The variability of the all-in cost of wind energy, however, may still be a barrier for increased deployment of wind energy across the globe. From the outset of project development, investors in wind energy have relatively certain knowledge of the plant’s lifetime cost of wind energy.
This is because a wind energy project’s installed costs and mean wind speed are known early on, and wind generation generally has low variable costs, zero fuel cost, and no carbon emission costs. Even with these inherent characteristics, there are, however, wide variations in the cost of wind energy from wind farm project to project, within a country, and internationally. That is the focus of this effort.
Objective and Approach
Using a multi-national case-study approach, this work seeks to understand the source of wind energy cost differences across seven countries under International Energy Agency (IEA) Wind Task 26 – Cost of Wind Energy. The participating countries include Denmark, Germany, the Netherlands, Spain, Sweden, Switzerland, and the United States.
Assessing the cost of wind energy requires evaluation of a number of components including investment cost, operation cost, finance cost, and annual energy production, and how these cost streams vary over the life of the project. Representation of each of the different temporal cost parameters as a single descriptive value may be accomplished using a variety of methods and approaches.
For this project, we considered the levelized cost of energy (LCOE) as the primary metric for describing and comparing wind energy costs. The LCOE represents the sum of all costs over the lifetime of a given wind project, discounted to the present time, and levelized
based on annual energy production. Furthermore, the LCOE can be calculated with a number of different methods or approaches to represent several differing perspectives. This report describes two of these perspectives and approaches – a high level scenario planning approach and a sophisticated financial cash flow analysis approach.
The majority of the analysis in this report focuses on assessing the cost of wind-generated electricity, from the perspective of a private investor, in a given wind project, in each of the represented countries. More specifically, the LCOE analysis in this report represents the country specific financial cost of wind energy for a domestic investor financing their project using the adopted model and methodology. It is important to note that the financial cost comparisons are not a socio-economic cost evaluation of wind energy (i.e., the cost to society of this particular form of energy).
When calculating the financial cost of wind energy, this analysis tabulates all of the expenditures required to install, operate, and finance a wind project. In addition to assessing the pure cost of wind energy, this analysis also describes the revenues and wind energy incentives that are available to wind project owners in each of the represented countries. Differences that arise in cost elements among the countries are identified.
This report begins with a brief description of the cost elements that comprise the levelized cost of energy. Then, the spreadsheet model developed under the auspices of this project is described. Based on the data provided by each represented country, a Reference Case is defined to provide a common point of comparison among countries. The cost elements from each country are compared to the Reference Case to identify the source of the differences in levelized cost of wind energy. The next section briefly identifies an alternative method, from the private investor perspective, to calculating levelized cost of wind energy. The report then presents different LCOE estimates, based on the cost elements defined in the Reference Case, to demonstrate the variability in LCOE associated with the different methods. Finally, each of the participating countries provided a chapter that summarizes the cost elements of a typical wind project in their country. These constitute the bulk of this report.
Levelized Cost of Wind Energy
The principal components of the cost of wind energy include capital investment, operation and maintenance, and finance. Within each category, a number of elements are included and Appendix A describes the individual cost elements considered in this report.
Wind projects require a significant capital investment comprised of a number of other costs beyond the wind turbines alone. However, approximately 75% of the total investment cost is associated with the cost of the wind turbines. Other costs include grid connection, foundations, installation, and construction-related expenses, summarized as percentages. These are based on a selection of data from Germany, Denmark, Spain, and the UK. Decommissioning costs are set aside at the initiation of a project and these are included in the initial capital investment because they are required by some countries.
Cost elements of wind project capital investment
Share of total cost (%)
Typical share of other cost (%)
Turbine (ex works) 68-84 –
Grid-connection 2-10 35-45
Foundation 1-9 20-25
Electric installation 1-9 10-15
Land 1-5 5-10
Financial costs 1-5 5-10
Consultancy 1-5 1-3
Source: The Economics of Wind Energy, EWEA Report 2009
Operation and maintenance (O&M) costs contribute to the total cost of wind energy. A portion of these costs typically include fixed costs representing insurance, administration, and service contracts for scheduled maintenance. Variable O&M costs typically include scheduled and unscheduled maintenance and component replacement. These costs vary from one year to another; therefore, estimates often are made by assuming a constant cash flow stream over the life of the project. Since wind projects do not require annual fuel expenditures, O&M costs constitute the majority of annual costs. In some electricity markets, operating costs associated with power system services, such as reactive power compensation, are required for wind farm projects.
