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Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria

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  • Austrian Institute of Technology, Austria, Vienna

Abstract and Figures

Although the amount of solar photovoltaic systems installed in residential buildings is increasing globally, it is largely limited to single-occupancy dwellings and is extremely uneven across jurisdictions. Deployment on apartment buildings remains low, even in Australia with its world-leading residential photovoltaic penetration, or in countries subject to specific enabling legislation, such as Austria. We present a comparative study of photovoltaic system deployment on multi-occupancy residential buildings in these two countries, examining the impact of their distinct climates, financial settings, heating and cooling technologies and regulatory environments. A mixed-integer linear optimisation model is used to compare cost-optimal photovoltaic system size and achievable cost savings for a nine-apartment building. We find that Australia's higher insolation and lower investment costs drive higher optimal system size and bill savings, but lower electricity tariffs and regulatory barriers constrain deployment. By contrast, European enabling legislation has not yet achieved success in overcoming Austria's higher investment costs and lower solar exposure, partly due to significant administrative hurdles. Our findings point to possible country-specific policy approaches to increase deployment in this important sector.
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The impact of climatic, market and regulatory factors
on the profitability of shared PV for self-consumption
in multi-apartment buildings: A comparison of
Australia and Austria
Bernadette Fina a,c,1,
, Mike B Robertsb,d,1, Hans Auerc, Anna Bruceb,d , Iain
MacGillb,e
aAIT Austrian Institute of Technology, Giefinggasse 4, 1210 Vienna, Austria
bCollaboration on Energy and Environmental Markets, University of New South Wales,
Sydney 2052, Australia
cEnergy Economics Group (EEG), Technische Universit¨at Wien, Gusshausstraße 25-29,
E370-3, 1040 Vienna, Austria
dSchool of Photovoltaic and Renewable Energy Engineering, University of New South
Wales, Sydney 2052, Australia
eSchool of Electrical Engineering and Telecommunications Engineering, University of New
South Wales, Sydney 2052, Australia
Abstract
Although the amount of PV installed in residential buildings is increasing
globally, it is largely limited to single-occupancy dwellings and is extremely un-
even across jurisdictions. Deployment on apartment buildings remains low, even
in Australia with its world-leading residential PV penetration, or in countries
subject to specific enabling legislation, such as Austria. We present a compara-
tive study of PV deployment on multi-occupancy residential buildings in these
two countries, examining the impact of their distinct climates, financial settings,
heating and cooling technologies and regulatory environments. A mixed-integer
linear optimisation model is used to compare cost-optimal PV system size and
achievable cost savings for a nine-apartment building. We find that Australia’s
higher insolation and lower investment costs drive higher optimal system size
and bill savings, but lower electricity tariffs and regulatory barriers constrain
deployment. By contrast, European enabling legislation has not yet achieved
success in overcoming Austria’s higher investment costs and lower solar expo-
sure, partly due to significant administrative hurdles. Our findings point to
possible country-specific policy approaches to increase deployment in this im-
portant sector.
Keywords:
Photovoltaics; Apartment buildings; PV sharing; Energy communities;
Corresponding Author, Email address: fina@eeg.tuwien.ac.at
1Both authors contributed equally to the work.
Preprint submitted to Applied Energy September 1, 2020
This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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Residential electricity; Mixed integer linear optimisation; Self-consumption;
Austria; Australia
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This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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1. Introduction
In order to address the urgent issue of climate change, most countries world-
wide have ratified the Paris Agreement, with its commitment to keep global
temperature rise well below 2 C [1]. An important and necessary step to achiev-
ing this target is the increased diffusion of renewable energy throughout all
energy-intensive sectors. Since – along with industry, agriculture and transport
– building electricity and heating and cooling are major contributors to global
emissions [2], increasing deployment of renewable energy sources, particularly
solar photovoltaics (PV) on buildings is making an important contribution to-
wards achieving the global climate goals.
Although residential installations comprise a significant part of this deployment
globally, they are very unevenly distributed. In Austria, for example, with a
total of 1.4 GW of PV connected to the distribution network [3], only a mod-
erate number of PV systems are to be found on the rooftops of single-family
buildings. In contrast, Australia has 8.9 GW of rooftop PV installed on 27 % of
stand-alone houses, with residential penetration as high as 50 % in some local
government areas [4]. However, in common with many other jurisdictions, both
countries see very low levels of PV deployment on multi-occupancy residential
buildings. While the disparity in residential PV penetration between these two
dissimilar countries might be explained by differences in a range of exogenous
factors, including climate, building types, financial and regulatory settings, the
reasons for the similarity in their lack of PV deployment on apartment buildings
is less clear.
The aim of this study is to examine the country-specific factors that influence
the deployment of residential PV and, in particular, the differential impact of
these factors on multi-occupancy buildings compared to stand-alone housing.
Using the examples of Austria and Australia, we first compare the exogenous
factors which might influence residential PV deployment in general. We then
investigate the impact of these factors on the cost-optimal design of, and achiev-
able cost savings from, a PV system for a nine-apartment residential building
sited in Sydney, Australia or in Vienna, Austria, simulated using different com-
binations of real, diverse apartment load profiles. The analysis focuses on PV
generation for shared self-consumption, an area of increasing interest [5], as
current payments for export are low or may be unavailable where commercial
tariffs are applied to aggregated building loads.
The novel contribution of this study lies in its consideration of the separate
and combined impacts of diverse direct and indirect influencing factors, specif-
ically climate, market conditions, building characteristics and regulatory en-
vironments, on residential PV deployment. The contrasting impacts of these
factors on the penetration and profitability of rooftop PV for stand-alone hous-
ing and for apartment buildings is compared across two geographically remote
countries. Additional to this theoretical analysis, an optimisation model is used
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This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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to quantify the optimal PV installation capacities and achievable cost saving
potential of PV on a multi-occupancy building in each country, and their sen-
sitivity to different exogenous factors. In integrating this modelling with the
comprehensive comparative study of influencing factors and suggested policy
approaches, the article combines theoretical research with practical implemen-
tation to fill a gap in the existing literature.
The remainder of this paper is organised as follows. Section 2 provides a
brief overview of the existing literature concerning both inter-jurisdictional com-
parison of factors affecting PV deployment and deployment of PV in multi-
occupancy buildings. Section 3 compares the two countries in views of climate,
building stock, costs and subsidies, and relevant regulatory arrangements. The
optimisation model used in the study is introduced in Section 4, along with
the details of the building being modelled and associated data. In Section 5,
we present the outputs of the modelling, including cost-optimal PV design and
consequent energy bill savings for each location and their dependence on specific
influencing factors. In Section 6, we draw some conclusions, make some tenta-
tive policy suggestions for increasing PV deployment in this building sector, and
identify some potential topics for future research.
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This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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2. State of the Art and Progress Beyond
In this section, we present a selective review of the literature pertaining to
(Section 2.1) the deployment of shared PV in multi-occupancy residential build-
ings and (Section 2.2) between-country comparison of the conditions (climatic,
economic and regulatory) impacting PV deployment. Section 2.3 summarises
the context for our research and highlights the novelty of this paper.
2.1. PV Sharing in Buildings
Deployment of shared PV in multi-occupancy buildings is of increasing im-
portance as the twin drivers of reducing carbon emissions and constraining elec-
tricity costs favour an increased market share of decentralised renewable elec-
tricity generation combined with local self-consumption. While deployment on
stand-alone housing was initially supported, in some Australian and European
jurisdictions, by subsidised tariffs for export, self-consumption is now likely to
be more financially attractive to households [5].
