1. 1
Masters Programmes
Assignment Cover Sheet
Submitted by: 1467070
Date Sent: 11th September 2015
Module Title: Project and Dissertation
Module Code: IB93T0
Date/Year of Module: 1st July – 10th September 2015
Submission Deadline: 11th September 2015
Word Count: 15,979 (excluding cover, content, reference and
appendix)
Number of Pages: 79 (including cover, reference, appendix)
Question:
The review of ProductLife Cycle InternationalBusinessTheory with
evaluation ofbestmarketfor Tesla Energy’s Home BatteryProduct
“This is to certify that the work I am submitting is my own. All external references and
sources are clearly acknowledged and identified within the contents. I am aware of the
University of Warwick regulation concerning plagiarism and collusion.
No substantial part(s) of the work submitted here has also been submitted by me in other
assessments for accredited courses of study, and I acknowledge that if this has been
done an appropriate reduction in the mark I might otherwise have received will be made.”

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The review of ProductLife Cycle InternationalBusinessTheory with
evaluation ofbestmarketfor Tesla Energy’s Home BatteryProduct
Contents
Assignment Cover Sheet..............................................................................................................1
1. Introduction ..................................................................................................................................6
1.1 Background ............................................................................................................................6
1.2 Scope and Objective..............................................................................................................8
1.3 Structure.................................................................................................................................9
2 Literature review .........................................................................................................................10
2.1 Reasons for Expansion Abroad...........................................................................................10
2.1.1 Competitive Advantage .................................................................................................10
2.1.2 Stage Theory : Uppsala model......................................................................................12
2.1.3 Product life cycle internationalization theory.................................................................12
2.2 The Process and rationale of selecting International Market Entry Mode ..........................13
2.2.1 Hierarchical theory.........................................................................................................14
2.2.2 Resource Commitment..................................................................................................15
2.2.3 Risk & Return, control....................................................................................................15
2.3 Main factors for Successful Expansion................................................................................16
2.3.1 Transaction Cost Theory (Brouthers & Hennart, 2007) (Williamson, 1998).................16
2.3.2 Eclectic Paradigm (Dunning, 2000; Dunning & Lundan, 2008) ....................................16
2.3.3 CSAs and FSAs.............................................................................................................17
2.3.3.1 Country-Specific Advantages( CSAs) : The Diamond Theory (Porter, 1990) ...........18
2.3.3.2 Firm-Specific Advantages (FSAs)..............................................................................19
2.3.4 Institutional Theory (Brouthers & Hennart, 2007) .........................................................19
2.3.5 Social Capability Theory (Chetty & Agndal, 2007; Prashantham, 2011) .....................20
3. Operationalisation and Hypotheses ..........................................................................................21
3.1 Characteristics of Home Battery System customer ....................................................................21
3.2 Hypotheses for identifying the target customer........................................................................22
3.3 Research questions .................................................................................................................22

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4. Methodology...............................................................................................................................24
4.1 Study framework ..................................................................................................................24
4.2 Data collection......................................................................................................................25
4.2.1 1st
Round: Residential solar PV drivers ........................................................................26
4.2.2 2nd
Round ........................................................................................................................26
5. Rationale of 2nd
Round factors.......................................................................................................30
5.1 Value of Electricity storage ..................................................................................................30
5.2 Factors for measuring the value of electricity storage................................................................30
5.2.1 Reserve margin................................................................................................................30
5.2.2 Capacity of gridintegration of renewable energy................................................................31
5.2.3 Existence of Substitutes : Hydropower including PHS.........................................................32
5.3 User Value..............................................................................................................................35
5.3.1 Smart metering................................................................................................................36
5.3.2 Daily Demand profile.........................................................................................................37
5.3.3 Price of instalment............................................................................................................39
5.4 Government Support..............................................................................................................39
5.4.1 customer mobility(level of retail price liberalization)...........................................................39
5.4.2 Institutional support..........................................................................................................40
5.5 Supply chain support...............................................................................................................40
5.5.1 Installer credibility............................................................................................................40
5.6 Customer acceptance..............................................................................................................42
5.6.1 Drive to economic benefit .................................................................................................42
5.6.2 Drive to environmental benefit..........................................................................................42
5.7 Market Size.............................................................................................................................42
5.7.1 Projected amount of PV instalment....................................................................................42
5.7.2 Off-grid PV........................................................................................................................43
5.7.3 Income level.....................................................................................................................43
6. Data analysis and finding...........................................................................................................45
6.1 Data collection (1st
round : residential solar PV drivers) .....................................................45
6.1.1 Result of correlation analysis .............................................................................................45
6.1.2 Findings .........................................................................................................................45
6.2 ‘2nd
Round’ Data collection and analysis by country...................................................................46

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6.2.1 Reserve margin and Grid integration by countries...............................................................46
6.2.1.1 OECD America................................................................................................................47
6.2.1.2 OECD Asia Oceania.........................................................................................................48
6.2.1.3 OECD Europe .................................................................................................................49
6.2.1.4 Non-OECD......................................................................................................................50
6.2.2 Demand Profile.................................................................................................................51
6.2.3 The value of Energy storage...............................................................................................52
6.2.4 non-economic parameter..................................................................................................53
7. Discussion ....................................................................................................................................57
7.1 Further consideration for attractive market..............................................................................57
7.2 Recommendation....................................................................................................................58
8. Conclusion....................................................................................................................................60
Reference ........................................................................................................................................62
Appendix..........................................................................................................................................66

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List of figures
FIGURE 1INTERNATIONAL STRATEGY(BARTLETT & GHOSHAL,1987)....................................................................................................11
FIGURE 2AHIERARCHICAL MODEL OF CHOICEOF ENTRY MODES (PAN & TSE,2000)...........................................................................14
FIGURE 3THE ECLECTIC PARADIGM’S MOTIVEFOR FDI IN THE FSA/CSA MATRIX(RUGMAN,2010).....................................................18
FIGURE 4LOCATION ADVANTAGE ADOPTED FROMTHE DIAMOND THEORY (PORTER, 1990) ..................................................................19
FIGURE 5THEEVOLUTION OF THE VOLUMEOF GLOBAL SOLAR PVCAPACITY.(OECD, 2015,P9)...........................................................21
FIGURE 6SOLAR PVANNUAL CAPACITYADDITIONS BY REGION(IEA,2014C,P174)...............................................................................25
FIGURE 7 THEMATURITYOF THETECHNOLOGIES (IEA,2014A,P16) ...................................................................................................33
FIGURE 8EES PRESENTFEASIBILITY,FUTURE POTENTIAL,NEED FOR FURTHER RESEARCH AND DEVELOPMENT(CHATZIVASILEIADI ETAL.,
2013).......................................................................................................................................................................................34
FIGURE 9CURRENTGLOBAL INSTALLED GRID-CONNECTED ELECTRICITYSTORAGECAPACITY (MW, (IEA, 2014A,P17) ............................34
FIGURE 10HOW HOMEBATTERY SYSTEMWORKS DURING THE DAY (TESLA,2015A)...............................................................................36
FIGURE 11 EXPECTED EVOLUTION OF THENETLOAD OF A TYPICAL SPRING DAYIN CALIFORNIA (OECD,2015,P34) ...............................38
FIGURE 12HOURLYELECTRICITYCONSUMPTION PROFILES FOR DIFFERENTBUILDING TYPES IN GERMANY (IEA,2014B, P 154) ..............39
FIGURE 13DESIGN OF TESLA ENERGY’S HOME BATTERY SYSTEM (TESLA,2015A)..................................................................................41
FIGURE 14RENEWABLEPOTENTIAL IN VARIOUS COUNTRIES (IEA,2011B,P53).....................................................................................47
FIGURE 15DAILY DEMAND CURVEIN 6 REGEIONS (IEA,2011B,P63)..................................................................................................51
FIGURE 16FIGURE 16TWO TYPES OF DAILYDEMAND PROFILEIN FOUR TYPICAL REGIONS.(INAGE,S.,2010) ..........................................52
FIGURE 17INFLUENCEOF PVPENETRATION ON DEMAND-SUPPLYBALANCE (INAGE,S.,2010)...............................................................52
FIGURE 18DPMFOR ATTRACTIVEMARKETOF HOMEBATTERY SYSTEM.................................................................................................55
List of Tables
TABLE 1SOURCEOF COMPETITIVE ADVANTAGE (GHOSHAL,1987).......................................................................................................11
TABLE 2CONTINGENCYFRAMEWORK (KUMAR & SUBRAMANIAM,1997)..............................................................................................15
TABLE 3OLI FRAMEWORK (DUNNING & LUNDAN,2008).....................................................................................................................17
TABLE 4 LIST OF VARIABLES FOR ANALYSING SOLAR PVDRIVER .............................................................................................................26
TABLE 5CLASSIFICATION OF EES SYSTEMS (CHATZIVASILEIADI ETAL., 2013) .........................................................................................33
TABLE 6SMART METER ROLLOUT PLANS (COOKE,D., 2011,P30).........................................................................................................37
TABLE 7 SCORE OF SUB-TOTAL OF NON-ECONOMIC FACTOR SURVEY ......................................................................................................54

