Editing IPCC:AR6/WGIII/Chapter-15 (section)

=== Box 15.5 | The Role of Enabling Environments for Decreasing Economic Cost of Renewable Energy ===

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A widely used indicator for the relative attractiveness of renewable energy but also development of price levels is the [https://www.sciencedirect.com/topics/engineering/levelised-cost-of-energy levelised cost of energy] (LCOE). It is applied by a wide range of public and private stakeholders when tracking progress with regard to cost degression ( [[#Aldersey-Williams--2019|Aldersey-Williams and Rubert 2019]] ). LCOE calculation methodologies vary but in principle consider project-level costs only ( [[#NEA--1989|NEA 1989]] ). Besides other weaknesses, the LCOE concept usually does not consider societal costs resulting from de-risking instruments and/or other public interventions/support and therefore caution has to be applied when using the LCOE as the sole indicator of the success of enabling environments. The yearly IRENA mapping on renewable energy auction results demonstrates the extremely broad ranges of LCOEs (equal to the agreed tariffs) for renewable energy which can be observed ( [[#IRENA--2019a|IRENA 2019a]] ). For example, in 2018, solar PV LCOEs for utility-scale projects came in between USD0.04 kWh –1 and USD0.35 kWh –1 with a global weighted average of USD0.085 kWh –1 . However, comparative analysis taking into account societal costs is hardly available driven by challenges in the context of the quantification of public support.

The GET FiT concept argued that the mitigation of political and regulatory risk by sovereign and international guarantees is cost-efficient in developing countries, illustrating the estimated impact of such risk-mitigation instruments on equity and debt financing costs, and consequently required feed-in tariff levels ( [[#Deutsche%20Bank%20Climate%20Change%20Advisors--2011|Deutsche Bank Climate Change Advisors 2011]] ). The impact of financing costs on cost of renewable energy generation is well researched with significant differences across countries and technologies being observed, with major drivers being the regulatory framework as well as the availability and type of public support instruments ( [[#Geddes--2018|Geddes et al. 2018]] ; [[#Steffen--2019|Steffen 2019]] ). With a focus on developing countries and based on a case study in Thailand [[#Huenteler--2016|Huenteler et al. (2016)]] demonstrate the significant effect of regulatory environments but also local learning and skilled workforce on cost of renewables. The effect of those exceeds the one of global technology learning curves.

[[#Egli--2018|Egli et al. (2018)]] identify macroeconomic conditions (general interest rate) and experience effects within the renewable energy finance industry as key drivers in developed countries with a stable regulatory environment, contributing 5% (PV) and 24% (wind) to the observed reductions in LCOEs in the German market with a relatively stable regulatory environment. They conclude that ‘extant studies may overestimate technological learning and that increases in the general interest rate may increase renewable energies’ LCOEs, casting doubt on the efficacy of plans to phase out policy support’ ( [[#Egli--2018|Egli et al. 2018]] ). A rising general interest rate level could heavily impact LCOEs – for Germany, a rise of interest rates to pre-financial crisis levels in five years could increase LCOEs of solar and wind by 11–25% respectively ( [[#Schmidt--2019|Schmidt et al. 2019]] ).

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'''Box 15.6, Figure 1 | Two worlds – energy transition outcomes under alternative model assumptions (Keynesian vs General Equilibrium).''' Source: [[#Mercure--2019|Mercure et al. (2019)]] .

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