Energy and Carbon Emission Efficiency Prediction: Applications in Future Transport Manufacturing

Ragosebo Kgaugelo Modise, Khumbulani Mpofu and Olukorede Tijani Adenuga
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Ragosebo Kgaugelo Modise: Department of Industrial Engineering, Tshwane University of Technology, Pretoria 0001, South Africa
Khumbulani Mpofu: Department of Industrial Engineering, Tshwane University of Technology, Pretoria 0001, South Africa
Olukorede Tijani Adenuga: Department of Industrial Engineering, Tshwane University of Technology, Pretoria 0001, South Africa

Energies, 2021, vol. 14, issue 24, 1-15

Abstract: The long-term impact of high-energy consumption in the manufacturing sector results in adverse environmental effects. Energy consumption and carbon emission prediction in the production environment is an essential requirement to mitigate climate change. The aim of this paper is to evaluate, model, construct, and validate the electricity generated data errors of an automotive component manufacturing company in South Africa for prediction of future transport manufacturing energy consumption and carbon emissions. The energy consumption and carbon emission data of an automotive component manufacturing company were explored for decision making, using data from 2016 to 2018 for prediction of future transport manufacturing energy consumption. The result is an ARIMA model with regression-correlated error fittings in the generalized least squares estimation of future forecast values for five years. The result is validated with RSS, showing an improvement of 89.61% in AR and 99.1% in MA when combined and an RMSE value of 449.8932 at a confidence level of 95%. This paper proposes a model for efficient prediction of energy consumption and carbon emissions for better decision making and utilize appropriate precautions to improve eco-friendly operation.

Keywords: energy efficiency; carbon dioxide emission; energy consumption; ARIMA (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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