Although some countries have adapted their legislation to support PV shar-
ing concepts, there are still multiple barriers hampering further PV uptake in
different countries [6, 7, 8], including Australia [9], where a range of issues spe-
cific to apartment buildings have held back deployment in this building sector
(which houses 13 % of families [10]) despite a significant opportunity [11]. Even
in northern European regions, where PV may not achieve grid parity for indi-
vidual single-family buildings, shared PV systems can achieve grid-parity when
being implemented in energy communities (ECs) and efficiently combined with
electrical heating systems [12]. This aligns with broader findings [13] that a PV
community approach can be decisive for the profitability of PV. Specifically, PV
sharing across ECs is shown to add value [14] at the medium scale and increase
the cost-optimal PV potential for larger communities [15].
Shared use of PV enables higher self-consumption through aggregation of di-
verse household loads [16, 17], giving multi-occupancy buildings a profitability
advantage, even without subsidy [18, 19]. Self-consumption can be further en-
hanced through co-location with battery storage [20], although profitability of
battery storage is still hard to achieve [21].
Drivers of residential PV deployment are diverse, however, and include envi-
ronmental, social and policy influences [22] as well as financial motivations.
Besides the issues outlined above, future increased diffusion of PV in general -
and PV sharing concepts specifically - will depend on the development of ap-
pealing business models [23, 24, 25].
2.2. Comparative Literature
Besides the general literature focusing on PV integration and sharing in
buildings and ECs, there is a limited selection of studies comparing drivers and
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barriers for diverse deployment levels for renewable energy, and especially dis-
tributed PV, between different countries.
A number of articles describe the impact of solar irradiation on the profitability
of PV in different geographic locations, either within a country [26] or between
different European countries [27]. Others focus on financial factors, assessing
the profit-optimal PV size for European locations with similar climate but dif-
ferent financial settings [28].
Some authors have made global comparisons, combining climatic and financial
considerations. Rodrigues et al. [29] identify economically optimal locations
for PV system in countries worldwide, taking into account country specific ra-
diation, subsidies and prices. Similarly, Keiner et al. [30] determine the cost-
optimal technology mix for residential PV prosumers across all global regions,
though the authors acknowledge that not all jurisdictional differences were ac-
counted for.
Other researchers have compared the impact of different regulatory frameworks
on PV deployment. Romero et al. [31] examine the characteristics of sustainable
ECs and relevant legal support frameworks to explore the lack of sustainable
ECs in Spain, relative to Germany. These factors are explored for European
countries [32, 33, 34] and beyond [35]. A broad but compact overview of the
global regulatory environment for PV sharing concepts, specifically in apart-
ment buildings, is provided by [5], while [36] present a comprehensive analysis
of the legal and regulatory frameworks available for collective ECs in nine EU
countries.
2.3. Contribution
The studies discussed above comparing PV implementation and PV shar-
ing in different countries have focused either on the underlying legal regulatory
(support) framework or on the techno-economic implications of different climatic
conditions. In contrast, this study provides a holistic approach to comparing
country-specific factors influencing PV diffusion in the growing multi-occupancy
residential building sector. The influencing factors considered in this study are
(i) climatic conditions, (ii) costs, tariffs and subsidies, (iii) type of heating and
cooling appliances, (iv) residential building stock and (v) governance arrange-
ments and regulatory environment.
Moreover, this study not only provides a theoretical comparison between the
influencing factors in two contrasting countries, but also presents the results of
a case study for a small multi-apartment building of a type commonly found
in the housing stock of both countries (Australia and Austria). The impact of
the different exogenous influencing factors on the profitability and the optimal
installation capacities of shared PV are quantified. These results are presented
in the context of the differences and similarities between the two countries, and
the policy implications are discussed.
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This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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3. Exogenous Influencing Factors to PV Implementation
In this section, we discuss the range of exogenous factors that influence, di-
rectly or indirectly, the take-up of PV in the residential building sector. Factors
including climate, PV capital costs and electricity tariffs directly influence the
financial costs and benefits of PV deployment, while indirect influencing factors
include the electricity market structure and regulatory regime, the age, design
and construction of the housing stock, and arrangements for governance and
ownership of housing.
3.1. Climate
Climatic conditions have a significant impact on both the energy yield from
a PV system (and, therefore, the cost of generated energy) and on the size
and temporal distribution of energy demand for heating ventilation and cooling
(HVAC). The highly dissimilar climates of Australia and Austria are described
below and key metrics are compared in Table 1.
Australia’s large land mass (approximately 7 690 000km2) spans over 30 degrees
of latitude and over 40 degrees of longitude, while its 34000 km of coastline is
strongly influenced by ocean currents. Consequently, its climate is highly vari-
able and includes large hot arid and semi-arid areas, pockets of Mediterranean
and even Alpine climate, and tropical, sub-tropical and oceanic regions that in-
clude the main population centres. This study is focused on Sydney, Australia’s
most populous city (with over 5 million people, 21 % of the national population),
which has an average annual global horizontal irradience (GHI) of 1700kWh/m2,
at the midpoint of the national range of 700 kWh/m2to 2700 kWh/m2.
Austria is a much smaller country with a surface of a little less than 84 000 km2
located in Central Europe. Outside the mountain regions, therefore, the tem-
perate and humid climate can be considered relative homogeneous, with annual
solar exposure in the range of 1000 kWh/m2to 1300 kWh/m2. Data for the cap-
ital city Vienna shows that within the last 40 years, the temperature has never
exceeded 40 C in summer, while in winter temperatures well below 10 C are
recorded2.
Table 1 shows key climate metrics for the two cites while Figure 1 shows the
monthly variability of temperature and solar insolation. Note that, although
Vienna’s climate has much greater annual variability than Sydney, with winter
minimum temperatures well below zero, average and maximum summer tem-
peratures only differ by a few degrees between the two cities. However, Sydney
enjoys average daily solar exposure almost 50 % higher than Vienna and has
twice the average annual precipitation.
2Weather data for Vienna originates from the weather station Vienna - Hohe Warte (202 m
above sea level). These values deviate from the data of the weather station Wien-Innere Stadt
in the city centre, which are higher due to the ’heat island effect’ of cities.
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This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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Metric Unit Sydney Vienna
Mean annual maximum temperature C 28.9a33.6b
Mean annual minimum temperature C 8.9a
12.4b
Mean annual precipitation mm 1148a643b
Mean annual snowfall cm 0 72b
Mean maximum windspeed km/h 120a107b
Mean daily global horizontal irradience kWh/m24.55c3.10d
Table 1: Key climate data for Sydney and Vienna
a29 yr average to 2019[37]
b68 year average to 2018[38, 39]
c29 yr average to 2019[40]
dRepresentative year[41, 42]
Figure 1: Average monthly Global Horizontal Irradience (GHI) in kWh/m2and average
monthly temperature for a representative year in Vienna and Sydney.
3.2. Costs and Tariffs
In this section, the financial parameters likely to affect PV deployment in
Australia and Austria are compared, specifically electricity prices, PV system
costs and access to finance.
3.2.1. Retail Market and Tariffs
Australia’s residential customers are able to choose from a diverse and con-
fusing array of tariffs [43]. These include competitive offers with flat or time
of use volumetric rates, as well as a Default Market Offer (DMO) regulated to
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This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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protect customers unable or unwilling to engage in regular switching between re-
tailers. In 2018, typical flat rate volumetric tariffs were in the range 12 c/kWh3
to 24 c/kWh [45]. Fixed charges for customers are high, due in part to high
network charges which comprise around 44 % of residential electricity bills [46].
