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Bringing climate policy up to date – decreasing cost projections for renewable energy and batteries and their implications - Case study Chile Case study Chile

Authors: Hanna Fekete, Leonardo Nascimento

May 2019

Bringing climate policy up to date – decreasing cost projections for renewable energy and batteries and their implications

Case study Chile

Project number

17022

© NewClimate Institute 2019

Authors

Hanna Fekete, Leonardo Nascimento Contributing authors

Niklas Höhne, Jakob Wachsmuth

Disclaimer

This paper has been commissioned by the German Environment Agency (Umweltbundesamt, UBA) under contract 3717 41 1020. The views expressed in this paper do not necessarily comply with those of UBA and remain the authors’ responsibility. Cover picture: Photo by Jiri Rezac / CC BY-NC-SA 2.0

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Bringing climate policy up to date – decreasing cost projections for renewable energy and batteries

and their implications - Case study Chile

NewClimate Institute | May 2019 i

Table of Contents

Table of Contents ......................................................................................................................................i

List of Figures ........................................................................................................................................... ii

List of Tables ........................................................................................................................................... iii

Abbreviations ........................................................................................................................................... iv

1 Introduction ....................................................................................................................................... 1

2 The starting point: Renewables and electric vehicles in Chile’s NDC .............................................. 1

3 Results: Impact of revised cost estimates on emissions and fuel spending..................................... 3

4 Conclusions: NDC revision possible based on reduction of cost estimates ..................................... 5

References .............................................................................................................................................. 6

Annex I: Emissions levels tables ............................................................................................................. 7

Annex II: Methodological assumptions .................................................................................................... 7



NewClimate Institute | May 2019 ii

List of Figures

Figure 1 Comparison of adjusted emissions levels to NDC (absolute values and relative change of

emissions intensity compared to reference year 2007) ........................................................................... 3



NewClimate Institute | May 2019 iii

List of Tables

Table 1 Overview of different indicators in scenarios informing the NDC, matched to NDC targets ...... 2

Table 2 Comparison of technology cost projections in MAPS phase 2 and long-term energy strategy,

compared to global data from (Wachsmuth and Anatolitis, 2018). ......................................................... 2

Table 3 Adjusted technology additions resulting from reinvesting cost savings of RE and EV

technologies ............................................................................................................................................ 4

Table 4 Impact of reinvesting cost savings on fuel savings .................................................................... 4

Table 5 Adjusted emission levels resulting from considering decreased costs as presented in Figure 2

................................................................................................................................................................. 7

Table 7 Main methodological assumptions ............................................................................................. 7



NewClimate Institute | May 2019 iv

Abbreviations

CO2 Carbon dioxide

EVs Electric vehicles

GDP Gross Domestic Product

GHG Greenhouse Gas Emissions

MAPS Mitigation Action Plans and Scenarios

NDC Nationally Determined Contributions

RE Renewable energy



NewClimate Institute | May 2019 1

1 Introduction

Under the Paris Agreement, countries defined their mitigation commitments as part of their nationally

determined contributions (NDC) in the run-up to the Paris Climate Summit 2015, COP21. A few countries

have revised their NDCs since the adoption of the Paris Agreement (e.g. Argentina), or communicated

a different approach (e.g. USA will leave the Paris Agreement and no longer pursue its NDC). On

aggregate, NDCs are not yet sufficient to limit temperature increase to the limits agreed in the Paris

Agreement, and would lead to warming of about 3°C (Climate Action Tracker, 2018b).

The Paris Agreement foresees regular revisions of NDCs following the Global Stocktake, with the

objective to increase ambition over time. These revisions should be informed by up to date information

on the country circumstances (Northrop et al., 2018). Costs of zero or low-carbon technologies are one

factor that countries could consider when thinking about revised ambition levels.

The costs for renewable electricity generation and electric vehicles have dropped since the NDCs were

developed, and future cost projections also decreased as a result. Wachsmuth and Anatolitis (2018)

suggest a simple method to estimate increased RE capacities and EV penetration resulting from these

cost decreases. The method assumes that lower battery costs lead to a higher market uptake of EVs

and that the savings from decreased RE capacity cost are reinvested in the same technology. If

technology costs forecasts halved since the preparation of the NDC, for example, the country could now

add double the capacity compared to earlier expectations. Wachsmuth and Anatolitis provide global

data on future technology cost progressions since 2015.

