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Rural Electrification in Indonesia:
Can the Benefits of Micro Hydro
Trickle Down to Rural Communities?
A Case Study of Nias Island
[DRAFT]
Energy Economics & Policy
Prof T. Rutherford
Ratri Sryantoro
10-938-976
1
1 Introduction
Over the past decade, Indonesia has shown remarkable growth following the deep financial crisis
which affected most of Asia during the period of 1997 – 1998. Recently, Indonesia’s economy again
proved its resilience in escaping relatively unscathed following the global financial crisis charting
phenomenal GDP growth rates of 6.2% in 2010, boosting it to become the region’s largest economy
1. However, this rapid growth did not come without a price. Despite increasing GDP levels, the
electricity sector has been unable to keep up with the rapidly growing demand. In the past five
years, the demand of electricity has grown by 6% across the country. In contrast, the aggregate
electricity generation capacity has only grown by 2% over the same period.
The state-owned power utility Perusahaan Listrik Negara (PLN) currently places Indonesia’s
electrification ratio at only 65%. This figure is amongst the lowest in the South East Asia region
(Jayawerdana & et al., 2005). In 2005, the World Bank with the Government of Indonesia (GOI)
commissioned a study to identify options for increasing electricity access in Indonesia. The report
identified three significant barriers to achieving a higher electrification: inability to recover costs of
distribution, lack of financing sources, and coordination and process streamlining (Jayawerdana & et
al., 2005).
To eradicate the nation’s energy poverty, the GOI has set an ambitious target of reaching an
electrification ratio of 90% by 2020. Many are sceptical of how realistic this is, given the vast spatial
dispersion of its population across 17,000 islands. Much of the population still live in remote rural
areas that are currently serviced by low-voltage (20kV) power lines. Such infrastructures are typically
very susceptible to adverse weather conditions, and they provide a poor quality of supply (Haanyika,
2005) . Furthermore, out of 70,192 villages across the country, 6,200 villages are technically very
difficult to reach through grid extension (Kusidana, 2008).
Rural electrification has long been a thorny issue in the electricity sector in Indonesia. The financial
strain on PLN due to the ballooning cost issues, has greatly limited their capacity to invest in high
capital cost projects with low economies of scale, such as rural electrification. In 2001, following a
corporate restructure the rural electrification division was disbanded. To worsen the matter, policy
landscape in the electricity sector is currently in a state of flux following a failed attempt to liberalize
the electricity market in 2002 (Jayawerdana & et al., 2005).
Most of PLN’s capital works projects are now focussed towards increasing generation capacity and
upgrading the busiest transmission grids in Java, Bali and Sumatra which often experience
1 Indonesia’s 2009 GDP is $540.7 billion according to The World Bank figures
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bottlenecks. This has left rural electrification projects to be completed by various NGOs in a rather
ad hoc manner, without nationwide co-ordination. So, the critical question is, if high cost is the
primary barrier to rural electrification, is there an optimal mix of technologies that can be deployed
to ensure the least cost electrification program?
This paper aims to investigate the costs of achieving the 90% electrification target by 2020 based on
three options for rural electrification. These options include: grid extension, off-grid generation and
household solution using battery charging (Siemons, 2001). As a case study, we will look at a small-
scale example of rural electrification strategies and costs, based on the Island of Nias located in
North Sumatra province. The island was severely damaged by the 2004 tsunami and earthquake
events. The local government has spent much of the last 6 years rebuilding its infrastructure, but
power deficit remains the main barrier for inhabitants to return to their income-generating business
activities. We will focus on micro hydropower as an option for off-grid generation given presence of
large number of rivers across the island. Furthermore, the Ministry of Energy & Mineral Resources
claimed that there are 450MW potential for micro hydro power across Indonesia and have recently
identified it as a favoured solution for rural electrification (Kusidana, 2008).
In Section 2 a brief background on the electricity sector in Indonesia and the state of rural
electrification is presented. We visit the key challenges of rural electrification and possible
technological solutions. We also look into the potential of micro hydropower and its suitability for
remote area generation. In Section 3, we analyse the key needs of electricity sectors in Nias Island
and discuss previous studies concerning potential for micro hydropower generation in the area. We
then present a simplified economic model for calculating the lowest cost options for electrification
of Nias in Section 4. Section 5 will present a discussion of the results. Finally, Section 6 concludes
with a summary of the key findings, drawbacks and limitations of the study and recommendation for
future studies.
2 Background
2.1 Electrification in Indonesia: the enormous task of providing access to
230 million across 17,000 islands
In Indonesia, the 1945 State Constitution regulates that all vital utilities concerning the greater
population must be controlled by the state. Since 1985, the electricity sector in Indonesia is
controlled by the state-owned power utility business Perusahaan Listrik Negara (PLN). After its
formation, PLN became the sole responsible body for the provision of electricity across Indonesia.
3
The Ministry of Energy & Mineral Resources serves as the policy making body and regulator for PLN.
However, other ministries within the GOI also serve as stakeholders providing different governing
and support functions. In a bid to boost electricity generation capacity to keep up with demand
growth, the GOI recently opened up the generation market for competition. Independent Power
Producers can now produce electricity, but are required to sell the electricity back to PLN for
distribution. Figure 1 shows the schematic of key players in the Indonesian electricity sector.
Despite having significantly developed its generation, transmission and distribution network over the
years, the national electricity network remains significantly strained. Growth in generation capacity
has been unable to keep up with electricity demand growth. Since 2009, the Java-Bali transmission
grid is particularly congested, leading to “transmission bottlenecks” which often forced PLN to
impose rolling blackouts across the two islands.
Today, with an electrification ratio of 65%, more than 70 million people still do not have access to
reliable and affordable electricity services (Jayawerdana & et al., 2005). Of this figure 80% reside in
rural areas and almost all live outside of the most populated islands, Java and Bali. Figure 2 shows a
clear evidence of this situation, where the northern and eastern parts of Indonesia are particularly
suffering from lack of access to electricity.
