Production portfolio optimisation under uncertainty: threats of emissions trading

Zapletal, František

doi:10.1504/ijads.2017.085083

Cited by 1 publication

(5 citation statements)

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“…Market demand for products and EUA price are crucial factors when exploring the influence of the EU ETS on companies, as shown by [9]. Unfortunately, it is not possible to use a longer time period because the last available observation on the demand provided by the company is for December 2016, despite more recent data on the EUA price are available.…”

Section: Modelmentioning

confidence: 99%

“…But, the aim of this paper is to analyse the potential effect of the uncertain parameters on the company, and not to get the 'best' possible estimate of the future. Therefore, a different approach based on [9] is applied here. In that single-period model, the author has used the last observation as a core of the particular fuzzy number (the current value presents the least uncertainty) and the variation range for the considered time period as a support of that fuzzy number.…”

Section: Fuzzification Of Selected Datamentioning

confidence: 99%

“…Therefore, in this paper, the fuzzy approach is used instead. The only one fuzzy optimisation model in this field, which has been published so far, is [9]. However, this paper was built only for a single period.…”

Section: Introductionmentioning

confidence: 99%

“…This study stems from [9] and extends the model into the multi-period environment. The proposed fuzzy optimisation model, which includes fuzzy EUA price and fuzzy demand, is solved using the possibilistic approach based on possibility and necessity measures [13].…”

Section: Introductionmentioning

confidence: 99%

“…The proposed fuzzy optimisation model, which includes fuzzy EUA price and fuzzy demand, is solved using the possibilistic approach based on possibility and necessity measures [13]. The model is verified using the data of the same real-life industrial company as in [8,9].…”

Section: Introductionmentioning

confidence: 99%

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Impacts of Emissions Trading on a Company Under Uncertain Multi-Period Environment

Zapletal

2019

Fuzzy Information and Engineering

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Emissions trading within the Emissions Trading Scheme of the European Union (EU ETS) influences European industrial companies since 2005. The companies must choose their strategy, how to reduce the costs of emissions allowances. The changing system's conditions and volatile price of allowances make this decision very tough. Moreover, the effect of this system on companies still increases as the policy-makers want to increase its efficiency, and the emission price increases. Despite several studies devoted to the relationship between the EU ETS and companies have already been published, there is still a gap in this field. Authors usually use the stochastic approach, which is not always applicable and it reveals the expected future result. In this paper, the potential range of impact of emissions trading is explored. Namely, the multi-period fuzzy possibilistic programming model is developed to reveal possible costs of emissions trading, optimal strategy on allowances and effect of banking the allowances for hedging against the risk. The model is verified using the data of a real-life industrial company. The results show that the costs of emissions trading are perceptible for the company and they can be reduced by up to 6% using banking.

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Section: Modelmentioning

confidence: 99%

Section: Fuzzification Of Selected Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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