RETScreen - Introduction - Speaker's notes
SLIDE 1: Overview of RETScreen 4
RETScreen 4, a major new edition of the RETScreen software, helps rapidly evaluate whether a proposed clean energy project makes sense and is worth further consideration. This presentation introduces RETScreen 4, highlights its new features, and describes the RETScreen approach to project analysis.
SLIDE 2: New Features of RETScreen 4
RETScreen 4 improves on previous versions in six major ways:
First, RETScreen now goes beyond renewable energy and cogeneration, and deals with a wide range of energy efficiency measures. The efficiency project model can be used for new building design or energy audits in projects ranging from small houses to large industrial complexes. It can be used for residential, commercial and institutional buildings, both new and existing, as well as for industrial processes.
Second, RETScreen 4 includes more climate data, with a global climate database that has been expanded from 1000 to 4700 ground measurement stations. Furthermore, through its continued collaboration with NASA, RETScreen utilizes global climate data derived from 20 years of satellite observations. These NASA data, useful where there is no nearby ground station, are now integrated directly into the RETScreen software, so that the user no longer need copy data from the NASA website.
The third major development of RETScreen 4 is the integration of all the different project technologies into a single workbook. In previous versions, each different technology had its own independent workbook. Now renewable energy, cogeneration, and efficiency measures are all in the same tool.
Fourth, RETScreen 4 includes a project database of case studies and templates, to which users can add their own projects. Over 100 case studies, each with an assignment, solution, and description of the real world implementation of the project, are now available from within the software itself. The solutions are accessed from the project database and the assignment and real project description are in the help manual. The case studies are excellent aides for learning about clean energy technologies and how to use RETScreen. The project database also includes templates, or analyses pre-filled with typical values for a variety of common projects. Templates provide a reasonable starting point for the analysis, which the user can then rapidly refine.
A fifth significant improvement in RETScreen 4 is the ability to save an analysis in a compact ".ret" file. A .ret file is essentially a user-defined project database, with the data from one or more scenarios or projects. In previous versions of RETScreen, the entire Excel workbook was saved, resulting in files up to 10 MB in size. The new .ret files may be as small as 10 KB, making it easier to share analyses by e-mail. Furthermore, the .ret file decouples the project data from the underlying software, so that project data can be loaded into the most recent RETScreen upgrade without having to manually transfer data from an older version of the software.
Sixth, RETScreen handles many languages, collectively spoken by 2/3rds of the world's population. With a click of the mouse, the RETScreen interface can be switched from one language to another. Partners located around the world can use different languages in their RETScreen analyses but share the .ret files describing their project.
SLIDE 3: Project Analysis
The dark section of wall seen on this building is a solar air heating system. Perforations permit building ventilation air to be drawn in through the wall; sunlight warms the wall and the air around it, and this preheating reduces the fuel required to heat ventilation air.
When this project was proposed, it was unknown whether it would make sense. As in all clean energy projects, many things had to be considered, including:
First, the energy resource. Historical climate data for solar energy had to be obtained, and then the solar energy that would strike a south-facing vertical surface had to be estimated.
Second, the performance of the equipment. For the solar wall, the reduction in conventional heating fuel usage was calculated according to the solar absorptivity of the collectors, the airflow rate, and the demand for ventilation air heating.
Third, the initial project costs-that is, the cost of the solar collectors, additional fans and ducting, and equipment installation.
Fourth, base case credits. Recognizing that by doing the clean energy project, certain base case costs would be avoided, these costs were subtracted from the initial project costs to determine the incremental costs. For example, this solar air collector is a form of building cladding, so there was a base case credit equal to the cost for conventional cladding.
Fifth, annual and periodic costs. These included annual operation and maintenance costs as well as periodic costs, such as replacement of dampers every 10 years. Once again, the incremental costs were of interest, so that the solar wall was credited for any avoided annual or periodic costs associated with conventional cladding, beyond fuel savings.
Thus, even for a simple project, a number of considerations enter the analysis. RETScreen provides a framework for these considerations.
SLIDE 4: How RETScreen Fits into Project Analysis
The figure on this slide illustrates the findings of a retrospective study, conducted for the World Bank, of cost estimates for around 50 hydropower projects. Compared to the final as-built costs, cost estimates were accurate to within only +- 5% at the tender stage, +- 10% at the pre-tender stage, +-15 to 25% at the feasibility study stage, and +- 40 to 50% at the prefeasibility stage, or outset of project consideration.
It was observed that while there were many sophisticated tools for design and detailed cost estimation, there were few tools aimed at the early stages of the project. This made feasibility and prefeasibility studies costly and time-consuming. A tool that facilitated these studies would not need to achieve especially accurate estimates: rather, it would need to provide insight, as rapidly and as easily as possible, as to whether a proposed project passed an initial screening for energetic and financial viability.
