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

December 2020
Applied Energy 283(7)

DOI:10.1016/j.apenergy.2020.116309

Authors:

Bernadette Fina

Austrian Institute of Technology, Austria, Vienna

Mike B Roberts

UNSW Sydney

Anna Bruce

UNSW Sydney

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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.

Average monthly Global Horizontal Irradience (GHI) in kWh/m 2 and average monthly temperature for a representative year in Vienna and Sydney.

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Case study illustration

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Cost-optimal PV system size and cost reduction for Sydney, with and without HVAC

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Impact of varying retail electricity prices on the overall energy cost reduction, with HVAC considered

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Comparison of optimal PV capacities and cost savings for PV prices with and without subsidies, without consideration of HVAC

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Figures - uploaded by Mike B Roberts

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Content uploaded by Mike B Roberts

Content may be subject to copyright.

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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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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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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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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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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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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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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have greater per-dwelling solar rooftop potential [58].

Dwellings Australia

(2016)[10]

Austria (2011)[59]

Detached Houses / buildings

with one dwelling

71 % 47 %

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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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=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).

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

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 %.

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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.

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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).

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b1-VIE b1-SYD b2-VIE b2-SYD b3-VIE b3-SYD

PV Peak Capacity in kW

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

PV Peak Capacity in kW

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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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

PV Peak Capacity in kW

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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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.

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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

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

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b1-VIE b1-SYD b2-VIE b2-SYD b3-VIE b3-SYD

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

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

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

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

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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

PV Peak Capacity in kW

Cost Reduction in %

Figure 8: Comparison of optimal PV capacities and cost savings for PV prices with and

without subsidies, without consideration of HVAC

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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

PV Peak Capacity in kW

Cost Reduction in %

Figure 9: Comparison of optimal PV capacities and cost savings for PV prices with and

without subsidies, with HVAC considered

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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

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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.

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References

[1] European Commission, Paris Agreement (2020).

URL https://ec.europa.eu/clima/policies/international/

negotiations/paris_en

[2] EPA United States Environmental Protection Agency, Global greenhouse

gas emissions data.

URL https://www.epa.gov/ghgemissions/

global-greenhouse-gas-emissions-data

[3] IEA-PVPS, National survey report of pv power applications in austria 2018,

Report, IEA Photovoltaic Power Systems TCP (2019).

[4] Australian Photovoltaic Institute, Solar pv status - data from the clean

energy regulator (2020) [cited 18.08.2020].

URL https://pv-map.apvi.org.au/historical

[5] A. J¨ager-Waldau, G. Adinolﬁ, A. Batlle, M. Braun, C. Bucher, A. Detol-

lenaere, K. H. Frederiksen, G. Graditi, R. G. Lemus, J. Lindahl,

G. Heilscher, M. Kraiczy, G. Masson, B. Mather, C. Mayr, D. Moneta,

D. Mugnier, J. Nikoletatos, G. Neubourg, G. Platt, A. Reinders, M. B.

Roberts, Y. Ueda, Self-consumption of electricity produced with photo-

voltaic systems in apartment buildings - update of the situation in various

iea pvps countries, in: IEEE PVSC-47.

[6] A. K. Shukla, K. Sudhakar, P. Baredar, R. Mamat, Solar PV and

BIPV system: Barrier, challenges and policy recommendation in in-

dia, Renewable and Sustainable Energy Reviews 82 (2018) 3314–3322.

doi:10.1016/j.rser.2017.10.013.

URL https://www.sciencedirect.com/science/article/pii/

S1364032117313862

[7] D. N. yin Mah, G. Wang, K. Lo, M. K. Leung, P. Hills, A. Y. Lo, Barriers

and policy enablers for solar photovoltaics (PV) in cities: Perspectives

of potential adopters in hong kong, Renewable and Sustainable Energy

Reviews 92 (2018) 921–936. doi:10.1016/j.rser.2018.04.041.

URL https://www.sciencedirect.com/science/article/pii/

S1364032118302508

[8] P. Mirzania, A. Ford, D. Andrews, G. Ofori, G. Maidment, The impact

of policy changes: The opportunities of community renewable energy

projects in the UK and the barriers they face, Energy Policy 129 (2019)

1282–1296. doi:10.1016/j.enpol.2019.02.066.

URL https://www.sciencedirect.com/science/article/pii/

S0301421519301569

[9] A. Tayal, V. Rauland, Barriers and Opportunities for Residential Solar PV

and Storage Markets - a Western Australian Case Study, Global Journal

PREPRINT

of Research In Engineering. 16 (7): pp. 44-58. (2016).

URL https://espace.curtin.edu.au/handle/20.500.11937/50073

[10] ABS, Census of population and housing, Report, Australian Bureau of

Statistics (2016).

URL https://auth.censusdata.abs.gov.au/webapi/jsf/

dataCatalogueExplorer.xhtml

[11] M. Roberts, A. Bruce, I. MacGill, Opportunities and barriers for pho-

tovoltaics on multi-unit residential buildings: Reviewing the australian

experience, Renewable and Sustainable Energy Reviews 104 (2019) 95–110.

doi:10.1016/j.rser.2018.12.013.

URL https://www.sciencedirect.com/science/article/pii/

S1364032118308086

[12] J. Hirvonen, G. Kayo, A. Hasan, K. Sir´en, Zero energy level and eco-

nomic potential of small-scale building-integrated PV with diﬀerent

heating systems in nordic conditions, Applied Energy 167 (2016) 255–269.

doi:10.1016/j.apenergy.2015.12.037.

