metadata: authors: 0: author: Nicolas,Claire Marion
1: author: Samson,Benjamin
2: author: Rozenberg,Julie
count: Africa
docna: 0: docna: Meeting the Sustainable Development Goal for
            Electricity Access -- Using a Multi-Scenario Approach to
            Understand the Cost Drivers of Power Infrastructure in
            Sub-Saharan Africa
docty: Policy Research Working Paper
subtopic: Energy Policies & Economics,Electric Power,Energy and Mining,Energy and Environment,Energy Demand,Energy Sector Regulation
teratopic: Energy
abstracts: cdata!: This paper explores the investments
            needed to achieve universal access to electricity in
            Sub-Saharan Africa by 2030, and the additional operation and
            maintenance costs these investments entail. It also explores
            the drivers of these costs, by exploring hundreds of
            scenarios that combine alternative assumptions on the level
            of service targeted, population growth, urbanization,
            industrial demand, and technology cost. The main driver of
            electrification costs is found to be the tier of service
            offered to newly connected households. The annual investment
            required to reach universal access varies between US$14.5
            billion per year on average for the basic access scenarios
            (0.7 percent of the region's gross domestic product per
            year over the period) and US$22.7 billion on average for the
            high-quality scenarios (1 percent of gross domestic
            product). In the basic access scenario, costs depend mostly
            on industrial demand, which takes a large share of total
            demand. In the high-quality scenarios, costs depend on
            urbanization rates, as it is cheaper to connect urban
            households to the grid. Investment costs are not sufficient
            to provide reliable service, and when operations and
            maintenance are accounted for, total costs increase to
            US$39.7 billion on average for the basic scenarios and
            US$61.5 billion on average for the high-quality scenarios.
repnme: repnme: Meeting the Sustainable Development Goal
            for Electricity Access -- Using a Multi-Scenario Approach to
            Understand the Cost Drivers of Power Infrastructure in
            Sub-Saharan Africa
display_title: Meeting the Sustainable Development
            Goal for Electricity Access -- Using a Multi-Scenario
            Approach to Understand the Cost Drivers of Power
            Infrastructure in Sub-Saharan Africa
listing_relative_url: /research/2019/02/30837725/meeting-sustainable-development-goal-electricity-access-using-multi-scenario-approach-understand-cost-drivers-power-infrastructure-sub-saharan-africa
topicv3: Energy Access m1325609 521,Energy and Extractives m1326595 507,Power and Electricity Sector m1327094 515,Population, Aging and Health m1327736 640,Electricity Access m1503452 3922
publishtoextweb_dt: 2019-02-19T00:00:00Z
historic_topic: Energy
no_of_pages: 19
author_keys: 0: author_key: 1529065
1: author_key: 1641791
2: author_key: 1296276
model_extractions: Policy Research Working Paper 8747

**Beyond the Gap** How Countries Can Afford the Infrastructure They Need While Protecting the Planet

_Background Paper_ Meeting the Sustainable Development Goal for Electricity Access Using a Multi-Scenario Approach to Understand the Cost Drivers of Power Infrastructure in Sub-Saharan Africa _Claire Nicolas Benjamin Samson Julie Rozenberg_ Sustainable Development Practice Group Office of the Chief Economist February 2019
Policy Research Working Paper 8747

# **Abstract**

This paper explores the investments needed to achieve universal access to electricity in Sub-Saharan Africa by 2030, and the additional operation and maintenance costs these investments entail. It also explores the drivers of these costs, by exploring hundreds of scenarios that combine alternative assumptions on the level of service targeted, population growth, urbanization, industrial demand, and technology cost. The main driver of electrification costs is found to be the tier of service offered to newly connected households. The annual investment required to reach universal access varies between US$14.5 billion per year on average for the basic access scenarios (0.7 percent of the region’s gross domestic product per year over the period) and US$22.7 billion on average for the high-quality scenarios (1 percent of gross domestic product). In the basic access scenario, costs depend mostly on industrial demand, which takes a large share of total demand. In the high-quality scenarios, costs depend on urbanization rates, as it is cheaper to connect urban households to the grid. Investment costs are not sufficient to provide reliable service, and when operations and maintenance are accounted for, total costs increase to US$39.7 billion on average for the basic scenarios and US$61.5 billion on average for the high-quality scenarios.