Chile has submitted an NDC with an unconditional target of 30% reduction of GHG emissions-intensity

of GDP compared to 2007 by 2030. The NDC further contains a conditional target of a 35–45% reduction

of GHG emissions-intensity of GDP compared to 2007 by 2030 (Government of Chile, 2015a). Chile

has extraordinary conditions for renewable energy, with extremely high solar radiation and significant

wind resources (International Energy Agency, 2018).

Our analysis applies the method from Wachsmuth and Anatolitis to Chile, using country specific data

sources for costs and expectations on technology development. It aims to present the potential impact

of taking renewable generation and storage cost reductions into account to raise ambition of NDCs, as

one element of various to consider for NDC revisions. It first describes the expectations for renewable

energy and EV underlying the NDC and gathers cost estimates from that time and today. Section 3

illustrates potential adjusted target levels from the NDC, looking at increased ambition in renewable

energy and EVs exclusively. The last section discusses the results in the context of other policy

documents and current developments in the country and draws conclusions on the feasibility of the

adjusted numbers.

2 The starting point: Renewables and electric vehicles in

Chile’s NDC

Chile’s NDC states the following targets for climate change mitigation (Government of Chile, 2015a):

• Reduce CO2 emissions per GDP unit by 30% below their 2007 levels by 2030.

• Subject to the grant of international monetary funds, reduce CO2 emission per GDP unit by 2030

by 35% to 45% with respect to 2007 levels.




• Sustainable development and recovery of 100,000 hectares of forest land, mainly native, which

will account for greenhouse gas sequestrations and reductions of an annual equivalent of

around 600,000 kt of CO2 as of 2030.

The NDC document does not detail the development of specific sectors, except for land use, land-use

change and forestry. It is thus not possible to clearly say which renewable energy capacities and EV

expansion underlies the different reduction targets. However, the NDC is based on mitigation scenarios

developed under MAPS Chile (phase 2) (Government of Chile, 2015b), besides other (non-public)

sources.

This research uses the MAPS Chile (phase 2) scenarios to estimate the development of renewable

technologies and EVs: we match the absolute emission levels resulting from the targets according to

Climate Action Tracker to different scenarios from the MAPS study. This is a simplification, and it should

be noted that the NDC explicitly states that “measures analysed by the MAPS Chile Project do not

necessarily represent the mitigation strategy chosen by the Government of this country”.

Table 1 Overview of different indicators in scenarios informing the NDC, matched to NDC targets

Unconditional

target

Conditional

target - max

Conditional

target - min

Absolute emissions levels in 2030 (CAT

2018), excl. LULUCF [MtCO2e/year] 131 121 103

Closest MAPS phase 2 scenario Escenario Base Escenario ER Escenario alto

Additional PV capacity by 2030 in MAPS

scenario (2016 – 2030) 897 MW 2,833 MW 2,833 MW

Additional wind capacity by 2030 in MAPS

scenario (2016 – 2030) 3,036 MW 3,823 MW 3,823 MW

Additional EV by 2030 in MAPS scenario

(2016 – 2030) - - 5,000

Note that MAPS scenarios only foresee an increase in electric taxis. No EV taxis assumed in Base scenario. No

detail available for ER scenario.

Even though wind and solar installed capacity in 2030 of both conditional scenarios is the same, the

absolute emissions level is lower in Escenario alto because it assumes higher micro hydro and

geothermal installed capacity, which are technologies not covered by the current methodology.

The MAPS scenarios also provide costs for the different RE technologies. As part of the methodology,

we compare these estimates published in 2015 to more recent estimates from the Long-term Energy

Planning published by the Chilean Ministry of Energy (Ministerio de Energía, 2017c), see Table 2.

Table 2 Comparison of technology cost projections in MAPS phase 2 and long-term energy strategy,

compared to global data from (Wachsmuth and Anatolitis, 2018).

