Conference PaperPDF Available

Sharing Benefits in Community Embedded Networks with Renewable Energy

Abstract and Figures

The shift to low-emissions energy production has gained significant traction in Australia and around the world. Community Renewable Energy (CORE) projects are on the rise, reflecting the desire of communities to take control of their own energy goals, and embedded networks (ENs) are emerging as part of the CORE movement. An EN is operated by an EN operator (ENO), who can purchase electricity at the parent point and on-sell it to customers within the EN. This provides the opportunity for innovative internal electricity tariff structures to be designed that can help meet community goals such as increased local renewable energy and improved equity impacts. This study aims to understand the implications of Community EN arrangements and tariff design for the financial, environmental and social outcomes of those connected to the EN. An energy sharing EN model is used to simulate financial outcomes for participants and the ENO in a Community EN of 60 households as a function of:-EN PV penetration, and-internal retail tariff structure. It was found that with the appropriate internal settings all solar and non-solar customers could save an average of approximately $200 at all levels of PV penetration. However, arrangements with PV penetrations above approximately 50% were not viable as the ENO lost profitability since EN loads could be fully met by internal solar generation. These results indicate that there may be some conflicts between Community EN financial, renewable and equity goals. While achieving all goals simultaneously can be difficult, it is apparent that the 'Community EN with energy sharing' model is a credible option in the CORE space to help meet community goals, and careful internal design can help ensure that the desired goals are prioritised. In addition, both non-solar and solar customers are able to benefit through a scheme such as that explored here, addressing a key inequity in the energy industry.
Content may be subject to copyright.
Asia Pacific Solar Research Conference, Sydney, December 4-6 2018
Emily Banks
Sharing Benefits in Community Embedded Networks with Renewable Energy
Emily Banks1, Anna Bruce1,2 and Rob Passey1,2
1School of Photovoltaics and Renewable Energy Engineering, UNSW, Sydney, Australia
2Centre for Energy and Environmental Markets, UNSW, Sydney, Australia
E-mail: emilybanks7669@gmail.com
1. Abstract
The shift to low-emissions energy production has gained significant traction in Australia and around
the world. Community Renewable Energy (CORE) projects are on the rise, reflecting the desire of
communities to take control of their own energy goals, and embedded networks (ENs) are
emerging as part of the CORE movement.
An EN is operated by an EN operator (ENO), who can purchase electricity at the parent point and
on-sell it to customers within the EN. This provides the opportunity for innovative internal electricity
tariff structures to be designed that can help meet community goals such as increased local
renewable energy and improved equity impacts.
This study aims to understand the implications of Community EN arrangements and tariff design
for the financial, environmental and social outcomes of those connected to the EN. An energy
sharing EN model is used to simulate financial outcomes for participants and the ENO in a
Community EN of 60 households as a function of:
- EN PV penetration, and
- internal retail tariff structure
It was found that with the appropriate internal settings all solar and non-solar customers could save
an average of approximately $200 at all levels of PV penetration. However, arrangements with PV
penetrations above approximately 50% were not viable as the ENO lost profitability since EN loads
could be fully met by internal solar generation.
These results indicate that there may be some conflicts between Community EN financial,
renewable and equity goals. While achieving all goals simultaneously can be difficult, it is apparent
that the ‘Community EN with energy sharing’ model is a credible option in the CORE space to help
meet community goals, and careful internal design can help ensure that the desired goals are
prioritised. In addition, both non-solar and solar customers are able to benefit through a scheme
such as that explored here, addressing a key inequity in the energy industry.
2. Introduction
“Community Renewable Energy is an approach to renewable energy development that involves the
community in initiating, developing, operating, owning and/or benefiting from the project”
(Community Power Agency, 2015). CORE initiatives are acknowledged as important contributors in
the transition to a low-emissions energy market (Bauwens, 2016). They draw on the power of
communities coming together to make a change, and by their very nature should serve the public
interest as community participation is essential for successful deployment.
Asia Pacific Solar Research Conference, Sydney, December 4-6 2018
Embedded networks are private electricity networks which serve multiple customers and are
connected to another distribution or transmission system in the national grid through a parent
connection point(AEMC, 2015). Figure 1 provides a visualisation of an EN arrangement.
Figure 1. EN visualisation
They are generally operated by ENOs, which can purchase electricity and network services from
the grid at the parent connection point and then sell this on to customers within the EN. Due to the
aggregation of loads behind the parent meter, the load at the parent meter is likely to be large
enough to be on a commercial tariff, which would have a lower usage charge than standard
residential retail tariffs, and therefore costs passed onto customers within the EN can be lower than
for a standard retail market customer (Bowyer, 2015).
“Community ENs” can be defined broadly as ENs that are owned by and/or provide benefits to the
community of households connected to them. If there are renewables behind the parent meter,
which is a common motivation for a community energy project, particularly with falling costs of
distributed PV, they can therefore be classed as a subset of CORE and be used to facilitate CORE
initiatives. Given that the ENO can set the tariff rate they pass on, there is an opportunity for
innovative tariff structures to be designed to meet the goals of the community (Bowyer, 2015).
