Case Study Finance

This case study explores the finance of a joint venture between CS Energy and Alinta Energy Limited for the production of electricity. It includes a cash flow analysis, capital budgeting techniques, and risk assessment. The project requires government approval and considers both quantitative and qualitative risks. The study concludes that the project is feasible and recommends its implementation.

Running head: CASE STUDY FINANCE
Case Study Finance
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Author Note

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Executive Summary
CS Energy and Alinta Energy Limited have agreed for a joint venture for the purpose
production of electricity. A spreadsheet model was developed by using the cash flows that
related to the project. The capital budgeting techniques were used to analyse the project.
The quantitative and qualitative risks were identified by conducting a sensitivity as well as
scenario analyses for the project to focus on its feasibility and operations. The permission
of the Government was taken to construct the project.

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Table of Contents
Introduction............................................................................................................................3
Spreadsheet Model Development..........................................................................................3
Quantitative and Qualitative Risk..........................................................................................4
Project Modelling and Recommendation..............................................................................7
Business Proposal..................................................................................................................8
Conclusion.............................................................................................................................8
Reference list.........................................................................................................................9

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Introduction
The cash flow of the project has been used for the financial analysis of CS Energy.
There are various factors that have been taken into consideration for the development of
this project. The techniques like Internal Rate of Return, Net Present Value, Payback
Period and Discounted Payback Period have been used to take decisions about its
feasibility. A better understanding of the project has been done by assessing the qualitative
and quantitative aspects of the nuclear power plant (Hong, Bradshaw and Brook 2014).
The Sensitivity analysis has been done by considering different values for the inputs of the
project and the most profitable combination has been decided for the identification of
quantitative risk. The effect on the Net Present Value and its relatable outcome have been
used to analyse the project. Certain factors like the inflation rate, operating efficiency,
discount rate, tax rate and various other factors have also been taken into consideration. A
scenario analysis has also been done by changing the factors of construction and
identifying the best situation as well as the worst case situation for it (Mu et al. 2016).
However, there are some legislative barriers, regulatory frameworks and legal compliances
that the company needs to adhere for the construction of the project. An approval from the
Government is of utmost importance. As the Government had banned generation of
nuclear power.
Spreadsheet Model Development
There has been a joint venture agreement between the two companies CS Energy
and Alinta Energy Limited for providing electricity to the people of Queensland. There is
huge requirement of assets for the development of this project. A period of 5 years is
required for the construction of the project starting from the year 2021. The power plant is
expected to operate for 60 years of time. The relevant construction costs for the project

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have been identified. It has been decided not to spend a large amount of money in the
construction phase of the project. The revenue generated on the basis of the tariff rates,
after deduction of depreciation allocations, taxation and storage costs to arrive at the net
profit. The resources used in the project are non-renewable and the technology involves
high risk (Chang and Myers 2015). The project also has concerns relating to the
environment issues and climate change even though it is a widely used and clean source of
energy. There has been an ongoing debate regarding the use of traditional resources like
gas and coal as compared to the trend of developing sustainable resources like water, wind
and so on. The uranium is that is used for the storage and purchase of the project have a
very low cost due to the manner in which they are used (Chen and Cafarella 2014). There
are also some issues relating to the foreign potential ownership issues with the company as
it is owned by company based in Hong Kong. Even though foreign involvement in this
sector has been a very common trend. The cash flow of the project has been discounted for
the evaluation of its performance. The construction cost has been calculated (Sovacool,
Nugent and Gilbert 2014).
Quantitative and Qualitative Risk
The company should have a mix of both debt and equity in their source of
financing to diversify its risk. The Weighted Average Cost of Capital has been used to
measure the required returns (Modarres 2018). The cost benefit analysis has been done
using the profitability index, net present value, internal rate or return and payback period
methods as the quantitative measures (Shakouri, Nabaee and Aliakbarisani 2014). The
cash flow were forecasted as accurately as possible. The project will take a period of 9.5
years to recover its initial amount of investment in the power plant.

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A sensitive analysis for the power plant has been done by assuming changes in the
operating efficiency factor, real tariff price, internal rate of return and the inflation rate.
The operating efficiency factor of the project has been assumed to vary from 91% -
95% and the changes have been noted. It is the ratio used to improve the ratio of output
with the input. The inputs that have been used for the project and the outcomes earned is
defined by this factor. A 7% loss is relating to the maintenance of work on the reactors.

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The average cost of uranium has been estimated as US$1,500 each pound and the
tariff rate has been calculated as $85. This cost includes transformation, enrichment and
refining of the nuclear rods into nuclear reactors.
The average cost of M & O that is used for forecasting the profits from the
potential investments that were made in the project. This rate of 8% will help to arrive at
the zero value of net present value. This was the most appropriate rate determined for its
operations and construction. The average of maintenance and operating costs including the
vehicles, equipment, nuclear reactor operation, treatment of water for the purpose of
cooling have been estimated at 40%.
As the values are forecasted for the future, certain inflation rates have also been
assumed that may affect the performance of the company. It is a reflection of the entire rise
in Consumer Price Index that was calculated using the weighted average price of the
factors. The range of 2.3% has been assumed within the target range of Reserve Bank of
Australia.

