Port Augusta Solar Thermal
Generation Feasibility Study
Milestone 4 Report
Final Balance of Study
July 2015
A project jointly funded by:
-
Alinta Energy
-
Australian Renewable Energy Agency, Emerging Renewables Program
-
Government of South Australia, Enterprise Zone Fund
For more information:
www.alintaenergy.com.au/Port-Augusta-Solar-Thermal-Generation-Feasibility-Study
Table of Contents
1
2
Executive Summary ....................................................................................... 5
Introduction .................................................................................................... 6
2.1
3
4
Review of Assumptions ............................................................................................ 7
Analysis of Measure Progress ...................................................................... 9
3.1
Data Collection ......................................................................................................... 9
3.2
Balance of Study....................................................................................................... 9
3.2.1
Scope of Works ................................................................................................................ 9
3.2.2
Methodology ................................................................................................................... 10
3.2.3
Uncertainties discovered ................................................................................................ 13
Financial Modelling and Assessment ......................................................... 15
4.1
Overview of financial modelling .............................................................................. 15
4.2
Methodology ........................................................................................................... 15
4.3
Input Data ............................................................................................................... 15
4.3.1
Capital Costs .................................................................................................................. 16
4.3.2
Operational Costs........................................................................................................... 16
4.3.3
Electricity Generation ..................................................................................................... 16
4.3.4
Pricing ............................................................................................................................ 17
4.3.5
Other Assumptions ......................................................................................................... 19
4.4
Financial Modelling Outputs ................................................................................... 19
4.5
Cost Uncertainty Analysis ....................................................................................... 21
4.6
Parameter Sensitivity Analysis ............................................................................... 21
4.6.1
LCOE vs. Simple Payback Time .................................................................................... 21
4.6.2
Plant Configuration ......................................................................................................... 21
4.6.3
Market Forecast ............................................................................................................. 23
4.6.4
Time of Day Pricing vs DNI datasets .............................................................................. 24
4.6.5
Dispatch Methodology .................................................................................................... 25
4.7
Project Financial Viability ........................................................................................ 25
4.7.1
Financial parameter benchmarks required for project viability........................................ 26
4.7.2
LCOE Assessment ......................................................................................................... 30
4.8
Unexplored Concepts ............................................................................................. 31
4.8.1
Storage from grid power ................................................................................................. 31
4.8.2
Use of waste heat........................................................................................................... 31
4.8.3
Hybridised solar.............................................................................................................. 31
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4.8.4
5
6
7
Alternative location ......................................................................................................... 32
Near Commercial Technologies .................................................................. 32
5.1
Technical Maturity................................................................................................... 32
5.2
Financial Potential .................................................................................................. 32
Further Information ...................................................................................... 33
Conclusion ................................................................................................... 33
Table of Figures
Figure 1: AUD:USD exchange rates July 2014 – May 2015 ...................................................................... 11
Figure 2: Financial modelling methodology ................................................................................................ 15
Figure 3: Construction cost curve assumption ........................................................................................... 16
Figure 4: Forecast lifetime electricity production by quarter ....................................................................... 17
Figure 5: Forecast peak and off-peak electricity prices .............................................................................. 18
Figure 6: Forecast LGC price path ............................................................................................................. 18
Figure 7: Project lifetime cashflows ............................................................................................................ 20
Figure 8: LCOE as a function of IRR and CAPEX – Base Case/Reference Curve ................................... 27
Figure 9: LCOE as a function of IRR and CAPEX – Variation 2 ................................................................ 28
Table of Tables
Table 4: Cost localisation factors ................................................................................................................ 10
Table 5: CAPEX cost estimate comparison: Options Study vs Balance of Study ...................................... 11
Table 6: Results of further industry consultation ........................................................................................ 12
Table 7: Solar resource data inputs for generation modelling .................................................................... 13
Table 8: Base case financial modelling key outputs ................................................................................... 20
Table 9: +/-30% financial modelling key outputs ........................................................................................ 21
Table 10: Alternate system configurations ................................................................................................. 22
Table 11: Alternate Systems – modelling outputs ...................................................................................... 22
Table 12: Base case vs. forward price curves ............................................................................................ 24
Table 13: IRR as a function of system design & forward price curve ......................................................... 24
Table 14: NPV @ 12% as a function of system design & forward price curve........................................... 24
Table 15: Minimum financial benchmarks for CSP investment at Port Augusta ........................................ 26
Table 16: Sensitivity of IRR & NPV to multiple variables ........................................................................... 29
Table 17: Contributions to LCOE by category and CAPEX vs OPEX ........................................................ 30
Table 18: LCOE contributions by category compared to SunShot targets ................................................. 30
Table 19: VAST Solar scaled base case vs. forward price curves ............................................................. 33
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Acronyms
Alinta
Alinta Energy group of companies
ARENA
Australian Renewable Energy Agency
CAPEX
Capital Expenditure
CPI
Consumer Price Index
CSP
Concentrating Solar Power
DNI
Direct Normal Insolation
GHI
Global Horizontal Insolation
IRR
Internal Rate of Return
LCOE
Levelised Cost of Energy
LRET
Large scale Renewable Energy Target
LGC
Large scale Generation Certificates
MW
Megawatt
MWe
Megawatt electric
NEM
National Electricity Market
NPS
Northern Power Station
NPV
Net Present Value
OPEX
Operational expenditure
PPA
Power Purchase Agreement
SAM
System Advisor Model
TMY
Typical Mean Year
WEM
Western Electricity Market
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1
Executive Summary
Alinta has completed the pre-feasibility investigations detailed in the Port Augusta Solar Thermal
Generation Feasibility Study. This is the fourth and final milestone report contributing to Stage One of the
study. This Milestone Four Report (Final Balance of Study Report) presents the findings of Alinta’s
extensive financial modelling and scenario analysis of the potential for a Concentrating Solar Thermal
plant in Port Augusta, South Australia. It builds upon the Draft Balance of Study Report previously
released.
Over the last several months Alinta has given further consideration to a range of additional possibilities
including five alternative CSP plant configurations, three additional forward price curves and adjustments
to capital cost, operating cost, revenue stream and capital grant funding. The most significant finding
presented in this report is that across the range of sensitivities, system types and forward curve
assumptions considered, there is no combination which returns a positive Net Present Value in the
financial model.
Further industry consultation has confirmed the suitability of the cost estimate assumptions made in the
Balance of Study Report.
Alinta’s internal analysis suggests that in order for a project of this type to attract private sector
investment at this time, the costs would need to be reduced by approximately 60%. If CAPEX and OPEX
were reduced by 60%, then the LCOE of this type of plant would drop from $201/MWh to $80/MWh. This
would be in line with the 2020 target for a drop in the cost of solar thermal technology that is being
pursued by the SunShot Initiative funded by the US Department of Energy.
While the investigations and options reviewed as part of this study have been robust, thorough and
conclusive, there are several unexplored concepts which may have the potential to either reduce costs or
increase revenue. None of the concepts identified would have an impact large enough to be material to
the viability a CSP plant in Port Augusta at this time, however as the landscape of the electricity industry
changes over the next several years, these concepts may begin to play a role in project viability. There is
at least one local technology manufacturer which could be offering commercially competitive prices for
solar thermal generation in the near to medium term and there may be other investors better positioned in
a range of ways to further explore these possibilities.
At this time Alinta can definitively conclude that the construction of a 50 MW, molten salt power-tower
located in the town of Port Augusta is not an economically feasible option for Alinta.
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2
Introduction
This report represents the fourth of six milestones which comprise the Port Augusta Solar Thermal
Generation Feasibility Study. Milestone One, Project Definition Report, was submitted to ARENA in
January 2014 and Milestone Two, Options Study and Siting Study, was submitted to ARENA in May
2014. Milestone Three, Draft Balance of Study, was submitted to ARENA in January 2015. A public
version of all of these Milestone Reports has been posted on the Alinta Energy website:
www.alintaenergy.com.au/Port-Augusta-Solar-Thermal-Generation-Feasibility-Study
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2.1 Review of Assumptions
There were several high level assumptions made by Alinta which were inputs into the early stages of the Port Augusta Solar Thermal Feasibility Study.
The assumptions first presented in Milestone 1 (Project Definition Report) are shown in Table 1 below along with a current assessment of these
assumptions.
Table 1: Changes to Assumptions from Milestone 1 Report
Initial Assumption
The location of the Augusta Power Station, and in the
vicinity of the facility, is suitable for the siting and
development of a solar thermal facility.
Previous changes
The site identified as optimal in the Siting
Study is now known to be the subject of a
Development Application by a third party.
The proximity of the CSP plant to the
Spencer Gulf raises potential corrosion
issues due to salt water spray/deposition.
Alinta Energy understands the current arrangements
for land tenure permit the siting and development of a
potential solar thermal facility on land within the control
of Alinta Energy or adjacent to subject to the Sale /
Lease arrangements between Flinders Power
Partnership and the Government of South Australia.
No change
The life of the Leigh Creek Mine, which supplies coal to
the Augusta Power Stations, would be extended
through further investment by Alinta Energy.
No change
The Augusta Power Stations would remain in
operation, in their current form supplied by the Leigh
Creek Coal Mine, until at least 2028 to 2032.
No change
The useable life of the Augusta Power Stations,
including re-use of facility components, extends
beyond the current expected life of the Leigh Creek
Mine.
There are significant technical challenges
to running NPS on only solar once the
coal resource has been exhausted which
would require extensive re-engineering of
large parts of the plant.
Milestone 4
No change
No change
In June 2015 Alinta Energy
announced an intention to cease
operating the Northern and
Playford power stations and the
Leigh Creek Coal Mine by March
2018.
No change
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Initial Assumption
Previous changes
The pre-measure activities and studies relied upon in
the development of this study which detail the potential
value and strength of the solar resource, the potential
for hybrid solutions, and the potential utilisation of
components from the Playford B Power Station is the
best estimate and advice of the respective experts.
Use of components from Playford B was
determined to be infeasible. Procurement
of spares and replacement parts is
extremely difficult. The entire facility
would require upgrading in order to
support the use of usable components.
The range of project benefits, fuel diversity
opportunities for South Australia, dispatchable energy
potential, compatibility with South Australian energy
system, network connection options, technology costs
and acceptable technology types do not materially
deviate from those understood at the commencement
of this study.
Analysis by the Australian Energy Market
Operator suggests that the grid in South
Australia is oversupplied which leads to a
disincentive for adding generation
capacity of any kind.
Progress beyond the study will depend on a number of
factors outside the scope of this piece of work which
have not been estimated or modelled at this point in
time.
No change
Milestone 4
No change
The reduction in generating
capacity due to the future closure
of Northern and Playford is not
large enough to negate the
oversupply of capacity in the South
Australian electricity market.
No change
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3
Analysis of Measure Progress
3.1 Data Collection
On 5 July 2014 Measurement Engineering Australia (MEA) sent two representatives to the Northern
Power Station in Port Augusta to install a solar tracker, weather station and data collection equipment.
The equipment has since been recording the following variables at one minute intervals:
Weather Station

