Skip to main content
eScholarship
Open Access Publications from the University of California

UC Berkeley

UC Berkeley Electronic Theses and Dissertations bannerUC Berkeley

Adoption of Renewable Energy Technologies Under Uncertainty

Abstract

Abstract

Adoption of Renewable Energy Technologies under Uncertainty

by

Kiran Nari Torani

Doctor of Philosophy in Agricultural and Resource Economics

University of California, Berkeley

Professor Gordon Rausser, Chair

This dissertation presents both a theoretical and empirical examination of the optimal allocation of public R&D investments in combination with downstream policy instruments across emerging renewable technologies. The central issue remains how best to enable technological change, and accelerate innovation and widespread adoption of new energy technologies and move towards a more sustainable energy system.

The first essay presents a stochastic dynamic real options model of the adoption of solar PV in the residential and commercial sector, evaluating the threshold and timing of the consumer's optimal investment decision given two sources of uncertainty. Analytic results regarding the threshold of adoption under alternative regimes of R&D funding and technological change, electricity prices, subsidies and carbon taxes are derived. And we simulate the model to obtain a cumulative likelihood and timing of substitution amongst energy resources and towards solar PV under plausible rates of technological change, electricity prices, subsidies and carbon taxes.

The results indicate that there will be a displacement of incumbent technologies and a widespread shift towards solar PV in the residential and commercial sector in under 30 years, under plausible parameter assumptions - and that crucially, this can occur independent of consumer subsidies and carbon pricing policies (at $21/ton CO2, $65/ton CO2 and $150/ton CO2). In general, results across all scenarios consistently indicate that average historic consumer subsidies and carbon pricing policies up to $150/ton CO2 have a modest effect in accelerating adoption, and may not be an effective part of climate policy in this regard. Instead, we find that R&D support and further technological change is the crucial determinant and main driver of widespread adoption of solar PV - suggesting that subsidies and taxes don't make a substantial difference in a technology that's not viable, while research does. This further suggests that optimal policies may change over time, however current continued R&D support and technological advancement is the crucial determinant of widespread transition to solar and plausibly other backstop technologies - and that it should play a key role in policy measures intended to combat climate change. The results do not imply that carbon pricing shouldn't play a role in climate policy in general. Carbon pricing may be effective in reducing emissions and encouraging the transition towards other clean technologies - however it has a decidedly modest impact in accelerating adoption of solar PV at levels up to $150/ton CO2.

The second essay examines the role of technology features in policy design, and provides a broader discussion and context to the results from the first essay. It examines the key role of the technology innovation cycle and changing optimal policies at every stage of the technology in the transition towards renewable energy technologies. And it examines the stages of the technology innovation process and the role of policy incentives at every stage - including the timing, sequencing, and role of investments in public R&D, in deployment polices, and in CO2 taxes.

We examine the notion that that optimal policies will change over time, driven primarily by the characteristics of the technology, and its stage in the innovation cycle - and that this will crucially determine the impact, gains and tradeoffs between alternate policy measures such as R&D policies, deployment policies, and carbon pricing policies. We find that technology and policies must be deployed in a coordinated manner such that emission reduction benefits are achieved at an acceptable cost. And we find that targeted policy should consider every stage of the technology innovation cycle - from R&D to commercialization in overcoming barriers to the development and widespread adoption of nascent technologies.

Based on our analysis and results we find that there is a pressing need for the reallocation of public resources from consumer subsidies towards public R&D budgets in emerging energy technologies such as solar PV, and plausibly other backstop technologies. We argue for an expanded role of aggressive R&D policies and increased public R&D funding - and contend that there is an imbalance in resources allocated towards adoption and commercialization subsidies relative to R&D investments for a technology such as solar PV. We contend that increased and aggressive R&D investments will be the key policy initiative in enabling the transition towards clean energy technologies such as solar PV in a sustainable manner.

When deployment policies are justified, the appropriate timing and sequencing in the technology development stage is crucial. Investments in commercialization and deployment subsidies before sufficient R&D investments and breakthroughs have occurred will be ineffective and unsustainable, or alternatively will need to be very high to have any significant impact (Torani, Rausser, and Zilberman, 2014). Widespread adoption and commercialization of emerging and unproven technologies and systems will be unlikely to occur unless sufficient major technological discoveries and improvements have taken place - which will need to be driven by appropriate and sufficient R&D investments. The logical sequence of policies necessitates first making sufficient investments and allocating resources towards R&D and the necessary technological discoveries, which can then be followed by downstream investments to enhance adoption, experience and LBD. In general, we find that the appropriate emphasis and sequencing of R&D and learning investments is a pertinent issue, and optimal timing and allocation between the two depends in part on the characteristics of the technology itself.

In addition, while almost all economic studies find a case for imposing immediate restraints on GHG emissions, e.g. with initially low carbon taxes, we find that reasonable and plausible levels of CO2 taxes may not be effective in encouraging technology adoption and reducing emissions while clean technologies are not commercially viable as yet. To be effective in encouraging technology adoption at an early stage of technological innovation, we contend that a large CO2 tax may be needed, far larger than suggested at reasonable levels - with significant implications on distributional effects and political feasibility. We emphasize that technology and policies must be deployed in a coordinated manner such that the emission reduction benefits are achieved at an acceptable cost (Williams et al., 2012). Our results suggest that the first and most important stage does not lie in imposing CO2 taxes, but rather in investing in R&D and technological advancements. Once clean technologies are sufficiently ready, reasonably priced carbon taxes will bite to a larger extent and be more effective at plausible levels. We find that one plausible strategy would be either to introduce high CO2 taxes or to subsidize R&D first, followed by deployment and LBD policies, and then to impose reasonable carbon taxes - in which case scientific advances and technological changes would make CO2 emissions abatement less costly, and CO2 pricing would be effective at reasonable levels.

The third essay provides a precursor and basis for the other two chapters. The paper outlines an analytical framework to determine the optimal combination of renewable energy public R&D investment in combination with downstream policy instruments across the emerging technologies as an ex-ante portfolio analysis of public and private R&D under risk and uncertainty. Our framework is based on the estimation of probability distributions for potential future cost reductions resulting from R&D investments from the public and private sectors.

To date, the government lacks coordinated support of renewable energy technologies across upstream R&D investments and downstream policy instruments. Without an objective, ex-ante guide for renewable energy investment, governments are likely to promote technologies based on the effectiveness of political economic efforts. The government's policies should however depend on the technology's probability distribution of cost breakthroughs for each technology and on the environmental impact. In this paper we outline an analytical framework to develop a portfolio analysis of R&D investments in renewable energy technologies, with the subsequent analysis designed to allocate R&D investments across renewable energy technologies in a manner that minimizes the risk for a specified level of expected returns, taking into account both the expected reductions in cost and the variance of the expectations of cost reductions, and thus providing an objective benchmark for efficient allocation of resources across renewable energy technologies. Special emphasis is placed on the estimation of probability distributions based on elicitation from experts in each field of technology in terms of the mean and standard deviation - on which we base the characterization of the underlying probability distributions on cost and productivity measures, and which forms the basis for executing a portfolio analysis of renewable energy technologies.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View