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Benefits of energy efficiency policies in Thailand: an ex-ante evaluation of the energy efficiency action plan

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Abstract

The paper presents the results of an ex-ante evaluation of the economy-wide benefits that may be achieved through the implementation of the 20-year Energy Efficiency Action Plan (EEAP) in Thailand. The objective of the EEAP is to reduce energy intensity by 25 % in 2030 compared to 2010. This is to be reached by reducing the projected energy consumption by 20 % or 38 Mtoe until 2030. We have specified an analytical framework, which allows for a calculation of the overall energy cost savings, energy import cost reductions and reduced CO2 emissions. Moreover, we calculated the induced energy efficiency investments, employment effects and impacts on governmental budget. The evaluation shows that an effective implementation of the plan may lead to a reduction in energy expenditure of 37.7 billion EUR by 2030. Moreover, the EEAP-induced energy savings will significantly reduce the greenhouse gas emissions as well as Thailand’s energy import costs and generate private investment in energy efficiency of about 5 billion EUR annually in 2030, which in turn may lead to about 300,000 new jobs. The size of the net impact of the plan on Thailand’s governmental budget is uncertain due to positive and negative effects on corporate and income tax revenues, expenses for unemployment benefits, governmental energy consumption, expenses for energy subsidies and energy tax income.

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Notes

  1. Average real GDP growth rates were at 4.2 % between 2002 and 2012 (BOT 2013a, b).

  2. Kilotonne of oil equivalent. 1ktoe = 41.9 TJ = 11.6 GWh (IEA 2015).

  3. Tonne of oil equivalent.

  4. While energy security was enhanced by expanding domestic hydropower between the 1960s and 1990s, such infrastructure projects have been facing tremendous public opposition since the mid-1990s (Greacen and Palettu 2007).

  5. The EEAP includes values on expected energy savings, cost savings, CO2 reductions, but no information on the calculation approach and the assumptions.

  6. The quantification of rebound effects is outside the scope of this study.

  7. Emission estimations are based on CO2eq emission factors from the EEAP and therefore include not only carbon dioxide but also other greenhouse gases as CO2 equivalents.

  8. For savings from ‘traditional’ and ‘modern renewable energies’ listed in the EEAP impact assessment, the emission factor for biomass/charcoal listed was applied.

  9. For the conversion of end-use electricity to primary energy, a conversion factor of 2.5 has been applied. This factor results from average Thai electricity generation efficiency of about 40 % (Enerdata 2014).

  10. In practice, reductions in energy demand may impact the relative share of energy products (and the power plant loading order), as well as line losses (operating at capacity vs. below capacity). These effects can have significant impacts on greenhouse gas emissions but cannot be treated here.

  11. This calculation is based on the assumption of average GDP growth of 4.3 % (Ministry of Energy 2013). Estimates expect import expenses to rise from 34.2 billion EUR (1.4tn THB) in 2013 (EPPO 2013) to more than 120 billion EUR (5tn THB) in 2030 and are close to the forecast of IEA (2013).

  12. Energy efficiency subsidy programme in Thai industrial sector. Data on 428 energy efficiency measures are available to the authors (Nexant 2003).

  13. For currency adjustment, the following exchange rates were used: 1 US Dollar = 31.218 THB; 1 EURO = 40.186 THB (July 6, 2013 from Bankenverband (2013)). For energy unit conversion, conversion factors of Quasching (2003) were used.

  14. The external validity of non-Thai CSE values (i.e. their transferability) is questionable but the best approach at hand.

  15. Note: This approach calculates additional investments in energy efficiency, irrespective of the financing source. The investments may either come from other sectors, crowding-out alternative investments or be additional if funded, e.g. by additional credit programmes.

  16. Direct policy implementation costs have not been considered in this evaluation.

  17. In a previous version of this paper (Suerkemper et al. 2014), we used data from World Energy Outlook 2013. Note that IEA has revised Thai subsidy figures for the years 2011–2012 substantially and published new data for 2013 in the 2014 World Energy Outlook (IEA 2014b). For this study, this led to a downward revision of subsidy figures by about 2/3.

  18. Greacen and Greacen (2012) discuss how Thai utilities can be incentivised to promote energy efficiency.

  19. For details on deductions and allowances, see The Revenue Department (2013b).

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Acknowledgments

The research was partly funded by the International Climate Initiative (ICI) of the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (BMUB). We are grateful for the very helpful and detailed comments of several anonymous referees which greatly improved the paper. We also thank Thomas Adisorn for his support in revising the paper and Gregory Scutt for proofreading. Helpful comments to an earlier conference version were also provided by panellists of the IEPPEC 2014 conference.

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Authors and Affiliations

  1. Wuppertal Institute for Climate, Environment, Energy, Döppersberg 19, 42103, Wuppertal, Germany

    Felix Suerkemper, Johannes Thema & Stefan Thomas

  2. indepecon Unternehmergesellschaft, Sixtstr. 7, 75217, Birkenfeld, Germany

    Florian Dittus

  3. Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH (GIZ) c/o Energy Policy and Planning Office (EPPO), 3rd Fl. 121/1-2 Petchburi Rd. Ratchathewi, Bangkok, 10400, Thailand

    Monthon Kumpaengseth & Milou Beerepoot

Authors
  1. Felix Suerkemper
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  2. Johannes Thema
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  3. Stefan Thomas
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Corresponding author

Correspondence to Felix Suerkemper.