URL https://www.sciencedirect.com/science/article/pii/

S0306261915016104

[13] B. Fina, A. Fleischhacker, H. Auer, G. Lettner, Economic assessment and

business models of rooftop photovoltaic systems in multiapartment build-

ings: Case studies for austria and germany, Journal of Renewable Energy

2018 (2018) 1–16. doi:10.1155/2018/9759680.

URL https://www.hindawi.com/journals/jre/2018/9759680/cta/

[14] B. Fina, H. Auer, W. Friedl, Proﬁtability of PV sharing in energy

communities: Use cases for diﬀerent settlement patterns, Energy 189

(2019) 116148. doi:10.1016/j.energy.2019.116148.

URL https://www.sciencedirect.com/science/article/pii/

S0360544219318432

[15] B. Fina, H. Auer, W. Friedl, Cost-optimal economic potential of shared

rooftop PV in energy communities: Evidence from austria, Renewable En-

ergy 152 (2020) 217–228. doi:10.1016/j.renene.2020.01.031.

[16] R. Luthander, J. Wid´en, D. Nilsson, J. Palm, Photovoltaic self-

consumption in buildings: A review, Applied Energy 142 (2015) 80–94.

doi:10.1016/j.apenergy.2014.12.028.

URL https://www.sciencedirect.com/science/article/pii/

S0306261914012859

[17] M. B. Roberts, A. Bruce, I. MacGill, A comparison of arrangements

for increasing self-consumption and maximising the value of distributed

photovoltaics on apartment buildings, Solar Energy 193 (2019) 372–386.

doi:10.1016/j.solener.2019.09.067.

PREPRINT

URL https://www.sciencedirect.com/science/article/pii/

S0038092X19309429

[18] T. Lang, D. Ammann, B. Girod, Proﬁtability in absence of subsidies:

A techno-economic analysis of rooftop photovoltaic self-consumption in

residential and commercial buildings, Renewable Energy 87 (2016) 77–87.

doi:10.1016/j.renene.2015.09.059.

URL https://www.sciencedirect.com/science/article/pii/

S0960148115303384

[19] B. Fina, H. Auer, W. Friedl, Proﬁtability of active retroﬁtting of multi-

apartment buildings: Building-attached/integrated photovoltaics with

special consideration of diﬀerent heating systems, Energy and Buildings

190 (2019) 86–102. doi:10.1016/j.enbuild.2019.02.034.

URL https://www.sciencedirect.com/science/article/pii/

S0378778818333826

[20] M. B. Roberts, A. Bruce, I. MacGill, Impact of shared battery en-

ergy storage systems on photovoltaic self-consumption and electric-

ity bills in apartment buildings, Applied Energy 245 (2019) 78–95.

doi:10.1016/j.apenergy.2019.04.001.

URL https://www.sciencedirect.com/science/article/pii/

S0306261919306269

[21] F. M. Camilo, R. Castro, M. Almeida, V. F. Pires, Economic assessment

of residential PV systems with self-consumption and storage in portugal,

Solar Energy 150 (2017) 353–362. doi:10.1016/j.solener.2017.04.062.

URL https://www.sciencedirect.com/science/article/pii/

S0038092X17303675

[22] E. Karakaya, A. Hidalgo, C. Nuur, Motivators for adoption of photo-

voltaic systems at grid parity: A case study from southern germany,

Renewable and Sustainable Energy Reviews 43 (2015) 1090–1098.

doi:10.1016/j.rser.2014.11.077.

URL https://www.sciencedirect.com/science/article/pii/

S1364032114010168

[23] A. Stauch, P. Vuichard, Community solar as an innovative business model

for building-integrated photovoltaics: An experimental analysis with

swiss electricity consumers, Energy and Buildings 204 (2019) 109526.

doi:10.1016/j.enbuild.2019.109526.

URL https://www.sciencedirect.com/science/article/pii/

S0378778819311995

[24] S. Zhang, Innovative business models and ﬁnancing mechanisms for dis-

tributed solar PV (DSPV) deployment in china, Energy Policy 95 (2016)

458–467. doi:10.1016/j.enpol.2016.01.022.

PREPRINT

[25] L. Strupeit, A. Palm, Overcoming barriers to renewable energy diﬀusion:

business models for customer-sited solar photovoltaics in japan, germany

and the united states, Journal of Cleaner Production 123 (2016) 124–136.

doi:10.1016/j.jclepro.2015.06.120.

URL https://www.sciencedirect.com/science/article/pii/

S0959652615008537

[26] M. Varela, L. Ram´ırez, L. Mora, M. S. de Cardona, Economic analysis

of small photovoltaic facilities and their regional diﬀerences, International

Journal of Energy Research 28 (3) (2004) 245–255. doi:10.1002/er.963.

URL https://onlinelibrary.wiley.com/doi/abs/10.1002/er.963

[27] M. ˇ

S´uri, T. A. Huld, E. D. Dunlop, H. A. Ossenbrink, Potential

of solar electricity generation in the european union member states

and candidate countries, Solar Energy 81 (10) (2007) 1295–1305.

doi:10.1016/j.solener.2006.12.007.