RETScreen was developed in response to this need. It is not a design tool, but rather performs prefeasibility and, feasibility studies. It satisfies three objectives. First, it improves the accuracy of estimates. Second, it speeds up project analysis. Third, and most important, it reduces the cost of doing prefeasibility and feasibility studies. In this way, more potential projects can be screened, so that resources can be allocated to those that have the most promise. As such, it aims to move clean energy out of the realm of showcase projects and into the mainstream.
SLIDE 5: Financial Analysis
Financial parameters are often as important to project viability as costs and energy.
One important parameter is the cost of the conventional source of energy: when this is high, clean energy technologies earn bigger returns. In RETScreen the term "Base case fuel cost" is given to the cost of the relevant conventional energy source. For example, this might be heating oil or natural gas for the solar air-heating project considered earlier. Note that RETScreen considers electricity to be a "fuel," such that for a wind project the base case fuel cost could be the price paid for electricity under a power purchase agreement.
The debt ratio, or fraction of the project that is financed with debt, as well as the term of the loan and the interest rate, all have a strong bearing on the profitability of the project.
Both sales taxes and income taxes should be included. Energy efficiency projects reduce operating costs, thus raising profits and income taxes, at least for taxable organizations.
Environmental considerations drive clean energy projects, and can be a basis for selecting among competing projects. The environmental characteristics of the base case fuel are therefore important. Coal, for example, is a dirtier fuel than natural gas, both in terms of greenhouse gases and local pollution. Environmental credits and subsidies, such as greenhouse gas emissions reductions credits and deployment incentives, are sometimes available.
Finally, there is no single right measure of cost-effectiveness: different decision-makers use different criteria. A cash-strapped enterprise might require a one year simple payback, an investor might seek a return-on-investment in excess of 18%, a company might want a positive net present value at a discount rate of 12%, and a wind developer might desire energy production costs below 5.5 cents per kWh. RETScreen calculates a suite of financial indicators automatically.
SLIDE 6: Financing Options
Let's further examine the impact of financing. At the same time, we'll see the pitfalls of one of the most common financial indicators, the simple payback period.
Imagine a large building or plant that consumes 1 million cubic metres of natural gas per year. Gas costs $0.40/m³, so annual fuel costs are $400,000. A proposed efficiency measure with an installed cost of $300,000 reduces gas consumption by 25%, for a savings of $100,000. Energy costs escalate at a rate of 2% per year over the 20-year life of the project. Is the project cost-effective?
This table shows that there is no single right answer: it depends on how the project is financed and the decision-maker's definition of cost-effectiveness.
To begin, note that the simple payback period, or number of years before the project's initial cost is recouped through annual savings, is 3 years for this $300,000 investment that saves $100,000 per year. Many companies would consider this too long. But according to the internal rate of return, or true interest yield of the investment over its lifetime, the project is very attractive: the project's IRR falls in the range of 12 to 92%, far better than most savings accounts, stocks or bonds. So simple payback, while essential for cash-strapped organizations, often rejects excellent investment opportunities.
While it does not appear in the simple payback, project financing impacts the IRR. In the column labelled "Cash," the full cost of the project is paid for in equity: that is, no debt is incurred. In the next two columns, 70% of the cost of the project is paid for in debt, and 30%, or $90,000, through equity. As shown by the row "Pre-tax IRR - equity," this greatly improves the profitability of the project, since the proponent's investment is slashed by 70% without any reduction in the fuel cost savings.
Longer-term debt, as seen in the middle column, makes the project more attractive yet, since the proponent achieves better returns earlier in the project.
Some of the impact of financing is captured by the equity payback, which is the time required to recoup the equity investment out of pre-tax cash flows reflecting inflation and debt payments. When equipment is leased or provided by an external company through an energy performance contract, there is no equity investment, and the equity payback is immediate. By this measure, these options are the most attractive of all. Yet the IRR (calculated on the $300,000 of assets) shows that, in fact, purchase of the equipment is more profitable than these options.
SLIDE 7: A Five-Step Analysis
RETScreen 4's five-step standard analysis runs under Microsoft Excel, which provides a familiar interface. Behind Excel, RETScreen contains over 70,000 lines of code, making it powerful and flexible.
The Start sheet appears when RETScreen is opened. Here the user specifies the project name and type, the language, the currency, the unit system, and the climate data. The user can choose between "Method 1," a simplified single spreadsheet, or "Method 2," a more detailed approach. Then the five-step RETScreen analysis begins.
First, an energy model determines the energy benefits of the proposed project compared to a conventional alternative. Second, the incremental costs of the clean energy project are evaluated. Third, an optional greenhouse gas analysis calculates the emissions reductions associated with the project, according to a standardized methodology developed in collaboration with the United Nations Environment Program and the World Bank's Prototype Carbon Fund. Fourth, a financial summary indicates whether the project is financially attractive, considering cash flows, taxation, incentives, and emissions reductions credits. And fifth, a sensitivity and risk analysis reveals how changes in inputs affect the viability of the project, in part through a "Monte Carlo" simulation that reruns the analysis 500 times with random variations in key parameters.