Global solar radiation

Air temperature

Humidity

Wind speed (min, max, ave)

Wind direction

Barometric pressure
Solar Data Station

Global solar radiation (min, max, ave)

Global diffuse radiation (min, max, ave)

Direct normal irradiance (DNI) (min, max, ave)

Temperature of shaded pyranometer

Temperature of un-shaded pyranometer

Temperature of pyrheliometer
Alinta has made a provision for validation of a full 12 month dataset which will allow for correlation
between satellite data and ground station records.
3.2 Balance of Study
3.2.1 Scope of Works
The scope of works for the Balance of Study is identified in the Agreement and is summarised below:

Details of the plant and its operation;

Capital and operating and maintenance costing at +/-30%;

Energy yield and generation profile;

Infrastructure requirements;

Environmental studies including land use, profile and identification of environmental issues;

Planning and development requirements for a Development Approval;

Network connection;
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
*Stakeholder consultation plan; and

*Preliminary financial evaluation.

*Sensitivity analysis on the effect on financial viability of a range of parameters
The items marked with “*” were determined to be within the core capability and expertise of Alinta
personnel and were completed internally. The remaining scope was completed by Parsons Brinkerhoff
(PB).
3.2.2 Methodology
The majority of the high level plant design was completed and reported in the Options Study Report
which comprised one of the deliverables for Milestone 2. Therefore only those aspects that have been
further refined or have changed or new challenges which have arisen will be discussed here.
Capital Cost
Project capital costs were estimated by a combination of scaling the detailed reference plant cost
estimate and generating estimates using commercial software and the internal estimating experience of
PB personnel. Alinta and PB discussed at length the value of the labour cost multiplier in the context of
the Port Augusta economy and local labour-force skills. Variation in this parameter could have a material
impact on both the capital and operations cost estimates. While there is a real potential for the labour
cost multiplier to be less than that used in the study, it would be well within the +/- 30% accuracy which
characterises the pre-feasibility stage.
Capital cost multipliers used in this report are show in Table 2 below.
Table 2: Cost localisation factors
Factor
Value
Labour cost multiplier
1.14
Material cost multiplier
1.34
Currency exchange rate
1.1
Comments
Ratio of Australian union labour rates to Californian
union labour rated (from Thermoflow PEACE)
further localised to Port Augusta
Ratio of Australian to Californian material cost
multiplier (from Thermoflow PEACE) further
localised to Port Augusta
AUD to USD
There is a significant reduction in estimated capital cost presented in the Balance of Study Report
compared to the cost estimate provided in the Options Study Report. Cost estimates in the Options
Study were based entirely on a literature review and desktop investigation. Alinta requested PB to
conduct a cost tightening exercise which would draw on direct industry current experience and
knowledge as well as consider the relative maturity of the solar thermal industry against well understood
technology price curves. The cost estimates provided in the Balance of Study report are informed by
conversations with leading industry players and consider more heavily the public knowledge around real
costs incurred by reference plants.
The overall capital cost estimate dropped approximately $200M following this exercise. The most
significant reduction came from the heliostat field. Early estimates using the labour, exchange and
2
material cost multipliers referenced above resulted in an estimated cost of $262/m for the heliostat field.
2
Following discussions with manufactures and installers of heliostats, a revised estimate of $150/m was
determined to be realistic.
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Another significant reduction in the CAPEX cost estimate was realised by taking a weighted average of
contingency values applied to individual components rather than applying the same % contingency to the
final project cost. Table 3 below summarises the difference in CAPEX cost estimates by major
component.
Table 3: CAPEX cost estimate comparison: Options Study vs Balance of Study
Component
Site Improvements
Heliostat Field
Tower
Receiver
Thermal Energy Storage
Balance of Plant
Contingency
EPC & Owner Costs
TOTAL
Options Study
CAPEX
$M
Balance of
Study CAPEX
$M
32.3
230.4
26.0
8.2
138.2
21.5
90.4
79.3
129.5
117.6
81.8
787.2
86.0
83.4
118.1
67.9
53.4
577.0
Difference
$M
-24.1
-92.1
-4.5
-4.4
4.1
-11.1
-49.7
-28.4
-210.2
Clearly the assumptions about foreign exchange rates and labour rates could have a material impact on
the CAPEX cost estimate. Preliminary analysis indicates that the CAPEX estimate has an exposure of
approximately 30-35% to the labour rate and an exposure in the vicinity of 50% to foreign exchange
rates. The current exchange rate is closer to 1.3 rather than 1.1 AUD:USD. This would have an effect of
adding ~10% or ~$60M on the CAPEX cost estimate.
Figure 1 below shows the movement of the Australian Dollar vs. the US Dollar over the previous 12
months.
Figure 1: AUD:USD exchange rates July 2014 – May 2015
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Additional Industry Consultation
Alinta Energy contacted numerous industry participants in an effort to confirm the cost estimate
assumptions used by PB in the Balance of Study report. After this consultation Alinta has concluded that,
while there is still a moderate amount of variation in the values used by various suppliers, the values
used in the Balance of Study assessment conducted by PB are accurate within the scope of the Study.
The exception is the Power Block which appears to have been too conservatively estimated. Table 4
below summarises the information gathered through additional industry consultation and the percent
difference between the Balance of Study cost estimate and the recent response from industry.
Table 4: Results of further industry consultation
Cost Item
Full Project
Heliostats
Salt supply &
melting
Power Block
Industry Response
One organization that has previously constructed
similar infrastructure undertook a high level review
of a cost estimate for a CSP plant as specified in
the Alinta study.
Another company experienced in construction and
operation of solar thermal infrastructure replied to
Alinta’s request with a statement that within the
context of their experience and the recent study into
the feasibility of CSP in Western Australia, the cost
estimates in the Draft Balance of Study are of the
right order of magnitude and therefore judged to be
appropriate at this level of the study.
2
The BoS estimate was $150/m of aperture area. A
local South Australian manufacturer of heliostats
has separately provided an indicative cost estimate
for manufacture, supply and installation of heliostats
2
at a rate of $155/m .
Parsons Brinkerhoff inquired to 2 European
companies for the supply and melting of 20,000
cubic meters of thermal salts for a CSP plant in Port
Augusta. The combined cost estimate came to
~$40M.
A high quality engine manufacturer provided an
indicative price for a 50MW steam turbine package
of approximately $18M. The cost estimate used in
the Balance of Study is ~$29M.
BoS est.
($M)
Industry
Response
Difference
$577
~$500
-13%
~
~
$138
~$143
3%
$48
~$40
-17%
$29
~$18
-38%
~
Six other companies did not respond in writing to Alinta’s request to provide comment on the cost
estimates contained in PB’s Balance of Study report.
Operational Cost
Operating and maintenance costs were also scaled from the reference plant in a manner similar to the
capital cost estimate. A burdened labour rate of 30% was assumed. Where there is a support function
that could be considered a corporate service, no labour cost was included. These roles, such as IT,
finance and human resources are assumed to be provided by existing Alinta Energy personnel.
With the decision to close Northern Power Station there will be an increase in annual estimated labour
cost as many of the resources that were assumed to be shared with existing operations would no longer
be shared. While this would be a material difference in cost it is not expected to be significant and would
certainly not stray from the +/- 30% accuracy band.
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As with CAPEX, the OPEX cost estimate is also sensitive to labour rates, however less so to foreign
exchange rates. The ~$8M annual operational costs has an exposure of approximately 60% to the
labour rate.
Solar Resource Data