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The qualitative parameters are the non-financial considerations that also have an
impact on the operations of the business (Van Vliet et al. 2016.). The reasons for rejection
of a project does not always be due to the quantitative reasons, sometimes the qualitative
parameters can also lead to its rejection (Mihas 2019.). The qualitative concerns of the
company were safety of the working conditions of its workers, environmental damage and
a wider range of protection for the community members having activities of construction,
mining and oil rigs that are offshore (Tsvetkov 2014). The asbestos exposure, health of its
consumers, injury and harmful radiations are also taken into account for determining its
risk. Certain political issues and problems including the risk linked with sovereignty with
its overseas project and investment also have an impact on it.
Project Modelling and Recommendation
The model is a powerful and comprehensive representation of the cash flows and
asset structure of the company. It is a big and complicated model that has been developed.
On proper development of the project, it can be entirely integrated and allowed for quick
modification of the parameters of the project and updating of changes in the information.
This modelling assists for conducting the sensitivity analysis (Ikonen and Tulkki 2014).
The effect of the Net Present Value on the project has been evaluated. The variables have
been substituted to assess the impact on its Net Present Value. The changes in the inputs
that have resulted in a great change of the outcome has been considered more sensitive
than the other inputs that have impacted it less. The scenario analysis is done for the
projects that have long period of time where the variations in the inputs would lead to
greater changes in its expected outcome.
Therefore, CS Energy is recommended to begin its nuclear power station in
collaboration with Alinta Energy Limited. The company wants to increase the electricity

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capacity in Queensland. It needs to take approval from the Government. The feasibility
analysis is favourable for this project. Therefore, it will benefit its people.
Business Proposal
The business case proposal is being prepared for the Australian Federal
Government to request permission for the construction of the nuclear power plant. It had
been banned in the country. Now, that the company is making use of the natural resources
like the sea water and other non-renewable resources it requires the approval to proceed
with it (Wolfram, Wiedmann and Diesendorf 2016). The ethical issues of the power plant
has focused on its comparison between the hazards and benefits of its power generation.
The severe impact that it may have on its people in case of an accident. Therefore, safety
measures have been adopted to prevent such kind of loss as they affect the global health.
Conclusion
The report helps us to conclude that the nuclear power station proposal by CS
Energy is a feasible project. The company will be successful in providing electricity to its
people living in Queensland. The types of quantitative and qualitative risks associated have
been highlighted. A sensitivity analysis has been conducted. The ethical issues relating to
its construction have been emphasised.

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Reference list
Chang, K.S.P. and Myers, B.A., 2015, April. A spreadsheet model for handling streaming
data. In Proceedings of the 33rd Annual ACM Conference on Human Factors in
Computing Systems (pp. 3399-3402). ACM.
Chen, Z. and Cafarella, M., 2014, August. Integrating spreadsheet data via accurate and
low-effort extraction. In Proceedings of the 20th ACM SIGKDD international conference
on Knowledge discovery and data mining (pp. 1126-1135). ACM.
Hong, S., Bradshaw, C.J. and Brook, B.W., 2014. Nuclear power can reduce emissions and
maintain a strong economy: Rating Australia’s optimal future electricity-generation mix by
technologies and policies. Applied energy, 136, pp.712-725.
Ikonen, T. and Tulkki, V., 2014. The importance of input interactions in the uncertainty
and sensitivity analysis of nuclear fuel behavior. Nuclear Engineering and Design, 275,
pp.229-241.
Mihas, P., 2019. Qualitative data analysis. In Oxford Research Encyclopedia of Education.
Modarres, M., 2018. What every engineer should know about reliability and risk analysis.
CRC Press.
Mu, H.N., Liu, J.W., Lu, M.C., Chen, J.F. and Yi, X.J., 2016, December. Reliability
analysis method of phased-mission nuclear power equipment based on goal oriented
methodology. In 2016 IEEE International Conference on Industrial Engineering and
Engineering Management (IEEM)(pp. 1375-1379). IEEE.
Shakouri, H., Nabaee, M. and Aliakbarisani, S., 2014. A quantitative discussion on the
assessment of power supply technologies: DEA (data envelopment analysis) and SAW

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(simple additive weighting) as complementary methods for the “Grammar”. Energy, 64,
pp.640-647.
Sovacool, B.K., Nugent, D. and Gilbert, A., 2014. Construction cost overruns and
electricity infrastructure: an unavoidable risk?. The Electricity Journal, 27(4), pp.112-120.
Tsvetkov, V.Y., 2014. Opposition variables as a tool of qualitative analysis. World Applied
Sciences Journal, 30(11), pp.1703-1706.
Van Vliet, M.T., Wiberg, D., Leduc, S. and Riahi, K., 2016. Power-generation system
vulnerability and adaptation to changes in climate and water resources. Nature Climate
Change, 6(4), p.375.
Wolfram, P., Wiedmann, T. and Diesendorf, M., 2016. Carbon footprint scenarios for
renewable electricity in Australia. Journal of Cleaner Production, 124, pp.236-245.