Timing of investment under technological and revenue-related uncertainties

Murto, Pauli

doi:10.1016/j.jedc.2006.05.010

Cited by 61 publications

(53 citation statements)

References 10 publications

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“…), and technological uncertainty ( [19][20][21][22][23][24][25]). The basic model used in this article for the optimization of plant-level decisions and the derivation of the profit distributions for the portfolio optimization is closest to [17] and [18], also in terms of solution methodology, even though neither of the two has stochastic fuel prices and the subject is rather different.…”

Section: Literature Reviewmentioning

confidence: 99%

Robust Energy Portfolios Under Climate Policy and Socioeconomic Uncertainty

Szolgayová

Fuss

Khabarov

et al. 2011

Environ Model Assess

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Concerning the stabilization of greenhouse gases, the UNFCCC prescribes measures to anticipate, prevent, or minimize the causes of climate change and mitigate their adverse effects. Such measures should be cost-effective and scientific uncertainty should not be used as a reason for postponing them. However, in the light of uncertainty about climate sensitivity and other underlying parameters, it is difficult to assess the importance of different technologies in achieving robust long-term climate risk mitigation. One example currently debated in this context is biomass energy, which can be used to produce both carbon-neutral energy carriers, e.g., electricity, and at the same time offer a permanent CO 2 sink by capturing carbon from the biomass at the conversion facility and permanently storing it. We use the GGI Scenario Database IIASA [3] as a point of departure for deriving optimal technology portfolios across different socioeconomic scenarios for a range of stabilization targets, focusing, in particular, on new, lowemission scenarios. More precisely, the dynamics underlying technology adoption and operational decisions are analyzed in a real options model, the output of which then informs the portfolio optimization. In this way, we determine the importance of different energy technologies in meeting specific stabilization targets under different circumstances (i.e., under different socioeconomic scenarios), providing valuable insight to policymakers about the incentive mechanisms needed to achieve robust long-term climate risk mitigation.

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Section: Literature Reviewmentioning

confidence: 99%

Robust Energy Portfolios Under Climate Policy and Socioeconomic Uncertainty

Szolgayová

Fuss

Khabarov

et al. 2011

Environ Model Assess

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“…Stochastic investment cost has traditionally been modelled with a Brownian motion process [25], a geometric Brownian motion (GBM) [26][27][28] or a GBM with jumps [29]. More recently, Murto [30] and Fuss and Szolgayová [31] let the investment cost be dependent on a Poisson random variable. Jaimungal et al [32] point out the mean reverting behavior of the investment cost and assume that it follows the exponential of a mean reverting process.…”

Section: Introductionmentioning

confidence: 99%

Investment in electric energy storage under uncertainty: a real options approach

et al. 2016

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Problem descriptionThe growing portion of renewables in the generation mix has led to an increasing need for ancillary services in the electricity grid. As a part of this green shift, the role of storage in the electricity market has changed. Traditionally, the motivation for investing in storage was based on time arbitrage of the spot price. Today, the investments in storage are being linked with the need for improving the power quality and balancing the grid.Recent research papers point out that investments in small storage facilities are not profitable today without public support. This thesis will apply the real options framework, and investigate the profitability of energy storage under uncertain electricity prices, balancing prices and investment cost. It will further consider how policy makers can trigger investments in electric energy storage. PrefaceThis is a master thesis written within the field of Financial Engineering at the Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology (NTNU). We would like to thank our supervisors, Verena Hagspiel and Stein-Erik Fleten, for professional guidance throughout the project. We also wish to thank Professor Sonja Wogrin at Universidad Pontificia Comillas de Madrid for technical assistance, PhD candidate Lars Ivar Hagfors at NTNU for valuable input and Statkraft for providing market data. Trondheim, 8th of June 2015Ida BakkeBeate Norheim AbstractThe transition from conventional power sources to renewable energy sources is taking place in a number of European countries. Electric energy storage has been proposed as an environmentally friendly solution to make this transition possible. This thesis analyzes the profitability of investing in a battery bank in Germany and the UK, using a real options model. The model determines the option value and the optimal investment time, under the conditions of uncertain revenues and investment cost. The results show that it is profitable to invest in both countries, given that the battery banks can participate in both the spot and balancing market. The valuation also gives insight into how the battery bank should be operated between the two markets to maximize its expected profits and discovers that the battery earns over 70 % of its profit from ancillary services. This finding underlines the importance for investors to not only consider revenues from the spot market. The thesis further analyzes how uncertainty affects investor behavior and explains why there is a reluctance to invest in storage technology under the current market conditions; the investor is favoring the option to wait for more information. SammendragOvergangen fra konvensjonelle energikilder til fornybare energikilder finner sted i en rekke europeiske land. Elektrisk energilagring har blitt foreslått som en miljøvennlig løsning forå gjøre denne overgangen mulig. I denne masteroppgaven utvikler vi en realopsjonsmodel for a analysere lønnsomheten vedå investere i batteribanker i Storbritannia og Tyskland. Mode...

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“…Grenadier and Weiss (1977), Farzin et al (1998), Doraszelski (2004. Moreover, Pauli Murto (2007) investigates the interactions between the technological and the revenue-related uncertainties. The main reason why the scholars valuate a real asset (a project or firm value) by the real option approach is that the traditional NPV method underestimates the value of the real asset because of the neglect of the uncertainty and the manufacturing flexibility (Pindyck, 1991;Triantis and Hodder, 1990).…”

Section: Introductionmentioning

confidence: 99%