Using Regression Analysis to Predict the Demand Function of Electricity: A Case Study

Khozani, Hasan Karimian; Esmaeili, Esmaeil; Bisheh, Mohammad Najjartabar; Ayatollahi, Seyed Ahmad; Gilanifar, Mostafa

doi:10.3844/ajeassp.2020.759.767

Cited by 1 publication

(1 citation statement)

References 16 publications

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“…Furthermore, there are four graphs of linear regression lines are also shown in Figure 8 can be used as a fast method of visually depicting the relationship between the IV, x and the DV, Y. The information displayed in Figure 7 is not only important for the calculation of saving later on but also can be used to give some insights for proper actions for future energy saving measures (ESM) [20]. For instance, IV 1 shows the lowest correlation with the r-squared=0.2982 which can be interpreted as a very low correlation and has no significant effect on future ESM [21].…”

Section: Discussionmentioning

confidence: 99%

GUI-Based Data Visualisation Tool for Option C IPMVP using Jupyter Notebook

Abdullah

2023

JMechE

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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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Section: Discussionmentioning

confidence: 99%

GUI-Based Data Visualisation Tool for Option C IPMVP using Jupyter Notebook

Abdullah

2023

JMechE

View full text Add to dashboard Cite

show abstract

Using Regression Analysis to Predict the Demand Function of Electricity: A Case Study

Cited by 1 publication

References 16 publications

GUI-Based Data Visualisation Tool for Option C IPMVP using Jupyter Notebook

GUI-Based Data Visualisation Tool for Option C IPMVP using Jupyter Notebook

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