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1. Introduction
1.1 Background
While energy storage is not a new technology, many people have said that its value is
immense, and that it can revolutionise the whole energy industry provided its cost is
reduced sufficiently for commercialization.
The value of energy storage is twofold. Firstly, it can create a balance between the supply
and demand of electricity. With renewable generation on the rise, the value of energy
storage is a decisive factor. This is because it is natural for grid operators to be concerned
about the storage of energy derived from intermittent renewables. Secondly, energy
storage can change the load profile (load shifting) to the form, which allows economical
operation of power supply and transmission.
In this context, Tesla Motor has recently started a new battery business through a new
subsidiary called ‘Tesla Energy’. The company has launched two battery products,
namely ‘Powerwall’ for stationary residential use and ‘Powerpack’ for commercial use.
Mindful of market trends, Tesla, a leader in the field of energy products has brought down
the cost of storage below the threshold pf 350$/kWh. However, critics still downplay the
product noting that it is little more than a luxurious toy for the rich because its cost
outweighs the obvious benefits.
Even though critics have analysed Tesla Energy’s initiative as providing less economic
benefit to customers, their critique seems to be limited in terms of the definition of target
customers. They seem to describe customers as only price-sensitive residential
customers, whereas according to Tesla, there are five types of customer or partners
and in each category there are sub categories of buyers and users who may have
different objectives for using the product:
 1) Solar PV owner: to be smart energy user and to save bill
 2) Retail companies: to reduce supply outage and to provide service to solar PV
owners
 3) Large business: to save bill and reliable operation backed by seamless
electricity providing
 4) Utility: to provide electricity without outage
 5) Transmission operating company: to optimise the power system in terms of
reliability and affordability

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This study focused on these questions:
 Who can be the target customer for Tesla Energy’s stationary battery system?
 And what can be the driver of the customer?
Tesla Energy chose the first market as the US with Powerwall displaying the features of
premium product. For example, the color and design of the product are quite luxurious.
The focus of this study was the exploration of the rationale behind the marketing
strategy chosen by Tesla. Therefore, this study used the theory of internationalization
such as Vernon’s Product Cycle theory to interpret the findings.
A second driver of the study spanned the following questions:
 If the rationale was defined by the examination, which market other than the US
is the most attractive market?
 Which international market is next for Tesla Energy’s Home battery product?
 Will it follow the track of Tesla Motor, which is EU and then China? Or else?
By seeking responses to these, this study explored an area of significance because 1)
there have been plenty of academic studies on the international market entry strategy
especially related to the Product Cycle theory but not in the context of electricity, 2) the
exploration of the next market of a major electricity market provided broad knowledge
about each electricity market and respective trend.
For example, to understand the economic benefit of energy storage in different power
systems, questions related to the variables below needed to be examined:
- Size of solar PV instalment
- Share of renewable generation
- Reserve margin
- Share of Hydropower(including, PHS) resources
- Smart meter deployment plan
- Customer mobility(level of retail price liberalization)
- Solar PV grid-parity
- Daily demand profile
- Electric Vehicle demand and value
Next, several academic theories (Brouthers & Hennart, 2007; Chetty & Agndal, 2007;
Porter, 1990; Prashantham, 2011) suggested that non-economic factors also needed to
be investigated to evaluate the attractive market, for instance government support,
supply chain support and customer acceptance.

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These questions were useful and meaningful because they provided better
understanding of;
 The main driver of stationary storage battery business.
 The different environment of the business in the countries
 Adaptation of international market entry model to new business.
1.2 Scope and Objective
As seen before, energy storage customers can be placed into five categories. Each
customer category has different drivers, and Tesla Energy can seek to expand its
business by orienting it to different types of customers in different countries according to
the specific contexts. Hence, this study focused on the residential customers who had
installed or would install solar panels on their house rooftops in the future.
The first constraint was that of time for data collection. Each customer analysis required
a different data set, and additionally the other products, excepting the residential battery
(Powerewall) were still in a developing stage in terms of concept and usage as well as
contingence upon government policy.
Therefore, this paper examined the attractive market of the home battery system
product of Tesla Energy by investigating these two aspects:
 Which location is the best for residential stationary storage battery in terms of
economic benefit and the sizeable potential market size?
 Next, amongst the countries surveyed, which country has favourable institutional
environment and favourable customers for the product?
In terms of technology prospects, energy storage system (ESS) is of two types: thermal
energy and electric energy. Because Powerwall was related to storage of electricity, this
was the sole focus of the study.
Also, this study did not calculate the profitability for each country, as it was not
meaningful to calculate profitability at specific time. The profitability is dependent on the
mid and long term environmental changes, and the government can change the support
policy according to the evolution of technology development. So, this study did not focus
on the cost-linked benefits of the Home battery system in country-based comparisons or
when the cost of storage would attain the level of break-through.

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Additionally, the study did not address the production capability and operational strategy
of Tesla Energy. Firstly it was not possible to examine this as the data is not disclosed
even within the company and it can also be too early to build specific plans. This study
also did not aim to present strategic recommendations to TESLA.
1.3 Structure
This study covered the following in the sequence below.
1) Literature review about internationalization theory to see what aspect needed to be
considered for Tesla Energy’s move in the past and the future.
2) Definition of variables in these two steps:
- First : variables were identified to find out the drivers of solar PV customer: the
potential customer of Home battery system in the different stages of the product cycle in
order to investigate the differences in the customer, who will be the user of home
battery system, in each product cycle of solar panel.
- Second: the economic and non-economic variables to measure the attractiveness of
Home battery system in the 19 countries, which have been projected by the
International Energy Agency (IEA) to deploy cumulatively over 2GW solar PV by 2020
3) Data collection and analysis in order to make league tables and DPM by examining
product characteristics and status of power system in each country surveyed.
- 1st Round data collection: secondary data collection
- 2nd Round data collection: primary data about non-economic factors by survey to
energy industry experts.
4) Presenting of league tables and DPM and discussion of study findings and
recommendations for international business theory, especially Product Cycle theory.

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2 Literature review
This chapter examines the literature on internationalization to identify the rationale
behind the selection of international markets, which would be useful to Tesla Energy.
The selection of an appropriate entry mode in a new market makes a significant
difference in the result of the choice. So it is obvious that multi-national enterprises
(MNEs) have a specific rationale for expanding their business to foreign countries. The
key rationale identified through a review of the existing research can be applied
practically to Tesla Energy and vice versa, while taking the characteristics of the power
system into account.
There are many academic theories for International market selection. However it is hard
to say that there is a dominant theory as immense variation can exist within the situation
and the businesses themselves. In addition, these theories are interconnected and take
a different stance, even though the main theme may have the same foundations. The
academic theories can be categorised as constituting :
 1) the discussion about the reason why companies try to expand their business
while taking risks of liability of foreignness,
 2) the process and effectiveness of the international market search practice,
 3) and the main factors which will allow the firm to maintain or develop
competitive advantage by expanding its business into foreign countries.
2.1 Reasons for Expansion Abroad
2.1.1 Competitive Advantage
Competitive advantage is the capability by which companies maintain superiority over
the competitors and new entrants. It is a crucial factor for keeping ahead of competitors
in the highly competitive market. One of reasons why companies try to expand their
business is to hold onto their competitive advantage (CA) and develop it even further.
Ghoshal (1987) has summarized three sources of CA. He notes that companies, which
have achieved efficiency in current operations, can expand to foreign market. As a
result of that, they can manage risks by diversifying and growing their CA through
innovation, learning and adapting from new market experiences and collaborating
between new markets. This is presented in Table :

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Table 1Source of Competitive Advantage (Ghoshal, 1987)
With reference to CA, MNEs can adapt their strategy by considering two factors:
pressure of cost and response to local needs. These two factors can affect their CA
(Bartlett & Ghoshal, 1987). This adaptation is categorised in Fig. below:
Figure 1International strategy (Bartlett & Ghoshal, 1987)
This model can be related with the other theories because these four categories are
contingent upon product characteristics, resource commitment and host market
(location) advantages, which serve as approaches for achieving effective entry into
international markets.

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2.1.2 Stage Theory : Uppsala model
The Uppsala model describes international market entry as a phase, which succeeds
domestic success or extends domestic CA to foreign markets. The expansion phase
occurs in the following way. Firstly, the company begins by exporting excessive stock to
foreign countries. As experience accumulates, it uses the agent or intermediary in host
countries to meet new needs of the customers. Finally, it builds subsidiaries and
manufacturing capability to meet the demand and to exploit profit. (Anderson &
Gatignon, 1986)
However, the facet has changed significantly as cost of transportation goes down and
institutional support increases. Nowadays, it is common for new start-ups to aim at
international operations even in the initial stage. However, the strength of Upsala theory
is that companies necessarily have limits to their resources and need to manage risks.
Thus, it relates to the resource -based theories and with extensive empirical evidence to
substantiate its premises.
2.1.3 Product life cycle internationalization theory
As seen in its name, the PLC model (Vernon, 1979) explains the reason for
internationalisation of MNEs as a result of the reaction to the change of PLC. It explains
that MNEs, which have developed technology and produced innovative products, first try
to expand business by exporting with high margin of price in markets nearer to the home
market. As competition grows, the need to produce with low cost and seek investment in
foreign countries, which can provide lower factors increases. This product is amenable to
standardization due to the potential for exploitation of economy of scale. And at last when
the advantage of the product is displaced by new innovative products, two options will
remain : move to relocate or to stop production of the product.
This theory incorporates previous theories such as competitive advantage (Ghoshal,
1987) and stage model(Anderson & Gatignon, 1986), which explain internationalisation
as one of the attempts at seeking demand (market) within resource constraints.
In addition, the PLC theory is in the line with internalization by explaining the merit of
internalization as the MNEs’ need to adjust according to evolution of product cycle and
there are a number of empirical evidence that demonstrate the pattern(Giddy, 1978)
This theory, especially, explains well innovation based MNEs and the evolution of
products, the competitive advantage of which is based on new technology.(Vernon, 1977)