Despite having these official figures, it has been very difficult to quantify the real progress in rural
villages only since the disbandment of PLN’s rural electricity division. The Ministry of Energy &
Mineral Resources maintains that only 16.7% of rural villages have no electricity access. However,
the definition of ‘electrified’ means that at least one location within the villages are connected to
PLN’s low voltage grid. A clearer indication of true electrification ratio would be the number of
electrified households. Unfortunately to date this data has been unavailable.
4
Figure 1. Key players in the Indonesian Electricity Sector (Source: DE&P, 2008)
Figure 2 Percentage of electrification ratio per province (Source: DE&P, 2008)
.
2.2 Key challenges in Indonesia’s rural electrification
2.2.1 Oil Domination
One of the primary challenges in Indonesia’s energy sector is overcoming its high level of oil
dependency. Over the past three decades, the government has provided significant fuel subsidies in
a bid to increase access to cheap fuel to the whole population. This has resulted in the current
primary energy mix which is heavily dependent on oil (52.5% of primary energy source). Not only
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does this subsidy come at a high cost ($11.5b per year it also discourages fuel efficiency and can
hamper the development and uptake of renewable energy technologies.
The negative effects of Indonesia’s reliance on fuel subsidies are clearly present in the electricity
sector. The current national generation capacity sits at 30,320 MW. 35% of these facilities are fossil
fuel thermal power plants located on the six main islands and fuelled by oil, coal and natural gas
(PLN data 2007). Smaller scale oil-fired diesel power plants are typically used in rural areas due to its
compactness and low investment costs. Despite their low efficiency and negative environmental
impact, diesel power plants remain the most attractive option given the levels of fuel subsidy. With
such high dependency on oil and petroleum products for energy generation, PLN’s operating costs
have blown up in recent years due to steady increases in oil prices.
2.2.2 Lack of investments
Lack of energy services often correlates with poverty particularly in rural areas. It hinders people
from performing efficient income generating activities, which may help break the poverty cycle
(Kemmler, 2006). This is reinforced by the lack of financing from PLN, and their inability to
incentivise the private sector to invest in the electricity sector.
Prior to the Asian financial crisis, PLN enjoyed full financial support from the government and were
still generating profits. This allowed PLN to significantly invest in high capital cost investments such
as rural electrification. Post crisis, government investments were significantly reduced yet PLN are
still obliged to maintain a positive margin as a corporation2. Under such constraints, PLN was forced
to disband non-profitable investments such as access maximization and rural electrification. PLN’s
current investments are primarily focussed on projects aimed at loss minimization in its existing
grids, mainly in Java, Bali and Sumatra. As a result, investments in rural electrification have taken a
back seat for many years and have only marginally improved from 60% in 2000 to 65% in 2010.
2.2.3 Inability to Recover Costs of Distribution
PLN’s largest issue to date still remains its inability to recover costs of distribution. Electricity theft,
low labour productivities and inefficient aging grid infrastructure are the main contributors towards
PLN’s growing losses.
In a bid to make electricity affordable to the greater population, the Ministry of Energy & Mineral
Resources set a low uniform tariff structure set (US$0.06 per kWh in 2010). However, given the
lower demand and customer densities in rural areas particularly outside of the Java-Bali grid, the
2 Under GOI Law 19/2003, State-Owned Enterprises must operate on a commercial basis and make a profit.
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cost of distributing electricity in these areas is much higher than the set tariffs. These factors have
resulted in unsustainable revenue levels which are insufficient to cover PLN’s costs of distribution.
2.3 Moving forward: legislations and targets
The GOI recently set the 90% electrification target by 2020, as a subset of Vision 2025: Building New
Indonesia strategy3. To achieve this target, a clear framework needs to be implemented to reform
the electricity sector away from the PLN’s current inefficient and financially unsustainable business
model. To support this vision, a number of regulations have been in issued as a policy framework in
achieving this target.
Appendix 1 outlines a summary of current regulations relevant to rural electrification. The first key
piece of legislation was the (now annulled) Law 20/2002, which attempted to pursue the unbundling
of PLN’s services to introduce competition into the electricity sector. Following its annulment, this
was replaced by the Government Regulation 26/2006 which is a ‘reduced’ version of the previous
law, to allow local government and private parties to participate in rural electrification efforts.
In conjunction with 26/2006, under the Ministerial Decrees 1122/2002, 01/2006 and 02/2006, small
cooperatives and local enterprises are now permitted to operate small-scale (<1MW) and medium-
scale (up to 10MW) power plants and sell the produced electricity to PLN for distribution. However,
these regulations still do very little in incentivising private parties to participate. According to the
pricing structure under these decrees, PLN is only obliged to purchase the power at 80% utility
production cost when the plant is connected to medium voltage network and 60% when connected
to low voltage network.
Despite having not yet published a decree focusing on rural electrification, in 2008 the Ministry of
Energy & Mineral Resources published a draft Rural Electrification Program which proposes
guidelines for off-grid electrification in rural areas (Kusidana, 2008). The program proposes that
moving forward:
• The proportion of diesel power plant in rural electrification is to be reduced and priority is to
be given to locally available renewable energy resources specifically microhydro, wind and
solar photovoltaic
• Central and Local government are obliged provide a budget for rural electrification, including
establishment of local institutions to carry out operation and maintenance of plants
3 Vision 2025 Building New Indonesia is a long-term development plan published by the National Development
Planning Agency (Bappenas). It lists a set of targets to achieve by 2025 focusing in the areas of economics,
poverty eradication, and equal access to vital utilities across the nation.
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• The GOI will commit a budget of US$43m towards renewables based rural electrification
Furthermore, the Directorate General of Electricity and Energy Utilisation are currently carrying out
ongoing discussions regarding financing and tariff structures for rural electrifications.
2.4 Potential for rural electrification
According to (Siemons, 2001) rural electrification is characterised by areas that are remotely located
from large-scale electricity grids and show a need for installation of small power capacities.