In addition to RETScreen's climate database, discussed earlier, there is a product database of over 7000 clean energy devices, ranging from wind turbines to fuel cells. A thousand page help manual guides the user and explains clean energy technology. A host of tools performs detailed engineering calculations directly applicable to RETScreen-for example, for sizing a ground heat exchanger or estimating the thermal properties of a building envelope-and helps with unit conversions, steam properties, GHG equivalencies and more.
In addition to software, RETScreen offers a comprehensive distance learning course, training material in many languages, a detailed textbook revealing the algorithms behind RETScreen and providing background information on clean energy technologies, case studies, and links to energy resource maps.
SLIDE 8: EcoAction and other Government Programs
In Canada, RETScreen is a part of the Federal Government's larger efforts in climate change and the environment. EcoAction offers incentives, tools, and advice beyond RETScreen. Consult the website for more information.
Slide 9: A Wind Project Example
Let's learn about RETScreen by using it to compare two simple scenarios. The proposed project is a 2 MW wind turbine, to be installed on the Toronto waterfront, like the turbine in this photo. Based on other wind projects, a capacity factor of 23% is estimated; that is, the winds at the site are strong enough for the turbine to produce, on average, 23% of its 2 MW rated power. Installed turbine costs are estimated at $2000 per kW. In the first scenario, we examine whether it is financially attractive to sell this electricity at 11 cents per kWh. In the second scenario, we investigate whether a 1 cent per kWh green power production incentive would be preferable to a payment of $15 per tonne of greenhouse gas emissions reductions.
SLIDE 10: Software Demo
We'll open a .ret file corresponding to the first scenario of the project. The Start page appears within Excel. A RETScreen drop-down menu appears in the Excel menu bar. It and a floating RETScreen toolbar provide access to the help manual; product, climate, hydrology, and project databases; and RETScreen resources available through the website. Many of these can also be accessed through underlined, blue hyperlinks found at relevant points in the spreadsheets.
RETScreen cells are colour coded. The first cells on the Start page are for the project name and location, and play no part in calculations. In RETScreen such cells are grey. Yellow cells require user input for the calculations, blue cells are the same except that database information is available, and RETScreen's output appears in white cells. Only grey, yellow and blue cells can be changed; white cells cannot be edited.
The project type is selected from a drop down list, covering energy efficiency, power, heating, cooling, and various combinations of these. This is a power project, a category that includes technologies ranging from photovoltaics to tidal power to combined cycle gas power plants: a single RETScreen 4 spreadsheet deals with all of these.
Clicking on "show settings" permits the selection of the language for the software, the language for the help manual, the currency, and the unit system in which outputs will be displayed. The user selects the units for each input individually.
The climate database contains annual and monthly climate data for all parameters relevant to clean energy projects. Once again, the choice of units is up to the user.
All the world's inhabited areas are covered by database entries drawing on ground station data, satellite data, or a mix of both, as indicated by the "source" cells. The locations of the database entries are shown in the online help manual, which can be opened, for example, by clicking on the button at the bottom right.
Once the location has been selected, the user clicks on the green checkmark to paste the data into the analysis. The user can see and modify these data by checking "show data."
We want to do a quick, simple analysis of this wind project. Therefore, we use Method 1. For a more detailed analysis, selecting Method 2 would add in-depth spreadsheets to our workbook, which would be accessed by the tabs along the bottom of the screen.
Let's click on the energy model tab and do our analysis. We enter 2000 kW, the rated power of our turbine, and 23%, the capacity factor. RETScreen tells us that the turbine generates a bit over 4 GWh per year.
Then we enter the $4,000,000 installed cost of the project, the $0.11/kWh tariff, an inflation rate of 3 % and a project lifetime of 25 years. We assume 70% of the project will be financed by a loan with an interest rate of 8% and a term of 15 years.
That's it. RETScreen now provides a simplified assessment of our turbine's financial viability. A cumulative cash flow graph, on the right, shows that revenues cover the loan until it is paid off in year 15, after which yearly net income increases sharply. The pre-tax IRR on equity is 16.1%-a pretty good return that would be passed by based on the simple payback period of nearly 10 years.
Which would improve our project's return more: a 1 cent per kWh production incentive or a carbon trade valuing emissions reductions at $15 per tonne?
The first possibility is examined by adding $10 to our base tariff of $110 per MWh; to see this in $ per kWh, we click on "Show alternative units." The Pre-tax IRR on equity rises from 16.1% to 18.8%.
The second possibility requires a greenhouse gas emissions analysis, which appears in simplified form when the check box is clicked. The user must supply a reasonable emissions factor for the base case, that is, the tonnes of CO2 equivalent emitted per MWh of conventional electricity generated. This should reflect the fuels that the wind turbine will displace. To help out, RETScreen lists average emissions factors for grid electricity, for each country and, within Canada, for each province: we choose Ontario.
