Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity...

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Alexey KABALINSKIY Korea, Jeju 27 - 28 March, 2017

Transcript of Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity...

Page 1: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

Alexey KABALINSKIY

Korea, Jeju 27-28 March, 2017

Page 2: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

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Introduction

Data collection

Modelling Methodology

Model assumptions

Selected results

Future work

Table of contents

Page 3: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

Introduction

Page 4: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

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• Volume 1: APEC: sectoral view

• Volume 2: Economy Review

APEC EDSO 6th edition

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The APEC Leaders have introduced an aspirational goal

of

”doubling the share of renewables in the APEC energy mix, including in power generation, from 2010 levels by 2030”

(Beijing Declaration, 2014)

APEC EDSO 6th edition Scenarios framework

Improved Efficiency

High Renewables

Alternative Power mix

Business-as-Usual (BAU)

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BAU and High Renewables scenario comparison

BAU High RE

Policies Current policy Support RE development

Energy demand Historical trend Historical trend

RE Capacity additions

Historical trend +Current policy

Historical trend +Current policy +

All announced targets

RE CAPEX Modest CAPEX reductionAccelerated CAPEX

reduction

RE Capacity factor

No/slow improvementAccelerated improvement

for Solar and Wind

Applicable All sectorsFocused on Power and

Transport, other sectors same as BAU

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Renewable Energy technologies in the 6th Edition

Renewables

HYDRO

Hydro

Pumped storage

WIND

Onshore

no grid storage

with grid storage

Offshore

no grid storage

with grid storage

SOLAR

Solar Photovoltaics

Utility

no grid storage

with grid storage

Solar Photovoltaics

rooftops

no grid storage

with grid storage

Concentrated Solar power

BIOENERGY GEOTHERMAL

Geothermal power

Page 8: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

Data collection

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Example of data sources

Publisher Selected publications

APEC • Establishment of the Guidelines for the Development of Biodiesel Standards in the APEC Region

IEA • Projected Costs of Generating Electricity• World Energy Statistics 2015• Integration of Variable Renewables

IRENA • Rethinking Energy: Towards a New Power System• Renewable Capacity Statistics 2016

REN21 • Renewables 2014 Global Status Report

FAO • Data on unutilized arable land, yields, trends

Economy’s data sources

• Ministries, statistics bureau etc.

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Energy policy context: Japan’s example

1 Act on Purchase of Renewable Energy-Sourced Electricity by Electric Utilities (2011)

RE specific legislation Strategic Energy Plan 2014 (Section 3, Chap. 3); Long-term Energy Supply and Demand Outlook 2015

RE-related policy/plan Energy mix increases RE to about 15% from 10% in FY2010

Target RE generation share

22%-24% in 2030 (hydro 9.2%, solar 7.9%, wind 1.7%)

Feed-in tariff (FiT) 23.10 ~ 57.75 JPY/kWh (tax included)1

Renewable Portfolio Standard (RPS)

Was available, but replaced by FiT

Tax incentive Tax for Climate Change Mitigation (2012)

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Renewable policies summary for power in APEC

Economy RE-specific legislation

RE-related policy /plan

Development strategy

Target RE generation share

Feed-in Tariff (FiT)

RE portfolio standard

(RPS)

Tax incentive

Australia √ √ √ 23.5% in 2020 - - √

Brunei Darussalam - √ √ 10% by 2035 - -

Canada - √ √ √* √* √* √

Chile √ √ √ 20% in 2025, 70% in 2050 - - -

China √ √ √ 20% primary in 2030 √ √ -

Hong Kong - √ √ √ - - √

Indonesia - √ √ 232 Mtoe (247.4 GW) in 2050 √ - √

Japan √ √ √ 22-24% in 2030 √ - √

Korea √ √ √ (13.4%) in 2035 - √ √

Malaysia √ √ √ 3% in 2020 √ √

Mexico √ √ √ (29.1%) in 2028 - - √

New Zealand - √ √ 90% in 2025 - -

Papua New Guinea - - - 100% in 2050 - -

Peru √ √ √ 60% (5%^) in 2020 - -

The Philippines √ √ √ (+9.9 GW, +200%) in 2030 √ √ √

Russia - √ √ 4.5%^ (25 GW^) in 2030 √ - -

Singapore - √ √ - - - -

Chinese Taipei √ √ √ 12.6% (27.1%) in 2030 √ - √

Thailand - √ √ 20% in 2036 √ √

United States - √ √ √* √* √* √

Viet Nam - √ √ 6% in 2030 √ - -

Note: √ = existing; - = not existing currently; * = applied in some local territories or states; ^ = target excludes large-scale hydro; (…) corresponds to installed renewables capacity targetsSources: APERC analysis and economy reports