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They can make use of their monopolistic advantage in technology in near markets with
little concern for making lower priced products. And as competition grows, they make the
decision to expand to foreign countries, which are still imperfect markets, where they can
exploit by making use of the internalization advantage.
However, there are some empirical studies that do not follow the track of PLC theory in
some industry(Giddy, 1978) as business environment has been changing. This is found
even in Vernon’s study, which says that the MNEs’ ability of multinational scanning has
changed the business(Vernon, 1977). There is also criticism that the theory does not give
properly explain the phenomenon under study in some industries such as raw material
industries, and that it does not provide enough strategic recommendations for
effectiveness in the competition in the foreign host market. Also some critics (Dhalla &
Yuspeh, 1976) complain that PLC theory does not give predictive suggestions and that it
could provide wrong sign to abandon the product or market which can be revived.
2.2 The Process and rationale of selecting International Market Entry Mode
The reasons for choosing international market entry mode have been explored within
literature. Pan & Tse( 2000) investigated the cases of companies, which had invested in
China since the commencement of China’s open policy and categorised the entry
choices into four modes as depicted in Figure below, arguing that MNEs make
decisions in a hierarchical order. (Pan & Tse, 2000)
Many researchers have tried to understand which factors affect the choice of entry
mode, largely through empirical quantitative studies. Lindqvist (1991) examined the
preferred entry modes of Swedish young technology based firms. Similarly, a study
(Grønhaug & Kvitastein, 1993) has investigated the factors that influence the firm’s
choice of institutional arrangements for expansion to foreign markets. For instance,
Burgel & Murray (2000) have investigated the rationale of young technology SMEs in
UK to export mainly to nearby markets such as the EU and the US. In a similar way,
overseas market expansion strategies of technology SMEs, especially in the
perspective of regulation have been examined by Crick and Jones (2000). In extension
of the work on entry modes, a study (Carlos Pinho, 2007) has investigated how
ownership advantage, managerial practice and location advantage create an impact on
entry mode decisions, establishing that the international experience of firms, capability
of innovation and market specific knowledge are key factors in this. Additionally, there
are multiple empirical studies, which have investigated the effectiveness of new market
entry mode decision, depending on considerations such as the preferences of CEOs,

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resource constraints and product characteristics.(Hill et al., 1990). These studies are
meaningful in that they suggest a plenty of cases and implications in the application of
theory. Especially, hierarchical theory (Pan & Tse, 2000) gives a succinct picture of the
entry mode to help make decisions efficiently. Other theories have investigated factors
determining international market entry choices, which include resource commitment,
risk and return, and control.
2.2.1 Hierarchical theory
According to Pan & Tse (2000), there are mainly four entry modes, which include
Export, Contractual Agreements, Equity Joint Ventures, and Wholly Owned Subsidiary
(WOS). They analysed empirical cases in China and categorised these four modes and
highlighted evidence of two steps taken by MNEs while deciding the mode. Firstly,
MNEs decide between Non-Equity modes and Equity modes. Then those who select
Non-Equity modes have to make a further choice between export and contractual
agreement, while those who select Equity modes have to choose between JV or WOS.
Figure 2A Hierarchical Model of Choice of Entry Modes (Pan & Tse, 2000)

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This theory gives holistic view of the types of internationalization and quick
understanding to the advantage and disadvantage of each mode. However it is the
result of empirical search to companies entering into China market and have no
discussion about the rationale of hierarchical step and about the context of locality and
have little suggestion to international strategy.
2.2.2 Resource Commitment
All the entry modes require specific resources. For example, even for export mode,
companies need to have resources to monitor the host countries’ intermediaries in order
to protect the product’s originality. Establishing a wholly owned subsidiary using the
Greenfield method requires considerable financial investment and a longer period of
time. On the contrary, contractual agreement such as licensing and franchising require
high level of monitoring resources investment (Hill et al, 1990)
It is natural for companies to consider the feasibility of strategic decision. The fact that
SMEs most use the entry mode of export(Lindqvist, 1991), Burgel and Murray (2000)
says that.
2.2.3 Risk & Return, control
Besides resource commitment, the level of risks compared with return and the level of
control are also important considerations. (Hill et al., 1990; Kumar & Subramaniam,
1997) Firstly, resource commitment is linked with the level of risk. The higher the
resource investment such as Greenfield construction or acquisition is, the more risks
there will be. In similar context, Kumar & Subramaniam (1997) have suggested a
decision frame of risk, return and control as shown in the Table below, which is known
as ‘contingency framework’. It is suggested that the controllability is an important factor
for MNEs seeking to decide the entry mode.
Table 2contingency framework(Kumar & Subramaniam, 1997)
Export License
FDI (Equity mode)
JV Acquisition Greenfield
Risk Low Low Moderate High High
Return Low Low Moderate High High
Control Moderate Low Moderate High High
The level of control is a crucial factor for MNEs, which strive to create a favourable
market environment and to affect local customers throughout the period. For example,
when Coca Cola entered China(Mok et al., 2002), it chose JV at first because of the
regulations imposed by the Chinese government. However, as its network has grown in
China, it has tried to change the regulations and adapt to changes. As a result of this, it

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has succeeded in being allowed to achieve the greenfield investment in concentrate
facility, instead of JV, which enables the protection of the secret technology. Likewise,
many MNEs which seek to implement their own operational and strategic decisions opt
for an entry mode that allows for more controllability and risk. (Anderson & Gatignon,
1986)
2.3 Main factors for Successful Expansion
Lastly, there is extensive research, which has investigated the success factors for
internationalization. These are transaction cost theory, eclectic paradigm (OLI
framework), institutional theory and social capability (network) theory. This also explains
the reason for internationalization and the choice of entry mode.
2.3.1 Transaction Cost Theory (Brouthers & Hennart, 2007) (Williamson, 1998)
This theory states that when transaction cost is high, MNEs choose FDI as an entry
mode. (Brouthers and Hennare, 2007). According to this theory, MNEs choose a
specific entry mode and organisation structure that harmonises with the strategy in
order to minimize transaction cost, which includes negotiating, monitoring and enforcing
a contract (Williamson, 1998). This theory is also known as internalisation theory
because MNEs make the international transaction internal to reduce transaction cost. In
this context, this theory is incorporated in the PLC internationalization theory in that PLC
theory says in a maturity stage MNEs starts to reduce transaction cost to compete with
rivals.
2.3.2 Eclectic Paradigm (Dunning, 2000; Dunning & Lundan, 2008)
Dunning and Lundan (2008) have established the Eclectic paradigm, otherwise known
as the OLI framework. This theory is presented in the table below. According to this
theory, MNEs choose FDI when they can find or need three advantages in the market,
which are Ownership advantage, Internalization advantage, and Location Advantage.
On the contrary, in markets where they cannot find location advantage, MNEs they can
just choose export or license mode. And where there is no Internalization advantage,
they choose license mode.

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Table 3OLI framework(Dunning & Lundan, 2008)
Ownership
Advantage
Internalization
Advantage
Location
Advantage
FDI O O O
Export O O X
License O X X
Each advantage represents these merits:
- Ownership advantage refers to the advantage, which is still useful and effective
irrespective of location. Or, competitive advantage does not necessarily depend
on the location.
- Location advantage means that any traits such as markets, resources, clusters
and institutional support offer better advantages than those available in the home
country.
- Internalisation advantage refers to the advantage of making one of the value
chains internalised because of high international transaction cost.
Resource based theory and transactional theory are combined with this theory because
deciding the entry mode requires the capability of resource commitment and because the
origin of each advantage is linked to reducing transaction cost and enhancing
controllability.
2.3.3 CSAs and FSAs
This theory states that internationalization is a way to develop its competitive ownership
advantage in the home country and transfer or expand this to the market where there is
location advantage. This reduces the transaction cost by keeping the company’s
ownership advantages in foreign market in order to compete with local
companies.(Rugman, 2010) Within this context, this theory can be interpreted as
signifying that internalization is a new way to maintain the competitive advantage.
Therefore, it can be explored to the different answer to the question of where the CA
come from.
Rugman (2010) has suggested the matrix of CSAs and FSAs and showed that the aim
of the internationalization can be decided by the constraints of combination of these two
factors : country-specific advantages(CSAs) or firm-specific advantages(FSAs). This
matrix suggests that country specific advantage will attract MNEs to choose FDI, and

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this FDI can be defined differently according to the purpose of each, namely resource
seeking, market seeking, efficiency seeking and asset seeking.
Figure 3 The Eclectic Paradigm’s motive for FDI in the FSA/CSA Matrix(Rugman, 2010)
2.3.3.1 Country-Specific Advantages( CSAs) : The Diamond Theory (Porter, 1990)
CSAs can be found in the theory of Michael Porter, which is known as the diamond
theory. Porter (1990) notes that nations become successful by providing locational
advantage and raising successful leaders with inner-rivary. So this theory also provides
a bottomline about which aspect attracts the MNEs to a particular country, and this
eventually creates prosperity within the chosen country. According to the Diamond
Theory, there are four factors which enable countries to increase national wealth.
Among these, three are related with the lacation advantage: factor condition, demand
condition as well as related and supporting industries as seen below figure.
For example, if a government tries to make a free trade zone or be part of economic
blocs, it will attract MNEs. This is easily observed in cases such as NAFTA, effected in
1994. For instance, through new alliances, Mexico enhanced the size of trading
(averaging $12 billion) with the US, and MNEs increased FDI into Mexico significantly
(Peng & Meyer, 2011, p275) and many MNEs have entered the Chinese market
seeking new potential customer (demand condition) and lower labour cost (factor