Similarly to Australia, Austria also offers a variety of retail electricity tariffs
[47]: (i) flat rates with fixed volumetric rates over a specified time horizon, (ii)
indexed tariffs based on the market value of electricity (e.g. based on the Aus-
trian electricty price index), (iii) smart tariffs - also called time of use tariffs or
(iv) interruptible tariffs. In Austria, flat rate tariffs do not differ significantly to
the Australian ones and lie between 19.5 c/kWh [48, 49] and 20.7 c/kWh [50].
However, the fixed component of residential tariffs are significantly lower than
in Australia, due to lower network charges comprising only around 25% of bills.
In the absence of subsidised Feed-In-Tariffs (FiTs) (see Section 3.5), Australian
retailers also offer market FiTs, with some states publishing recommended rates.
In New South Wales (NSW), FiTs as high as 12 c/kWh are still available to res-
idential customers, although these are likely to be bundled with relatively high
volumetric consumption rates and FiTs of 3.2 c/kWh - 7.0 c/kWh are more com-
mon. FiTs are generally not available to commercial customers, which include
apartment buildings that have aggregated their energy demand through an em-
bedded network to utilise a single grid connection point. In Austria, retailers
also offer market FiTs for surplus PV electricity feed-in. These tariffs vary with
the retailer, but lie below the price for retail electricity purchase [51], while, for
some customers, a fixed-rate, subsidised FiT is also available, as described in
Section 3.5.
3.2.2. PV System Costs
Although PV module costs are relatively homogeneous internationally, bal-
ance of system and installation costs show some variation. Moreover, installa-
tion costs are sensitive to system size and to building-specific factors. In NSW,
typical installed cost for residential (5 - 10kW) PV systems is 1100 EUR/kW,
including taxes [52, 45], falling as low as 750 EUR/kW after government subsi-
dies (Section 3.5). By contrast, installed system costs in Austria are significantly
higher at around 1570 EUR/kW without subsidies [3, 53], and 1270 EUR/kW
with subsidies [54] taken into account (Section 3.5).
For a range of technical and organisational reasons, costs for retrofitting
infrastructure to apartment buildings are significantly higher than those for
installation on new buildings, with anecdotal evidence of 50 % increases to per-
Watt installation costs due to building height, roof types and wiring require-
ments for apartment buildings [11]. Meanwhile, in many older buildings, PV
3All financial quantities are quoted in Euros and Euro cents, based on an exchange rate of
AUD1.00 = EUR0.58 [44]
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deployment must compete for investment funding with other sustainability up-
grades, including increasing the efficiency of lighting, pumps and other loads or
improving building thermal efficiency, which may give higher returns on invest-
ment. Even so, only approximately 1 % of the floor area of European buildings
undergoes any type of sustainability retrofit each year [55].
3.2.3. Finance
The availability and cost of finance is dependent on the PV business model
[56] and, to some extent, on the ownership and governance arrangements of the
building. Where the building has a single owner (more common in Austria than
Australia), the owner can make the PV investment and ’provide’ electricity to
residents. For buildings under multiple ownership, the owners’ community or
strata body can make the investment, provided split incentives between owner-
occupiers and investment owners can be overcome. However, in Australia, fi-
nance costs may be higher for strata bodies than for individual owners as they
cannot use the building as collateral for a secured loan. In all these cases, the
appropriate discount rate to apply to the investment cost is dependent on the
specific circumstances of the building owner or owners’ community, including
availability of reserves and access to loans, as well as on their appetite for risk
given uncertain future electricity tariffs. Alternatively, a third party energy
retailer or solar company can invest in the PV system and sell the generated
electricity to residents (often under a power purchase agreement(PPA)) or (in
Austria) lease the system to the building owners or residents.
3.3. Housing
In this section, a comparison of the characteristics of the residential housing
stock of Australia and Austria is presented, along with a brief outline of the
dominant ownership models.
3.3.1. Building Stock
The prevalent residential building types in these two countries reflect their
different population densities. Although 87% of Austria’s nearly 2 million resi-
dential buildings in 2011 were detached houses, more than half of the dwellings
were in buildings containing three or more units. In Australia, by contrast, 73 %
of dwellings are detached houses, and only 14 % are apartments. Nevertheless,
while Austria’s 2.3 million dwellings in multi-occupancy buildings house 46 % of
the population, Australia’s 1.4 million apartments house 10 % of the Australian
population and this proportion is growing, with less than 60 % of residential
building approvals in 2019 being for houses [57].
In both countries, a large proportion of apartments are in smaller, low-rise build-
ings. In Austria, 71 % of apartment buildings contain ten or less apartments,
while in Australia 60 % of apartments were in buildings of less than four storeys
in 2016 (although higher-rise buildings are more common in recent construc-
tion). This is significant for PV deployment, as low-rise apartment buildings
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This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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have greater per-dwelling solar rooftop potential [58].
Dwellings Australia
(2016)[10]
Austria (2011)[59]
Detached Houses / buildings
with one dwelling
71 % 47 %
a
Semi-detached houses / build-
ings with 2 dwellings
13 %
Apartments / buildings with 3 or
more dwellings
14 % 53 %
Approximate Total Dwellings 9 705 500 4 300 000
Table 2: Proportion of dwellings by building type in Australia and Austria
aIn Austrian data [60], there is no distinction made between buildings with one or two
dwellings.
3.3.2. Building Age and Energy Use
In general, the heat load of dwellings in multi-occupancy buildings is sig-
nificantly lower than for single-family buildings, due to smaller external wall
(and ceiling and floor) areas resulting in lower heat losses. However, the apart-
ment building stock in both countries is diverse in age, design and construction
and, while some data is available for Austria, there is little quantitative in-
formation available about the Australian building stock. Many of Australia’s
older apartment buildings are two- or three-storey ’walkups’, often brick-built,
while recent years have seen an increase in medium- and high-rise buildings of
more modern construction. However, many of these newer buildings have been
found to have construction and safety defects, with one study finding that 97 %
of apartment buildings constructed in NSW between 2003 and 2018 have at
least one defect, predominantly related to waterproofing and fire safety systems
[61]. These findings have impacted demand for new apartments and, along with
reduced population growth and the impact of the COVID-19 pandemic, have re-
sulted in a (likely temporary) decrease in the rate of apartment construction [62]
In Australia, all new residential buildings are subject to minimum country-wide
energy efficiency requirements, detailed in the National Construction Code, as
well as state-level performance standards. These are commonly verified through
the Nationwide House Energy Rating Scheme (NatHERS) which rates thermal
comfort on a scale of 0 to 10 stars. The average star rating of apartment build-
ings constructed in NSW increased from 5.7 to 6.4 between 2016 and 2020,
while houses built in the year to May 2020 average 6.0. These newer apartment
buildings have an average annual cooling load of 6.2 kWh/m2and heating load
of 8.8 kWh/m2, but this average figure masks high variability with 20% of new
apartment buildings rated 5.0 or less [63]. There is little empirical data available
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This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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for older buildings, but anecdotal evidence suggests star ratings of 3.0 are not
uncommon, with an equivalent annual heating and cooling load in Sydney of
27.0 kWh/m2.
Because of Austria’s cooler climate, specific heating load for newer buildings
in Vienna are around seven times the average heating loads for Australia, as
shown in Table 3, which also demonstrates how the specific heating load of
Austrian apartments and houses varies with the construction period [64].
Specific heat load in kWh/m2/yr
Construction
period
Multi-apartment
buildings
Single-family
buildings
before 1919 145 245
1919-1944 160 270
1945-1960 145 265
1961-1970 125 235
1971-1980 115 225
1981-1990 80 180
after 1990 60 160
Table 3: Austrian building standard for specific heat load in apartments and houses, by
construction period [64].