Finally, finance costs are a significant portion of the levelized cost of energy. The type of finance structures that are used to support construction of wind farm projects, and the associated levels of debt and equity contributors, vary among countries. The corresponding expected returns, by debt or equity investment providers, also vary significantly. In addition, each country’s corporate tax structure influences the total financial costs associated with wind projects.
The upfront investment costs, annual O&M costs, and financial variables are included. Because wind projects ultimately produce electricity, it is important to normalize the levelized cost with annual electricity production. Energy production depends on the wind turbines physical characteristics and the wind resource characteristics at a given project site.
Revenues and Incentives
Electricity is the product sold by a wind project owner, and the markets for electricity vary by country. While this project focuses on the costs associated with generation of electricity from wind power plants, the revenues and incentives in each of the electric markets represented are summarized. In addition to revenue from electricity sales, a variety of incentives are employed to assure that the costs of wind-generated electricity are recovered. These incentives include feed-in tariffs, production-based tax credits, renewable energy certificates, or other mechanisms.
A number of aspects to wind-generated electricity are not currently monetized and thus, are not included in an assessment of revenues or cost. These externalities, or societal costs, are associated with secondary impacts from electricity generation technologies. In general, renewable technologies have very low external impacts compared to conventional generation technologies.
The IEA Renewable Energy Costs and Benefits for Society (RECaBS) project estimates the costs and benefits of electricity generation from renewable sources compared to those of conventional generators using a transparent methodology (RECaBs 2007). According to the ReCABS methodology, the analysis includes five externalities:
“Climate change; greenhouse gasses, in particular CO2 and CH4
Other air pollutants: SOx, NOx, and particles
Grid integration; primarily added costs to the electrical infrastructure including power balancing costs and reduced capacity value of wind turbines
Security of fuel supply; substitution of fuel imports with indigenous resources.
In addition to the externalities described above, electricity generation from wind does not rely on fuel consumption and the associated volatility of fuel prices. The investment risks for wind technology differ from the risk profile of fossil-fuel generation technologies. All of these characteristics create an important difference in the value proposition for wind technology relative to other generation technologies, but this study does not attempt to make such comparative assessments.
LCOE Model Description
The cash flow model developed by the Energy Research Centre of the Netherlands (ECN) forms the basis for the estimations of the LCOE and the financial gap (FG) for wind energy in this project. The ECN model is a discounted cash flow model, originally designed to calculate the feed-in premium subsidies for renewable electricity in the Netherlands. Currently, it is used by ECN to advise the Dutch government on the magnitude of the production costs for different renewable options.
In the course of developing IEA Wind Task 26, the model has been tailored and extended to estimate cost structures in the participating countries. It is now a flexible, detailed tool for calculating the cost of wind energy. It contains modeling parameters such as unit size, operational time/full load hours, economic life, investment costs, O&M costs, project financing characteristics, and a wide range of additional relevant parameters. The model has been refined with more functionality and versatility when applying it to various countries and regulatory regimes, in general.
For example, the revised cash flow model allows for adjustments to diverse technical and financial parameters, according to the respective regulatory regime of a wind power project. Such a flexible model is important, not only in the calculation of total investment costs, but also to account for the different operational features and financial instruments and incentives between countries and wind farms.
Basic Concept of the Model
A high level of detail in calculating the cost of wind energy can be achieved using the cash flow spreadsheet model, with its full range of parameters detailed in Appendix A. This spreadsheet model consists of six different worksheets. The first three worksheets provide the detailed information needed to calculate the cost wind energy in a specific country.
In the first worksheet, “Year-independent” variables can be set. These include project features, the total upfront investment costs, total decommissioning costs,2 operational time in terms of full load hours, and the time horizon for the cost calculations. The investment and decommissioning costs can be given either as a total, or as a sum, of the various components. This is informative for cross-country comparisons of the differences in realized costs. In addition, a range of financial variables can be set in this worksheet. These include: inflation, to account for rising variable costs; return on debt; return on equity; and a debt/equity ratio, to reflect the financial risk associated with the project. Moreover, the cash flow model takes national and state corporate taxes into account.
