Electricity cost estimates: How accurate are they, and are they fit for purpose in policy analysis?

This thesis is concerned with the history of electricity generation costs, how they have changed over time, and the accuracy of forecasts of future costs. These costs are a critical input to policy, yet both estimates and forecasts have frequently proved to be wrong or have changed dramatically over relatively short timescales. The thesis presents evidence from three technology case studies (offshore wind, nuclear power and solar PV), supported by a review of the range of cost measures used in the economic, business and policy spheres, and the methodologies used to understand the factors that bear upon cost trajectories and approaches to forecasting future costs. Drawing upon the evidence from the case studies, the thesis examines how cost forecasts have changed over time, the (frequently wide) range of forecasts, the sources of errors, and how policy has responded to uncertainty and changes in both cost estimates and forecasts. The findings address the limitations of commonly used cost metrics, challenge assumptions that costs will necessarily fall, discuss the meaning of regulatory certainty in the face of uncertain future costs, and emphasise the importance of context (why estimates are commissioned, and by whom, and also who they are undertaken by). The evidence suggests that the co-presentation and use of estimates and forecasts for technologies with very different technical and financial characteristics implies significantly more comparability between them than is wise, and can convey the message that the underlying uncertainties are similar, when in fact the reasons may be fundamentally different in character. This highlights how important an understanding of technology characteristics is when deriving estimates and forecasts, not simply because those characteristics bear upon the numerical values of the results, but because of the influence they have on the nature of the uncertainty of those results.Open Acces

How long does innovation and commercialisation in the energy sectors take? Historical case studies of the timescale from invention to widespread commercialisation in energy supply and end use technology

Recent climate change initiatives, such as ‘Mission Innovation’ launched alongside the Paris Agreement in 2015, urge redoubled research into innovative low carbon technologies. However, climate change is an urgent problem – emissions reductions must take place rapidly throughout the coming decades. This raises an important question: how long might it take for individual technologies to emerge from research, find market opportunities and make a tangible impact on emissions reductions? Here, we consider historical evidence for the time a range of energy supply and energy end-use technologies have taken to emerge from invention, diffuse into the market and reach widespread deployment. We find considerable variation, from 20 to almost 70 years. Our findings suggest that the time needed for new technologies to achieve widespread deployment should not be overlooked, and that innovation policy should focus on accelerating the deployment of existing technologies as well as research into new ones

The costs and impacts of intermittency: An ongoing debate: "East is East, and West is West, and never the twain shall meet."

A recent issue of Energy Policy carried a new contribution to the ongoing debate over the implications of a high penetration of wind power for the UK electricity system [Oswald, J., Raine, M., Ashraf-Ball, H., 2008. Will British weather provide reliable electricity? Energy Policy 36 (8), 3202-3215]. That paper made a number of points that require comment or qualification, in relation to both system-wide impacts and the impact on conventional thermal generation. The purpose of this forum piece is to respond to these points, and to explain where we believe the Oswald paper risks repeating the mistakes of the past by interpreting data in a selective manner, or by erroneously singling out alarming sounding findings which do not reflect how electricity systems and markets operate. The latest EU renewable energy targets do imply a wind penetration level which is considerably higher than that which has hitherto been envisaged, and new research is require to understand the potential impacts. However, such research must be based on statistical or time series simulation modelling.Electricity Intermittency Wind power

Winds of change: How high wind penetrations will affect investment incentives in the GB electricity sector

Wind power is widely expected to expand rapidly in Britain over the next decade. Large amounts of variable wind power on the system will increase market risks, with prices more volatile and load factors for conventional thermal plant lower and more uncertain. This extra market risk may discourage investment in generation capacity. Financial viability for thermal plant will be increasingly dependent on price spikes during periods of low wind. Increased price risk will also make investment in other forms of low-carbon generation (e.g. nuclear power) more challenging. A number of policies can reduce the extent to which generators are exposed to market risks and encourage investment. However, market risks play a fundamental role in shaping efficient investment and dispatch patterns in a liberalised market. Therefore, measures to improve price signals and market functioning (such as a stronger carbon price and developing more responsive demand) are desirable. However, the scale of the investment challenge and increased risk mean targeted measures to reduce (although not eliminate) risk exposure, such as capacity mechanisms and fixed price schemes, may have increasing merit. The challenge for policy is to strike the right balance between market and planned approaches.Wind power Electricity market reform Investment

How are future energy technology costs estimated? Can we do better?