3.3.3. Heating and Cooling
Since HVAC can account for a significant proportion of residential loads,
consideration of the energy sources and technologies used in each country is
necessary. In Austria, space heating in multi-apartment buildings is predom-
inantly supplied by gas [65], while electric cooling is rarely deployed. While
gas heating also exists in some older Australian apartment buildings, and many
households still have no heating provision, split system electric air-conditioning
now predominates, in part because of its ability to provide cooling in addition
to heating services.
3.3.4. Building Ownership
The ownership and governance arrangements for multi-occupancy buildings
affect the availability of finance and the decision-making process for building
upgrades, including installation of sustainability infrastructure such as rooftop
PV. In particular, investment decision making can be more challenging when
multiple owners are involved and can be further complicated by split incentives
between owners and residents. Similar ownership arrangements exist in both
these countries, but the proportion of apartments governed under each structure
diverge.
Common types of sole ownership include:
Private entity: Owned by private individual or company.
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Social housing: Owned by government housing authority.
Cooperative or community housing: Owned by not-for-profit housing co-
operative or community group.
Under sole ownership, the owner is able to develop the property, but may lack
commercial incentive to invest in a PV system or other sustainability infras-
tructure where the benefit rather flows to tenants. Conversely, for social or
community housing, sustainable investment can create benefit for (sometimes
vulnerable) tenants.
Although there are a number of possible arrangements to facilitate ownership of
an apartment building by multiple owners, the majority of shared properties in
both these countries are owned under Strata Title or Condominium Ownership,
which entails joint ownership of the building structure and grounds, so that
development of or changes to the building structure require agreement between
owners. In Austria, this requires a majority of owners to agree, while, in Aus-
tralia, the details of governance arrangements (including the type of majority
needed) vary between states and the type of proposed development [11]. New
apartment buildings are usually owned and built by a single developer who has
the opportunity to invest in solar prior to establishing the strata body or selling
individual apartments, without the complexity of collective decision making.
PV deployment is therefore likely to be easier to achieve for new buildings than
for brownfield sites.
In both countries, approximately two thirds of apartments are rented4. How-
ever, looking at rentals across all housing types, in Austria, 17 % of tenants are
in social housing, 39 % in cooperative housing and only the remaining 44 % pay
rent to a private landlord [67]. In contrast, 82 % of Australian tenants pay rent
to a private landlord or real estate agent, while only 12 % live in social housing
and 2 % rent from a co-operative or community organisation [10].
3.4. Regulation relating to shared PV
This section compares regulatory and legislative environments in the two
countries that affect PV implementation in apartment buildings. While Austria
has enacted specific legislation to enable PV sharing in residential buildings, in
Australia, PV sharing is allowed by omission but faces a range of regulatory
barriers.
Different technical arrangements are possible to facilitate deployment of PV
to meet apartment energy loads [17]:
4In Australia, 32 % of apartments are owner-occupied and 66 % are rented (excluding ’Not
stated’ and ’Not applicable’ categories) [10] while, in Austria, 26 % of dwellings in buildings
of three or more dwellings are owner-occupied and 67 % are rented [66].
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(1) Individual PV systems for each apartment: Applying PV generation to
the energy used in a single apartment is analogous to the arrangement
in houses, and has been implemented for some new build and retrofitted
buildings in Australia, but is relatively rare - though theoretically permit-
ted - in Austria. Where the building is under multiple ownership, how-
ever, there is administrative complexity around the equitable allocation
of shared roof resources to individual apartment owners and, regardless of
ownership arrangements, the use of multiple small systems incurs higher
investment costs and results in lower self-consumption than a shared sys-
tem. In Australian strata buildings, this type of deployment requires a
’strata bylaw’ to be passed by the building owners.
(2) Shared PV system distributed ’behind the meter’: In Austria, amend-
ments to the Electricity Industry and Organization Act [68], which came
into force in 2017, specifically allow the implementation of behind-the-
meter shared PV systems in buildings with more than one apartment. In
this arrangement, residents continue to buy grid electricity from a retailer
through their usual meter and purchase solar generation through a sec-
ondary distribution and metering system (which increases the investment
cost). In Australia, this arrangement is allowed provided the sale of the
solar energy is by an authorised energy retailer or arranged under a PPA.
(3) Shared PV system connected through an embedded network (EN): If a
shared PV system is connected within an EN or microgrid, the generated
energy can be bundled with grid electricity (purchased at commercial tar-
iffs5through the main grid connection point, leveraging the aggregated
building demand) and sold to apartment residents. If the EN is owned
and operated by the building owners, the dual benefits of lower grid elec-
tricity cost and cheap PV generation can be passed on to apartment owners
and, potentially, residents. However, changes to Australian retail energy
law, focused on extending competitive electricity market access to apart-
ment residents, set a high administrative barrier to establishing an EN.
Although allowed under the 2017 legislation, the authors are not aware of
any existing embedded networks in Austrian apartment buildings.
(4) Peer-to-peer (P2P) energy trading: Where apartments have their own in-
dividual PV system (as in (1) above) or an allocated portion of a shared
system, they may be able to trade their generated energy with other apart-
ment residents. This trading will either utilise the distribution grid in-
frastructure (which, in Australia, incurs high Distribution Use of Service
charges) or requires an embedded network (with the difficulties outlined in
(3)), which has been trialled in one Western Australian apartment building
[69]. In Austria, P2P trading is allowed within buildings, while trading be-
5Commercial tariffs generally have lower volumetric rates than residential, although they
may be combined with peak demand charges.
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tween multiple buildings is currently the subject of pilot projects and the
legislative framework to enable P2P trading between multiple buildings is
under development6.
3.5. Government Incentives for PV Deployment
In both Australia and Austria, policy measures used to support PV deploy-
ment on residential buildings, have included sudsidised Feed-In-Tariffs (FiTs)
and capital subsidies [3, 45]. However, in Australia, the high FiTs (around
35 c/kWh) funded by state governments to stimulate widespread deployment of
residential PV have now been closed, bar some legacy arrangements, although
market FiTs are still available for solar households (see 3.2.1).
In Austria, ’tariff subsides’ (FiTs) are mandated annually, valid nationwide
and applied for 13 years [54, 72]. The relevant body, Oemag, buys exported
rooftop PV generation with a 2020 tariff of 7.67 c/kWh[54, 72]. The FiT is
only available for PV systems between 5kW and 200 kW [73] and up to a total
annual subsidy budget of 8 000 000 EUR, allocated according to the proportion
of self-supply and the time of application [73, 72]. For owners dissatisfied with
Oemag’s tariff offer, or having PV systems below 5 kW or above 200 kW, or
if the Oemag budget is fully utilised, there is the option of selling surplus PV
to the retailer7as described in Section 3.2.1. The low FiT rates in both coun-
tries act as an incentive for PV systems designed to maximise self-consumption,
which includes shared PV systems in apartment buildings.
Both countries also provide investment subsidies towards the purchase and in-
stallation costs of a residential PV system. In Australia, these take the form
of Small-scale Technology Certificates (STCs) [74]. One STC is generated for
each MWh of renewable energy assumed to be generated by the PV system and
can be traded at a market rate, around 23 EUR [75], which is equivalent to a
discount of approximately 35c/W on the installation price of a 10 kW PV sys-
tem in Sydney. In Austria, the federal government provides a grant of 27.5 c/W
for rooftop systems up to 5 kW or 25 c/W for systems under 100 kW, up to a
maximum 30 % of the total investment cost [3].
Australian state and territory governments also operate a number of incentive
schemes for residential PV (and battery) deployment, but these are generally
short-term and often exclude multi-occupancy dwellings. In Austria, besides the
nationwide valid subvention schemes, it is possible for federal states to apply in-
dividual incentive schemes for PV and/or battery storage [76]8. Such individual
incentives are provided for business as well as residential buildings.