The “Year-dependent” worksheet contains multiple entries that constitute the fixed and variable annual costs including O&M, land rent, and grid-related costs. Again, the detailed subdivision allows for cross-country comparison. Definitions for the electricity price and small determining factors, like contract and balancing costs, are provided.
In the third worksheet, labeled “Policies,” the applicable feed-in tariffs, tax credits, and other incentives are considered. As an option within the model, the benefits associated with tax breaks can be limited to the project’s cash flow or, alternatively, designated as unlimited.3 The input parameters are used to determine the LCOE of the wind energy project, and the financial gap (FG) of electricity production, in the subsequent worksheets. The “Input_Output” worksheet presents the resulting LCOE and FG. It summarizes the variables used in the calculation. The actual cash flow calculations take place in the “Project cashflow” and “LCOE cashflow” worksheets.
LCOE and FG Calculations
The LCOE and FG result from cash flow calculations made from the perspective of a private financial investor; thus, the nominal after-tax return on equity is used as a discount rate for both LCOE and FG. However, the LCOE and FG include different streams of cash flows for each calculation. These are briefly described below.
LCOE is typically reported in terms of the investment outlays, annual costs, depreciation, and the chosen discount rate. Therefore, within this context, the LCOE calculation is defined as the production-dependent income required to achieve a zero net present value (NPV) of the equity share of the investment outlay, and the sum of all years’ discounted after-tax cash flows. In the LCOE calculation, the cash flows related to income, from electricity production and/or wind energy incentives specific to wind energy, are not taken into account.
Cost of Onshore Wind Energy in Participating Countries
The following section presents the country-specific financial cost of onshore wind energy for a domestic investor financing their project in each of the seven participating countries. This uses the ECN model and methodology. Cross-country comparisons of key onshore wind energy cost variables identify differences among each of the countries and offer a baseline onshore wind energy project cost. Due to limited available data, the cost of offshore wind energy is not presented in detail; however, a small sample of reported cost data is included.
Limitations of Reported Data
It is critical to note that, within this analysis, extensive efforts were made to verify the accuracy and validity of all collected wind energy costs, performance, and financial data. However, due to the numerous and diverse sources of data, the quality of the reported data varies among countries and sources. For example, reported cost data are intended to be presented in €2008, though in some instances, it is unclear whether they are presented in current or constant prices. Similarly, the parameters listed below are intended to be reflective of a wind project constructed in 2008; however, it is likely that some of the components were in fact ordered and paid for prior to 2008.
Data limitations prevented correction of this possible discrepancy. Furthermore, while IEA Task 26 aims to represent a “typical” project from each country, the actual cost of wind energy is site and project specific. Therefore, the following data are presented as illustrative of overall countryspecific conditions only and should be considered with this in mind.
Country-Specific Model Assumptions, LCOE, and the Reference Case
The country-specific costs of wind energy are compared against a baseline project, herein referred to as the “Reference Case”. The Reference Case represents a composite of wind energy cost elements from each country. The cost elements in the Reference Case include both technical parameters (e.g., project features, performance, investment outlays, and decommissioning costs, operations and maintenance costs, and others), as well as, financial parameters (e.g., debt and equity shares, return on equity, debt interest rate, loan length, and national tax rate).
The Reference Case does not include any revenue or wind energy policies or incentives due to each country’s unique approach in supporting wind energy. As such, only the LCOE calculation is presented for the Reference Case.
The country-specific technical parameters are shown in Table 1-2.4 For each technical parameter, the Reference Case value is calculated as the project-capacity weighted average across all countries. The technical parameter’s Reference Case values also are shown in Table 1- 2, and are heavily weighted towards Sweden and the United States due to their relatively large project capacities (98 and 85 MW respectively) in 2008. The Reference Case is weighted with project-capacity, instead of total domestic wind energy capacity, to illustrate a more or less typical project experienced in 2008 among each of the seven countries. While there are many differing options to construct the Reference Case project, it is important to point out that the choice of the Reference Case does not impact the country-specific LCOE or FG calculations. Simply, the Reference Case provides a general point for 2008 comparisons to present the country-specific results.
The country-specific financial parameters are shown in Table 1-3. For each financial parameter, the median value across all countries is used as the Reference Case value. As noted previously, the calculation of the Reference Case does not impact the country-specific LCOE or FG results. Although the ECN model uses the return on equity as the discount rate, the weighted average cost of capital (WACC) is also shown in Table 1-3 for illustrative purposes. The WACC incorporates several individual financial parameters (debt to equity ratio, return on equity, debt interest rate, and national tax rate) into a single metric descriptive of overall financing costs.