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Biofuel policies in APEC

Economy Regulation Blend rate mandate Blend rate target Incentives, subsidies and

taxationBioethanol Biodiesel Bioethanol Biodiesel

Australia √ √* √* E4/E5* B2* √

Brunei Darussalam - - - - - -

Canada √ up to E8.5^ up to B4^ E5 B2 √

Chile - - - - - -

China - E10^ - 10 Mt (2020) 2 Mt (2020) √

Hong Kong √ - - - - √

Indonesia √ E3 B10 E20 (2025) B30 (2025) √

Japan √ √ - 0.5 million Loe (2017) √

Korea √ - B2 - B5 (2020) √

Malaysia √ - B7 - B10 √

Mexico √ E2 - √ - √

New Zealand - - - - - -

Papua New Guinea - - - - - -

Peru √ - - E7.8 B5 √

The Philippines √ E10 B2 E20 (2020) B20 (2025) √

Russia √ - - - - -

Singapore - - - - - -

Chinese Taipei √ - - - - √

Thailand - - B7 4 billion L/yr 5 billion L/yr √

United States √ up to E15^ up to B10^ 136 billion L/yr (2022)^ √

Viet Nam √ E5 -# E10 (2017) - √Note: √ = existing; - = not existing currently; * = applied in New South Wales and Queensland for bioethanol and in New South Wales for biodiesel; ^ = applied at federal level and in some local territories or states; # = biofuels traded with no mandated blend rate; Mt = million metric tonnes; Loe = litres of oil equivalent; L/yr = litres per year.Sources: APERC analysis and IEA statistics 2015.

Page 13: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

Modelling methodology

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Modelling Renewables in Power for BAU and High Renewables

• BAU demand is used in both cases

• Doubling the share of RE in power from 16.1% (2010) to 32.2% (2030)

• RE Supply curve based on LCOE

Running Power

Model for High RE

•Final results:

•for capacity and generation,

•refined CF (Variable RE),

•grid storage

RE in High RE

•High RE assumptions:

•maximum potential, targets,

•additional RE capacity as per supply curve

Running Power

Model for BAU

•Power results:

•refined capacity,

•generation (incl. daily load curves)

RE in BAU

•BAU assumptions:

•RE capacity,

•RE shares,

•RE CFs

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RE assumptions: Wind and Solar CAPEX in Australia

Shared vertical axis; Unit: USD

Source: APERC analysis

0

1,000

2,000

3,000

4,000

5,000

6,000

2012 2016 2020 2024 2028 2032 2036 2040

Wind technologies

BAU - WINDON - CAPEX - 2012-2040

BAU - WINDOFF - CAPEX - 2012-2040

HiREN - WINDON - CAPEX - 2012-2040

HiREN - WINDOFF - CAPEX - 2012-2040

2012 2016 2020 2024 2028 2032 2036 2040

Solar technologies

BAU - PVROOF - CAPEX - 2012-2040

BAU - PVUTILITY - CAPEX - 2012-2040

BAU - CSP - CAPEX - 2012-2040

HiREN - PVROOF - CAPEX - 2012-2040

HiREN - PVUTILITY - CAPEX - 2012-2040

HiREN - CSP - CAPEX - 2012-2040

Wind onshore

Wind offshore

PV Utility

PV Rooftop

CSP

2015 USD

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RE assumptions: CF for Wind and Solar in Australia

