Dopantes

Overall, the findings confirm well-known challenges in the geothermal sectors (Siwage 2014). Investors face high exploration risks which are exacerbated by the absence of government guarantees to cover those risks. In addition, geothermal resources are frequently located in remote areas which makes connection to PLN grids costly. There is also a lack of human resources and capacity in preparing documents in a complex tender process. Lack of local capacity in project maintenance is a prominent factor. Moreover, there are problems in interpreting the regulations. Finally, the price of electricity is not economically feasible for IPPs to sell to PLN (Siwage2014).

The analysis in this and the preceding chapter have made it clear that the FIT regulations in Indonesia have not been effective. The main underlying factor is that PLN simply prefers to buy coal- or gas-fired generation which are cheaper than renewables. The utility does take coal- and gas-fired generation costs as benchmarks to set average BPP in all grids in Indonesia. In most off-grid areas, PLN relies on diesel-based generators to connect rural communities. Despite diesel being more expensive than renewables, it has

been subsidised for much of the period under investigation (1990–2015) so that PLN has only reluctantly taken up renewables in off-grid areas. It should also be noted that the potential for solar and wind varies across the archipelago. The costs of supplying integrated maintenance and supply systems might be a significant factor that prevents the utility to switch to renewables in remote islands.

Essentially, the design of past and current FIT regulations could not resolve the following dilemma: on the one hand, the Indonesian FIT does not act as a premium price sufficiently attractive to many IPPs, while on the other hand, PLN is in many cases not willing to buy renewables at the mandated tariff rates because it has cheaper options available. Thus, the FIT is a purely price-based instrument without a legally binding obligation for the utility to meet a quantitative RE target.

Figure 4.2 provides an intuitive economic analysis to illustrate the effects of the FIT in the Indonesian RE market, including both SMPPs and geothermal power. The RE supply curve (S curve) represents the quantity of RE IPPs are willing to supply to the grid, with increasing prices incentivising more players to enter the market. Changes in the cost structure of renewable technologies could push the supply curve up and to the left, reducing the quantity at a higher cost. Conversely, lower costs would push the curve down and to the right, increasing the supply of renewables. An example for the former case would be geothermal technology which has high fixed costs and faces many regulatory uncertainties. Solar power technologies are an example of the latter case, as global costs have come down considerably, but this has not yet translated into lower costs in Indonesia due to regulatory uncertainties associated with the FITs.

Figure 4.2: Feed-in tariffs and supply of renewable energy

Currently, PLN is only willing to buy renewables at price PBPP, a level that presents the utility’s average BPP, resulting in a quantity of RE QBPP. Note that this represents the

maximum amount of RE PLN is willing to buy: as discussed in the previous chapter, FIT regulations have for a long time not mandated specific tariff levels but set purchasing prices as a percentage of PLN’s production costs.

Since 2009, FITs for both geothermal and SMPPs were set at fixed prices for PLN to buy renewables. These tariffs were set above PLN’s average production costs, which are largely driven by coal and natural gas-based generation costs. PFIT and QFIT would

represent the optimal quantity of renewables that would be achieved in the market if the utility would buy at the mandated FIT levels. The empirical and historical analysis provided so far suggests the utility is only willing to buy or invest in renewables at an amount somewhere between QBPP and QFIT and treating themandated FIT at PFIT as a

ceiling price, with room to push for an even lower price when negotiating PPAs with IPPs.

If the FIT would be designed as a true premium price, at PFIT*, then QFIT* denotes the

quantity of renewables that would be delivered by IPPs in the market. Arguably, this

Price (IDR/kWh) Subsidy to bridge cost cap PFIT* PFIT PFITQ Q PBPP

Coal-driven production cost Full economic cost

QBPPP p

QFITQ QFIT _{QFIT* Quantity (MWh)}

S

premium price could be set at a level that represents the ‘true’ economic cost of fossil fuel–based power generation, which includes the significant cost of fossil fuel subsidies (see Chapter 5) and the environmental damage costs of coal-based power generation. Thus, the difference between PBPP and PFIT* would constitute an ‘incremental cost gap’

(Castlerock 2011) or the subsidy needed to bridge the cost between PLN’s supply cost and the premium FIT.

The shortcomings of the Indonesian FITs confirm some of the main disadvantages associated with this instrument, which are documented in the literature. First, the size of the incremental cost of supporting FIT schemes can be a significant barrier to effective design. Huenteler (2014) found in the case of Thailand that these incremental costs can be quite substantial, estimated at around US$21 billion or 3.2 per cent of GDP in 2012. Looking at the case study of setting up a global FIT fund in Tanzania, Rickerson et al. (2013) found that mitigation of project development and financial risks would be the primary objectives to enable a FIT scheme. In short, setting up FIT schemes requires substantial funding from government, private sector and international donors.

Second, incremental costs to support FIT regimes do exhibit significant uncertainty, as they are largely driven by the savings obtained from avoiding costs of fossil fuel consumption. However, coming up with estimates of counterfactuals (e.g., built power plants and fuel types consumed in the absence of renewable power generation) that are acceptable to the domestic government requires a long process of policy learning and experimentation. Moreover, this uncertainty affects the design of a FIT schemes, as donors might be unwilling to commit to backing FIT schemes, if they do not know the required size of the financial flows. Investors might also hesitate if no guaranteed long- term support commitment in place (Huenteler 2014, p. 870).