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condition) or Silicon Valley where new technological support, network, and talents are
available.
2.3.3.2 Firm-Specific Advantages (FSAs)
FSAs are the advantages the company maintains by itself, which are similar to the
ownership advantage and internalization advantage in Dunning’s context. The last two
advantages can be obtained through internalization (Dunning 2009)
2.3.4 Institutional Theory (Brouthers & Hennart, 2007)
Institutional theory (Brouthers & Hennart, 2007) contends that the host country’s
institutional support affects internationalization because it is reflected in the whole
aspect of the environment, which is fundamental to the marketing strategy as reflected
in the PESTEL analysis: political, economic, social, technology, environment, and legal
aspect. Therefore, the theory includes formal and informal institutional support:
- Formal : law, accounting practice, advisory agency
Location
Advantage
Figure 4Location Advantage adopted from the Diamond Theory (Porter, 1990)

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- Informal : cultural characteristics and political rules and regulations to cognitive
and normative dimensions (Scott, 1995)
For example, it is often studied how much important the alliance with government and
partner is in specific condition under which legitimation has a crucial effect on the
performance. (Dacin et al., 2007)
2.3.5 Social Capability Theory (Chetty & Agndal, 2007; Prashantham, 2011)
This theory refers to the capability of acquiring and exploiting resources through
business networks (Chetty & Agndal, 2007). The network or socialising takes place with
customers, suppliers and competitors. Therefore, it is connected to theory of Michel
Porter’s 5 forces. Using proper entry modes, MNEs can enhance their capability, which
will reduce transaction cost and augment the power of the company in the competitive
environment. Also social capability theory is connected with institutional theory in that
social capital as reflected in institutional support will help to reduce external
uncertainties associated with formal and informal contract (Prashantham, 2011)
These types of theory are in line with a what has been discussed above because the
success factor will affect the process and mode choice, and also because the four
theories overlap with each other to some extent in terms of the scope of definition. For
example, if the location advantage of OLI framework is explained broadly, it can
accommodate the institutional theory and the social network theory.

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3. Operationalisation and Hypotheses
3.1 Characteristics of Home Battery System customer
Home battery products are quite unique in that they affect the power grid system,
because of which, these are considered not just consumer goods but also public goods.
This home battery product provides value to the owner and the whole power system at
the same time. Therefore, measuring the value of the Home battery was important in
order to identify the benefits both for the users and for the whole power system.
The first consideration was the type of customer who would use this product. While the
kind of customer likely to purchase the Tesla Powerwall can vary, preferences based on
nationality are not likely to set the customers apart, and it is most likely that, at the very
least, the solar panel installers will be drawn to buying the product. In this respect, it is
quite useful to identify the drivers of residential solar panel customers and to look at the
evolution of these drivers in view of the fact that the Home battery system is a high
technology product, which is in the early stage of the product life cycle rather like the
solar panel technology was a decade earlier. Statistics as to the evolution of the solar
panel instalment around the world indicate that it entered into the maturity phase after
2010, with sales growing exponentially due to the increase in supply by Chinese
manufacturers.
Figure 5The evolution of the volume of Global solar PV capacity. (OECD, 2015, p9)

22. 22
In this context, it is important to be aware that each country is experiencing a different
status of the power system and has a different type of demand profile, which leads to
variation in the economic value of the battery system. This value is also different
amongst countries according to the gap in solar radiation and the level of government
support.
3.2 Hypotheses for identifying the target customer
One study (Dastrup et al., 2012) describes the solar panel installers in San Diego
County as ‘environmentalists, the college-educated, baby-boomers and later
generations, and richer households’ and also notes that owners of large nice homes in
rich white neighborhoods are more likely to install solar panels than small homes within
poor minority neighborhoods. Thus, it leads one to draw the conclusion that customers
located in comparatively high income community might be less sensitive to the price of
the panel. However it may be noted that the study was carried out before 2012 and only
released in 2012. The customers observed were people who had installed panels
between 1997 and 2000, with the data being sourced from real estate transactions
during that period. This suggests that financial benefits had little effect as a driver, at
least before 2010. Therefore, it can be assumed that before 2010, solar panels were
more likely to be installed in countries where household income was high as a whole
rather than where income level was low.
According to this estimation, marketing theory may suggest looking at the product life
cycle of the solar panel, which might indicate the trend of number of installed solar
panels. It is also assumed that following the increase in the solar power installations, the
customer base may have changed, which is another issue this paper aimed to
investigate. If household saving ratio is used for the variable representing household
income level, it can be assumed that solar power cannot be installed and used more,
while can be before 2010, in a country where household saving ratio is higher in the
period after 2010 when the technology enters growth or maturity stage in the product life
cycle.
3.3 Research questions
This study investigated two main questions by using correlation analysis and qualitative
analysis. Firstly, it was assumed that the driver of solar PV installation would imply the

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drivers (variables) of the Home battery system. And the evolution of the driver according
to the product life cycle needed to be investigated. Lastly, on the basis of the correlation
analysis and qualitative analysis, variables affecting the sales of Home battery system
were defined. By collecting the data for each variable across the countries, we
estimated which countries were the best target market for Tesla Energy. And if the
result says the best market is not the US which is the first market but somewhere else it
will give meaningful implication in terms of PLC theory.
Throughout the processes above described, the main questions in this study were as
follows:
1) Who was the target customer for Teslar’s Home battery system around the world?
 Economic incentive might not be the first and only driver for Solar PV installation
 It will be safe to infer the main driver of Home battery system from that of solar
PV users
2) Which countries and segments provided maximum economic value to Tesla Energy?
 Home battery system was an issue not only for solar PV users but also for
transmission operators and the government because it provided economic
benefits to both using household and the whole economy including transmission
operation and emission reduction.
 The value of Energy storage, which varied according to the situation of power
operation system and the magnitude of the value would be used to motivate the
designing of complementary schemes.

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4. Methodology
4.1 Study framework
This study was aimed at identifying the best foreign market for Tesla home battery
installed with solar panels. The literature review helped to identify this gap in research,
thereby helping to define pertinent research questions for this study. Firstly, several
International market entry models were investigated to appropriately apply theory to the
Tesla Energy case. To do this, the theoretical approach was challenged and fortified by
examining the main drivers of solar PV through correlation analysis (1st round data
analysis).
Next, the detailed power operation system status of each country was analysed to define
relevant factors for Tesla home battery. Those were identified, which were likely to have
impacts on the economic benefits of both residential customers and public authorities as
well as transmission operators.
Lastly, the values of the economic and non-economic variables were tabulated in order
to draw perceptual positioning map of potential countries and to build league table in
terms of market attractiveness in the current product life cycle (2nd round data analysis).
This study was premised on the assumption that the main driver, which once encouraged
solar PV installer would work similarly in the case of opting for panel connection to the
Home battery by customers. This assumption is sensible because potential customers of
battery system are who have already installed solar PV on their roof and have
experienced the usage of the panel.
Therefore, firstly correlation analysis was conducted to detect and to compare the driver
of solar PV in 2008 and in 2010, which might be evident in the link between the shares of
installed PV capacity compared to income level of households. This analysis was
implemented amongst EU countries for two reasons. Firstly comparing EU countries
eliminated the difference of government policy vis-a-vis renewable energy, while there
are still difference in the commitment to the policy between EU countries.(Dusonchet &
Telaretti, 2010b) Secondly, it has been established that solar panel use is the most
prevalent in the EU amongst the world, which signifies that the evolution of the product in
terms of PLC could be examined with few errors within this market as seen below figure.

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Figure 6Solar PV annual capacity additions by region(IEA, 2014c, p174)
This data analysis established the most important driver, or the importance of the
economic incentive for target customers. According to this result, appropriate variables
for Home battery product were defined and analysed through the second data collection.
Lastly, target customer positioning by considering the weight of each variable was
conducted with the matrix of economic and non-economic factors of each country. This
DMP graph provides a clear view of the target market to Tesla Energy and can be also
used to develop a league table according to any specific variable between the countries.
4.2 Data collection
A large body of the quantitative data needed was obtained by secondary research from
International Energy Agency (IEA), which is a subsidiary institution of Organisation for
Economic Co-operation and Development (OECD).
While IEA publications were accessed electronically through library certification, however,
some detailed data could not be accessed due to copyright and methodology for
projection data is disclosed with limitation. So these were collected during a research trip
to Paris where the IEA is located. And the methodology of projection solar PV was also
investigated via interviews during the same trip.
Data collection was undertaken in two stages. The first stage focused on identifying the
solar panel driver in the EU market. The second stage focused on calculating
attractiveness of 19 countries around world for home battery system in consideration of
two aspects: economic benefit and non-economic benefit.

