Regional analysis

Table 6.6 shows that most regional costs in 2028 under RUPTL would be lower than regional costs in 2017. Figures 6.7.a and 6.7.b show that there is a significant decrease in the share of oil-based electricity production in all regions from 7.5% of total electricity production in 2017 to 1.6% of total electricity production in 2028. Several exceptions are Riau Archipelago, Maluku and West Papua because electricity productions from oil PP and OCGT in these regions are still relatively high. This situation will not only add a financial burden to electricity subsidy but also to government efforts of providing a single oil price for transportation uses in all regions (MEMR, 2016c). Similarly, almost all regions under the emission reduction scenarios have lower generation costs than that in 2017. One of the exceptions is North Maluku that lacks hydropower potential, so it must rely on high-cost CCGT and oil PP to meet the emission limits.

Table 6.6 Regional electricity generation costs (USD/ MWh)

Regions 2017

2028

RUPTL 11%

Scenario

14%

Scenario

1: Sumatera 121.4 68.6 81.8 83.5

2: Riau Archipelago 157.3 129.5 113.8 117.7

3: Bangka Belitung 200.3 92.0 88.2 88.2

4: Java, Madura & Bali (Jamali) 71.8 63.6 63.5 63.2

5: West Kalimantan 91.0 55.3 61.9 63.3

6: South Kalimantan, East Kalimantan, North Kalimantan & Central Kalimantan

116.3 58.5 66.2 66.2 7: North Sulawesi & Gorontalo 122.6 62.8 82.5 78.2 8: South Sulawesi, Central Sulawesi & West

Sulawesi

71.0 53.0 60.4 60.7

9: Southeast Sulawesi 155.1 57.1 63.8 64.4

10: West Nusa Tenggara 136.8 65.8 93.7 80.6

11: East Nusa Tenggara 122.9 60.3 74.0 74.4

12: Maluku 139.0 118.1 81.2 85.4

13: North Maluku 145.4 76.9 176.6 186.5

14: Papua 126.5 73.9 68.5 71.0

15: West Papua 127.0 115.7 93.0 89.6

(a) 2017 (b) RUPTL in 2028

(c) 11% scenario in 2028 (d) 14% scenario in 2028

Figure 6.7 Regional electricity production mix

Note for regional electricity systems: 1. Sumatera; 2. Riau Archipelago; 3. Bangka Belitung; 4. Java & Bali; 5.

West Kalimantan; 6. South Kalimantan, East Kalimantan, North Kalimantan & Central Kalimantan; 7. North Sulawesi & Gorontalo; 8. South Sulawesi, Central Sulawesi & West Sulawesi; 9. Southeast Sulawesi; 10. West Nusa Tenggara; 11. East Nusa Tenggara; 12. Maluku; 13. North Maluku; 14. Papua; and 15. Papua Barat.

A comparison of our study with that of Handayani et al. (2017) for the Jamali region under the 14% emission reduction target is presented in Table 6.7. Findings in this study suggest that a lower share of fossil-fuelled electricity production and, consequently, a higher share of renewable energy production than that proposed by Handayani et al. (2017). As a result, this study contradicts the findings by Handayani et al. (2017) who found increasing costs in the Jamali electricity system due to emission reduction targets. This study found that the target could reduce electricity generation costs in Jamali region by 0.4 USD/ MWh compared to RUPTL, as shown in Table 6.6. Handayani et al. (2017) estimated the cost for CO2e

reduce the cost by 1.31 USD/ tCO2e in 2028. The comparison is conducted over different years because Handayani et al. (2017) did not provide results for 2028.

