GUI-based data visualisation tool for option C IPMVP using Jupyter notebook / Ezmin Abdullah ... [et al.]
IPMVP is an acronym for International Performance Measurement and Verification Protocol, used for calculating energy savings by taking some external factors into account to give an equal base for a linear comparison between two periods. However, determining the significant independent variable for r...
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Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Faculty of Mechanical Engineering Universiti Teknologi MARA (UiTM)
2023
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Subjects: | |
Online Access: | https://ir.uitm.edu.my/id/eprint/72408/1/72408.pdf https://doi.org/10.24191/jmeche.v20i3.23898 https://ir.uitm.edu.my/id/eprint/72408/ https://doi.org/10.24191/jmeche.v20i3.23898 |
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Summary: | IPMVP is an acronym for International Performance Measurement and Verification Protocol, used for calculating energy savings by taking some external factors into account to give an equal base for a linear comparison between two periods. However, determining the significant independent variable for routine adjustment causes inconvenient repeated action of regression analysis modeling, which leads to the exhaustive calculation and human error risk. These exasperating actions led to the creation of this project, which aims to provide a user-friendly, insightful, and accurate energy-saving calculation program tool. Thus, the main objective of this project is to develop an energy-saving computational tool for option C IPMVP using web-based data analytic tools to improve efficiency and accuracy in each project. This paper used a web-based mathematical computation, Jupyter Notebook, to determine the significant independent variable for routine adjustment of the adjusted baseline. The program tool was validated using V-model software verification and validation methodology based on IEEE 1012 standards. The study can be concluded that the exhaustive calculation to determine the energy saving based on IPMVP standards can be significantly reduced with precision values at 50%, 80%, 90%, and 95% confidence levels using the proposed program which is equipped with insightful graphs and a user-friendly interface. |
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