Producing energy in a stochastic environment: Switching from non-renewable to renewable resources

Mosiño, Alejandro

doi:10.1016/j.reseneeco.2012.04.002

Cited by 10 publications

(7 citation statements)

References 35 publications

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“…where inf stands for infimum or greatest lower bound, see [Mosino (2012)] for example. For presentation purposes we take the the deterministic path followed by C as our 5e/tCO 2 Investment Cost Function I(T ) e214.5 × 10 6 exp(−0.0202T ) Difference in Plant gross revenues △α e(22 + 50) × 10 6 /y Difference in emission coupling Constants △q 2.397 × 10 6 tCO 2 /y reference path, even in the stochastic case.…”

Section: A Numerical Example Of the Investment Decision In The Rest Omentioning

confidence: 99%

When to invest in carbon capture and storage technology: A mathematical model

Walsh¹,

O’Sullivan²,

Lee³

et al. 2014

Energy Economics

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Section: A Numerical Example Of the Investment Decision In The Rest Omentioning

confidence: 99%

When to invest in carbon capture and storage technology: A mathematical model

Walsh¹,

O’Sullivan²,

Lee³

et al. 2014

Energy Economics

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“…Pindyck (2002) and Pindyck (2007) use single-factor real option models in addressing similar problems in environmental economics. The nearest papers apparently to ours are Boomsma et al (2012), Mosiño (2012) and Abadie and Chamorro (2013), but their solutions are either numerical (and often more realistic) or based on somewhat different assumptions and objectives, including capacity determination, and switching from non-renewable to renewable resources (see also Tahvonen and Salo, 2001).…”

Section: Introductionmentioning

confidence: 99%

“…Output could be electricity, biodiesel, ethanol or directly useful energies (like heat), each of which are likely to follow somewhat different diffusion processes. Sometimes, these specific diffusion processes will not enable analytical solutions, see Mosiño (). Note gBm may not be appropriate for modeling electricity prices, which may be mean‐reverting, so solutions using the Kummer function as shown in Dockendorf and Paxson () may be required.…”

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confidence: 99%

Subsidies for Renewable Energy Facilities under Uncertainty

Adkins

Paxson

2015

The Manchester School

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We derive the optimal investment timing and real option value for a facility with price and quantity uncertainty, where there might be a government subsidy proportional to production quantity. Where the subsidy is proportional to the multiplication of the price and quantity, dimensionality can be reduced. Alternatively, we provide quasianalytical solutions for different quantity subsidy arrangements: permanent (policy is certain); retractable; suddenly permanent; and suddenly retractable. Whether policy uncertainty acts as a disincentive for early investment depends on the type of subsidy arrangement. The greatest incentive for early investment is an actual retractable subsidy, a 'flighty bird in hand'.

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“…The realization of this study required a prior analysis of the relevant literature with a view to gaining an insight into the various rapeseed production and cultivation techniques [25,26,27,28,29,30,31,32]. The resulting information was integrated by the outcome of a series of interviews conducted with the main agricultural consortiums and trade associations of the Viterbo Province.…”

Section: Methodsmentioning

confidence: 99%

Analysis of the economic and application-related sustainability of biofuels - A case study

Mosconi¹,

Poponi²,

Parsi³

2014

ams

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Biofuels represent for the European Union an important energy source, and their production has been encouraged by a series of policies aimed at controlling oil prices, reaching the security of the energy supply and cutting the greenhouse gas emissions. This paper deals with the production of biofuels from the point of view of its economic sustainability and of the effects that the EU directives have had on the Italian productive context. Besides, this paper presents the outcome of an empiric study based on the economic sustainability of the production of rapeseed intended to fuel a new power plant. The study, conducted in the territory of the Viterbo Province (Italy), singles out the various types of rapeseed seeds that best adapt to the climatic-environmental features of the territory and, based on their yield and the production target of the new power plant, ascertains the land area to be reconverted or to be devoted to this type of crop. 6482Enrico Maria Mosconi et al.

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Producing energy in a stochastic environment: Switching from non-renewable to renewable resources

Cited by 10 publications

References 35 publications

When to invest in carbon capture and storage technology: A mathematical model

When to invest in carbon capture and storage technology: A mathematical model

Subsidies for Renewable Energy Facilities under Uncertainty

Analysis of the economic and application-related sustainability of biofuels - A case study

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