This paper was commissioned by the World Bank Group’s Chief Economist office for Sustainable Development Practice Group and is a background paper for the World Bank Group’s report: _“Beyond the Gap: How Countries Can Afford the Infrastructure They Need While Protecting the Planet.”_ It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/research. The authors may be contacted at cnicolas@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
Meeting the Sustainable Development Goal for Electricity Access—Using a Multi‐Scenario Approach to Understand the Cost Drivers of Power Infrastructure in Sub‐Saharan Africa Claire Nicolas, Benjamin Samson, Julie Rozenberg JEL: O13, Q40 Keywords: electrification; sustainable development goals; infrastructure investment needs; universal electricity access; scenario analysis;
# Introduction

Sustainable Development Goal 7, which aims at providing access to affordable, reliable, sustainable and modern energy for all by 2030, is still far away. In 2016, 13% of the world population was still living without electricity or a bit less than 1 billion of people, more than half of them living in Sub‐ Saharan Africa (United Nations, 2018). Meeting SDG 7 will require a high level of investment in the coming years. The question of how much will be needed is of importance for developing countries but also for all development actors. Yet, there are multiple ways of reaching this goal in terms of pace, technology, and level of access, but also many uncertainties be it demography, costs, climate constraint or technology evolution. Hence the relevant question is less what the cost of meeting SDG 7 is and more what the drivers of this cost are and how decision makers can use these levers.

In this paper, we focus on Sub‐Saharan Africa’s (SSA) investment needs, as this region concentrates 14 of the 20 countries with the highest number of people without access to electricity (Figure 1). Moreover, Sub‐Saharan Africa is the only region where electrification has not kept up with population growth: 154 million more people in rural areas lacked access in 2014 than in 1991 and the number of people in urban areas without access rose from 58 million in 1991 to about 108 million in 2014 (SEforALL, 2018).

Over recent years, several attempts have been made to estimate the investments required to reach universal access by 2030 (Pachauri et al. 2013; Dobbs et al 2011; IEA, UNDP, and UNIDO 2010). One recent review underlines several limitations of these attempts, the main one being the lack of transparency on the underlying assumptions used in the estimation models (Bazilian et al. 2014). Other limitations include: (i) most studies focus on capital costs and do not consider variable costs; (ii) most models focus on generation, ignoring transmission and distribution; (iii) decentralized energy investments are often omitted; and (iv) the impacts of geography and population density on costs are typically ignored. To overcome some of these limitations, we use AIM (SE4ALL Access Investment Needs Model), a costing tool created to estimate country‐level funding requirements (Jordan‐Antoine et al. Forthcoming) and that includes all costs for both generation and transmission and distribution (capital, maintenance, variable, fuel).

Future electricity demand in SSA countries is uncertain because of low access rates ‐‐ and thus absence of data on past demand patterns – and because SSA countries cannot be compared with other countries having recently transitioned toward high access rates. In parallel, on the supply side, the emergence and recent improvements of new technologies could change the access landscape and allow for an increase of the electrification pace. Indeed, high learning rates and the corresponding falling costs of renewable energy technologies (RET) and batteries, together with new payment facilities, will modify the usual electrification channels. In addition, if the cost of capital was to increase, large capital‐intensive power plants would be harder to finance and therefore less attractive than small‐scale renewable solutions (Schmidt 2014).

