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Renewable Power Generation Costs in 2019

Die aktuellste Studie der IRENA zeigt auf, dass über die Hälfte des aus EE-Anlagen generierten Stroms, zu geringeren Kosten generiert werden kann, als bspw. Strom aus den neuesten Kohlekraftwerken. © IRENA 2020, IRENA (2020), Renewable Power Generation Costs in 2019, International Renewable Energy Agency, Abu Dhabi. www.irena.org

RENEWABLE POWER

RENEWABLE POWER GENERATION COSTS 2019 Figure 1.13 Investment value and new capacity added by renewable power technology, 2010-2019 Onshore wind Solar PV - distributed Concentrating solar power Hydropower 100 50 0 100 50 0 100 50 0 100 50 Offshore wind Solar PV - utility Geothermal Bioenergy 100 50 0 100 50 0 100 50 0 100 50 60 40 20 0 60 40 20 0 60 40 20 0 60 40 20 0 0 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2019 USD billion 2019 USD billion 2019 USD billion 2019 USD billion Capacity GW Capacity GW Capacity GW Capacity GW 0 Source: IRENA Renewable Cost Database and IRENA, 2020a. Note: Investment value is represented by bars and new capacity additions by lines. SENSITIVITY TO COST OF CAPITAL With either no, or trivial, fuel costs for renewable power generation technologies – except for bioenergy – and typically low O&M costs, 15 the level of total installed costs, capacity factor and the cost of capital become key determinants of the cost of electricity from renewable power generation projects. Yet, while the IRENA Renewable Cost Database provides insights into the total installed cost at the project level, the data for cost of capital is almost always unavailable. Unfortunately, even the availability of this information from secondary sources for timely, up-to-date data on the average cost of capital for individual renewable technologies in different markets in different years is seriously lacking. Indeed, the data available provides only a very partial view of the cost of capital in some markets, for some technologies and for some years. There is not nearly enough data available for IRENA to include a technology, country and year-specific WACC assumption that can be based on robust empirical data. This remains a key gap in our understanding of the global trends in the cost of electricity from renewable power generation projects. 15 There are some exceptions to this, notably for geothermal (where make-up wells can be considered an O&M expense) and certain bioenergy technologies (notably the gasification of woody biomass). These do not, however, broadly undermine the argument that the cost of capital has an important impact on the cost of electricity. 42

LATEST COST TRENDS As a result of the lack of data on the key determinants of project-level WACC – that is to say the cost of debt and equity, as well as the debt tenure and debt-to-equity ratio – for different technologies in different years, IRENA and others (e.g., the International Energy Agency) 16 rely on broad WACC assumptions. By necessity, however, these miss the granularity inherent in project-level WACC’s and their differentiation by market, technology and year. While an average assumption for the project-level WACC is not necessarily a critical failing, it does mask what would otherwise be useful insights. Yet, the lack of data for even differentiated country-level technology WACC’s over the period 2010 to 2019 means there is a significant risk that at any given point, the simplistic WACC assumptions used become a poor indicator of real world conditions and hence bias the results. By way of example, Figure 1.14 presents the LCOE for offshore wind from the IRENA Renewable Cost Database of projects, plotted against the adjusted Auction/PPA price for the same project. The data is therefore a subset of the database where we have data for both these metrics. The Auction/PPA price has been adjusted to ensure that it conforms as closely as possible with the IRENA LCOE methodology. This requires an estimate of the value of the “merchant tail” of projects which have contracts that are shorter than their economic life. It also necessitates putting all values into real currency terms, for those whose strike prices are not indexed to inflation, or only partially indexed. When plotting the results, the implication is that for those projects which are significantly above or below the 45 degree line, the actual WACC experienced by the project has deviated significantly from the assumption made by IRENA of a real value of 7.5%. 17 The data tends to suggest that in the early years of offshore wind deployment, more projects were around the 45 degree line or above, implying a WACC value exceeding the IRENA assumption of 7.5% for all years. This is perhaps to be expected, given that project developers had less experience in both developing and proving the ongoing performance of offshore wind projects. Banks would have taken this into account when pricing debt, while shareholders would have factored it in to hurdle rates for equity. Similarly, the relative lack of experience of financing institutions with offshore wind projects and their relative lack of understanding of the technology specific risks in operating wind farms offshore would likely have resulted in higher risk premiums to cover this uncertainty. In contrast, recent projects and those to be commissioned out to 2025 are clustered more tightly around the 45 degree line, implying that the WACC assumption of 7.5% is more reasonable today than it was for projects being commissioned between 2010 and 2016. Depending on market maturity, the situation for each technology and even country will differ, while the ability to collect sufficient data to extract meaningful trends would be a very resource-intensive task. This is the case for solar PV. The LCOE and PPA data in Figure 1.3 for utility-scale solar PV diverge materially from around 2016 onwards. This can, in part. be explained by selection bias, given that competitive procurement processes are by their nature likely to lead to lower prices. The order of magnitude of the difference, especially in 2018 and 2019, however, tends to imply that the anecdotal evidence supporting lower WACC's for solar PV than assumed in the LCOE calculations is having a material impact. To fill this significant data gap, IRENA proposes conducting a global survey of financial sector professionals on costs of capital for solar and wind technologies, in order to establish a reliable, replicable and well-documented database. The data collected through this survey effort will potentially add a new level of insight to IRENA Renewable Cost Database and analysis. It will also benefit IRENA’s member states and other stakeholders who need accurate cost of capital assumptions (e.g., regulators, researchers, energy system and climate modellers, etc.). The initial results of this exercise will be seen in Renewable Power Generation Costs in 2020, to be released in 2021. 16 IRENA assumes a real WACC of 7.5% in OECD countries and China, and 10% elsewhere for all technologies. While the IEA, in contrast, assumes 8% in developed countries and 7% in developing countries (IEA, 2019). 17 It is also possible that the IRENA O&M assumptions might differ materially from project-specific values, but these will have a proportionately lower impact on LCOE values, meaning the majority of variation should be due to the WACC assumption. It does, however, imply that the comparison of individual projects may be of limited value and that a large body of data is needed to draw robust inferences about overall trends in WACC. 43

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