Financing conditions - A missing link to explain rapid ...

Florian Egli, Energy Politics Group, ETH Zürich

Financing conditions - A missing link to explain rapid cost decreases in renewable energies?Frontiers in Energy Research, Zurich/Switzerland, 5 March 2019

|Florian Egli | Energy Politics Group | ETH Zürich

EU Horizon 2020 Project“generate new, state-of-the-art low-carbon pathways for the European Union”

Cross-cutting finance work-stream Project partners

1

This work contributes to the European Union's Horizon 2020 research and innovation programme project INNOPATHS. It has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 730403 as well as from the Swiss State Secretariat for Education, Research and Innovation (SERI) [contract number 16.0222]. The opinions expressed & arguments employed herein do not necessarily reflect the official views of the Swiss Government.

Background

This talkThe research project


Agenda

2

Dynamics of financing conditions3

Finance and the energy transition2

Introduction1

Research question, method and data3.1

Results3.2

Conclusion4


Agenda

3



Introduction1


Results3.2

Conclusion4

|Florian Egli | Energy Politics Group | ETH Zürich 4

A milestone: the 2015 Paris Agreement

Introduction | Methods and Data | Results | Conclusion


We are not on track…

Introduction | Finance & energy transition | Dynamics | Conclusion

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1990 1995 2000 2005 2010 20150

2.000

12.000

4.000

6.000

8.000

10.000

Billion tons of CO2eq

Manufacturing industries and construction

Transport

Other EnergyOther

Electricity production (Excluding CHP)

Source:IEA, own calculationsNote:Other Energy includes CHP plants, hearing plants and other energy industry own use.

Low-carbon electricity is key to reach Paris Agreement targets


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Global average levelized cost of electricity generation(USD2016/kWh)

Note:For 2010 – 2017 based on IRENA data; wind data for earlier years based oninformation from BNEF and Lawrence Berkeley National Laboratory. Biomass datafrom earlier years referring to wooden biomass from Sweden, as provided byJunginger et al. 2006, Energy Policy 34, 4024-4041. Fossil-fuel based range fromIrena (2018), “Renewable Power Generation Costs in 2017”

0

5

10

15

20

25

30

35

40

45

1980 1985 1990 1995 2000 2005 2010 2015 2020

Fossil-fuel based electricity cost range

Solar PVWind

Sources:https://www.bloomberg.com/news/articles/2017-10-03/saudi-arabia-gets-cheapest-ever-bids-for-solar-power-in-auctionhttps://www.pv-magazine.com/2018/02/20/germanys-auction-for-large-scale-solar-bids-below-e0-04-kwh-for-the-first-time/https://www.greentechmedia.com/articles/read/mexican-solar-record-low-price-latin-america#gs.FVwCkgI

Renewable energy competitive in many places



Agenda

8



Introduction1


Results3.2

Conclusion4


Investment decision

Source: Polzin, F., Egli F., Steffen B., and Schmidt T.S. (2019). How Do Policies Mobilize Private Finance for Renewable Energy?—A Systematic Review with an Investor Perspective. Applied Energy (236), 1249–68.



Project finance

96%

88%

50%

22%

50%

94%

78%

100%

4%

12%

Solar PV

Windoffshore

Windonshore

6%Gas

Hard coal

Lignite

100%

Project finance Corporate finance

Feed

-in ta

riff

Mer

chan

t

German power generation projects 2010–2015

96%

88%

50%

22%

50%

94%

78%

100%

Gas

4%

Windoffshore

Windonshore

Solar PV

12%

Hard coal

6%

Lignite

100%

Project finance Corporate finance

Feed

-in ta

riff

Mer

chan

t

German power generation projects 2010–2015

Source: Steffen, B. (2018), The importance of project finance for renewable energy projects, Energy Economics (69), 280–294.

Project finance in practice


Project finance definition

Jargon: Sponsor realises project, lender provides financing

Project = separate legal and commercial entity (SPV)

Off-balance sheet Non-recourse; i.e., lender can only

access project asset and cash flows

The financing conditions are project-specific


NPV and the role of risk

y0

Cos

t Time

Rev

enue

s

y1 y2 y3 y4 y5

Cash-flow (nominal)

Investment costs (upfront)

Cash-flow (real)

y0

y1

y2

y3

y4

y5NPV

( )∑= +

+=n

tt

t

rcashflowinvestmentNPV

10 1

r = cost of capitalt = year of cash-flown = expected lifetime of investment



Components of the cost of capital

KE = cost of equityKD = cost of equityT = tax rate

r (1 )E D

E DK K T

V V= + −

E = equityD = debtV = project volume

Higher risks increase the cost of capital in several ways

- Increasing cost of debt and equity- Decreasing leverage (i.e., capital structure)- Other financial indicators (e.g., loan tenor)



For renewables, cost of capital particularly important

Note: Assumes 5% cost of debt, 10% cost of equity, European fuel costs. Fossil fuel based is the average of hard coal, natural gas and diesel.