The country-specific LCOE and FG results are shown in Table 1-4 for each country and the Reference Case. The results include the 2008 levelized cost of energy and the financial gap calculation. While the results are intended to be illustrative of overall costs for onshore wind energy by country, the actual LCOEs for any wind project are site and project-specific.
As presented in Table 1-4, the LCOE by country ranges from €120/MWh ($167/MWh)7 in Switzerland to €61/MWh ($85/MWh) in Denmark. The Reference Case LCOE is estimated at €68/MWh ($95/MWh). The primary reasons for the variations of LCOEs across countries are due to differences in country-specific energy production, O&M expenditures, investment costs, and financing. The impact of these parameters on the country-specific LCOE is explored in the following section.
Cross-Country LCOE Comparisons
The cross-country analysis examined the LCOE impact of four key cost parameters between countries. For each country, the LCOE was estimated, with a single cost parameter set at a country-specific value, while all other parameters were set to the Reference Case value. The analysis isolated the impact of the country-specific input parameter compared to the baseline metric (the Reference Case parameter value). The key parameters tested in the cross-country analysis included energy production, investment costs, operations and maintenance costs, and financing costs. The results were then compared across all countries.
For example, the LCOE impact, of each country’s unique full load hours, is shown in Figure 1-3, which compares three distinct test cases. First, the grey bars show the unique country LCOE previously presented in Table 1-4, in which all input parameters are set to their country-specific values. Second, the blue line shows the baseline Reference Case LCOE at €68/MWh, in which all parameters are set to the Reference Case values. Third, the green circular markers show a mixed case, in which full load hours are set to the country-specific value while all other parameters are set to the Reference Case values.
Figures 1-3 though 1-6 present this analysis of energy production (described above), investments costs, operations and maintenance costs, and financing costs, respectively. The country-specific LCOE (grey bars) and the Reference Case LCOE (blue line) are constant in each of the figures, while the key cost parameter is unique to each figure and is shown with distinct markers.
Some explanations for the variation in the key wind energy cost parameters across countries include, but are not limited to, the following:
Energy Production (Full Load Hours): The variation of full load hours across countries is due to a number of common and independent factors. For example, in Germany, land constraints have pushed project development to southerly sites with poorer wind resources.
In Denmark, spatial planning may promote repowering of existing wind sites ahead of expansion of undeveloped sites within the country. Consequently, some of the premier wind resource sites in Denmark were targeted in 2008 for repowering. In Switzerland, limited mountain accessibility has led to the development of just a few projects through 2008. In the United States, there are numerous project sites with sufficient to excellent wind resources; however, limited transmission access and availability have influenced project location decisions and, in some cases, forced the curtailment of energy output.
Similarly, land constraints in Sweden are less of an issue than in other countries in the study. In the Netherlands, a feed-in-tariff premium, which is capped at a maximum amount of full load hours, may reduce the financial incentive to develop premier sites or utilize the most sophisticated technology.
Investment Costs: Investment costs range significantly across countries. In both Denmark and the Netherlands, a feed-in tariff premium subsidy based on full load hours influences the choice of the wind turbine and, therefore, a project’s investment costs. In Denmark, preference may be given to turbines with large generators to maximize the value of the subsidy per full load hour, while in the Netherlands preference may given to less expensive turbine technology since the subsidy is capped at maximum full load hours. In Denmark, some costs of installing a wind project, such as those interconnecting to the electric grid, are paid by the project’s end users (ratepayers) as opposed to the project’s developers.
As such, interconnection costs are not included in Denmark’s investment costs. However, in Spain, Germany, and several other countries, interconnection costs and other grid reinforcement costs are paid for by the project developer and are included in investment costs. In Sweden, there is a simplified procedure for grid interconnection that may offer some investment cost savings. Germany’s expansion of wind projects to southerly sites, with poorer wind resources, caused developers to compensate by constructing many of those projects at higher hub heights using larger rotor diameters (both of which are significant investment cost contributors). In Switzerland, difficulty accessing mountainous wind project sites, and the lack of economies of scale, have also contributed to high investment costs.
