Agbondinmwin U. and Ebhojiaye R. S.*
Department of Production Engineering, University of Benin, Benin City, Nigeria
*Corresponding Author: email@example.com
Vol. 5 No. 1 | March 2021 | Pages 152 – 164
In this study, multiple linear regression models were employed in the correlation of gas supply and power generation using a gas Power Plant in Niger Delta, Nigeria as a Case study. From the analysis based on outlier detection, reliability analysis and test of homogeneity, it was observed that the independent variable data such as ambient temperature, gas pressure and compressed temperature failed normality test. Therefore, the use of any linear model for either analysis or modelling of the data was not acceptable. Data used for reliability analysis of the gas pressure and compressed temperature difference were positively correlated with power generation, having a covariance value of 0.639 and 113.148. The ambient temperature was negatively correlated with power generation, having a covariance value of 14.564. The positive value showed that both dimensions exclusively increased and decreased together with respect to the output while the negative value showed that increment in value of one variable led to decrease in the value of the other, and vice versa.
Keywords: Natural gas, Power generation, Regression models, Power plant, Ambient temperature
This work is licensed under a Creative Commons Attribution 4.0 International License.
Cite this article as:
Agbondinmwin U. and Ebhojiaye R. S. 2021. Modelling of Input Parameters for Power Generation using Regression Models. Nigerian Journal of Environmental Sciences and Technology, 5(1), pp. 152-164. https://doi.org/10.36263/nijest.2021.01.0241