2.1 APEC Energy efficiency

template

Elvira Torres Gelindon

Senior Researcher (ESTO)

The 16th APEC Workshop on Energy StatisticsTokyo, Japan, 10-12 July 2018

2

Outline of Presentation

Background

• Milestone

• Data components

Status of Energy Data Collection

• Submissions/Timeliness

• Completeness

Sample Analysis

• Use of indicators

Way forward

Feedback

Background

4

Dec 2014

•Introduction of Energy Efficiency template

Dec 2015

•Sent Questionnaire & User Manual

Mar–Apr 2016

•Collection of Questionnaire from APEC economies

May–June 2016

•Data evaluation

Nov 2016

•Reported progress in 28th EGEDA

June 2017

•Questionnaire revised per agreement in 28th

EGEDA

Sept–Oct 2017

•Submission evaluation

•Data analysis

Nov 2017

•Reported progress in 29th EGEDA

Jan 2018

•Questionnaire revised to include transport and industry sectors as agreed in 29th EGEDA

Milestone

5

2017 Revised questionnaire components

Commercial and Public Services

• Space Heating

• Space Cooling

• Lighting

• Other Building Energy Use

• Non-Building Energy Use

• Total Energy Use in Commercial Sector

Residential

• Space Heating

• Space Cooling

• Water Heating

• Cooking

• Lighting

• Refrigerators / Freezers

• Other kitchen facilities

• Laundry facilities

• Television/PC and other Home entertainment

• Other Appliances

• Total Energy Use in Residential Sector

Activity data

• Activity and structure indicators (population, HHs, floor area, etc)

• GDP

• Value added

To analyze energy demand and how to improve energy efficiency, detailed information for energy end-use / energy related data are important for policy makers & energy analysts.

6

Transport and Industry Sectors added

2018 Revised questionnaire components

Transport sector (by fuel)

•Road transport

•Railways

•Domestic Aviation

• Inland waterways

Industry sector (by fuel)

•Food products and textiles

•Wood and wood products

•Paper and paper products

•Chemicals, basic pharmaceuticals, petrochemicals

•Non-metallic minerals

•Basic metals

•Fabricated metals

•Motor vehicles, trailers etc

•All Other manufacturing

•Mining and Quarrying

•Construction

Activity data

• Number of vehicles ( by type, by mode, by fuel type)

• Passenger-km (Passenger)

• Vehicle-km

• Tonne-km (Freight)

Status of Data Collection

8

*Thailand shared some information, unfortunately not useful at the moment

2016 Revised EE template submission (1)

13 APEC-Non-OECDmembers

June 2018

Remarksnumber Timeliness Completeness

Submitted 6 5 2BD; HKC; PHL; RUS; CT; THA*

No submission

7

IEA/OECD members

June 2018

Remarksnumber Completeness

Shared 2 2 AUS; JPN

Chile shared old survey result but it still needs to be reflected in Chile’s end use data

9

Completeness

2016 Revised EE template submission (2)

Economy Activity Commercial Residential Transport Industry

BD No HH and transport related data; value added;

Aggregated data (by fuel) By fuel/mode

Aggregated data

HKC No data onheating/cooling; passenger-km; vehicle-km

Disaggregated by end-use By fuel/mode

By industry sub-sector

PHL No data on heating/cooling; passenger-km; vehicle-km

Aggregated data (by fuel) By fuel/mode

By industry sub-sector

Russia No data onheating/cooling; GVA and transport data

Aggregated data By fuel/mode

By industry sub-sector

CT Time-series gaps Disaggregated by end-use By fuel/mode

By industry sub-sector

Data analysis

11

Source : Members’ submission

BD

Electricity is the major fuel in the commercial sector

Commercial Energy consumption (ktoe)