Table 6.7 Result comparisons

Results Handayani et al. (2017) PowerGen-ABM

Emission reduction 14% 14%

Analysis year 2030 2028

Coal share (%) 63.00 49.29

Natural gas share (%) 17.00 10.15

Geothermal share (%) 10.00 16.45

Hydro share (%) 4.00 7.29

Wind share (%) - 16.75

Oil share* (%) - 0.04

Biomass share⁺ (%) 6.00 0.02

Cost-effectiveness of CO2 mitigation (USD/ tCO2e) 17.70 -1.31 Note: ^* rounded to zero; ⁺ including waste to energy

6.4 Discussions

6.4.1 Policy implications

All scenarios suggested that coal is still the most cost-effective option in the Indonesian electricity sector, as shown in Figure 6.4. This finding calls for the accelerated commercial implementation of clean coal technologies, which are currently being piloted and researched in the country. However, this does not mean that PLN should only rely on a high share of clean coal technologies and reject the use of high-cost renewables. International coal prices have continuously increased since 2017 (MEMR, 2018a, Insider, 2019), and the Indonesian government relies on this to increase coal exports, improve the trade balance, and bolster foreign income. Hence, it potentially puts a pressure on domestic coal prices.

Renewable energy is the most cost-effective option in the long term. Renewable energy may have higher costs in the short term, but the costs still can be covered by the reference tariffs that are relatively high due to the high share of oil-based electricity production.

Renewables can significantly reduce electricity generation costs in regions, which are still planned to retain a high share of oil-based electricity production in RUPTL. Therefore, power plant expansion plans in RUPTL should be adjusted by minimising oil PP share and maximising renewables, especially geothermal, wind energy, and micro-hydro.

However, the main problems hampering geothermal are non-technical issues. Several examples of the problems causing the delay or cancellation of geothermal projects in Indonesia

are regulation conflicts, especially with forest protection regulations, and rejection by communities. Consequently, geothermal development during the premium feed-in tariff (FIT) policy regime has not followed the path expected.

Analysis results in this study, suggesting a more significant role of wind energy in Indonesia’s electricity system (see Figure 6.4), is supported by increasing global wind energy production (REN21, 2018). Indeed, many developed countries can achieve wind turbine targets over geothermal targets, indicating the lower risk of wind energy projects (Al Irsyad et al., 2019b). Wind energy is also considered the most sustainable technology (Suomalainen and Sharp, 2016). Nevertheless, Indonesia does not have adequate skills and expertise to develop wind turbine power on a significant scale. PLN and several state-owned institutions have had wind turbine pilot projects in place for several years, but the performance of the projects did not meet expectations, and most have been closed. Reflecting these circumstances, our findings regarding wind energy capacity in 2028 (as in Figure 6.4) should be viewed as an ideal share of wind energy capacity and, therefore, it should act as a guide for policy formulation and research. This situation should alter in the near future with UPC Renewables, an investor from the United States, beginning to produce electricity from a 75 MW wind farm in Sidrap, South Sulawesi from April 2018 (construction started in 2015). This successful project at least will be followed by a 50 MW wind farm, Sidrap II, and a 72 MW wind farm, Tolo I, in South Sulawesi. Moreover, with 3.25 million km² of sea surface, Indonesia has substantial off-shore wind energy potential (Roza, 2017). Off-shore wind turbines have more stable electricity production so off-shore wind turbines are predicted to grow at a faster pace than on-shore wind turbines (Perveen et al., 2014, Bilgili et al., 2011). PLN also has drastically changed their wind energy target from 92.4 MW in RUPTL 2016 – 2025 to 1,450 MW in RUPTL 2019 – 2028 (PLN, 2019, PLN, 2016b).

The next most cost-effective renewables are hydro PP and MHP, as suggested by all scenarios. The differences are that the emission reduction scenarios suggest higher electricity production from MHP and, at the same time, lower production from hydro PP. MHP industries, operating in small villages and isolated areas, often feel threatened by PLN’s grid expansions since their customers will likely shift to PLN’s electricity supply. Those industries cannot afford and do not have the resources to protect their market or to sell their electricity to PLN (moves that would attract high-cost business permits and commissioning). These problems need government intervention and also innovative funding, such as block chain technology (Mengelkamp et al., 2018, Basden and Cottrell, 2017).