Carbon Footprint Management: A Pathway toward Smart Emission Abatement
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date
2019
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Language
en
Pages
13
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IEEE Transactions on Industrial Informatics, Volume 16, issue 2, pp. 935-948
Abstract
There is an increasing concern about controlling and reducing carbon emissions in power systems. In this regard, researchers have focused on managing emissions on the generation side, which is the main source of emissions. Considering emission limits on the generation side results in an increase in locational marginal prices that negatively affects social welfare. However, carbon emissions are a by-product of electricity generation that is used to satisfy the demands on the consumer side. Consequently, demand side emission control may not be achieved if only generation is taken into account. In order to fill this existing gap, in this paper, a demand-side management approach aiming at carbon footprint control is proposed. First, the carbon footprint is allocated among the consumers using an improved proportional sharing theorem method. Each consumer learns about their real-time carbon footprint, excess carbon footprint, and the incurred surcharge tax. Then, demands are adjusted via a proper adjustment procedure. This provides enough information for consumers where demand management may result in carbon footprint and demand reductions as well as the exemption of incurred taxes. Profit analysis for both generation and demand sides is carried out to show the effectiveness of the proposed framework using two illustrative case studies. The results obtained, compared with existing policies such as carbon cap, cap-and-trade, and carbon tax, prove the fairness and the advantages of the proposed model for both the demand and the generation sides.Description
Keywords
Carbon footprint allocation, Carbon abatement, Demand side management, Power tracing, Tax exemption
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Citation
Pourakbari-Kasmaei, M, Lehtonen, M, Contreras, J & Mantovani, J R S 2019, ' Carbon Footprint Management : A Pathway toward Smart Emission Abatement ', IEEE Transactions on Industrial Informatics, vol. 16, no. 2, pp. 935-948 . https://doi.org/10.1109/TII.2019.2922394