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

160.00

180.00

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Oil Gas Coal RE Heat Elect

0.00

500.00

1,000.00

1,500.00

2,000.00

2,500.00

3,000.00

3,500.00

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Oil Gas Coal RE Heat Elect

HKC

0.00

500.00

1,000.00

1,500.00

2,000.00

2,500.00

3,000.00

3,500.00

4,000.00

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Oil Gas Coal RE Heat Elect

PHL

0.00

2,000.00

4,000.00

6,000.00

8,000.00

10,000.00

12,000.00

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Oil Gas Coal RE Heat Elect

THA

0.00

10,000.00

20,000.00

30,000.00

40,000.00

50,000.00

60,000.00

70,000.00

80,000.00

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Oil Gas Coal RE Heat Elect

RUS

0.00

1,000.00

2,000.00

3,000.00

4,000.00

5,000.00

6,000.00

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Oil Gas Coal RE Heat Elect

CT

elect

heat

gas

oil

RE

coal

12

Source : Members’ submission

BD

Electricity is the major fuel in the residential sector in BD; HKC and CT; renewables in the PHL and THA; heat in RUS

Residential Energy consumption (ktoe)

HKC PHL

THARUS CT

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

160.00

180.00

Oil Gas Coal RE Heat Elect

0.00

200.00

400.00

600.00

800.00

1,000.00

1,200.00

1,400.00

1,600.00

Oil Gas Coal RE Heat Elect

0.00

1,000.00

2,000.00

3,000.00

4,000.00

5,000.00

6,000.00

7,000.00

8,000.00

9,000.00

10,000.00

Oil Gas Coal RE Heat Elect

0.00

20,000.00

40,000.00

60,000.00

80,000.00

100,000.00

120,000.00

140,000.00

Oil Gas Coal RE Heat Elect

0.00

1,000.00

2,000.00

3,000.00

4,000.00

5,000.00

6,000.00

7,000.00

Oil Gas Coal RE Heat Elect

0.00

2,000.00

4,000.00

6,000.00

8,000.00

10,000.00

12,000.00

14,000.00

Oil Gas Coal RE Heat Elect

13

Energy consumption pattern per capita (1990-2015)

Commercial sector

Source : Members’ submission

Energy consumption per capita varied per economy; in commercial sector, energy per capita requirement increased together with income per capita

In HKC and RUS energy per capita in residential sector were almost constant while income per capita increased;

Residential sector

0.00

50.00

100.00

150.00

200.00

250.00

300.00

350.00

400.00

450.00

500.00

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 100.00

en

erg

y p

er

cap

ita

(to

e)

Income per capita at PPP (constant 2011 international $) ● Income per capita at PPP (current international $)

BD

HKCRUS

CT

THA

PHL

● Income per capita at (current international $)

0.00

100.00

200.00

300.00

400.00

500.00

600.00

700.00

800.00

900.00

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 100.00

en

erg

y p

er

cap

ita

(to

e)

Income per capita at PPP (constant 2011 international $) ● Income per capita at PPP (current international $)

BD

HKC

RUS

CTTHA

PHL

● Income per capita at (current international $)

14

Electricity consumption pattern per capita (1990-2015)

Income drives electricity consumption per person, as income increases electricity consumption per capita increases; in RUS and HKC, household electricity consumption was almost constant while income increases faster; in THA, electricity consumption grew faster than income per capita

Electricity has the biggest potential for energy efficiency

Commercial sector

Source : Members’ submission

Residential sector

0.00

50.00

100.00

150.00

200.00

250.00

300.00

350.00

400.00

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 100.00

en

erg

y p

er

cap

ita

(to

e)

Income per capita at PPP (constant 2011 international $) ● Income per capita at PPP (current international $)

BDHKC

RUS

CT

THAPHL

● Income per capita at (current international $)

0.00

50.00

100.00

150.00

200.00

250.00

300.00

350.00

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 100.00

en

erg

y p

er

cap

ita

(to

e)

Income per capita at PPP (constant 2011 international $) ● Income per capita at PPP (current international $)

BDHKC

RUS

CT

THAPHL

● Income per capita at (current international $)

15

Source : Members’ submission

by GVA (ktoe/GVA)

Energy intensity ktoe/GVA services constant 2010 USD and ktoe/services have different patterns but both show improvement over time

Energy intensity (Service sector)

0

500

1000

1500

2000

2500

3000

3500

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Brunei Darussalam Hong Kong, China Philippines Russia Chinese Taipei Thailand

Kto

e/C

on

sta

nt

20

10

US

D)

