Power Generation Financial Modelling and Analysis a Practical Guide

Power Generation Financial Modelling & Analysis: A Practical Guide


David Whittaker

EUROMONEY

BOOKS

Published byEuromoney Institutional Investor PLCNestor House, Playhouse YardLondon EC4V 5EXUnited Kingdom

Tel: +44 (0)20 7779 8999 or USA 11 800 437 9997Fax: +44 (0)20 7779 8300www.euromoneybooks.comE-mail: [email protected]

Copyright 2013 Euromoney Institutional Investor PLC

ISBN 978 1 78137 175 6

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vContents

Acknowledgements ixAbout the author xi

1 Introduction 1

2 Background to the world market 3

3 Energy units of measure and calculations 9Installed capacity 10Annual capacity factor 10Fuel costs 10Operations and maintenance costs 10Capital costs and plant life 11

4 Building the power generation option appraisal financial model 13Financial modelling best practice 13Scope 18Designing the financial model 18Layout 18

Layout exercise 19Timeline 19

Timeline exercise 20Monthly calculations 20

Monthly calculations exercise 22Monthly cash flow 22

Monthly cash flow exercise 23Annual corporation tax 23

Annual corporation tax exercise 23Annual cash flow 24

Annual cash flow exercise 24Summary 24

Summary exercise 24Finalising the existing option appraisal financial model 24

Exercise finalising the existing option appraisal financial model 28Sources of error 28Self testing the financial model 28

Top level analytical review 28Key output review 30Flex and sensitivity review 31Exercise self testing the financial model 31

vi

Contents

Using the model 31Disclaimers 32

5 Power generation projects 33Natural gas combined cycle gas turbine 33Coal fired 37Energy from waste 41Solar thermal 44Hydroelectricity 48Tidal power 52Geothermal 55Wind farms: onshore 58Wind farms: offshore 62

6 Funding options for the power generation sector 65Project finance as a source of funding 65Financial modelling best practice 66Designing the financial model 70Layout 70

Layout exercise 72Timeline 72

Timeline exercise 73Construction 73

Construction cost exercise 73Financing 73

Financing exercise 78Tariff receipts 78

Tariff receipts exercise 79Operating costs 79

Operating costs exercise 80Working capital 80

Working capital exercise 83Accounting 84

Fixed asset accounting 84Borrowing costs 84Interest during construction and bid costs 84Accounting exercise 85

Taxation 85Taxation exercise 85

Dividends 86Dividends exercise 86

Profit and loss account 87Profit and loss exercise 87

Contents

vii

Cash flow 87Cash flow reforecast exercise 88

Balance sheet 88Balance sheet reforecast exercise 88

Checks 89Checks exercise 89

Sensitivities 89Sensitivity exercise 92

Checks 92Checks exercise 92

IRRs 93IRRs exercise 94

Lenders ratios 94Lenders ratio exercise 95

Summary 95Summary exercise 95

Optimising the tariff 95Energy tariff optimisation exercise 97

Sensitivity logic 97Sensitivity exercise 100

Debt sculpting 100Debt sculpting exercise 106

Sources of error 106Self testing the model 106

Top level analytical review 107Key output review 107Flex and sensitivity review 107Limited scope financial model reviews 107Design review 108Analytical review 109Degree of integration and reconciliation of financial statement forecasts 109Flex testing and sensitivity review 109Parallel or shadow modelling 110Macro review 110Exercise self testing your project finance model 111

Using the model 111Private equity as a source of funds 111

7 Using Excel VBA 115An introduction to Excel VBA 115Protect functionality 118Unprotect functionality 119Menu functionality 119Auto open functionality 123

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Contents

Auto close functionality 123Using a timeout facility for demo financial models 124Unhide sheets 126Hide sheets 127

Exercise Excel VBA 127

8 Reviewing and auditing power generation financial models 129Scoping 133Work plan 168Coding review 170Analytical review 173Data book and legal documentation 173Tax 173Accounting 173Review comments 173Iterations and base case clearance process 173Sensitivities 174Second senior review 174Partner sign off 174

9 Financial modelling management issues 175Project managing financial modelling projects 175

Exercise 176The use of template and generic financial models 176

Exercise generic and template financial models 176

10 Approaches to risk 177Data tables 177Scenario manager 177Goal seek 178Custom scenarios 178

Risk exercise 179

11 Conclusion 181

Glossary 183

ix

Acknowledgements

I would like to dedicate this book to my family. In particular, my daughter Daniella Whittaker who at the time of writing this book has completed her first year at school and is developing her reading, writing and arithmetical skills at a great level of advancement. I look forward to the day when she can fully appreciate my books.

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About the author

David Whittaker is a Chartered Management Accountant who has over twenty years experi-ence within financial modelling for commerce, industry, the public sector and the big four financial modelling practices. He has led several financial modelling training courses and seminars for the power generation sector.

1Section 1

Introduction

This book has been specifically written to address the financial modelling and analysis needs of power generation sector transactions and projects. Readers may currently be at the beginner or intermediate level. However, it is also useful for managers who require a further understanding of the process without having to go through the learning curve of actually becoming hands on. The major areas which require analysis are addressed by the use of relevant extracts of a demonstration financial model for example purposes. The reader will be able to go through the process of building the financial models on a step by step basis with reference to the example exercises at their own pace, providing an excellent source of skills transfer.

It is important to note that the figures or the Excel example logic used in this book do not represent any past, current or indeed future energy sector transactions or projects of any kind. The numbers and results contained herein are purely fictional.

Accessing your supporting spreadsheet files this book is accompanied by spreadsheets in MS Excel format. On placing your order you will have received an email with details of how to download these. If you have any queries please contact our Customer Services Team [email protected] or call +44 (0)20 7779 8610.

3Section 2

Background to the world market

We will start by discussing the current position regarding the supply, generation and distri-bution of the worlds energy.

The final consumer is usually the end product of certain energy conversion processes. The primary energy source is usually fuel, such as oil, coal and so on. The amount of electricity actually generated is what reaches the ultimate consumer after auxiliary consump-tion needs or transmission losses in the electricity distribution grid. This is referred to as delivered energy.

A typical energy market supply chain starts with the supply of the raw material which is used for electricity generation and its distribution via a grid. Around a third of the primary energy use is lost in the generation and transmission process by waste heat from power stations.

Electrical power is produced by electrical generators. Electricity is usually sold by the kilowatt-hour (kWh), which is the product of power in kilowatts multiplied by the running time of the power generating unit in hours.

The electrical power industry provides the production and delivery of power in suf-ficient quantities to areas that need electricity through a grid connection. The grid distributes electrical energy to customers.

Demand for electricity is driven by the need to power domestic appliances, office equip-ment, industrial machinery and both commercial and domestic heating.

In the final stage, electrical distribution is undertaken by delivering the electricity to the end user. A distribution system network carries electricity from the transmission system and delivers it to customers. The networks kit includes power lines, substations and pole mounted transformers, low voltage cable and meters.

This book specifically concentrates on the power generation side.It is evident that the worlds current use of fossil fuels is likely to have negative effects

on the environment. The environmental effects of fossil fuel use for power generation include the depletion of fuel resources, acid rain, air pollution and global climate change.

Climate change is caused by the emissions of gases from burning fossil fuels. The earths surface temperature is controlled by the greenhouse gases (carbon dioxide, water vapour and methane) that act like the window pane of a greenhouse. The outcome of this natural green-house effect is to maintain planet earths surface temperature at a suitable level. However, the use of fossil fuels increases the amount of carbon dioxide adding extra greenhouse gas to the atmosphere.