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4.2.1 1st Round: Residential solar PV drivers
The first round of data collection focused on identifying the solar panel driver in the EU
market. These were all quantitative and secondary data collected through electronic
means. Also the data sets of 2008 and 2010 was collected to compare and analyse
whether drivers had evolved according to the PLC phase.
Table 4 List of Variables for analysing Solar PV driver
Variables Type1 Type2 Data Source
Share of Solar PV to
the Renewable Energy capacity
Secondary Quantitative IEA
IRR(%) Secondary Quantitative Academic
research(Dusonchet
& Telaretti, 2010a;
Dusonchet &
Telaretti, 2010b)
PV Energy Yearly Produced
(kWh/kWp)
Secondary Quantitative
Gross Household Saving Rate(%) Secondary Quantitative Eurostat
Amongst 28 European Union (EU) countries, the values of 20 countries were examined,
while eight countries were excluded due to the restricted availability of data.
- Countries examined : Austria, Belgium, Czech Republic, Denmark, Estonia, Finland,
France, Germany, Greece, Hungary, Italy, Luxembourg, Netherlands, Poland,
Portugal, Slovakia, Slovenia, Spain, Sweden and the UK
- Countries excluded : Bulgaria, Croatia, Republic of Cyprus, Ireland, Latvia, Lithuania,
Malta, Romania
4.2.2 2nd Round
The second round of data collection required both quantitative and qualitative data
because in addition to the economic benefits, non-economic factors are also important in
evaluating the location advantage.(Dunning & Lundan, 2008; Porter, 1990). Also the
examined countries are 19 countries around the world including the US, which are
expected by the IEA (2014c) to deploy over 2GW solar PV cumulatively by 2020.
- 19 countries : The US, Canada, Chile, Mexico, Australia, Japan, Korea, Germany, Italy,
Turkey, UK, France, Spain, South Africa, China, India, Thailand, Saudi Arabia and Brazil

27. 27
The rationale for restricting the scope of data collection into sizable countries in terms of
solar PV was simply that the Home battery system would be deployed with solar PV.
Hence, the market in countries which had projections of cumulative capacity below 2GW
in 2020 could be neglected because of lack of economic scale.
4.2.2.1 Qualitative data
For qualitative data, energy industry experts were surveyed through two methods. The
first survey was administered via email to a total of 135 respondents, consisting of energy
subject related master degree students and alumni currently employed in electricity utility
companies such as E.ON and NationalGrid as well as experts who frequently carry out
discussions on topics such as energy storage and renewable energy in Linkedin groups,
and via posting on expert website of Linkedin group such as ‘Energy storage and Grid
Technology’, ‘Energy Storage Association’, ‘Warwick London Alumni Network (W.LA.N)’,
‘The Renewable Energy Network’, ‘Warwick Global Energy & Utilities Professional
Network’, ‘Young Energy Professionals’, ‘Smart Grid / Energy Storage Experts Power’,
‘Utilities & Renewables’, ‘Group Power Transmission’, ‘Power Generation in the UK’,
‘IEEE Power & Energy Society’ and ‘Energy Institute’
The questionnaire was designed with 5 score, which consisted of question items on
customer behavior in terms of economic drive and environmental drive, institutional
support credibility, and government commitment to climate change. The questionnaire is
appended in Appendix 1. Even though it takes 5 score, there is the option ‘6’ which is for
the respondent who is not familiar with specific country. This was the last resort to reduce
drop rate after two times trial with the recognising that it is unrealistic to answer all 19
countries, adding on this, each question can be passed without answering.
4.2.2.2 Quantitative data
Quantitative data set was collected by measuring the scale of economic benefit in each
of the 19 countries. The variables were defined by reasoning, described in following
paragraph, about the characteristics of Home battery product and solar PV, which will be
worked together and power system such as grid status and level of liberalization etc. The
variables are provided in Appendix 2.
4.3 Rationale for Variables
4.3.1 1st Round Variables
‘Share of solar PV to the Renewable Energy capacity’ was selected as the dependent
variable. The main purpose of correlation analysis with SPSS tool was to find out the
independent variables, which have a causal influence on the share of installed PV.

28. 28
In terms of validity of the ‘Share of solar PV to the Renewable Energy capacity’, it can be
argued that the Share of solar PV to the Renewable Energy capacity can be determined
by the condition of solar radiation, or because the countries which have better solar
resources are more likely to favor solar panels than other renewable energy sources. For
example, the countries having a surfeit of hydro resources can have lower share of solar
PV to renewable capacity even though share of solar PV to total capacity is relatively
higher. So, as a dependent variable, Share of solar PV to ‘Total capacity’ was also tested,
but a similar result was found.
As independent causal variables, three variables were considered to see the causal link
to profitability of solar panel, solar radiation, and income level.
- IRR is used as the proxy of profitability of solar panel,
- volume of yearly produced PV Energy, which is closely dependent on solar radiation,
is used for Solar radiation,
- and gross household saving rate which is the proxy of household disposable income.
Grid parity is also optimal variable, which can show the profitability of solar PV. However,
grid parity data of the 20 countries was not available because it includes all subsidies
such as Feed in Tariff (FIT), tradable green certificates (TGC), tax credit and net metering
etc. In this situation, Luigi & Enrico (2010a; 2010b) calculated the profitability of solar PV
in EU countries by calculating the cash flow, the Net Present Value (NPV) and the Internal
Rate of Return (IRR). Every factor affecting profitability such as Grid parity, levelized cost
of electricity(LCOE), retail electricity price and production volume per unit solar PV is
reflected in their work. Among the indices, IRR is chosen just because more value was
created in their paper.
4.3.2 2nd Round Variables : Variables for investigating attractive Home battery market
Variables for qualitative analysis were defined according to Country-Specific Advantages
(CSAs), which are referred to Porter‘s Diamond theory, including four factors of
determinant to National attractiveness. Among these factors, three factors which
established the attractiveness of the countries were considered as categories: factor
condition, demand condition, and related and supporting industries.
- Factor condition : economic benefit variables which comes from economic value to
grid and customer.
- Demand condition : Market size (Income level and Size of solar panel instalment)
- Supporting industries : institutional support (government policy consistency and
credibility of downstream supply chain, or instalment service provider)

29. 29
Rationale of each detailed category will be investigated in the following chapter by looking
at the characteristics of solar PV and energy storage industry.

30. 30
5. Rationale of 2nd
Round factors
This chapter explores energy storage technology to identify what imparts value to
electricity storage products and to explicate the rationale for factors that help to evaluate
attractive markets for the home battery product.
5.1 Value of Electricity storage
Electricity storage is a valuable technology for a low carbon society because its use
links up to several important values. The benefit is mainly categorized into two: load
shifting and balancing the supply and demand (IEA, 2014a)
- Load shifting: peak load demand can be met through the use of stored electricity,
which will provide twofold benefits. Firstly, it will reduce the capital investment for
extra peak plant construction. Secondly, it will reduce the production of expensive
peak power plant.
- Balancing the supply and demand : frequency regulation, load following, voltage
support, black start, transmission and distribution(T&D) congestion relief, Off-grid
Spinning and non-spinning reserve and investment deferral
These values are crucial for reliable power system operation because it allows for the
supply and consumption of the electricity simultaneously. If it does not have the backup
of the stock, this might create huge inefficiency in system operation and even the
possibility of blackout (Dunn et al., 2011)
The value of this function specially has significantly increased as renewable energy has
increased because it allows renewable energy generation for later use, thereby
reducing the amount of curtailment and providing the grid with flexibility to react to
intermittent renewable generation.
5.2 Factors for measuring the value of electricity storage
5.2.1 Reserve margin
Securing enough capacity to meet demand in power system is crucial because of the
unique characteristic of electricity. The supply cannot surpass the demand at any
moment and vice versa. So, when there is lack of supply, the electricity storage values

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go up significantly due to load shifting value which is found in two aspects. One is
avoiding peak plant investment, and the other is smart usage, which is deferral of the
use of electricity when price is low or sale of it when the price is high.
In the market where the reserve margin is narrow, the value of investment avoided is
considerable. Reserve margin means spare capacity after meeting of the demand. So,
the narrower the margin is in the power system, the higher is the value of flexibility of
power grid and load shifting because when the reserve margin is small, grid flexibility
significantly shrinks to lead inefficient power system operation.
5.2.2 Capacity of grid integration of renewable energy
Flexibility in grid operation is a prerequisite for increasing renewable generation. This
results from the unique characteristic of electricity. When renewable generation ramps
up in strong wind or sun, conventional thermal plants should run down accordingly to
balance demand and supply, if they cannot follow that speed of the renewables’
ramping up, renewable output should be curtailed or wasted for the balancing.
The problem is that conventional thermal plants are slower to start or stop than
renewables, and that when their running scale goes lower, their marginal cost goes up.
In this respect, the base load thermal plants such as coal and nuclear experience more
difficulty in reacting. Therefore, usually combined cycle gas turbin(CCGT) power plant
play an important role in adjusting to the volatile movement, but CCGT is the one that
requires high variable cost of LNG, or other plants so called peaking plant are more
expensive.
For example, in Germany sometimes wholesale price has gone into minus, which
means that if the power plant is generating, it should pay to the market instead of be
paid for in terms of the cost of fuel. This occurs when the renewable generation surges
unexpectedly and requires slowing down in the output to conventional power plants
such as those that are coal fired. However, the plants are not flexible enough to slow
down the output quickly enough.
Sometimes when the conventional power plant fail to cut back in response to increasing
renewable generation, energy generated sometimes need to be curtailed, which means
the wasting away of the renewable output. This is a big loss for the power system. In
theory the most cost-efficient way of operation is that base load plant should continue to
operate with less fluctuation. To do that levelling the load is important, which means
reducing of peak load and raising of minimum load to make base load and middle load
power plants stable.