Appendix

Appendix

Input data: energy savings as expected by the EEAP

   

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

2026

2027

2028

2029

2030

Transport

Total

ktoe

57

158

531

1146

805

1350

2130

2750

4153

4275

5085

5924

6789

7685

8619

9585

10,579

11,603

12,658

15,323

Thermal

ktoe

57

158

531

1146

805

1350

2130

2750

4153

4275

5085

5924

6789

7685

8619

9585

10,579

11,603

12,658

15,323

Electricity

ktoe

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

GWh

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

Industry

Total

ktoe

18

50

429

1521

2634

3774

4916

6057

7200

8360

9629

10,886

12,092

12,611

13,131

13,757

14,373

14,992

15,625

16,256

Thermal

ktoe

2

5

255

1039

1822

2655

3488

4322

5155

5988

6918

7847

8758

9135

9512

9939

10,366

10,793

11,219

11,646

Electricity

ktoe

16

45

174

482

812

1119

1428

1735

2045

2372

2711

3039

3334

3476

3619

3818

4007

4199

4406

4610

GWh

184

525

2038

5658

9531

13,129

16,748

20,371

24,000

27,838

31,807

35,659

39,126

40,792

42,465

44,804

47,031

49,284

51,703

54,107

Large commercial buildings

Total

ktoe

12

26

182

342

509

679

851

1089

1319

1558

1810

2055

2246

2416

2595

2798

3001

3211

3418

3631

Thermal

ktoe

2

4

31

78

125

178

230

283

336

389

455

514

548

563

578

606

634

661

676

692

Electricity

ktoe

10

22

151

264

384

501

621

806

983

1169

1355

1541

1698

1853

2017

2192

2367

2550

2742

2939

GWh

118

260

1770

3103

4503

5883

7280

9451

11,534

13,715

15,902

18,092

19,918

21,747

23,664

25,725

27,788

29,922

32,170

34,493

SME and residence

Total

ktoe

74

158

296

490

690

854

1010

1196

1354

1526

1671

1836

2070

2278

2499

2712

2929

3157

3395

3635

Thermal

ktoe

33

67

104

171

240

300

361

424

489

556

615

676

768

832

898

961

1026

1092

1161

1231

Electricity

ktoe

41

91

192

319

450

554

649

772

865

970

1056

1160

1302

1446

1601

1751

1903

2065

2234

2404

GWh

478

1058

2261

3747

5282

6498

7606

9052

10,148

11,389

12,396

13,618

15,290

16,967

18,792

20,553

22,338

24,232

26,219

28,213

Total

Total

ktoe

160

392

1438

3500

4639

6656

8906

11,092

14,026

15,719

18,195

20,702

23,197

24,990

26,844

28,852

30,883

32,963

35,095

38,845

Thermal

ktoe

94

235

921

2434

2993

4483

6210

7779

10,133

11,208

13,073

14,961

16,863

18,215

19,607

21,091

22,604

24,149

25,714

28,891

Electricity

ktoe

66

157

517

1066

1646

2173

2696

3313

3893

4511

5122

5741

6334

6775

7237

7761

8279

8814

9381

9954

GWh

780

1842

6069

12,507

19,316

25,510

31,634

38,875

45,683

52,943

60,105

67,368

74,334

79,506

84,921

91,081

97,157

103,439

110,092

116,813

Corporate tax

Table 9 Tax rates by company type
Full size table

Income tax rates

Thai personal income taxes follow a progressive scheme (see Table 7). These rates are to be paid on the Footnote 19

$$ \mathrm{taxableincome}=\mathrm{assessableincome}-\mathrm{deductions}-\mathrm{allowances} $$
Table 10 Thai income tax rates
Full size table

Energy taxes

Table 11 Assumption on energy carrier taxation
Full size table

Petroleum products are charged with excise tax, municipality tax, VAT on wholesale price as well as on retail price. Conservation and oil fund levy are not affecting the governmental budget; these levies are for cross subsidisations of petroleum products and the promotion of energy efficiency measures. In cases of unknown price structures, only VAT was considered for tax revenue calculation.

Natural gas is primarily consumed in the industrial sector. As industry can reclaim VAT, respective revenues are not counted as ‘foregone’.

Electricity is consumed in all sectors. Foregone VAT revenues are calculated for the residential sector. As industry can reclaim VAT, respective revenues are not counted as ‘foregone’.

For coal and renewables, no information on taxes was available and thus not accounted for in the calculations.

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Suerkemper, F., Thema, J., Thomas, S. et al. Benefits of energy efficiency policies in Thailand: an ex-ante evaluation of the energy efficiency action plan. Energy Efficiency 9, 187–210 (2016). https://doi.org/10.1007/s12053-015-9357-z

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