Scientists have calculated that if emissions rise at the current rate there will be associated increases in the temperature of the earths surface causing extreme effects on the climate leading to floods and droughts. The environmental consequences of the use of fossil fuels have led many governments around the world to set targets for renewable energy sources, often providing financial incentives.


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We will now consider the likely trends in the primary energy sources that are forecast to occur around the world between the historic start point of 2010 and the year 2040. Illustration 1 shows the world energy consumption mix.

Illustration 1

World energy consumption mix (quadrillion BTUs)

0

Source: International Energy Agency

Fossil fuels remain the number one source of energy around the globe. However, we will see renewable energy sources growing rapidly. Oil, gas and coal will all grow through to 2040. However, there is a fall in their combined growth as natural gas is forecasted to over-take coal in our world energy consumption mix by 2040. This is mainly due to less carbon


5

dioxide emissions associated with natural gas and its more advantageous price. Renewable energy sources are forecast to grow between 2010 and 2040 mainly due to financial incen-tives provided by governments, falling costs, and the rising price of fossil fuels.

British Petroleum estimated in a 2010 study that the worlds coal reserves could last 120 years before full depletion. Oil could last 45 years and natural gas around 60 years. This has implications for the use of alternatives such as renewable energy sources becoming much more important in the longer term.

We will now turn our attention to the likely trends in world population that are forecast to occur around the world between the historic start point of 2010 and the year of 2040. Illustration 2 shows the world population trends.

Energy demand in emerging markets (non-OECD) will rise 65% by 2040 compared with 2010, reflecting the growth, prosperity and expanding economies. Overall, global energy demand will grow 35%, even with significant efficiency gains, as the worlds population expands from about 7 billion people today to almost 9 billion people by 2040. The growth will be led by growth in Africa and India. We can see in Illustration 2 that there is a projected growth in both India and Africa across all age categories between 2010 and 2040. This shows us that there is a great market potential in both of these emerging markets for electricity generation.

In summary, we can see that the emerging markets (particularly India and Africa) represent a prospect given the expected growth rates. There are also fuel types or technologies which present areas for growth. Consequently, it is important that we understand the risks and opportunities that this presents and the leverage from the financial modelling and analysis techniques that this book addresses.


6

Illustration 2

World population trends

(a) OECD, billions of people

(b) China, billions of people

Continued


7

(c) India, billions of people

(d) Africa, billions of people

Source: World Bank

9Section 3

Energy units of measure and calculations

This section outlines the different ways of expressing energy units and making key calculations.Energy generation typically involves very large numbers and these are often more manage-

able when used in a short form. These are shown in Illustration 3.

Illustration 3

Energy short formsPrefix Multiple Description

Kilo 10^3 One thousand

Mega 10^6 One million

Giga 10^9 One billion

Tera 10^12 One quadrillion

Peta 10^15 One quintillion

Source: Authors own

In terms of the gas and electricity markets the unit of measure for energy is the kilowatt-hour (kWh). The rate of use of one joule per second is equal to the power of one watt. One kWh is equal to 3.6 megajoule (mJ).

To calculate the cost of generating electricity from any type of generating unit whether it is a renewable energy source or a fossil fuel plant, there is a need to take account of the following cost elements:

capital costs; fuel costs; and operation and maintenance (O&M) costs.

During the course of this book we will be looking at the financial impact of the above aspects for various plant types, that is, whether these are fossil fuel or renewable energy sources.

We shall now look at the important variables and drivers involved in power plant economics or financial analysis.


10

Installed capacity

Installed capacity represents the maximum power output of a power plant usually expressed in megawatts (mW) or kilowatts (kW).

Annual capacity factor

The annual capacity factor is the total electricity generated to the maximum limit that could be produced if operating for 24 hours per day and 365 days per year. The things that limit capacity include availability which represents the percentage of the year that the plant is in full working order. The time that it is not on line due to breakdowns is often known as forced outages and planned maintenance programs, often known as planned outages. For certain renewable or sustainable energy sources there is an availability issue.

The capacity factor for a wind farm in the UK can range from 25% to 40% per annum. The net electricity generated per year can be calculated thus: kWhs = mW * 1,000 * Capacity Factor * 365 days * 24 hours per day.That is, a 200 mW coal fired power station with a 85% capacity or load factor can be

shown as follows: 200 mW * 1,000 * 85% * 365 * 24 = 1,489,200,000 kWh per annum.

Fuel costs

Both fossil fuel and biomass technologies have significant fuel costs whereas many renewable energy technologies have a zero fuel cost, such as solar and wind power.

When looking at the fuel aspects it is important to consider the purchase cost of the fuel and the efficiency of the fuel given the level of generation.

Turning our attention to Illustration 4 (see Illustration4.xlsx), waste is purchased at 60 per tonne and has a calorific value of 18 gigajoules (gJ) per tonne. Note that 1 mJ is equal to 0.2778 kWhs.

Here, the fuel cost purchased per tonne is worked up into pence. This number is divided by the number of kWh which is calculated by taking the gJ per tonne and multiplying this by 1,000 to account for the multiple between kilo and giga, and multiplied by the mJ per kWh conversion factor.

The fuel cost per kWh generated is calculated by taking the cost of energy purchased per kWh and dividing this by the efficiency factor.

The efficiency factor is a ratio of the energy output divided by the energy input. So, therefore, if the efficiency factor is 35% the fuel cost per kWh generated is 3.43 pence.

Operations and maintenance costs

The plants O&M costs can typically be split between fixed and variable O&M costs. Variable costs are those which vary with power generation and/or output. Fixed costs do not vary with power plant generation or output and are thus period costs. O&M costs for offshore wind farms are materially higher than onshore ones, due to the freight, travel and so on required to maintain offshore wind farms.

Energy units of measure and calculations

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Fixed costs typically include staff costs and other overheads.Variable costs are, for example, fuel handling costs. Variable costs are usually expressed

in pence per kWh.

Capital costs and plant life

The capital costs for each technology option is critical. The turnkey cost is usually referred to as the engineering and procurement cost (EPC). This is often expressed as a cost per kW or in pounds.

Of course, different power plant technologies have different economic useful lives, which is a key variable for the financial returns, that is, the internal rate of return (IRR) or net present value (NPV) of the plant type considered.

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Section 4

Building the power generation option appraisal financial model

Financial modelling best practice

A recommended approach to financial modelling best practice (FMBP) is shown in Illustration 5.

Illustration 5

Financial modelling best practice

Source: Authors own


14

A structured approach which should ideally be adopted is often referred to as financial modelling best practice. It is because the financial modelling for energy sector projects is high risk, due to the fact that millions of pounds are involved with a number of complex calculations and arrangements, that a structured approach is desired.

We recommend that an FMBP approach is applied to all financial modelling projects not just energy sector projects.

However, in the past the question has often been asked: Isnt FMBP too rigid? The answer to this is that a balance should ideally be struck given the fact that an organisation is bidding or trying to close a transaction over a reasonably tight timescale. Although, the vast majority of financial close models are not particularly well designed given this very fact.

Let us walk-through Illustration 5 and discuss how FMBP relates to our need to build and rely upon the results to be derived from our option appraisal financial model.

In the scoping stage, we will first take a look at stating the purpose of the model. The purpose of the model here is to prepare forecasts of the power plant over its economic useful life. The logic and numbers prepared from this initial model build will be used for various transactions and illustrations later on in this book.

In terms of the key output schedules that are required, these would be the cash flow which is required on both a monthly and annual basis. There would need to be some key outputs shown which addresses the internal rate of return (IRR), net present value (NPV) and payback periods.

Sensitivities, that is, the ability to flex the companys assumptions and observe the impact upon the results in the base case, should be derived from the companys risk assessment process. The major business and financial risks should always be defined as sensitivity cases and the impact measured and mitigated accordingly.

