objective optimization (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (21) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:35:y:2010:i:12:p:5483-5496
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Series data maintained by Dana Niculescu ().