6based on the European document Clean Energy for all Europeans Package and more
specifically the Renewable Energy Directive [70] and the Electricity Market Directive [71].
7End-users can access a FiT either from their retailer or from Oemag, not both.
8For example, in Lower Austria there is the possibility of subsidising a photovoltaic system
in combination with thorough building renovation.
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3.6. Observed effects of direct and indirect influencing factors
In 2018, Austria had deployed less than 1.5 GW of PV in total, almost all
of it connected to the distribution network [3]. In 2016988.3 % of PV was de-
ployed on the roof or the facade of buildings [77]. Although it is not known what
proportion of this is on residential buildings, the total amount of residential PV
is likely significantly below 1.3GW. By contrast, 51% of Australia’s 17.6 GW
of installed PV is on residential buildings [4]. This discrepancy is likely the
result of multiple factors, including Australia’s higher solar resource and con-
sequent PV yield and lower PV investment costs. However, a significant factor
in Australia’s high residential solar deployment is the country’s proportion of
stand-alone or semi-detached dwellings, driven by low population density com-
pared to Austria and many other countries, and comparatively low proportion
of rental properties.
Whilst, for houses (whether detached, semi-detached or terraced), there is a
clear correspondence between a roof area and the dwelling below (which are often
both owned by a single household), apartment buildings entail more complexity,
in both the physical and governance relationships, which make PV deployment
more challenging. Austria has legislated to support shared PV systems in these
buildings, though without, to date, substantive changes to the deployment rates,
in part because of organisational and bureaucratic barriers and remaining reg-
ulatory uncertainty. Meanwhile, Australia’s reliance on a regulatory structure
that favours individual market participation over co-ordinated engagement has
also failed to deliver deployment in this sector.
9Prior to the amendment of the Electricity Industry and Organization Act which allowed
PV sharing concepts in multi-apartment buildings.
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4. Model and Method
The previous section highlighted both differences and similarities between
the climatic conditions, building stock (building standards), costs and tariffs and
regulatory contexts of these two countries. The combined influence of these fac-
tors results in high residential PV penetration in Australia compared to Austria,
but low PV deployment on apartments in both countries. The aim of the follow-
ing analysis is to identify the impact of these exogenous factors on cost-optimal
PV installation capacities and on residents’ financial benefits, expressed as net
present value (NPV). The optimisation model used to conduct this analysis,
with the objective of maximising the residents’ NPV, is introduced in Section
4.1. In Section 4.2, the building under investigation is presented and parameters
for the case studies are defined. Section 4.3 describes the load and PV genera-
tion data used for the study, Section 4.4 describes the heating and cooling loads
and Section 4.5 sets out the financial settings for the analysis.
4.1. Optimisation Model
An optimisation model is set up to maximise the building residents’ NPV
over a specified time horizon. In the course of the NPV maximisation it is de-
termined whether installing a PV system has a positive impact on the residents’
or building owners’ finances. Where PV system installation is profitable, the
cost-optimal PV system capacity is determined. This analysis concerns the ag-
gregated financial outcomes for all apartment residents; details of how costs and
benefits are distributed between different stakeholders are beyond the scope of
this article.
The NPV calculation in its original form (Equation 1) juxtaposes upfront in-
vestment costs I0(e.g. for installation of PV systems) with the sum of properly
discounted future cash-flow streams. A cash flow stream is defined as annual
revenues R(y)10 minus annual costs C(y) (for heat, electricity and cooling as
well as technology maintenance costs).
N P V =I0+
Y
X
y=1
(R(y)C(y))
(1 + z)y(1)
Significant factors for the NPV calculation include the different cost terms,
the discount rate zand the time horizon of investigation Y.
The optimisation model is subject to a variety of constraints, of which the most
important are the necessity to supply the electricity load, heating and cooling
demand at all times:
10In this specific implementation, R(y) is always zero as the model assumes a FiT of zero
(Section 4.5).
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The underlying electricity load (excluding HVAC) can be supplied by PV
generation (where a PV system is determined to be profitable and has
therefore been installed) or by grid-purchased electricity.
For a building with electric heating, the conventional electricity load is
enlarged by the heating demand; for gas heating the cost of gas energy
demand is calculated separately.
For a building with cooling demand, the conventional electricity load is
enlarged by the cooling demand.
The PV system is modelled (Equation 2) such that the PV generation, which
is determined by the installed PV capacity (optimisation variable) and the
location-specific climate data, is applied to the electricity load epv2eload (t, y)
(which may include HVAC load), with any surplus PV generation fed into the
grid epv2grid (t, y).
X
d
Ppv(d)·I RRsolar (d, t, y) = epv 2eload(t, y) + epv2grid (t, y) (2)
The model determines the cost-optimal energy flows as well as the cost-
optimal PV capacity. Where a PV system is found not to be profitable, the
optimisation model would determine the optimal PV capacity to be zero. Spe-
cific variable/parameter definitions are to be found in Table 4.
Abbreviation Explanation Classification
C(y) Annual costs Variable
I0Upfront investment costs Variable
IRRsolar(d, t, y ) Solar irradiation per direction,
year and timestep
Input data
N P V Net present value Optimisation objective
Ppv Cost-optimal PV capacity Optimisation variable
R(y) Annual revenues Variable
YTime horizon in years Input data
dDirection
(North/South/East/West)
-
epv2eload (t, y) PV electricity for electricity load
coverage
Optimisation variable
epv2grid (t, y) Surplus PV electricity feed into
the grid
Optimisation variable
tTimestep (35040 quarter-hours
per year)
Control variable
yYear Control variable
zInterest rate Input data
Table 4: Nomenclature
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4.2. Building Set-Up and Case Study Definition
In order to quantify the impact of a variety of factors on the profitability
of residential PV sharing and according optimal PV system sizes, a simulated
three-storey multi-apartment building with nine residential units (typical of the
building stock in both Sydney and Vienna) is chosen for investigation. The
building specifications (Table 5), including dimensions, building quality and
roof slope (as described in Appendix B) are assumed equal in both locations,
while variable characteristics, including the type of heating system implemented
and jurisdictional-specific electricity tariffs and PV installation costs are applied
as appropriate. The model parameters are illustrated in Figure 2.
Metric Vienna Sydney
Basic electricity loadaNine real-measured apartment profiles
HVAC Gas heating only Electric heating and cooling
Specific heat load 145 kWh/m2/yr N/A
Array tilt 30 C 30 C
Array orientation South North
Table 5: Characteristics of Sydney and Vienna buildings used in the optimisation model
aexcluding HVAC
Figure 2: Case study illustration
4.3. Load and Generation Data
The nine residential units in the building are allocated real measured apart-
ment household load profiles at a 15-minute resolution. Excluding HVAC loads,
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the likely difference between household demand of apartments situated in Vi-
enna and Sydney is considered to be insignificant compared to the impact of
other household and apartment characteristics. The same data has therefore
been used for both locations, sourced from a datset of 30-minute interval load
data for 13 700 NSW households [78]. Load profiles were filtered for apartments
(as opposed to houses) and for households without air-conditioning (heating or
cooling) infrastructure, as indicated by the associated survey data. Moreover,
to ensure the analysis remains robust to the diversity of apartment load profiles
within the dataset [79], three selections of nine buildings (identified below as
buildings b1,b2 and b3 ) are used independently as inputs to the model. Com-
mon property loads for this type of apartment building are usually very low,
often comprising only a few light fittings [17], and have been disregarded for
this analysis. The average daily load profiles for each building are shown in
Appendix A and annual electricity demand for each building is shown in Table
6.
