A realistic ‘what if’ model
This is the fifth blog in the no resource is 100% reliable series
Catherine Mitchell, IGov Team, 3rd August 2015
No resource is 100% reliable: a realistic ‘what if’ model
This blog series has argued that GB does not currently have a credible energy policy, and that because of this a sensible response is to investigate a no-regrets energy policy based on the global realities of increasing RE investment, changing energy system costs and operation, and the difficulties of nuclear and CCS. Part of that no-regret policy is to better understand the issues of resource variability (Welsch et al 2015): no resource is 100% reliable.
The extent to which GB has thought about a no-regret policy can be gauged to some extent by how much modelling has been done for GB on this topic, and also to find out the degree to which the modelling, which is currently available in GB, has incorporated the costs and new practices of the rapidly changing energy system in other parts of the world.
Models and scenarios are different: the latter envisages particular futures and attempts to input data which enable those different imaginings. Models tend to be used to answer a specific question like how much energy will we use in 2030? What would the system costs be of a 100% RE system? What will the impacts of increasing carbon dioxide emissions be?
Both models and scenarios, however, have to choose inputs and variables, such as the expected price of different energy forms etc.
As a result, energy models and scenarios, to my mind, occupy a particularly sensitive area of energy policy in GB for a number of reasons:
- Outputs from a model, along with economic assessments, which are often very (or entirely) intertwined with a model, are often said by policy makers to be the reasons behind a choice of policy and its details. This may or not be true in practice but, even if policy choices are made for other reasons, models are a central aspect of energy policy making. This leads to multiple models in the GB space, developed by many different stakeholders, often saying very different things.
- Models are only as good as their inputs and variables. It has always been the case that a client can choose a model, or an institution or company can choose variables and parameters, to get the outcome it wants. Because of this, an outsider has to be careful about how they assess and use models.
- For those modellers with integrity, it is very difficult for them to keep the models up to date in this time of rapid, and complex, energy change. If a model is used to inform the policy debate, it may well (however unintentional, and however diligent the modeller is) be using out of date information.
In some senses, it is not that difficult to think about the basic building blocks of a model which investigates the costs, benefits and needs of a no-regrets policy. What is difficult is getting those building blocks right (eg how much wind power is ‘right’ in GB in 2030). The building blocks are:
- a high penetration renewable energy system – apart from the semantics of how to measure it – and this requires renewables and one needs to know what the output and variability of that system could be.
- energy efficiency to achieve as small a system size as possible (ie so need to know how low demand could be).
- to have as flat a demand curve as possible to reduce capacity needs as much as possible, so a sophisticated demand response sector (and we need to know what that resource is / could be in GB).
- to be able to flex the system through interconnectors, storage, new ways to enable flexible technical characteristics (and we need to know what those capabilities and resources are/could be), (probably) some fossil resource for a few hours here and there to manage the longer term aspects of variable renewables.
- governance to get there.
There is increasing experience (see here and here) of managing an energy system with a high penetration of renewables; the sort of policies which lead to their deployment; the sort of policies which leads to reduced total energy use. But more than this, it is (1) the supply costs of certain technologies which are changing, and what that means for the economics of energy, (2) how new technologies are enabling integration within the system, and what this means for different services (and their costs) that can be provided (and the implications of this for interactions with customers, business models and so on); the changes in the way systems are being operated and managed, and the impacts on system costs and resource use; (3) the way society and individuals are prepared (or not) to accept certain technologies and interactions with energy; and (4) the way social innovation is changing ownership, non traditional business models, markets and aspirations. All these have impacts on total energy used, what sort of energy is used, its costs and so on.
Incorporating inputs which reflect the speed, and dimensions of change is difficult, even if building a new model, much less trying to incorporate it into an older one. Furthermore, some of these changes have reached GB (ie falling solar costs) whilst other changes have not (ie new operational mechanisms). This means that the modeller has to decide whether to consider adding inputs which might be the norm in Germany but which don’t exist particularly in Britain (ie coops and expected rates of return (low).
In some ways one can argue that ‘old’ energy systems are based on providing electricity capacity from power plants, gas from pipelines and oil from wherever to meet demand. A ‘new’ energy system might be argued to be one which is more active in its sculpting of demand and more concerned with efficient integration of available resources between sectors – whether from a power plant, or an interconnector, storage or via flexibility characteristics. Models and scenarios will need to incorporate this ‘new’ way to better predict the future.