Solar PV Wind (onshore)

2020 2025 2030 2020 2025 2030

MAPS phase 2

(USD/kW)

1,730 to

2,640

1,490 to

2,270

1,260 to

1,930

1,650 to

2,420

1,550 to

2,260

1,450 to

2,120

Long-term energy

strategy (USD/kW)

1,020 to

1,190

760 to

1,070

630 to

1,030

1,700 to

1,800

1,460 to

1,800

1,380 to

1,800

Reduction of cost

estimate

-55% to -

41%

-53% to -

49%

-50% to -

47%

-26% to

+2%

-20% to -

5%

-15% to -

4%

Global reduction of

cost estimate

-50% to -

25%

-52% to -

20%

-52% to -

17%

-56% to -

30%

-51% to -

11%

-51% to -

15%

Note: Global reduction of cost estimates are based on the Levelized Costs of Energy, while Chile specific estimates

result from investment costs (because of data availability)




For electric vehicle or battery costs, no country specific data for Chile is available. Chilean sources refer

to the Bloomberg report, also used by Wachsmuth and Anatolitis (2018). We use the global data

reported there for this technology (reductions of cost estimates of -33% to+40% the last historical year,

-32% to +14% for 2025, and -52% to -19% for 2030).

The savings from decreased fuel spending remain as a net-benefit to the economy. Theoretically, Chile

could reinvest those and iterate this step until the additional savings tend towards zero. Such an

approach would maximise the technology additions while balancing costs and benefits. Nonetheless,

there might be a mismatch of actors within the country. For example, owners of electric vehicles will not

invest their fuel savings in more EVs. For power generation, fuel savings are a result of displacing fossil

technology. Actors spending less in fuel are fossil power producers that will not necessary invest the

savings in renewable energy alternatives.

3 Results: Impact of revised cost estimates on emissions

and fuel spending

Assuming that cost savings are reinvested completely in the same technology and within the same time

period (2016 – 2020, 2021 – 2025, and 2026 – 2030) leads to increased additions in renewable

capacities and electric vehicles, according to the method suggested by Wachsmuth and Anatolitis

(2018), which in turn causes changes in GHG emissions and fuel spending.

Figure 1 and Table 3 illustrate the resulting adjusted emissions levels compared to the NDC values,

depending on the original ambition level (unconditional target, or conditional min/max) and the

assumption of reduction of cost estimates (worst case/best case). The unconditional NDC target of 30%

improvement of GHG intensity compared to 2007 moves downward by 1 to 2 p.p., and the conditional

targets of 35% to 45% by 3 to 5 p.p. This reflects a reduction of 2 to 4 MtCO2e in 2030 of the

unconditional target and 7 to 10 MtCO2e in 2030 of the conditional target range.

Figure 1 Comparison of adjusted emissions levels to NDC (absolute values and relative change of

emissions intensity compared to reference year 2007)

131

103

121

93

127

-129

93-9

6

11

2-1

15

0

20

40

60

80

100

120

140

2007 2030Unconditional

2030Conditional

min

2030 -Conditional

max

GH

G e

mis

sio

ns

excl

. LU

LUC

F [M

tCO

2e/

yea

r]

NDC Historical values Adjusted NDC - best case Adjusted NDC - worst case

-30%

to

-31

%

-45

% t

o -4

9%

-35

% t

o -3

9%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

2030Unconditional

2030Conditional

min

2030 -Conditional

max

Rel

ati

ve c

ha

nge

co

mp

are

d t

o r

efer

ence

yea

r 2

00

7




Table 4 shows the adjusted capacity additions and EV penetration, compared to the original values.

Total renewable electric capacity additions over 2016 – 2030 are 1.0 – 1.7 GW higher than under

scenarios that represent the unconditional NDC target. In the scenario closest to the conditional targets,

capacity additions between 2016 and 2030 would even be 2.9 to 4.1 GW higher. The increase of EV is

more modest since they are only considered under the highest ambition level. Implementation of the

adjusted ambition would lead to about 460 to 4,200 additional vehicles over the period up to 2030. Even

though this represents a small absolute improvement, the more optimistic end is a significant increase

compared to the original value of 5,000 vehicles by 2030.

