Shimon Awerbuch

Investing in photovoltaics: risk, accounting and the value of new technology

Abstract In Europe and the US, national energy planning agencies value resource alternatives using outmoded techniques, conceived around the time of the Model-T Ford. These models, long since discarded in manufacturing and other industries, bias in favor of riskier fossil alternatives while understating the true value of photovoltaics (PV) and similar low-risk, passive, capital-intensive technologies. PV and similar renewables offer a unique cost-risk menu along with other valuable attributes that traditional valuation models, conceived long before such attributes became technologically feasible, cannot “see” because they are steeped in the vocabulary and measurement concepts of a different technological era. Properly understood and exploited, the attributes of PV could undoubtedly form the basis for reengineering the electricity production and delivery process to deliver cost reductions in ways that can yet not be imagined. Lenders and investors likewise do not yet fully understand the unique financial properties of PV as differentiated from traditional resource alternatives. Policy makers have a responsibility to broaden the analytic horizons to include new valuation models and concepts that more properly reflect the unique attributes of PV.

Capital budgeting, technological innovation and the emerging competitive environment of the electric power industry

Abstract For most of this century the electric utility industry has operated as a regulated natural monopoly which produced a commodity product in an environment of low technological progress and sold it to a homogeneous captive market. Given these conditions, the primary capital budgeting issues involved the timing of capacity additions and the mix of base load and peaking capacity. This relatively simple and stable situation, however, has been eroded by market, regulatory and technological changes. As a consequence, old embedded capital budgeting approaches are hindering the pursuit of efficiency with respect to the production and distribution of electric energy. Our purpose in this paper is to assess traditional utility capital budgeting procedures and to explore possibilities for improvement. We begin with a review of traditional capital budgeting decision processes. Next, we overview the changes that have emerged over the last two decades and explore capital budgeting processes more appropriate to this ‘early competitive environment’. Finally, we project the changes a bit further and explore the capital budgeting techniques that may be useful in an ‘advanced competitive environment’.

Do consumers discount the future correctly?: A market-based valuation of residential fuel switching

Abstract DSM and energy-efficiency options are generally evaluated using engineering oriented discounted cash flow procedures which value all cost and benefit streams using a single arbitrary discount rate — usually the firms weighted average cost of capital (WACC). The WACC based approach ignores financial risk and hence leads to unreliable results. In a recent paper in this journal Hassett and Metcalf depart from this tradition; they reflect financial risk by simulating the total variability of returns from energy saving investments. Their findings indicate that DSM projects are potentially risky, suggesting that the net benefits must be discounted at significantly higher rates, thus lowering their present values. This paper presents a market based evaluation of a particular DSM option — residential fuel switching — using the capital asset pricing model (CAPM). Under the CAPM approach, a risk adjusted, market based discount rate is estimated for each cost stream — fuel, maintenance and avoided outlays for electricity. The market based results, which reflect the systematic risk of each cost stream, suggest that fuel switching is probably not cost-effective because it is considerably more risky than indicated by a WACC based analysis. This supports Hassett and Metcalfs conclusion that consumers who reject DSM projects are not necessarily acting irrationally.

Chapter 3 – Using Portfolio Theory to Value Power Generation Investments

Publisher Summary nThis chapter introduces the intuition and theory underpinning the application of Mean-Variance Portfolio theory to the power sector. Mean-Variance Portfolio theory can usefully complement traditional valuation approaches to inform a country or utility on the optimal generation portfolio to minimize the impact of some critical risks in liberalized power markets. Electric utilities operating in liberalized markets are faced with a wide range of risks and uncertainties when evaluating different generation technologies. While many of the risks facing power producers in liberalized electricity markets existed in the fully regulated and vertically integrated industry, investors can no longer pass these costs on to consumers or taxpayers automatically. The traditional “levelized cost” valuation approach was well adapted to assess power investments prior to liberalization. The levelized cost methodology remains widely used in the liberalized industry, both by energy planners and by electric companies. Most importantly, the levelized cost methodology values investment projects on a stand-alone basis. The various generation technologies have different risk–return profiles, and there are potentially great advantages in operating a diversified portfolio of plants for a utility. Because it does not take into account the complementarity in the risk–return profiles of different plants that a utility operates, the levelized cost methodology cannot inform a utility or country on the optimal technological choice for an additional power plant, given the current portfolio that a utility or country operates. The expected risk of an electricity portfolio is a weighted average of the risks of the individual technology costs, tempered by their correlations or covariances.