Furthermore, the consumers are typically quite dispersed and have low consumption pattern.
Hence, rural electrification generally requires generation facilities to be operated at low load factors
(Haanyika, 2005), with a capacity between 10 – 200kW.
Naturally, there are three options for rural electrification:
• Extension of existing grid. Usually associated with high capital cost and still associated with
electricity theft risks
• Small isolated grid, powered by small-scale generator. This is usually associated with high
initial investment cost, but the lowest ongoing annual maintenance cost and levelised cost
of energy (LCOE). A comparison of different technologies for small-scale local generation
technologies is given in Appendix 2 (Holland & Derbyshire, 2009).
• Provision of batteries at household levels, which can be charged at the local charging station
powered by the small-scale generator
2.4.1 Microhydro power: the perfect small-scale generator for rural communities?
Given the guidelines of the draft Rural Electrification Program, micro hydropower plants (MHPP)
have the potential to become the generator of choice for remote rural communities, as it is a
relatively mature and successful technology. Micro- and pico- hydro plants of various scales (5 –
100kW) have successfully been installed globally, particularly in rural communities in developing
countries such as China, Nepal, Vietnam and many South American countries. Hence, MHPP is
associated with a lower perception of investment risks and has the potential to attract a larger
number of investors than other generation technologies.
MHPP has the advantage of reducing the dependency on fossil fuels and reducing the negative
environmental and health effects associated with use of diesel power plants. It has relatively low
technological and infrastructure requirements as it does not require dam or reservoir storage as it
relies on minimal water flow typically available all year round. Construction of MHPP is also
8
relatively simple compared to larger hydro power plants, as it can be done by manual labour without
the need for complex engineering equipment or access roads to the site.
A typical size MHPP is 100kW and can be operated at low capacity factor, but would still be sufficient
to meet the electricity demand of an average Indonesian village 4. Furthermore, UNDP has identified
that Indonesia would have a capacity of 458MW, and only 4% has of this figure has been harvested
(UNDP Indonesia, 2009). . These theoretical figures make MHPP an attractive choice for use as small-
scale generator to serve both as an isolated grid and battery charging station. This paper aims to
assess the economic feasibility of constructing MHPPs at the identified potential sites and whether
it makes economic sense to solely rely on MHPPs for rural electrification? If not, what is the best
technology mix that will minimise the total cost of electrification to a rural community given the
spread of their location?
3 Nias Island: a case study
3.1 Rebuilding after the tsunami
Nias is the largest Island in a group of islands located off the west coast of Sumatra. It falls under the
jurisdiction of the North Sumatra province and is divided into two administrative areas: Nias and
South Nias. The island is home to 711,976 people living across its 21 regions. Following the
2004/2005 Boxing Day earthquake and tsunami events, Nias suffered extensive destruction with at
least 80% of its already weak infrastructure damaged (Bureau of Statistics of Indonesia, 2005).
The primary industries in Nias include agriculture (rubber and palm oil), livestock farming, tourism,
and fishery – all of which are dependent on electricity supply for production. Nias has long been
known internationally as a prominent cultural tourist and surfing destination. Hence following the
tsunami, a large number of international agencies poured into the island to aid reconstruction
efforts. Much has been achieved in the past six years, but yet thousands still live in refugee camps
throughout the island. The remoteness of the island proves to be the greatest challenge for the
reconstruction process, as supply of construction materials are difficult to obtain. Furthermore,
there is insufficient road network across the island preventing access to many of the damaged
villages.
Nias Island was selected as a case example for this paper due to a number of factors:
• The remoteness of the island allows a proper analysis of an ‘isolated electricity network’;
4 According to (Holland & Derbyshire, 2009) a typical Indonesian village would contain 155 households and
require 225kWh of electricity per day.
9
• There is scope to test the optimal reconstruction scenario since most of its electricity
infrastructure was damaged due to the 2005 earthquake;
• Reasonable amount of data is publicly accessible for the purposes of this study.
Figure 3 Nias Island geography and electricity supply profile
3.2 Current electricity grid
The PLN electricity network in Nias is split into two grids: Nias and South Nias, as depicted in Figure
3. The Nias grid is supplied by a diesel power plant located in the capital Gunung Sitoli (4.5MW),
whereas the South Nias grid is supplied by another diesel power plant in Teluk Dalam (2.3MW). The
electrification statistics in Nias Island are as follows:
Area Number of
cities / villages
Number of
households
Village electrification
ratio
Total electrification
ratio
Nias 443 83,276 70.33% 60.85%
South Nias 214 50,873 48.37% 59.06%
Table 1 Electrification statistics in Nias Island (PLN North Sumatra, 2007)
Nias is currently experiencing power deficit of 6.4 MW as the generation facilities are unable to meet
demand. The primary issue faced by PLN Nias is its inability to recover costs, caused by (Nias Online,
2008):
• Growing cost of maintenance on aging infrastructure as both plants have now been
operating for 30 years 5
5 Commercial lifetime is typically 18 years
10
• Increasing fuel costs due to increasing oil price, amounting to US$1m per month
• Electricity theft and a large number of customers that are unable to make electricity bill
payments, resulting in a monthly revenue of just US$250,000 6.
In 2008, PLN Nias was forced to start implementing rolling blackouts across the island. Total
blackouts across the island often occurred whenever any maintenance activities or equipment
outages were carried out. This significantly damaged the economy of Nias as many small businesses
were unable to maintain levels of income-generating production capacity. Some businesses reverted
to purchasing dirty and expensive diesel generators in order to maintain their electricity supply. As a
temporary quick fix, in 2010 PLN Nias engaged with Independent Power Producers to purchase
additional 8 MW of generation capacity. Additionally, PLN’s 2010 – 2019 capital expenditure plan
includes the addition of 2 x 3 MW coal-fired power plant in South Nias to accommodate for demand
growth. (PLN , 2010)
Electricity throughout the island is distributed using low-voltage (20 kV) power lines. The existing
transmission grid is depicted in Figure 4. It is visible that the grid in the South Nias and western parts
of Nias is still very sparse. Furthermore, with lack of access roads in these areas it is technically very
difficult for PLN to extend the existing grid.
