Discount rate for technology assessment

Stocks, K. J.

doi:10.1016/0140-9883(84)90014-8

Cited by 15 publications

(4 citation statements)

References 9 publications

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“…Our results match well with the findings of Höglund-Isaksson (2012), and they also give a potential explanation for why other studies have shown contradicting results. Bearing in mind the irregularity of our results over ambition levels, it is perfectly possible that the non-impact of changing interest rates in van Harmelen et al (2002) and Markandya et al (2018) is consistent with the large impact of varying discount rates presented in Stocks (1984), Dimson (1989), andde Vries et al (2007).…”

Section: Discussionmentioning

confidence: 50%

“…van Harmelen et al (2002) controlled for the impacts of interest rates and found that 'The choice of the interest rate of 4% has only a minor influence on the technology mix ', and Markandya et al (2018) noticed that a discount rate variation of 0-6% had little impact on results. Stocks (1984), however, showed how the cost-optimal choice of energy technologies in an Australian energy system would differ substantially depending on the discount rate used in the cost calculations, with similar results shown for British utilities in Dimson (1989). Further, de Vries et al (2007) showed how global future estimated potential of wind power and solar photo voltaic is affected by interest rates.…”

Section: Introductionmentioning

confidence: 92%

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Investment perspectives on costs for air pollution control affect the optimal use of emission control measures

Åström

Kiesewetter

Schöpp

et al. 2018

Clean Techn Environ Policy

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Cost-effective air pollution emission control has been in focus for decades in international air pollution regulations. Despite large observed emission reductions for many air pollutants, environmental and human health problems persist and more efforts are needed. However, some stakeholders are concerned that the costs for remaining emission control measures are prohibitively high. There are several reasons for concern, and one can be the difference in investment perspectives-i.e. costs of borrowing and time constraints-held by stakeholders. By using the integrated assessment model GAINS, we study whether differences in investment perspectives of Nordic stakeholders influence measures selected for cost-effective emission control and can motivate concerns for high costs of emission control. We distinguish the control cost calculations between a social planner perspective and a corporate perspective and apply these to the GAINS model database on emission control measures. A cost-minimized selection of measures in 2030 is then calculated for increasing environmental and health ambitions for both perspectives. The results show an irregular pattern, but for a range of ambition levels the corporate perspective affects the selection of measures and implies surplus costs for the Nordic social planner of up to 120 million € per year. This is 36% more expensive than the costs of the social planners' selection. Conversely, from a corporate perspective the social planners' selection can imply cost increases of up to 180 million €. We therefore suggest that control of investment perspective effects should be standard in analysis of cost-effective air pollution measures.

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Section: Discussionmentioning

confidence: 50%

Section: Introductionmentioning

confidence: 92%

Investment perspectives on costs for air pollution control affect the optimal use of emission control measures

Åström

Kiesewetter

Schöpp

et al. 2018

Clean Techn Environ Policy

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“…The cash flow of Figure 1 summarizes this information, while Table 1 shows the NPV of selecting the high technology battery over the conventional one for different discount rates λ, from 0% to 20%. It can be observed that lower discount rates favor the adoption of the high technology alternative, in accordance with [34]. The second disadvantage of the NPV is that it does not provide information about the initial effort.…”

Section: Net Present Valuementioning

confidence: 59%

Generation of Alternative Battery Allocation Proposals in Distribution Systems by the Optimization of Different Economic Metrics within a Mathematical Model

Martinez

Tabares

2021

Energies

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Battery systems bring technical and economic advantages to electrical distribution systems (EDSs), as they conveniently store the surplus of cheap renewable generation for use at a more convenient time and contribute to peak shaving. Due to the high cost of batteries, technical and economic studies are needed to evaluate their correct allocation within the EDS. To contribute to this analysis, this paper proposes a stochastic mathematical model for the optimal battery allocation (OBA), which can be guided by the optimization of two different economic metrics: net present value (NPV) and internal rate of return (IRR). The effects of the OBA in the EDS are evaluated considering the stochastic variation of photovoltaic generation and load. Tests with the 33-node IEEE test system indicate that OBA results in voltage profile improvement (~1% at peak time), peak reduction (31.17%), increased photovoltaic hosting capacity (18.8%), and cost reduction (3.06%). Furthermore, it was found that the IRR metric leads to a different solution compared to the traditional NPV optimization due to its inherent consideration of the relation between cash flow and investment. Thus, both NPV and IRR-based allocation alternatives can be used by the decision maker to improve economic and technical operation of the EDS.

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“…Clean energy technologies require substantial upfront financing due to their high capital intensity (Borenstein, 2012). Therefore, their cost-competitiveness for large-scale deployment strongly depends on their cost of capital (Hirth & Steckel, 2016;Stocks, 1984), which can be reduced substantially through debt financing (Schmidt et al, 2019)-particularly if higher leverage ratios can be obtained by using project finance (Steffen et al, 2018). However, this requires bank loans as long as technologies and firms have not matured sufficiently to tap bond markets (Berger & Udell, 1998).…”

Section: Literature Reviewmentioning

confidence: 99%

Mobilizing Credit for Clean Energy: De-Risking and Public Loan Provision Under Learning Spillovers

Waidelich,

Krug,

Steffen

2023

SSRN Journal

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Discount rate for technology assessment

Cited by 15 publications

References 9 publications

Investment perspectives on costs for air pollution control affect the optimal use of emission control measures

Investment perspectives on costs for air pollution control affect the optimal use of emission control measures

Generation of Alternative Battery Allocation Proposals in Distribution Systems by the Optimization of Different Economic Metrics within a Mathematical Model

Mobilizing Credit for Clean Energy: De-Risking and Public Loan Provision Under Learning Spillovers

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