Making informed estimates of future energy technology costs is central to understanding the cost of the low-carbon transition. A number of methods have been used to make such estimates: extrapolating empirically derived learning rates; use of expert elicitations; and engineering assessments which analyse future developments for technology components' cost and performance parameters. In addition, there is a rich literature on different energy technology innovation systems analysis frameworks, which identify and analyse the many processes that drive technologies' development, including those that make them increasingly cost-competitive and commercially ready. However, there is a surprising lack of linkage between the fields of technology cost projections and technology innovation systems analysis. There is a clear opportunity to better relate these two fields, such that the detailed processes included in technology innovation systems frameworks can be fully considered when estimating future energy technology costs. Here we demonstrate how this can be done. We identify that learning curve, expert elicitation and engineering assessment methods already either implicitly or explicitly incorporate some elements of technology innovation systems frameworks, most commonly those relating to R&D and deployment-related drivers. Yet they could more explicitly encompass a broader range of innovation processes. For example, future cost developments could be considered in light of the extent to which there is a well-functioning energy technological innovation system (TIS), including support for the direction of technology research, industry experimentation and development, market formation including by demand-pull policies and technology legitimation. We suggest that failure to fully encompass such processes may have contributed to overestimates of nuclear cost reductions and under-estimates of offshore wind cost reductions in the last decade

Do energy scenarios pay sufficient attention to the environment?

Scenario development is widely used to support the formation of energy policy, but many energy scenarios consider environmental interactions only in terms of climate change. We suggest that efforts to develop more holistic energy pathways, going beyond post hoc analysis of environmental and social implications, can usefully draw on environmental scenarios. A detailed content analysis of UK energy and environmental scenarios was therefore undertaken, with energy scenarios selected on the basis that they were recent, had a direct link to energy policy, and covered a range of scenario types. The energy scenarios rarely considered societal drivers beyond decarbonisation and focused on quantifiable parameters such as GDP, while the environmental scenarios provided a richer narrative on human behaviour and social change. As socio-economic issues remain fundamental to the success of energy policies, this is a key area which should be better addressed within energy scenarios. The environmental impacts of energy scenarios were rarely considered, but could have a significant bearing on the likelihood of pathway outcomes being realised. Fuller evaluation of the environmental interactions of energy systems is therefore required. Although the analysis focuses on the UK, some international scenarios show similar limitations, suggesting that the conclusions are more widely applicable

A socio-technical framework for assessing the viability of carbon capture and storage technology

Carbon capture and storage (CCS) is seen as a key technology to tackle climate change. The principal idea of CCS is to remove carbon from the flue gases arising from burning fuels for electricity generation or industrial applications and to store the carbon in geological formations to prevent it from entering the atmosphere. Policy makers in several countries are supportive of the technology, but a number of uncertainties hamper its further development and deployment. The paper makes three related contributions to the literatures on socio-technical systems and technology assessment: 1) It systematically develops an interdisciplinary framework to assess the main uncertainties of CCS innovation. These include technical, economic, financial, political and societal issues. 2) It identifies important linkages between these uncertainties. 3) It develops qualitative and quantitative indicators for assessing these uncertainties. This framework aims to help decision making on CCS by private and public actors and is designed to be applicable to a wider range of low carbon technologies. The paper is based on a systematic review of the social science literature on CCS and on insights from innovation studies, as well as on interviews about assessment of new technologies with experts from a range of organisations and sectors