An ontology-based decision support tool for optimizing domestic solar hot water system selection

Citation data:

Journal of Cleaner Production, ISSN: 0959-6526, Vol: 112, Page: 4636-4646

Publication Year:
2016
Usage 202
Abstract Views 194
Link-outs 8
Captures 35
Readers 33
Exports-Saves 2
Citations 6
Citation Indexes 6
DOI:
10.1016/j.jclepro.2015.08.088
Author(s):
Efstratios Kontopoulos, Georgios Martinopoulos, Despina Lazarou, Nick Bassiliades
Publisher(s):
Elsevier BV
Tags:
Energy, Environmental Science, Business, Management and Accounting, Engineering
article description
In an effort to tackle climate change most countries utilize renewable energy sources. This is more pronounced in the building sector, which is currently one of the major consumers of energy, mostly in the form of heat. In order to further promote the use of domestic solar hot water systems in buildings, an ontology-based decision support tool has been developed and is presented in this paper. The proposed tool aids non-technical consumers to select a domestic solar hot water system tailored to their needs, containing up-to-date information on its components and interrelationships, installation costs etc., in the form of an ontology formulated in OWL (Web Ontology Language). The optimum system configurations are computed based on various specific parameters, such as number of occupants, daily hot water requirements and house location. The backbone of the proposed system is an ontology that represents the application domain and contains information regarding the various domestic solar hot water system components along with their interrelationships. Ontologies are a rapidly evolving knowledge representation paradigm that offers various advantages and, when deployed specifically in the domestic solar hot water systems domain, deliver improved representation, sharing and re-use of the relevant information. As a conclusion, this paper presents an ontology-driven decision support system for facilitating the selection of domestic solar hot water system, which delivers certain advantages, such as sustainability of the decision support system itself, due to its open and interoperable knowledge-base, and its adaptability/flexibility in decision making policies, due to is semantic (ontological) nature.

This article has 0 Wikipedia reference.