Evaluating the power investment options with uncertainty in climate policy

Yang, Ming; Blyth, William; Bradley, Richard A.; Bunn, Derek W.; Clarke, Charlie; Wilson, Thomas S.

doi:10.1016/j.eneco.2007.06.004

Cited by 186 publications

(96 citation statements)

References 9 publications

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“…In accordance with the literature we assume a 5% trend for the EUA price process (Yang et al, 2008;Fuss et al, 2008Fuss et al, , 2009Fuss et al, , 2010.…”

Section: Price-processesmentioning

confidence: 99%

“…For EUA prices we follow current results in the literature that attempt to model their price development (Yang et al, 2008;Fuss et al, 2008Fuss et al, , 2009Fuss et al, , 2010, by assuming the price development to follow a geometric Brownian motion (GBM) with a positive trend. The basic reason for using GBM to model the price process, is that it is generally expected that prices for allowances will reach a higher long-term price than the current one, despite possible price reductions from time to time.…”

Section: Price-processesmentioning

confidence: 99%

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The Clean Development Mechanism, Stochastic Permit Prices, and Energy Investments

Hieronymi¹,

Schüller²

2015

Political Economy and Instruments of Environmental Politics

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In this paper we evaluate the simultaneous impact of two emission permit classes with stochastically evolving prices on energy investments. We consider permits that are allocated and auctioned inside the EU (EUA) and secondary Certified Emission Reductions permits (sCER), which are resold primary CER from the CDM. One price taking firm subject to emission regulation has the choice to invest in a wind power plant, a gas power plant or can choose do to nothing. An investment in either plant type is considered to be irreversible. When investing in the gas plant the investor also has to consider the future development of emission prices. We use Monte-Carlo simulation to generate price paths for the emission permits, which serve as an input for a recursive optimization problem. We find that allowing the usage of offset permits in the present policy framework leads to a significantly lower probability of an investment into wind power taking place. If the quota of sCER permits is doubled, the decrease in the investment probability into wind is more than proportional. Decoupling the price processes does not significantly alter the results. Since the CDM has been under a lot of criticism over the years, recently especially concerning its baseline-methodology and a subsequent over-supply of emission permits, policy makers should be careful in constructing new offset mechanisms without properly understanding the impact on investment behavior. JEL-Classification: C63,Q47

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“…In accordance with the literature we assume a 5% trend for the EUA price process (Yang et al, 2008;Fuss et al, 2008Fuss et al, , 2009Fuss et al, , 2010.…”

Section: Price-processesmentioning

confidence: 99%

Section: Price-processesmentioning

confidence: 99%

The Clean Development Mechanism, Stochastic Permit Prices, and Energy Investments

Hieronymi¹,

Schüller²

2015

Political Economy and Instruments of Environmental Politics

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“…In the review of Dias and Shackleton (2005) [44] switching between the options to invest or disinvest is analysed considering different methods of stochastically evolving interest rates: the (CIR) model and the Vasicek model. In more recent studies [45] it is argued that the simulation of interest rates may contribute to the elimination of arbitrary risk premium assumptions, mainly within the framework of real-options models. The capital costs may decrease over time due to the global experience on similar projects, introducing further time-dependent characteristics in the analysis of energy investments [21,46,47].…”

Section: Time Dependent Investments Under Uncertaintymentioning

confidence: 99%

An impact assessment of electricity and emission allowances pricing in optimised expansion planning of power sector portfolios

Tolis

Rentizelas

2011

Applied Energy

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This version is available at https://strathprints.strath.ac.uk/44919/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. AbstractThe present work concerns a systematic investigation of power sector portfolios through discrete scenarios of electricity and CO2 allowance prices. The analysis is performed for different prices, from regulated to completely deregulated markets, thus representing different electricity market policies. The modelling approach is based on a stochastic programming algorithm without recourse, used for the optimisation of power sector economics under multiple uncertainties. A sequential quadratic programming routine is applied for the entire investigation period whilst the time-dependent objective function is subject to various social and production constraints, usually confronted in power sectors. The analysis indicated the optimal capacity additions that should be annually ordered from each competitive technology in order to substantially improve both the economy and the sustainability of the system. It is confirmed that higher electricity prices lead to higher financial yields of power production, irrespective of the CO2 allowance price level.Moreover, by following the proposed licensing planning, a medium-term reduction of CO2 emissions per MWh by 30% might be possible. Interestingly, the combination of electricity prices subsidisation with high CO2 allowance prices may provide favourable conditions for investors willing to engage on renewable energy markets.

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“…Note that, while portfolio theory allows for a top-down view of the energy mix, the real options approach is more suited to represent decision-making at the plant and investment project level. Recent applications to energy investment include Madlener et al (2005), Fleten et al (2007), Laurikka and Koljonen (2006), Szolgayová et al (2008), Yang et al (2008), for which the use of real options approaches is practically limited by issues of computational practicality. See also Kann and Weyant (2000) on this topic.…”

Section: Box Real Options Theorymentioning

confidence: 99%

Technology Portfolios: Modelling Technological Uncertainty and Innovation Risks

Grübler¹,

Fuss²,

McCollum³

et al. 2013

Energy Technology Innovation

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AUTHORS' SUMMARYThe case study reviews a range of methodologies and model-based applications that can assist policy decisions under irreducible technology innovation uncertainties. One approach uses scenario analysis. A scenario study that explored a range of salient future uncertainties identified energy efficiency and conservation as the single most important and also most robust technology option for climate mitigation. Another approach uses portfolio theory to quantify the benefits from diversified technology portfolios in the framework of risk-averse decision-making. Such studies suggest risk aversion leads to higher adoption rates of currently higher-cost energy technology options such as modern biomass, renewables, and also carbon capture and storage (CCS). Diversification not only reduces the mean of risk exposure but also drastically lowers the tails of extreme undesirable outcomes. Portfolio theory and scenario analysis can also be combined, as illustrated by a study of three different energy system objectives (energy security, air pollution, climate change) within a multi-criteria optimization framework. Scenarios in which objectives were met individually, and then all together, under a range of uncertainties again demonstrated the benefits of portfolio diversification with greater emphasis on energy efficiency and "general purpose" energy conversion technologies. These examples discussed in this case study show that formal tools and approaches, including scenario analysis, portfolio theory, and multi-criteria optimization, are increasingly available to move technology portfolio decisions onto a more rational ground.

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Evaluating the power investment options with uncertainty in climate policy

Cited by 186 publications

References 9 publications

The Clean Development Mechanism, Stochastic Permit Prices, and Energy Investments

The Clean Development Mechanism, Stochastic Permit Prices, and Energy Investments

An impact assessment of electricity and emission allowances pricing in optimised expansion planning of power sector portfolios

Technology Portfolios: Modelling Technological Uncertainty and Innovation Risks

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