Power curves prediction using empirical data regression on small scale compressed air energy storage

Author:

. Widjonarko,Soenoko R.,Wahyudi S.,Siswanto E.

Abstract

The key to optimizing the system is to know the operating point of the system at the time of loading, or it is known as the power curve. However, to identify the power curve, the existing method is to model the mathematical of the system. Therefore some component characteristics need to be known and need additional observations if the component variable is unknown, and it becomes a long identification process. So, in this exploratory research will be presented the way to find out the power curve of a system without modeling mathematical of the system, but by using the polynomial regression technique. This regression technique form is using the empirical data of the power curve form parameter on SS-CAES prototype. The method is based on five approach model in which is the variation of loading sampling data to be used with the purpose is to find the best sampling of prediction. The data will be analyzed in the form of statistical parameters and the graph to show the evaluation process of this technique. From the results of the regression can be concluded that the power curve of SS-CAES can be identified with a high correlation value of 0.997 (99,745% accuracy) and the best way to take samples of data to be used in this technique is presented in the paper.

Publisher

Universiti Malaysia Pahang Publishing

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering,Mechanics of Materials,Energy Engineering and Power Technology,Fuel Technology,Computational Mechanics

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3