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# Scenario database

Five policy choices were modeled, representing different ways of achieving universal access by 2030 across Sub‐Saharan Africa. Four depict different paths to universal access (table 1): in the “High quality” consumption policy the government chooses to increase access mostly via the grid with a quality and level of service enabling productive use, while in the “Basic” and “Middle range” the goal is to provide a more basic electricity service to unserved households. BAU depicts a world where newly connected households benefit from the same tier mix as the already connected households in the country when the progressive choice is a scenario where all newly connected households end up at Tier 3 in 2030 but passing through tier 1 and tier 2 in the meantime (universal access is reached earlier but with low tier level). In the fifth policy choice case, “constant access,” investments are made to maintain access and consumption at the current level for households—although they allow for growing industrial demand.

# **TABLE 1 POLICY CHOICE: NEW CUSTOMERS CONSUMPTION LEVEL**

|**Consumption**<br>**Strategies**|**Basic**|**Middle**<br>**range **|**High quality**|**BAU**|**Constant**<br>**access**|
|---|---|---|---|---|---|
|**Objective:**<br>**universal**<br>**access in 2030**|50 percent of<br>newly<br>connected<br>households<br>are assigned<br>to Tier 1, the<br>rest to Tier 2|Newly<br>connected<br>households<br>are assigned<br>to Tier 3|50 percent of<br>newly<br>connected<br>households are<br>assigned to Tier<br>4, the rest to<br>Tier 5|Newly<br>connected<br>households<br>are assigned<br>the current<br>Tier<br>breakdown|Newly<br>connected<br>households to<br>keep up with<br>demographic<br>growth, Tier<br>breakdown is<br>BAU.|

Source: Authors. Note: industrial demand varies independently of the access scenarios.

These five policy choices were assessed under dozens of scenarios for each of the 48 countries, by varying five parameters: population growth, urbanization rate, industrial demand growth, technology cost evolution, and fuel price.

The fossil fuel price was defined for two levels (low and high) based on the World Bank Commodities Price forecast (World Bank, 2016, July) for the short term and World Energy Outlook 2015 (IEA (2015)) low oil price scenario and current policies scenario the long term. The renewable technology cost and performance outlooks were defined in three levers (low, reference and high) which are based on the projected learning rates from (NREL, 2016).

# **TABLE 2 INPUT PARAMETERS**

||Values|
|---|---|
|Populationgrowth|5 values: 5 SSPs|
|Urbanization|5 values: 5 SSPs|
|Techno costs|3 values (NREL low,<br>medium and high ref)|
|Fuelprices|2 values: low & high|
|Industrial demand<br>growth|5 values: same as GDP<br>growth of the 5 SSPs|

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Population growth, urbanization and GDP projections (where possible) were related to the five Shared Socio‐Economic pathways (SSP) for narrative consistency (O’Neill et al. 2017). The SSPs consist of five future pathways organized around challenges to climate change mitigation and adaptation. SSP1 is characterized by sustainability with low challenges to mitigation and adaptation. Population growth is low due to higher education and living standards, and GDP growth is high. SSP2 is called the “Middle of the road” scenario, in which it is assumed that historical trends also drive the future. SSP3 is characterized by regional rivalry with high challenges to mitigation and adaptation due to poor cooperation between countries and regions. This pathway has a high population growth but low GDP growth. The SSP4 pathway is characterized by inequality, where power becomes concentrated to a small elite, there are low challenges to mitigation but high challenges to adaptation. The population growth is expected to be intermediate whereas the GDP growth is low. The final pathway, SSP5, is characterized by fossil‐fueled development where challenges to mitigation are high but challenges to adaptation are low. The economic growth is high coupled and with increasing living standards the population growth is low.

GDP, population and urbanization rates are projected at the country level for each of the SSPs.

The industrial demand has been calculated by applying the GDP growth rates to the base year industrial demand provided with the original AIM model.