2.1. Motivations behind the CORE movement
There are many reasons for communities or parties within a community to engage in CORE
projects. Firstly, the current pace of sustainable energy policy developments in Australia is
generally perceived to be lagging behind technological advances, driving communities to take their
own actions to meet local sustainability goals (Bowyer, 2015). Similarly, community-owned
electricity sharing schemes (which are classified as CORE initiatives) are seen as a way to move
away from traditional electricity grid arrangements and attain local energy autonomy (Stringer et
al., 2017). CORE initiatives may also provide a valuable and sustainable income stream to the
community (Adams and Bell, 2015), since internal tariffs in Community ENs can generate
monetary savings for participants compared to them remaining with market-offers. Further, the sale
of energy produced by the community may generate income which can be used for additional
community projects (Wen et al., 2013).
2.2. Assessing equity in CORE projects
Adams and Bell (2015) explore the equity issues associated with local energy projects. They refer
to how the costs and benefits, risks and impacts of such projects may be unevenly distributed.
Their findings also highlight the risks associated with the high upfront costs for such projects which
contribute to being inaccessible to certain members of the community. Where the impacts, costs
and benefits aren’t clearly explained, even those who can afford the upfront cost, may not realise
that the investment would be beneficial for them.
Incentives such as solar FiTs (Adams and Bell, 2015), and policy schemes (Rogers et al., 2008),
are recommended to help ensure individual participation in CORE projects, but many of these
studies do not address the potential inequities that might arise due to the exclusion of participants
Asia Pacific Solar Research Conference, Sydney, December 4-6 2018
who may not be able to afford the infrastructure costs but may still wish to participate. Chan et al.
(2017) explored the use of community shared solar as a method to allow more inclusion in
community projects. Although they discussed a variety of models in which communal solar arrays
may be owned and consumers can purchase a certain portion of generated electricity, they
focussed on offsite solar projects. While ENs are quite widespread in Australian shopping centres,
airports and sometimes apartment buildings, community owned or run ENs focussed on supporting
sustainable energy outcomes are a relatively new phenomenon, and there is scant analysis or
published best practices assessing the impact of different arrangements on the outcomes for the
participants or the community. Thus, given the potential of CORE EN projects to address inequities
in the energy system and support RE deployment, this paper examines the impact of different PV
penetration levels and different tariff arrangements on the financial outcomes for participants, the
incentives for PV uptake and the equity implications. .
2.3. Existing Australian Community EN case studies
2.3.1. Byron Arts and Industrial Estate
The Byron Bay Shire in Australia is in the process of implementing a 100% Renewables initiative
(ITP Renewables, 2017). Stringer et al. (2017) reported on a case study of a local energy sharing
scheme for a pseudo-EN (essentially a peer to peer trading arrangement) in the Byron Arts and
Industrial Estate. It modelled 11 commercial customers with and without solar, and quantified the
financial outcomes for the participants, the DNSP and the retailer. Only simple flat and TOU tariff
designs were tested. While there was limited quantitative comparison between outcomes for the
customers in the EN, it was noted that the benefits of the local electricity sharing scheme were
unevenly shared, providing a key opportunity for further research.
2.3.2. PV for Apartment Buildings
Roberts, et al. (2017) explored the potential for PV in apartment complexes to offset apartment
loads. They included details on three designs for such a scheme individual solar behind the
meter (BTM), shared solar BTM, and an EN and discussed the financial benefits for the complex
as a whole. The results indicated financial savings for the complex when implementing an EN
arrangement with and without solar, but only presented financial outcomes for the building as a
whole. As such, Roberts identifies a “clear need for more detailed analysis of the distribution of
costs and benefits between all stakeholders under a wide range of financial settings” (p.11).
2.3.3. Nerara Ecovillage
Nerara Ecovillage is currently under construction in the NSW Central Coast Region and includes a
Community EN. It is an example of a ‘greenfield’ EN as the internal infrastructure will be purpose-
built for this project. Bowyer (2015) conducted an in-depth analysis into potential arrangements for
Nerara Ecovillage EN, exploring residential and commercial electrical load and water supply
options, including a preliminary exploration of the implications of different internal tariff designs.
However, the paper did not propose assessment criteria for appropriate tariff design and therefore
did not specifically assess the tested tariff designs.
Existing Australian studies of CORE EN projects have explored community embedded networks in
greenfield scenarios, apartments and commercial settings, but not for existing communities of
stand-alone residences. These studies have not attempted to quantify distributional impacts across
different types of participants in CORE ENs, and have provided only a preliminary exploration of
the impact of PV penetration levels.
Asia Pacific Solar Research Conference, Sydney, December 4-6 2018
The objective of this paper is:
To understand the implications of PV deployment and internal EN tariffs on financial,
environmental and social outcomes for participants in Community ENs and use this to
evaluate the place of Community ENs in the CORE space.