0

10

20

30

40

50

60

70

80

90

100

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Brunei Darussalam Hong Kong, China Philippines Russia Chinese Taipei Thailand

Kto

e/C

on

sta

nt

20

10

US

D)

By employees) (Ktoe/service worker)

*CT – GVA was constant LCU

16

Source : Members’ submission

GVA for services/Number of service workers

Value of out provided by each worker in the services sector was increasing overtime; BD’s case is unique as its income depends largely on oil and gas production

Labor productivity (Service sector)

0

50

100

150

200

250

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

Brunei Darussalam Hong Kong, China Philippines Russia Thailand

cons

tant

con

stna

t 20

10U

S$/w

orke

r

0

200

400

600

800

1000

1200

1400

1600

1800

19

90

19

91

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Chinese Taipei

con

stan

t LC

U/w

ork

er

17

Source : Economy submission

Hong Kong electricity consumption

Electricity consumption grew by CAGR 1.8% since 2001; space cooling and lighting declined by 2.2; space heating by 5.7% and all others increased by 2.1%

Aside from all others, space cooling share was 27%; lighting share 15% and space heating share was very small, on average

Commercial sector (1)

0.0

500.0

1,000.0

1,500.0

2,000.0

2,500.0

3,000.0

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

All others Space cooling Lighting Space heating

ktoe

18

Source : Economy submission

Intensity analysis – Ktoe/GVA services

Commercial sector (2)

Energy intensity in the commercial sector of HK continuously improving since 2000

-600%

-500%

-400%

-300%

-200%

-100%

0%

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Space heating Space cooling Lighting All others Total

19

Source : EGEDA

Japan - Energy consumption in manufacturing sector

Energy consumption in the manufacturing declined by 0.11% since 1990

Energy intensive industries include manufacturing of chemicals and petrochemicals (32%) and manufacturing of basic metals [iron and steel] (27%)

Industry sector (1)

0.0

20.0

40.0

60.0

80.0

100.0

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Food, Bev, Tob Textiles, wearing apparel

Wood and products Paper

Chemicals and petrochem Non-metallic min (Rubber..)

Basic Metals (iron and steel) Fabricated metal products, machinery and equipment

Motor vehicles, trailers, other transport equipment Not Elsewhere Specified

20

Source: EGEDA (Energy data), World Bank (GVA)

Japan – Intensity analysis

Growth in manufacturing GVA (0.7%) surpassed growth in total manufacturing energy consumption (-0.11%) since 1990

Decline in Japan’s energy consumption in manufacturing sector was mostly due to Structural effect and Activity effect

― energy intensive industries have a smaller share of GDP compared with the base year

The Pure intensity effect was obvious after 2005

Industry sector (2)

-40 000 -30 000 -20 000 -10 000 10 000 20 000 30 000

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

Activity Effect (billions of 2005$ PPP) Structure effect (billions of 2005$ PPP) Pure intensity (toe/USD) Change in manufacturing energy demand (ktoe)

21

Variables used in decomposition

Sector Sub-sector Activity (A) Structure (S) Intensity (I=E/A)

Household

Space heatingWater heatingCookingLightingAppliance

Population

Flr area/capitaPerson/hhPerson/hhFlr area/capitaOwnership/capita

Heat/floor areaEnergy/capitaEnergy/capitaElectricity/flr areaEnergy/appliance

Transport

CarsBusRailDom air

Passenger-km

Share of total passenger-km

Energy/passenger-km

Service Total services Services GDP Energy/GDP

Manufacturing

Paper and pulpChemicalsNon-metallicIron and steelNon-ferrous metalsFood and bev

Value added

Share of valueadded

Energy/value added

Other industry

Agri and fishingMiningConstruction

Value added

Share of total value added

Energy/value added

22

Continue analysing other sectors;

ESTO will make a study on energy efficiency indicators;

Assess template which indicators can be obtained or estimated; needs to be simplified.

Way forward

23

Feedback on filling out EE template?

problems encountered

share experiences in filling-out

How can ESTO help in filling out the data?

For Discussion

We appreciate any feedback

http://www.egeda.ewg.apec.org

Thank you for your kind attention