Alastair Buckley is a senior lecturer in the department of physics at the University of Sheffield. His research investigates the integration of solar PV into future energy systems from technological and socio-technical viewpoints. His Sheffield-based research team has developed real-time PV power monitoring for the UK transmission network.
What are the main insights that we aim to achieve through the development of energy systems models?
In the past, the main use of academic and policy-led energy models was to understand the flows of traditional energy resources in the contexts of value for money and security of supply. More recently, the emphasis of academic modelling has been to understand low-carbon energy transitions and, in doing this, the models need to look much further into the future and try and predict how the system will evolve and what consequences such an evolution will have. However I think the real challenge is to understand what “we” we are talking about when we develop models – who are the intended audience and is that audience listening? From an academic point of view, the end goal is typically to get your model used in a policy context. However, policy-makers often typically have already invested in their own models and, as we found as a spiller from our research, in terms of getting used, the language, culture and added value of a model is as important as the technical accuracy or scope.
How do these models help to balance uncertainty in the energy system?
We reviewed a range of academic and policy models of energy systems but, in terms of balancing uncertainty in the energy system, a key interaction is the use of a range of different models by system operators. Short term energy security needs to be negotiated alongside the transition to a more sustainable energy system, so highly accurate and numerical operational models need to be in conversation with future scenario-based models. In the UK, the National Grid “Gone Green” scenario model is a good example of how this is done in practice. “Gone Green” sits at the interface between the system operator National Grid and their day-to-day operational modelling, with policy-led transitional models held by the UK government energy department (now as part of the department for Business, Energy and Industrial Strategy) and academic energy models. It is cited formally and informally across these stakeholders and has a big role in discussions around transitions in the UK energy system.
You recently conducted a review of energy system models in the UK. What were the main findings from this review?
We found that the majority of publications of modelling results came from only a very few different models and that the policy documents cite the same models as the academic literature. This is a good thing, as it means that the academic and policy communities are joined up. From our research I think it’s fair to say that there isn’t the same international travelling of energy systems modelling as in other science and technology fields. The models that we found cited in the UK science and policy literature were mainly home-grown. It would be interesting to do a comprehensive study to see where models have travelled internationally and how this has impacted on energy policy in those countries.
What are some of the limitations of existing energy system modelling tools?
I think one of the major challenges is the integration of qualitative research from the social sciences around scenarios and policy changes. It’s all very well having highly accurate and granular energy flow models for different future generation mix scenarios but if the transition to these scenarios is entirely dependent on political factors at both the EU, national and local level then the model is kind of irrelevant. I think investment in new approaches to the democratisation of modelling with participation from key stakeholders would be very interesting. We have attempted this in a UK-based research project and found computational energy models to be impenetrable by most of these stakeholders.
Based on your review, do you have any recommendations regarding the optimisation of modelling capacity?
I think that opening up all energy based data across the academic, policy and system operator communities would result in a step change in integration of the different modellers. Access to data is a key constraint in modelling and open data sources would allow validation of different models across different scenarios. This, in turn, would result in a wider variety of stakeholders to use a wider variety of models. I think this would be highly beneficial.