There is a plethora of modelling and scenarios, from academia, large multi-nationals like Shell & BP, the IEA, government and wider actors like the CCC and National Grid. They show a huge range of plausible outcomes for future energy use, rather than a simple or clear answer and they reflect the assumptions and biases of those that produced them (Evans 2014) and IEF . A review from UKERC shows that because different assumptions are taken, on a range of variables such as cost, technology development etc, it can be hard to draw robust conclusions (Ekins et al 2013). Hence, the linking of models to everyday energy problems can be lacking.
With respect to finding models which have looked at a no regrets policy or a high penetration of renewables or what levels of flexibility there are in Britain – there is very little obviously available. Certain academics like Goran Strbac have looked at different sections of this in detail. The CCC commissioned work by Powry in 2010 to establish whether differing amounts of renewable energy would lead to an unreliable and expensive energy system, or not. This still remains probably the most useful analysis out there – and one that really needs to be updated to take account of the almost totally different costs of technologies, business models, ownership, social preferences and so on. Sustainability First has used a model to assess the potential of demand side response a winter evening in GB at 4-7 pm (18GW) and this is an incredibly useful number to have – given it is one of the four resource types that can be called on in times of low renewables provision. WWF has a (now oldish) model (Positive Energy) to illuminate the link between policies and different penetrations of renewables (one of which provides nearly 90% of energy in GB; CAT has produced a model for all sectors, looking at how we can reach a low carbon Britain; RTP Engine Room, 2014 has a Distributing Power Scenario, which has high amounts of distributed energy, including large amounts of biomass. Most of these will be based on now out of date information.
Most stakeholders in the GB energy system either have their own, or have access to, modelling capabilities but the paucity of work related to ‘progressive’ or ‘no-regret’ energy policy may be because GB Government energy policies are so conservative, with a small c. Not only has there not been much change in terms of GB supply technology use, but as a result of this, there has also been limited change in system operation and other practice change.
Inputs often relate to the type of policies (and their goals) in place in GB at the moment. The FES works on a combination of reality (because it knows how much wind energy is in the pipeline etc) combined with Government policies and goals, for example, for nuclear or CCS. The same goes for ETI’s latest scenarios and the Deep Decarbonisation Pathways Project (here and here) looking at different technological pathways within a 2 degree temperature rise. This is not to knock those models / scenarios. Nevertheless, the situation arises if those policies for various technologies are not working – ie nuclear or CCS is not available to the degree the model says – and the models and scenarios are based on them being available, then they are only helpful up to a point.
All of us in the energy world, whether academics, regulators, Government, businesses, local authorities, consumers and so on, are all trying to make sense of the rapid societal (and energy) changes we see unfolding in front of us. Models (and their modellers) can help to make sense of that changing world for us non-modellers, particularly if they have worked out how they themselves can create models to reflect the rapidly changing energy world.
Although it is hard for any model to keep up to date, it is also important that GB has modelling and scenario capability to reflect ‘what if’ situations – particularly if in this instance it actually looks like the ‘what if’ situation is the realistic situation: ie what should Britain do / need if:
- we can expect 0/1/2 nuclear power plants to built by 2030,
- CCS is not available for industry at all before 2025, and then for only small incremental levels thereafter and not for power plants;
- fracking is widely unpopular and produces minimal output;
- solar continues to be the technology of choice for households
- non traditional business models (including local authority energy companies) continue to develop rapidly
- demands for local tariffs and local energy markets also increase rapidly.
This is the kind of information I want but I also think it is the kind of information the Minister and Regulator should be getting.
No resource is 100% reliable series:
- Blog 1: A No-Regret Energy Policy: Reduce, flatten and flex
- Blog 2: The Belgian nuclear winter
- Blog 3: US polar vortex and energy
- Blog 4: A 100% renewable energy system operation on no wind, no sun days
- Blog 5: This blog
« Previous No resource is 100% reliable: a 100% renewable energy system operation on no wind, no sun days No Resource is 100% Reliable: Embracing change and capturing opportunities of the ‘new’ energy system requires a new mind set Next »