dc.contributor.author | WIDJONARKO, Widjonarko | |
dc.contributor.author | SOENOKO, Rudy | |
dc.contributor.author | WAHYUDI, Slamet | |
dc.contributor.author | SISWANTO, Eko | |
dc.date.accessioned | 2020-07-21T03:13:07Z | |
dc.date.available | 2020-07-21T03:13:07Z | |
dc.date.issued | 2019-06-01 | |
dc.identifier.uri | http://repository.unej.ac.id/handle/123456789/99855 | |
dc.description.abstract | The research on small scale compressed air energy storage (SS-CAES) becomes an interesting topic
especially in optimizing the performance of the system. In this topic, the characteristic curve of the energy storage
system is the key to control the system to reach optimum power to the load. In previous research, mathematical
equations were used to get the characteristic curve. This paper proposes the polynomial regression based on the
actual output data from the prototype to model the characteristic curve of the SS-CAES prototype. The authors have
compared the use of mathematical models and polynomial regression in modeling the power curve with actual
observational data and determining the level of accuracy of modeling. The results showed that by using polynomial
regression, the characteristics of the SS-CAES prototype power curve could only be obtained by using the sample
data from the system output with accuracy value 0.967 for R-square. Thus, an approach using this method would
facilitate researchers to obtain the characteristics of the curve of the system. | en_US |
dc.language.iso | en | en_US |
dc.publisher | International Energy Journal, Volume 19, Issue 2, June 2019 | en_US |
dc.subject | modeling | en_US |
dc.subject | optimization | en_US |
dc.subject | polynomial regression | en_US |
dc.subject | power curve | en_US |
dc.subject | small scale compressed air energy storage (SS-CAES) | en_US |
dc.title | Modeling of Power Characteristic Curve on Small Scale Compressed Air Energy Storage using Regression Analysis | en_US |
dc.type | Article | en_US |
dc.identifier.kodeprodi | KODEPRODI1910201#Teknik Elektro | |
dc.identifier.nidn | NIDN0008097102 | |