Between the power plant and the end-user, there are transmission and distribution, or "T&D," losses of, say, 8%. These increase the emissions factor from the consumer's point of view. The wind turbine also suffers T&D losses, so for a fair comparison, RETScreen in effect assumes that the base case grid makes up for these losses, with the associated emissions attributed to the wind turbine.
The wind turbine reduces emissions by about 1000 tonnes of CO2 equivalent per year. Is this a lot? RETScreen puts this in context with a handy calculator: the project's emissions reductions are equivalent to that of 213 cars and light trucks being taken off the road for a year, or, as another example, the carbon absorbed annually by 360 hectares of forest.
So is a carbon trade at $15 per tonne better than the 1 cent per kWh incentive? We remove the incentive, add in the carbon trade, and find that the IRR is now 17.0%, less than with the incentive. But were our project in Alberta, which generates most of its electricity with coal, instead of Ontario, which uses much nuclear and hydropower, our IRR would be 19.2%, better than with the incentive.
Up to now, we've assumed a capacity factor for the project. Often we will not know the capacity factor, or will want to investigate how input parameters affect the capacity factor. In those cases, we'll need a more sophisticated energy model. Just like we chose a single spreadsheet analysis by choosing Method 1 on the Start sheet, we can specify the level of detail for the energy analysis itself by selecting Method 1, 2, or 3 at the top of the Energy Model sheet. We've been using Method 1, which deals with the capacity factor. Now let's choose Method 2 and work with annual wind data and a turbine power curve. If we wanted to refine our analysis with measured monthly wind data and tariffs that varied according to the season, we would use Method 3.
SLIDE 11: Wind Resource Atlas-Maps
RETScreen does not automatically paste wind speed data from the climate database into the spreadsheet, as it does with every other climate parameter. This is intentional: the wind speed disproportionately affects turbine production, and to minimize errors only the best wind speed data should be used. Ground station and even satellite measurements may not be representative, so RETScreen links to high resolution wind resource maps available over the Internet. For this project, we select the Ontario Wind Atlas, zoom in on Toronto, and find the wind speed at 80 or 100 m, the heights nearest the turbine hub.
Occasionally it may be unclear what to enter for a cell. For example, the user might not know what the "wind shear exponent" is or what to estimate for this parameter. Selecting this cell and opening the help manual provides both a definition and guidance.
The "See product database" hyperlink accesses the wind turbines in the RETScreen product database. When this database is opened via this hyperlink, as opposed to through the menu or floating toolbar, the turbine characteristics, including the power curve, can be pasted directly into RETScreen by clicking on the green checkmark button. Note that there is also a button that accesses the website of whichever manufacturer is selected, so that the user can get more information or contact the supplier.
Having pasted in the power curve from the database, the user can modify the values, or simply hide them away by deselecting "show data."
Based on the wind speed data, RETScreen revises the estimate of capacity factor from 23% to 25.2%. This raises the IRR to 19%. Seeing that this is a promising project, we would choose to invest more time and effort in a detailed analysis. Returning to the Start page, we select Method 2. This creates in-depth cost, emissions, and financial analysis pages where we can refine our estimates.
For costs, we no longer merely assume a $2000 per kW-installed cost, but rather consider costs on an item-by-item basis. Here, too, RETScreen allows a simplified Method 1 cost analysis or a more detailed Method 2 cost analysis.
The emissions analysis similarly expands, and offers three levels of sophistication, Methods 1 through 3, permitting a wider range of assumptions about the fuels displaced, future changes in the generation mix, and adjustments to emissions factors.
The financial analysis permits us to consider inflation and fuel cost escalation separately, account for income taxes and depreciation of capital, and include production incentives, subsidies, and tariff changes. RETScreen calculates a more complete suite of indicators of financial viability. Furthermore, uncertainty is directly addressed in the risk analysis page. For example, having specified the range of possible values that key parameters might take, we can examine the frequency distribution of probable project outcomes, in terms of after-tax IRR on equity, to ensure that 97.5% of these outcomes exceed a certain minimum acceptable return. This "Monte Carlo" simulation was introduced to help lenders with due diligence studies.
SLIDE 12 and 13
As mentioned earlier, RETScreen operates in many languages. Perhaps someone from Japan might be interested in this Norwegian landfill gas project. From the start page, we could instantly convert to Japanese. Perhaps a German bank might be providing financing. Another click, and we could share our project information with them.
SLIDE 14: RETScreen Software: Cumulative Growth of User Base
RETScreen's power and ease of use has led to a huge worldwide user base. As of early 2008, there were 145,000 users in 222 countries. Over 900 new users download RETScreen every week. In Canada alone there are over 30,000 users, including engineers, architects, managers, and educators. Within 10 years, RETScreen aims to be helping over one million users with their clean energy projects.