The timescale that you have for your energy sector modelling project, given where you are, is critical given the size of the scope or type of resource required. For example, if time is tight you may want to limit the outputs of your model to a bare minimum and ensure that you use an experienced modeller on the project, who is able to close out the work efficiently.

Functionality refers to the need to have special facilities in the model over and above the basic calculations. In this particular case, we would require the ability to switch between technology options and observe the results.

At the specification stage, it is advisable to prepare a document that considers the purpose of the model, key outputs, material calculations and assumptions as highlighted in the scoping stage above. An example of a template that could be completed in order to scope and specify the financial model is shown in Illustration 6.

Moving on to the design stage, it is often important to consider whether Microsoft Excel is the best platform for this modelling and given the nature of energy sector projects the answer to this point is almost always a yes with 99.9% certainty.

Consider how many Excel workbooks are required. Given our knowledge and experience of energy sector financial modelling, normally a single Excel workbook will suffice. However, a very important consideration is the models structure and layout. We prefer to adopt a modular approach reflecting the sheet names which are labelled with common sense names.

From experience, we have often witnessed financial staff and modellers jump straight into the build stage and indeed many best practice methodologies ignore the other processes or stages associated with FMBP outlined in this book.


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Illustration 6Specification template

Specification V1The Financial Model for The Project XXXXXXXX Forecasting Purposes

Contents

Objective of the Model Page xxUsers of the Model Page xxOutput Schedules Required Page xxMaterial Calculations Page xxInput Data Page xxFunctionality Required Page xxAppendices Page xx

Continued

However, once you are at your keyboard with your copy of Microsoft Excel, we recom-mend that the following simple concepts are adopted. The first principle is to keep a clear separation of inputs, calculations and outputs. More simply put, try to design the model so that it reads like a book from left to right. Where you cannot avoid including calculations with your inputs, please ensure that you protect the calculation cells appropriately. The second principle is to only use one unique formula per row. Exactly what this means is the logic placed in the first column should be copied across all columns of a timeline. This makes it both easier for you and others to review your formulae. Third, in order to ensure logical accuracy along the way, we recommend as many cross checks and audit checks as possible are placed in the model. Some obvious ones are balance sheets balancing, cash flows equalling the movement in the balance sheet, and net profits equalling the movement in the balance sheet retained earnings, amongst many others that could be cited. Our final point is to try to keep your formula as simple as possible and your labels as clear as possible. However, it is also recognised that it is often difficult to have very simplistic formulae when a financial model builder is trying to gain flexibility in respect of the calculations and assumptions in the financial model. Again, we recommend that a balanced approach is adopted.

Documentation refers to the need to produce user and technical documentation, and a data book, which is more fully discussed in Finalising the existing option appraisal financial model.

Testing and the use of the model will also be more fully discussed in Self testing the financial model.

Our further recommendations are that both version and change control logs are kept in your model. First, ensure that each model version has a sequentially numbered suffix at the end of the excel filename (for example, financialmodelV1.xlsx) and, where timing permits, log the differences between each model version in the models version control sheet, please see Illustration 7. Second, you can use the models change request log for changes requested or work outstanding and their status, please see Illustration 8.


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1 Objective of the ModelThe model is required in order to calculate the cash flow forecasts (both on a monthly and yearly basis) and its associated key outputs, that is, NPV, IRR and payback over the economic useful life of each plant technology option.

Cash flow ; Key outputs NPVs, IRRs and paybacks.

Appendix A shows the outputs outlined above.

2 Users of the ModelThe model will be owned and used by xxxxxxxx and his team.

The model will be made available to .

3 Output Schedules RequiredThe output schedule formats are outlined in Appendix A.

4 Material Calculations

(i) Plant operating characteristics, that is, Generated kWhs, capacity factor. (ii) Tariff mechanism.(iii) Fuel costs.(iv) Operating and maintenance costs.(v) Construction Costs.

5 Input DataThe inputs are as required to be derived from the models outputs and calculations and MS will define these.

More specifically .

6 Functionality RequiredThe ability to switch between plant technology options and observe the results.

Any other areas.

Appendix AOutput Schedules

Cash flow format. Attach specimen Outputs.

Key output summary. Attach specimen Outputs.

Appendix BInput schedulesThe inputs are as required from the models outputs and calculations, and the financial modeller will define these where they have not been outlined.

Source: Authors own

Illustration 6 continued


17

Illustration 7

Version control

Number Filename Date Changes/comments Modellersname

1

2

3

4

5

6

7

Source: Authors own

Illustration 8

Change control

Number Filename Date Changerequest Modellersname

1

2

3

4

5

6

7

Source: Authors own


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We will now go through the process of an option appraisal financial model. The approach that is taken is step by step referring to Excel financial model extracts. During our step by step approach to building the financial model we will often use Excel Visual Basic for Applications (VBA) logic or macros, it is important to note that the basics regarding Excel VBA and macros are considered beyond the scope of this book and reference should be made to appropriate text or training in this rather detailed area. Of course, readers with limited Excel VBA knowledge will find this preparation a pre-requisite for understanding some of the more advanced techniques used, and essential for our financial modelling and analysis requirements.

Scope

Obviously, given the discussions regarding FMBP outlined above, our starting point for the purposes of this book is to define the scope of our energy sector financial model build project.

First, we need an option appraisal financial model that is capable of computing cash flow forecasts both monthly and annually over the life of a number of power plant technologies.

Second, we require IRRs, NPVs and paybacks to be calculated for each option. Third, we require a well-designed and laid out financial model that can be adjusted and

updated for the potential energy sector options outlined in the course of this book.

Designing the financial model

Again, given the discussions regarding FMBP outlined above our next stage is to define the design for our energy sector financial model.

It is obvious to us that our financial model can and will be built in Excel. Any version from Excel 2007 onwards will be suitable for our requirements. One workbook is all that is required and we will design our model on a modular basis breaking down the key areas of the logic.

Layout

The next stage is to define the structure of the power generation model in Excel, starting with the outputs and working back to the required inputs. This enables us to complete the logic, define the inputs and collect them.

The example outlined in Illustration 9 (see Illustration9.xlsx) shows a layout of the financial model which will allow us to complete the build.

The financial model layout includes administration sheets at the front, followed by yellow sheets for inputs, the intermediate calculations sheets are in green, and the output sheets are in blue. The colour scheme adopted visually presents us with an increase of colour shading from left to right in the form of white, yellow, green and blue. This is a standardised model layout that we adopt for all financial model build projects. You will notice that the sheets are organised on a modular basis given the scope and purpose of the financial model. The sheet names are clear and fairly self-explanatory. Where there is an exception to this rule, please refer to the model layout listing in Illustration 10, which explains the purpose of each


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sheet. Essentially, the input and calculations are in worksheets where you would logically expect to find them. You will notice that the output schedules are already included, as at this stage in the financial model build project it is quite standard to have agreed these with the end client. We have included a format for the Cash flow, Summary and the Check sheets.

Illustration 10

Layout

Worksheet Description

Cover This represents the cover with the disclaimer

Version control This is the version control sheet

Change control This is the change control sheet

User and technical guide This is the guide on how to run the model and how to technically update it

Assumptions This is where the plant assumptions are entered

Monthly calculations This is where all the monthly calculations are made

Annual corporation tax This is where the annual corporation tax calculation is made

Monthly cash flow These are the monthly cash flows

Annual cash flow These are the annual cash flows

Summary This is the summary of the outputs

Source: Authors own

When you cross reference the text above to Illustration 10 it is plain to see that the names used in our layout appear to be relatively self-explanatory and straightforward. This is what one would expect to find from undertaking such an approach.