6 However, typically a grace period of 3 months is still given before disconnection, thus accruing a backlog of
losses for PLN
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Figure 4 Electricity Distribution Map in Nias Island
3.3 MHPP in Nias
With hundreds of rivers with sufficient heads flowing through the island and an annual rainfall of
2,930mm, Nias has great potential for installation of MHPP across the island to provide independent
local generation for remote rural communities. A study commissioned by UNIDO 2005 identified
potential sources for MHPP location at 11 points along rivers across the island (United Nations
Industrial Development Organisation, 2005) 7. Figure 5 shows the locations of these sites.
7 A feasibility study of four sites confirmed potential of 242 kW. A conservative estimate of the potential
generation capacity of the other seven sites is approximately 340 kW.
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Figure 5 Identified potential locations for run-of-the-river micro hydro power plants in Nias Island
4 Model Specification
4.1 Analysis Framework
While efforts to maximise rural electricity access have long been undermined by PLN due to its
commercial unattractiveness, the GOI’s ambitious 90% target by 2020 has finally called for attention
to tackle this issue. Combined with the energy sector’s urgent need to reduce dependency on oil as
energy source, there is a real scope to finally propel the adoption of MHPP as small-scale generator
in rural communities and increase rural electrification ratio.
13
The objective of this analysis is to recommend a feasible power generation strategy to achieve 90%
electrification across Nias Island. The first analysis will look into the possible cost structures of the
island electrification, given the three options of electrification outlined in Section 2.4. For each of the
village to be electrified, they have to face the trade-off between the benefits of grid extension (lower
investment cost / higher operating cost), and MHPP (higher investment cost / lower operating cost).
Our hypothesis is that as costs of grid extension becomes too high with increasing distance, the cost
of generation with MHPP becomes more favourable and the villages will select the MHPP option. .
The objective function of this analysis is to minimise the aggregate cost of connection for all the
villages subject to the constraints of total available capacity from PLN generators, total available
capacity from all identified MHPP sites, and requirement to satisfy at least 90% of electricity demand
in the island. Several scenarios varying the capacity parameters are also carried out to observe the
model’s sensitivity.
In the second part of the analysis, we incorporate the household’s utility of consuming electricity
into the electrification strategy decision. The objective function here is to maximise relative utility of
consumption8, given their level of consumption or non-consumption
Due to the lack of data on household level, some assumptions needed to be made:
• Firstly, it is assumed that we only consider a scenario where a complete overhaul for the
electricity supply network in Nias is possible. We have not accounted a scenario where
households or villages that are already electrified can switch between types of generators.
• Secondly, as household data for electricity demand profile is also unavailable, the willingness
to pay for demanded electricity amount will be an exogenous variable arbitrarily assigned
depending on the size of villages 9.
• Thirdly, we assume that all present power plants, planned projects and MHPPs at previously
identified sites will be built. This assumption is further discussed in Section 4.2
• Finally, we have only assumed a one year scenario and have not included provision of
demand of growth or costs.
This electrification cost minimisation model should allow for a feasibility assessment on what would
be the best strategy for Nias’ electrification, by optimally selecting the right mix of electrification
options. The results of this model should be able to provide an insight of the significance of MHPP in
this electrification mix, and to what extent they can be utilised.
8 Relative utility of consumption is defined as utility of consumption of electricity per unit consumed [kW].
9 There will be two types of villages (small and large) based on the number of population, with each type of
village having a particular demand profile
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4.2 Capacity constraints
The capacity constrains assume the available generation facilities available for the period of model
analysis are outlined in Table 2. We assume that all planned additional generation work and all
identified potential sites for MHPP will be realised.
Power Plant Capacity Owner Status
Diesel PP – Gunung SItoli 4.5 MW PLN Operating
Diesel PP – Teluk Dalam 2.3 MW PLN Operating
Diesel PP – Gunung Sitoli 5 MW IPP Lease (assume until 2020)
Diesel PP – Teluk Dalam 3 MW IPP Lease (assume until 2020)
Thermal PP (Coal) - Simanere 6 MW PLN In PLN’s capital expenditure plan for
2012 (PLN Sumatera Utara, 2010)
Total Capacity from PLN Grid 20.8 MW
MHPP – Nias & South Nias 0.6 MW PLN Feasibility studies completed
Total Capacity from Isolated Grid 0.6 MW
Total generation capacity for Nias 21.4 MW
Table 2 Assumed total generation capacity available to Nias Island
We will denote these capacity constraints as the following:
�����: is total capacity of all fossil fuel power plants (diesel and coal) [kW]
���� : is the capacity of MHPP j [kW]
���� = ∑ ��������� : is the total MHPP capacity of the island from all 11 identified sites [kW]
4.3 Demand profile for electricity
Using guidelines from studies of rural electrification in Laos and Phillipines, we create a demand
function based on the village size, assuming that villages with larger population are likely to have
higher demand for electricity as they have more access and need to non-critical electronic goods 10
(World Bank IEG, 2008). Therefore we assume demand per household ����������is given by:
���������� �65���ℎ !"#$%&ℎ', )* $ +,-&)$% ≥ 80042���ℎ !"#$%&ℎ', )* $ +,-&)$% < 800
We can thus deduce a total demand per village which is given by:
10
The most critical electronic good is lighting. The most common non critical electronic goods are TV, fan, rice
cooker, mobile phones.
15
��: total annual demand in village i based on the number of households annually (kW)
4$ � : population of village i
Assuming that each household consists of 5 people, we have �� = ��567 ∙ ���������� ∙ 12.We will
assess demand for the entire island which consists of n villages. Furthermore, for simplicity we
assume that each household uses electricity for 4 hours per day on average.