URL https://www.sciencedirect.com/science/article/pii/

S0038092X07000229

[28] A. Arcos-Vargas, J. M. Cansino, R. Rom´an-Collado, Economic and envi-

ronmental analysis of a residential pv system: A proﬁtable contribution to

the paris agreement, Renewable and Sustainable Energy Reviews 94 (2018)

1024–1035. doi:10.1016/j.rser.2018.06.023.

[29] S. Rodrigues, R. Torabikalaki, F. Faria, N. Cafˆofo, X. Chen, A. R. Ivaki,

H. Mata-Lima, F. Morgado-Dias, Economic feasibility analysis of small

scale PV systems in diﬀerent countries, Solar Energy 131 (2016) 81–95.

doi:10.1016/j.solener.2016.02.019.

URL https://www.sciencedirect.com/science/article/pii/

S0038092X16001158

[30] D. Keiner, M. Ram, L. D. S. N. S. Barbosa, D. Bogdanov, C. Breyer, Cost

optimal self-consumption of pv prosumers with stationary batteries, heat

pumps, thermal energy storage and electric vehicles across the world up to

2050, Solar Energy 185 (2019) 406–423. doi:10.1016/j.solener.2019.04.081.

[31] C. Romero-Rubio, J. R. de Andr´es D´ıaz, Sustainable energy communities:

a study contrasting spain and germany, Energy Policy 85 (2015) 397–409.

doi:10.1016/j.enpol.2015.06.012.

URL https://www.sciencedirect.com/science/article/pii/

S030142151500230X

[32] A. Campoccia, L. Dusonchet, E. Telaretti, G. Zizzo, Comparative analysis

of diﬀerent supporting measures for the production of electrical energy

by solar PV and wind systems: Four representative european cases, Solar

Energy 83 (3) (2009) 287–297. doi:10.1016/j.solener.2008.08.001.

URL https://www.sciencedirect.com/science/article/pii/

S0038092X0800203X

PREPRINT

[33] A. Campoccia, L. Dusonchet, E. Telaretti, G. Zizzo, An analysis of feed’in

tariﬀs for solar PV in six representative countries of the european union,

Solar Energy 107 (2014) 530–542. doi:10.1016/j.solener.2014.05.047.

URL https://www.sciencedirect.com/science/article/pii/

S0038092X14002904

[34] C. J. Sarasa-Maestro, R. Dufo-L´opez, J. L. Bernal-Agust´ın, Photovoltaic

remuneration policies in the european union, Energy Policy 55 (2013) 317–

328. doi:10.1016/j.enpol.2012.12.011.

[35] S. Avril, C. Mansilla, M. Busson, T. Lemaire, Photovoltaic energy

policy: Financial estimation and performance comparison of the public

support in ﬁve representative countries, Energy Policy 51 (2012) 244–258.

doi:10.1016/j.enpol.2012.07.050.

URL https://www.sciencedirect.com/science/article/pii/

S0301421512006441

[36] C. Inˆes, P. L. Guilherme, M.-G. Esther, G. Swantje, H. Stephen,

H. Lars, Regulatory challenges and opportunities for collective re-

newable energy prosumers in the eu, Energy Policy 138 (2020).

doi:10.1016/j.enpol.2019.111212.

[37] Bureau of Meteorology, Climate statistics for australian locations (2020).

URL http://www.bom.gov.au/jsp/ncc/cdio/cvg/av?p_stn_

num=066062&p_prim_element_index=0&p_comp_element_index=0&

redraw=null&p_display_type=statistics_summary&normals_years=

1991-2020&tablesizebutt=normal

[38] Stadt Wien, Extreme Wetterwerte seit Beginn der Messungen (2019).

URL https://www.wien.gv.at/statistik/lebensraum/tabellen/

extreme.html

[39] Zentralanstsalt fuer Metereologie und Geodynamik (2019). [link].

URL https://www.zamg.ac.at

[40] Bureau of Meteorology, Monthly mean daily global solar exposure - sydney

(observatory hill) (2020).

URL http://www.bom.gov.au/jsp/ncc/cdio/weatherData/av?p_

nccObsCode=203&p_display_type=dataFile&p_startYear=&p_c=&p_

stn_num=066062

[41] Energy Economics Group, Solar database (2017).

[42] Zentralanstalt fuer Metereologie und Geodynamik (2017). [link].

URL https://www.zamg.ac.at/cms/de/aktuell

[43] Australian Competition and Consumer Commission, Restoring electricity

aﬀordability and australia’s competitive advantage: Retail electricity pric-

ing inquiry—ﬁnal report, Report (2018).

PREPRINT

[44] European Central Bank, Euro foreign exchange reference rates [cited

18.06.2020].

URL https://www.ecb.europa.eu/stats/policy_and_exchange_

rates/euro_reference_exchange_rates/html/eurofxref-graph-aud.

en.html

[45] IEA-PVPS and Australian PV Institute, National survey report of pv power

applications in australia 2018, Report, IEA Photovoltaic Power Systems

TCP (2019).

[46] Australian Energy Market Commission, Residential electricity price trends

2019 (2019).

[47] Stromliste, Stromtarife vergleichen (2020).

URL https://stromliste.at/stromtarife

[48] Statistik Austria, Preise, Steuern (2018).

URL https://www.statistik.at/web_de/statistiken/energie_

umwelt_innovation_mobilitaet/energie_und_umwelt/energie/

preise_steuern/index.html

[49] E-Control, Preisentwicklungen (2019).

[50] Oesterreichs Energie, Daten und Fakten zum Strompreis in Oesterreich

(2019).