32. 32
IEA has investigated the cost of integrating large share of intermittent renewables and
noted that ‘total electricity costs at 45% of variable renewables would be increased by
about 10% to 15% with current wind and PV technology costs.’ (OECD, 2015, p37)
Challenge for integration in transmission and distribution (T&D) line can be evaluated
through the following three variables : amount of renewable generation, the age of the
grid and disconnection of the grid.
5.2.2.1 amount of renewable generation
The more the renewables used in the power system, the more valuable electricity
storage can be because variable or intermittent renewables require the power system to
be more flexible and resilient.
5.2.2.2 level of age of the grid and disconnected
Due to its balancing role, electricity storage can defer transmission investment. As an
example, we can cite Pressidio case in Texas where the Sodium-sulphur battery has
been installed for deferring transmission investment.( IEA, 2014a, p22). Old
transmission problem can be alleviated by storage backup. Therefore, the status of
existing and planned infrastructure investments in both transmission and distribution line
affects the need for storage.
For example, in a study of “Renewable Electricity Futures Study” done by the United
States Department of Energy in 2012, it was forecasted that the nation’s total installed
electricity storage capacity could grow to between 103 GW and 152 GW in 2050. (IEA,
2014a, p32) And this range of demand has been developed through the increase in new
transmission investments. Therefore it makes sense that the transmission and
distribution line investment plan is a key factor in deciding the value of storage.
5.2.3 Existence of Substitutes : Hydropower including PHS
The balancing demand and supply can be managed by the use of electricity storage
technology, and these types of technology and applications are under development.
The fewer the substitutes, the greater will be the value of the Tesla Powerwall.
With respect to technology, there are several technologies for electricity storage, which
can be compared as substitutes to Tesla Powerwall. These are SMES, EDLCs,
Flywheels, PSH, CAES, Electrochemical Batteries and Hydrogen system as shown in
the table below.(Chatzivasileiadi et al., 2013)
In these technological classes, each technology has been developed for
commercialization. And this status is presented in the figure below, which shows the
implications of the competitors of Tesla Energy.

33. 33
Table 5Classification of EES systems (Chatzivasileiadi et al., 2013)
Tesla Powerwall falls into the Lithium-based (Li-ion) batteries in the electrochemical
class. According to the study, feasibility for specific applications are as below. As of
2011, Li-ion technology can be ideal for a range of applications. (Chatzivasileiadi et al.,
2013)
Figure 7 The maturity of the technologies (IEA, 2014a, p16)

34. 34
Figure 8EES present feasibility, future potential, need for further research and development (Chatzivasileiadi et al., 2013)
Therefore, in situations where each technology has been competing with others in terms
of advantages, which are allowed in specific circumstances, the only matured and
cheapest substitute can be PHS. This is evident by the fact that PHS is used for
currently 99% of Energy storage (IEA, 2014a)
Figure 9Current global installed grid-connected electricitystorage capacity (MW, (IEA, 2014a, p17)

35. 35
The only disadvantage is country specific, which can span dependence on geographic
situations, time expended in construction and in some countries environmental issues.
So, in countries which have ample PHS resources, PHS can be utilized at the end,
which reduces the need for electricity storage demand, thereby acting as Electricity
storage substitute.
5.2.3.1 The share of Hydropower resources
Hydro power plant can ramp up and down rapidly to respond to intermittent renewable
generation. Therefore, it is used as tool to raise the flexibility of power grid. Pumped
Storage Hydropower (PSH) is also a part of this category.
These resources are highly restricted to conditions of geography. Some countries such
as Northern Europe and China have ample resources compared to others, which
implies that these countries have less need of storage than countries with fewer hydro
resources.
2.2.3.4 Electric Vehicle deployment
Electric Vehicle( EV) can be regarded as large scale storage of electricity. Therefore, it
can be used as a countermeasure for variable renewable generation integration. EV
can also be used as a load shifting tool. It will be obviously be a substitute for balancing
the role of Home battery system.
However, in this study it was not considered as factor because of three reasons. Firstly,
it is a meaningful substitute in the long term because it takes a long period to acquire
complementary infrastructure such as smart grid, adequate super chargers and
supporting electricity policy for assuring harmonious charging to grid operation.
Secondly, this is still in the early stage of diffusion, and the projection of EV is not
reliable. Lastly, it is not obvious EV will be a substitute or complementary product. If EV
changes customer behaviour in favour of the home battery system and smart house
concept, then it can be seen as complementary.
5.3 User Value
The logic of Tesla Energy’s Home battery system rests on saving electricity during the
day, rather than selling it to the grid, when the price is not high or low enough and using
the stored electricity during the night or when the price is high. So, user value is
dependent on both market structure and energy use pattern.

36. 36
According to Tesla(2015a), the value of Powerwall comes from deferring the usage time
to different times when the electricity price is high, which falls into the load shifting value
category as shown below:
Figure 10How home battery system works during the day (Tesla, 2015a)
In situations where solar panel produces electricity when demand is low(in the middle
above picture), the storage of the production will bring much value for the solar panel.
As implied in the figure, the value of storage will vary by these two factors
- Demand profile : for example if the demand during mid-day is contrary that reflected
in the figure above, the need for storing electricity reduces.
- Time of Use : if power system cannot record the time electricity is used and
produced, the deferral of usage is useless.
5.3.1 Smart metering
By using the Home battery system, household can avoid high rate of payment or sell at
high rate, which will vary according to the rate system. (Tesla, 2015b) This shows the
basic assumption that electricity rate is levied by the time or at least peak or non-peak
categories, which will be set according to different levels of rate. So, value creation is
complemented by these two market systems: measuring by time period and levy
according to so called Time-of-Use.

37. 37
In the markets, where smart meters are available, the probability of battery system
yields more financial value is higher because the home battery system produces
financial value only in this rate system, which levies the rate on the time basis(Time of
Use ; TOU). In addition, the net-metering system in several countries such as the US
has played a significant role by providing economic benefits to solar PV installers. This
infrastructure and enabling settlement system is dependent to government commitment
to adopting new technology and attaining targets.
According to IEA publication, each countries smart meter implementation plan is as
follow.
Table 6smart meter rollout plans (Cooke, D., 2011, p30)
5.3.2 Daily Demand profile
Energy storage battery gives best value when the gap between the peak and the low
demand for electricity is large, and this materialises in the rate system, encouraging
customers to change the consumption pattern accordingly.
There are mainly two types of daily load profiles in countries where solar PV is
prevalent. The difference is the period when the peak occurs. For example, temperate
countries such as the UK have peaks in the late afternoon, while in other countries such
as Japan this occurs around noon when the sun is strong. (OECD, 2015)

38. 38
Therefore the value of battery is greater in temperate countries because they are
allowed to store electricity during the afternoons before peak time and to use more
stored electricity at peak period.
Also, the more solar PV generation takes place, the more volatile the demand curve
becomes, raising the system operating cost. As seen in the figure below, which shows
the net load curve of spring days in California, the so-called the ‘duck chart’ (OECD,
2015, p34), as the amount of solar PV increases year by year, the gap between peak
and low demand becomes noticeable. However, if it has a higher peak during mid-day,
the solar PV increase would reflect a levelling demand profile instead.
Figure 11 Expected evolution of the net load of a typical spring day in California (OECD, 2015, p34)
So, When PV account for more share of electricity generation, systems may require
more reserves to ensure balancing. This makes the value of storage bigger because it
prevent the risks of failures in operating the power system.
When demand profile is examined by the usage as below Figure, household profile show
the evening peak type. This imply household user value of battery system can be bigger
at least in the demand type aspect.

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Figure 12Hourly electricityconsumption profiles for different building types in Germany(IEA, 2014b, P154)
5.3.3 Price of instalment
Instalment price is one of the most important factors in determining profitability.
However, currently there is a lack of information because of the pre-mature stage of the
product. But it is obvious that instalment price will vary by the region as in the case of
the solar panels. When it comes to solar panels, the price varies much because of the
soft cost, which includes financing environment or the number of installers etc.
Therefore, in this study, price of instalment was ignored under the assumption that the
solar PV projection would already reflect it.
5.4 Government Support
Government support is a crucial factor in identifying location advantage according to
internationalization theory. In terms of renewable industry, its importance is greater
because renewable energies are heavily dependent on subsidies and several
incentives. In this study, most non-economic factors in potentially significant markets
have been ranked through surveys by experts in the energy industry.
5.4.1 customer mobility(level of retail price liberalization)
Customer mobility is defined as the rate of switching suppliers, which happens in
countries where the retail market has been liberalised. It can be assumed that in high
mobility the customer is likely to be aware of the changes and respond more to
discernible economic benefits. However, when it comes to Home battery system, which

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is in the pre-mature stage in terms of product life cycle, customer mobility might be a
less important factor.
However the infrastructure which encourage the customer mobility will motivate
communication between regulator and installer and customer which will make diffusion
of new product easily. So, the easiness of switching supplier will be examined and be
taken into account as one of factor. This has meaning in other aspect because retail
price liberalization is prerequisite of supplier switching and this imply higher level of
retail price without any cross-subsidy.
5.4.2 Institutional support
The consistency in renewable subsidy policy is one of important criteria to decide the
investment in renewable investment because the profitability or bankability heavily relies
on subsidy or FIT scheme. When it comes to solar panel in some countries government
have changed its subsidy policy without advance notice or even retrospectively and this
negatively affect to motivating renewables.
Especially when new technology grow, regulatory institutions need to intervene to get
rid of old regulations to disperse the new technology. Also timely developing new
scheme for supporting the deployment is crucial to encourage the renewable, the
storage battery is same category. This is possible in the countries where the institutional
support is guaranteed.
For example, in the US Federal Energy Regulatory Commission Orders 755 in 2011
and 784 in 2013 have put positive impact on energy storage deployment. Without the
Orders, energy storage must have encountered into difficulty because it supply service
in both the transmission and generation portions which was discouraged in order to
maintain the independence transmission grid operators. (IEA, 2014a, p13)
In addition, to high-tech company, technology protection is crucial aspect in decision
making because it is majority of competitive advantage. With the assumption that patent
protection tendency varies by the countries, it was incorporated in the questionnaire to
investigate by survey.
5.5 Supply chain support
5.5.1 Installer credibility