Renewables w/ high upfront investment… …hence LCOE are sensitive to WACC

17%

18%

3%

15%

15%

56%

58%

85%

12%

8%Avr fossil fuel-based power

Wind turbines(onshore)

4%

SolarPhotovoltaic

9%

CAPEXCost of equityOPEX (O&M, fuel)Cost of debt

4%0%

0%

100%

27%

73% 56%

44%

8%

56%

135

105

44%

12%

81

59

Financing costsCAPEX & OPEX

LCOE $/MWh (example solar PV)

WACC

Percentage of LCOE



Agenda

14



Introduction1


Results3.2

Conclusion4


Renewable energy (RE) cost dynamics Detailed understanding on renewable

energy technology cost reductions,large ‘experience curve’ literature(e.g., Nemet 2006; Ferioli et al. 2009)

Role of financing dynamics of RE cost Conceptual studies on drivers impacting

RE investment decisions(e.g., Wüstenhagen & Menichetti 2012)

Model-based studies on impact of financing conditions on technology costs (e.g., Schmidt 2014; Hirth & Steckel, 2016)

1. How and why did solar PV and wind onshore financing conditions in DE change over time?

2. What is the effect of these changes on technology costs?

15

Research adds to experience curve & RE financing literatures

Our research questionsPrevious literature

Challenges:- Scarce data, as financial details of

project finance deals not disclosed- For “why” part: Interest rate levels

affected by multitude of drivers



We follow a mixed-method approach in four steps

Descriptive: Elicitation and mapping of project finance data Cost of equity, cost of debt/debt margin Leverage, loan tenor, debt service coverage ratio

Qualitative: Investor interviews to identify drivers for changes Semi-structured interviews, grounded theory-type coding of arguments

Quantitative: Regression analysis for experience curves Various specifications of dependent and independent variables

Model-based: Split-up of LCOE into technology cost effects Calibration of levelized cost of electricity (LCOE) in different settings

1

2

3

4



Deployment history (2000 – 2016)‒ Most solar deployed in 13 of 17 years‒ Most wind deployed in 8 of 17 years

Policy regime ‒ Electricity market liberalized since 1998 and investments

largely private‒ Landmark feed-in tariff in since 2000

Project finance Project-specific financing structures predominant for solar

and wind

17

Case selection – why Germany?

Best suited to study financing dynamics



Data: Interview sample

IDInterview type

Current organisation Current position

RET investment experience since

1 Structured Debt provider Head of Division Energy & Utilities 20062 Structured Debt provider Vice President 19903 Structured Debt provider Associate Director Project Finance & Capital Advisory 20114 Structured Debt provider Associate Director Infrastructure & Power Project Finance 20095 Structured Debt provider Executive Director Project Finance Renewable Energies 19976 Structured Debt provider Associate Director Global Infrastructure Debt 20137 Structured Debt provider Head Renewable Energies 19918 Structured Debt provider Project Finance Analyst 20079 Structured Debt provider Vice President Corporates & Small Business Project Finance 2007

10 Structured Debt provider Director Structured Finance Power & Renewables 200711 Structured Debt provider Director Structured Finance Utilities, Power & Renewables 200712 Structured Debt provider Senior Manager Structured Finance Renewable Energy 199913 Structured Debt provider Director Project & Structured Finance Utilities, Power, Ren. 200714 Structured Debt provider Director Corporate Strategy 199915 Structured Debt provider Head of Renewable Energies 199516 Structured Debt provider Head of Project Finance Origination Renewable Energies 201017 Structured Debt provider Managing Director Project & Acquisition Finance 200618 Structured Equity provider Head Risk Advisory 200519 Structured Equity provider CEO 200820 Structured Equity provider Founder and CEO 201321 Structured Equity provider Principal 201322 Structured Equity provider Partner 200923 Structured Equity provider Director Infrastructure Equity Investment Team 200624 Structured Equity provider Vice President Renewables 201525 Structured Equity provider CIO 201626 Structured Equity provider CEO 201627 Structured Equity provider Associate Director Energy & Cleantech 200628 Structured Equity provider Associate 200029 Structured Public actor Head Energy Services 200630 Structured Public actor Deputy Head Energy Management 201531 Structured Public actor CEO 201132 Structured Public actor Head Portfolio and Asset Management Renewable Energies 201033 Structured Public actor Vice President Origination and Structuring 201234 Exploratory Equity provider Founding Partner 200035 Exploratory Equity provider Investments Director 200636 Exploratory Equity provider Head Risk Advisory 200537 Exploratory Equity provider Partner 200938 Exploratory Equity provider Principal 201339 Exploratory Other Head Hybrid Power Solutions (former researcher) 200640 Exploratory Public actor Senior Investment Manager 200741 Exploratory Public actor Economist 2003