4.4 Cost of electrification options
The cost assumptions in this analysis rely on estimates from a study of rural electrification in four
provinces in Indonesia by (Holland & Derbyshire, 2009). We will use “Levellised Cost of Energy”
(LCOE) as a normalised measure of electricity cost for different electrification options. LCEO allows
for evaluation of life-cycle energy cost and life cycle energy production. It can be used to directly
compare the alternative technologies with different operating time, investment cost and scale of
operation. The cost of using each electrification option is then defined by LCEO multiplied by the
quantity consumed (;�) by the village using that electrification option, measured in kW.
4.4.1 Option 1: Cost of grid extension
The capital costs of electrifying a village by grid extension will involve upgrading the LV networks and
auxiliary equipment (transformers, service drops and meters). Using figures from (Holland &
Derbyshire, 2009), the LCOE of grid extension (USc/kWh) is a linear function of distance from grid.
Table 3 outlines the LCEO as a function of distance from the power line.
Cost per kwh (USc/ kwh) Distance from main grid (up to x km)
7.1 5
13.9 10
20.7 15
27.4 20
34.2 25
41.0 30
47.7 35
54.5 40
61.3 45
68.0 50
74.8 55 Table 3 LCOE 'ladder' for electrification cost by grid extension
Therefore, we have the following parameters:
<�=>6? is the total cost of connecting village i by means of grid extension, which already includes
production and distribution costs
16
@�=>6? is the perpendicular distance between village i and power line [km]
A<BC�����@�=>6?' is the LCOE for grid extension (USc/kWh), as a function of distance @�=>6?
This results in the grid extension cost equation
<�=>6? = A<BC���� D@�=>6?E ∙ ;�=>6? (1)
4.4.2 Option 2: Cost of micro hydro
Using a 14.7 kW micro hydro generator unit, we assume the LCOE is 15.9 USc/kWh. This assumes a
capital cost of US$37,852 and annual cost of US$5,188 (Holland & Derbyshire, 2009). As outlined in
Appendix 2, MHPP is the lowest cost option amongst other isolated grid generator options. We will
ignore the cost of distribution as it is assumed that it is very small compared to the capital and
annual costs. We define A<BC���as the LCOE for MHPP (USc/kWh), we obtain the annual cost
equation for village i using MHPP: Furthermore, to ensure that MHPP are optimally used for local
generation, we introduce a distribution cost which increases as a function of distance from village to
grid (@���).
<��� = A<BC��� ∙ ;��� + 1000@��� (2)
4.4.3 Option 3: Cost of charging battery
For cost estimation of battery charging option, we use guidelines from a study of PV battery charging
station for remote communities in Lao PDR (Asian Institute of Technology, 2005). We assume the
use of 85Ah / 12 V battery for each household, which results in A<BCGHII��J of 35.4 USc/kWh.
Appendix 4 outlines the derivation of LCEO for battery technology. For battery technology we
include an additional constraint that it can only be used by villages located less than 10 km than the
micro hydro power plant, which serves as the charging station. To model this constraint, we use a
step increase in LCOE if distance to the MHPP (@���) exceeds 10 km.
Therefore we derive the cost of electrification using battery as:
<�KLMM = A<BCGHII ∙ ;�KLMM where NA<BCGHII = 0.354, )*@��� ≤ 10A<BCGHII = 0.7, )*@��� > 10 (3)
17
4.5 Model Specification
We are interested in minimising the cost (∑ <�S��� 'of the electrification program. Therefore our
objective function becomes:
T)%)#)U! ∑ <� =S��� ∑ min�<�=>6? , <��� , <�KLMM'S��� (4)
Subject to constraints:
Y;�=>6?S
���+Y;���
S
���+Y;�KLMM
S
���≤Y0.9��
S
���
(5) At least 90% of the island’s total electricity
demand is met
Y;�=>6?S
���≤ ����� (6) Capacity constraint of fossil fuel power plants
Y;���S
���+Y;�KLMM
S
���≤ ���� (7) Capacity constraint of MHPPs
;�=>6? , ;���,;�KLMM ≥ 0 (8) Non-negativity
4.5.1 Scenario 1: Base Case
First we consider a base case scenario with 12 ‘artificial’ villages of Nias with similar population
profile to the real data. Figure 6 shows the illustration of this problem.
Using Excel Non-Linear Solver, we obtain the least cost electrification strategy which can achieve the
90% electrification ratio target, as outlined in Table 4. The least cost strategy involves 8 villages
connected by grid extension and 4 villages connected to MHPPs. This results in a total cost of
$344,097
In total there are 4 villages that can be connected to MHPPs either through an isolated grid
connection or using it as a battery charging station. In this analysis we see that Village #5 will not
have access to electricity, except with the small possibility of obtaining 0.8kW from MHPP1 by using
it as a battery charging station. However this may indicate that there is a potential for Village 5 to be
connected to the isolated grid of MHPP 1 should the plant have increased capacity. We also see that
the capacities of both MHPPs are fully depleted, suggesting that the optimal least-cost option
require the existence of MHPPs.
We specifically chose total generation capacities (1010kW) that is less than the total demand
(1043W) to mimic the current situation in Nias. The results show that with the installation of the two
18
typical – sized MHPPs, 90% of the demand can be met and even leaving remaining capacity on the
PLN grid which can provide a safety margin of operation.