# **TABLE 3 SUB SAHARAN AFRICA POPULATION GROWTH AND URBANIZATION FOR SSP1‐SSP5**

|Scenario|Average annual population<br>growth for SSA|Average annual rural flight for<br>SSA|
|---|---|---|
|SSP 1|1.8%|0.85%|
|SSP 2|2.1%|0.52%|
|SSP 3|2.4%|0.17%|
|SSP 4|2.4%|0.84%|
|SSP 5|1.8%|0.86%|

# Results

Combining all these assumptions leads to 750 scenarios, but to limit computation time a random sample of 300 scenarios are run and then analyzed along several cost dimensions (total cost, variable costs and maintenance costs) for the region as a whole but also at the country level.

The output variables analyzed are: total costs divided by GDP, capital investment requirements and variable and fixed costs. This cost breakdown is useful because even when total costs are similar, a different distribution between capital costs and variable costs can have very different implications for the utilities and governments.

For all these output variables, we identify the inputs that result in the largest variance in outputs.

# Costs are primarily driven by policy choices

The service tier targeted makes a significant difference in the cost of achieving universal access: the annual investment required for Sub‐Saharan Africa by 2030 varies between US$14.5 billion, on average, for the basic scenario (representing 0.7 percent of the region’s GDP per year over the period) and US$22.7 billion, on average, for the high‐quality scenario (or 1 percent of GDP per year) (figure 3).

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demand‐side constraints account for some 40 percent of the access deficit. Adapting the electrification offer to the socio‐economic situation of the households or regions targeted could help reduce these demand‐side constraints. Newly connected households need not stay in low tiers in the long run. However, the electrification pathway could begin with tailored technological solutions instead of directly aiming at connecting the whole population to the grid. This may also be the only affordable way forward for a number of countries. The emergence of new technologies and business models for mini‐grid and off‐grid electrification should help reduce costs and facilitate the journey towards universal access.

# References

- Bazilian, Morgan, Ryan Economy, Patrick Nussbaumer, Erik Haites, Kandeh K. Yumkella, Mark Howells, Minoru Takada, Dale S. Rothman, and Michael Levi. 2014. _Beyond Basic Access: The Scale of Investment Required for Universal Energy Access_ . Oxford University Press. http://www.oxfordscholarship.com/view/10.1093/acprof:oso/9780199682362.001.0001/ac prof‐9780199682362‐chapter‐9.

- Bhatia, Mikul;, and Niki Angelou. 2015. “Beyond Connections: Energy Access Redefined.” ESMAP Technical report. Washington, D.C: World Bank.

- http://www.worldbank.org/en/topic/energy/publication/energy‐access‐redefined.

- Blimpo, Moussa, and Malcolm Cosgrove‐Davies. 2018. “Electricity Uptake for Economic Transformation in Sub‐Saharan Africa.” World Bank report. DC: World Bank.

- Blimpo, Moussa Pouguinimpo, Justice Tei Mensah, K. Ochieng’ Opalo, and Ruifan Shi. 2018. “Electricity Provision and Tax Mobilization in Africa.” WPS8408. The World Bank. http://documents.worldbank.org/curated/en/456951523908618247/Electricity‐provision‐ and‐tax‐mobilization‐in‐Africa.

- Chakravorty, Ujjayant, Martino Pelli, and Beyza Ural Marchand. 2014. “Does the Quality of Electricity Matter? Evidence from Rural India.” _Journal of Economic Behavior & Organization_ 107 (PA): 228–47.

- Dobbs, R., J. Oppenheim, F. Thompson, M. Brinkman and M. Zornes. 2011. “Resource Revolution: Meeting the World’s Energy, Materials, Food and Water Needs.” New York, NY, USA: McKinsey Global Institute.

- https://www.mckinsey.com/~/media/mckinsey/business%20functions/sustainability%20and %20resource%20productivity/our%20insights/resource%20revolution/mgi_resource_revolu tion_full_report.ashx.

- “Electrification | Sustainable Energy for All (SEforALL).” n.d. Accessed December 21, 2018. https://www.seforall.org/heatmaps/electrification.

