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How to upgrade an enterprise’s low-carbon technologies under a carbon tax: The trade-off between tax and upgrade fee

Senyu He, Jianhua Yin, Bin Zhang and Zhao-Hua Wang ()

Applied Energy, 2018, vol. 227, issue C, 564-573

Abstract: Reducing CO2 emissions is a hot topic, and an important policy to achieve this target is carbon tax. When an enterprise is subject to a carbon tax, it has to pay this extra fee for the long-term if it does not upgrade its production technology. It needs to pay a certain upgrade fee in the short-term if it chooses to upgrade its plant. Thus, it has been an important problem for enterprises seeking to balance the trade-off between the ‘long-term tax fee’ and the ‘short-term upgrade fee’. This paper explores how to optimise an enterprise’s production technology upgrade strategy based on existing low-carbon technologies, to minimise the total upgrade cost subject to an expected total cost per product. An integer programming model is proposed to formulate the problem, and a ‘multi-agent system – genetic algorithm’ method is presented for its solution. The model is applied to a numerical example and the results indicate that the proposed method is feasible. The impacts of carbon tax and enterprise’s expected cost on its technology upgrade strategy are further discussed.

Keywords: Carbon tax; Production technology upgrade; Strategy optimisation; Multi-agent system; Genetic algorithm (search for similar items in EconPapers)
Date: 2018
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