The savings from decreased fuel spending remain as a net-benefit to the economy. Theoretically, Chile

could reinvest those and iterate this step until the additional savings tend towards zero. Such an

approach would maximise the technology additions while balancing costs and benefits. Nonetheless,

there might be a mismatch of actors within the country. For example, owners of electric vehicles will not

invest their fuel savings in more EVs. For power generation, fuel savings are a result of displacing fossil

technology. Actors spending less are fossil power producers that will not necessary invest the savings

in renewable energy alternatives.

Table 3 Adjusted technology additions resulting from reinvesting cost savings of RE and EV

technologies

Unconditional

target

Conditional

target - max

Conditional

target - min

Additional PV capacity (cumulative over 2016 –

2030) [MW] 847 to 919 2,664 to 2,911 2,664 to 2,911

Additional wind capacity (cumulative over 2016

– 2030) [MW] 120 to 719 132 to 938 132 to 938

Additional EV (cumulative over 2016 – 2030)

[number of vehicles] - - 458 to 4,191

Note that MAPS scenarios only foresee an increase in electric taxis. No EV taxis assumed in Base scenario. No

detail available for ER scenario.

Considering the cumulative capacity up to 2030, the method estimates of emissions reductions and fuel

savings implied. For Chile we assume that all additional renewable electricity generation supports the

phase-out of coal, which Chile has committed to (Ministerio de Energia del Gobierno de Chile, 2018). A

small share of RE electricity fulfils the additional electricity demand from EVs. We assume that the

additional renewable electricity replaces coal-based generation exclusively.

Shifting away from coal also results in fuel savings; 92% of Chilean coal demand is needed for electricity

generation. Reduction in coal installed capacity would results in a proportional decrease in fuel

consumption for electricity generation if the same capacity factor for all coal-fired power plants is

assumed. Main assumptions are available in detail in Annex II.

Table 4 Impact of reinvesting cost savings on fuel savings

Unconditional NDC Conditional NDC – max Conditional NDC - min

2025 2030 2025 2030 2025 2030

Savings from decreasing

coal electricity generation

[Million USD/year]

-47 to -

122

-72 to -

154

-184 to -

382

-339 to -

588

-184 to -

382

-339 to -

589

Savings from decreasing

oil demand in transport

[Million USD/year]

0 0 0 0 0 to -1 0 to -3

Note: The increased electricity demand from EVs is deducted from the additional renewable electricity generation

and thus reflected in these estimates.




4 Conclusions: NDC revision possible based on reduction

of cost estimates

This research suggests that by considering technology cost developments of wind, solar PV and

batteries since 2015, Chile could increase the ambition of its NDC targets. Assuming that cost savings

in those technologies would be reinvested in the same area, the unconditional NDC target of 30%

improvement of GHG intensity compared to 2007 moves downward by 1 to 2 pp, and the conditional

targets of 35% to 45% by 3 to 5 pp. This reflects a reduction of 2 to 4 MtCO2e in 2030 of the unconditional

target, and 7 to 10 MtCO2e in 2030 of the conditional target range.

Compared to current developments in the country, the adjusted renewable energy additions seem

feasible; the adjusted numbers would mean an average annual capacity increase of wind and solar of

0.4 to 0.8 GW up to 2030. In 2016, 0.7 GW wind and solar PV came online in Chile, in 2017 the

combined installed capacity was 1.4 GW (IRENA, 2018). The current policies scenario of the Mitigation

Plan for the Energy Sector of the Ministry of Energy increases solar and wind capacities by 0.6 GW per

year up to 2030 on average (Ministerio de Energía, 2017b), compare scenario “politicas actuales

(=current policies)”, and is thus within the range. For comparison: the MAPS phase 2 scenarios which

informed the NDC had expected average annual capacity additions of 0.3 to 0.5 GW.

