IEEE Power & Energy Magazine - May/June 2020 - 32

table 4. A comparison of the different levels of certainty in network access required by customers.
Certainty in Customer
Network Access
Requirements

Network Access Offered
by Network Operators

High
Low

Network Activity

User System Charges

Rate of Return to
Distribution Owner

Firm

Traditional asset
investment

High

Low

Intermittent

Short-run flexible
operation

Low

High

One approach to managing uncertainty could be by offering flexible network access, recognizing that future distribution network operators would have two core businesses:
traditional long-term network investment and short-term
flexible operation that mobilize inherent resources at the
customer and network levels to manage uncertainties. For
the latter, it is important to understand that resources have
finite capacity over limited time periods; therefore, network
operators could be rewarded if they are willing to take risks
and develop greater capability in understanding and mitigating uncertainties through short-term operational intelligence, thus minimizing investments in new assets.
As more customers opt for less-expensive intermittent network access, there could be less of a need for customers to
request firm capacity, and the cost of accessing firm capacity to
serve fewer customers would become excessively expensive. In
such a situation, local energy provisions may become competitive when compared to their distant counterparts. This pricing
framework would drive an efficient future-proof network over
time, which would have less network investment and rely more
on network operations that reduce congestion and uncertainties.
Such networks would provide the capacity to deal with shortterm uncertainties rather than a network dominated by longerterm plans for network asset additions; however, regulators
would need to consider social justice issues arising from users
requiring set electrical service, such as the elderly, the disabled,
and caregivers.

Summary
The degree of sophistication in network pricing has improved
dramatically in the last 30 years, moving away from pure
cost allocation to cost-reflective pricing, indicating both the
-characteristics of the network and its users to improve overall
network utilization. Decarbonization and digitalization have
fundamentally changed the energy landscape and created
major uncertainties in customer demand and network use as
well as the future outlook. These changes challenge the present
principles and charging methodologies of electric rates, which
do not adequately consider uncertainties in network customer
use. Many types of regulatory regimes can address this issue.
In this article, we quantified the diversity in network and
customer uncertainty, identified opportunities for mitigating uncertainty through sharing network use and customer
demand response and generator assets, and proposed future
directions for network pricing that offer flexible network
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ieee power & energy magazine

access to mitigate uncertainties. In doing so, the risk of
making mistakes in costly investment can be substantially
reduced, and network operators can be rewarded for their
improved ability to mitigate uncertainties.

For Further Reading
"Digest of United Kingdom Energy Statistics (DUKES)
2016: Main chapters and annexes," Department for Business,
Energy and Industrial Strategy, U.K. Government, London,
Sept. 9, 2016. [Online]. Available: https://www.gov.uk/
government/statistics/digest-of-united-kingdom-energy
-statistics-dukes-2016-main-chapters-and-annexes
F. Li et al., "Distribution pricing: Are we ready for the
smart grid?," IEEE Power Energy Mag., vol. 13, no. 4, pp.
76-86, July 2015. doi: 10.1109/MPE.2015.2416112.
"Structure of electricity distribution charges: Consultation on the longer term charging framework," Ofgem, 2005.
[Online]. Available: https://www.ofgem.gov.uk/publications
-and-updates/structure-electricity-distribution-charges
-consultation-longer-term-charging-framework
F. Li and D. L. Tolley, "Long-run incremental cost pricing
based on unused capacity," IEEE Trans. Power Syst., vol. 22,
no. 4, pp. 1683-1689, 2007. doi: 10.1109/TPWRS.2007.908469.
F. Li, D. Tolley, N. P. Padhy, and J. Wang, "Framework
for assessing the economic efficiencies of long-run network
pricing models," IEEE Trans. Power Syst., vol. 24, no. 4, pp.
1641-1648, 2009. doi: 10.1109/TPWRS.2009.2030283.
"Delivering the electricity distribution structure of charges project," Ofgem, 2008. [Online]. Available: https://www
.ofgem.gov.uk/publications-and-updates/delivering-electricity
-distribution-structure-charges-project
"Project TransmiT," Ofgem, 2011. [Online]. Available:
https://www.ofgem.gov.uk/electricity/transmission-networks/
charging/project-transmit
"Charging futures forum," Ofgem, 2017. [Online]. Available: https://www.ofgem.gov.uk/publications-and-updates/
charging-futures-forum

Biographies
Furong Li is with the University of Bath, United Kingdom.
Chenghong Gu is with the University of Bath, United
Kingdom.
Ran Li is with the University of Bath, United Kingdom.

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