Figure 6 Least Cost Electrification Strategy for Scenario 1
Vi-
llage
#
Population Total
Demand
[kW]
Quantity
Consumed
[kW]
Dist to
Grid [km]
Selected Option Cost of
electrification
[$]
V1 876 75.9 75.9 9.4 Grid Extension 18,995
V2 931 80.7 80.7 13.3 MHPP 1 - battery 51,414
V3 1078 93.4 93.4 18.0 Grid Extension 46,078
V4 340 19.0 19.0 30.2 MHPP 1 –grid 19,069
V5 1213 105.1 0.8 7.5 MHPP 2- battery 527
V6 913 79.1 79.1 14.1 Grid Extension 29,483
V7 2354 204.0 204.0 4.7 Grid Extension 26,073
V8 971 84.2 84.2 26.1 Grid Extension 62,105
V9 1065 92.3 92.3 17.8 Grid Extension 45,522
V10 1420 123.1 123.1 1.1 Grid Extension 15,728
V11 893 77.4 77.4 9.4 MHPP 2 23,725
V12 156 8.7 8.7 22.5 Grid Extension 5,378
TOTAL COST 344,097
19
Generator Capacity [kW] Capacity demanded with least
cost solution [kW]
Fossil fuel plants 830 760.74
MHPP 1 100 99.73
MHPP 2 80 78.22
Total Electricity Demanded [ 1043.0
Total Electricity Consumed [Qi] 938.69
Electrification ratio in area 90%
Table 4 Results with Scenario 1
4.5.2 Scenario 2: Scaling up the MHPP capacities
In this scenario, we attempt to analyse the effects of scaling up of the MHPP capacities on the total
cost. The capacities of MHPPs are doubled from the base scenario and become 200kW and 160kW
respectively. To keep the same capacity constraint as Scenario 1, we have reduced the PLN fossil fuel
plants capacities to 650kW. The least cost solution is illustrated in Figure 7. The full results of the
simulation are given in
Table 5.
We see that more villages have now opted for electrification by connection to the MHPPs (6
villages). We also start to see a pattern whereby grid extension is generally preferred up to about
18km, and from there MHPP becomes the cheaper option 11. One village (Village 3) is still left
unelectrified despite the achievement of 90% target electrification in the area overall.
The least cost option has now increased to $464,984. This indicates that perhaps there still exists
diseconomies of scale with the MHPP technology with increasing capacity. Furthermore, similar to
the base scenario, the capacity of both MHPPs are almost fully exploited, leaving spare capacity in
the fossil fuel plants to allow for a safety margin.
11
An exception is Village 12, where it can be seen that the cheapest option for this village is to connect to the
grid. However we suspect this is caused by the small demand (8.7 kW), and given the very remote geographical
location it is still cheaper to connect to the grid rather than battery charging.
20
Figure 7 Least Cost Electrification Strategy for Scenario 2: Scaling up the MHPP Capacities
Vi-
llage
#
Population Total
Demand
[kW]
Quantity
Consumed
[kW]
Dist to
Grid [km]
Selected Option Cost of
electrification
[$]
V1 876 75.9 73.4 9.4 MHPP 2- battery 92,443
V2 931 80.7 80.7 13.3 Grid Extension 30,064
V3 1078 93.4 0.0 18.0 Grid Extension 0
V4 340 19.0 19.0 30.2 MHPP 1 – grid 19,069
V5 1213 105.1 96.8 7.5 MHPP 1 - battery 121,976
V6 913 79.1 79.1 14.1 Grid Extension 29,483
V7 2354 204.0 204.0 4.7 Grid Extension 26,073
V8 971 84.2 84.2 26.1 MHPP 1 – grid 29,933
V9 1065 92.3 92.3 17.8 Grid Extension 45,522
V10 1420 123.1 123.1 1.1 Grid Extension 15,728
V11 893 77.4 77.4 9.4 MHPP 2 - battery 49,315
V12 156 8.7 8.7 22.5 Grid Extension 5,378
TOTAL COST 464,984
Generator Capacity [kW] Capacity demanded with least
cost solution [kW]
Fossil fuel plants 650 587.93
MHPP 1 200 200.00
MHPP 2 160 150.76
21
Table 5 Results with Scenario 2: Scaling up MHPP capacities
4.5.3 Scenario 3: Observing effect of reduced LCEO
As we suspected that diseconomies of scale with increasing MHPP capacity may still exist, we wish to
analyse the effects of reduced LCEO. This reduction can be attributed from several sources including:
government subsidy, grants from NGOs or other private sources. We assume a reduction of 15% in
LCEO as suggested by (Jayawerdana & et al., 2005). The results are illustrated in Figure 8.
The cost of the optimal solution is now reduced to $331,296, which translates to $352.93/kW
consumed when compared to Scenario 2 [$495.3/kW]. It is also lower compared to the base
scenario with less capacity installed. Therefore we see that by reducing LCEO we can achieve
economies of scale with increasing capacity of MHPP.
Figure 8 Least Cost Electrification Strategy for Scenario 3: Reduced LCOE
22
Vi-
llage
#
Population Total
Demand
[kW]
Quantity
Consumed
[kW]
Dist to
Grid [km]
Selected Option Cost of
electrification
[$]
V1 876 75.9 75.9 9.4 Grid Extension 18,995
V2 931 80.7 80.7 13.3 Grid Extension 30,064
V3 1078 93.4 92.5 18.0 MHPP 1 – grid 47,027
V4 340 19.0 17.1 30.2 MHPP 1 – grid 17,398
V5 1213 105.1 105.1 7.5 Grid Extension 26,303
V6 913 79.1 - 14.1 MHPP 1 – battery -
V7 2354 204.0 204.0 4.7 Grid Extension 26,073
V8 971 84.2 63.7 26.1 MHPP 2 – battery 80,322
V9 1065 92.3 90.4 17.8 MHPP 1 – grid 45,508
V10 1420 123.1 123.1 1.1 Grid Extension 15,728
V11 893 77.4 77.4 9.4 MHPP 2 – grid 18,501
V12 156 8.7 8.7 22.5 Grid Extension 5,378
TOTAL COST 331,296
Generator Capacity [kW] Capacity
demanded with
least cost solution
[kW]
Fossil fuel plants 650 587.93
MHPP 1 200 200.00
MHPP 2 160 150.76
Table 6 Results from Scenario 3
4.6 Utility Maximisation Model
We now incorporate a measure of relative utility of consumption of electricity where we define that
the consumption of the first unit of electricity is much larger than the subsequent units. The model’s
objective function is then to maximise the aggregate utility of consumption of electricity for the
entire area. We will use relative utility as a measure of consumption (utility per kW consumed).