Chile is also starting to push electric vehicles. In 2017, Chile published the National Strategy on

Electromobility, stating that in 2050, 40% of private vehicle in 2050 and 100% of public transport shall

run on electricity (Ministerio de Energía, 2017a). Since then, it supported the first 60 electric taxis, and

introduced 100 electric buses (Aislinn Laing, 2018; Climate Action Tracker, 2018a). Chile has opened

bids to increase electric taxis outside Santiago (Electricidad, 2019) and is also expanding the charging

stations grid (Aislinn Laing, 2018). In spring 2018, there were about 300 EVs on Chile’s roads

(BNAmericas, 2018). This number today is still far below our analysis which presents an adjusted

number for EVs of 5,500 to 9,100 in 2030. However, experience in other countries has shown, that

electric vehicle penetration can increase extremely quickly (Bloomberg NEF, 2018). In any case, the

development so far is more ambitious than the EV penetration expected in the MAPS phase 2 scenarios,

that we mapped to the unconditional NDC target and to the less ambitious end of the conditional targets.

As a result of the methodology, dividing the original capacity additions with the cost reduction factor

results in higher capacity increase in scenarios that originally assume more ambitious RE additions.

This may seem counter-intuitive as one could assume that in a less ambitious scenario it would be

easier to increase the share of renewables. Also, technologies that do not have a role in the original

NDC will remain outside the scope of analysis (because multiplying any cost reduction with zero capacity

addition results in zero). In practice this means that EVs are only pushed further in the more ambitious

end of the conditional target, because only the scenario underlying this target considers EVs at all.

Finally, the method does not consider limitations of the scope, e.g. as is the case for EVs, where the

MAPS phase 2 scenarios only look at electric taxis.

This research recommends considering the stronger-than-expected decrease in technology costs when

adjusting the Chilean NDC. This document provides a first rough estimate of the potential impact of this

development. The examples shown here for a few technology areas using a simplified method illustrate

that the fast developments can have a significant impact on future ambition. Still, revising the NDC would

need to consider several other developments in other sectors, as well as their interlinkages, while

evaluating the broader political and economic landscape.




References

Aislinn Laing (2018) Enel y BYD dicen implementación de autobuses eléctricos en Chile anticipan más inversiones para la región, Reuters. Available at: https://lta.reuters.com/articulo/chile-transporte-enel-byd-idLTAKBN1OC2SF (Accessed: 15 May 2019).

Bloomberg NEF (2018) Electric Vehicle Outlook 2018. Available at: https://about.bnef.com/electric-vehicle-outlook/ (Accessed: 10 July 2018).

BNAmericas (2018) ‘Chilean Energy Minister inaugurates fleet of electric cars’, 22 March. Available at: https://www.bnamericas.com/en/news/electricpower/chilean-energy-minister-inaugurates-fleet-of-electric-cars.

Climate Action Tracker (2018a) Climate Action Tracker - Chile. Available at: http://climateactiontracker.org/countries/chile.html.

Climate Action Tracker (2018b) Some progress since Paris, but not enough, as governments amble towards 3°C of warming. Available at: https://climateactiontracker.org/documents/507/CAT_2018-12-11_Briefing_WarmingProjectionsGlobalUpdate_Dec2018.pdf.

Electricidad (2019) ‘Región de Valparaíso contará con 120 taxis eléctricos este año’. Available at: http://www.revistaei.cl/2019/01/09/region-valparaiso-contara-120-taxis-electricos-este-ano/# (Accessed: 15 May 2019).

Government of Chile (2015a) Intended Nationally Determined Contribution towards the Climate Agreement of Paris 2015.

Government of Chile (2015b) MAPS Chile Mitigation Options for a Low Carbon Development.

International Energy Agency (2018) Energy Policies beyond IEA Countries - Chile 2018. doi: http://dx.doi.org/10.1787/23070897.

IRENA (2018) IRENA Country Profile - Chile. Available at: http://resourceirena.irena.org/gateway/countrySearch/?countryCode=CHL (Accessed: 14 October 2018).

Ministerio de Energía (2017a) ‘Estrategia Nacional de Electromovilidad Un camino para los vehículos eléctricos’.

Ministerio de Energía (2017b) Plan de Mitigación de Gases de Efecto Invernadero para el Sector Energía.

Ministerio de Energía (2017c) Proceso de Planificación Energética de Largo Plazo.