In the United States, the cost-benefit of large project sizes is particularly applicable to the purchase of turbines, and there is evidence of price discounts as order size increases. The larger wind farm project sizes and less expensive investment costs in the United States, when compared to the Reference Case, suggest that the United States developers benefit from quantity discounts. Interestingly, Sweden does not benefit from a price reduction corresponding to large project size. This could be attributed to a smaller amount of total domestic installations in 2008 compared to the modeled project capacity.
Operations and Maintenance Costs: Operations and maintenance cost data for each country were indicated as either highly uncertain or not readily available. In Denmark, creditors of wind projects typically require long-term O&M service contracts for 5-10 years. These were reported to cost approximately €25/kW annually. The Netherlands reported that their O&M costs typically also include a service contract that is priced consistently across projects, and a land-rent component, with a cost that varies significantly across projects, reportedly from €5/kW to €23/kW. Full service contracts often are required for a minimum of five years in Germany, as well. In Switzerland, limited O&M experience, high labor costs, accessibility difficulties, and turbine icing or turbulence may have led to higher O&M expenditures than in other countries.
In the United States, O&M costs, on average, appear to be lower for projects installed more recently, and for larger project sizes. However, anecdotal evidence suggests that U.S. O&M cost estimates, including premature component replacements of gearboxes, blades, or generators, may be under-represented in the reported data. Germany also reported increased O&M expenditures for smaller projects due to the necessity of stocking replacement components. Moreover, Germany reported costly periodic site inspections as an important component of overall O&M costs. In Sweden, the spread of operations and maintenance costs varies widely by project developer.
Financing Costs: The financing costs of onshore wind projects are similar across countries, with the exception of the United States. In Denmark, Germany, and the Netherlands, wind projects are typically project-financed, unless they are developed by a utility that finances wind projects on their balance sheets. In Denmark and Sweden, onshore wind projects are generally viewed as a low risk venture and finance pricing for onshore projects reflects this. In every country, except the United States, high debt ratios are utilized to finance a project, typically ranging from 60% to 87%.
The United States is a relative anomaly in the financing of wind projects. In 2008, many projects in the United States were financed with very high equity percentages (often 100%) and little to no project-based debt. This was due to federal tax subsidies that led to the proliferation of a specialized form of equity financing, known as tax equity. Because of the preference for tax equity financing, the cost of capital was generally higher in the United States than in other countries (i.e., tax equity is typically more expensive than debt).
When considering the spread, of country-specific input parameters, from lowest to highest, energy production and investment costs resulted in the largest LCOE impacts. This is generally consistent with previous wind LCOE sensitivity analyses (IEA 2010, Cory and Schwabe 2009).
Interestingly, however, the range of reported O&M expenditures increased the LCOE estimates by a larger amount than the highest cost investment or financing expenditures, when comparing the Reference Case value to the highest-cost value. This could suggest that the uncertainty and availability of O&M data, and thus the wide range of country-specific input parameters, limits the precision of the LCOE estimate. Future analysis to reduce the differentials due to O&M expenditures may be needed.
Cost of Offshore Wind Energy in Participating Countries
In addition to onshore wind, the ECN model can estimate LCOE for offshore wind installations. At this time, however, very limited offshore data is available; particularly the full suite of input variables that are necessary to estimate country-specific LCOE. As such, cross-country LCOE comparisons for offshore wind are not made, nor is an offshore Reference Case constructed.
It is important to note that, in Denmark, connecting to the grid and the necessity of a sea cable are socialized costs and, therefore, not borne by the project developer. Because the model used in this analysis is from the perspective of the project developer, these costs are not captured in the Danish investment cost estimate. Although not used in the modeling analysis, the inclusion of these grid connection costs would increase the Danish investment cost estimate to approximately €3,000/kW. Table 1-7 shows the LCOE and financial gap estimated for these offshore wind energy projects.
Other Approaches to LCOE Calculation
LCOE is calculated for a variety of purposes, motivations, and audiences. The general public, policymakers, investors, project developers, and others use LCOE for their particular needs. Therefore, each may utilize a different methodological approach. The level of detail, or the necessary assumptions, to estimate LCOE varies among methods and can have a significant impact on the LCOE outcome. Therefore, an alternative approach to calculating levelized cost of energy is described below, in contrast to the ECN model and methodology used thus far in the analysis.