We define the objective function as:
T-[)#)U!Y\���
���]ℎ!"!\� = �0)*;� = 05 + ;�)*;� > 0
(9)
The other constraints as defined in (5) to (8) still hold.
Finally we obtain the following results
23
Vi-
llage
#
Population Total
Demand
[kW]
Quantity
Consumed
[kW]
Dist to
Grid [km]
Selected Option Cost of
electrification
[$]
V1 876 75.9 75.9 9.4 Grid Extension 18,995
V2 931 80.7 80.7 13.3 MHPP 1 – grid 30,032
V3 1078 93.4 93.4 18.0 Grid Extension 46,078
V4 340 19.0 0.0 30.2 Grid Extension 0
V5 1213 105.1 93.8 7.5 MHPP 2 – grid 31,160
V6 913 79.1 79.1 14.1 Grid Extension 29,483
V7 2354 204.0 143.1 4.7 Grid Extension 18,294
V8 971 84.2 84.2 26.1 MHPP 1 – grid 29,933
V9 1065 92.3 92.3 17.8 Grid Extension 45,522
V10 1420 123.1 123.1 1.1 Grid Extension 15,728
V11 893 77.4 65.3 9.4 MHPP 2 – grid 20,447
V12 156 8.7 7.8 22.5 Grid Extension 4,799
TOTAL COST 290,471
Generator Capacity [kW] Capacity
demanded with
least cost solution
[kW]
Fossil fuel plants 650 614.78
MHPP 1 200 164.84
MHPP 2 160 159.07
Table 7 Results from Utility Maximisation Model
It is interesting to note that this approach yields the lowest total cost for the optimal electrification
technology mix, compared to the previous scenarios where the objective function is to directly
minimise total cost. In this model, we see that one village also remains unelectrified (Village 4).
However, the optimal outcome of this model actually ‘favours’ MHPP less than the previous
scenarios, as the full capacity of the MHPPs are ‘less depleted’ .
4.7 Discussions of model
The model and scenarios discussed this far has been implemented using ‘artificial’ village data that is
designed to mimic the real geographical and population dispersion in Nias Island. This approach was
selected due to the limitation of accurate population and geospatial data at village level. Most data
available for public access has been mainly on district or state level only.
Despite these limitations the model has been particularly useful in revealing the large potential for
MHPP in a rural electrification strategy. All scenarios under minimising cost model have shown that
the optimal strategy is highly dependent on the ability to exploit the full capacity of MHPP (see Table
8).
24
Scenario 1 Scenario 2 Scenario 3 Scenario 4
Objective function Minimise cost Minimise cost Minimise cost Maximise utility
% ‘used’ capacity from
fossil fuel plants at
optimal solution
92% 90% 92% 95%
% ‘used’ capacity from
MHPPs at optimal
solution
99% 97% 95% 90%
Table 8 Required percentage of total plant capacities at optimal level
Aside from data limitation, there are also certain limitations with the models itself that can be
further improved:
• At present, the model is limited to ‘artificial’ villages and only considers very basic setup of
one grid and two sites for MHPP. An improved model which takes into account multiple
access to grids and larger number of MHPPs is required to get a better understanding of
costs of electrification strategy, and assess the scalability of such solution.
• The model only allows a static analysis (one point in time). A dynamic model which takes
into account growth of demand and other variables would be more useful in determining
the optimal path towards the 90% electrification target over a period of time.
• The subsidy level at present is a simple percentage reduction on the LCOE. Other subsidy
and financing structures associated with MHPP construction are available from examples of
other developing countries. Incorporation of this factor would be beneficial in determining
the true optimal least cost electrification strategy when financing sources other than from
PLN is available.
• The cost of distribution of MHPP is currently a linear function of distance. Further
refinement in quantifying this cost would be useful to get a better understanding of the
‘threshold’ distance for switching between grid and MHPP, if this exists.
• Finally, we have approached the analysis from a cost perspective and have not taken into
profitability of PLN and various pricing structures for the end consumer.
However, the immediate step in this study is of course to utilize real data of villages, grid and
MHPP potential sites in the island.
5 Further Considerations to Implementation of MHPP
The potential role of MHPP cannot be assessed on a basis of economics alone (least – cost). It is
important to consider external factors to economic feasibility to reflect the ‘true’ potential of MHPP.
25
There are several significant issues that PLN still has to overcome, which may call for the need of
additional policies to increase the attractiveness of MHPP adoption.
Firstly, as PLN is a state-owned company they are prone to political interference from politicians and
the government. Low labour productivity and over-employment may result from inefficient
government policies, implemented for example during election times to gain support from the
public. To prevent the risk of occurrence of this be, there is a need of separation between regulating
and policy making function, which is currently still held by the Ministry of Energy & Mineral
Resources alone. An accepted structure in most developed countries that may be transferrable to
Indonesia, is where an independent regulator exists which is responsible for balancing interests of
consumers, utility and government; and determines appropriate pricing structure to ensure fair and
optimal costs for rural consumers (Haanyika, 2005).
Secondly, the risk of indirect rebound effect associated with improvements in cost-effective energy
efficiency may result over time from the adoption of MHPP for rural electrification. Access to
electrification may have positive effects for rural communities such as increased income and
productivity, for example through the use of electrical equipment instead of manual labour for
agriculture purposes. There is a potential for the consumers to exploit the cost savings from these
benefits to purchase other high energy demand goods and purposes (indirect effect). Alternatively,
direct effects such as increased use of electricity for households that were already electrified may
also result from establishing a ‘cheaper’ generation option. In a case of backfire, it is possible that
the expected energy savings are entirely offset, leading to zero net savings (Sorrell, 2009). Such
scenario may result in a continued state of energy deficit as generation capacities can never keep up
with demand growth.