Ministerio de Energia del Gobierno de Chile (2018) Gobierno y Generadoras anuncian fin de nuevos desarrollos de plantas a carbón. 30 January, 2018, http://www.energia.gob.cl. Ministerio de Energia del Gobierno de Chile. Available at: http://www.energia.gob.cl/tema-de-interes/gobierno-y-generadoras-anuncian (Accessed: 27 November 2018).

Northrop, E. et al. (2018) Working Paper - Achieving the Ambition of Paris: Designing the Global Stocktake. Available at: https://wriorg.s3.amazonaws.com/s3fs-public/achieving-ambition-paris-designing-global-stockade.pdf.

Wachsmuth, J. and Anatolitis, V. (2018) Bringing climate policy up to date – decreasing cost projections for renewable energy and batteries and their implications. Dessau-Roßlau; Germany. Available at: http://www.umweltbundesamt.de/publikationen.




Annex I: Emissions levels tables

Table 5 Adjusted emission levels resulting from considering decreased costs as presented in Figure 2

Reference Unconditional NDC Conditional NDC -

max

Conditional NDC -

min

Original

value

Original

value

With

updated

cost

estimates

Original

value

With

updated

cost

estimates

Original

value

With

updated

cost

estimates

2007 2030 2030 2030 2030 2030 2030

Emission

levels (excl.

LULUCF, in

MtCO2e/year)

91 131 127 to 129 121 112 - 114 103 94 to 96

Emission

intensity

relative to 2007

-30% -31% to -

32% -35%

-39% to -

40% -45%

-48% to -

50%

Annex II: Methodological assumptions

Table 6 Main methodological assumptions

Technology Type Assumption Source

All Data sources

MAPS scenarios attributed to NDC targets based on emissions

levels in 2030

Unconditional scenario: Escenario Base

Conditional scenario:Escenario Alto

Conditional scenario: Escenario ER

Chile NDC and

MAPS

Solar Assumption Assumed all solar electricity generation is PV (neglecting solar

thermal installations) Expert judgement

Wind Assumption Assumed only wind onshore because of lack of flat coasts. Also,

there is currently no wind offshore installed. IRENA

EVs Assumption

MAPS scenario only foresees an increase in electric taxis. No EV

taxis assumed in Base scenario. No detail is available for ER

scenario.

MAPS

EVs Assumption Assumed Chilean battery cost reduction will follow global trends Informe Final

2017/2018

Wind and Solar Assumption Coal phase out planned, so assumed that additional RE will

support this phase out and displace coal-fired power generation MAPS

EVs Assumption

Assumption that EVs will decrease gasoline/diesel emissions, but

increase electricity emissions (average grid intensity factor, no

overlap with RE additions considered)

Expert judgement

Wind and Solar Assumptions

Coal capacity reduction will impact coal demand proportionally.

Assumption i: all coal-fired power plants have the same capacity

factor, Assumption ii: only impact the share of coal demand that

goes to electricity.

Expert judgement

EVs Assumption

For each extra EV, one gasoline or diesel car were removed from

the fleet. This results in fuel savings proportional to the number of

cars, their overall fuel consumption and fuel prices.

Expert judgement

Wind and Solar Calculation

Lowest cost projections result in less savings so that is considered

the worst-case scenario. Highest cost projections were used for

the best -case scenario.

Expert judgement

EVs Calculation Average fuel consumption: 0.06 l/km Expert judgement

EVs Calculation Average distance: 20,000 km/year Expert judgement

Wind and Solar Calculation

Power capacity and generation for renewables used to calculate

capacity factor. Capacity factor used to translate capacity into

power generation.

IRENA

http://resourceirena.irena.org/gateway/countrySearch/?countryCode=CHL

http://pelp.minenergia.cl/informacion-del-proceso/resultados

http://pelp.minenergia.cl/informacion-del-proceso/resultados

http://resourceirena.irena.org/gateway/countrySearch/?countryCode=CHL




Technology Type Assumption Source

Wind and Solar Calculation Emissions intensity of fossil fuels in 2015 used to calculate

emissions reduction. IEA Balances

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