URL https://oesterreichsenergie.at/

daten-fakten-zum-strompreis.html

[51] Selektra, Einspeisetarife fuer Photovoltaik-Kunden in Oesterreich (2020).

URL https://selectra.at/energie/tipps/photovoltaik/

einspeisetarife

[52] Solar Choice, Solar panel costs based on live database february 2020

(2020) [cited 20.03.2020].

URL https://www.solarchoice.net.au/blog/

commercial-solar-pv-price-index-for-february-2020/

[53] Oberoesterreichischer Energiesparverband, Land Oberoesterreich, Clean-

tech Cluster, Pv eigenverbrauchsanlagen checkliste und planungshilfe

(2019).

URL https://www.energiesparverband.at/fileadmin/esv/

Broschueren/PV-Eigenverbrauchsanlagen-Betriebe.pdf

[54] Photovoltaic Austria Federal Association, Photovoltaik- und Speicherfo-

erderung in Oesterreich (2020).

URL https://www.pvaustria.at/forderungen/

[55] European Commission, Energy performance of buildings directive (2019).

URL https://ec.europa.eu/energy/en/topics/

energy-efficiency/energy-performance-of-buildings/

energy-performance-buildings-directive

PREPRINT

[56] PV-Gemeinschaft.AT, Informationsplattform (2020).

URL http://pv-gemeinschaft.at/allgemeines/

[57] ABS, Building approvals, australia,, Report, Australian Bureau of Statis-

tics (2020).

URL https://www.abs.gov.au/Ausstats/abs@.nsf/mf/8731.0

[58] M. B. Roberts, J. Copper, A. Bruce, Analysis of rooftop solar potential on

australian residential buildings, in: Proceedings of the 2018 Asia-Paciﬁc

Solar Research Conference, APVI, 2018.

[59] Statistic Austria, Gebaeude und Wohnungen 2011 nach Art des (Wohn-)

Gebaeudes und politischen Bezirken (2011).

URL http://www.statistik-austria.at/web_de/statistiken/

menschen_und_gesellschaft/wohnen/wohnungs_und_

gebaeudebestand/index.html

[60] Statistik Austria, Gebaeude und Wohnungen 2011 nach dem Eigentuemer-

typ des Gebaeudes und Bundesland (2011).

URL http://www.statistik-austria.at/web_de/statistiken/

menschen_und_gesellschaft/wohnen/wohnungs_und_

gebaeudebestand/index.html

[61] N. Johnston, S. Reid, An examination of building defects in residen-

tial multi-owned properties, Report, Deakin University,Griﬃth University

(2019).

[62] W. Jolly, Coronavirus to cause apartment construction to plummet [cited

26.06.020].

URL https://www.savings.com.au/home-loans/investing/

coronavirus-to-cause-apartment-construction-to-plummet

[63] C. Scientiﬁc, I. R. Organisation, Australian housing data portal [cited

26.06.2020].

URL https://ahd.csiro.au/dashboards/energy-rating/states/

[64] P. Biermayr, Einﬂussparameter auf den Energieverbrauch der Haushalte,

Ph.D. thesis, Technische Universitaet Wien (1998).

[65] Statistik Austria, Heizungen 2003 bis 2018 nach Bundesl¨andern, verwen-

detem Energietr¨ager und Art der Heizung (2018).

URL https://www.statistik.at/web_de/statistiken/energie_

umwelt_innovation_mobilitaet/energie_und_umwelt/energie/

energieeinsatz_der_haushalte/index.html

[66] Statistik Austria, Register-based census 2011 - housing census: Conven-

tional dwellings (2011) [cited 27.08.2020].

URL https://statcube.at/statistik.at/ext/statcube/jsf/

tableView/tableView.xhtml

PREPRINT

[67] Statistik Austria, Housing conditions (2019).

URL https://www.statistik.at/web_de/statistiken/menschen_und_

gesellschaft/wohnen/wohnsituation/index.html

[68] Nationalrat, Elektrizitaetswirtschafts- und Organisationsgesetz elwog,

Rechtsinformationssystem des Bundes, Fassung vom 19.02.2020 (2020).

URL https://www.ris.bka.gv.at/GeltendeFassung.wxe?Abfrage=

Bundesnormen&Gesetzesnummer=20007045

[69] M. Syed, P. Hansen, G. M. Morrison, Performance of a shared solar and

battery storage system in an australian apartment building, Energy and

Buildings (2020). doi:10.1016/j.enbuild.2020.110321.

[70] European Parliament and Council, Directive (eu) 2018/2001 of the Euro-

pean Parliament and of the Council of 11 december 2018 on the promotion

of the use of energy from renewable sources (2018).

URL https://eur-lex.europa.eu/legal-content/DE/TXT/PDF/?uri=

CELEX:32018L2001&from=EN

[71] European Parliament and of the Council, (2019).

URL https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=

CELEX%3A32019L0944

[72] Republik Oesterreich, Oekostrom-Einspeisetarifverordnung 2018 (2017).

[73] WKO, Photovoltaik Foerderungen fuer 2020 (2020).

URL https://www.wko.at/service/noe/umwelt-energie/

photovoltaik-foerderungen.html

[74] Clean Energy Regulator (CER), Small-scale technology certiﬁcates [cited

05.08.2020].

URL http://www.cleanenergyregulator.gov.au/RET/

Scheme-participants-and-industry/Agents-and-installers/

Small-scale-technology-certificates

[75] Green Energy Markets, Enlightening environmental markets [cited

18.06.2020].

