Luuk Beurskens

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.

Chapter 6 – Portfolio Analysis of the Future Dutch Generating Mix

Publisher Summary Technology costs have been chosen in accordance with the cost–benefit analysis study for offshore wind. Input data have been composed with utmost attention and care, but the true future costs remain highly dependent on external factors. This chapter presents results of an application of Markowitz Portfolio Theory (MPT) to the future portfolio of electricity generating technologies in the Netherlands in the year 2030. Projections of two base-case generating mixes and general scenario assumptions have been taken from two specific scenarios designed by the Dutch Central Planning Bureau (CPB). Risk estimates were derived following a predefined methodology, and projections of long-term cost and risk for generating options specifically and portfolios at large remain difficult, even under the most up-to-date approaches. Furthermore, fuel correlations and technology parameter correlations are indicative and based on expert judgments. This chapter focuses on the electricity cost–risk dimension of the Dutch portfolio of generating technologies and the potential for additional deployment of renewable generating technologies to enhance the efficiency of base-case generating mixes in year 2030. The major results of this study are, in both scenarios, that the base-case generating mix is not very efficient. Graphical analysis suggests that diversification may yield up to 20% risk reduction at no extra cost; promotion of renewable energy can greatly decrease the portfolio cost risk and defining mixes without renewables results in significantly riskier mixes in the absence of concomitant significant changes in portfolio costs; because of its relatively low cost risk and high potential, large-scale implementation of offshore wind can reduce cost risk of the Dutch generating portfolio.

Renewable Heating and Cooling: The Key to A Large Contribution of Renewable Energy

Heating and cooling in the industrial, commercial, and domestic sectors constitute around 40–50% of global final energy demand. Renewable energy heating and cooling (REHC) technologies offer an important alternative to conventional fuels to fulfill these demands. As a joint project of the International Energy Agency (IEA) Renewable Energy Technology Deployment Program and the IEA Renewable Energy Unit, this paper presents an up-to-date review of the status of available REHC technologies including a delineation of cost. Some solar thermal, geothermal, and biomass heating technologies are already cost-competitive with conventional technologies fueled by electricity or gas. A broad market overview is provided. Political support for REHC has not been commensurate with existing support for renewable electricity and biofuels. In an examination of the limited support available, policies across 12 OECD nations are summarized. Financial incentive schemes are analyzed in terms of renewable heating capacity deployed per budget allocated. Examples of good practice policies for each technology are elaborated in each respective category: carrot-based incentives, stick-based regulations, and guidance-based informative schemes. Results indicate that a combination of carrot, stick and guidance based schemes, is the most effective in advancing the deployment of REHC technologies.