Preprint Article Version 1 This version is not peer-reviewed

# Prediction of Power Characteristic Curve on Small Scale Compressed Air Energy Storage by Using Regression Analysis

Version 1 : Received: 12 June 2018 / Approved: 13 June 2018 / Online: 13 June 2018 (11:20:00 CEST)

How to cite: Widjonarko, W.; Soenoko, R.; Wahyudi, S.; Siswanto, E. Prediction of Power Characteristic Curve on Small Scale Compressed Air Energy Storage by Using Regression Analysis. Preprints 2018, 2018060212 (doi: 10.20944/preprints201806.0212.v1). Widjonarko, W.; Soenoko, R.; Wahyudi, S.; Siswanto, E. Prediction of Power Characteristic Curve on Small Scale Compressed Air Energy Storage by Using Regression Analysis. Preprints 2018, 2018060212 (doi: 10.20944/preprints201806.0212.v1).

## Abstract

The characteristic curve of a system, is the key to being able to control the system so as to provide optimum power to the load. In this paper, the researchers predicted the characteristic curve of the Small Scale Compressed Air Energy Storage prototype (SS-CAES) built using a polynomial regression analysis and based on the actual output data on the prototype. In this paper, researchers have compared the use of mathematical models and approach models using polynomial regression with actual observational data to determine the level of accuracy on the predictive curve of SS-CAES characteristic. The results showed that by using polynomial regression, the characteristics of the SS-CAES prototype power curve can be known without the need to model the mathematical equations of the system first and use only the sample data from the system output. Thus, approaching using this method will facilitate researchers in knowing the characteristics of the curve of the system.

## Subject Areas

empirical; mathematical; power curve; regression; Small Scale Compressed Air Energy Storage (SS-CAES)