URL http://greenmarkets.com.au/

[76] Stadt Wien, Foerderung von Photovoltaikanlagen in Oesterreich (2020).

URL https://www.stadt-wien.at/immobilien-wohnen/photovoltaik/

foerderung.html

[77] H. Fechtner, C. Mayr, A. Schneider, M. Rennhofer, G. Peharz, Technologie-

Roadmap fuer Photovoltaik in Oesterreich, bmvit - Bundesministerium fuer

Verkehr, Innovation und Technologie (2016).

URL https://nachhaltigwirtschaften.at/resources/edz_pdf/1615_

technologie_roadmap_photovoltaik.pdf

PREPRINT

[78] Australian Government Department of the Environment and Energy, Smart

grid smart city customer trial data (2014).

[79] M. B. Roberts, N. Haghdadi, A. Bruce, I. MacGill, Characterisation of

australian apartment electricity demand and its implications for low-carbon

cities, Energy 180 (2019) 242–257. doi:10.1016/j.energy.2019.04.222.

[80] National Renewable Energy Laboratory, System Advisor Model (SAM)

(2019).

URL https://sam.nrel.gov/

[81] T. Lee, (N.D.).

URL http://www.exemplary.com.au/download/Lee%20-%20Paper%

201298%20-%20Climate%20Data%20For%20Building%20Optimisation%

20for%20IBPSA%202011.pdf

[82] Government of New South Wales, Proposed amendments to the strata

schemes management act 2015 (2020).

PREPRINT

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

0.2

0.4

0.6

0.8

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

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

0.2

0.4

0.6

0.8

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

0.2

0.4

0.6

0.8

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

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Figure A.13: Winter HVAC Load

Figure A.14: Summer HVAC Load

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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

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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.

Critical Review on Community-Shared Solar—Advantages, Challenges, and Future Directions

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Apr 2023

In the last few years, many innovative solutions have been presented to address the climate change crisis. One of the innovative solutions is the participation of community members in the collective production of solar electricity instead of individual production. The current study aims to provide a critical literature review of the collective production of solar electricity, which is called “community-shared solar” (CSS). Sixty-seven peer-reviewed publications were selected based on the setting up of a combination of related keywords. To analyze the concept of CSS in the existing literature, a multi-level perspective (MLP) framework was used to observe the CSS innovation at the niche, regime, and landscape levels. Four aspects, including the technical, economic, socio-political, and regulatory and institutional, were considered to evaluate those three levels. The results revealed that in the technical and economic aspects, CSS has reached maturity and internal momentum that can take it to the next levels. However, a lack of attention to the socio-political aspect and the regulatory and institutional aspect, in particular, is the potential barrier to the emergence of CSS and its potential position as a leading energy system.

Pathway for decarbonizing residential building operations in the US and China beyond the mid-century

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APPL ENERG

With global carbon budget targets looming, residential buildings in top economies must become carbon neutral as soon as possible to reserve more emission space for emerging carbon-emitting economies. This study is the first to compare the operational decarbonization process of China’s and the United States (US) residential buildings from 2000 to 2060 by combining the end-use emission model with the decomposing structural decomposition (DSD) method and Monte Carlo simulation. The results show that from 2001 to 2020 China decarbonized 1544 mega-tons of carbon dioxide (MtCO2) and the US decarbonized 1848 MtCO2. In the business-as-usual scenario, China will hit its emission peak in 2031 (±3) with 934 (±61) MtCO2, while the US will maintain a lock-in level of 736 (±133) MtCO2 since the 2030s. In the decarbonization scenario, operational carbon neutrality for residential buildings in 2060 is promoted by an increase in clean power generation proportion, building-integrated power generation level, building electrification level, and a reduction in end-use energy intensity, which will contribute 34.4 %, 21.4 %, 14.3 %, and 29.9 % in China and 32.9 %, 33.1 %, 8.2 %, and 25.8 % in the US, respectively. Especially, building-integrated power generation in China only costs about 40 % of what it costs in the US. Besides, high-decarbonization strategies for residential building operations are proposed as references for governments to formulate targeted climate policies. Overall, this study offers data benchmarks for buildings’ carbon neutrality of top economies to further promote synergistic carbon neutrality with the buildings of emerging economies in the age of Post COP27.

Pathway for decarbonizing residential building operations in the US and China beyond the mid-century

Preprint

Full-text available

Apr 2023

Please cite this accepted manuscript as: Zhang S, Zhou N, Feng W, Ma M, Xiang X, You K. Pathway for decarbonizing residential building operations in the US and China beyond the mid-century. Applied Energy 2023. DOI: 10.1016/j.apenergy.2023.121164

Optimal sizing of PV-BESS units for home energy management system-equipped households considering day-ahead load scheduling for demand response and self-consumption