3. Methodology
To fulfil the objective of this study, we propose criteria for assessing the appropriateness of EN
arrangements, use a model developed in Python to simulate a Community EN with energy sharing,
and under different arrangements, calculate outcomes for the for the ENO, compare financial and
equity outcomes between participants with and without solar and A/C, and assess the incentives
for PV deployment. An existing Python model developed for use in the study by Stringer et al.
(2017) and adapted for this purpose.
The model can track electricity and financial flows for participants and the ENO, with an inbuilt
energy sharing regime that allocates excess locally generated solar amongst participants before
exporting via the parent-point of connection to the main grid. The critical model inputs required
were half-hourly load profiles for each participant, half-hourly solar generation profiles for each
participant, and solar and tariff pricing and timing for the required tariff types
1
.
The Community EN modelled is a ‘brownfield’ design, rather than a ‘greenfield’ design such as that
in Bowyer et al., (2015). A ‘brownfield’ design is one based predominantly on existing infrastructure
in comparison to ‘greenfield’ which uses purpose-built infrastructure. Brownfield Community ENs,
such as existing communities of houses, e.g. community housing precincts, don’t require
significant new infrastructure beyond the necessary metering.
3.1. Data grouping
Participant load data was sourced from the Ausgrid Smart Grid Smart City (SGSC) dataset, and
solar data was sourced from the Ausgrid 300 Solar Homes study, both for the year July 2012-June
2013. The demographic data available in the SGSC set allowed customers to be grouped by house
type.
A Community EN with 60 participants (households) was chosen to represent a ‘brownfield’
community in which this type of EN might be applied. The key assumptions used for selecting
participants for the EN included: no gas, so that the load profiles could be assumed to include all
electric appliance use, no pool pumps, to ensure the controlled load (CL) data was all water
heating, and no solar water heating, to simplify interpretation of the data. Participants both with and
without air-conditioners (A/C) were included in the Community EN.
The characteristics of the Community EN used in this study are as in Table 1:
Table 1. Characteristics of Community EN in this study
Number of households (participants)
60
Number of non A/C participants
15 (25%)
Number of A/C participants
45 (75%)a
1
More comprehensive details of model logic may be found in the paper. The original model script may be found here:
https://github.com/luke-marshall/embedded-network-model
The altered model scripts used in this study may be found here: https://github.com/emily-banks/embedded-network-
model/tree/emilyfinal and https://github.com/emily-banks/embedded-network-model/tree/fast
Asia Pacific Solar Research Conference, Sydney, December 4-6 2018
Annual load (inc CL)
449 MWh
a This figure was determined by consulting census data from the ABS (2014)
Participant annual consumption (including CL) ranged from approximately 3000 to 12000 kWh for
non A/C customers and 2000 to 17000 kWh for A/C customers, with A/C customers having higher
daytime usage than non A/C.
3.2. Case modelling
The PV penetration cases used for testing are presented in Table 2:
Table 2. Overview of test cases
Case name
Case
Base
No EN, no participants with solar
No solar
Within EN, no participants with solar
25% solar
Within EN, 25% of participants have solar (assigned randomly)
50% solar
Within EN, 50% of participants have solar (assigned randomly)
75% solar
Within EN, 75% of participants have solar (assigned randomly)
100% solar
Within EN, all participants have solar
For the modelling of all scenarios with solar (25-100%), controlled load (CL) data for all participants
(solar and non-solar) was shifted to be between 11am and 3pm to minimise exports at the parent
point (since no FiT is received here), and solar data was scaled to have each system between 4
and 5 kW to reflect current system size trends. Several iterations of randomly assigning solar data
to households were conducted to achieve a spread of results.
3.2.1. Setting the internal tariff rate
The base case was tested with each participant not within an EN, on a flat tariff with the price set at
15% below both fixed and volumetric charges provided by EnergyAustralia (2018), since
customers on a market offer tariff are likely to pay around 15% less than on a standing offer
(AEMC, 2017; Roberts, et al., 2017). Each tariffs scenario within the EN had an additional discount
of 12% applied to the volumetric charges only based on achieving a balance between customer
savings and ENO profit (fixed charges remained constant to reflect the costs of supplying
electricity).
Four internal tariff cases were tested for each PV penetration case (excluding the base case).
These were:
- Flat tariff with 12.5 c/kWh FiT and 12.5 c/kWh local solar charge
2
- Flat tariff with 15 c/kWh FiT and 15 c/kWh local solar charge
- TOU with 12.5 c/kWh FiT and 12.5 c/kWh local solar charge
- Seasonal TOU with 12.5 c/kWh FiT and 12.5 c/kWh local solar charge
The appendix gives the rates and structures for each of these internal tariffs.
2
The local solar charge is the rate for which excess locally generated solar is sold to neighbours
Asia Pacific Solar Research Conference, Sydney, December 4-6 2018
3.2.2. Setting the tariff rate at the parent-point
A commercial tariff is usually applicable at the parent-meter of an EN since the load is a similar
scale to a large commercial customer. These rates are lower than residential rates, giving the ENO
some flexibility in setting the internal tariff paid by participants. Commercial rates depend on the
annual load of the customer, which in this case is the aggregate of the annual loads of the
participants, equal to 449 MWh (Table 1).