Layoutexercise

You are now ready to start to build your power generation option appraisal financial model in your copy of Excel. Please prepare the model layout by using the same sheet layout and output schedules as used in the example.

Timeline

We will now compute the timeline for the option appraisal financial model. We will now go through the logic of this module with reference to Illustration 11 (see Illustration11.xlsx).


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The timeline is added to the layout. The timeline is driven by the project start date assumption in the Assumption sheet. The option selected is triggered from cell AI9 of the Assumption sheet.

In the Monthly calculations sheet, row 4 calculates the monthly timeline over 50 years.In cell C4, the logic states that if the cell is blank then use the first date, otherwise use

the EOMONTH by accessing the previous months date and incrementing it by 1.The timeline is referenced in row 4 of the Monthly cash flow sheet.The Annual cash flow sheet has project year logic in row 5. The logic states where the

previous cell is a blank place a 1 otherwise increment by 1.

Timelineexercise

In the financial model that you have built to date, please add the following logic to compute the logic for the models timeline. Use the EOMONTH formula to automate the yearly timeline for the green calculation modules and the blue calculation modules.

Monthly calculations

We will now discuss the logic for building the Monthly calculations module as appropriate. Illustration 12 (see Ilustration12.xlsx) shows the logic behind the monthly calculation module.

Each technology option should be set up in the Assumption sheet with all the neces-sary inputs.

There will be the ability to select the specific technology option to be run. The mecha-nism for undertaking the option switch is via cell B4. This represents a dropdown box that allows the selection of numbers 1 to 11.

For the readers who are unfamiliar with the process of setting up dropdowns in Excel, we shall outline this here. Select the Data ribbon, select Data Validation then Allow List and in the source select the range of labels required and select ok.

The relevant technology option assumptions are selected in column AI which is used to perform the calculations in the Monthly calculation sheet. Similar logic is chosen in each of the cells used to make the calculations in columns AH to AJ.

Excels CHOOSE function is used in order to select the assumption based upon the technology option selected in cell B4.

In row 7, the monthly capital expenditure or construction cash flow is linked by refer-encing the timeline to the Assumptions sheet.

In row 8, the inflation index is applied (note that this is not necessary if a fixed price turnkey or engineering and procurement cost (EPC) quote is provided.) This is calculated by referencing the previous index multiplied by the annual capital expenditure assumption at the power of a twelfth.

The construction cash flow is calculated by multiplying the construction by the inflation index.

In row 10, the capital allowance type is selected by reference to the timeline.Row 12 shows the operations flag. This is used to indicate when the operation of the

power plant starts and ends over its economic life, given when the construction is completed.


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The logic states that if the Month Ending is greater than or equal to the first month of operations and less than or equal to the last month of operations a 1 is inserted, otherwise a zero is inserted.

Turning our attention to the generation side, the megawatt (mW) installed for the specific power plants technology can be seen in row 16. This is activated by the operations flag appropriately.

Next, in row 17, the maximum available hours are calculated. This is calculated by the number of days in the month at 24 hours per day activated by the operations flag appropriately. The maximum capacity in kWhs are calculated by taking the mW and multiplying these by 1,000 (that is, the factor between kW and mW) and multiplying this by the maximum kWhs.

Next the plant unavailability is calculated over the forecast period.Forced outages represent the chance of a breakdown which is uncontrolled. This can

be seen in row 21.The unavailable percentage is a factor whereby the plant is unable to generate electricity,

for example, due to no or limited sunrays being available during winter months for solar parks. Planned outage for minor maintenance routines represents the percentage factor

whereby the plant is unable to generate electricity due to planned maintenance programs. The minor maintenance logic is calculated by scheduling the month of the year that the outage occurs.

Planned outages for major maintenance routines represent the percentage factor whereby the plant is unable to generate electricity due to major planned maintenance programs. The major maintenance logic is calculated by scheduling the month of the yearly cycle that the outage occurs.

Range B27 to B46 calculates the yearly interval dates for each major maintenance. Each row schedules a 1 for the date the outage hours are phased into the timeline in row 49.

The total percentage plant unavailability is calculated in row 53, that is, the sum of the forced outages, unavailable capacity and the planned outages.

The important statistic of the plant capacity factor percentage is calculated in row 54 and represents 1 less the percentage of Total plant unavailability.

The generated kWhs are calculated in row 46. This represents the mW installed, multi-plied by the maximum available hours, multiplied by 1,000 in order to reflect the factor between kWs and mWs.

Variable O&M costs are calculated by multiplying the megawatt-hour (mWh) and infla-tion. The product of this calculation is divided by 1,000 in order to calculate the amount in pounds.

Fixed O&M costs are calculated by taking the amount per kW per annum in pounds. This calculation is divided by 1,000 in order to calculate the amount in pounds.

Fuel is calculated by taking the purchased price per tonne in pounds and multiplying by 100 to convert this to pence. This amount is divided by the following: the calorific value is multiplied by 1,000 and multiplied by megajoules (mJ) / kWh. In order to derive the purchased cost in pence per kWh, the number calculated just prior is divided by the efficiency factor in order to calculate fuel cost pence per kWh generated.

In order to calculate the fuel cost, the fuel cost in pounds generated is multiplied by the kWh generated at the fuel price inflation.


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Financial incentives are awarded by the UK government for renewable energy projects. So where applicable, the following incentives will be awarded.

The Renewable Obligations Certificate (ROC Incentive) will be applied on a buyout price per mWh. The ROC buyout price is divided by 1,000 in order to reflect the multiple between mW and kW. Indexation is applied and the total is divided by 1,000 in order to calculate the amount in pounds.

The Levy Exemption Certificate (LEC Incentive) will be applied on an mWh basis.The LEC price is divided by 1,000 in order to reflect the multiple between mW and kW.

Indexation is applied and the total is divided by 1,000 in order to calculate the amount in pounds.The tariff is calculated in rows 96 to 102. There are essentially two parts to the tariff,

that is, an energy charge expressed in pence per kWh and a standing charge expressed in pounds per kW per annum (although the latter is not used on this occasion).

The energy charge calculated in row 100 takes the kWhs and multiplies this by the energy charge which is divided by 100 to derive pounds. Inflation is applied and the total derived is divided by 1,000 in order to calculate the totals in pounds.

The standing charge in row 101 is calculated by dividing the charge by 12 to reflect the monthly charge. The mWs are multiplied by 1,000 in order to reflect the difference in the kW to mW multiple, inflation is applied and the sum is divided by 1,000.

The total tariff receipt in pounds is a total of the energy and standing charges.The capital allowance monthly proportions are calculated in rows 105 to 117. The

capital allowance label is referenced in rows 105 to 107.Rows 110 to 112, calculate the frequency of times that the capital allowance arises

during the financial year. Rows 115 to 117 calculate the percentage phasing per month.

Monthlycalculationsexercise

Based upon the financial model built to date, please ensure that you refer to the example provided for further guidance. Please complete the monthly construction cash flows, incor-porate the logic to calculate the kWhs generated, the fuel cost, O&M costs and the relevant financial incentives that relate to renewable projects.

Monthly cash flow

We will now discuss the logic for building the Monthly cash flow module as appropriate. Illustration 13 (see Illustration13.xlsx) shows the logic behind the monthly cash flow module. You will see that the month ending in row 4 is referenced from the monthly calculations sheet. Essentially, upon the anniversary of the projects start date month an increment of 1 is added. Each of the cash flows in rows 9 to 17 are referenced from the monthly cash flow sheet, with the exception of the corporation tax which is referenced from the specific sheet.