Given the ineffective use of FITs, should other policy instruments be considered? A body of literature suggests that an effective promotion of RE is not a matter for prioritising one instrument over others, but that the right mix of policy instruments matters. Davies (2012) makes the case for combining RPSs with FITs. In many ways, both instruments complement each other, thereby allowing policymakers to reap the benefits of regulatory synergies (Davies 2012, p. 313). PRSs focus on quantity-based targets and thus provide accountability in both policy and regulatory terms. FITs, as discussed

earlier, are price-based instruments and could complement RPSs with market certainty by setting an upfront cost of compliance and guaranteeing the purchase of renewables- based electricity (Davies 2012, p. 313).

Quota obligations for utilities have been used in various countries and are known as RPSs in the US, RESs in India, Renewables Obligations in the United Kingdom, and Renewable Energy Targets (RETs) in Australia (IPCC 2011, p. 895). Under these quota systems the utility is obliged to take up renewables into the grid and any additional costs can be passed on to the consumer.

Several studies suggest that RPS work well in combination with other policies and in long-term settings. Carley (2011) undertook a comparative scenario analysis of state- based policies in the US and found evidence that RPSs in combination with another instrument—a carbon price—is more effective in reducing emissions than when applied alone. Fischer (2009) argues that RPS are essentially a combination of both a subsidy (given to RE producers) and a tax (imposed on producers on fossil fuel–based energy suppliers). The impact of RPS on electricity prices depend on the size of the tax and subsidy effects, which in turn depend on the elasticity of supply curves in renewable and non-RE markets. Most studies suggest that if there are rigidities in natural gas supplies, then RPSs will lower consumer prices. This might be relevant for the Indonesian context where much of the generated electricity is highly dependent on domestic natural gas production. Finally, evidence from US-based literature suggests that RPSs are particularly effective in creating green investment and business, if they are allowed to persist in force for a number of years (Bowen, Park & Elvery 2013).

So how could PLN be incentivised to take up more renewables in the future? Clearly, as a purely price-based mechanism, past and current versions of Indonesian FITs did not work because PLN was not obliged to take up a legally binding quantitative target of renewables. In Indonesia, future policies could strengthen the effectiveness of FITs with RPSs for the utility. Looking at Figure 4.2, such a quantitative target could be curve S1 which lies between PLN’s preferred price at PBPP and PFIT, resulting in a price level at PFITQ.

It would still not be a tariff which reflects the full economic cost of renewables, but recent reforms have made electricity tariffs more cost reflective and made the utility less dependent on the PSO subsidy (see Chapter 5). In future, these tariff reforms should

put PLN in a better position to take up renewables at prices closer to the premium level, especially with costs of solar and wind power falling.

4.5

Conclusion and outlook

This chapter has provided an analysis of the geothermal policy framework, focusing on three aspects. First, it gave an historical analysis of the policy and regulatory framework governing the geothermal sector since the 1990s, finding that FITs have only really played a role since 2009 as part of a broader, complex regulatory and investment climate context. Despite being the only RE sector governed by laws, Geothermal Laws No. 27/2003 and then No. 21/2014, implementing regulations were not consistent, thereby increasing investment uncertainty in the sector. Regulatory barriers included overlapping administrative processes with regard to processing forestry licenses, land permits and environmental impact assessments. These were aggravated by the unclear allocation of responsibilities between central and regional government in processing geothermal licenses.

Second, based on interviews with geothermal IPPs and policymakers, the chapter presented the key issues and challenges associated with the implementation of the geothermal FIT regulations, focusing on the period 2009–2015. Like in the case of SMPPs, the design of the geothermal FIT instrument is deemed ineffective by most stakeholders due to a mix of inadequate tariff levels and wider regulatory and investment climate risks. Moreover, geothermal FIT regulations are tied to a competitive tender mechanism for project developers. Much of the uncertainty stems from the unclear relationship between the geothermal FIT price and the tender mechanism, which resulted in lengthy negotiations between PLN and geothermal producers.

Third, the chapter presented an intuitive economic analysis to capture the effects of the Indonesian FIT regime—both for the geothermal IPPs and SMPPs—on the supply of RE in the Indonesian electricity sector. Specifically, it addresses the core dilemma of the Indonesian FIT regulations for both geothermal IPPs and SMPPs: mandated tariff levels are not set at a premium rate high enough to attract most IPPs, while at the same time PLN perceives the prevailing FITs as too costly relative to cheaper coal-based generation options.

Increasing the effectiveness of future FIT regimes depends to a large extent on the financial conditions of PLN and the price competitiveness of renewables vis-à-vis coal and gas. Policymakers have recognised that the design of an effective FIT regime must acknowledge this ‘incremental cost gap’ between renewables and thermal generation. In the geothermal sector, reforms since 2014 have moved the FIT regime from a purely production cost-based FIT to competitive tender-determined ceiling tariffs based on avoided costs. However, if increasing renewables is a serious goal for policymakers, then a price-based instrument like a FIT must set a sufficiently high premium price or a mandatory quantitative RE target should be set for the utility.

Overall, the Indonesian experience with implementing FIT regulations suggests that their shortcomings confirm some of the main disadvantages associated with this instrument which are in line with similar studies in the literature. These problems mainly relate to uncertainties regarding the size and the stream of the incremental cost of supporting FIT and determining the appropriate level of tariffs to attract IPPs, especially within a policy context of a state utility exercising its leverage as a single buyer on the grid.

A body of literature on energy policy instruments suggests that the Indonesian context warrants the application of a right mix of instruments rather than prioritising one instrument (e.g., FITs) over others. Future policies could strengthen the effectiveness of FITs with RPSs for the utility. This would combine the incentives of a price-based instrument with the policy accountability associated with a quantity-based RPS.