Article

May 2022
ENERG BUILDINGS

Today, selling electricity to the grid has lost its former profitability with reduced feed-in tariff (FiT) rates. This makes it crucial for prosumers to increase self-consumption and size their photovoltaic (PV) and battery energy storage system (BESS) units accordingly. Self-consumption can be increased through demand-side management (DSM) and an efficient DSM can be achieved using home energy management systems (HEMSs). Therefore, as its main contribution, this study proposes an optimal PV-BESS sizing model for HEMS-equipped prosumers considering day-ahead load scheduling-based DSM. Unlike other studies in the literature, the proposed model takes into account the determination of optimal PV tilt angle, load scheduling of all types of controllable appliances (time-shiftable, thermostatically controllable, power-shiftable), consideration of battery degradation, and vehicle-to-home (V2H) availability in the sizing procedure. First, the mixed-integer linear programming (MILP)-based model performs demand response (DR) and increased self-consumption to minimize the daily bill. Second, it simulates one year of HEMS operation and determines the net present value (NPV) of a PV-BESS configuration over the system lifetime. Finally, it repeats the same process for each combination of PV capacity-PV tilt angle-battery number and chooses the combination with the highest NPV as the optimal design. The simulations were conducted to find the required PV-BESS capacity for a HEMS-equipped household with average daily electricity consumption of 37.5 kWh in Istanbul, Turkey. The optimal configuration was found to be 3 kW PV without BESS at the tilt angle of 10°. A techno-economic sizing comparison was made between households using and not using HEMS. The NPV of PV-BESS was found to be significantly higher with HEMS use ($2273) compared with that without HEMS use ($920). Lastly, a sensitivity analysis was performed based on rising electricity prices (+25%, +50%, +75%, +100%) and declining battery prices (-25%). The use of BESS became viable in Turkey even with +25% electricity prices or -25% battery prices.

Optimising the self-consumption and self-sufficiency: A novel approach for adequately sizing a photovoltaic plant with application to a metropolitan station

Article

Oct 2021
J CLEAN PROD

The recent trends in designing sustainable power systems emphasize the importance of self-consumption (SC) both at individual and community level. This new paradigm changes the way in which we design photovoltaic facilities for residential houses and for various municipality services as well. In this context, the paper aims to formulate several optimisation problems using criteria such as self-consumption, self-sufficiency (SS) and net present value (NPV) as objectives to provide an optimal photovoltaic (PV) plant size for a singular power system - a subway station. By using this multi-objective approach, the work emphasizes how each criteria impacts the profitability and value of the overall investment, involving possible shareholders in the design process by choosing a desired solution from the Pareto-efficient set of configurations. Moreover, a global optimal solution is provided by formulating an optimisation problem through a single-objective Mixed Integer Linear Programming (MILP) approach involving an equivalent metric, the net-energy exchanged with the grid (NEEG). The proposed methodology is validated in a case study on the power system of a subway station in Bucharest (Romania), thus identifying a configuration that focuses on self-consumption maximisation and a solution that reduces the yearly energy bill of the respective power system by 25%.

Efficient, effective and fair allocation of costs and benefits in residential energy communities deploying shared photovoltaics

Article

Jan 2022
APPL ENERG

Deployment of rooftop solar photovoltaics on multi-family buildings lags behind other residential buildings sectors, despite the benefit of significantly higher self-consumption achievable by applying on-site generation to aggregated building load. This is, in part, because of challenges in developing suitable business models to ensure the fair allocation of costs and benefits between different stakeholders. Embedded networks can provide a mechanism for consumers to co-ordinate their engagement in the energy market, as well as to distribute on-site generation between multiple households. However, to succeed, an embedded network must deliver benefits to all households as well as providing returns to investors. This paper uses a case-study of a 72-apartment complex in Sydney Australia to explore different ways to distribute the costs and benefits of a potential shared photovoltaic system between apartment owners and residents. A range of tariff structures, including demand or capacity charges as well as fixed and time-varying volumetric charges, are compared for their ability to recover investment costs, incentivise efficient energy behaviour and achieve customer acceptance through fairness and transparency. The analysis demonstrates the tension between these desired outcomes and the significant challenge of designing a mechanism to deliver them all. In particular, tariff structures incorporating peak demand charges, while cost-reflective and efficient, are unable to deliver benefits to all stakeholders and thereby ensure the sustainability of the embedded network. The findings have implications for market design and for policy approaches to support embedded networks and energy communities.

Is dynamic energy sharing really necessary? The case study of collective renewable self-consumers in Croatia

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Environmental and economic analyses of different size photovoltaic installation in Poland

Article

Oct 2022

In Poland, in the last 3 years, there has been a sharp increase in the number of photovoltaic micro-installations, especially in the power range of 2–10 kWp. The study analyzes the economic viability and environmental aspects of the resulting installations. A distinction was made according to the size of the installation, which translates into its productivity and the scale effect of the assembly. For the first time in Poland, the emission levels of CO2 and other pollutants were determined based on the power of PV installations. Both the Life Cycle Assessment and the cash flow analysis were used in the research. In the analyzed range of installation power, changes in the calculated environmental indicators ranged from 5.4 to 7 %, and the most environmentally effective option in the My Electricity program is a 10 kWp installation, while the highest economic efficiency was achieved for installations with a capacity of 2 kWp. In addition, the impact of the installation of many installations under the My Electricity program on the reduction of the carbon footprint, emission of dust, nitrogen oxides and sulfur dioxide in the conditions of the Polish power industry was analyzed.