For a more accurate assessment of solar resource and generation profile of the plant, Alinta purchased a
typical mean year (TMY) data set synthesised from a 15 year record between 1999-2013. The report
provides a retrospective analysis of the past 15 years of solar irradiance, wind and temperature data.
The data used is comprised of hourly values, however the long-term average values are only calculated
using complete calendar years.
The difference between the dataset used during modelling for the Options Study and this purchased
dataset is shown in Table 5 below. The differences in these datasets does not make a material
difference on the selection of the plant configuration made during the Options Study. The overall
increase in solar resource expressed in the dataset purchased by Alinta for the Balance of Study
increases the modelled annual generation by the plant and therefore a nominal increase in modelled
revenue.
Table 5: Solar resource data inputs for generation modelling
Parameter
Units
Data for Options
Study
Data for Balance of
Study
Difference
Standard Error
%
16%
<9%
-7%
Annual average DNI
W/m
2
235.5
279.2
+19%
Peak DNI
W/m
2
886
981
+11%
Summer average DNI
MJ/day
24.7
28.5
+15%
Winter average DNI
MJ/day
15.9
19.7
+24%
Annual average GHI
W/m
215
222.1
+3%
2
Network Connection
The obvious location to connect into the network is at the Davenport Substation just to the East of
Northern Power Station. There is currently a spare bay inside the substation that could potentially accept
the assets that would be required to connect the Augusta Solar Thermal plant. There are various options
in the definition of asset ownership and boundaries with ElectraNet, which owns and operates the
Davenport substation. The decision on what type of arrangement would suit best would be determined
by a commercial and contractual discussion that is detail beyond the scope of this report. The connection
of 50 MW of solar thermal power at Davenport substation would also not have a material impact on the
Marginal Loss Factor (MLF) of the network.
3.2.3 Uncertainties discovered
Plant Siting
Since the Siting Study was completed there has been a material change to the availability of land near
Northern Power Station. The land parcel identified as Option 1 has since been the subject of a
Development Application for a nearby operation and would no longer be available as a location for the
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solar thermal plant. The next best location that was part of the siting study is approximately four
kilometres further south in the same direction from Northern Power station.
This increases the cost of constructing a transmission line to the switchyard and increases the cost and
complexity of sharing any infrastructure or services between the solar thermal plant and the existing
activities at Northern Power station.
Another concern that has arisen is the potential for salt corrosion on the plant components. This is a
particular concern for the heliostats, however is relevant to all equipment and materials that would be
exposed to salt spray and deposition.
Cooling System
The proximity to the Spencer Gulf and the existing cooling water loops used for Northern Power Station
make a wet cooled condenser an obvious first option. However the expense of constructing adequate
pipework is prohibitive and therefore a cooling tower is proposed. The use of salt water in a cooling
tower introduces additional complications and has the potential to increase fouling and corrosion on
nearby infrastructure.
The logical conclusion is to move to an air cooled condenser which is also at additional cost.
These issues that have arisen with the plant siting have almost entirely removed the potential benefit that
was once thought to exist by co-locating the plant with Northern Power Station. It is Alinta’s opinion,
therefore, that the initial constraint of choosing a location in proximity to Northern is now not relevant. For
the purposes of the Study Alinta has continued to contemplate the location identified by PB in the Siting
Study.
Should a full feasibility study of a CSP plant in the vicinity of Port Augusta be undertaken by Alinta or
another party in the future, a new location in the region would likely be sought.
Time of Day Pricing
As part of the preliminary analysis undertaken for the Draft Balance of Study Report, Alinta investigated
the relationship between LCOE and simple payback time in the context of different CSP plant
configurations. This analysis led to the conclusion that there was the potential for systems with less
thermal storage, smaller heliostat field and therefore lower capital cost to have similar payback times to
the Base Case. When considering external investment and/or capital grant funding, a reduced CAPEX
would mean the same quantum of investment and/or grant would have a proportionally greater effect on
the viability of a project.
The value of Time of Day pricing becomes more significant as the storage capacity of the plant is
reduced, therefore it is important to understand the impact that ToD pricing has on the financial viability of
systems with less storage.
In the financial model, market prices are represented by peak and off-peak time-weighted average rates.
In order to determine the effect of hourly price granularity, an analysis was done comparing the revenue
generated by a system with the dispatch optimised to the time weighted average prices versus dispatch
optimised to an hourly price profile. The difference in recorded revenue between the two price curves
was less than 5%. While this is a material difference, it is not significant and is comfortably covered by
the hypothetical scenarios assessed by Alinta. The accuracy benefit gained by this level of modelling
does not justify the significant additional effort required. Alinta determined that the use of peak and offpeak time-weighted average price signals is appropriate for this study.
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Section 4.6 contains detailed results of further parameter sensitivity analysis and the impact on the
financial position of a CSP plant in Port Augusta.
4
Financial Modelling and Assessment
4.1 Overview of financial modelling
The financial viability of the proposed 50 MW Solar Thermal Power Station in Port Augusta is a key factor
in assessing whether to continue to develop the project business case. Alinta has developed a financial
model to analyse the overall financial viability of the project. The evidence from the financial analysis is
that commercially the project is unviable. Even selecting for all of the most favourable and optimistic
assumptions, the modelled CSP plant does not achieve a 12% IRR.
The remainder of this section sets out the financial modelling undertaken and presents the detailed
outputs from the financial viability assessment.
4.2 Methodology
The financial modelling draws upon a number of information sources in order to calculate the ungeared
post tax nominal cash flows associated with the project. The financial modelling is undertaken on a
quarterly basis. The modelling methodology is set out in Figure 2:
Figure 2: Financial modelling methodology
4.3 Input Data
Input data is sourced from independent third party reports wherever possible. A number of the third party
reports have been specifically commissioned as part of the Port Augusta Solar Thermal Feasibility Study,
whilst others are commissioned by Alinta for use across within its broader business activities and have
been leveraged for use in this Study. In some instances, Alinta has made assumptions, drawing upon its
internal expertise where required.
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4.3.1 Capital Costs
The $577M capital cost of the project used in the financial modelling is based upon the Balance of Study
Report prepared by PB. Alinta has supplemented the total capital cost estimate prepared by PB with a
construction cost curve, to forecast the potential actual expenditure over an assumed 2 year build period.
It is assumed, that construction starts on 1 January 2017. The resulting quarterly construction
expenditure curve is shown in Figure 3.
Figure 3: Construction cost curve assumption
4.3.2 Operational Costs
The $7.89M of annual operating costs in the financial modelling are based upon the Balance of Study
Report prepared by PB. Alinta has supplemented the estimated annual operating costs with the
assumption that the operating costs will escalate each July by CPI, and will be incurred equally across
the year.
4.3.3 Electricity Generation
The PB Balance of Study Report estimates the energy production capability of the project over its
expected life. Importantly, the financial model converts the information in the PB report into peak (7:00 to
22:00 workdays) and off-peak for each calendar quarter. Specifically, the model calculates:

Average proportion of peak and off-peak energy production for each month (based upon average
daily production profiles in each month )

Average proportion of peak and off-peak energy production for each quarter (based upon total
monthly production profiles )

Energy production during peak and off-peak times for each quarter for each forecast year. This
utilises the forecast total annual production for each year of operation from the report (which
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takes into account degradation) and applies the average quarterly peak and off-peak proportions
(calculated in 2) above)
The total forecast peak and off-peak production by quarter is shown in Figure 4 below.
Figure 4: Forecast lifetime electricity production by quarter
4.3.4 Pricing
South Australian pool prices are based upon the forecasts contained in Acil Allen Consulting’s Australian
Energy Market, Analysis of the National Electricity Market (NEM), Western Electricity Market (WEM) and
Large scale Renewable Energy Target (LRET) report. The time weighted nominal quarterly forecast peak
and off-peak prices to Dec 2030 have been utilised. The price path is then interpolated between 2030
and 2035, and also 2035 to 2040. Beyond 2040, it is assumed that prices remain flat.
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Figure 5: Forecast peak and off-peak electricity prices
Forecast large scale generating unit certificate (LGC) prices are also sourced from Acil Allen Consulting’s
Australian Energy Market, Analysis of the NEM, WEM and LRET report. Acil Allen’s reference case is
adopted for the base financial viability assessment. LGC prices are only forecast to 2030, when the
LRET scheme is currently scheduled to end. The forecast price path is shown in Figure 6 below and was
generated on the basis of the original RET target of 41,000 GWh. The outcome of the recent RET
Review was not known in time to be incorporated into this analysis. The expected effect would be a
small, downward pressure on LGCs.
Figure 6: Forecast LGC price path
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4.3.5 Other Assumptions
A number of generic assumptions have been adopted in the financial modelling:

Tax assumptions:
o
To calculate the post-tax cashflows of the project, we have adopted the current company
tax rate of 30%
o
Tax depreciation is based upon the diminishing value methodology, with a 200%
multiplier and an assumed asset useful life of 25 years from construction completion

A number of costs and prices are assumed to escalate by CPI. Within the model it is assumed
that CPI increases by 2.5% per annum, with adjustments occurring on 1 July in each of the
forecast years.