Full-spectrum portfolio and diversity analysis of energy technologies

Publisher Summary Energy diversity and security are evaluated using Stirlings Multi-criteria Diversity Analysis (MDA) as well as more classical Markowitz Mean Variance Portfolio (MVP) theory. Each of these approaches is capable of producing an Efficient Frontier (EF) that shows optimal generating mixes—those that maximize performance (i.e. minimize cost) while minimizing risk or uncertainty (i.e. maximizing diversity). MDA covers the full spectrum of “incertitude,” reaching into areas where little is known about the range of possible outcomes, let alone their probabilities. However, MDA does not exploit statistical information that is available in certain parts of the risk spectrum where historic means, variances, and co-variances of outcomes are known as well as are used to make inferences about the future. MVP operates precisely in this space, although, like other capital market models, its prescriptive value rests on the idea that the past is the best guide to the future and that. As such MVP can be blind to unforeseen events that create future structural change.

The Role of Wind Generation in Enhancing Scotland’s Energy Diversity and Security: A Mean-Variance Portfolio Optimization of Scotland’s Generating Mix

Todays dynamic and uncertain energy environment requires portfolio-based techniques that reflect market risk and de-emphasize stand-alone generating costs. MVP theory is well tested and ideally suited to evaluating national electricity strategies. It helps to identify solutions that enhance energy diversity and security and are therefore more robust than arbitrarily mixing technology alternatives. Portfolio analysis reflects the cost interrelationship (covariances) among generating alternatives, which is crucial for correctly evaluating generating portfolios. The analysis does not represent or advocate for a particular capacity expansion plan. Rather, its purpose is to demonstrate that increasing the share of wind in Scotland generally lowers overall generating costs, even if it is believed that wind costs more than gas. Larger wind shares appear to insulate better the generating mix from systematic risk of gas (and coal) price movements, which have historically been quite correlated. Given the high degree of uncertainty about future energy prices, the relative value of generating technologies must be determined not by evaluating alternative resources, but by evaluating alternative resource portfolios. Energy analysts and policy makers face a future that is technologically, institutionally and politically complex and uncertain. In this environment, MVP techniques help to establish renewables targets and portfolio standards that make economic and policy sense. They also provide the analytical basis that policy makers need to devise efficient generating mixes that maximize security and sustainability.

The Virtual Utility: Some Introductory Thoughts on Accounting, Learning and the Valuation of Radical Innovation

This paper examines the problems associated with the application of traditional capital budgeting practices to the valuation of radically new processes and technologies in an environment of rapid technological change. It focuses on a restructured utility industry, and the possible emergence of the Virtual Utility.

The cost of geothermal energy in the western US region:a portfolio-based approach a mean-variance portfolio optimization of the regions' generating mix to 2013.

Energy planning represents an investment-decision problem. Investors commonly evaluate such problems using portfolio theory to manage risk and maximize portfolio performance under a variety of unpredictable economic outcomes. Energy planners need to similarly abandon their reliance on traditional, least-cost stand-alone technology cost estimates and instead evaluate conventional and renewable energy sources on the basis of their portfolio cost--their cost contribution relative to their risk contribution to a mix of generating assets. This report describes essential portfolio-theory ideas and discusses their application in the Western US region. The memo illustrates how electricity-generating mixes can benefit from additional shares of geothermal and other renewables. Compared to fossil-dominated mixes, efficient portfolios reduce generating cost while including greater renewables shares in the mix. This enhances energy security. Though counter-intuitive, the idea that adding more costly geothermal can actually reduce portfolio-generating cost is consistent with basic finance theory. An important implication is that in dynamic and uncertain environments, the relative value of generating technologies must be determined not by evaluating alternative resources, but by evaluating alternative resource portfolios. The optimal results for the Western US Region indicate that compared to the EIA target mixes, there exist generating mixes with larger geothermal shares at equal-or-lower expectedmorexa0» cost and risk.«xa0less