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

2010 2015 2020 2025 2030 2035 2040

BAU - SOLAR - CF - 2012-2040 HiREN - SOLAR - CF - 2012-2040

BAU - WIND - CF - 2012-2040 HiREN - WIND - CF - 2012-2040

Wind

Solar

Page 17: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

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Power model structure

Source: APERC

Power supply model structure

Load curves

Prices and costs• Energy and CO2 prices

• Initial/O&M costs

Existing capacity

Operational info.• Plant availability

• Capacity credit

• Efficiencies

• Minimum output level

• Reserve margin target

Policy information• Power development

plans/policies

• Renewables/nuclear

policies

Electricity

Supply

Model

Capacity additions

Investment needs

Generation by

plant type

Plant dispatch and

capacity factor

Fuel consumption

Emissions and

emission intensity

Total and average

power generation costs

‘Least cost’ approachCapacity addition and generation volume is

determined based on costs (initial, O&M,

fuel and carbon costs) under various

technical and political constraints.

Yearly demandDemand

modelsGeneration• Nuclear• Coal-fired (sub-

critical)• Coal-fired (super /

ultra-super critical)• Gas turbine• Gas combined cycle• Oil-fired• Solar PV & solar

thermal• Wind (onshore,

offshore)• Geothermal• Biomass and others

Storage• Pumped hydro• Battery

Modelled technologies

• Least cost optimisation model (written in GAMS)

Page 18: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

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Total cost ($/kWh)

LCOE for power generation

- Economic lifetime,

- capacity factor,

- CAPEX and OPEX,

- fuel cost,

- interest rate,

- loan repayment period,

- share of equity,

- cost of equity,

- thermal efficiency

System (grid) cost

Available generation

(GW or GWh)

Potential renewable energy

- Government target or plan

- organization reference,

- APERC expert estimates

Max. generation to the grid

Cost curve for renewable power

generation available in APEC

0

50

100

150

200

0 100 200

LC

OE o

f R

E p

ow

er,

$/M

Wh

RE potential, GW

0.00

0.10

0.20

0.30

0.40

0 1,000 2,000 3,000 4,000

$/k

Wh

TWh

Renewables supply cost curve

RE supply cost curve details

A mix of additional RE generation is defined by using the supply curve, while knowing the required RE generation for a certain year

Total cost of RE electricity = LCOE of RE generation + system (grid) costs

Page 19: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

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Variable RE assumptions and LCOE calculation

• Variable RE technologies, despite the grid storage are limited to:

– 20% in developing economies, and

– 30% in developed economies

• With technology improvement, and increasing CF, LCOE will lower each year,

𝐿𝐶𝑂𝐸 =

𝑡

𝐼𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡𝑡 + 𝑂&𝑀𝑡 + 𝐹𝑢𝑒𝑙𝑡 ∗ (1 + 𝑟)−𝑡

𝑡(𝐸𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦𝑡 ∗ (1 + 𝑟)−𝑡)

Where:

Investmentt : Investment in year “t” (i.e. CAPEX)

O&Mt : Operation and maintenance costs in year “t” (i.e. OPEX)

Fuelt : Fuel costs in year “t”

(1 + r)-t : The discount factor for year “t”

Electricityt : The amount of electricity produced in year “t”

• LCOE varies from $0.03/kWh (hydro) to $0.31/kWh solar PV rooftop

Page 20: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

Selected results

Page 21: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

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Renewables expand greatly in China, the United States and South-East Asia.

China is leading in both installed capacity and generation.

Current renewable policy falls short of the doubling

Renewable generation by scenario

0

1 000

2 000

3 000

4 000

5 000

6 000

7 000

8 000

9 000

10 000

1990

1995

2000

2005

2010

2015

2020

2025

2030

2035

2040

TW

h

Series17

Series16

Series15

RE generation in

HiREN

Policy RE

generation

RE generation in

BAU

→ Projection

RE policy, additional to BAU

Additional renewables based on least cost

Renewable generation in 2040

47%

4%

23%

5%

10%

3%8%

High Renewables

8 911 GWh

China

Russia

United States

Other north-east Asia

Other Americas

Oceania

South-East Asia

Note: this map is for illustrative purposes and is without prejudice to the status of or sovereignty over any territory

Page 22: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

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RE capacity increases fourfold from 620 GW to 2 510 GW (2030), translating to about 100 GW/yr