To prevent rebound effects, consumer education on ‘quality over quantity’ of electricity supply is
very critical. Hence, newly electrified households may need to be educated on energy saving
behaviours. Alternatively, using a stick approach, the regulator may choose to increase tariffs or
reduce subsidies on MHPP to force consumers to reduce consumption to sustainable levels.
Third, it is important to consider the most appropriate financing structure to reduce the financial risk
and burden on PLN and GOI. According to (Jayawerdana & et al., 2005), although the operations of
MHPP is typically fully commercial, subsidies on initial construction and connection costs are still
required, as such high costs remains the main hurdle to realisation of MHPP projects. Typical
subsidies can range between 15-20% of investment costs. But to further encourage adoption of
MHPP, it is possible to have higher levels of subsidies for off-grid projects compared to on-grid
26
projects. Furthermore, subsidies can be enhanced by micro-financing from private institutions,
development banks or NGOs. Such institutions have the right expertise and knowledge of the right
financing mix, risk profile, and credit enhancements for small rural-based based projects, which large
utilities (PLN) may have little knowledge in (Jayawerdana & et al., 2005). This will further reduce the
investment risk of MHPP projects.
Finally, it is important for PLN to start building the right technical knowledge and set of technical
standards for MHPPs to ensure successful and high quality project completion. Apart providing
technical education to engineers and technicians, standards of MHPP operations will need to be
developed as guidelines for users. Potential environmental issues such as safe battery disposal will
also need to be addressed.
6 Conclusion
This study set out to determine whether micro hydropower could become part of an effective
electrification strategy for rural Indonesia, and to explore the costliness of meeting Indonesia’s 90%
electrification target, with a specific focus on Nias Island. To date, a simplified model of this study
has been carried out using data of an ‘artificial environment’ consisting of a small number of villages
which have the option of either connecting to MHPPs or an electricity grid to gain electricity access.
Despite the simplified nature in which this model has been currently run, we believe the model
demonstrates some insights to the role of MHPP in rural electrification.
From our analysis, we have observed that MHPP can be an integral part of a low-cost rural
electrification strategy. Our findings suggest that electricity access using MHPP either as an isolated-
grid or battery charging station has the best potential for villages with significant electricity demand
but are located at a considerable distance from the grid (18km and above) and are technically
difficult to reach by extension of PLN’s grid
Despite demonstrating MHPP as a vital ingredient for an optimal low-cost electrification strategy for
rural communities, we expect there will be other non-economic barriers to accelerating the adoption
of MHPPs. We observed that there still exists diseconomies of scale (in terms of the overall
electrification costs) with increasing MHPP capacity. However, if the increase in capacity has an
associated reduction in MHPP to 15% below the current LCEO level, this effect was reversed and we
observed economies of scale with increasing generation capacity. Furthermore, the bulk of total cost
of electrification is due to construction and development costs, whereas the operation costs are
relatively low. It is unlikely that for a large-scale (non-ad hoc) rural electrification program, PLN
would have the sufficient capital to cover these initial investments, particularly given their current
27
financial struggle. Therefore a study on possible financing structure which incorporates a certain
level of support of NGOs, micro-financing, or even contribution from the rural community itself is
still required.
Finally, a firm policy framework is urgently required to eliminate inefficiencies in the electricity
sector to ensure PLN can build the right financial and technical capacity to focus on access
maximisation. Such a policy will reduce the uncertainties in the electricity sector, which could serve
to incentivise investments from the private sector and alleviate the financial responsibilities for rural
electrification from the public sector alone.
28
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30
Appendices
Appendix 1 – Policies Relevant to Rural Electrification
Decree & Law Reference / Year Description
Issued by Government of Indonesia
State Constitution 33/1945 Provision of vital utilities must be controlled by the state
Law 15/1985 PLN status as sole institution with full authority in electricity
provision
Law 20/2002 PLN’s role as the sole electricity provider is reduced. The
function is to be partly delegated to Central and Local
Government in a bid to accelerate electrification access.
Status: annulled due to violation of State Constitution 33/1945
Government Regulation
26/2006
A ‘reduced’ version of 20/2002, allowing central and local
government to grant licenses to cooperatives and businesses if
no PLN services are present in the area. Obligates central and
local government to provide funds towards rural electrification.
Issued by Ministry of Energy & Mineral Resources
Ministerial Decree 1122 / 2002 Provision of small scale distributed renewable energy power
generation
Ministerial Decree 10/2005 Procedures for Electric Power Business Licenses for Inter-
Provinces, Regions or for National Grid Connections
Ministerial Decree 01/2006 Procedures for Electric Power Purchasing and/or Rental of
Transmission Lines
Ministerial Decree 02/2006 Provision of medium scale distributed renewable energy power
generation Table 9 List of regulations relevant to rural electrification in Indonesia (Source: Directorate General for Electricity and
Energy Utilization, Ministry of Energy & Mineral Resources, 2007)
31
Appendix 2 – Comparison of energy costs on isolated grids
Appendix 3 – Cost of grid extension
Cost breakdown Rp ('000) US$
LV line
Unit cost per km 77,790 8,972
Units per connection (km) 0.0094 0.0094
Cost per connection 731 84
Transformer (50 kVA)
Unit cost per km 55,197 6,366
Units per connection 0.0024 0.0024
Cost per connection 132 15
Service drop
Unit cost per km 1,023 118
Units per connection 1.0000 1.0000
Cost per connection 1,023 118
Total supply cost per connection 1,887 218
Estimated cost of wiring and metering at household
level
32
Total cost of grid extension per household 250
Note: 1US$ = Rp 8,760
Appendix 4 – Cost of battery
Battery cost (85Ah/1kWh, 12V) US$ 100
Charging subscription cost ($2 per month) over lifetime of 10 years,
allowing up to 8 charges per month US$240
Usage per lifetime (kWh) 960
LCOE (USc/kWh) 35.4