Renewable Investment in Indonesia: A decarbonized electrical supply vision to 2030

Spatial Analysis of Energy Data Coursework

1. Country snapshot and its energy demand
To understand the renewable infrastructure needed for Indonesia, first, the consultant needs to
report what is the current status of the country in regards to its population, land usage, energy
demand and energy mix. This allows having the current snapshot of the country with its different
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needs and challenges. As well, the consultant needs to find out what renewable power plants are
already in operation, under construction or planned since these will be already covering part of the
electrical demand (e.g. you can use your power plant vector layer for this). A map with the location
and installed power of the existing, under construction and planned renewable plants, is required
in the report.
After the snapshot, the consultant should project Indonesia’s electrical energy demand and planned
electrical installed capacity for the year 2030. This can come in the form of a reference or assumption
taken by the consultant (e.g. electric energy consumption per capita and then multiply by the
population size). The data or assumption used needs to be the most up to date available (check the
IEA or IRENA websites, or Indonesia’s reports cited in this document
2. Potential new powerplants and renewable electricity production by 2030
Here the consultant will explore and report the potential energy available for Indonesia just
considering:
 Wind (on and off-shore)  Fixed or floating
 Solar  Photovoltaic
It will bring forward suitable places where future renewable power plants may be installed to cover
38% of the projected electrical installed capacity by 2030 (i.e. considering the existing, planned and
under construction renewable power plants in 2021). The consultant can choose a single source of
renewables (e.g. just wind power) or a mix of them (i.e. solar and wind power). You will assess the
renewable power potential of different sites which can bring the installed power needed to comply
with Indonesia’s 2030 objective (i.e. 38% of the projected electrical installed capacity by 2030).
The consultant will need to find the actual electrical power production of the new renewable
powerplants suggested for four hours in the day for the average summer and winter months: 8AM,
12PM, 2PM and 4PM (e.g. Figure 2). The government will give you the solar and wind resource hourly
layers from which you should obtain representative availability for each hour studied. However,
beforehand you know that there is an issue with the layers: They have missing data for some of the
study regions. You will need your GIS skills to infill these values and reflect what level of uncertainty
the process has added to the analysis. The provision of statistical validation (p-values and confidence
intervals) will be a plus in your report. This step will require the interpolation and time-series analysis
tools covered later in the course.
For each of the renewable power plants, there is a limit of a maximum of 12 km2
per site. You will be
provided in an R script with a value of nominal generation capacity per area unit (e.g. m2
/kWh) and a
set of assumptions made to obtain these values: Generation unit models and specifications (i.e.
irradiance vs power output for PV and wind speed vs power output for wind turbines), along with
sizing and costs. These assumptions will have an impact on the efficiency of the sites chosen and as
such you will be welcome to review/change them if you find alternative models better suited to the
sites identified. The rationale for the plants’ locations and a short explanation of the changes on
assumptions -if any- need to be presented in the report. As well, the table of assumptions with the
values used (see Appendix I) has to be added to the report as an appendix.
Consider for your selection where the grid is located, near populations and landscape (i.e. elevation)
to name a few. In particular to Indonesia, one of their main priorities is to stop or minimise its rapid
pace of deforestation and peatland conversion. This was Indonesia’s strategy to comply with their
Nationally Determined Contributions (NDCs) which aimed for a 26% greenhouse gases (GHG)
reduction by 2030 [1]. This set of preferences set high importance on land usage especially when land
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is classified as forest, jungle or peatland. You need to report in your calculations/decisions the
distance from the renewable site to the electrical grid.
Figure 2: Power production for a hypothetical solar power plant considering the time of day and seasonality [2].
It is left to the consultant to decide how many maps are needed to present the required information
in this section. The maps need to balance clear, concise and precise messages with aesthetics and
cluttering level (e.g. it is better to have two maps with complementary messages than one single
clutter map, however, having too many maps can lose the overall message of this section). It is
expected that each map will contain the minimum accepted elements and quality as discussed in the
map tutorial and map coursework (see further requirements in section 5).
2.1 Investment in renewables
After selecting suitable locations and renewable power plant sizes, the consultant will deliver a simple
investment analysis for the government of Indonesia. For this section, you will be provided with a
basic R script that will contain the main costing equations and relevant assumptions for you to make
a quick assessment of the investment needed. As inputs, you will need to provide the renewable type’s
total installed capacity and distances to the grid. The script will include assumptions on CAPEX, OPEX,
discount rates and payback periods to provide as outputs the Net Present Value (NPV) project cost
and the levelised cost of energy (LCOE). You are expected to review the assumptions made and
comment on the reasons for either agreeing to them or if disputed, changing them.
You will need to report the final cost of your recommendation and contrast the investment required
against Indonesia’s GDP.
Use a value of 7.67p/kWh (£0.0767/kWh) as the price at which the government can sell the energy to
the electricity suppliers in 2030 to compare against the LCOE obtained. If you think a different value
should be used for comparison, please use it and explain the reason.
With this information at hand, you should be able to recommend the government if they should
proceed with the renewable roadmap (Question 1 in the Assignment Brief section).
3. Green ammonia manufacturing
The government of Indonesia is keen on exploiting the zero-carbon fuel for the international maritime
sector and green fertiliser markets. From the shipping point of view, zero-carbon fuels are the most
viable solution to decarbonise the sector without the excessive land demand from first-generation
biofuels. Further, since Indonesia is conveniently located to capture shipping energy demand (see
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Figure 3), its potential to become an important player in the shipping sector is large. Furthermore,
Indonesia has an important agricultural sector that needs to reduce its carbon intensity. One option
that the government is looking at is the use of green fertilizers.
