IEEE Power & Energy Magazine - May/June 2020 - 29

to receive at least a £5-6 billion investment between 2010
and 2015. Recognizing that flat-rate charging posed a major
barrier to the cost-effective integration of renewables, in
2015, Ofgem called for a major reform in the long-term
charging structure to provide greater incentives to minimize
distribution network development costs from low-carbon
resources. In 2006, long-run incremental cost (LRIC) pricing, the first locational pricing methodology for the distribution system, was developed (see Li and Tolley in the "For
Further Reading" section). Its impact assessment indicated
that a cost savings of £200 million could be achieved over
the next 20 years for electricity consumers if the industry
moved to locational pricing (see Li et al. in the "For Further
Reading" section). By 2007, Western Power Distribution,
the United Kingdom's largest distribution network operator, had implemented LRIC pricing to its extra high-voltage (EHV) distribution system (from 132 down to 33 kV)
throughout its two distribution areas operated in Southwest
and South Wales. By 2011, all 14 distribution areas across
Great Britain had adopted locational network pricing for
their HV distribution areas.
The subsequent reform of the transmission system in
2013 demonstrated the U.K.'s continued efforts to refine
network charges that address new challenges introduced by
decarbonization and differentiating generation technologies,
including their impacts on long-term network investment.
Because transmission and distribution networks have traditionally displayed inherently different characteristics, their
reforms followed different developmental pathways prior
to 2017. In 2017, however, Ofgem set up the Future Charging Forum to perform overall coordination and integration
of network charges across the transmission and distribution
networks, given the rapid changes in Great Britain's energy
systems introduced by decarbonization and digitalization. In
particular, system changes included the growth of distribution
operations, new energy resources (including both generation
and demand) at all levels of the distribution system, two-way
interactions, and indistinct boundaries between the transmission and distribution systems. In addition, decarbonization and digitalization also created major uncertainties in the
long-term outlook of the energy system. This fundamentally
challenged traditional charging principles and methodologies,
which reflected deterministic network planning with a certain
future outlook.
An enduring network pricing principle should properly
account for long-term uncertainty in the energy landscape
and thus be able to minimize the risk of under and over network investment. In particular, it should answer the following questions:
1)	 What would be the impact on long-term investment
from customers with different uncertainties?
2)	 How might these uncertainties propagate through the
distribution and transmission system?
3)	 How could these uncertainties be managed or reduced
by network operators and network customers?
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4)	 What would be the effect on long-term investment as
well as the use of system charges if uncertainty management strategies were put in place?

Opportunities to Reduce Uncertainties
The large-scale penetration of low-carbon technologies and
flexible demand will bring unprecedented uncertainties to
distribution network planning. Reducing uncertainty is key to
reducing costly mistakes in network asset investments. Characterizing and quantifying these uncertainties across customer
and network levels can provide opportunities for reducing
and managing future uncertainties. Against an increasingly
uncertain future, network users should provide estimated certainty of their future network access needs, which can reduce
the risk of investment mistakes and alleviate the burden to
network operators of forecasting the state of the system.
Network operators who understand the system would recognize differences in use by various customers over a range
of periods and identify opportunities for capacity sharing of
the existing network, which would improve network utilization and minimize new network investments. This would be
particularly beneficial to renewable generation and flexible
demand, as they do not require full network capacity all of
the time. Through a well-designed sharing system, the existing network could result in a substantial increase in network
utilization and thus serve a far greater volume of customers
than it does today. This would, in turn, lead to significantly
reduced network costs.

Uncertainties Across Customer Types
The degree of energy uncertainty differs among customers due to their various lifestyles or nature of businesses
and reflects: 1) temporal uncertainties, the time when
peak demand occurs, and 2) magnitude uncertainties, the
predictability of the demand. This will have an direct
impact on the uncertainty of network peak demand, which
will directly affect network capacity investment and thus
should be a key driver to be factored in network charges.
Uncertainties can be further studied across different customer types in terms of their tariff regime and net demand
characteristics [such as owners of electric vehicles (EVs) or
photovoltaics (PVs)].
Figure 1 shows the temporal distributions of the daily peak
for four groups of residential consumers. R1 and R2 consumers share a similar pattern, with consistent evening peaks from
4 to 10 p.m. For groups R3 and R4, the load peaks are randomly distributed throughout the day, which suggests uncertainties associated with PVs and EVs. The uncertainty of R3
consumers could be due to the intermittency of renewable
energy, while that of R4 consumers could be from variations
in charging locations and times.
Figure 2 shows the temporal distributions of daily peak
occurrence for the small- and medium-sized enterprise
(SME) consumers, which appear different from residential
customers. Most of the peaks consistently occur between
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IEEE Power & Energy Magazine - May/June 2020

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