Summary of Master Thesis for SAEE. Fuelling Renewable Energy Diffusion in non-oecd Countries

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1 Summary of Master Thesis for SAEE Fuelling Renewable Energy Diffusion in non-oecd Countries - A techno-economic assessment of financial requirements Robin Born ETH Zurich, Supervised by: Prof. Dr. Roland Siegwart ETH Zurich, Autonomous Systems Lab Prof. Dr. Volker H. Hoffmann Dipl.-Ing. Tobias Schmidt Dr. Malte Schneider ETH Zurich, Chair of Sustainability and Technology

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3 Currently the Clean Development Mechanism (CDM) is the largest international mechanism which aims at the diffusion of abatement technologies in non-oecd countries. As there exist technology- and country-specific differences in support requirements, the CDM s effects have been limited for most renewable energy technologies (RET). The current international climate debate indicates that the CDM s drawbacks have been understood and hence a trend towards Nationally Appropriate Mitigation Actions (NAMAs) can be observed. However, a detailed understanding of national requirements is still missing. In the thesis, we first propose an approach which considers technology and country differences to calculate financial support requirements for RET diffusion in non-oecd countries and second, apply the approach to 6 non-oecd countries to prove its applicability. It is the policy maker s responsibility to consider these differences adequately in the formulation of sound NAMA methodologies and procedures. In that sense, we show that direct financial RET support is insufficient, and that further actions such as fuel subsidy removal, energy market reform and technology transfer are necessary. Introduction Many authors (e.g. Bazilian et al., 2010; Neuhoff, 2009; Rayner, 2010) call for support mechanisms which take into account national differences. This call has been implemented in the Cancun agreement with the concept of NAMAs (UNFCCC, 2011, paragraph 48). NAMAs allow developing countries to establish their own national integrated policies with technology, financing and capacity building support from developed countries. Furthermore, in order to support RET diffusion, the Cancun agreement establishes the Green Climate Fund (GCF) (UNFCCC, 2011, paragraph 100) and the Technology Mechanism (TM) (UNFCCC, 2011, paragraph 117). The GCF will be responsible for the administration of a significant share of the multilateral funding which will provide up to 100 billion USD annually by 2020, while the TM will facilitate the implementation of technology development and transfer actions. To ensure optimal policy formulations, both on a national as well as an international level, quantitative data of support requirements is necessary. Some data is already available, but we see a lack of data based on medium-granular bottomup models which take into account technology and country differences and provide a broader national and international picture of financial requirements. In order to approach this gap, in the first part of the thesis, we develop a new medium-granular bottom-up model which considers technology- and country-specific differences. As the methodology used for this model is relatively easy applicable to many countries it can provide relevant input for the current international climate policy debate about NAMAs. In the second part, we prove its applicability by feeding the model with publicly available data of 6 non- OECD countries (Brazil, Egypt, India, Kenya, Nicaragua, Thailand) in order to answer our four research questions. First, we analyse the levelized cost of electricity (LCOE) of solar PV and on-shore wind to achieve a 10 % target share of each technology of the national electricity production (Figure 1). We find that solar PV still is a very expensive technology whereas on-shore wind is closer to market readiness. Second, the country-specific cost and emission baseline is calculated (Figure 2). Third, based on the country-specific cost baseline, we identify three different financial gap groups with either a relatively large financial gap, a gap close to zero and even a negative gap, meaning under our assumptions, RET exhibit lower LCOE than the baseline technologies (Figure 3). We then convert the financial gaps into CO 2 -specific terms and additionally find that for two countries, the gaps are in a similar magnitude of today s carbon prices. Furthermore, the total annual financial gap is derived and we find that with 1.4 % of the GCF s 100 billion USD resources, the 10 % wind target share of all countries under study could be financed. Fourth, we illustrate how fuel subsidies significantly distort competition in Egypt (Figure 4). In this summary, we focus on the results as they give a better understanding of the scope of the thesis. However, also the approach is a very important contribution to the international energy community. Levelized cost of electricity of RET As can be seen in Figure 1, in all countries, on-shore wind is economically much more attractive in Furthermore, despite the higher cost downs of PV, wind remains more attractive in Okubo et al. (2011) propose that feed-in tariffs (FITs) are adequate instruments in the context of NAMAs. As FITs should be designed in order to allow a RET project to reach break-even, they can be directly compared to LCOE. Consequently, policy makers in non-oecd countries can use the results obtained as a guiding point for their FIT considerations, or in countries with FITs already implemented, they can be compared to our results.

4 Figure 1 LCOE of solar PV (red) and on-shore wind (green) in 2010 and 2020 with average grid connection cost. The spread indicated by the black error bars represents the LCOE without and at very high grid connection cost. As the wind LCOE in 2010 are relatively low and the cost downs for the next ten years are rather incremental, wind diffusion should be promoted now. In the case of PV, one might argue that in order to bring down cost further, more R&D efforts are needed before diffusion is promoted via market-pull policies. This calls for public R&D support. On the other hand, market-pull effects can also strongly contribute to cost downs via learning effects and economies of scale. If international policy makers decide to employ market-pull policies, further research should clarify whether they are more cost-effective in OECD or non-oecd countries. As our results show, LCOE of PV might be lower in non- OECD countries and thus market-pull policies should be enacted there. On the contrary, in order to increase learning from technology use, diffusion should take place near respective innovation systems, i.e. in countries with large PV industries. In that sense, national policy makers could also consider fostering a local RET industry via own investments and the attraction of foreign direct investments. Here, NAMAs could support technology transfer and raise engagement of relevant private actors. Cost and emission baseline In Figure 2 the country-specific cost and emission baseline is depicted. Regarding the emission baseline, we observe that the results are relatively wide spread. Regarding the cost baseline, three groups emerge. As can be seen in the next section, these cost baselines have a major influence on the financial gap. The countries with the lowest cost baseline are India and Thailand. By contrast, the cost baseline in Brazil and Egypt is approximately 20 % higher. However, it is still rather low compared to the high cost baseline in Kenya and Nicaragua. Figure 2 Country-specific cost and emission baseline in The baselines are based on state of the art technology and international (i.e. unsubsidised) fuel market prices.