The net cash flow is simply the difference between the total receipts and the total payments. In row 22, the cumulative cash flow is calculated in order to derive the break-even point.

In row 23, the payback date is identified. This is indicated by a flag where the previous month is negative and the current months cumulative cash flow is equal to or greater than zero.


23

In cell B25, the payback date is referenced. This is by using Excels nested INDEX MATCH functionality. The timeline is indexed and matched to where the payback date label occurs.

The payback months are simply calculated in cell B26. The IRR is calculated on a monthly basis by using Excels XIRR function.

The NPV is calculated on a monthly basis by using Excels XNPV function.

Monthlycashflowexercise

Based upon the financial model built to date, add the monthly cash flows as in the format of your work in progress model, ensuring that you can report the payback date, payback months and the IRR and NPV outputs.

Annual corporation tax

We will now discuss the logic for building the Annual Corporation Tax module as appropriate. Illustration 14 (see Illustration14.xlsx) shows the logic behind the monthly cash flow module.

In row 7, the corporation tax payment date is added. This represents the use of the EOMONTH formula by adding a number of months to the year ending date.

In rows 9 to 15, the tax loss memorandum is calculated. This allows any unused tax losses to be carried forward and offset against future taxable profits.

The opening balance is simply the previous years closing balance. Where a tax loss arises in a given year this is added to the memorandum balance. The opening balance plus the tax loss relieved against the current taxable year is reduced from the balance accordingly.

Row 17 shows the capital expenditure added from the monthly cash flows on an annual basis.

In rows 19 to 28, the capital expenditure type is allocated.In rows 30 to 58, the capital allowances are calculated for each category.The corporation tax computation is calculated by taking the tariff receipts less the fuel

and O&M costs making any adjustment for depreciation and disallowables, which in this case will always be equal to zero.

The taxable profits are derived from the above and the capital allowances are deducted, and any tax losses relieved given the tax memorandum position. The profits chargeable to corporation tax are multiplied by the corporation tax rate to calculate the corporation tax liability.

Row 74 shows the monthly cash flow for the payment of the corporation tax. This is calculated by referencing the corporation tax payment date in row 7 and the corporation tax liability in row 71 by use of Excels SUMIF function.

Annualcorporationtaxexercise

Based upon the financial model built to date, please add the annual corporation tax logic. More specifically, please add the tax loss memorandum, the capital allowance computations, the corporation tax liability and the corporation tax paid logic.


24

Annual cash flow

We will now discuss the logic for building the Annual cash flow module as appropriate. Illustration 15 (see Illustration15.xlsx) shows the logic behind the working capital calculation.

The project year in row 5 increments by 1 up until the end of year 50.The total receipts and payments detailed lines are all referenced from the monthly cash

flow sheet by summarising into years by the use of SUMIF and the project year indicator used in row 5. Checks are added to column B to ensure that the annual equals to the monthly for each line detailed in the annual cash flow.

In rows 25 to 30, each detailed cash flow has calculated pence per kWh. This is simply the cash flow for the year multiplied by 1,000 to convert to pence. This is divided by the number of kWhs. This is very useful for sense checks.

In rows 33 to 39, each detailed cash flow has a calculated pound per mWh. This is simply the relevant cash flow multiplied by 1,000 to derive pounds. This is divided by the number of mWhs, that is, the kWhs divided by 1,000, in order to reflect the conversion to mWhs. This is very useful for sense checks.

Annualcashflowexercise

Based upon the financial model built to date, please add the annual cash flows together with cross checks reconciling to the annual cash flows. (Note, with the exception of the capital expenditure and corporation tax.) Please add the pence per kWh and pound per Annual cash flow exercise mWh outputs to each of these.

Summary

We will now discuss the logic for building the Summary module as appropriate.The summary sheet simply comprises the key results for the case, that is, IRR, NPV,

payback and capacity factor.

Summaryexercise

For your financial model built to date, please add the key output measures together with a graph of the cumulative annual net cash flows.

Finalising the existing option appraisal financial model

During the course of our option appraisal financial model build stage we have built a number of specific modules.

However, there are a number of processes and menu designs that ideally will make your financial model easier to update and more secure. These points are more useful if the model that you are building is a template or re-useable energy sector model. These are the protection of the worksheets and workbook as appropriate.

First, we shall consider the automation of running the model.


25

We recommend that the workbook is appropriately protected. In terms of appropriate protection, we recommend that only the yellow input cells can be updated, the worksheets and the workbook is protected. This will prevent any corruption to the model. The Excel VBA code shown in Illustration 16 can be used to serve this purpose.

Once you have built a re-usable financial model such as this, it is good practice to protect it accordingly. The starting point would be to ensure that all yellow input cells are unprotected as appropriate. This could be done by manual means but is often more error prone. We recommend the use of similar VBA logic as outlined in Illustration 16. The important part of the code for doing this is where the code starts with For Each Sheet In Activeworkbook.Sheets and ends with Next Sheet. Here, the code is going through each sheet in the workbook and each cell in the sheet, if the cells colour index is 6 (yellow), the cell is unlocked.

Illustration 16

Unprotecting the yellow input cells in the energy sector model

Sub UnProtectEachYellowInputCell()

==================================================UNPROTECTS EACH YELLOW INPUT CELL IN THE MODELUSEFUL FOR USER PROTECTION OF CALCSAND UNPROTECTION OF INPUT CELLSwww.modellingsolutions.co.uk==================================================

Application.ScreenUpdating = FalseDim Sheet As WorksheetDim Cell As Range

On Error Resume NextUnProtectEachSheet For Each Sheet In ActiveWorkbook.SheetsSheet.Select

For Each Cell In ActiveSheet.UsedRange.CellsApplication.ScreenUpdating = FalseCell.Select

Continued


26

If Cell is yellow then unprotectIf Selection.Interior.ColorIndex = 6 ThenSelection.Locked = False

ElseEnd If

Next CellApplication.StatusBar = Now Working On Sheet : & ActiveSheet.NameNext Sheet

ProtectEachSheetApplication.ScreenUpdating = TrueApplication.StatusBar = Ready

End Sub

Source: Authors own

After unprotecting the specific cells, we recommend protecting the workbook and sheets accordingly. Again, this can be done manually, but if this has to be done a number of times it is better if it is automated. We will turn our attention to Illustration 17. In the subroutine ProtectEachSheet we can see the workbook being protected by the use of Activeworkbook.protect (Password). Each sheet in the financial model is protected by the use of the code embedded in the For Each Sheet In Activeworkbook.Sheets and ending with Next Sheet. The subroutine UnprotectEachSheet uses similar logic as the protection routine above except the use of unprotect is for both the worksheet and workbooks.


Illustration 17

Workbook and worksheet protection

Sub ProtectEachSheet()Application.ScreenUpdating = False

Dim Sheet As WorksheetOn Error Resume NextActiveWorkbook.Protect (xxxxxxx ) For Each Sheet In ActiveWorkbook.SheetsSheet.SelectSheet.Protect (xxxxxxx)

Next SheetApplication.ScreenUpdating = TrueEnd Sub

Sub UnProtectEachSheet()Application.ScreenUpdating = FalseDim Sheet As WorksheetOn Error Resume NextActiveWorkbook.Protect (xxxxxxx) For Each Sheet In ActiveWorkbook.SheetsSheet.SelectSheet.Unprotect (xxxxxxx )

Next SheetApplication.ScreenUpdating = TrueEnd Sub

Source: Authors own


28

Exercisefinalisingtheexistingoptionappraisalfinancialmodel

Based upon the energy sector model that you have built to date, please add the final touches. Unprotect the entire financial models input cells, protect all the worksheets.