Abbreviation Description Annual electricity load
b1 Multi-apartment building 1 27 289 kWh/yr
b2 Multi-apartment building 2 23 771 kWh/yr
b3 Multi-apartment building 3 28 310 kWh/yr
Table 6: Abbreviations and total annual load for the three buildings modelled
The solar PV generation for each location is calculated per kW-peak, using
the PVWatts Model in NREL’s open-source software tool SAM [80]. For Syd-
ney, a weather file (solar irradiation, temperature and wind speed) derived from
Bureau of Meteorology data for a ’Reference Meteorological Year’ was used [81],
while the weather file for Vienna used data for a representative year from the
database of the Energy Economics Group, TU Wien [41] and ZAMG (Austrian
metereological institute) [42]. The PV array modelled11 is orientated at 180
and 0 for Vienna and Sydney, respectively, with modules tilted at 30 (which
is approximately the optimum array tilt to maximise annual energy generation
for both cities, despite their different latitudes).
The annual solar PV generation determined by SAM is 780kWh/kWdc and
1409 kWh/kWdc in Vienna and Sydney, respectively (equivalent to 936 kWh/kWac
and 1691 kWh/kWac ). Note that the system generates 81 % more energy in
Sydney than in Vienna, due to the combined effect of higher solar exposure and
higher solar elevation at lower latitude.
11SAM default system settings were used for the study, i.e. DC to AC ratio of 1.2, inverter
efficiency of 96 % and total losses of 14 %.
20
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4.4. HVAC Energy Demand
As described in Section 3.3.3, HVAC requirements are very different between
these two cities. In order to explore the impact of this, two scenarios have been
modeled. In the first scenario (Section 5.1) the same energy requirements are
assumed in both countries, with no HVAC load included (pure conventional elec-
tricity load only). In the second scenario (Section 5.1), a gas-fuelled heating load
is considered in the Austrian context, while the Sydney apartment load profiles
are increased to allow heating and cooling using split-system air-conditioning.
This additional HVAC load profile is derived using the SGSC dataset (Section
4.3) as the difference between the average load profile for apartments with split
system air-conditioning and the average load profile for apartments with no
air-conditioning. The resultant profile (Figures A.13 and A.14), shows both
summer and winter HVAC load, with higher morning and evening peaks in win-
ter. This average HVAC load has been added to each apartment load for the
second scenario.
4.5. Financial Parameters
Table 7 shows the location-specific cost parameters used as inputs to the
model. Note that PV investment costs include currently available subsidies in
each country (Section 3.5); although these subsidies are expected to be phased
out over time, customer investment costs are unlikely to increase substantially as
capital costs are also expected to decline. Sensitivity to removal of investment
subsidies (without the benefit of reduced capital costs) is shown in Section
5.5. Although modest residential feed-in tariffs are currently available in both
countries, policies to support self-consumption and low (or negative) wholesale
costs as PV penetration increases may see them phased out over time. Since
the focus of this analysis is on shared PV for self-consumption, zero payment
for export has been assumed.
By using identical building characteristics (size, thermal properties, roof
form, basic electricity load) for both locations, the impact of different exoge-
nous country-specific factors on the profitability of PV systems and optimal
installation capacities can be quantified.
21
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Description Costs
Vienna Sydney
PV System
PV investment costs 1270 EUR/kW 750 EUR/kW
PV maintenance costs 60 EUR/yr 60 EUR/yr
PV cleaning costs 2.5 EUR/m2/yr 2.5 EUR/m2/yr
Electricity Tariff
Volumetric charge 0.20 EUR/kWh 0.17 EUR/kWh
Fixed retail charge 110 EUR/yr 183 EUR/yr
Feed-in tariff 0.00 EUR/kWh 0.00 EUR/kWh
Gas Tariff
Volumetric charge 0.05 EUR/kWh no gas heating
Maintenance gas heating 150 EUR/yr no gas heating
Other
Discount ratea6 % 6 %
Time horizon 20 years 20 years
Table 7: Financial settings for Vienna and Sydney used in the model
aA discount rate of 6 % is assumed, to allow for inflation and a level of investment risk.
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5. Results - Profitability and Optimal Sizing of PV
This section shows the impact of different exogenous influencing factors on
the profitability and optimal capacities of implementing PV systems by com-
paring results for Sydney, Australia (SYD) and Vienna, Austria (VIE).
The impact of exogenous influencing factors is quantified by first determining
the cost-optimal PV system capacities for the individual case studies, along with
the assessment of the achievable reductions in the energy bills, without heating
or cooling loads (’noHVAC’) in Section 5.1. The impact of including appro-
priate heating and cooling (’HVAC’) loads is then shown in Section 5.2. The
impacts of differential solar exposure and retail electricity tariffs are explored
in Sections 5.3 and 5.4 respectively, and sensitivity to removal of investment
subsidies is examined in 5.5.
The cost reduction Cred is calculated as described in Equation 3.
Cred =N P VnoP V N P VwithP V
N P VnoP V
(3)
5.1. Base case: no HVAC
Figure 3 shows the results for cost-optimal PV system implementation in
Vienna and Sydney if heating and cooling loads are not taken into account.
Optimal system size is in the range 4.0 kW to 5.5 kW for Vienna and 6.0 kW
to 7.0 kW in Sydney. This low optimal size, compared to typical system sizes
installed on Australian houses, is due in part to the lower household load of
apartments [79], but is also a consequence of modelling a zero-FiT scenario,
which results in self-consumption of 89 % of PV generation in Vienna and 66 %
in Sydney. Although the Sydney system has lower investment cost, higher an-
nual generation and, therefore, lower energy cost, it is offsetting cheaper grid
electricity than in Vienna, which has the effect of moderating the increase in
cost-optimal system capacity. However, the achievable cost reduction in Sydney
is up to five times that of Vienna. The results show little variation between the
three buildings, suggesting that aggregation of the diverse load profiles within
each buildings largely eliminates random variability between the selected load
profiles.
5.2. Impact of HVAC loads
If heating and cooling loads for each location are considered, the difference
in optimal PV capacity and cost reductions become more obvious, as shown in
Figure 4. For Vienna, it is evident that consideration of HVAC has no impact
on the cost-optimal PV capacities (compared to Figure 3), since the building is
gas heated in this location. However, consideration of (gas) heating costs as well
as electricity costs significantly reduces NPV and, therefore, cost savings due to
PV are significantly reduced as a proportion of total energy costs (Equation 3).
23
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b1-VIE b1-SYD b2-VIE b2-SYD b3-VIE b3-SYD
0
2
4
6
8
10
12
PV Peak Capacity in kW
0
2
4
6
8
10
12
Cost Reduction in %
8.32%
9.29%
8.84%
Figure 3: Cost-optimal PV system size and cost reduction, without consideration of HVAC
b1-VIE b1-SYD b2-VIE b2-SYD b3-VIE b3-SYD
0
2
4
6
8
10
12
14
PV Peak Capacity in kW
0
2
4
6
8
10
12
14
Cost Reduction in %
11.09% 10.85%
11.89%
Figure 4: Cost-optimal PV system size and cost reduction, HVAC considered
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This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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For Sydney, however, addition of HVAC increases the cost-optimal PV ca-
pacity to meet the increased electrical load. As the increased PV generation is
applied to the total (base plus HVAC) load, the proportional cost reductions
are also increased. As shown in Figure 5, addition of HVAC loads increases
the cost optimal PV system size by approximately 2.5 kW or 36 % - 38 % of
the optimal size without HVAC, due to the high proportional increase in load
(Table 8). The increase in proportional cost reduction when applying PV gen-
eration to aggregated Base + HVAC load can be understood with reference to
Figures A.14 and A.16 which show summer cooling loads having a relatively
high daytime component, thereby aligning with peak summer PV generation.
