Deepmind algorithms to manage
the Grid could be just the start of a consumer focused revolution in the power
sector. The need to manage much more complex low carbon systems means there are
strong incentives to manage consumer demand more pro-actively. This could be
good news for consumers, offering them more choice, and also defusing some of
the concerns that sit around supply security.
Yesterday’s FT reports[1]: Google’s DeepMind is in discussions with the UK’s National Grid to use
artificial intelligence to help balance energy supply and demand in Britain. “… It would be amazing if you could save 10
per cent of the country’s energy usage without any new infrastructure, just
from optimisation. That’s pretty exciting,” Demis Hassabis, DeepMind’s chief
executive told the Financial Times. National Grid’s role in balancing the
system has become more difficult in recent years, however, as intermittent
renewable sources of electricity — such as wind and solar power — have become a
bigger part of Britain's energy mix. DeepMind’s algorithms could more
accurately predict demand patterns and help balance the national energy system
more efficiently.
This is currently a task that
is at least partially delegated to the market. The principle behind most “spot”
wholesale markets is that generators declare their marginal costs of generating
(per kWh unit of energy produced) and are then selected to run in ascending
order of cost (the so-called “merit order”), with the cheapest chosen first,
and the most expensive plant that runs setting the price. That principle will be
increasingly dysfunctional or inapplicable in the real world, partly because such
a high proportion of current and future generating plant has zero or negative
marginal costs of operation, and partly because the operational efficiency constraints
on the power system are becoming more complex, involving considerations of
plant inflexibility, intermittency, and energy storage, rather than just a simple
stacking by ascending cost. Sophisticated algorithms are prima facie exactly what
is needed to replace a defunct merit order.
This implies moving beyond
prediction of demand patterns, for which fairly sophisticated approaches
already exist, and addressing predictions of intermittent supply as well. It
also means developing algorithms to make operational decisions that make sense
in terms of efficiency and the secure operation of the system. The promise of a
10% saving in energy may be an exaggeration, not least because of
the dominance of capital costs, and relative insignificance of fuel, in low
carbon generation. But the bigger contribution of an algorithmic approach lies
in the broader options it creates for the ways that the power system is managed
and the ways in which consumption is managed. This could allow leaner systems and also transform the way that
we think about electricity as a service.
Future Options
The conventional utility model
has consumers able to treat electrical energy supply as “on tap”, with limited
or no differentiation between applications (e.g. as between lighting, heating
or mechanical power). Tariffs and prices for the most part approximate to an
averaging of the costs of supplying electricity, with limited ability to
differentiate on grounds of differing incremental costs, and a common security standard
for all consumers and all applications.
Consumer behaviour needs to be
incorporated as a much more active component.
What is needed is to redefine the “consumer offering”, with electricity
as a set of services, rather than a homogeneous commodity. This requires
starting with a clean sheet in defining the nature of the services that
consumers will want, and the basis on which they pay. So, to take a particularly dramatic example,
a consumer wanting to charge electric vehicle batteries might request 75 kWh to
be delivered in a specified period, over several hours or even several days (eg
a weekend), and the consumer’s terms of supply might specify that this
requirement will be met in full but with timing that is “at the supplier’s
discretion”. Different arrangements and
different tariffs could apply to the purchase of power for heat, and for some
other uses, reflecting in each case the nature of the load, the extent to which
it could be time-shifted without inconvenience, and the level of reliability for
which the consumer was willing to pay. Commitments
to individual consumers would be made by energy service companies who would be
able to aggregate consumer requests and feed them in to become part of the Grid’s
system optimization routines. Such services might even be packaged with the
provision of appropriate equipment (eg storage heaters).
The role of suppliers is then
to act as aggregators, and their essential function would be to manage the
complex interaction between consumer loads and system balancing requirements,
including shaping and managing the pattern of consumption. This provides a major
opportunity for a much more innovative approach to all aspects of metering and
for the terms on which consumers purchase power. Suppliers could at the same
time enter into individual contracts with generators, or a system operator or other
agency, which would reflect the economic benefits of their ability to shape
consumer loads. They would also take responsibility for managing loads within
network constraints at lower voltages, ie within local distribution networks.
This has some powerful
advantages. First it allows consumers to
purchase power for particular usages in ways more akin to their purchase of other
goods and services, as opposed to perpetuating the “instantaneous commodity”
characteristics that have hitherto been a unique and constraining feature of
the power sector. This can reflect what consumers actually want and need from a
utility. At the same time it would help make
the services more affordable. Consumers
could still choose to take some power “on tap” and would normally pay a higher
price for this.[2]
Many of the issues associated with administrative setting of security standards
would become much less significant. Security standards would be chosen in a
market, not dictated by a central authority.[3]
This change is enabled by one
set of technologies – those that surround metering, remote control, and system
optimisation (Deepmind). But it also
helps to resolve the problems posed by another set of technologies, those
linked to intermittent or inflexible sources of non-fossil generation and
distributed generation.
………..
These ideas have also been explored
by the author in Double standards for reliability in power supplies. Not
such a bad idea. This was a defence of a controversial proposal
from Andrew Wright of OFGEM on a proposal for consumers to choose the level of
reliability that they want. They have been presented in a broader context in a
paper, Markets, policy and regulation
in a low carbon future, produced by the author for the Energy Technologies Institute
(ETI), which published a number of perspectives on low
carbon futures in 2016.
[2]
“Electricity Markets and Pricing for the Distributed Generation Era”, John
Rhys, Malcolm Keay and David Robinson. Published as Chapter 8 in Distributed Generation and its Implications
for the Utility Industry, ed. F.
Sioshansi, Elsevier, August 2014.
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