An analysis of ’D3’ in DECC’s energy system models
In response to CSE expertise in both software engineering and policy analysis, the then Department for Energy and Climate Change (DECC) engaged us to review its approach to understanding ‘D3’, the family of technologies and interventions which affect the use and production of energy on the demand side of the system. This included demand reduction, demand response, and distributed energy.
These are interventions whose effects are meeting demands themselves (e.g. by reducing the energy required to deliver the service) or changes which move energy around near the ends of the distribution network, through microgeneration, distributed storage and so on.
‘Demand reduction’ measures are those which reduce overall demand, either by increasing efficiency (e.g. through insulation or better heating controls) or by reducing the desire for ‘useful work’ (e.g. a campaign to persuades people to wear an extra jumper and turn down their thermostat).
‘Demand-side response’ (DSR) technologies are those which allow the supply side to automatically control demand in some way, such as with real-time electricity pricing, or by providing ‘demand destruction’ to the grid as an option for meeting supply (sometimes referred to as negawatts). Demand response is typically thought of as a mechanism for reducing peak loads by moving some of the peak to times of day when demand is lower. Consequently it may not reduce overall energy demand, but instead affects the peak power demand.
‘Distributed energy’ encompasses technologies which produce heat or electrical power near the end of the distribution network, and energy storage systems which can balance loads at a similarly local scale. Examples include solar energy, heat storage etc.
The research involved face to face interviews with analysts from DECC, along with source-code reviews of a number of computer models. Between them they provided a fascinating insight into the way in which the department models the energy system and its policy interventions.
CSE’s Head of Research & Analysis, Josh Thumim, said “We found that DECC uses a large number of models to represent different aspects of the energy system, and the effects of different policies. These models are in general well designed for their original purposes; however the complex interactions which characterise some D3 interventions (think district heating, embedded power generation, time-of-use tariffs) are inherently difficult to model, and are likely to require new approaches.”
Our report has added to DECC’s understanding of the suite of models it uses and the ways in which they currently interact. It has also highlighted some opportunities for improving its management of models in general, and its representation of D3 interventions in particular.
Josh continued: “This work, which demonstrates CSE’s expertise in both software engineering and policy analysis, will support DECC as it continues to improve and develop its modelling in the critical processes of policy development and evaluation
“Our recommendations include proposals for integrating certain existing models to extend their functionality, for developing new models where we identified gaps, and for increasing the systematic management of the population of models in use at DECC.”
The report presents a picture of the following:
- What challenges D3 poses for energy modelling
- How DECC’s models represent D3
- How the models are connected together
- How the models are already used to consider D3 questions
- Where the models may fail to capture D3 costs or benefits, either because of the way they are used, or due to fundamental limitations in the design
- What DECC could do to improve their models or use of models in the analysis of demand side policy and D3.
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