A lower CAPEX for solar leads to enormous increase in its installed capacity - 73 times increase from 2010 to 2030 compared with BAU

Renewable capacity in the High Renewables

Source: IEA (2015), APERC analysis

NOTE: BAU = Business-as-usual, HR = High Renewables

0

500

1 000

1 500

2 000

2 500

3 000

3 500

2000

2005

2010

2015

2020

2025

2030

2035

2040

GW

South-East Asia

Oceania

Other Americas

Other north-east Asia

Russia

United States

China

South-East Asia

Oceania

Other Americas

Other north-east Asia

Russia

United States

China

RE capacity in HR

RE capacity in BAU

→ Projection

0

500

1 000

1 500

2 000

2 500

3 000

3 5002000

2005

2010

2015

2020

2025

2030

2035

2040

GW

Geothermal+

Biomass and

others+Solar+

Wind+

Hydro+

Geothermal

Biomass and others

Solar

Wind

Hydro

RE capacity in HR

RE capacity in BAU

→ Projection

Page 23: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

Transport

Page 24: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

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Transport: projecting biofuel

Source: APERC analysis

• Historical production and productivity are used for the base year 2010, then productivity increases due to improved technology

• In each case regional feedstock potential is calculated

• Demand and Supply for two fuels: Bioethanol and Biodiesel are considered

• Doubling the share of RE from 2010 to 2030: 4.6% (= 2 x 2.3%)

Unit: Mtoe 2010 2015 2020 2025 2030 2035 2040

Total Biofuels Demand 28.6 38.3 46.2 51.3 55.6 60.7 64.6

Bioethanol 25.9 30.5 35.0 36.6 37.3 39.9 41.9

Biodiesel 2.8 7.8 11.2 14.7 18.3 20.7 22.8

Total BAU Supply Biofuels 62.0 71.8 77.6 83.6 89.6 95.6 100.9

Bioethanol 32.5 37.2 39.2 41.0 42.8 44.5 46.1

Biodiesel 29.5 34.7 38.4 42.6 46.8 51.1 54.9

APEC Biofuels Demand and Supply in BAU scenario

Page 25: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

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1st generation biofuels from 12 energy crops,

maximising the arable land and enhancing productivity,

surplus energy crops could be used as potential feedstock for biofuel supply,

Biofuels demand is estimated through the current gov’t biofuels policy and plan, in the absence of which, the supply potential is considered to introduce biofuels minimum blend rates.

Transport: biofuel supply potential estimation

Crop produduction

(tonnes)

Productivity

(tonnes/Ha)

Area

(Ha)

Surplus

Export

Domestic

consumption

GDP,

population

Food

consumption,

potential

feedstock for

biofuels

Potential

feedstock for

biofuel

Page 26: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

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Biofuel supply growing 2.7%/yr could meet over 5% of transport demand.

Enough bioethanol to meet the growing demand, and surplus of biodiesel.

APEC biofuels in BAU and the High Renewables scenario

Sources: APERC analysis and IEA statistics 2015.

0%

1%

2%

3%

4%

5%

6%

7%

8%

0

20

40

60

80

100

120

140

160

2010 2020 2030 2040 2010 2020 2030 2040

BAU High Renewables

Sh

are o

f b

iofu

els

Mto

e

Biodiesel demand

Bioethanol

demand

Biodiesel supply

potential

Bioethanol supply

potential

Share of biofuels(right axis)

Page 27: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

Future work

Page 28: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

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Future Work

Water-energy nexus (aspirational target)

Socio-economic-energy outlook

Improve load curves and power grid topology to quantify RE impacts

Detailed load curves being added for EDSO 7

APEC RE for Heating & Cooling applications assessment

Research project is underway

Detailed RE potential estimation by economy and by sector

Currently performed for Buildings and Industry (demand) and Bioenergy (supply)

Page 29: Alexey KABALINSKIY Korea, Jeju 27-28 March, 2017IEA • Projected Costs of Generating Electricity • World Energy Statistics 2015 • Integration of Variable Renewables IRENA •

http://aperc.ieej.or.jp/

Thank you!