For example, high-level planning scenarios often estimate levelized cost of energy using a simplified representation that is based on the present values of the investment cost and the average annual costs discounted using a social discount rate. Under this approach, assumptions for explicit financing terms, such as debt to equity ratios, costs of debt and equity, loan duration, and corporate taxes, are not made. Instead, the simple approach relies on the value chosen for the discount rate, and this represents all of the characteristics of the finance instrument.
From this social perspective, IEA uses a discount rate range from 5% to 10%, with 5% representing “a rate available to an investor with a low risk of default in a fairly stable environment” and 10% representing “the investment cost of an investor facing substantially greater financial, technological, and price risks” (IEA 2010). The more simplistic, high-level planning scenario minimizes the number of input parameters, and the level of detail facilitates LCOE comparisons among many different electric generation types.
Conversely, sophisticated cash flow models, like the ECN model, are used by developers to evaluate specific projects, their LCOE, and a number of other financial metrics, such as net present value, internal rate of return, or payback period. These models often include several owners, a suite of explicit financing assumptions, tax impacts, and other revenue or cost influences. They are often structured to evaluate all likely cost streams and to solve for an energy price that provides a return large enough for a company to invest in a particular project (Harper et al. 2007). Under this more detailed methodology, LCOE is impacted by numerous influences beyond the investment or annual costs. As the ultimate decision to build a project often rests with the investor, it is important to understand the investor perspective to understand the cost threshold that will allow wind capacity installations to continue.
As an example, the ECN model used in this analysis is a sophisticated cash flow model that estimates a project-specific LCOE, while ensuring a pre-defined return on equity (ROE) to the equity investor. As described earlier, the additional detail in the ECN cash flow model allows the explicit representation of financing structures that have debt and equity interests.
Representation of the cost of wind energy, from the perspective of the project developer, provides an estimate of the cost of wind generation that must be offset with income streams for a project to proceed.
Comparison of Discount Rates on LCOE Calculation
Table 1-8 shows a discount rate and LCOE methodology comparison. Using both the simple and the sophisticated cash flow analysis methods, the LCOE is estimated over a range of discount rates, while all other costs parameters were set to their Reference Case values. In addition, the discount rate value that yields the Reference Case LCOE (€68/MWh) is presented under both methods.
The typical discount rate values selected to represent the perspective of the social investor tend to be lower than the corresponding values representing the private project developer or investor perspective. According to IEA 2010, the reason for using the lower discount rate in the social perspective is that public investors typically face lower financing costs and risks because the risk is spread over a large number of individuals instead of a smaller number of private investors. Correspondingly, the social perspective LCOE estimates also tend to be lower than the estimates for the private developer.
As shown in Table 1-8, under both approaches, the difference in the selection of the discount rate impacts the LCOE value significantly. A discount rate of 9.5% is necessary to calculate the Reference Case LCOE of €68/MWh, using the simple calculation representing the social perspective. Therefore, based on the reported data by countries in this study, the discount rate should near the high end, 5-10% of values suggested in the IEA range of the simplified social planning method, to approximate the sophisticated cash flow approach.
Conversely, the use of a lower discount rate (the low end of the suggested range) is used to represent the case of public investors. Therefore, when calculating the LCOE, and also when comparing the LCOE of wind energy to that of other generation sources, it is imperative that either the project developer perspective, or a broader utility or system-level perspective, is clearly identified. The selection of the discount rate value should correspond to the represented perspective. Utilization of various equations to represent LCOE requires clear interpretation of the perspective represented, the discount rate, and other parameter values chosen.
Results of IEA Wind Task 26 indicate that the LCOE varies considerably between countries. The magnitude of this variation has been attributed to energy production, investment cost, operations cost, and financing cost. As expected, the largest LCOE impacts, from country to country, were the anticipated energy production based on the inherent wind regime or wind turbine technology specifications. Market forces greatly impacted the overall cost of wind energy through large variations in both capital expenditures and differences in financing terms for a wind project. Costs attributed to the operation of a wind project ranged widely across countries and had a sizable LCOE impact.
The nature of LCOE, as a single overall metric descriptive of the cost of energy, allows for seemingly simple comparisons to be made across countries, purposes, audiences, and other uses. However, the various methods of calculating LCOE require careful attention to precisely how, and from what perspective, the calculation is made. LCOE is not a universal, interchangeable calculation. Rather, LCOE is an informative and useful tool that can be adapted to a particular need. Therefore, comparisons should be made and interpreted carefully.
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