Characterisation of the field
The scope of energy system analysis is broad, and fits within an integrated energy modelling approach. This is inherently interdisciplinary, with particular contributions from economics and engineering. Other social science insights (e.g., political science, international relations, sociology and policy analysis) and natural science (e.g., environmental studies, atmospheric chemistry) are incorporated as appropriate. The empiricalfocus of the model can be the whole energy system (economy-wide), particular elements of the ‘ energy chain’ (either upstream or downstream) or on key sectors (electricity, residential etc).
Energy modelling holds a key position within interdisciplinary research owing to the central role of energy projections in policy decision-making and the political importance of modelling results in policy debates. A particularly notable area of activity is the development and quantification of scenarios relevant to the assessment of energy policy.
In modelling, a broad distinction is usually drawn between top-down and bottom-up models:
Top-down models (both computable general equilibrium (CGE) and macro-econometric) analyse aggregate behaviour using historically derived economic indices of prices and elasticities. Top-down models are more suitable for studying economy-wide responses to energy policies and other drivers, and can generate insights intoincome, GDP, and competitiveness impacts. Technological detail and real-world constraints on investment and use are aggregated.
Bottom-up models, notably optimization or simulation approaches, can focus at the system or sectoral level, and may accommodate a wider range of policy options. Bottom-up models are more suitable for studying specific technical opportunities and their energy, cost and emission implications, although exogenous forecasts of economic activity may be used. Bottom-up models typically require extensive data sets and necessitate a difficult compromise between the realism of high levels of disaggregation and the constraints of data availability.
A particularly important difference is that top-down models tend to be more pessimistic than bottom-up models about the costs of energy policies. This is related to the difference in the scope and potential for energy efficiency improvements as well as the treatment of technological change. Partly to address these issues and partly to attempt to glean the best out of each modelling framework, a number of hybrid approaches are under development to link the macro and technological approaches to energy modelling.
A third key metric is micro-economics and complementary approaches to model behavioural change. This can be embodied in terms of energy supply, including oligopolistic or monopolistic behaviours, or in terms of energy demand with regards to price responses, heuristics in energyuse and diffusion of new technologies.
Furthermore a range of complementary approaches in energy modelling include greater temporal or spatial detail, explicit treatment of institutions, a systematic treatment of uncertainty, a focus on individual sectors or networks, and integrated assessment with environmental or social systems. These models often involve ‘soft-linking’ different types of models to investigate particular areas of interest (e.g., Geographic Information Systems (GIS) for spatial characteristics).
Research Challenges
Historically, issues related to energy system costs and security of supply have dominated energy modelling. However, in recent years the assessment of environmental issues (notably climate change and CO2 reductions), have become equally important. Such assessments of restructuring towards low carbon energy systems have produced a range of analytical challenges, including the assessment of long-run technological change, realistic modelling of behavioural responses, wider environmental and sustainability concerns, the accurate depiction of policy, and the relationship between the energy sector and economic drivers. As a result, energy model types are similarly broad to meet specific research questions, as detailed in the table in Section 2.
Fundamental research challenges include the interdisciplinary nature of the energy system and the resultant need to balance detailed representation of technical systems with regulatory, political, economic and social processes. Data availability for the UK is comparable to other OECD countries, with generally good coverage on traded energy commodities, end-user prices and technology inputs. Less data is available on behavioural responses to energy prices, as well as social and institutional factors in energy decision making. Long-term projection and analysis is problematic in how consumer preferences and technology development may evolve.
Quantitative energy modelling presents a difficulty in translating complex modelling into useful outputs for policy makers. A key challenge is encapsulating and emphasizing uncertainty in modelling outputs.
In the UK, uncertainties in the funding environment throughout the 1990s and early 2000s created difficulties for developing and maintaining modelling expertise within UK universities. Most models require extensive and long-term investment to construct and maintain, with much of this expertise embodied in teams of researchers. While short-term consultancy funding can be obtained for using models to address particular market or policy questions, this is insufficient to maintain modelling capacity. Over the last decade a sustained growth in funding spearheaded through the Research Councils (initially the Towards a Sustainable Energy Economy (TSEC), followed by the RCUK Energy Programme) is partially addressing this.