Building HVAC as % of total
electricity load
Increase in optimal PV
capacitiesa
b1 25.9 % 38.4 %
b2 28.6 % 38.1 %
b3 25.2 % 36.7 %
Table 8: Contribution of HVAC to total load and its impact on cost-optimal PV system size
in Sydney
aDifference between PV capacities (with and without HVAC considered) divided by the
base case optimal PV capacity.
b1-SYD-noHVAC
b1-SYD-HVAC
b2-SYD-noHVAC
b2-SYD-HVAC
b3-SYD-noHVAC
b3-SYD-HVAC
0
2
4
6
8
10
12
14
PV Peak Capacity in kW
0
2
4
6
8
10
12
14
Cost Reduction in %
2.47kW
2.53kW 2.47kW
Figure 5: Cost-optimal PV system size and cost reduction for Sydney, with and without HVAC
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This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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5.3. Impact of Solar Irradiation
As discussed in Section 5.1 the relatively small difference in cost-optimal PV
installation capacities in Sydney and Vienna for the default setting is due, in
part, to the higher solar exposure and therefore PV output in Sydney. However,
this result is also affected by differential retail tariffs and PV installation costs.
Therefore, to be able to isolate the influence of the solar irradiation, the retail
electricity prices and PV system investment costs are levelled for Vienna and
Sydney (to the average of the respective costs in both locations). The results
given in Table 9 are calculated with the following levelised costs/prices for both
locations:
Volumetric electricity charge: 0.185 EUR/kWh
Fixed electricity charge: 146.5 EUR/yr
PV system installation costs: 1010 EUR/kW
Cost Reduction (%) Cost-optimal PV
capacity(kW )
HVAC No HVAC HVAC No HVAC
b1 VIE 1.31 2.61 4.85 4.85
SYD 11.12 10.03 8.09 5.85
b2 VIE 1.68 3.56 5.52 5.52
SYD 12.25 11.29 7.94 5.81
b3 VIE 1.82 3.58 6.00 6.00
SYD 11.33 10.33 8.17 5.96
Average VIE 1.60 3.25 5.46 5.46
SYD 11.57 10.55 8.07 5.87
Table 9: Comparison of cost-optimal PV capacity and achievable cost reduction, with and
without HVAC, using levelised electricity price and PV investment costs
Table 9 shows a comparison of the cost-optimal PV system size and pro-
portional cost reductions achievable (with and without consideration of HVAC)
with these levelised costs. Without HVAC, the average optimal PV system size
in Sydney is only 7 % higher than in Vienna, but the average cost reduction
is 10.55 %, compared to only 3.25 % for Vienna. With consideration of HVAC
loads, the average optimal PV system size for Sydney increases to 8.07 kW and
the average cost reduction increases to 11.57% while, for Vienna (with no change
in system size), the average cost reduction falls to 1.6% of total energy costs.
26
This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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5.4. Impact of Electricity Prices
To understand the impact of the volumetric electricity price on achievable
cost savings, the analysis is repeated with the volumetric tariff components in-
terchanged, so that the cost in Sydney is raised from 0.17 EUR/kWh to Viennese
levels of 0.20 EUR/kWh while the Viennese price is lowered to 0.17 EUR/kWh.
The results for the base scenario are summarised in Figure 6 and those with
consideration of HVAC are shown in Figure 7. Table 10 gives an overview of
cost reduction and PV system sizes for both scenarios.
b1-VIE b1-SYD b2-VIE b2-SYD b3-VIE b3-SYD
0
2
4
6
8
10
12
14
16
Cost Reduction in %
Electr. Price 17c/kWh
Electr. Price 20c/kWh
1.42%
1.93%
1.83%
2.17%
1.74%
1.92%
Figure 6: Impact of varying retail electricity prices on the overall energy cost reduction,
without consideration of HVAC
Figure 6, where no HVAC load is considered, shows the 3 c/kWh cost dif-
ference in retail electricity prices results in an overall energy cost reduction
difference between one 1 % and 2 % in most cases. However, it should be noted
that those small cost differences are more significant in Vienna, where achiev-
able cost reductions are in the range 0.5 % - 3 %, than in Sydney where 10.5 %
- 14 % savings are achievable. Thus, the impact of a change in volumetric retail
electricity prices has a greater impact in jurisdictions with limited profitability
of PV than where high cost savings are already achievable due to other factors
such as high solar irradiation.
With HVAC loads considered, the impact of the 3 c/kWh tariff change on
achievable cost savings as a proportion of total energy costs remains at around
2 % in Sydney (Figure 7), although it should be noted that this represents a
smaller impact on absolute savings than for the base scenario. In Vienna, by
contrast, the proportional impact of the 3 c/kWh tariff change is approximately
27
This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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b1-VIE b1-SYD b2-VIE b2-SYD b3-VIE b3-SYD
0
2
4
6
8
10
12
14
16
Cost Reduction in %
Electr. Price 17c/kWh
Electr. Price 20c/kWh
0.73%
1.97%
0.89%
1.94%
2.14%
0.92%
Figure 7: Impact of varying retail electricity prices on the overall energy cost reduction, with
HVAC considered
halved if HVAC is considered, as it has no impact on the cost of the HVAC gas
bill.
Electricity Price
in EUR/kWh Cost Reduction in % Cost-optimal PV
Capacity in kW
HVAC No HVAC HVAC No HVAC
b1
VIE 0.2 0.93 1.85 4.16 4.16
0.17 0.20 0.44 3.22 3.22
SYD 0.2 13.99 12.63 10.10 7.36
0.17 12.03 10.69 9.12 6.59
b2
VIE 0.2 1.24 2.61 4.77 4.77
0.17 0.35 0.78 3.79 3.79
SYD 0.2 15.27 14.07 9.90 7.16
0.17 13.13 11.90 8.94 6.47
b3
VIE 0.2 1.36 2.66 5.25 5.25
0.17 0.44 0.93 4.26 4.26
SYD 0.2 14.15 12.90 10.22 7.46
0.17 12.21 10.99 9.19 6.73
Table 10: Impact of varying the volumetric component of the retail tariff on cost-optimal PV
size and achievable cost reductions
28
This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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5.5. Impact of Higher PV System Costs
Since the PV system investment costs shown in Table 7 include subsidies
per kW of installed PV capacity, this Section examines the differences in opti-
mally installed PV system capacities if PV system costs are considered without
subsidies. This means that in Sydney the PV installation costs are increased
from 750 EUR/kW to 1100 EUR/kW, and in Vienna from 1270 EUR/kW to
1570 EUR/kW.
As expected, the higher the PV system installation costs, the less profitable
PV system installation becomes. As a result, the cost-optimal PV system in-
stallation capacities shrink in this scenario along with the cost saving potential,
in comparison to the default setting with lower, subsidised investment costs.