The 2018/2019 Network Price List for the Ausgrid Zone (Ausgrid, 2018) was used to obtain
Network Use of System (NUOS) component of the commercial tariff at the parent point assuming a
Low Voltage connection. The EA305 tariff applies to a customer with this annual load range of 160-
750MWh. The retail component of the commercial tariff, which is subject to a market offer, was set
at an additional flat rate of 9.5 c/kWh based on the approach of Roberts et al. (2015) (Table 3). The
combined tariff was applied to total energy imports to determine the ENO’s costs at the parent
connection point, assuming a billing period of July 1-June 30 for the capacity charge. Note that
there is typically no FiT offered to commercial customers for solar export, so any excess
generation exported to the grid provides no financial benefit.
Table 3. Commercial tariff applied at parent point
Tariff
Code
Tariff
Name
Network Energy Charges
Network
Capacity
charge
(cents/kVA)
Retail
charge
(cents/kWh)
Peak (2-8pm)
(cents/kWh)
Shoulder (7am-
2pm and 8pm-
10pm)
(cents/kWh)
Off-peak
(cents/
kWh)
EA305
LV 160-
750 MWh
(System)
5.8132
2.6617
1.2152
40.1023
9.5000
No additional charges were added to account for EN infrastructure costs as ENO’s are prohibited
from retrieving these costs via tariffs. In addition, these are highly case dependent and not always
paid by the ENO (Roberts et al., 2018).
4. Results
4.1. ENO profit
To calculate the benefits to the ENO, the profit at the parent point was determined for each case by
applying the commercial tariff rate to energy imports then subtracting this from the total bill paid by
all participants to the ENO. For the EN to be viable, it needs to make profit. This may be fed back
into the community in a variety of ways, for example, to community projects, for communal solar or
storage, etc., and can also be used to recover capital costs. Figure 2 gives the annual profit made
by the ENO for each PV penetration level, with each tariff structure.
Asia Pacific Solar Research Conference, Sydney, December 4-6 2018
Figure 2. ENO annual profit variation with PV penetration and tariff structure
The ENO profit decreases as solar uptake increases because there is less demand for electricity
from the main grid due to the increase in local solar sharing, which reduces the profit it makes from
the difference in the retail and commercial tariffs. This is partly offset by the benefits it receives
from the decrease in demand charges at the parent point due to greater solar generation.
Note that the decrease is not linear. Between the no solar and 25% cases, the ENO profit
decreases by approximately $15,000 and between the 75% and 100% cases only by
approximately $10,000. At the high solar percentages, the level of solar within the EN becomes
saturated, and so instead of being sold to other customers in the EN, it is exported to the main
grid. At these levels, there are three different impacts, which when combined, result in smaller
incremental losses for the EN:
1. For each kWh of solar electricity generated, the losses incurred because of reduced sales
of grid electricity are smaller (because they were often already buying internal solar),
2. For each kWh of solar electricity generated, the benefits from reduced demand charges are
reduced (because the new demand charge peaks are outside the time of solar generation),
and
3. The ENO does not receive any payment for electricity exported to the grid.
Importantly, at 75% and 100% solar uptake, the ENO is losing money, or is close to losing money,
posing obvious issues for its viability. This means that this scheme cannot support higher PV
penetrations at the modelled internal tariff rates. Correcting this would involve increasing the
internal retail tariff offered to customers and/or decreasing the local solar payments, but this would
mean that customers would not make as much (or any) savings from joining the EN.
ENOs earn the least profit under the Seasonal TOU scenario. This is most likely because the PV
generation reduces sales during the Summer and Winter peak time from 2pm-8pm. Under the
TOU, the peak time is 5pm-10pm year-round.
The increase in FiT to 15c/kWh understandably decreases the ENO profit as the solar percentage
increases because a greater proportion of the solar generation is exported to the main grid, for
which, as above, the ENO receives no payment.
Overall, losses (or gains) for the ENO due to changing the internal tariff range from $12,000 to
$4,000 per year, so the internal tariff design is a significant design consideration for the viability of
-20000
-10000
0
10000
20000
30000
40000
no solar 25% 50% 75% 100%
Profit ($)
Flat, 12.5c FiT Flat, 15c FiT TOU, 12.5c FiT Seasonal TOU, 12.5c FiT
Asia Pacific Solar Research Conference, Sydney, December 4-6 2018
an EN. At high PV percentage this loss can be approximately 25% of profits, although the absolute
amount is greater at lower PV penetrations.
4.2. Participant Impacts
To analyse outcomes for participants, the yearly bill for each participant was calculated and the
spread of outcomes presented for solar and non-solar customers with and without A/C. To ensure
that customers purchase electricity from the ENO, it is important that their bills are lower than in the
base case (no EN). Figure 3 gives the total bill (averaged across all PV penetration cases) for each
participant within the EN compared to what they would pay outside it (base case). Because of
space constraints only the results for the flat tariff are shown.