RETScreen 4, a major new edition of the RETScreen software, helps rapidly evaluate whether a proposed clean energy project makes sense and is worth further consideration. This presentation introduces RETScreen 4, highlights its new features, and describes the RETScreen approach to project analysis.
SLIDE 2: New Features of RETScreen 4
RETScreen 4 improves on previous versions in six major ways:
First, RETScreen now goes beyond renewable energy and cogeneration, and deals with a wide range of energy efficiency measures. The efficiency project model can be used for new building design or energy audits in projects ranging from small houses to large industrial complexes. It can be used for residential, commercial and institutional buildings, both new and existing, as well as for industrial processes.
Second, RETScreen 4 includes more climate data, with a global climate database that has been expanded from 1000 to 4700 ground measurement stations. Furthermore, through its continued collaboration with NASA, RETScreen utilizes global climate data derived from 20 years of satellite observations. These NASA data, useful where there is no nearby ground station, are now integrated directly into the RETScreen software, so that the user no longer need copy data from the NASA website.
The third major development of RETScreen 4 is the integration of all the different project technologies into a single workbook. In previous versions, each different technology had its own independent workbook. Now renewable energy, cogeneration, and efficiency measures are all in the same tool.
Fourth, RETScreen 4 includes a project database of case studies and templates, to which users can add their own projects. Over 100 case studies, each with an assignment, solution, and description of the real world implementation of the project, are now available from within the software itself. The solutions are accessed from the project database and the assignment and real project description are in the help manual. The case studies are excellent aides for learning about clean energy technologies and how to use RETScreen. The project database also includes templates, or analyses pre-filled with typical values for a variety of common projects. Templates provide a reasonable starting point for the analysis, which the user can then rapidly refine.
A fifth significant improvement in RETScreen 4 is the ability to save an analysis in a compact ".ret" file. A .ret file is essentially a user-defined project database, with the data from one or more scenarios or projects. In previous versions of RETScreen, the entire Excel workbook was saved, resulting in files up to 10 MB in size. The new .ret files may be as small as 10 KB, making it easier to share analyses by e-mail. Furthermore, the .ret file decouples the project data from the underlying software, so that project data can be loaded into the most recent RETScreen upgrade without having to manually transfer data from an older version of the software.
Sixth, RETScreen handles many languages, collectively spoken by 2/3rds of the world's population. With a click of the mouse, the RETScreen interface can be switched from one language to another. Partners located around the world can use different languages in their RETScreen analyses but share the .ret files describing their project.
SLIDE 3: Project Analysis
The dark section of wall seen on this building is a solar air heating system. Perforations permit building ventilation air to be drawn in through the wall; sunlight warms the wall and the air around it, and this preheating reduces the fuel required to heat ventilation air.
When this project was proposed, it was unknown whether it would make sense. As in all clean energy projects, many things had to be considered, including:
First, the energy resource. Historical climate data for solar energy had to be obtained, and then the solar energy that would strike a south-facing vertical surface had to be estimated.
Second, the performance of the equipment. For the solar wall, the reduction in conventional heating fuel usage was calculated according to the solar absorptivity of the collectors, the airflow rate, and the demand for ventilation air heating.
Third, the initial project costs-that is, the cost of the solar collectors, additional fans and ducting, and equipment installation.
Fourth, base case credits. Recognizing that by doing the clean energy project, certain base case costs would be avoided, these costs were subtracted from the initial project costs to determine the incremental costs. For example, this solar air collector is a form of building cladding, so there was a base case credit equal to the cost for conventional cladding.
Fifth, annual and periodic costs. These included annual operation and maintenance costs as well as periodic costs, such as replacement of dampers every 10 years. Once again, the incremental costs were of interest, so that the solar wall was credited for any avoided annual or periodic costs associated with conventional cladding, beyond fuel savings.
Thus, even for a simple project, a number of considerations enter the analysis. RETScreen provides a framework for these considerations.
SLIDE 4: How RETScreen Fits into Project Analysis
The figure on this slide illustrates the findings of a retrospective study, conducted for the World Bank, of cost estimates for around 50 hydropower projects. Compared to the final as-built costs, cost estimates were accurate to within only +- 5% at the tender stage, +- 10% at the pre-tender stage, +-15 to 25% at the feasibility study stage, and +- 40 to 50% at the prefeasibility stage, or outset of project consideration.
It was observed that while there were many sophisticated tools for design and detailed cost estimation, there were few tools aimed at the early stages of the project. This made feasibility and prefeasibility studies costly and time-consuming. A tool that facilitated these studies would not need to achieve especially accurate estimates: rather, it would need to provide insight, as rapidly and as easily as possible, as to whether a proposed project passed an initial screening for energetic and financial viability.
