TY - JOUR VL - 13 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84876467656&doi=10.3923%2fjas.2013.377.384&partnerID=40&md5=cf7884f4cde3309a22b5fb0daf679fef A1 - Majid, M.A.A. A1 - Sulaiman, S.A. A1 - Mokhtar, H. A1 - Tamiru, A.L. JF - Journal of Applied Sciences Y1 - 2013/// KW - Absorption process; Current performance; Data clustering; Multi-state reliability; Overall efficiency; Performance monitoring; Steam absorption; Tri-generation plants KW - Absorption cooling; Clustering algorithms; Energy management; Recovery; Refrigerators; Steam generators; Trigeneration plant; Waste heat KW - Cluster analysis ID - scholars3661 N2 - As part of a tri-generation plant, an absorption process provides the means to recover the energy that otherwise would be lost to the environment. Since the overall efficiency relies on the amount of energy recovered in all subsystems, knowing the current performance of the absorption process is vital to proper management of the resources. This study proposes the use of data clustering technique to estimate the most frequent operating point experienced by the absorption system in a given year. The same technique is applied to identify operating point trajectory of the system over nine years. In order to demonstrate applicability of the proposed approach, an absorption system that is comprised of two 12 ton h-1 heat recoveiy steam generators and two 1250 RT double-effect LiBr-H2O steam absorption chillers is considered as a case study. It was observed that data clustering technique is an effective method in establishing the relationships between the supplied heat and the amount of energy recovered by each subsystem. The heat recoveiy steam generators were identified as operating at part load ratio of about 0.41. The clustering method clearly revealed that both chillers deteriorated in performance. The absorption systems were mostly run at part load ratio of about 0.8. As such, at this operating point the energy demand was by 43 higher than that required for a healthy system. The proposed technique is applicable for performance monitoring, optimization and multi-state reliability studies of the absorption system. © 2013 Asian Network for Scientific Information. IS - 3 EP - 384 SN - 18125654 TI - Operating point estimation for an absorption process using data clustering technique SP - 377 N1 - cited By 1 AV - none ER -