Figure 3. Annual bill for each customer averaged across all PV penetration cases
As is expected, each participant benefits from being in the EN compared with the base case on
average across each of the PV percentage cases. This is due to a combination of the solar sharing
scheme and the cheaper retail rate (12% discount on volumetric charges). Bills for A/C customers
are greater than for non-A/C customers, given the greater annual load. The bill for solar
participants is also significantly smaller, as expected.
The savings accessed by non-solar customers by joining the EN and participating in the buying
component of the solar sharing scheme are given in Figure 4.
Base EN Base EN
non-solar solar
Asia Pacific Solar Research Conference, Sydney, December 4-6 2018
Figure 4. Savings on total bill compared with base case for non-solar customers on flat
tariff
Non-solar customers can benefit most from participating in these schemes when there is a high
percentage of solar and therefore greater potential for solar sharing. Simply being within the EN in
the no solar case also produces savings given the discount on retail tariff rates. The decrease in
savings for non-solar customers between the no solar and 25% solar cases has likely occurred due
to the shifting of CL to daytime for all participants for all the solar cases. Gains from receiving
shared solar at the FiT rate to meet regular load does not outweigh losses of paying for the CL at
the retail rate (which is higher than the CL rates) for such a small pool of shared solar available. In
this case, having these participants remain on the CL tariff for a low solar percentage case could
avoid this problem.
The savings accessed by solar customers in participating in the EN and solar sharing scheme are
given in Figure 5.
No solar 25% solar 50% solar 75% solar
Asia Pacific Solar Research Conference, Sydney, December 4-6 2018
Figure 5. Savings on total bill compared with base case for solar customers on flat tariff
Solar customers save more in an EN when there is a higher solar percentage. But savings are
quite consistent and only vary by approximately $50 per year.
Overall, solar and non-solar customers can access similar savings within the EN scenarios
modelled. Although solar customers do benefit more, compared to the base case (conventional
grid), an EN decreases the inequity between solar and non-solar customers in that the non-solar
customers can purchase solar electricity at the FiT rate, rather than at the full retail tariff. While a
higher FiT incentivises PV deployment, the 15c FiT skews savings further towards the solar
customer. Here there is inequity between solar and non-solar customers, as savings to the former
increase while savings to the latter decrease with the FiT change.
5. Discussion
5.1. Overall Financial Benefit
The results indicate that significant financial benefit can be achieved by both the ENO and
participants in Community ENs through access to cheaper parent-point/child-point rates and solar
sharing schemes.
The overall financial benefit to the ENO was greatest in the Solar TOU case because the peak rate
was applied all year round. Income to the ENO would decrease on both TOU tariffs if customers
shifted their load out of the peak period and into the solar time. Participants were also able to
access savings to varying degrees simply by participating in the EN. These savings averaged
approximately $200 for joining the EN to access the 12% discount on retail tariff charges and the
solar sharing scheme, and an additional $900 if solar was installed.
It was found that customers with solar and A/C accessed the largest savings, given the existence
of the solar FiT and the suitability of the load profile for accessing benefits of solar sharing. While
non-solar customers were somewhat disadvantaged (with negative savings) in some cases due to
the shifting of controlled load data into peak times, this could be remedied to ensure that
participants would not exit the EN.
25% solar 50% solar 75% solar 100% solar
Asia Pacific Solar Research Conference, Sydney, December 4-6 2018
5.2. Encouraging PV Deployment
As was expected, the higher the FiT, the greater the benefits from installing PV, thereby
encouraging PV deployment by the customer. The payback times for PV when in the EN were
approximately 1 year less than outside the EN because of the higher FiT rates (although this effect
would have been offset to some extent by the on-site use of solar avoiding a lower retail rate in the
EN). Although not shown here, the 15 c/kWh FiT approximately doubled yearly participant savings
compared to the 12.5 c/kWh FiT. As more customers installed solar, the per customer savings for
doing so decreased, although by a small amount relative to the approximately $900 saved.
5.3. Equity Outcomes
Equity outcomes under community ENs were assessed based on differences in benefits between
groups of participants and the payback time for installing PV. A key inequity in the energy industry
is that between solar customers and those who may wish to install solar to access savings (or
encourage RE production) but cannot afford it. The Community EN in this study addresses this
inequity to some extent through the solar sharing scheme, because non-solar customers can
access electricity at a lower rate than the daytime EN retail rate.
Another point apparent in the results from modelling that has not often been considered in the
literature is the disparity between A/C and non-A/C customers which was likely due to the shape of
their load profiles. While the difference is not of major financial significance, it is still an interesting
finding. A/C customers pay more overall for their electricity for all cases explored, but the savings
they were able to make on their bill in the solar sharing scheme were greater than for non-A/C
customers in some cases. This is potentially problematic as it reduces the disincentive for high
energy consumption. On the other hand, the proportions of bills saved are similar across A/C and
non-A/C customers and this may be a more important driver of energy consumption decisions.
6. Conclusions
The results of this modelling suggest that a Community EN with solar sharing can be a credible
option for a community wishing to meet various goals through a CORE project. All that remains is
the question of prioritising what is most important to the community.