- Gertler, Paul J., Kenneth Lee, and A. Mushfiq Mobarak. 2017. “Electricity Reliability and Economic Development in Cities: A Microeconomic Perspective,” December. https://escholarship.org/uc/item/96s8s43z.

- “IEA (2017), World Energy Outlook 2017,.” n.d. IEA. https://doi.org/10.1787/weo‐2017‐en. IEA, OECD. 2017. “World Energy Investment 2017.” France: IEA.

https://www.iea.org/publications/wei2017/.

- IEA, UNDP, and UNIDO. 2010. “Energy Poverty: How to Make Modern Energy Access Universal?” http://www.undp.org/content/undp/en/home/librarypage/environment‐ energy/sustainable_energy/energy_poverty_howtomakemodernenergyaccessuniversal.html

- .

Jordan‐Antoine, Rhonda, Sudeshna Banerjee, Will Blyth, and Morgan Bazilian. Forthcoming. “Estimates of the Cost of Reachig Universal Access to Electricity’.” _Working Paper_ . KPLC. 2016. “KPLC 2016 Annual Report.” 16
Longe, O. M., N. Rao, F. Omowole, A. S. Oluwalami, and O. T. Oni. 2017. “A Case Study on Off‐Grid Microgrid for Universal Electricity Access in the Eastern Cape of South Africa.” _International Journal of Energy Engineering_ 7 (2): 55–63.

- Mensah, Justice Tei. 2018. “Jobs ! Electricity Shortages and Unemployment in Africa.” WPS8415. The World Bank. http://documents.worldbank.org/curated/en/659751524142624281/Jobs‐ electricity‐shortages‐and‐unemployment‐in‐Africa.

- Ministère du Plan et Suivi de la, and Ministere de la santé publique. 2014. “DEUXIÈME ENQUÊTE DÉMOGRAPHIQUE ET DE SANTÉ (EDS‐RDC II 2013‐2014).”

- NREL, 2018 “Annual Technology Baseline and Standard Scenarios | Energy Analysis | NREL.” n.d. Accessed December 21, 2018. https://www.nrel.gov/analysis/data‐tech‐baseline.html.

- O’Neill, Brian C., Elmar Kriegler, Kristie L. Ebi, Eric Kemp‐Benedict, Keywan Riahi, Dale S. Rothman, Bas J. van Ruijven, Detlef P. van Vuuren, Joern Birkmann, and Kasper Kok. 2017. “The Roads Ahead: Narratives for Shared Socioeconomic Pathways Describing World Futures in the 21st Century.” _Global Environmental Change_ 42: 169–180.

- Pachauri, Shonali, Bas J. van Ruijven, Yu Nagai, Keywan Riahi, Detlef P. van Vuuren, Abeeku Brew‐ Hammond, and Nebojsa Nakicenovic. 2013. “Pathways to Achieve Universal Household Access to Modern Energy by 2030.” _Environmental Research Letters_ 8 (2): 024015. https://doi.org/10.1088/1748‐9326/8/2/024015.

- Samad, Hussain A., and Fan Zhang. 2016. “Benefits of Electrification and the Role of Reliability : Evidence from India.” WPS7889. The World Bank.

- http://documents.worldbank.org/curated/en/980911479147772730/Benefits‐of‐ electrification‐and‐the‐role‐of‐reliability‐evidence‐from‐India.

- Schmidt, Tobias S. 2014. “Low‐Carbon Investment Risks and de‐Risking.” _Nature Climate Change_ 4 (4): 237.

- “The Sustainable Development Goals Report 2018.” 2018. United Nations.

United Nations. 2015. “United Nations Energy Statistics Yearbook.” New York: United Nations.: United Nations.

- The World Bank. 2018. “Tracking SDG7 : The Energy Progress Report 2018.” 126026. The World Bank. http://documents.worldbank.org/curated/en/495461525783464109/Tracking‐SDG7‐ the‐energy‐progress‐report‐2018.

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