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According to Tesla(2015a), Powerwall products consist of a solar panel, an electrical
inverter, and now a home battery to store surplus solar energy for later use as shown in
the figure below:
Figure 13Design of Tesla Energy’s Home battery system (Tesla, 2015a)
Electricity generated from solar panels with a direct current (DC) is stored or used after
converting to s alternating current (AC) through the inverter. The performance of
invertor and battery management, which controls whether to use or store is crucial to
deciding performance of the whole system.
In solar panel, the quality of installer’s work is also important because performance
ratio, which is the measurement of efficiency of the panel, is dependent on their work
quality (IEA, 2011b). Besides that, the product will be used over 10 years. Customer’s
satisfaction and perception has been accumulated and dispersed in a strong way. So it
is obvious if the users of solar PV who has not been satisfactory to their existing solar
PV, they will not be likely to be encouraged by the maintenance company. So, the
installer’s credit or perceived credit can be assumed to affect the decision of home
battery as well.
Especially considered the characteristic of the product, customer will put the trust to
installer in more important decision criteria as solar panel customers did in the early
stage. Early adaptors of solar PV did not realize how much electricity they will produce
and the performance ratio will be credible. However they decided to install(Dastrup et
al., 2012), alluding significant trust in installer and consistency of government policy.

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5.6 Customer acceptance
5.6.1 Drive to economic benefit
The sensitivity to economic benefit is likely to affect home battery sales. Therefore, the
extent to which financial drive affected is a meaningful variable. Even though it is
assumed that in the early stage of Home battery, the customer may not be sensitive to
economic benefit, it is possible there is a variation in consideration of economic
benefits. Therefore, this was counted as a qualitative factor and covered in the
questionnaire.
5.6.2 Drive to environmental benefit
Solar PV and home battery contribute to achieve emission reduction goal. A study
(Dastrup et al., 2012) revealed that the price of house on which solar panels were
installed increased more than average when the neighbour is an environmentalist. So, it
can be assumed, this applies to the Home battery case as well, and that customer who
are more concerned with environmental benefit or who have environmentally aware
neighbours are more like to consider the home battery system’s benefits. Therefore, this
was counted as a qualitative factor and covered in the questionnaire which is found in
Appendix 1.
5.7 Market Size
5.7.1 Projected amount of PV instalment
Powerwall is basically complemented by solar PV. It is important aspect not to be
neglected that it can be used without solar panel. According to Tesla’s official
explanation of usage(Tesla, 2015b), Powerwall can store electricity directly from grid
when the rate is low, which will increase the value of the battery significantly. However,
whether storing electricity from grid can be beneficial is dependent on market policy and
supporting system infrastructure such as smart grid. So, in the mid-term period, it is
sensible to assume the target customers are likely to be users of solar PV.

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The size of solar PV is projected by IEA, and this can be used as a key variable
because the projection of IEA is one of most reliable projections, reflecting economic
factors such as solar PV hard and soft price and grid parity as well as non-economic
factors such as consistency of regulation and commitment to renewable energy
investment etc. In this regard, the IEA representative notes that ‘medium-term market
report does not forecast countries according to a linear or any sort of growth rate. In
order to understand forecast dynamics of a country, you will need to read about the
country in the book to understand drivers and challenges related to it where we look at
policy, demand growth, grid integration, financing and economic attractiveness to
forecast renewable capacity’ According to IEA the projection reflects factors such as
power demand growth, country solar PV capacity targets, grid integration constraints,
economic attractiveness (relative costs), policy incentives (economic support) and
project pipeline under construction. (IEA, 2014c; IEA interview)
5.7.2 Off-grid PV
One of unique merits of solar PV compared to other types of renewables is that it can
be utilized in off-grid. However, at this point it is not enough to act as a substitute to fulfil
the demands of the Diesel engine because of constraints of radiation resource.
However when there is a backup of electricity storage off-grid PV can be good
substitute of Diesel. And current diesel use customer can switch to solar PV with
storage. IEA estimated demand for solar PV can amount to 100GW mostly in mostly in
Africa and developing Asia. (IEA, 2011b, p25)
However the demand of off-grid PV is not considered in this study because of the size.
Even though the important role of electricity battery in off-grid PV the market size is
below 2GW, of which mostly can be utilized in the area where remote and need large
amount of transmission investment such as Africa and several regions of island is.
5.7.3 Income level
This factor can be taken into account on the basis of investigation of the solar PV
customer driver along with the product life cycle. As it is agreed, the income level is a
closely related factor of deploying the new, efficient and environmentally acclaimed

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product before the maturation stage. This study considered that this factor is already
reflected in the IEA’s projection so did not incorporate in the tabulation.

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6. Data analysis and finding
6.1 Data collection (1st
round : residential solar PV drivers)
This data analysis was carried to find out whether the first hypothesis was empirically
verified. To do this, two different data sets were collected, which included data related to
20 European countries in during the early stage before maturity of the solar panel
(2008) and during the maturity stage (2013) The details of the data and result are
appended in the Appendix 3.
 Data set 1 (2008) : 2008 PV capacity share(PV capacity /renewable capacity),
2008 Gross household saving rate, 2010 IRR (%)
 Data set 2 (2013) : 2013 PV capacity share (PV capacity /renewable capacity),
2012 Gross household saving rate, 2010 IRR (%)
6.1.1 Result of correlation analysis
The result of correlation analysis through SPSS showed there was a significant change
in correlation between variables, which verified the hypothesis that the category of solar
panel customer changes as the product life cycle proceeds.
As seen in the table below, in 2008 the correlation between Gross household saving
rate (the proxy of income level) and the share of solar panel has significant relationship,
which is 0.462. It also shows that correlation between IRR% (the proxy of economic
benefit) and the share of solar panel is not significant with a correlation of 0.211,
indicating a significance level of 0.372, which is far over the acceptable level of 0.05.
However, in 2013 the correlation registered a reversal. Correlation between economic
benefit and share of PV changed to a significant level rising to 0.691 with 0.001 level of
statistical significance, which is far over the acceptance level. The result of SPSS
correlation analysis is found in Appendix 4.
6.1.2 Findings
According to the correlation analysis above, the customer of solar panel in 2008 will
positively have a high income level and will be less likely to seek economic benefit

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maximization. On the contrary, the customer in 2013 is likely to seek higher economic
benefit. The price elasticity of the latter customer (in 2013) will be higher than that of the
former.
Also it in noticeable that there is low correlation between Energy produced yearly (Solar
radiation) and the PV share, which means also that the economic advantage is not a
strong driver because high solar radiation results in a higher performance rate, which
yields more electricity and raises IRR. This low correlation is found in the period of
2013. Therefore it is verified that in the earlier stage of solar panel product life cycle,
(PLC) customers belong to a high-income group, while in the mature stage customers
are more price-sensitive and belong to a lower-income group.
With this finding, it can be assumed that stationary Home battery is more likely to be
deployed by the customer who has a high level of income before the mature stage of
the PLC is reached and it can also be concluded that such customers might be less
price-sensitive.
6.2 ‘2nd
Round’ Data collection and analysis by country
Also IEA(2014c) evaluated the current and future forecasting to renewable energy
deployment in OECD and non-OECD countries. According to these studies each
economic variables was assessed and rated as following explanation. The result is
found in Appendix 5. as seen following Table.
6.2.1 Reserve margin and Grid integration by countries
The flexibility in grid integration of increasing renewable is invested by IEA(2011b) as
seen below Figure. And power system status of each countries will be following.

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Figure 14Renewable potential in various countries (IEA, 2011b, p53)
6.2.1.1 OECD America
The US : The reserve margin is moderate, but restriction to coal fired power plant affects
the effective margin thereby causing restriction (IEA, 2014c, p34). Coal plants account
for majority with 40% of total capacity. However, due to both Environmental Protection
Agency (EPA) emission regulations and weak demand growth for electricity, coal plants
have been switched to gas plants and also continued to retire, thereby reducing the
reserve margin and creating more opportunities for the use of renewables.
According to a National Renewable Energy Laboratory integration study on the US
Western Grid (WECC), which includes parts of Canada, the United States and Mexico,
35% of variable renewables can be integrated into the grid. However, some regional grids
partly, (for instance Texas) can suffer difficulty, but transmission investment has planned
and is under progress with the remaining challenge being co-ordination. (IEA, 2014c, p36-
38)
Canada : Within this context, the retirement of fossil-fuel plants is continuing. The reserve
margin is not much, but this is not an issue because fuel can be imported from the US.
Power generation is dominated by hydropower. (IEA, 2014c, p36) Within the grid, there

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are increased challenges for integrating renewable energy, thereby moderately
constraining the possibility of the latter (IEA, 2014c, p38)
Mexico : In Mexico, energy reform is under process. In 2014, the monopoly of the
vertically integrated state-owned utility ended, and the industry underwent new changes
such as establishing independent transmission operations and clean energy schemes
(IEA, 2014c,p36). The grid is weak, and there are limited interconnections and isolated
small grids, significantly constraining integration of renewables. (IEA, 2014c, p39)
Chile : Both insufficient generation and rapidly growing demand drive renewable
deployment (IEA, 2014c, p36). The connection of renewables has been an issue with
difficult certification requirements varying amongst different privately owned TSOs and
the persistence of congestion between two major transmissions. Within the grid, there is
a significant challenge (IEA, 2014c,p39) due to differently owned TSOs and transmission
congestion in the two major transmission areas (IEA, 2014c, p39)
6.2.1.2 OECD Asia Oceania
Japan : The reserve margin is moderate due to slow demand growth, but it is also
unstable due to uncertainty in the power mix, especially in nuclear plant operations. A
strong need for new generation capacity, the high cost of LNG generation drives, high
level of FIT level and the high level of retail prices motivate renewable expansion,
especially in solar PV (IEA, 2014c, p49)
Grids can integrate up to 30% renewable generation. However, fragmented structure and
weak interconnections make the chance of congestion higher, and plans have been made
to install large scale battery storage. When the expansion of renewables is considered,
grids seem to be constrained by a fragmented structure with weak interconnections
between utility supply areas and a transmission system occupying two separate
frequency areas (IEA, 2014c,p50).
Korea : The reserve margin is small due to dynamic demand growth, and it is unreliable
because of uncertainty in the nuclear plant operation, which accounts for around 30% of
total generation. This has resulted from insufficient generation investment with regulated
retail price (IEA, 2014c, p48)
Australia : The reserve margin is ample due to overcapacity and reduction of demand
with increasing load sharing via renewables. In a situation where coal generation
dominates energy generation, increasing renewable generation and slowing demand
have resulted in low utilisation of fossil fuel power plant. Within the grid, there is moderate
challenge to integrating renewables (IEA, 2014c, p47-50).

