DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Sooyoung | ko |
dc.contributor.author | Lee, Ji-Hyun | ko |
dc.contributor.author | Moon, Jin Woo | ko |
dc.date.accessioned | 2015-04-06T06:02:39Z | - |
dc.date.available | 2015-04-06T06:02:39Z | - |
dc.date.created | 2014-11-27 | - |
dc.date.created | 2014-11-27 | - |
dc.date.issued | 2014-12 | - |
dc.identifier.citation | BUILDING AND ENVIRONMENT, v.82, pp.328 - 338 | - |
dc.identifier.issn | 0360-1323 | - |
dc.identifier.uri | http://hdl.handle.net/10203/194766 | - |
dc.description.abstract | This study describes integrated logic for an artificial neural network (ANN) to control heating devices on a continuous basis. Two ANN-based control logic systems and two conventional rule-based logic systems were developed to control a heating device and the openings of a double skin enveloped building. The ANN-based logic controls heating devices on a continuous basis according to the indoor temperature. The rule-based logic controls heating systems and openings at envelopes in two-position on/off operation. Control performance for the developed logic was numerically conducted using computer simulations for a small office space with double skin envelopes during the heating season. Analysis results indicate that the ANN-based temperature control logic resulted in a more stable temperature near the center of the comfortable range with a reduced opening period of the internal envelope. The reduced number of on/off moments of the heating device and the openings in the ANN-based logic were predicted to save energy and prevent system degradation. The use of ANN-based logic would be effective for maintaining a stable thermal environment and for system operation. Rule-based logic can be effectively used to improve building energy efficiency. In this study, two ANN-based logic types were developed for heating devices controlled on a continuous basis and their performance was compared with those of rule-based on/off logic. Thus, in order to cover the limitation of this study, further study is warranted for examining the clear difference achieved by ANN-based vs. rule-based control, when they are applied to control heating output on a continuous basis. | - |
dc.language | English | - |
dc.publisher | PERGAMON-ELSEVIER SCIENCE LTD | - |
dc.subject | THERMAL-CONTROL METHODS | - |
dc.subject | RESIDENTIAL BUILDINGS | - |
dc.subject | ENERGY PERFORMANCE | - |
dc.subject | SOLAR BUILDINGS | - |
dc.subject | STRATEGIES | - |
dc.subject | COMFORT | - |
dc.subject | MODELS | - |
dc.subject | WINTER | - |
dc.subject | BEHAVIOR | - |
dc.subject | OFFICES | - |
dc.title | Performance evaluation of artificial neural network-based variable control logic for double skin enveloped buildings during the heating season | - |
dc.type | Article | - |
dc.identifier.wosid | 000346543500031 | - |
dc.identifier.scopusid | 2-s2.0-84923344375 | - |
dc.type.rims | ART | - |
dc.citation.volume | 82 | - |
dc.citation.beginningpage | 328 | - |
dc.citation.endingpage | 338 | - |
dc.citation.publicationname | BUILDING AND ENVIRONMENT | - |
dc.identifier.doi | 10.1016/j.buildenv.2014.08.031 | - |
dc.contributor.localauthor | Lee, Ji-Hyun | - |
dc.contributor.nonIdAuthor | Kim, Sooyoung | - |
dc.contributor.nonIdAuthor | Moon, Jin Woo | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Thermal control logic | - |
dc.subject.keywordAuthor | Variable heating devices | - |
dc.subject.keywordAuthor | Opening condition of envelope | - |
dc.subject.keywordAuthor | Rule-based controls | - |
dc.subject.keywordAuthor | Optimum control | - |
dc.subject.keywordAuthor | Artificial neural network | - |
dc.subject.keywordPlus | THERMAL-CONTROL METHODS | - |
dc.subject.keywordPlus | RESIDENTIAL BUILDINGS | - |
dc.subject.keywordPlus | ENERGY PERFORMANCE | - |
dc.subject.keywordPlus | SOLAR BUILDINGS | - |
dc.subject.keywordPlus | STRATEGIES | - |
dc.subject.keywordPlus | COMFORT | - |
dc.subject.keywordPlus | MODELS | - |
dc.subject.keywordPlus | WINTER | - |
dc.subject.keywordPlus | BEHAVIOR | - |
dc.subject.keywordPlus | OFFICES | - |
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