Selecting Representative Net Load Profiles of Solar Homes Using Clustering Techniques

Article

Jan 2021

Sodium Sulfur Batteries Allocation in High Renewable Penetration Microgrids Using Coronavirus Herd Immunity Optimization

Article

Sep 2021

Mohammed Alqarni

Energy storage batteries have been described as an ideal way to solve renewable energy problems, improve self-consumption rate (ScR), and pave the way for further growth in renewables penetration. In this work, an optimization framework is proposed to enhance a grid-connected microgrid performance in three stages. The first stage epitomizes maximization of the ScR of the highly-penetrated renewables hosted in the microgrid considered via sodium sulfur batteries allocation. The second stage epitomizes the minimization of the active power losses. The third stage epitomizes the calculation of the optimal energy management relying on diminishing the overall microgrid’s cost of operation depending on the optimal findings of the earlier two stages. The coronavirus herd immunity optimization algorithm is applied on MATLAB’s platform to solve the engineering problem formulated. Numerous linear and nonlinear constraints have been taken into account. The results have gotten validate the usefulness of the developed solutions and algorithm application.

Economic Viability of Renewable Energy Communities under the Framework of the Renewable Energy Directive Transposed to Austrian Law

Article

Full-text available

Nov 2020

This study is concerned with the national transposition of the European Renewable Energy Directive into Austrian law. The objective is to estimate the economic viability for residential customers when participating in a renewable energy community (REC), focused on PV electricity sharing. The developed simulation model considers the omission of certain electricity levies as well as the obligatory proximity constraint being linked to grid levels, thus introducing a stepwise reduction of per-unit grid charges as an incentive to keep the inner-community electricity transfer as local as possible. Results show that cost savings in residential RECs cover a broad range from 9 EUR/yr to 172 EUR/yr. The lowest savings are gained by customers without in-house PV systems, while owners of a private PV system make the most profits due to the possibility of selling as well as buying electricity within the borders of the REC. Generally, cost savings increase when the source is closer to the sink, as well as when more renewable electricity is available for inner-community electricity transfer. The presence of a commercial customer impacts savings for households insignificantly, but increases local self-consumption approximately by 10%. Despite the margin for residential participants to break even being narrow, energy community operators will have to raise a certain participation fee. Such participation fee would need to be as low as 2.5 EUR/month for customers without in-house PV systems in a purely residential REC, while other customers could still achieve a break-even when paying 5 EUR/month to 6.7 EUR/month in addition. Those results should alert policy makers to find additional support mechanisms to enhance customers’ motivations to participate if RECs are meant as a concept that should be adopted on a large scale.

Self-consumption of electricity produced with photovoltaic systems in apartment buildings - Update of the situation in various IEA PVPS countries

Conference Paper

Full-text available

Jun 2020

Over the last two decades, grid-connecte d solar photovoltaic systems have increased from a niche market to one of the leading power generation capacity additions annually. In 2019 the total worldwide installed photovoltaic electricity generation capacity exceeded 630 GW. It is forecasted that 1 TW will be reached by 2022. This further development is coupled with the question at what prices solar photovoltaic electricity can be provided and delivered to the customers. The installation of PV systems for self-consumption is already now an interesting option for many people but in general limited to those who have access to a rooftop they own or can use. Enabling residents of multi apartment buildings to commonly use electricity generated by a PV system (collective self-consumption) is a relatively new development and is still facing a lot of administrative and regulatory challenges. This paper provides an overview of existing regulatory schemes in IEA PVPS countries and presents and analysis of two self-consumption case studies .

Regulatory challenges and opportunities for collective renewable energy prosumers in the EU

Article

Full-text available

Dec 2019
ENERG POLICY

The transition to a low-carbon future based on renewable energy sources is leading to a new role for citizens, from passive energy consumers to active energy citizens - the so-called renewable energy (RE) prosumers. Recent EU energy policy seeks to mainstream RE prosumers in each Member State. This study carries out a cross-country comparison between the regulatory frameworks of nine countries and regions - Belgium (Flanders region only), Croatia, France, Germany, Italy, Portugal, Spain, Netherlands and the United Kingdom - to reveal the main challenges and opportunities that these have posed to collective RE prosumers (i.e. renewable energy communities, citizen energy communities and jointly-acting renewable self-consumers). Four countries have had more favourable frameworks for collective prosumers: France, Germany, Netherlands and United Kingdom. The results indicate that the current legal framework at the EU level represents a clear opportunity for collective prosumers. Spain and Portugal have both already shifted from a restrictive regulation to implementing in 2019 a legal framework for collectives. The study provides a starting point to distil policy implications for improving legal frameworks relevant for collective RES prosumers across Europe. DOI: https://doi.org/10.1016/j.enpol.2019.111212

Cost-optimal economic potential of shared rooftop PV in energy communities: Evidence from Austria

Article

Full-text available

Jun 2020
RENEW ENERG

In this study, a model is developed to estimate the cost-optimal large-scale economic potential of shared rooftop PV systems based on neighbourhood energy communities (ECs). In a first step, an optimisation model determines the cost-optimal rooftop PV capacities for representative neighbourhood ECs in characteristic settlement patterns (SPs). Next, the number of ECs in the large-scale area of investigation is determined by allocating buildings to SPs and ECs. Finally, the optimal large-scale, EC-based rooftop PV potential is determined by upscaling. A case study is provided for Austria, identifying a cost-optimal economic rooftop PV potential of approximately 10GWp. This PV capacity would already be sufficient (in terms of expected PV deployment) to meet the Austrian 2030 policy goal of a 100% renewable electricity generation. However, results also indicate that accommodating the cost-optimal rooftop PV capacity is difficult in cities/towns in contrast to rural areas. Thus, future ECs should be implemented not only on neighbourhood level, but across the boundaries of different SPs. Different sensitivity analyses are conducted, notably in terms of varying retail electricity prices, including a variation of distribution grid tariff structures, and PV system cost. The trade-off between these sensitivity parameters is critically discussed and provides recommendations for future work.

