2.2.5 Operational assumptions

2.2.5 Operational assumptions Bruno Prior Mon, 14/12/2020 - 22:34
  1. We provide defaults for the existing installed capacity and availability factors. These are based on figures from around the turn of 2018/19, when we were developing this model. In some cases (wind and solar), these figures are materially out of date. They can be adjusted by the modeller. We have chosen not to modify the defaults to the current position because to some extent they are aligned to the hourly seed data, although this is not a major factor as the seed data is used for the profile, not for absolute figures. The model is primarily about the future, so most of these values will be taking fresh inputs anyway, so the starting point is not significant, except that the base case for comparison will be roughly 2016-18, not 2020.
  2. The current reported capacities of the UK’s five interconnectors (one of them internal, to Northern Ireland) are given as the defaults, but can be modified to model increased interconnection capacity. We do not attempt to model the costs of interconnection. We do not have good data, and the national share of the costs would depend on the balance of import and export, which may vary depending on model assumptions. They arguably lie outside our system boundaries, although if an interconnector were built mainly to satisfy the UK’s needs, we should take account of that cost within overall system costs.
  3. The only aspect of transport fuel consumption that the model currently attempts to estimate on an hourly basis is that component that is electrified, in order to contribute to the overall electricity figures. It is in the nature of most forms of transport that there is no regular metering of usage, so granular data are not available. Longer-frequency estimates suggest a fairly predictable rhythm to road usage. We estimate hourly usage on the basis of reasonable and simple rules-of-thumb, e.g. usage is higher during the week than at weekend, highest around the rush hours, and marginally higher in summer than winter, but that this will be combined in the case of electric transport with choices to charge off-peak as far as possible.
    • The annual usage of fossil fuels and electricity are inputs with defaults based on current usage. They are allocated to hourly periods on the above basis.
    • An important constraint is that the model recognises the significant differences in on-vehicle conversion efficiency between Internal Combustion Engines (ICE) and electric motors, and tries to ensure that an adjustment to one is balanced by an equivalent adjustment to the other, such that the total post-conversion energy is not altered by a change to one component, though that total can be adjusted by the modeller. For example, given that electric motors are assumed by default to be 3.4 times more efficient than ICE on average, if we increase electricity’s share of road transport by 1 TWh, we reduce the non-electric component by 3.4 TWh and the total by 2.4 TWh. These default efficiency assumptions can also be varied by the modeller. The default efficiency for electric vehicles may look relatively low to proponents of the technology, but this is intended to reflect not only the efficiency in motion, but also inefficiencies in the charging process. We believe this is more realistic than the utopian figures sometimes used for electric-vehicle efficiency, but the modeller can apply their own assumptions. We have also seen lower efficiencies used by electric-vehicle sceptics.
    • Another important assumption in the model is that users have some but not unlimited ability to choose to charge their electric vehicles when other electricity demands are low and prices are then presumably also low, and conversely avoid charging during peak demand periods. In other words, we assume that electric vehicles will provide a significant degree of demand smoothing to help with balancing, but that this will be largely preset according to behavioural patterns and expectations, and not responsive to unexpected system pressures outside expected patterns.
    • There is a lot of talk of using vehicle batteries for electricity-system demand responsiveness. It seems to us that, whereas this might be true on the crude basis described above, it is fanciful on a more directed, on-demand basis. For example, few people will choose not to charge their car overnight so that they are unable to go to work the next day, no matter how much the system might need them to. This would have to be imposed against their will, and would be political suicide for any government attempting to instigate the capability. It is not inconceivable in this world of overmighty bureaucracies and misanthropic advisers, but we choose to assume a more benign, if less exactly-managed, world.