It is evident that there are inherent conflicts between some aspects of CORE EN design. While
ENO profits are highest at low levels of solar penetration, savings may be greatest to participants
at higher levels. While a higher FiT encourages PV deployment, this is at the expense of non-solar
customer savings and ENO profit.
There are, however, some aspects of a CORE EN that can address these tensions and help to
meet community goals through careful design, which would not be available on-market. Where an
ENO may lose profit under some arrangements, customer savings may be viewed as more
important, or if potential customer savings are compromised by ENO profit, this can be fed back
into the community through initiatives such as RE deployment or communal batteries.
Limitations of the research should be considered when interpreting results, including the limited
scope of inputs explored, and the lack of consideration of impacts on the wider electricity market.
Nevertheless, it is hoped that this study may simply encourage a broader discussion of social
outcomes in relation to energy projects.
Asia Pacific Solar Research Conference, Sydney, December 4-6 2018
7. References
ABS (2014) ‘Energy Sources Used by Households’, pp. 1–8.
Adams, C. A. and Bell, S. (2015) ‘Local energy generation projects: assessing equity and risks’,
Local Environment. Taylor & Francis, 20(12), pp. 14731488. doi:
10.1080/13549839.2014.909797.
AEMC (2015) ‘New Rules for Embedded Networks’. Available at:
http://www.aemc.gov.au/getattachment/04b21dd0-521c-48ca-b575-6fbe6b736a37/Information-
sheet.aspx.
AEMC (2017) Final Report: 2017 Residential Electricity Price Trends.
Ausgrid (2018) Network Price Guide. Available at: https://www.ausgrid.com.au/-
/media/Files/Network/Documents/ES/ES7.pdf.
Bauwens, T. (2016) ‘Explaining the diversity of motivations behind community renewable energy’,
Energy Policy. Elsevier, 93, pp. 278290. doi: 10.1016/j.enpol.2016.03.017.
Bowyer, J. (2015) Retail Arrangements and Load Management Opportunities for Community
Owned Embedded Networks.
Chan, G. et al. (2017) ‘Design choices and equity implications of community shared solar’,
Electricity Journal. Elsevier, 30(9), pp. 3741. doi: 10.1016/j.tej.2017.10.006.
Community Power Agency (2015) About Community Energy, Community Power Agency. Available
at: http://cpagency.org.au/about-community-energy/.
Energy Australia (2018) ‘Energy Price Fact Sheet - Single Rate with Controlled Load’. Available at:
https://www.agl.com.au/-/media/agldata/distributordata/pdfs/pricefactsheet_agl469895mr.pdf.
ITP Renewables (2017) Achieving 100% Renewable Electricity for Byron Shire.
Roberts, M. B. and Bruce, A. (2018) ‘Collective Prosumerism’, in IEEE, pp. 05.
Roberts, M. B., Bruce, A. and Macgill, I. (2017) ‘PV for Apartment Buildings : Which Side of the
Meter?’, Solar Research Conference.
Rogers, J. C. Ã. et al. (2008) ‘Public perceptions of opportunities for community-based renewable
energy projects’, Energy Policy, 36, pp. 42174226. doi: 10.1016/j.enpol.2008.07.028.
Stringer, N. et al. (2017) ‘Open Source Model for Operational and Commercial Assessment of
Local Electricity Sharing Schemes in the Australian National Electricity Market’, Solar Research
Conference 2017.
Wen, L. et al. (2013) ‘Transitioning to community-owned renewable energy : Lessons from
Germany’, Procedia Environmental Sciences. Elsevier B.V., 17, pp. 719728. doi:
10.1016/j.proenv.2013.02.089.
8. Acknowledgements
The authors thank Luke Marshall and Naomi Stringer for their assistance using and adapting the
EN energy sharing model, Mike Roberts for advice on Embedded Network arrangements, and
Navid Haghdadi and Zoe Hungerford for their assistance with extracting data for this study.