Exploratory interviews based on existing contacts

Theoretical interview sampling1. Publicly available addresses of

senior investment managers (BNEF)

2. Professional network (esp. via Allianz Climate Solutions)

3. Snowball sampling

17 private debt providers (13 commercial banks, 4 private investment banks)

16 private equity providers 7 public actors

(4 utilities that invested in RE, 3 public investment banks)

1 former researcher

Sampling

Sample



Data: Sample coverage

Project sample coverage

Capacity sample coverage

Investment sample coverage

42%

71%

19%

51%

15% 20%

58%

29%

81%

49%

85% 80%

Solar PV Wind onshore Solar PV Wind onshore Solar PV Wind onshore

100%

Sample coverage Rest


Source: Egli et al. (2018), cf. p.1.


Step 1: The data

0

5

10

15

20152010 20202000 2005 20102005 202020152000

CoCf debt

Solar PV Wind onshore




Step 1: The data (other financial indicators)

8

10

12

14

16

18

20

22

201520102000 2005 2020

eas

0.9

1.0

1.1

1.2

1.3

1.4

1.5

2000 2005 20152010 202020102005 20152000

0

0

0

0

0

2020

65

70

75

80

85

90

95

100

2015201020052000 2020

%

Leverage

Debt service coverage ratio

Year

Year

Wind onshore

d




Step 1: The dynamics

After-tax CoC (1 )E D

E DK K T

V V= + −


2.3

2.2

2.5

1.20.6

2.8

6

4

2

0

1.6

-69%5.1

0.9

Cost of debtCost of equity

2.1

1.4

2.31.1 1.0

2.4

0

1

2

3

4

5

6

4.5

1.9

0.9

-58%

Ø 2000 - 05 2017change




Step 2: The drivers

Economy

Renewable energy sector

Renewable energy

financing industry

Drivers of changes in financing conditions

Capital markets: Low-cost liquidity, few investment alternatives, low return expectations

Banks: Low-cost refinancing, low bank fees, preference for project finance

Availability of performance data: Accumulated operation experience of RET assets

Technology reliability: Proven track record of technology, low default rates of projects

Support policies: Regulatory environment, e.g. introduction of exposure to market risks

Learning by doing: In-house RET knowledge, better risk assessment and due diligence processes

Investment ecosystem: Standardised investment structures, frame contracts, partner networks

Market entry of investors: New investor types (e.g., large banks, insurers, pension funds), increasing investor competition

Level

Drivers specific to RET deployment and financing

Drivers related to general economic development

control for

estimate




Step 3: Identifying an experience effect

0.1

1.0

10.0

1 100 10,000

Wind onshore

0.1

1.0

10.0

1 100 10,000

Deb

t mar

gin

(%)

Solar PV

ER = 11 ± 8%ER = 11 ± 7%

Identification: 1

00

( ) ( )b

tt

IDebtMARGIN I DebtMARGIN II

−

=

Cumulative world investment ($) Cumulative world investment ($)




But…

0

1

2

3

4

5

6

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018

Year

%

Yield on 10 year German government bond (in %)



Step 3: Experience and financial crisis

2000 2005 2010 2015 2020

5

6

1

2

3

4

0

5.3%

2.5%

0.3%

2.1%

1.0%1.1%Bo

nd yi

eld

orm

argi

n(%

)

Year

Solar PV debt marginWind onshore debt marginGeneral interest rate level(10-year German government bond)




Financing expenditure of total LCOE

The change in financing expenditure

The channels contributing to the change

27

Step 4: Quantifying the effect on LCOE

, , 0i iit it CoC r it CoCLCOE LCOEδ = == −

, 1 , 2i i t i tδ δ= =∆ = −

EXP INT CAPEXi i i i∆ = ∆ + ∆ + ∆




Step 4: Channels of improved financing costs

313

187

8

0

100

200

300

400

500

LCO

E (U

S$ M

Wh

)

59%

2017

67

59

2000-2005

500

Change

36%4%

1%

ØØ

41% Change in

financing cost

54

85

7

28

0

20

40

60

80

100

120

($

)

60%

2017

62

2000-2005

113

Change

16%20%

4%

40% Change in

financing cost

General interest rate effectExperience effect

esLower capital expenditures

Change in financing cost from





Large effect of financing conditions on renewable energy cost empirically established – to be considered in changing interest rate environment: Future work on this under way

Experience effect qualitatively and quantitatively established – “co-benefit” of deployment policies for immature technologies

More work needed to - investigate other countries and technologies (differences)- reduce uncertainty on size of experience effect- understand learning mechanisms- understand risk perceptions in renewable asset financing

29

Conclusion



Thank you very much!@ETH_EPG | @floegli

Financing conditions - A missing link to explain rapid ...

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