RETScreen was developed in response to this need. It is not a design tool, but rather performs prefeasibility and, feasibility studies. It satisfies three objectives. First, it improves the accuracy of estimates. Second, it speeds up project analysis. Third, and most important, it reduces the cost of doing prefeasibility and feasibility studies. In this way, more potential projects can be screened, so that resources can be allocated to those that have the most promise. As such, it aims to move clean energy out of the realm of showcase projects and into the mainstream.
SLIDE 5: Financial Analysis
Financial parameters are often as important to project viability as costs and energy.
One important parameter is the cost of the conventional source of energy: when this is high, clean energy technologies earn bigger returns. In RETScreen the term "Base case fuel cost" is given to the cost of the relevant conventional energy source. For example, this might be heating oil or natural gas for the solar air-heating project considered earlier. Note that RETScreen considers electricity to be a "fuel," such that for a wind project the base case fuel cost could be the price paid for electricity under a power purchase agreement.
The debt ratio, or fraction of the project that is financed with debt, as well as the term of the loan and the interest rate, all have a strong bearing on the profitability of the project.
Both sales taxes and income taxes should be included. Energy efficiency projects reduce operating costs, thus raising profits and income taxes, at least for taxable organizations.
Environmental considerations drive clean energy projects, and can be a basis for selecting among competing projects. The environmental characteristics of the base case fuel are therefore important. Coal, for example, is a dirtier fuel than natural gas, both in terms of greenhouse gases and local pollution. Environmental credits and subsidies, such as greenhouse gas emissions reductions credits and deployment incentives, are sometimes available.
Finally, there is no single right measure of cost-effectiveness: different decision-makers use different criteria. A cash-strapped enterprise might require a one year simple payback, an investor might seek a return-on-investment in excess of 18%, a company might want a positive net present value at a discount rate of 12%, and a wind developer might desire energy production costs below 5.5 cents per kWh. RETScreen calculates a suite of financial indicators automatically.
SLIDE 6: Financing Options
Let's further examine the impact of financing. At the same time, we'll see the pitfalls of one of the most common financial indicators, the simple payback period.
Imagine a large building or plant that consumes 1 million cubic metres of natural gas per year. Gas costs $0.40/m³, so annual fuel costs are $400,000. A proposed efficiency measure with an installed cost of $300,000 reduces gas consumption by 25%, for a savings of $100,000. Energy costs escalate at a rate of 2% per year over the 20-year life of the project. Is the project cost-effective?
This table shows that there is no single right answer: it depends on how the project is financed and the decision-maker's definition of cost-effectiveness.
To begin, note that the simple payback period, or number of years before the project's initial cost is recouped through annual savings, is 3 years for this $300,000 investment that saves $100,000 per year. Many companies would consider this too long. But according to the internal rate of return, or true interest yield of the investment over its lifetime, the project is very attractive: the project's IRR falls in the range of 12 to 92%, far better than most savings accounts, stocks or bonds. So simple payback, while essential for cash-strapped organizations, often rejects excellent investment opportunities.
While it does not appear in the simple payback, project financing impacts the IRR. In the column labelled "Cash," the full cost of the project is paid for in equity: that is, no debt is incurred. In the next two columns, 70% of the cost of the project is paid for in debt, and 30%, or $90,000, through equity. As shown by the row "Pre-tax IRR - equity," this greatly improves the profitability of the project, since the proponent's investment is slashed by 70% without any reduction in the fuel cost savings.
Longer-term debt, as seen in the middle column, makes the project more attractive yet, since the proponent achieves better returns earlier in the project.
Some of the impact of financing is captured by the equity payback, which is the time required to recoup the equity investment out of pre-tax cash flows reflecting inflation and debt payments. When equipment is leased or provided by an external company through an energy performance contract, there is no equity investment, and the equity payback is immediate. By this measure, these options are the most attractive of all. Yet the IRR (calculated on the $300,000 of assets) shows that, in fact, purchase of the equipment is more profitable than these options.
SLIDE 7: A Five-Step Analysis
RETScreen 4's five-step standard analysis runs under Microsoft Excel, which provides a familiar interface. Behind Excel, RETScreen contains over 70,000 lines of code, making it powerful and flexible.
The Start sheet appears when RETScreen is opened. Here the user specifies the project name and type, the language, the currency, the unit system, and the climate data. The user can choose between "Method 1," a simplified single spreadsheet, or "Method 2," a more detailed approach. Then the five-step RETScreen analysis begins.
First, an energy model determines the energy benefits of the proposed project compared to a conventional alternative. Second, the incremental costs of the clean energy project are evaluated. Third, an optional greenhouse gas analysis calculates the emissions reductions associated with the project, according to a standardized methodology developed in collaboration with the United Nations Environment Program and the World Bank's Prototype Carbon Fund. Fourth, a financial summary indicates whether the project is financially attractive, considering cash flows, taxation, incentives, and emissions reductions credits. And fifth, a sensitivity and risk analysis reveals how changes in inputs affect the viability of the project, in part through a "Monte Carlo" simulation that reruns the analysis 500 times with random variations in key parameters.