5 Financial gap Figure 3 depicts the financial gap in energy-specific (per MWh), CO 2 -specific (per tco 2 ) as well as total annual terms. Similar to Okubo et al. (2011, p. 37), we propose that the financial requirements to close the gap could be provided by the international community (e.g. the GCF) via financial support of national FITs. In the following analysis we focus on on-shore wind, as the financial gap of solar PV is very high in all countries. Figure 3 Financial gap of solar PV (red) and on-shore wind (green) in 2010 with average grid connection cost. The spread indicated by the black error bars represents the gap without and at very high grid connection cost. a, Energyspecific financial gap. b, CO 2 -specific financial gap. c, Total annual financial gap. On-shore wind represents a very interesting case with three different financial gap groups. As mentioned above, the financial gaps, and therefore the groups are mainly determined by the cost baseline. Again we find the same three groups. In India and Thailand the on-shore wind financial gap is very high because of the low cost baseline. Moreover, the effect is amplified by the relatively high wind LCOE in those two countries. Due to the slightly higher cost baseline and lower wind LCOE, the financial gap of on-shore wind in Brazil and Egypt is close to zero, i.e. it is almost as attractive as the baseline technologies. In case of no grid connection cost, there is almost no financial gap, which could trigger wide diffusion. As the cost baseline in Kenya and Nicaragua is very high, the on-shore wind financial gap is negative, and thus wind is far more attractive than the baseline technologies. However, in spite of these opportunities no wind projects are being realised in Kenya and Nicaragua. Though it is not clear whether there will be a carbon price-based mechanism in the future, the CO 2 -specific gap (Figure 3b) is interesting as it can be compared to a hypothetical carbon price in 2010 which is paid over the whole lifetime of a project. It can thereby be contrasted to current CO 2 prices and future expectations. Doing so, we see that in India and Thailand the gap is far above current and historic prices, whereas in Brazil and Egypt the gap is in a similar order of magnitude of today s carbon prices. Similar as in the energy-specific gap, in the absence of grid connection cost, wind projects in Brazil and Egypt would already be profitable with current carbon prices. In Kenya and Nicaragua the negative gap seen in energy-specific terms also transforms into a negative carbon-specific gap. In Figure 3c, the total annual financial gaps can be compared to the resources that will be provided by the international community (e.g. GCF). In order to financially support wind projects in all the 6 countries under study, and thereby theoretically contribute to a 10 % share of wind in their electricity production, approximately 1 billion would be required annually. This compares to roughly 1.4 % of the GCF s annual resources of 100 billion USD. Similarly, in order to support solar PV in the 6 countries, 7.8 % would be required.

6 Fuel subsidies In Figure 4 the financial gaps in Egypt without and with fuel subsidies are depicted. As can be seen, fuel subsidies distort the competition significantly, which explains why only few wind projects are realised in Egypt (0.7 % of the national electricity production is generated from wind). On-shore wind in Egypt is almost as attractive as the baseline technology, but with fuel subsidies the attractiveness is lowered substantially. By the same token, the CO 2 -specific financial gap, i.e. the carbon price of 25 /tco 2 without subsidies is in an aspiring but realistic range, whereas a price of 56 /tco 2, assuming subsidies, is too high. Therefore, also the CDM has not been able to significantly support wind energy diffusion in Egypt (IGES, 2010). Figure 4 Energy-specific, CO 2 -specific and total annual financial gap in Egypt without (plain) and with (hatched) fuel subsidies. As our analysis is solely based on Egypt, where data is available, we cannot make statements about the other countries under study. However, in case the prices at which power generators procure fuel in these countries were available, the same calculation could be applied. In the light of our results, removing fossil fuel subsidies seems highly important and should thus be included in NAMAs. However, energy subsidy reforms are politically and socially a very complex process and thus occupies many organizations (e.g. GSI-UNEP, 2010). Discussion As we introduce a relatively easy replicable model, for the first time it is possible to indicate how much technology- and country-specific financial support requirements are needed for RET diffusion in non-oecd countries. Furthermore, the 10 % target share makes our results comparable across countries. In that context, important questions arise. First, how much of the financial gap should the international community (e.g. the GCF) finance, and what proportion should be raised domestically? Second, as support requirements differ greatly across countries, how will resources be distributed among them in a fair manner? Furthermore, with our results we contribute to the baseline discussion. In the sense of Okubo et al. (2011), our baseline approach could be employed as a measuring procedure for NAMA additionality. In that context, the advantage of our approach is that it incentivises governments to shift towards low-carbon alternatives, as additionality criteria cannot be breached by national energy policy. However, as our baseline approach does not capture the real financial gap, measures must be found to also support further actions such as fuel subsidy removal and energy market reforms. Such measures could also be included in NAMAs. Furthermore, in the context of NAMA formulation, countries with heterogeneous power sectors will face the challenge of formulating country-level NAMAs for region-level power sectors. Therefore, efforts to understand regional requirements are necessary. Moreover, it might also be an option to examine how different financial support mechanisms influence financial support requirements. As an example, lowinterest loans could be used to lower the discount rate, which in turn lowers the RET LCOE and financial gap. In summary, we provide a first model and first results which give robust and valuable support to national and international policy makers in the formulation of NAMAs and which are a starting point for further discussions of NAMA methodologies and procedures.