The Acil Allen reference curve assumes the current policy that there is no price on carbon.
4.4 Financial Modelling Outputs
During an internal audit of the financial model, Alinta discovered that nominal values had been used for
forecast revenue instead of real values. This had the effect of applying CPI twice to the forecast revenue
and thereby over-estimating the revenue that would be generated during the lifetime of the modelled
plant. The updated results of the model are presented below.
The forecast annual cashflows of the project are shown in the chart below. Figure 7 shows that once the
facility is operational, it would be profitable. However, based upon the metrics presented in Table 6
below, the level of expected future profitability does not justify the large capital investment required to
build the facility.
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Figure 7: Project lifetime cashflows
Table 6: Base case financial modelling key outputs
Value
Metric
Net Present Value
-$359.8M
Internal Rate of Return
Levelised Cost of
1
Energy
Realised revenue
1%
$201/MWh
2
$96/MWh
Comments
Based upon a target post tax cashflow discount
rate of 12% (ungeared).
Represents the size of the shortfall of the project
from being commercially viable.
Indicates that the project does not generate a
return on the capital invested in the project, as it
does not meet a hurdle rate of 12%.
Represents the revenue that would be required per
MWh for the project to achieve the required return
metrics.
Represents the revenue that is forecast to be
realised per MWh produced.
1
Levelised Cost of Energy is calculated as [NPV of Capital Costs and Operating Costs (excluding any tax payments)] divided by the
[NPV of Demand escalated CPI]
2
Realised Revenue is calculated as [NPV of Total Revenue] divided by the [NPV of Demand escalated CPI]
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4.5 Cost Uncertainty Analysis
The scope of this (Milestone 4 report) is to identify the cost of the project to within a tolerance of +/- 30%.
The financial evaluation has been based upon the expected costs estimated by PB to within this level of
accuracy. Given the level of accuracy with in the costs, it is prudent to undertake a sensitivity analysis to
confirm whether, across the plausible range of cost estimates (i.e. +/- 30%), the project could be
considered to be commercially viable. As the metrics in the table below indicate, even if the capital costs
have been over-estimated by 30%, the project would still be unviable, with a Net Present Value (NPV) of
-$180M, and an Internal Rate of Return (IRR) of 3.4%. It is on this basis that it is considered that the
project is unlikely to be commercial under any plausible cost estimate.
Table 7: +/-30% financial modelling key outputs
Metric
Capital costs
Net Present Value (@ 12% IRR)
Internal Rate of Return
Levelised Cost of Energy
Realised revenue
-30%
+30%
$403.9
$750.1M
-$182.3M
-$515.6
3.4%
-0.4%
$149/MWh
$253/MWh
$96/MWh
$96/MWh
4.6 Parameter Sensitivity Analysis
4.6.1 LCOE vs. Simple Payback Time
During the early phases of the Study, Alinta and Parsons Brinkerhoff selected LCOE as the defining
metric for use in optimising storage hours and solar multiple of each system under consideration. Use of
this metric is ubiquitous and fundamental to all investment decisions in generation infrastructure. Alinta
uses LCOE to rank the internal portfolio of potential projects in order of investment priority. Some
analysis undertaken for Milestone 3 suggested that LCOE may not be the most accurate metric for
evaluating a CSP plant against competing technology options.
The lowest LCOE system with 15 hours of storage effectively performs as a baseload plant. This leads to
electricity generation at times of lowest prices as well as highest prices. Systems with between 1-7 hours
of storage offer a small but material improvement in simple payback time. This is due to the ability of
these systems to regularly generate during the higher priced, late-afternoon/early-evening peak periods
while avoiding generation during the late-night/early-morning trough.
Reduction in hours of storage and a proportional amount of heliostats translates to a significant reduction
in CAPEX. A plant with 4 hours storage reduces CAPEX to ~65% of the cost of the reference plant with
15 hours storage.
4.6.2 Plant Configuration
In order to explore more fully the potential impact of plant configuration on financial viability, five
additional plant configurations were interrogated. The selection of storage hours and solar multiple was
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recommended by IT Power to cover the entire range of systems that were thought to have the potential
for better economic performance than the Base Case.
In order to align with the boundary condition set by Alinta at the outset of this study, the size of the power
block was held at 50MW. The hours of thermal storage and the size of the heliostat field were varied as
presented in Table 8 below.
Table 8: Alternate system configurations
Alternate
System
Power
Block
Storage
hours
Solar
Multiple
Base case
50 MW
15
3.5
AS 1
50 MW
4
1.8
AS 2
50 MW
6
1.7
AS 3
50 MW
6
2.2
AS 4
50 MW
6
2.5
AS 5
50 MW
8
2.4
Each of these systems was created in SAM and the output simulated against the same TMY file that was
used when modelling the base case. Hourly generation profiles were created out of SAM and each
generation profile was inserted into Alinta’s financial model.
Effect on LCOE & IRR
Key metrics for each of the alternate systems are presented in Table 9 below.
Table 9: Alternate Systems – modelling outputs
Alternate
System
CAPEX
$M
Annual
GWh
% peak
% off
peak
LCOE
(10%)
IRR
Base case
$577
301
%50
%50
$201
% 1.1
AS 1
$357
167
%72
%28
$230
% 0.0
AS 2
$362
166
%72
%28
$235
% -0.2
AS 3
$402
199
%70
%30
$215
% 0.7
AS 4
$431
205
%70
%30
$224
% 0.4
AS 5
$439
220
%66
%34
$214
% 0.6
The single metric which will determine the viability of an investment is the IRR. In Table 9 one can see
the IRR of the alternate systems is less in each case than the IRR of the base case. This indicates that,
once all factors are introduced into the calculation determining the economic payback, LCOE (ultimately
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driven by capacity factor) is still an appropriate metric to use for ranking the economic performance of
CSP systems in Port Augusta.
4.6.3 Market Forecast
In order to better understand the potential effects of forecast prices on the financial viability of a CSP
plant of this type, Alinta commissioned Acil Allen to create three forward curves for the spot price in the
South Australian market. Each of these forward curves incorporated different assumptions about
variables that were considered likely to impact the market: Renewable Energy Target policy, future
carbon price and rate of uptake of domestic PV.
The impact that these variables have on the expected future price of electricity in South Australia is
complex, however it is heavily dominated by assumptions about a future price on carbon.
Forecast price curves
The forward curve used in the reference case for the financial model in the Draft Balance of Study report
was commissioned by the Alinta Energy Wholesale department as part of strategy and planning for the
coming years. The alternative forward curves used in the modelling for this study are based on the
reference case with changes to one or more key assumptions that were thought to have the potential to
have a material impact on the financial viability of a CSP plant in Port Augusta.
The three alternative forward curves are described below.
Forward Curve 1 – Assumes a price on carbon is reintroduced into the market from July 2020 with
prices based on the current forward curve for emissions abatement permits in the EU.
Forward Curve 2 – Assumes a price on carbon is reintroduced by July 2020. Prices are based on the
assumption that there is a global agreement to reduce emissions by 2050 by 80 per cent on 2000 levels.
This scenario also assumes that the Large Scale Renewable Energy Target is unchanged from the
original target with a target of 41,000 GWh by 2020.
Forward Curve 3 – Assumes the same carbon prices as forward curve 2 but also assumes the RET is
changed so that the target equals 30% of demand by 2030 with the scheme expiring in 2040. Forward
curve 3 also assumes a stronger uptake in rooftop PV in line with the Rapid scenario presented in the
2014 National Electricity Forecasting Report published by AEMO.
Each of the Alternate System was modelled against these three additional forward curves to calculate
potential revenue
Effect on IRR
Unsurprisingly, the variable that has the most significant impact on the future market price of electricity is
the price of carbon. This is seen in the analysis where all scenarios have a greater IRR when run against
Forward Curve 2 and Forward Curve 3 where carbon prices drive a national target to reduce carbon
emissions to -80% of 2000 levels by 2050. This is much more ambitious than the current policy target of
-5% by 2020 and beyond most expectations of any near-term policy. Table 10 below presents the
financial metrics of the base case when the different forward curves are assumed. As the forward curve
affects only revenue, not expenses, there is no change to the LCOE of the system ($201/MWh).
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Table 10: Base case vs. forward price curves
Forward
Curve
IRR
NPV (12%)
$M
Reference
curve
1.07%
-$360
FC 1
0.80%
-$352
FC 2
2.10%
-$336
FC 3
1.96%
-$337
When the various alternate system configurations are also considered in the context of the different
forward curves there are two things that become apparent:
1. Shown by the data in Table 11, the capacity factor at which a CSP plant is run has more effect on
the IRR than altering system design to maximise the ratio of on-peak to off-peak generation. As
the storage component of the system increases, so does the capacity factor and the IRR.
2. Shown by the data in Table 12, the most significant factor driving the NPV of a CSP system in
this study is the capital cost. The Base Case has the highest CAPEX. CAPEX reduces from AS
5 down to the lowest for AS 1.
Table 11: IRR as a function of system design & forward price curve
Forward
demand curve
Reference curve
FC 1
FC 2
FC 3
System configuration
Base Case
1.07%
0.80%
2.10%
1.96%
AS 1
0.00%
-0.37%
1.05%
0.88%
AS 2
-0.16%
-0.53%
0.87%
0.70%
AS 3
0.66%
0.34%
1.72%
1.56%
AS 4
0.35%
0.02%
1.41%
1.25%
AS 5
0.55%
0.22%
1.64%
1.48%
Table 12: NPV @ 12% as a function of system design & forward price curve
Forward
demand curve
Reference curve
FC 1
FC 2
FC 3
System configuration
Base Case
- $ 359,792
- $ 351,537
- $ 335,773
- $ 337,413
AS 1
- $ 239,732
- $ 234,767
- $ 224,322
- $ 225,638
AS 2
- $ 245,552
- $ 240,670
- $ 230,289
- $ 231,626
AS 3
- $ 258,191
- $ 252,303
- $ 240,546
- $ 241,965
AS 4
- $ 282,880
-$ 276,648
- $ 264,028
- $ 265,544
AS 5
- $ 284,082
- $ 277,495
- $ 264,377
- $ 265,889
4.6.4 Time of Day Pricing vs DNI datasets
The revenue stream in the financial model assumes that the CSP plant would receive spot prices for all
electricity delivered to the grid during the lifetime of the plant. As both spot price and DNI are variables
which can move dramatically over short periods, Alinta commissioned an analysis of the correlation
between spot price and DNI. The significance of a correlation would be seen in an (assumed) increase in
105-RPT-006-Milestone_4_Summary_Report
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revenue when running historical spot price record against historical DNI data as opposed to a TMY file of
DNI data.
The results of this investigation show that:

There does not appear to be a real time correlation between spot price and DNI

There is a correlation between cumulative daily DNI and ambient temperature

There is a correlation between ambient temperature and spot price
Therefore, while DNI has a direct impact on the temperature of the day and the temperature of the day
does correlate to the spot price for electricity, at least during summer months, the short term fluctuations
in DNI which will be different between a TMY file and a real data file are not material when considering
their impact on the behaviour of the spot market.
Therefore a TMY file is appropriate for modelling the performance of a CSP system and potential revenue
streams in a dynamic electricity market.
4.6.5 Dispatch Methodology
It is not possible to implement sophisticated plant dispatch routines within SAM. When modelling a CSP
system that operates in a base-load pattern this is not a significant constraint to the model. However,
when the system is not designed as a base load and more closely resembles a peaking plant, the ability
to optimise the dispatch can have a significant impact on the financial performance by enabling a better
match between the electricity sent out and peaks in the market price.
Alinta engaged Solar Reserve in order to understand better the potential gains in revenue that could be
possible through optimising the plant dispatch. A CSP plant of the same configuration and capacity as
the Alinta base case was run through a dispatching protocol with perfect foresight of the spot market
prices. The revenue forecast through the perfect foresight model was approximately 18% higher than the
revenue forecast with the SAM dispatch regime.
There are two key assumptions that inform this analysis and must be noted here:
1. All electricity exported can be sold at the market rate; and
2. Dispatch of the CSP plant is done with full knowledge of all future market prices.
Both of these assumptions are unrealistically optimistic, however this exercise leads to the conclusion
that there is a material gain to be made by optimising the dispatch of a CSP plant, which cannot be
effectively done in SAM. It would be reasonable to assume that half (~10%) of this gain could be
captured by virtue of detailed market knowledge and understanding without having perfect foresight of
future market prices.
4.7 Project Financial Viability
All organisations will select investments based on different benchmarks and therefore an investment that
may not be attractive to one organisation may be considered a worthy investment by another. Some
variables that are key to a company’s decision whether to invest include, but are not limited to:

Requirement for minimum return on investment (Internal Rate of Return - IRR);

Organisational risk profile;

Access to and cost of capital; and

Logical synergies with existing assets and/or business strategies.
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These metrics and others will typically act as a filter and those potential projects which meet the minimum
criteria will then be ranked against each other to create a priority listing. Depending on the capital and
other resources which may be available, access to finance and other potential constraints. One or more
of the potential projects may be pursued. Therefore it may be the case that a contemplated project is
thought to be profitable but there are logistical or other constraints that prevent an investment being
made by a particular organisation.
4.7.1 Financial parameter benchmarks required for project viability
Any potential project investment will be determined by many and varied factors which are prioritised and
valued differently by different organisations. There are several different perspectives that can be taken on
how to make a CSP plant at Port Augusta a financially viable investment. The simplest approach is to
define the decrease in CAPEX that would be required to give the project a minimum IRR of 10%. This
level of IRR does not represent a benchmark for Alinta’s investment decisions, rather it represents the
lowest benchmark IRR that some companies may contemplate when shortlisting potential investments.
Holding all other parameters fixed, the reduction in CAPEX would need to be approximately 60% as
shown in Table 13 below.
Table 13: Minimum financial benchmarks for CSP investment at Port Augusta
Parameter
Modelled Value
Required Value
LCOE
$201 / MWh
$80 / MWh
Installed cost
$10.5M / MW gross
$4.2M / MW gross
CAPEX
$577M
$231M
CAPEX / kWh / yr
$1.86
$0.745
Difference
- 60%
This is presented graphically in Figure 8 below. Each of the three coloured lines represents a given IRR
(10, 12 & 15%). The green line represents the levelised revenue while the LCOE is determined by the
point on the IRR curve corresponding to the CAPEX of the project. The difference between the LCOE
and the levelised revenue is the shortfall which would need to be recovered in some form in order for the
investment to appear economic.
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Figure 8: LCOE as a function of IRR and CAPEX – Base Case/Reference Curve
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Running multiple sensitivity analyses on the variables under consideration shows that, while there could
be a significant difference in the shortfall depending on assumptions about cost and revenue, no
combination of assumptions considered makes the project appear economic. Making the most optimistic
assumption on all variables on the base case is represented graphically in Figure 9. The assumptions
behind this scenario include:

CAPEX is 30% less than estimated;

OPEX is 30% less than estimated;

An up-front grant of $100M is applied to CAPEX; and

Dispatch optimisation provides a revenue uplift of 10% over modelled value;
Figure 9: LCOE as a function of IRR and CAPEX – Variation 2
Table 14 on the following page contains the results of a range of sensitivity analyses that were run using
different combinations of cost assumptions and forward curves. It should be noted that there is equal
probability of the actual cost being 30% more than the estimate as being 30% less than the estimate. No
scenario with an increased capital cost has been explored.
In this case, no combination of assumptions about system design, forward curve and CAPEX/OPEX
combinations result in a system that is a viable investment.
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Table 14: Sensitivity of IRR & NPV to multiple variables
Scenario
Reference
Variation 1
Variation 2
Variation 3
Variation 4
Variation 5
Variation 6
Variation 7
Variation 8
Variation 9
Variation 10
Variation 11
Variation 12
Variation 13
Variation 14
Variation 15
Variation 16
Variation 17
Variation 18
Variation 19
Variation 20
Variation 21
Variation 22
Variation 23
Variation 24
Variation 25
Variation 26
Variation 27
Variation 28
Variation 29
Variation 30
Variation 31
Variation 32
Forward
Curve
Reference
Reference
Reference
Reference
Reference
FC 1
FC 1
FC 2
FC 2
Reference
Reference
FC 1
FC 1
FC 2
FC 2
Reference
Reference
FC 1
FC 1
FC 2
FC 2
Reference
Reference
FC 1
FC 1
FC 2
FC 2
Reference
Reference
FC 1
FC 1
FC 2
FC 2
System
Base case
Base case
Base case
AS 1
AS 1
AS 1
AS 1
AS 1
AS 1
AS 2
AS 2
AS 2
AS 2
AS 2
AS 2
AS 3
AS 3
AS 3
AS 3
AS 3
AS 3
AS 4
AS 4
AS 4
AS 4
AS 4
AS 4
AS 5
AS 5
AS 5
AS 5
AS 5
AS 5
CAPEX
$M
577
577 -30%
577 -30%
357 -15%
357 -30%
357 -15%
357 -30%
357 -15%
357 -30%
362 -15%
362 -30%
362 -15%
362 -30%
362 -15%
362 -30%
402 -15%
402 -30%
402 -15%
402 -30%
402 -15%
402 -30%
431 -15%
431 -30%
431 -15%
431 -30%
431 -15%
431 -30%
439 -15%
439 -30%
439 -15%
439 -30%
439 -15%
439 -30%
577
404
404
303
250
303
250
303
250
308
253
308
253
308
253
342
281
342
281
342
281
366
302
366
302
366
302
373
307
373
307
373
307
Capital Grant
$M
$
$
50
$
100
$
50
$
100
$
50
$
100
$
50
$
100
$
50
$
100
$
50
$
100
$
50
$
100
$
50
$
100
$
50
$
100
$
50
$
100
$
50
$
100
$
50
$
100
$
50
$
100
$
50
$
100
$
50
$
100
$
50
$
100
OPEX
$M/yr
7.9
7.9 -30%
7.9 -30%
6.0 -15%
6.0 -30%
6.0 -15%
6.0 -30%
6.0 -15%
6.0 -30%
6.0 -15%
6.0 -30%
6.0 -15%
6.0 -30%
6.0 -15%
6.0 -30%
6.3 -15%
6.3 -30%
6.3 -15%
6.3 -30%
6.3 -15%
6.3 -30%
6.7 -15%
6.7 -30%
6.7 -15%
6.7 -30%
6.7 -15%
6.7 -30%
7.2 -15%
7.2 -30%
7.2 -15%
7.2 -30%
7.2 -15%
7.2 -30%
7.9
5.5
5.5
5.1
4.2
5.1
4.2
5.1
4.2
5.1
4.2
5.1
4.2
5.1
4.2
5.4
4.4
5.4
4.4
5.4
4.4
5.7
4.7
5.7
4.7
5.7
4.7
6.1
5.0
6.1
5.0
6.1
5.0
Revenue
uplift
0%
10%
10%
0%
10%
0%
10%
0%
10%
0%
10%
0%
10%
0%
10%
0%
10%
0%
10%
0%
10%
0%
10%
0%
10%
0%
10%
0%
10%
0%
10%
0%
10%
IRR
1.1%
6.1%
7.4%
2.5%
8.2%
2.3%
8.4%
3.7%
9.7%
2.3%
7.9%
2.1%
8.0%
3.5%
9.3%
3.1%
8.4%
2.9%
8.5%
4.3%
9.8%
2.7%
7.6%
2.5%
7.7%
3.9%
9.0%
2.9%
7.9%
2.7%
8.0%
4.1%
9.3%
LCOE
$/MWh
$
201
$
125
$
110
$
169
$
107
$
169
$
107
$
169
$
107
$
172
$
110
$
172
$
110
$
172
$
110
$
160
$
105
$
160
$
105
$
160
$
105
$
168
$
113
$
168
$
113
$
168
$
113
$
162
$
109
$
162
$
109
$
162
$
109
NPV $M
(12%)
-$360
-$134
-$93
-$141
-$38
-$137
-$35
-$128
-$25
-$146
-$42
-$142
-$39
-$133
-$29
-$154
-$45
-$150
-$40
-$139
-$28
-$174
-$59
-$169
-$55
-$158
-$42
-$174
-$57
-$169
-$53
-$157
-$39
Note: LCOE is calculated on a 10% IRR
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4.7.2 LCOE Assessment
When breaking down the component contributions to LCOE as determined by Alinta’s financial model, it
is apparent that the findings are well aligned with existing literature. Alinta found that, in the context of
the base case, capital costs contribute approximately two-thirds to LCOE. As expected, the heliostat field
makes the single largest contribution in both CAPEX and OPEX. Table 15 below shows the contribution
the OPEX and CAPEX costs make to the LCOE of the base case plant modelled at Port Augusta.
Table 15: Contributions to LCOE by category and CAPEX vs OPEX
Category
CAPEX
contribution
OPEX
contribution
Total $/MWh
Solar Field
43
32
75
Receiver / HTF
31
7
39
Power Plant
35
23
57
Thermal Energy Storage
24
6
30
TOTAL $/MWh
133
68
201
Table 16 identifies the contributions that the major component categories make to the total LCOE
modelled. The four categories were chosen to align with the metrics use by the SunShot Initiative which
is being run by the Department of Energy in the United States. The SunShot Initiative has the aim of
reducing LCOE of CSP technologies by approximately 70% between 2010 and 2020.
Also in Table 16 is the 2013 technology costs achieved by SunShot and the 2020 target costs. The sum
of CAPEX expenses that were not clearly associated with one of these categories was allocated
according to the percentage of the known CAPEX costs for each category. General OPEX costs were
divided evenly among the four categories.
Table 16: LCOE contributions by category compared to SunShot targets
Category
Port
Augusta
Sunshot
2013*
Sunshot
target 2020*
Solar Field
75
68
27
Receiver / HTF
39
27
14
Power Plant
57
55
27
Thermal Energy Storage
30
27
14
TOTAL $/MWh
201
177
82
*converted from 2010 USD to 2014 AUD at exchange rate of $0.8 USD:AUD and inflation at 1.09
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If the SunShot Initiative is successful in reducing the technology costs in line with the targets summarised
above, a CSP plant as modelled in this study has the potential to be independently economic not long
after the year 2020.
4.8 Unexplored Concepts
Through internal workshops and through discussions with other industry participants, several concepts
have been identified that would be worthy of further investigation in Stage Two of the Study. These
concepts are not considered to be significant enough to overcome the financial viability gaps identified
thus far in the Study.
4.8.1 Storage from grid power
It would be possible to build in the capability to heat the thermal storage tanks with power imported from
the grid. This would give the flexibility to purchase electricity at low or negative prices and return
electricity to the grid during higher prices. There are several factors which would limit the benefit of this
concept:

Upgrade of the interconnection to Victoria is likely to flatten market fluctuations therefore raising
the minimum market prices and reducing peak prices;

The round trip efficiency of this process will be limited by the efficiency of the power block which
would be on the order of 40%;

As the thermal storage capacity of a CSP plant increases, the window for profitable purchase and
re-selling through this mechanism decreases;
The complexity that is introduced by this functionality could be very high. A deeper understanding of the
details would be required before knowing whether this idea would actually be of benefit.
4.8.2 Use of waste heat
In many settings, the economics of a CSP plant are enhanced because the useful energy is not just the
electricity that is generated, but the low grade waste heat from the system is also beneficial to some other
end user or industrial process. This is the case with the smaller solar thermal plant that is being
constructed by Sundrop Farms in Port Augusta.
In the context of the CSP plant modeled by Alinta at Port Augusta there is no obvious beneficial use for
waste heat from the power block.
4.8.3 Hybridised solar
Linear Fresnel is a cheaper technology than the central receiver with molten salt. The potential for using
a Linear Fresnel field to pre-heat the heat transfer fluid prior to entering the main receiver at the top of the
tower could be considered. This may reduce the overall area of the heliostats required.
There have been CSP plants recently commissioned which include a PV component. These plants are
cheaper per unit of installed capacity and therefore also in terms of LCOE. As discovered earlier,
capacity factor appears to drive LCOE more strongly than all other variables. Therefore, adding PV
capacity may reduce the average LCOE of a hybrid PV/CSP plant but presumably only if there were
additional CAPEX invested in adding PV to the design. The addition of PV capacity would not
economically replace thermal capacity, but would augment it.
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4.8.4 Alternative location
While Port Augusta is a convenient site in terms of infrastructure availability and solar resource, there are
other locations in South Australia which offer a better solar resource. Depending on the additional cost to
install a substation and/or high voltage transmission line, an alternative location could increase the output
of an identical CSP plant by a material amount.
5
Near Commercial Technologies
Of the inquiries made by Alinta into technologies that are expected to be commercial in the near term,
most were met with a reluctance to reveal information. Any technology that is under an advanced stage
of development would be expected to have an impact on the market and competitive influence of the
company developing the technology. This may be the motivation for the lack of information sharing in
this area.
The only company to respond with any information of substance was Vast Solar.
5.1 Technical Maturity
Alinta visited the Vast Solar demonstration facility in Jemmalong NSW in March 2015. This facility, once
operational, will have a 1.1 MWe capacity and is intended to prove the integrated operation of the
hardware and software developed by Vast Solar. While Alinta understands that the individual
components of Vast’s technology have all been trialed and tested, it is the successful operation of the
entire system that will encourage energy companies and developers to invest in Vast Solar.
Without making a thorough engineering analysis of the Vast Solar CSP System, Alinta’s view is that the
key items which will require rigorous testing and data records to verify performance will be the operation
of the heliostats, the material durability of the mirrored surfaces, the heat transfer properties/efficiency of
the receiver and storage system and the use of sodium as a heat transfer fluid.
Vast Solar technology has not yet proven itself to a stage that would make Alinta comfortable investing
substantially in the company, however Alinta believes there is promise in the path Vast Solar is taking.
5.2 Financial Potential
The cost estimates provided by Vast Solar for the purposes of this study have not been developed for a
CSP plant matching the Base Case in the study. Rather, Vast Solar have taken a cost estimation, which
they believe to be +/-10%, developed for a 30MW plant with 4 hours storage and scaled those cost
estimates to a CSP plant that is equivalent to Alinta’s Base Case.
Based on the assumption that the output from a Vast Solar plant with the same sized power block and
thermal storage would deliver the same electricity generation profile as the power tower in Alinta’s Base
Case, the revenue from a Vast Solar plant would be the same.
Table 17 below presents the results of Alinta’s financial model when the CAPEX and OPEX provided by
Vast Solar are used as primary inputs. Based on these results, if costs prove to be as projected, the Vast
Solar technology appears to be close to commercial.
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Table 17: VAST Solar scaled base case vs. forward price curves
Forward
Curve
6
IRR
NPV (12%)
$M
Reference
case
9.7%
-$35.8
FC 1
10.0%
-$30.5
FC 2
11.1%
-$15.2
FC 3
10.9%
-$17.1
Further Information
A dedicated public webpage has been established on Alinta Energy’s website:
http://alintaenergy.com.au/about-us/power-generation/port-augusta-solar-thermal.
All milestone reports and media releases have been publicly-available on this website through the course
of the study.
Also free to the public will be the data that Alinta has collected since the installation of the solar tracker
and weather station in early June, 2014. Monthly files containing all solar data and weather station data
will be freely available to the public upon request.
On Thursday 23 April 2015 Alinta held a public information session in Port Augusta. There were
approximately 50 attendees which included local and federal politicians, representatives of NGOs and
South Australian Government agencies as well as interested individuals. At this session Alinta presented
a comprehensive summary of the progress and findings of the study to date. The session was well
attended and attracted significant media. The presentation given on the day is available on the website
referenced above.
7
Conclusion
The cost of Stage One has been approximately ~$950,000. The forecast cost to undertake Stage Two of
the feasibility study is ~$1,160,000.
The outcome of Stage Two would be better certainty about the present day cost for the construction of a
CSP plant in Port Augusta. In Table 14 Alinta presented the results of thorough sensitivity analysis
including scenarios where all assumptions were at the extreme optimistic margin. Even in these
scenarios this potential project does not meet Alinta’s minimum benchmarks for further investment
consideration.
Alinta has an expectation on investment returns that is likely more aggressive than many other
organisations. Another proponent with a different appetite for risk, lower minimum investment returns
and potentially other strategic interests would be better placed to pursue a full feasibility stage of this
study or a similar study.
Based on the information compiled over the last 18 months of Stage 1 of the Port Augusta Solar Thermal
Generation Feasibility Study and the anticipated costs and benefits of refining the current level of
knowledge, Alinta has decided not continue into Stage Two.
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