In addition to RETScreen's climate database, discussed earlier, there is a product database of over 7000 clean energy devices, ranging from wind turbines to fuel cells. A thousand page help manual guides the user and explains clean energy technology. A host of tools performs detailed engineering calculations directly applicable to RETScreen-for example, for sizing a ground heat exchanger or estimating the thermal properties of a building envelope-and helps with unit conversions, steam properties, GHG equivalencies and more.
In addition to software, RETScreen offers a comprehensive distance learning course, training material in many languages, a detailed textbook revealing the algorithms behind RETScreen and providing background information on clean energy technologies, case studies, and links to energy resource maps.
SLIDE 8: EcoAction and other Government Programs
In Canada, RETScreen is a part of the Federal Government's larger efforts in climate change and the environment. EcoAction offers incentives, tools, and advice beyond RETScreen. Consult the website for more information.
Slide 9: A Wind Project Example
Let's learn about RETScreen by using it to compare two simple scenarios. The proposed project is a 2 MW wind turbine, to be installed on the Toronto waterfront, like the turbine in this photo. Based on other wind projects, a capacity factor of 23% is estimated; that is, the winds at the site are strong enough for the turbine to produce, on average, 23% of its 2 MW rated power. Installed turbine costs are estimated at $2000 per kW. In the first scenario, we examine whether it is financially attractive to sell this electricity at 11 cents per kWh. In the second scenario, we investigate whether a 1 cent per kWh green power production incentive would be preferable to a payment of $15 per tonne of greenhouse gas emissions reductions.
SLIDE 10: Software Demo
We'll open a .ret file corresponding to the first scenario of the project. The Start page appears within Excel. A RETScreen drop-down menu appears in the Excel menu bar. It and a floating RETScreen toolbar provide access to the help manual; product, climate, hydrology, and project databases; and RETScreen resources available through the website. Many of these can also be accessed through underlined, blue hyperlinks found at relevant points in the spreadsheets.
RETScreen cells are colour coded. The first cells on the Start page are for the project name and location, and play no part in calculations. In RETScreen such cells are grey. Yellow cells require user input for the calculations, blue cells are the same except that database information is available, and RETScreen's output appears in white cells. Only grey, yellow and blue cells can be changed; white cells cannot be edited.
The project type is selected from a drop down list, covering energy efficiency, power, heating, cooling, and various combinations of these. This is a power project, a category that includes technologies ranging from photovoltaics to tidal power to combined cycle gas power plants: a single RETScreen 4 spreadsheet deals with all of these.
Clicking on "show settings" permits the selection of the language for the software, the language for the help manual, the currency, and the unit system in which outputs will be displayed. The user selects the units for each input individually.
The climate database contains annual and monthly climate data for all parameters relevant to clean energy projects. Once again, the choice of units is up to the user.
All the world's inhabited areas are covered by database entries drawing on ground station data, satellite data, or a mix of both, as indicated by the "source" cells. The locations of the database entries are shown in the online help manual, which can be opened, for example, by clicking on the button at the bottom right.
Once the location has been selected, the user clicks on the green checkmark to paste the data into the analysis. The user can see and modify these data by checking "show data."
We want to do a quick, simple analysis of this wind project. Therefore, we use Method 1. For a more detailed analysis, selecting Method 2 would add in-depth spreadsheets to our workbook, which would be accessed by the tabs along the bottom of the screen.
Let's click on the energy model tab and do our analysis. We enter 2000 kW, the rated power of our turbine, and 23%, the capacity factor. RETScreen tells us that the turbine generates a bit over 4 GWh per year.
Then we enter the $4,000,000 installed cost of the project, the $0.11/kWh tariff, an inflation rate of 3 % and a project lifetime of 25 years. We assume 70% of the project will be financed by a loan with an interest rate of 8% and a term of 15 years.
That's it. RETScreen now provides a simplified assessment of our turbine's financial viability. A cumulative cash flow graph, on the right, shows that revenues cover the loan until it is paid off in year 15, after which yearly net income increases sharply. The pre-tax IRR on equity is 16.1%-a pretty good return that would be passed by based on the simple payback period of nearly 10 years.
Which would improve our project's return more: a 1 cent per kWh production incentive or a carbon trade valuing emissions reductions at $15 per tonne?
The first possibility is examined by adding $10 to our base tariff of $110 per MWh; to see this in $ per kWh, we click on "Show alternative units." The Pre-tax IRR on equity rises from 16.1% to 18.8%.
The second possibility requires a greenhouse gas emissions analysis, which appears in simplified form when the check box is clicked. The user must supply a reasonable emissions factor for the base case, that is, the tonnes of CO2 equivalent emitted per MWh of conventional electricity generated. This should reflect the fuels that the wind turbine will displace. To help out, RETScreen lists average emissions factors for grid electricity, for each country and, within Canada, for each province: we choose Ontario.