Figures 8 and 9 show a comparison of optimal PV installation capacities and
consequent cost savings for the scenarios with and without HVAC taken into
consideration. Note that the removal of subsidies significantly reduces optimal
system size and cost savings in both countries, with and without consideration
of HVAC, and that, in Vienna, this results in cost savings below 1%.
b1-VIE
b1-VIE-w/o subs
b1-SYD
b1-SYD-w/o subs
b2-VIE
b2-VIE-w/o subs
b2-SYD
b2-SYD-w/o subs
b3-VIE
b3-VIE-w/o subs
b3-SYD
b3-SYD-w/o subs
0
2
4
6
8
10
12
14
PV Peak Capacity in kW
0
2
4
6
8
10
12
14
Cost Reduction in %
Figure 8: Comparison of optimal PV capacities and cost savings for PV prices with and
without subsidies, without consideration of HVAC
29
This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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b1-VIE
b1-VIE-w/o subs
b1-SYD
b1-SYD-w/o subs
b2-VIE
b2-VIE-w/o subs
b2-SYD
b2-SYD-w/o subs
b3-VIE
b3-VIE-w/o subs
b3-SYD
b3-SYD-w/o subs
0
2
4
6
8
10
12
14
PV Peak Capacity in kW
0
2
4
6
8
10
12
14
Cost Reduction in %
Figure 9: Comparison of optimal PV capacities and cost savings for PV prices with and
without subsidies, with HVAC considered
30
This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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6. Discussion and Conclusion
The quantitative analysis presented above examines the impact of a range
of exogenous factors on the optimum PV system size and the achievable cost
savings for apartment buildings in Australia and Austria.
Climate - perhaps the most obvious difference between these two locations -
has a dual impact. Firstly, the greater solar exposure in Australia increases the
PV energy yield and, combined with lower investment costs in Australia’s ma-
ture PV market, increases the cost-competitiveness of PV generated electricity.
Although, on average, this results in only a 23 % increase in the cost-optimal
PV system size (for the scenarios without HVAC) in Sydney relative to Vi-
enna, the achievable cost-savings are more than four times higher. Secondly,
Sydney’s associated higher temperatures also create a cooling demand that has
some alignment with PV generation and contributes to cost-optimal system
sizes approximately 50 % larger in Sydney than in Vienna (for the scenarios
with HVAC). This result also highlights the significance of the use of split-
system air-conditioning in many Sydney apartments, to provide both heating
and cooling, in increasing year-round electricity demand, though it should be
noted that different outcomes would be obtained in other Australian jurisdic-
tions where either heating or cooling loads dominate.
The influence of Australia’s lower retail electricity tariffs reduces both the
achievable savings and the cost-optimal PV system size (Table 10). The results
suggest that lowering Austrian tariffs to Australian levels (so from 20 c/kWh
to 17 c/kWh) would have a much greater negative impact (proportionally) on
PV cost savings in that country and would therefore likely impede Austrian PV
deployment. Removal of government investment subsidies, without equivalent
market-led capital cost reductions, would significantly reduce PV deployment
in either country and, in Austria, would almost eliminate potential bill savings.
Note also that availability of FiTs for solar export from apartment buildings
would increase the optimal system size and achievable savings.
The impacts of climate, HVAC technology, PV costs, investment subsidies and
electricity tariffs apply to single dwelling buildings as well as to apartments and,
therefore, contribute to the high levels of PV deployment on Australian houses
(which comprise 85 % of residential dwellings) compared to Austria. However,
in Australia, PV deployment on apartment buildings remains very low. This
is due, in part, to investment barriers relating to shared building ownership
(under Strata Title), combined with split incentives between private landlords
and tenants. These barriers might be reduced by changes to tax laws that cur-
rently incentivise short-term property investment over owner-occupation, and
by forthcoming NSW legislatory changes to streamline the approval process for
sustainability retrofits in apartment buildings [82]. Nevertheless, an empha-
sis on energy users’ individual participation in the energy market means that
targetted regulatory support is lacking, both for shared PV ownership and for
31
This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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households acting co-operatively in aggregating their loads to leverage lower
energy costs [11].
In Austria, the investment decision-making barriers are less significant in the
higher proportion of social and co-operative housing. Additionally, there is
explicit regulatory support for ECs within apartment buildings, which allows
shared PV systems, although legislative loopholes and a significant adminis-
trative burden discourage potential EC participants. However, PV deployment
remains low in Austrian apartment buildings, as across the whole residential
sector. It is likely that this can largely be explained by lower PV energy yields
and high investment costs.
Deployment of solar PV for self-consumption in apartment buildings to gen-
erate low-cost, low-emission electricity in close proximity to residential loads
could reduce energy bills for households, ease grid constraints and help reduce
upward pressure on global temperatures. Moreover, in both countries apart-
ment residents are less able to access the benefits of self-generated renewable
energy than occupants of stand-alone housing, which presents an issue of so-
cial inequity. There is therefore a case for policy support to facilitate greater
deployment. Our study suggests that the low penetration of PV in the multi-
occupancy housing sectors of Austria and Australia have different causes and
highlights that, while financial incentives can assist, there are broader regula-
tory barriers to be addressed. Further research, focused on comparative analyis
of policy outcomes across multiple jurisdictions, would create greater under-
standing of the potential solutions.
Author Declaration
We wish to confirm that there are no conflicts of interest associated with
this publication and that there has been no financial support for this work that
could have influenced its outcome.
Declarations of interest: None.
32
This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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Appendix A. Load Profiles
Appendix A.1. Base Apartment Load Profiles (no HVAC)
The load profiles of the three buildings investigated are illustrated as the
mean values for each hour over one year.
2 4 6 8 10 12 14 16 18 20 22 24
Hours
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
Average hourly consumption in kWh
Unit 1
Unit 2
Unit 3
Unit 4
Unit 5
Unit 6
Unit 7
Unit 8
Unit 9
Figure A.10: Apartment load profiles of building b1
Appendix A.2. HVAC load profiles (Sydney)
Figures A.13 and A.14 show average winter and summer HVAC loads derived
from average load profiles for apartments with and without split-system air
conditioning. This profile has been added to each apartment profile to simulate
electrical HVAC loads in Sydney, with the resultant total building loads, with
and without HVAC, shown in Appendix A.3.
Appendix A.3. Total Building Load Profiles
42
This is a preprint: original submitted version. The published version of the article This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A.
Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-
consumption in multi-apartment buildings" is available at DOI: 10.1016/j.apenergy.2020.116309
in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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2 4 6 8 10 12 14 16 18 20 22 24
Hours
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
Average hourly consumption in kWh
Unit 1
Unit 2
Unit 3
Unit 4
Unit 5
Unit 6
Unit 7
Unit 8
Unit 9
Figure A.11: Apartment load profiles of building b2
2 4 6 8 10 12 14 16 18 20 22 24
Hours
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
Average hourly consumption in kWh
Unit 1
Unit 2
Unit 3
Unit 4
Unit 5
Unit 6
Unit 7
Unit 8
Unit 9
Figure A.12: Apartment load profiles of building b3
43
This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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Figure A.13: Winter HVAC Load
Figure A.14: Summer HVAC Load
44
This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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Figure A.15: Total winter load of buildings b1, b2 and b3 with and without HVAC
Figure A.16: Total summer load of buildings b1, b2 and b3 with and without HVAC
45
This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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Appendix B. Building Specifications
The object of investigation is an exemplary multi-apartment building with
nine residential units. The building dimensions are assumed realistically with
an average apartment size of 70 m2. The living area per floor therefore can be
assumed as 210 m2. Approximately 20 %-30 % of the total floor space is reserved
for general areas (staircase, aisle), leading to a building with a total floor area of
266 m2(14 m x 19 m). Based on that, the rooftop area (assuming a roof tilted
with 30 ) can be calculated to be approximately 154 m2in the directions of
North and South, respectively. The total rooftop area is therefore 308 m2.
46
This is a preprint: original submitted version. The published version of the article Fina, B., M. B. Roberts, H. Auer, A. Bruce and I. MacGill (2020). "Exogenous influences on deployment and profitability of photovoltaics for self-consumption in multi-apartment buildings in Australia and Austria." is available at DOI: 10.1016/j.apenergy.2020.116309
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