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6.2.1.3 OECD Europe
Some countries are dominated by fossil fuels; natural gas and coal account for 70% in
Turkey, 80% in Netherlands and gas is dominant (40%) in Italy, while nuclear energy
dominates 70% of generation in France. Also developed countries have been faced the
need for replacing and retiring old plants in countries such as France, Italy, Spain, UK
and Germany. Lastly, new generation needs are being created within growing economies
such as Turkey. (IEA, 2014c, p59-69) And high proportion of ageing transmission and
distribution lines need investment for increasing renewables as a whole(IEA, 2011a, p13)
Germany : Germany is characterised by slow growing demand, less overcapacity and
need for new generation. From 2015, nuclear power will be phased out, with gas being
switched to coal. New capacity will be reliant on renewables, which target meeting 35%
of the electricity demand in 2020. With respect to integration of renewables in the Grid
system, most regions have sufficient flexibility, serving as successful examples of this
trend, especially in the Northwest Europe and the Iberian region. However, Germany has
faced difficulties in connecting the North and South regions(IEA, 2011a), it has
experienced the need to replace old distribution networks, with solar PV growth raising
integration issues (IEA, 2014c, p65).
Italy and Spain : They have little concern over reserve margin due to overcapacity.
However, Italy has issues of policy uncertainties, which are evident in the details of post-
2015 auction system. Since 2013, there have been no new FITs for solar PV. In 2014,
Spain retroactively revised the incentive given to existing renewable generators,(IEA,
2014c,p68) which has created policy uncertainty.
France : France is experiencing increasing demand due to electrification of heat. Nuclear
generation is dominant, with over 70% of total generation in 2013 attributable to this
source of energy (IEA, 2014c, p 61). Half of the plants will reach 40-year lifetime limits
after 2020. In 2013, France has been criticized because of the prolonged permission
granting process, and the government has fixed the process (IEA, 2014c, p67) While most
generation in most countries is likely to expand slightly, that of Turkey and France is
forecasted to grow more due to over 4% GDP growth and increase in heating demand
respectively.
Turkey : Economic growth of 4% GDP growth drives increasing demand for energy, and
due to ample need for new power plants, it can be said the country has a slim reserve
margin. High wholesale price is a portion of the driver for new supply(IEA, 2014c, p62)

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UK : A small reserve margin is anticipated due to the imminent replacement of ageing
coal and environment concerns (IEA, 2014c, p61). As part of Electricity Market Reform
(EMR) in 2014, new capacity market will open for 2018 by auction.
6.2.1.4 Non-OECD
South Africa : In South Africa, coal power plants are dominant. With 48GW total capacity
and one quarter of its plants ageing, the reserve margin is extremely slim, and power cuts
are being experienced. In Africa only South Africa’s solar PV potential is over 2GW driven
by excellent resource and a new renewable national scheme titled the Renewable Energy
Independent Power Producer Procurement Programme(REIPPP). In South Africa,
economic attractiveness and excellent resource availability encourage the use of
increasing renewables such as solar and wind (IEA, 2014C, p87).
According to estimation by Eskom, a South African electricity public utility, the grid is
expected to have difficulty in integrating renewables after 2016 ( IEA, 2014C, p84) As a
result, distributed generation has been developed as a countermeasure, which can
motivate solar PV. However, this is impeded by a lack of supporting legislation such as
net metering (IEA, 2014C, p84).
Saudi Arabia : Amongst Middle East countries, Saudi Arabia plans to install over 2GW
solar PV by 2020. Saudi Arabia’s Power system consists mainly of oil and gas fired
generation. With the initiative by the government to reform the power market, fast growing
demand, excellent renewable resources and diversification needs, there is a drive to
develop 54GW renewables by 2032. However uncertainty over implementation remains
(IEA, 2014C, p121-125), and the grid faces moderate challenge in integrating renewables
in the medium term. The Gulf Cooperation Council (GCC) has plans to interconnect seven
gulf countries ( IEA, 2014C, p122).
Among non-OECD Americas, Brazil is the one, which is projected to install over 2GW
solar PV by 2020. With high proportion of hydropower, renewable sources make up over
70% of total power generation. Due to lack of water resources, gas plant has replaced
supply. The power demand is expected to grow over 3% annually, which will be served
by mostly renewable development including hydropower through the government’s
auction scheme. The government regulates the retail price to avoid high peak prices due
to lack of hydro resources. The grid will face few issues in integration of the renewables
due to high share of hydro power and extensive transmission system (IEA, 2014C, p127-
129).
Exceptions exist in countries where the electricity from the grid is significantly subsidised,
such as Egypt, Iran, various MENA countries, South Africa, Russia and Venezuela, and,
to a lesser extent, China and India (IEA, 2011b, p62).

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6.2.2 Demand Profile
The value of electricity storage with solar PV is greater if the peak load demand occurs
when the solar radiation is not strong because solar PV generation during day time makes
low load lower, which broadens the gap the peak and low as the picture of California’s
Duck profile has shown earlier.
According to IEA(2011b, p63) there are difference in daily electricity demand profile as
seen below Firgue.
Figure 15Daily Demand Curve in 6 regeions (IEA, 2011b, p63)
Developing countries, such as India, mostly show evening peaks. This is because of
lighting demand. Even in industrial regions such as California, the thermal inertia of
buildings drives the demand for air-conditioning several hours after sunset, while demand
for light adds to the peak, or at least mid-peak conditions (IEA, 2011b, p63-64)
However, California is quite a special case. Most hot and humid countries such as
Western Europe and Japan have peak demand around noon as shown below. The
demand curve of other countries is assumed with a consideration of the location and
income level.

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Also, Demand profile in four typical regions can be simplified depending on when the
peak demand occur as seen below Figure.
The U.S. Western Europe China Japan
Figure 16Figure 16two types of daily demand profile in four
typical regions. (Inage, S., 2010)
6.2.3 The value of Energy storage
Inage, S. (2010) simulated the measurement and comparison of the energy storage value
of electric vehicle (EV) and concluded that ‘using EVs to shift load would produce good
results in Western Europe and Japan by 2050. In contrast, V2G load shifting [was
expected to] provide limited benefits in the United States and China.’ This was attributable
to the share of middle load power plant. In Western Europe and Japan, the middle load
is low. As a result, the EVs, as a storage device, play an important role, which gives more
value to the grid and whole power system.
Figure 17Influence of PV penetration on demand-supplybalance (Inage, S., 2010)

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Therefore the effect of electricity battery for load shifting depends on the generation mix
in each country. In view of this, within this study, a higher score is given to countries,
which have fewer gas-fired plant share than Japan and Europe.
6.2.4 non-economic parameter
OECD America : In the US and Canada, institutional support seems to be good. However,
there are no national level targets and control. In the US, the soft cost makes solar PV
over 30% more expensive than the projected cost in Germany or in Italy, which is primarily
due to high cost of capital (Ardani et al., 2013).
Most countries provided advanced incentives such as net metering. However, the US and
Canada have more diverse incentive schemes, which offset their drawbacks. The US and
Canada have low whole sale price. On the contrary, Chile and Mexico do not have
financial incentive, but their power prices are high enough to motivate renewables, while
they have national level renewable targets. However, uncertainty in implementation
remains (IEA, 2014C, p41).
Japan : In Japan, the policy commitment is strong with the onset of the electricity market
reform scheme and 4th Strategic Energy Plan, which include profound changes in the
electricity system. These include ending the structure of regional monopoly of vertically
integrated utilities, introducing full retail competition, unbundling the transmission and
distribution sectors and increasing flexibility measures such as smart meters, storage and
EVs (IEA, 2014C, p49)
Korea : Since 2013, Korea has, under the renewable portfolio system(RPS) set the
renewable target of 10% of power generation by 2022. However, the policy commitment
is weak in that there is yet no law of enforcement as of 2014.
Australia : Excellent resources and falling cost of renewable technology have advantaged
solar generation as compared to fossil-fuel generation. For example, solar PV has
reached grid parity with an instalment price of around 60USD/MWh and rising retail price
(IEA, 2014C, p49). However, policy uncertainty remains in that, Australia repealed the
carbon pricing scheme and agency in charge in 2013.
6.3 Result of survey