Between the power plant and the end-user, there are transmission and distribution, or "T&D," losses of, say, 8%. These increase the emissions factor from the consumer's point of view. The wind turbine also suffers T&D losses, so for a fair comparison, RETScreen in effect assumes that the base case grid makes up for these losses, with the associated emissions attributed to the wind turbine.
The wind turbine reduces emissions by about 1000 tonnes of CO2 equivalent per year. Is this a lot? RETScreen puts this in context with a handy calculator: the project's emissions reductions are equivalent to that of 213 cars and light trucks being taken off the road for a year, or, as another example, the carbon absorbed annually by 360 hectares of forest.
So is a carbon trade at $15 per tonne better than the 1 cent per kWh incentive? We remove the incentive, add in the carbon trade, and find that the IRR is now 17.0%, less than with the incentive. But were our project in Alberta, which generates most of its electricity with coal, instead of Ontario, which uses much nuclear and hydropower, our IRR would be 19.2%, better than with the incentive.
Up to now, we've assumed a capacity factor for the project. Often we will not know the capacity factor, or will want to investigate how input parameters affect the capacity factor. In those cases, we'll need a more sophisticated energy model. Just like we chose a single spreadsheet analysis by choosing Method 1 on the Start sheet, we can specify the level of detail for the energy analysis itself by selecting Method 1, 2, or 3 at the top of the Energy Model sheet. We've been using Method 1, which deals with the capacity factor. Now let's choose Method 2 and work with annual wind data and a turbine power curve. If we wanted to refine our analysis with measured monthly wind data and tariffs that varied according to the season, we would use Method 3.
SLIDE 11: Wind Resource Atlas-Maps
RETScreen does not automatically paste wind speed data from the climate database into the spreadsheet, as it does with every other climate parameter. This is intentional: the wind speed disproportionately affects turbine production, and to minimize errors only the best wind speed data should be used. Ground station and even satellite measurements may not be representative, so RETScreen links to high resolution wind resource maps available over the Internet. For this project, we select the Ontario Wind Atlas, zoom in on Toronto, and find the wind speed at 80 or 100 m, the heights nearest the turbine hub.
Occasionally it may be unclear what to enter for a cell. For example, the user might not know what the "wind shear exponent" is or what to estimate for this parameter. Selecting this cell and opening the help manual provides both a definition and guidance.
The "See product database" hyperlink accesses the wind turbines in the RETScreen product database. When this database is opened via this hyperlink, as opposed to through the menu or floating toolbar, the turbine characteristics, including the power curve, can be pasted directly into RETScreen by clicking on the green checkmark button. Note that there is also a button that accesses the website of whichever manufacturer is selected, so that the user can get more information or contact the supplier.
Having pasted in the power curve from the database, the user can modify the values, or simply hide them away by deselecting "show data."
Based on the wind speed data, RETScreen revises the estimate of capacity factor from 23% to 25.2%. This raises the IRR to 19%. Seeing that this is a promising project, we would choose to invest more time and effort in a detailed analysis. Returning to the Start page, we select Method 2. This creates in-depth cost, emissions, and financial analysis pages where we can refine our estimates.
For costs, we no longer merely assume a $2000 per kW-installed cost, but rather consider costs on an item-by-item basis. Here, too, RETScreen allows a simplified Method 1 cost analysis or a more detailed Method 2 cost analysis.
The emissions analysis similarly expands, and offers three levels of sophistication, Methods 1 through 3, permitting a wider range of assumptions about the fuels displaced, future changes in the generation mix, and adjustments to emissions factors.
The financial analysis permits us to consider inflation and fuel cost escalation separately, account for income taxes and depreciation of capital, and include production incentives, subsidies, and tariff changes. RETScreen calculates a more complete suite of indicators of financial viability. Furthermore, uncertainty is directly addressed in the risk analysis page. For example, having specified the range of possible values that key parameters might take, we can examine the frequency distribution of probable project outcomes, in terms of after-tax IRR on equity, to ensure that 97.5% of these outcomes exceed a certain minimum acceptable return. This "Monte Carlo" simulation was introduced to help lenders with due diligence studies.
SLIDE 12 and 13
As mentioned earlier, RETScreen operates in many languages. Perhaps someone from Japan might be interested in this Norwegian landfill gas project. From the start page, we could instantly convert to Japanese. Perhaps a German bank might be providing financing. Another click, and we could share our project information with them.
SLIDE 14: RETScreen Software: Cumulative Growth of User Base
RETScreen's power and ease of use has led to a huge worldwide user base. As of early 2008, there were 145,000 users in 222 countries. Over 900 new users download RETScreen every week. In Canada alone there are over 30,000 users, including engineers, architects, managers, and educators. Within 10 years, RETScreen aims to be helping over one million users with their clean energy projects.