Asia Pacific Solar Research Conference, Sydney, December 4-6 2018
9. Appendix
Table 4. Flat tariff used for modelling with no EN
Flat Rate
Price (inc GST)
Consumption charge
27.4423 cents per kWh
Daily charge
78.6335 cents per day
Controlled Load 1
Price (inc GST)
Consumption charge
11.2761 cents per kWh
Daily charge
3.366 cents per day
Controlled Load 2
Price (inc GST)
Consumption charge
14.8291 cents per kWh
Daily charge
13.9315 cents per day
Table 5. Flat tariff used for modelling within EN
Flat Rate
Price (inc GST)
Consumption charge
24.1492 cents per kWh
Daily charge
78.6335 cents per day
Controlled Load 1
Price (inc GST)
Consumption charge
9.923 cents per kWh
Daily charge
3.366 cents per day
Controlled Load 2
Price (inc GST)
Consumption charge
13.0496 cents per kWh
Daily charge
13.9315 cents per day
Table 6. TOU tariff used for modelling within EN
TOU rate
Price (inc GST)
Peak (5pm-10pm) (weekday only)
44.3489 cents per kWh
Shoulder (7am-5pm)
23.203cents per kWh
Off-peak (10pm-7am)
14.1522 cents per kWh
Supply charge (all year)
Price (inc GST)
Daily
78.6335 cent per day
Controlled Load 1
Price (inc GST)
Consumption charge
9.923 cents per kWh
Asia Pacific Solar Research Conference, Sydney, December 4-6 2018
Controlled Load 2
Price (inc GST)
Consumption charge
13.0496cents per kWh
Table 7. Seasonal TOU tariff used for modelling within EN
Summer rates (1 Nov-31 Mar inclusive)
Price (inc GST)
Peak (2pm-8pm) (weekday only)
44.3489 cents per kWh
Shoulder (7am-2pm, 8pm-10pm)
23.203cents per kWh
Off-peak (10pm-7am)
14.1522 cents per kWh
Winter rates (1 Jun-31 Aug inclusive)
Price (inc GST)
Peak (5pm-9pm) (weekday only)
44.3489 cents per kWh
Shoulder (7am-2pm, 9pm-10pm)
23.203cents per kWh
Off-peak (10pm-7am)
14.1522 cents per kWh
Autumn/Spring rates (1 Apr-31 May and 1 Sep-31 Oct inclusive)
Price (inc GST)
Shoulder (7am-2pm, 9pm-10pm)
23.203cents per kWh
Off-peak (10pm-7am)
14.1522 cents per kWh
Supply charge (all year)
Price (inc GST)
Daily
78.6335 cent per day
Controlled Load 1
Price (inc GST)
Consumption charge
9.923 cents per kWh
Controlled Load 2
Price (inc GST)
Consumption charge
13.0496 cents per kWh
ResearchGate has not been able to resolve any citations for this publication.
Conference Paper
Full-text available
Local electricity sharing schemes have the potential to play an increased role in the Australian National Electricity Market as the penetration of distributed energy resources (DERs) continues to grow. These models allow participants to share energy between separately owned and operated DERs, however are largely untested. While embedded networks have generally been established for specific circumstances such as shopping centres and airports, there is growing interest in their wider application in providing a framework for local sharing of energy resources. However, the potential operational and commercial implications for key stakeholders (including consumers, network operators and retailers) are not well understood. An example of one such proposal is within the Byron Arts and Industrial Estate through which the community owned retailer, Enova, is seeking to offer a bespoke energy solution to its customers within the estate. In this paper, a new open source software model for assessing technical and commercial outcomes of local electricity sharing is presented. The model is applied to the Byron Arts and Industrial Estate case study which demonstrates the relevance of modelling to support appropriate investment and operational decision-making. 1. Introduction With significant reductions in photovoltaics (PV) and battery energy storage (BES) system costs over recent years, a range of new business and community models are emerging in electricity industries around the world, specifically designed to cater to a new class of consumer: participants that both generate and consume energy from distributed energy resources. These new approaches allow customers to buy and sell energy between each other (rather than from a centralised retailer or generator), and to aggregate their consumption to access a more beneficial interface with networks and electricity markets.
Conference Paper
Full-text available
Over 1.7 million Australian households have taken the opportunity to generate some of their own power and reduce both their electricity bills and carbon emissions by installing rooftop photovoltaic (PV) systems on their homes. However, regulatory, technical, financial and organisational challenges have largely prevented Australia's growing number of urban apartment dwellers from accessing these benefits. Although a number of apartment buildings have installed PV systems to meet common property (CP) loads, over 60% of Australian apartments are in buildings of less than four storeys, where potential rooftop PV generation is likely to exceed CP demand. Shared PV systems in such buildings might be configured to supply local generation to apartments either 'behind the meter' (BTM) or via an embedded network (EN). There are, of course, different implications for these approaches in terms of the risks, costs and benefits for different stakeholders. Aggregation of diverse apartment energy demands through an embedded network can flatten overall load profiles and increase PV self-consumption, as well as affording access to more beneficial retail arrangements. However, the complexities of the regulatory environment and costs of EN installation can create barriers to this approach. BTM solutions may allow residents to avoid engagement with the regulatory requirements placed on retailers and EN operators, but typically result in lower levels of self-consumption and higher household tariffs. This study seeks to compare the costs and benefits of these two possible arrangements. There is a dearth of published interval load data for Australian apartment buildings. However, the Smart Grid Smart Cities (SGSC) dataset includes 30-minute annual load for 2080 apartments across New South Wales. Firstly, using this data, this study examines the effect of aggregating apartment loads on the variability of total load profiles and on PV self-consumption. Then, SGSC apartment load profiles are combined with CP load profiles collected for building energy audits at 10 sites in the Sydney metropolitan area to create multiple 'virtual apartment buildings' for each site. Rooftop solar generation is modelled for these buildings using historic weather data and visual assessment of rooftop potential, and energy flows are calculated throughout the buildings for both EN and BTM arrangements. Some initial financial settings are applied to assess the relative total benefits of each scenario.