Figure 3: Shipping traffic through South Asia in 2012 [4].
Under this set of ambitions, the government of Indonesia is interested in the manufacture of green
ammonia through electrolysis, also known as e-NH3, as both a zero-carbon fuel and fertiliser (see
Figure 4). But before committing the budget to the development of the future infrastructure, the
government needs to understand the level of investment, green ammonia annual production while
maximising positive impacts on Indonesia’s development.
Figure 4: Simplified manufacturing process for e-NH3.
3.1 Green Ammonia Plant Location
The Indonesian government does not want to start big with the manufacturing of green ammonia. The
government wants to understand if there is a business case to install three renewable pilot-test plants
with green ammonia production capabilities. The consultant will assume that the whole renewable
electricity produced by the power plants will be solely utilised for ammonia production.
The consultant will have to decide on three optimal locations for the renewable power plant
producing ammonia, based on the selection done in section 2. But as a constraint, all power plants
need to be located in different provinces. The consultant will need to quantify the annual green
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ammonia production and estimate the business case (see subsection 3.1.3). But it is important to
highlight that the Indonesian government needs the consultant to create a new green development
index (GDI) that can balance the decision-making process between profits and societal impacts (see
the following subsection).
3.1.1 Green Development Index
The purpose of the GDI is to balance the pure business case rationale (e.g. LCOE or NPV) by adding
sustainable development impacts (e.g. lower emissions, employment, etc.) into the decision making
process. The GDI should allow the consultant to find locations that offer maximum development
impact for the lowest cost possible.
To produce the GDI, teams of four consultants will work in two separate surgery sessions that occur
on Tuesdays of the weeks when the spatial module (BENV0093) has a guest lecture (dates to be
confirmed). Each of the teams will have to develop a GDI prototype, look for data and test it to assess
if it is doing what the GDI needs to do. The first work session will focus on researching and sketching
the GDI while the second session will be the index testing and a 10-minute presentation of the work
done.
The coursework reading list has several documents that discuss different indexes on renewable
energy and human development (e.g. Human Development Index or the Multidimensional Poverty
Index). Please read the mandatory references before the workshop sessions since they will give a
good hint of what you will need to start.
Finalising the two workshop sessions, the consultant team should use the GDI produced individually
to find the most suitable locations for the three renewable plants with ammonia manufacturing
capabilities.
3.1.2 Other considerations when choosing the locations
Care has to be taken for the ammonia manufacturing process which needs considerable water for the
electrolysis process (i.e. it is optimal to have the ammonia plant near a water source). Since the
manufactured ammonia is going to be used in the maritime and agricultural sectors, the plants will be
more suitable to be near a port where the ships can/will bunker or near important agricultural areas
or islands.
3.1.3 Green Ammonia Business Case
For the e-NH3 business case, you need to consider the investment in renewables, grid connection from
the renewable power plant to the electrical grid, connection from the electrical grid to the ammonia
plant (assumed the same cost values), and the cost of the ammonia plant.
You will need to provide yearly ammonia production assuming that the ammonia plant can operate
the full 24 hours of every day for the whole year. A suggestion is to use the annual-averaged (i.e.
summer and winter energy availability1
) daily ammonia production to find the annual ammonia
production and earnings.
The consultant will assume for the business case that the green ammonia can be sold at
£800/t of e-NH3 (~1,070 USD/t of e-NH3) and that the whole yearly production of ammonia is sold to
the maritime and agricultural sectors.
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Be mindful that solar power plants only operate when there is sunlight, this will affect the daily green ammonia
production.
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Similarly, to the previous section, the R script will contain cost assumptions to facilitate the calculation.
You will need to provide the volume of installed capacity and the costs of your proposed renewable
source, including grid connection. The script will include assumptions for operating costs and discount
rates that you are expected to comment on and either agree to or change based on your assumption.
As an output, it will provide the NPV of the project at 5, 10 and 15 years. For this project, you should
base your investment assessment using the 15 years NPV.
3.2 Green Ammonia Vector file
As part of the requirements, the consultant will need to submit a vector file with the renewable
plants’ polygons with the following attributes:
 Unique ID
 Latitude and Longitude
 Renewable technology (i.e solar or wind)
 Renewable plant surface area (in km2
)  Remember that there is an upper limit of 12 km2
 Installed power in MW
 Distance to the grid in kilometres
 Annual green ammonia produced
 LCOE
 NPV
 GDI
3.3 Deliverable
Therefore the consultant needs to present in a map where the three renewable plants with
ammonia manufacturing capabilities will be located with an associated table presenting the main
characteristics as requested in section 3.2.
Finally, based on the results you should be able to recommend the government of Indonesia if it is a
good investment plan to scale up the manufacture of green ammonia for the shipping and
agricultural sectors (Question 2 in the Assignment Brief section).
4. Discussion
In this section, the consultant will bring forward the most relevant aspects of the results and the
arguments regarding the planned renewable plants, excess energy and ammonia manufacturing
plants. As well, it is recommended for the consultant to contrast the general results with similar works.
Moreover, you will need to discuss data uncertainty, its implications and how you can mitigate it.
Finally, the consultant will reflect on how the analysis could be improved if more time and resources
were available.
5. Vector layers and maps
The consultant is expected to submit the vector layers used and created for this work. Raster files are
not required to be submitted but maps produced need to be submitted as an image file (i.e. JPEG or
TIFF).