Sources of error

Given our discussions outlined in this book and the nature of energy sector financial models there are several potential sources of errors. These can be summarised as follows.

Logic error: a logic error arises due to a calculation error in the formula, that is, summing the wrong range and so on.

Assumption/input error: if an input assumption is not as it is in the financial case then an error occurs, for example, the discount rate should be 12% not 10%.

Documentation error: the debt repayment profile may not comply with the basis outlined in the relevant legal documentation.

Data book error: the debt repayment profile may not comply with the basis outlined in the data book.

Taxation compliance: if the tax treatment for a certain expense is not tax deductible and is subtracted from the taxable profit then we have a tax compliance issue of a sort.

Accounting compliance: if a certain item has been capitalised but under the relevant accounting treatment, that is, UK GAAP, IFRS and so on, immediate write off is required then we have an accounting compliance issue of a sort.

Self testing the financial model

Once the model builder has completed a draft model they should stand back and undertake some self review. We recommend that the minimum amount of self review or self testing should include the following methods.

Toplevelanalyticalreview

This technique involves reviewing the big picture. It is good for detecting potentially large errors for one model run for the base case or specific sensitivity cases. This is a similar technique to the review of financial statements in a financial audit. The approach may involve the computation of key ratios over the forecast period: look at revenue, cost and financing structures. Where possible you should correlate back to the inputs. Some examples of correlating the inputs with the outputs would be trade debtor assumptions, trade creditor assumptions, interest rate assumptions and any other assumptions in the model that you could relate to the models outputs.

Key areas can be graphed. This helps to review the trends and highlights any blips. You should look for any obvious irregularities such as balance sheets not balancing, cash flows for the period not equalling the movement in cash balance for the balance sheet, any nega-tive debt balances and any other basic checks.


29

We can now turn our attention to a specific example of analytical review techniques applied to our energy sector model in Illustration 18 (see Illustration18.xlsx) and in Illustration 19.

Illustration 19

Analytical Review

Doesconstructioncashflowequalstartandenddates? Yes. See comments: the annual cash flow

Doestheoperatingperiodequaltheeconomicusefullife? Yes. See comments: the annual cash flow

Dotheoperatingcashflowsequaltheoperatingusefullife? Yes. See comments: the annual cash flow

DotheamountsperkWhseemreasonable? Yes. See comments: the annual cash flow

Source: Authors own

You can see that we have created a sheet called Analytical review. The Annual cash flow and the Assumptions have been brought together in this electronic working paper in order to perform an analytical review of the cash flow projections.

Note that, obviously, for this financial modelling project there is only a cash flow, so the profit and loss and balance sheet review is not required as in the paragraph above.

If we turn our attention to Illustration 18, we can see various comments added to both the assumptions and cash flow outputs that confirm the check list in Illustration 19.

So from our analytical review we can confirm the following:

the construction cash flow equals the start and end dates; the operating period equals the economic useful life; the operating cash flows are equal to the economic useful life; and the amounts per kWh seem reasonable.

We can now turn our attention to a specific example of analytical review techniques using graphing which is applied to our energy sector model in Illustration 20 (see Illustration20.xlsx).

When looking at the sheet in the example called Graphing, we can see that we are undertaking a review method that will ultimately end in a graphing. We are looking at the operating cost per kWh in the cash flow for each year. The fuel and O&M costs are in line with the starting assumptions. Furthermore, we can also confirm that the growth assump-tions and the outputs correlate with the assumptions as in columns BA and BB. Looking at the graph, the dividend does not exceed the cash available thus, ringing no alarm bells.


30

Keyoutputreview

The key outputs metrics, such as IRRs, NPVs, paybacks and so on, are likely to produce material errors where an error exists, as they are at the highest level. It is recommended that the results and the logic behind the key outputs are reviewed appropriately.

We can now turn our attention to a specific example of key output review techniques applied to our energy sector model in Illustration 21 (see Illustration21.xlsx).

Illustration 22 is a run from the Operis Analysis Kit audit tool that has printed out all the distinct formula which derive or calculate the key output metrics. As these key outputs are a typical key risk it is advisable to use the output to check the logical integrity of each cell reported. In terms of logical integrity, you need to ensure that the calculation is doing what you would reasonably expect it to. For example, the NPV calculation discounts the correct range and uses the correct discount rate so that the correct output is achieved.

Illustration 22

Key output review

Distinct formulae listing: OptionAppraisalModelVersion7.xlsxReport generated: Saturday, 17 August 2013 3:08:03 PMWorksheet Address FormulaMonthly Cash flow $A$1 =IF(Project_Title=,,Project_Title)Monthly Cash flow $A$2 =Assumptions!AJ6Monthly Cash flow $C$4 =Monthly Calculations!C4Monthly Cash flow $C$5 =IF(B5=,1,IF(MONTH(C4)=MONTH(Assumptions!$AI$9

),B5+1,+B5))Monthly Cash flow $C$6 =Monthly Calculations!C18Monthly Cash flow $C$7 =Monthly Calculations!C56Monthly Cash flow $C$9 =Monthly Calculations!C102Monthly Cash flow $C$10 =Monthly Calculations!C87Monthly Cash flow $C$11 =Monthly Calculations!C92Monthly Cash flow $C$12 =SUM(C9:C11)Monthly Cash flow $B$14 =SUM(Monthly Calculations!C62:WD62)+SUM(C14

:WD14)Monthly Cash flow $C$14 =-Monthly Calculations!C62Monthly Cash flow $B$15 =SUM(Monthly Calculations!C68:WD68)+SUM(C15

:WD15)Monthly Cash flow $C$15 =-Monthly Calculations!C68Monthly Cash flow $B$16 =SUM(Monthly Calculations!C80:WD80)+SUM(C16

:WD16)Monthly Cash flow $C$16 =-Monthly Calculations!C80

Continued


31

Worksheet Address FormulaMonthly Cash flow $B$17 =SUM(Monthly Calculations!C9:WD9)+SUM(C17:WD1

7)Monthly Cash flow $C$17 =-Monthly Calculations!C9Monthly Cash flow $B$18 =SUM(Annual Corporation

Tax!C74:WD74)+SUM(C18:WD18)Monthly Cash flow $C$18 =-Annual Corporation Tax!C74Monthly Cash flow $C$19 =SUM(C14:C18)Monthly Cash flow $C$21 =C12+SUM(C14:C18)Monthly Cash flow $C$22 =SUM($C$21:C21)Monthly Cash flow $C$23 =IF(AND(B220),Payback Date,)Monthly Cash flow $B$25 =INDEX($C$4:$WD$4,MATCH(A25,$C$23:$WD$23,0))Monthly Cash flow $B$26 =(B25+1-Assumptions!AI9)/30Monthly Cash flow $B$27 =XIRR($C$21:$WD$21,$C$4:$WD$4,WACC)Monthly Cash flow $B$28 =XNPV(WACC,$C$21:$WD$21,$C$4:$WD$4)

Source: Operis Analysis Kit

Flexandsensitivityreview

Flex testing is a valuable technique for finding potentially large errors in a model. It involves the variation of inputs and the observation of the effect on the outputs. It is important to concentrate on key risk areas.

A sensitivity can be reviewed by changing inputs required for the designated sensitivity case and reviewing the results. However, it is better to use a sensitivity comparison to the base case, that is, tracking changes between the outputs and assessing whether the model changes in areas as expected. Both flex testing and sensitivity review should use this approach and should collaborate each sensitivity with a high level analytical review. The final part would be to rank each result in order and assess the relative ranking given your knowledge of the case.