Regulatory challenges and opportunities for collective renewable energy prosumers in the EU

Article

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A comparison of arrangements for increasing self-consumption and maximising the value of distributed photovoltaics on apartment buildings

Article

Full-text available

Nov 2019
SOL ENERGY

As subsidised feed-in-tariffs for distributed photovoltaic (PV) generation are reduced or abolished in many jurisdictions, there is growing interest in increasing self-consumption to realise greater value from rooftop PV generation. However, deployment of PV on apartment buildings lags behind other residential deployment despite the potential advantages of load aggregation. We present a study of electricity and financial flows in ten 'virtual' Australian apartment buildings under a range of technical implementations and financial arrangements, using real load profiles and simulated generation profiles. Aggregation of diverse household and shared loads, either through an embedded network or 'behind the meter' of individual dwellings, can increase self-sufficiency and self-consumption of on-site generation compared to separate systems supplying common property or individual apartments. While embedded networks can enable access to more beneficial retail arrangements, behind the meter solutions may allow residents to avoid regulatory complexities and additional costs. The relative benefits of each arrangement are dependent on building characteristics and financial settings.

Profitability of PV sharing in energy communities: Use cases for different settlement patterns

Article

Full-text available

Sep 2019
ENERGY

Many countries are changing their legislation to enable photovoltaic (PV) sharing beyond building boundaries. This work aims to investigate the profitability and optimal installation capacities of PV systems for energy communities (ECs) in comparison to individual buildings. To gain a wide spectrum of results, four characteristic settlement patterns with different building types are defined, ranging from urban to suburban and historical to rural areas. Analytically, a mixed-integer linear optimisation model is developed to maximise the net present value over a time horizon of 20 years. The results show that the profitability of implementing optimally-sized PV systems increases when forming ECs compared to the situation of considering buildings individually. The more different the load profiles, the more synergy effects, and the higher the cost saving potential. Consequently, a sensitivity analysis shows that taking into account large customers can increase the profitability of PV installation for the community significantly because large roof/facade areas are provided for optimal PV installation. In addition to a broad participant portfolio, a change in the technology set-up can have a positive influence. Battery- and hot water storage which complement PV systems and heat pumps can contribute to saving energy costs, if only marginally.

Characterisation of Australian apartment electricity demand and its implications for low-carbon cities

Article

Full-text available

May 2019
ENERGY

Understanding of residential electricity demand has application in efficient building design, network planning and broader policy and regulation, as well as in planning the deployment of energy efficiency technologies and distributed energy resources with potential emissions reduction benefits and societal and household cost savings. Very few studies have explored the specific demand characteristics of apartments, which house a growing proportion of the global urban population. We present a study of apartment electricity loads, using a dataset containing a year of half-hourly electricity data for 6,000 Australian households, to examine the relationship between dwelling type, demographic characteristics and load profile. The focus on apartments, combined with the size of the data set, and the representative seasonal load profiles obtained through clustering full annual profiles, is unique in the literature. We find that median per-occupant household electricity use is 21% lower for apartments than for houses and that, on average, apartments have lower load factor and higher daily load variability, and show greater diversity in their daily peak times, resulting in a lower coincidence factor for aggregations of apartment loads. Using cluster analysis and classification, we also show the impact of dwelling type on the shape of household electricity load profiles.

Performance of a shared solar and battery storage system in an Australian apartment building

Article

Jul 2020
ENERG BUILDINGS

This study presents the energy performance of a three unit apartment building in Perth, Western Australia equipped with a shared energy microgrid. Although there has been a dramatic growth of residential rooftop solar PV across Australia, apartment buildings and their occupants are rarely able to access the benefits associated with onsite renewable energy generation and consumption. To address this, an apartment building in Perth was fitted with a rooftop solar PV and battery energy storage system, with metering architecture. The microgrid topology enabled the sharing of energy between the apartment units. A one year dataset (December 2017 - December 2018) obtained from onsite pulse meters was analysed. Load profiles were assessed and grid minimisation was evaluated through a self-sufficiency metric. The three unit apartment showed a 22% reduction in average yearly energy consumption against the benchmark. The findings demonstrated an overall 75% dependency of the microgrid on renewables; and suggest that a shared energy microgrid may be more effective than separate supply connections.

Community Solar as an Innovative Business Model for Building-Integrated Photovoltaics An Experimental Analysis with Swiss Electricity Consumers

Article

Oct 2019
ENERG BUILDINGS

A currently pertinent research challenge is to find ways to keep the growth rate of solar power at a high level. The adoption of new technologies, such as building-integrated photovoltaics (BIPV), but also new and innovative business models such as community solar, have both been identified as relevant drivers. However, the adoption of BIPV is still encountering numerous barriers that hinder its more widespread deployment within the solar PV market. The goal of this research effort was to assess whether community solar as a successful business model for the adoption of conventional solar PV could be equally promising in relation to the further adoption of BIPV. For this purpose, we conducted an experimental survey (n = 413) to compare customers’ willingness to buy a community solar offer exclusively associated with BIPV to a community solar offer solely designed with conventional rooftop solar PV. Our results revealed no significant difference between willingness to buy based on our experimental treatment (BIPV vs. conventional PV), indicating that community solar can be a successful distribution channel for the further adoption of BIPV. As findings about specific business models for BIPV are rare, our research creates an important foundation upon which policy makers and project developers can build.

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

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