Like other interdisciplinarysocial science research, energy modelling falls between different academic departments and research networks. Coherence is aided through the co-ordination of international networks (including the IAEE, EMF and ETSAP), publication in a core set of academic journals (Energy Journal, Energy Economics, Energy Policy), and a growth in dedicated energy research groups and departments (e.g. at the Universities of Leeds, Sussex, Cambridge, Imperial and UCL).
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Table 2.1: UK Capabilities
As detailed in section 3 there is a broad range of energy models and modelling institutions. These encompass the range of top-down, bottom-up, hybrid and complementary approaches. UK modelling capacity is now building up through significant research council investments and supplemented by applied funders, all linked to increased interest in environmental, cost, and security of supply implications of energy supply and use.
The UK has a limited number of examples of energy modellingareas where it is very strong and world leading. The majority of UK energy modelling lies in the medium category illustrating competence and comparable expertise to other G8 countries. That the UK has relatively few weaknesses is a testament to the quality of UK modellers, and the positive impact of recent funding increases.
The unit of focus tends to be the UK as a whole. Aggregation into European or global models and disaggregation to regional or local models is becoming more prevalent, but is still in a minority of models.
In terms of specific modelling gaps in the UK, these include sectoral analysis (notably industry energy use), the impact of global drivers (i.e., resources, emissions trading, technological change), a better treatment of uncertainty via sensitivity and probabilistic assessments of model structure and parameter uncertainty, an enhanced understanding of the macro-economic implications of structural changes in the energy sector, and a deeper assessment of the role of behavioural change in energy use. Note, that the concept of market potential is not applicable to these underlying strategic analytical tools.
Table 3.1: Research Funding | Table 3.2: Key Research Providers
All UK activity is covered in this section as all energy modelling can be considered as basic/applied strategic research (from the Frascati (2002) definition of R&D).
UK capabilities in the energy modelling domain are arrayed between a number of academic departments, but also through government departments, and consultancies.
Energy modelling and analysis is one area where internal governmental resources have been maintained and even built up. This includes the DECC energy model and DECC pathways calculator. Sectoral-specific public expertise is seen via the National Transport Model, while the National Housing Model is currently under development.
A core set of academic modelling institutes exist that have a critical mass to undertake energy modelling and maintain and fund these analytical developments - these broadly align with the major UK centres of social science energy research. Major players include the University of Cambridge, University College London, University of Oxford, University of Leeds, Imperial College London, and University of Strathclyde. More isolated pockets of expertise exist in a range of other institutes.
Significant modelling expertise is retained in consultancies. These include former government research institutes (BRE and AEA) as well as a range of dynamic specialist firms (including Cambridge Econometrics, OXERA, Pöyry and Redpoint).
Additionally, major energy companies undertake a significant amount of model development and application (e.g., EON UK) but much of this is not in the public domain.
In terms of research funding, a welcome return to viability of undertaking long-term modelling capacities has been spurred by the sustained support of the RCUK Energy Programme. This has been supplemented with applied funding from European institutions, the Energy Technologies Institute (ETI), DECC and the Committee on Climate Change (CCC). However much of these latter funding streams remains generally ad hoc and short term.
Table 3.1: Research Funding
Table 3.2: Key Research Providers
Not applicable - see section 3.
Not applicable — energy systems analysis requires conventional computing power and good data sets rather than large capital equipment
Table 7.1: Networks
Energy modelling in the UK has no dedicated network. Instead, researchers interact through sector specific or discipline specific networks. UKERC’s NERN network is the major cross discipline information platform. With some researchers not attached to major modelling groups, there is likely to be a number of practitioners getting less interaction with potential collaborators.
Table 8.1: EU Framework Programmes
There is a considerable investment in energy systems analysis and modelling at the EU level. However UK participation in this is lower than that of other countries. One reason for this is the lack of UK access to and use of major European energy modelling tools, including POLES, PRIMES, GEM-E3 and PET-TIMES
Table 9.1: International Activities
Coherence within UK energy modelling and exposure to state-of-the-art modelling techniques and ideas have been greatly facilitated by increasingly good links with international initiatives. This has facilitated increased journal publications and international conference participation.
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