Exerciseselftestingthefinancialmodel

Based upon the power generation appraisal financial model that you have built to date, please undertake a self testing and review approach. More specifically, please undertake an analytical review of the cash flow forecasts, review the key outputs metrics and flex the key input assumptions using the flex testing approach. After you have undertaken your self testing or review of the financial model that you have built please make any necessary corrections.

Using the model

From the financial model that you have built you have the capability to evaluate the attrac-tiveness and risks of various power generation technology options.


32

Disclaimers

It is highly recommended that given the multiple sources that can give rise to errors in financial models of this nature, liability needs to be waived appropriately. The disclaimer below outlines a typical disclaimer that should always be placed in a financial model before it is distributed.

Disclaimer

This model has been prepared by Authors Own Limited (AO) from data provided by various parties. It has not been audited and recipients should use their own due diligence. No representation, warranty or undertaking (expressed or implied) is made in relation to it. No responsibility is taken or accepted by AO for the accuracy of the model or the assumptions on which it is based and all liability therefore is expressly excluded.

33

Section 5

Power generation projects

During this section of the book we shall undertake financial option appraisals of a number of plant generation options.

It is important to note that the figures or the Excel example logic used in this book do not represent any past, current or indeed future energy sector transactions or projects of any kind. The numbers and results contained herein are purely fictional.

For each technology option we have outlined the plant operating assumptions. Here, the installed megawatt (mW) is outlined and the project start date is detailed. The unavailable operating hours are outlined in detail, that is, the percentage of forced outages, the unavail-able percentage, together with the specific planned maintenance programs for the technology. The plants economic useful life is shown. The construction program over the months is also shown together with pounds per kilowatt (kW).

The fuel assumptions, variable operating and maintenance (O&M) costs and fixed O&M costs are detailed for each plant option.

The corporation tax assumptions are shown, that is, the rate and the month of payment. The capital allowance rates are shown.

The key project dates detailing the first month of operation, the final month of operation, the final month of construction and the number of months of construction is also shown.

The electricity tariff is detailed, that is, both the pence per kWh and the tariff basis.The financial incentives that relate to renewable energy projects, that is, Renewable

Obligation Certificates and Levy Exemption Certificates are also outlined.The weighted average cost of capital (WACC) is also shown. The general inflation applied

to each cash flow stream is also outlined.

Natural gas combined cycle gas turbine

This is a combination of a gas fired turbine and a steam turbine. A natural gas combined cycle gas turbine (CCGT) is often a very efficient combination. The technology is shown in Illustration 23.

Modern power station construction has moved towards natural gas and away from coal and oil fuelled stations. CCGTs achieved much better thermal efficiencies than coal or oil equivalents. The emissions of a natural gas CCGT are much lower than coal or oil fired equivalents. The technology produces almost no sulphur dioxide, carbon dioxide levels are halved and nitrogen dioxide levels are at a quarter.

The top part of the diagram in Illustration 23 shows a gas turbine generator, which is similar to an aircraft engine, linked to generators that produce electricity. The hot exhaust gases from the gas turbine are passed through the heat recovery boiler to produce steam from the steam turbine generators that produce electricity.


34

Based upon the specific assumptions made regarding the natural gas CCGT option we achieve a payback date of November 2019. This equates to 67 months. An internal rate of return (IRR) of 23.0% and a net present value (NPV) of 151,293,000 is forecasted.

Illustration 23

Natural gas combined cycle gas turbine

Source: Authors own

Illustration 24

Natural gas CCGT option appraisal

Technologyoption NaturalgasCCGT

Plantassumptions

Project start date May 2014

mW installed 200

Maximum available hours 8,760

Percentage forced outages per annum 10.0

Unavailable capacity % 7.0

Plannedoutages(minormaintenance)

Month 7

Outage hours 45

Plannedoutages(majormaintenance)

Every number of years 5

Outage hours 245

Economic useful life (years) 45

Capitalexpenditure

Date Expenditure000s Capitalallowance

May 2014 12,000 Plant and machinery

June 2014 13,000 Plant and machinery

July 2014 13,000 Plant and machinery

August 2014 13,000 Plant and machinery

September 2014 10,000 Plant and machinery

October 2014 13,000 Plant and machinery

November 2014 13,499 Plant and machinery

December 2014 13,000 Plant and machinery





January 2016 8,201 Plant and machinery

Total 160,000

Capital expenditure inflation per annum 82.0%

per kW .800%

Continued

Fuelcosts

Fuel purchased at per tonne 192

Calorific value gJ per tonne 54

1 mJ = kWh 0.2778

Fuel price inflation 2.5%

Efficiency 26.9%

Variableoperationsandmaintenance(O&M)

Variable O&M mWh 7.6

FixedO&M

Fixed O&M 000s per annum 10,943.5

Taxation

Corporation tax rate (%) 23.0

Payment months in arrears 9

Capitalallowances

Type Rate(%) Basis

Plant and machinery 25.0 Straight line

Industrial buildings 0.0 Reducing balance

Long life assets plant and machinery 4.0 Straight line

0 0.0 0

Keyprojectdates

First month of operations February 2016

Final month of operations January 2061

Final month of construction January 2016

Months of construction .21%

Tariff

Energy charge pence per kWh 9.0%

Standing charge s per kW annum 0 .0%

Tariff inflation 2.50%

Financialincentives

Applicable?

ROC buyout price mWh 0.00% No

ROC inflation per annum 0.00%

LEC price mWh 0.00% No

LEC inflation per annum 0.00%

Discountrate

WACC 12.50%

Generalinflationrate

General inflation per annum 2.50%


Continued


37

Results NaturalgasCCGT

Payback November 2019

Payback months 67

IRR 23.0%

NPV 000s 151,293

Source: Authors own

Coal fired

The coal fired technology is shown in Illustration 25. The power plant works by coal being ground to a fine powder in a mill. The fuel is mixed with preheated air. This mixture is forced into a boiler where it ignites. Water flows up the walls of the boiler where it turns into steam. The steam is sent to the high pressure turbine which generates electrical energy that is sent to the grid. The waste is sent through the chimney stack and the ash through the ash systems.

Based upon the specific assumptions made regarding the coal fired option we achieve a payback date of November 2020. This equates to 79 months. An IRR of 19.3% and an NPV of 112,377,000 is forecasted.

Illustration 25

Coal fired plant

Source: Authors own

Illustration 26

Coal fired option appraisal

Technologyoption Coalfired

Plantassumptions


mW installed 200





Month 6

Outage hours 20



Outage hours 200


Capitalexpenditure














January 2016 24,000 Plant and machinery

Total 193,799


per kW 969

Continued

Fuelcosts



1 mJ = kWh 0.2778


Efficiency 26.8%

VariableO&M


FixedO&M

Fixed O&M 000s per annum 11,269.4

Taxation



Capitalallowances

Type Rate(%) Basis

Plant & machinery 25.0 Straight line



0 0.0 0

Keyprojectdates

First month of operations February 2016

Final month of operations January 2061

Final month of construction January 2016

Months of construction 21

Tariff

Energy charge pence per kWh 9.0

Standing charge s per kW annum 0


Financialincentives

Applicable?

ROC buyout price mWh 0.00 No


LEC price mWh 0.00 No


Discountrate

WACC 12.50%




Continued


41

Results Coalfired


Payback months 79.2

IRR 19.3%

NPV 000s 112,377

Source: Authors own

Energy from waste

This technology is shown in Illustration 27. Energy from waste is the process whereby incin-eration of waste is used to produce electricity and or heat. The incineration process involves burning of waste that is used to boil water, which in turn provides steam for turbines to generate electrical energy.