Conference Paper
Full-text available
Currently in Australia there is a strong movement of communities seeking to live more sustainably. This is giving rise to the development of community owned and operated micro-grids which incorporate large amounts of renewable energy technology. While this is an emerging movement in Australia, there are still questions surrounding how these micro-grids can operate within the current regulatory and retail frameworks in Australia. This paper explores how the embedded network framework can be effectively applied to community-owned micro-grids. The objective of this paper is to explore the regulatory and retail arrangements for community-owned embedded networks through a case study of Narara Ecovillage. Working within the embedded network framework has complexities and challenges. To operate an embedded network, the embedded network operator (ENO) must take on the role of network service provider, local retailer and potentially embedded network manager (ENM). There are significant challenges associated with this such as following evolving Australian Energy Market Commission (AEMC) regulations, ensuring retail competition for customers, guaranteeing operational expenditure recovery and designing appropriate retail tariffs. Design considerations for the ENO tariffs include: recovering costs paid to the external retailer, recovering network operational expenditure, using tariff price signals to manage demand and ideally providing cheaper electricity for the customers than an external retailer would provide. This study designed and modelled potential tariff arrangements and concluded that the optimal tariff is a " Solar TOU " tariff which incentivizes customers to use more electricity during times of excess solar generation. Using the " Solar TOU " tariff, this case study could generate an annual operational profit, and provide a discount to the customers, when compared to a traditional external retailer tariff.
Article
Full-text available
Community-based renewable energy initiatives may be important actors in the transition toward low-carbon energy systems. In turn, stimulating investments in renewable energy production at the community level requires a better understanding of investors’ motives. This paper aims to study the heterogeneity of motivations that drive individuals to participate in community renewable energy projects and the underlying explanatory factors behind this, as well as the implications for their level of engagement in initiatives. Based on quantitative data from an original survey conducted with two renewable energy cooperatives in Flanders, the statistical analysis shows that cooperative members should not be considered as one homogeneous group. Several categories of members with different motives and levels of engagement can be distinguished. This heterogeneity is explained by contrasts in terms of institutional settings, spatial patterns and attitudes to the diffusion of institutional innovations. Regarding policy implications, the findings suggest that this heterogeneity should be taken into account in designing more effective supporting policies to stimulate investments at the community level. The activation of social norms is also shown to be a promising mechanism for triggering investment decisions, although the implications of its interplay with economic incentives should be further explored.
Article
Full-text available
It now widely acknowledged that the UK needs to increase renewable energy capacity and it has been claimed that community-based renewable energy projects, with high levels of public participation, are more likely to be accepted by the public than top-down development of large-scale schemes and may bring additional benefits such as increased engagement with sustainable energy issues. However, little research has investigated public expectations of how people would like to participate in such projects and why. The aim of this study was to explore one rural community's response to a proposed sustainable energy project. A questionnaire survey and semi-structured interviews provided quantitative and qualitative data. There was widespread support for local generation and use of renewable energy, with respondents expecting benefits from a project in terms of increased community spirit and conservation of natural resources. However, desire for active involvement was lower and residents viewed themselves participating as consultees, rather than project leaders. We suggest community renewable energy projects are likely to gain public acceptance but are unlikely to become widespread without greater institutional support.
Article
What is the best way to deploy solar energy to maximize clean energy growth while equitably sharing benefits? A promising model is community shared solar, which enables energy consumers to purchase shares of electricity generated in an offsite project. Noting how different states and utilities have approached program design, we explore how design decisions affect access to solar and the equity of cost and benefit sharing. We conclude with a set of questions for future research.
Article
Micro- and small-scale low-carbon energy generators embedded within villages, towns and cities can provide a valuable income stream for local communities among other potential benefits. There are a range of social, political, technical and environmental factors that may impact upon the success of a planned energy generation project; however, these factors are rarely considered in unison. The aim of this research is to investigate and understand the concerns relating to equity and distributional justice that impact upon local groups interested in developing energy projects and to determine whether a whole systems approach can be used to draw out perceived issues. This has been achieved by working with two small village groups to test a newly developed energy equity assessment tool. This paper reports research findings from two villages in the UK both planning energy projects that intended to benefit their respective villages and examines perceived issues relating to equity and distributional justice associated with the proposed schemes. The research highlights some challenges facing community groups when planning micro- and small-scale energy projects and demonstrates the commitment, tenacity and high levels of personal risk that these groups have to bear in order to bring their projects to fruition and comments as to the type of actions that may be required to more wholly consider equity issues while developing future energy policy.
Energy Sources Used by Households
  • Abs References
References ABS (2014) 'Energy Sources Used by Households', pp. 1-8.
Local energy generation projects: assessing equity and risks', Local Environment
  • C A Adams
  • S Bell
Adams, C. A. and Bell, S. (2015) 'Local energy generation projects: assessing equity and risks', Local Environment. Taylor & Francis, 20(12), pp. 1473-1488. doi: 10.1080/13549839.2014.909797. AEMC (2015) 'New Rules for Embedded Networks'. Available at: http://www.aemc.gov.au/getattachment/04b21dd0-521c-48ca-b575-6fbe6b736a37/Informationsheet.aspx.