Rajiv Venkatraman explains how disruption in the retail electricity market has created a need to solve technological, economic and political challenges, as well as the ability to grasp opportunities.
4. 1. Price regulation
Government controls how much
customers are charged
2. Government ownership
Government influences the market
by controlling electricity assets
3. Public/stakeholder consultation
The way government works with
customers to help them understand
how they are charged in the retail
electricity sector
5. Influence of government: examples3
LEVER
EXAMPLE
Price Regulation
Government
Ownership &
Market Share
Public and
Stakeholder
Consultation
RESULT
France
Active price
regulation (mainly
households).
Part state-owned
utilities - own most
power infrastructure.
Public outreach
efforts present but
few options available.
Satisfaction levels are
high compared to the
EU average.
Heavily regulated market
with slow innovation albeit
now starting to liberalise
after pressure from the EU.
Australia
Retailers can set
prices within
moderate
regulations.
Minimal state
ownership but
regulator has strong
influence on retailers.
Online tools allow
public to compare
prices but are difficult
to use.
Moderately regulated
market but unattractive
to new entrants and
dominated by vertically
integrated incumbents.
Texas
(USA)
No default supplier
forcing customers to
go to market.
State only provides
oversight.
Price to beat tariff
used to encourage
competition.
Proactive public
information
campaigns raise
awareness.
Singular data hub
allows efficient
switching.
An innovative market with
high customer awareness
and attractive to new
entrants.
Using the examples of three countries – you can see how they lead to different market scenarios
7. This can be framed by examining
the scale of disruption from an
individual household level to a
large city or country
8. Future sources of disruption
Households
Local
Communities
Large Urban Areas
(e.g. cities)
Peer-to-peer energy trading1
• Consumers trade excess energy
generation with one another
• Artificial intelligence helps match
load to generation
Microgrids and machine-to-machine
communication1
• Community batteries/energy generation
systems allow areas to go off grid
• Parts of a network communicate with one
another to ensure efficient energy usage
Shift from ‘consumer’ to ‘prosumer’1
• Use renewable technology (e.g. solar panels to
generate own renewable energy)
• Utilise batteries to store unused energy for later
• Using energy management systems allow efficient
energy consumption
NOTE: Heavy industries differ due to complex loads/requirements (e.g. heat, steam).
Co-generation and renewable energy generation/storage are options to go off grid1.
9. How does this effect decision-making
for the energy retail market?
10. A high-level visualisation
Actively plan for
long-term adoption.
Disregard adoption
unless requirement
is overwhelming.
Immediately
capitalise on the
opportunity and
adopt the
technology.
Consider adoption
in the long-term
while ensuring
flexibility to
legislative changes.
Uncertainty/complexity of legislation
Difficultyoftechnologyadoption
Decision-making from both a legislation and
technological perspective can be visualised
as a decision matrix.
Other considerations
• Safety
• Support to maintain and control systems
• Quality of power provided
• Robustness
• Simplicity
• Load profile and system inertia
12. Case study: Mallacoota
The isolated, south-east Australian town of
Mallacoota needed alternative power sources
as their sole source of electricity was affected
by bushfire, floods and wildlife/trees4.
Options:
Solar PV, biogas and battery storage to go
off grid5.
Barriers4:
• Access issues to provide support services
• Quality of power provided
• Difficulty to achieve economies of scale
due to population ≈ 1000
13. Case study: Remote West Australian communities
Remote West Australian communities trialled solar
and battery storage to avoid power outages and
were supported by the local utility provider
(Western Power) which sought alternatives to
replacing poles and wires6.
Options:
Solar and battery storage and early trials indicated
big promises
Barriers:
• Legislation prevented the utility from
generating energy which applied to the
trial and prevented its expansion
• Lack of government direction caused
the trial to be extended by three years
in hope of future legislation changes
14. Case study: Peer-to-peer energy trading platform
Origin Energy partnered with Perth start-up Power
Ledger to trial peer-to-peer energy trading
platform with historical consumer data7.
Options:
Technology lets consumers trade with one another
self-generated energy, removing the ‘middle men’
(retailers).
Technology is applied mostly in commercial trials.
Barriers:
Wide-spread usage was hindered by the
Australian Energy Markets Commission
who ruled against making network tariffs
flexible8.
15. How does this impact our
retail electricity markets?
16. • A gradual overhaul of pricing models
and an uncertain regulatory landscape
impacts how retailers envision their
future energy transition
• New tech start-ups are starting to
challenge incumbents but have limited
commercial success for the moment
• Incumbents are trying to define their
place in the market amid disruptive
technologies and examine new business
models
17. Threats
• Disruption has created a demand
to solve new problems requiring a
holistic understanding of technology,
economics and politics
• Traditional businesses (i.e. existing
utilities) are being challenged by
new tech start-ups
Opportunities
• Opportunities to work with a new
generation of retailers looking to scale
and enter the broader market
• A chance for industry to support
governments in crafting legislation that
supports an innovative and sustainable
electricity network
18. DISCLAIMER
This presentation has been prepared by a representative of Advisian.
The presentation contains the professional and personal opinions of the presenter, which are given in good faith. As such, opinions presented herein may not always necessarily reflect the position of
Advisian as a whole, its officers or executive.
Any forward-looking statements included in this presentation will involve subjective judgment and analysis and are subject to uncertainties, risks and contingencies—many of which are outside the
control of, and may be unknown to, Advisian.
Advisian and all associated entities and representatives make no representation or warranty as to the accuracy, reliability or completeness of information in this document and do not take responsibility
for updating any information or correcting any error or omission that may become apparent after this document has been issued.
To the extent permitted by law, Advisian and its officers, employees, related bodies and agents disclaim all liability—direct, indirect or consequential (and whether or not arising out of the negligence,
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information.
FOR MORE INFORMATION CONTACT:
Rajiv Venkatraman | Consultant
P: +61 410 167 552
E: Rajiv.Venkatraman@advisian.com
THEN SHOW DETAILED TABLE:
We can see how these levers operate using the examples of 3 different countries (France, Australia and Texas) to see how they lead to different market scenarios and understand how Australia fits in the global context i.e. see that Australia sits somewhere in the middle between extreme regulation and relaxed regulation
Now I’ve showcased a theoretical matrix with different scenarios that can result, next lets apply it to some case studies to see it in action
While the difficulties involved put it in the top right: Origin-Power Ledger partnership is attempting to push to the left by using the trial to give the regulator confidence in the technology who would be more inclined to relax regulations in this area
Peer to peer energy trading platform:
FRAMING: Origin Energy and Perth start up Power Ledger announced partnership to trial their software, success would mean consumers can trade energy with one another
TECHNOLOGY: The required technology had not been used on a large scale and mostly limited to small scale trials
GOVERNMENT: The governing regulator (Australian Energy Markets Commission) put an obstacle to any roll out of the technology by preventing networks tariffs to be more flexible
RESULT
Therefore: should be top right of matrix (But the partnership’s purpose was to give government confidence and make them conducive to relaxing regulations and reducing uncertainty). That’s why I have the arrows to show pushing to the left (BUT: I think remove the arrows as it might be unecessary since I can’t speak to them anyway)