There is a trend away from landfill towards incineration of waste that presents an opportunity for the energy sector. You may be thinking why is there a trend away from landfill methods for waste disposal? The answer to this lies in the fact that landfill methods of waste disposal are not good for the environment. Rotting food produces methane gas, which contributes towards global warning. Furthermore, waste such as packaging does not naturally biodegrade for hundreds of years. Such effects can be bad for both humans and wildlife close to the landfill site. Indeed, the UK government has penalised the use of landfill sites by imposing a per tonne landfill tax which has the effect of encouraging waste industry participants to invest in incineration as a more beneficial financial and environmental alterna-tive to landfill that also has the incremental benefit of energy from waste.

Producing energy from waste plants is required to meet strict emission standards. Based upon the specific assumptions made regarding the energy from waste option we

achieve a payback date of January 2020. This equates to 69 months. An IRR of 23% and an NPV of 166,460,000 is forecasted.

Illustration 27

Energy from waste plant

Source: Authors own

Illustration 28

Energy from waste option appraisal

Technologyoption Energyfromwaste

Plantassumptions


mW installed 50





Month 7

Outage hours 5



Outage hours 25


Continued

Capitalexpenditure













March 2016 3,500 Plant and machinery

April 2016 1,689 Plant and machinery


Total 161,379


Per kw 3,228

Fuelcosts



1 mJ = kWh 0.2778


Efficiency 50.0%

VariableO&M


FixedO&M

Fixed O&M 000 per annum 1,106.8

Taxation



Capitalallowances

Type Rate(%) Basis

Plant and machinery 25.0 Straight Line

Industrial buildings 0.0 Reducing Balance

Long life assets plant and machinery 4.0 Straight Line

0 0.0 0

Continued


44

Keyprojectdates

First month of operations June 2016

Final month of operations May 2046

Final month of construction May 2016


Tariff




Financialincentives

Applicable?

ROC buyout price mWh 42.02 Yes


LEC price mWh 4.56 Yes


Discountrate

WACC 12.50%



Results Energyfromwaste

Payback January 2020

Payback months 69.0

IRR 23.2%

NPV 000s 166,460

Source: Authors own

Solar thermal

This technology is shown in Illustration 29. Solar thermal technology is where solar thermal collectors are used to concentrate sunlight using mirrors or lenses which are generally used for electrical power production. Solar thermal technology is much more efficient than photo-voltaics (PV). The heat from the mirrors is passed through the tube with fluid that absorbs heat which is passed through a heat exchanger. The heat exchanger produces steam that drives the steam turbine and generates electricity that is sent to the grid.



45

Based upon the specific assumptions made regarding the solar thermal option we achieve a payback date of November 2018. This equates to 55 months. An IRR of 32% and an NPV of 694,546,000 is forecasted.

Illustration 29

Solar thermal plant

Source: Authors own

Illustration 30

Solar thermal option appraisal

Technologyoption Solarthermal

Plantassumptions


mW installed 150


Percentage forced outages per annum 8.0%

Unavailable capacity % 1.4%


Month 6

Outage hours 20



Outage hours 120


Capitalexpenditure













March 2016 30,150 Plant and machinery



Total 412,500


per kW 2,750

Continued

Fuelcosts



1 mJ = kWh 0.0000


Efficiency 0.0%

VariableO&M


FixedO&M


Taxation

Corporation tax rate % 23.0


Capitalallowances

Type Rate(%) Basis




0 0.0 0

Keyprojectdates

First month of operations June 2016




Tariff




Financialincentives

Applicable?





Discountrate

WACC 12.50%



Continued


48

Results Solarthermal


Payback months 54.8

IRR 32.3%

NPV 000s 694,546

Source: Authors own

Hydroelectricity

This technology is shown in Illustration 31. This is electricity generated by the force created by falling or flowing water. This is the most popular type of renewable energy used globally, mainly due to the low cost of electricity generation. It has a considerably low level of CO2.

The traditional type of technology is derived from the energy source from a dam using a water turbine and thus a generator. This technology involves a large pipe driving water to the turbine.

An alternative to the traditional hydroelectricity technology of dams is that of the run of the river. This is where the water that comes downstream is used for generation as it occurs. There is obviously an availability factor or variable that comes into play regarding the flow of the water used to generate electricity.

There is the ability to use pumped storage technology which moves water between reser-voirs. This is a form of energy storage used between peak and low demands. In the usual manner, the turbines use the energy to power the generator in order to send electricity to the grid.

Based upon the specific assumptions made regarding the hydroelecticity opion we achieve a payback date of March 2030. An IRR of 8.4% is forecasted and an NPV of 746,364,000 is forecasted.


Illustration 31

Hydroelectric plant

Source: Authors own

Illustration 32

Hydroelectricity option appraisal

Technologyoption Hydroelectricity

Plantassumptions


Mw installed 300





Month 4

Outage hours 20



Outage hours 120


Continued

Capitalexpenditure


May 2014 0, 110,000 Plant and machinery

June 2014 0, 109,900 Plant and machinery

July 2014 0, 109,800 Plant and machinery

August 2014 0, 109,700 Plant and machinery

September 2014 0, 109,600 Plant and machinery

October 2014 0, 109,500 Plant and machinery

November 2014 0, 109,400 Plant and machinery

December 2014 0, 109,300 Plant and machinery

May 2015 0, 109,200 Plant and machinery

July 2015 0, 109,100 Plant and machinery


March 2016 0, 108,900 Plant and machinery


October 2016 0, 108,700 Plant and machinery

May 2017 0,108,600 Plant and machinery





Total 1,800,000


per kW 6,000

Fuelcosts



1 mJ = kWh 0.0000


Efficiency 0.0%

VariableO&M


Fixed O&M


Taxation




Continued

Capitalallowances

Type Rate(%) Basis




0 0.0 0

Key project dates

First month of operations Jun 2021




Tariff

Energy charge pence per kwh 9.0

Standing charge s per kw annum 0


Financial incentives

Applicable?





Discount rate

WACC 12.50%



Results Hydroelectricity

Payback March 2030

Payback months 192.8

IRR 8.4%

NPV 000s 746,364

Source: Authors own


52

Tidal power

The technology is shown in Illustration 33. Wave energy is the provision of energy by ocean waves. The tides power is used to turn the turbines below the waves, which generates elec-tricity which is sent to the grid.

We shall now discuss wave energy and its use for large electricity grids. A number of wave energy converters can be used and connected by a sub-sea cable, which in turn would be connected to the national grid for distribution of electricity. It is important to note that wave energy has a very seasonal pattern of supply, obviously with a dip during the summer months as the wind intensity is usually expected to be lower.

Based upon the specific assumptions made regarding the tidal power option we achieve a payback date of November 2031.The equates to 213 months. An IRR of 9.6% and an NPV of 112,469,000 is forecasted. Clearly, some improvements need to be made here before we can take this option seriously.

Illustration 33

Tidal plant

Source: Authors own

Illustration 34

Tidal option appraisal

Technologyoption Tidalpower

Plantassumptions


Mw installed 200





Month 6

Outage hours 25



Outage hours 45


Capitalexpenditure
















Total 500,000


per kW 2,500

Continued

Fuelcosts



1 mJ = kWh 0.0000


Efficiency 0.0%

VariableO&M


FixedO&M


Taxation



Capitalallowances

Type Rate(%) Basis

Plant and machinery 25.0 Straight line



0 0.0 0

Keyprojectdates

First month of operations May 2024

Final month of operations April 2074

Final month of construction April 2024


Tariff




Financialincentives

Applicable?





Discountrate

WACC 12.50%

General inflation rate



Continued


55

Results Tidalpower


Payback months 213.1

IRR 9.6%

NPV 000s 112,469

Source: Authors own

Geothermal

This is a source of energy which

Power Generation Financial Modelling and Analysis a Practical Guide

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