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ALTERNATIVES FOR POWER GENERATION IN THE GREATER MEKONG SUB-REGION Volume 3: Power Sector Vision for the Lao People’s Democratic Republic Final 20 March 2016

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  • ALTERNATIVES FOR POWER GENERATION IN THE GREATER MEKONG SUB-REGION

    Volume 3:

    Power Sector Vision for the Lao People’s Democratic Republic

    Final

    20 March 2016

  • FINAL

    Intelligent Energy Systems IESREF: 5973 ii

    Disclaimer

    This report has been prepared by Intelligent Energy Systems Pty Ltd (IES) and Mekong

    Economics (MKE) in relation to provision of services to World Wide Fund for Nature (WWF).

    This report is supplied in good faith and reflects the knowledge, expertise and experience of

    IES and MKE. In conducting the research and analysis for this report IES and MKE have

    endeavoured to use what it considers is the best information available at the date of

    publication. IES and MKE make no representations or warranties as to the accuracy of the

    assumptions or estimates on which the forecasts and calculations are based.

    IES and MKE make no representation or warranty that any calculation, projection,

    assumption or estimate contained in this report should or will be achieved. The reliance that

    the Recipient places upon the calculations and projections in this report is a matter for the

    Recipient’s own commercial judgement and IES accepts no responsibility whatsoever for any

    loss occasioned by any person acting or refraining from action as a result of reliance on this

    report.

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    Intelligent Energy Systems IESREF: 5973 iii

    Acronyms

    AD Anaerobic Digestion

    ADB Asian Development Bank

    ASEAN Association of Southeast Asian Nations

    ASES Advanced Sustainable Energy Sector

    BAU Business As Usual

    BNEF Bloomberg New Energy Finance

    BTU / Btu British Thermal Unit

    CAGR Compound Annual Growth Rate

    CAPEX Capital Expenditure

    CCGT Combined Cycle Gas Turbine

    CCS Carbon Capture and Storage

    COD Commercial Operations Date

    CSP Concentrated Solar Power

    DNI Direct Normal Irradiation

    DTU Technical University of Denmark

    EDL Electricité du Laos

    EE Energy Efficiency

    EGAT Electricity Generation Authority of Thailand

    EIA Energy Information Administration

    EVN Electricity of Vietnam

    FAO Food and Agriculture Organisation of the United Nations

    FOB Free on Board

    FOM Fixed Operating and Maintenance

    GDP Gross Domestic Product

    GHI Global Horizontal Irradiance

    GMS Greater Mekong Subregion

    GT Gas Turbine

    HV High Voltage

    ICT Information and Communication Technology

    IEA International Energy Agency

    IES Intelligent Energy Systems Pty Ltd

    IPP Independent Power Producer

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    Intelligent Energy Systems IESREF: 5973 iv

    IRENA International Renewable Energy Agency

    LCOE Overall Levelised Cost of Electricity

    LNG Liquefied Natural Gas

    MEM Ministry of Energy and Mines

    MERRA Modern Era-Retrospective Analysis

    MKE Mekong Economics

    MOU Memorandum of Understanding

    MV Medium Voltage

    NASA National Aeronautics and Space Administration (the United States)

    NPV Net Present Value

    NREL National Renewable Energy Laboratory (the United States)

    OECD Organisation for Economic Co-operation and Development

    OPEC Organisation of the Petroleum Exporting Countries

    OPEX Operational Expenditure

    PDR People’s Democratic Republic (of Laos)

    PRC People’s Republic of China

    PV Photovoltaic

    RE Renewable Energy

    ROR Run of River

    SCADA/EMS Supervisory Control and Data Acquisition/Energy Management System

    SES Sustainable Energy Sector

    SWERA Solar and Wind Energy Resource Assessment

    SWH Solar Water Heating

    UN United Nations

    USD United States Dollar

    VOM Variable Operating and Maintenance

    WEO World Energy Outlook

    WWF World Wide Fund for Nature

    WWF-GMPO WWF – Greater Mekong Programme Office

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    Intelligent Energy Systems IESREF: 5973 v

    Table of Contents

    1 Introduction 7

    1.1 Report Structure 7 2 Background: Lao PDR Electricity Sector 9

    2.1 Industry Structure 9 2.2 Power System 10 2.3 Installed Capacity 12 2.4 Electricity Demand 13 2.5 Generation Supply 15 2.6 Exports and Imports 16

    3 Development Options for Lao PDR Electricity Sector 20

    3.1 Natural Gas Resources 20 3.2 Coal Resources 20 3.3 Hydro Power 21 3.4 Wind Power 22 3.5 Solar Power 25 3.6 Geothermal Energy 29 3.7 Biomass and Biogas 29 3.8 Renewable Energy Potential and Diversity 31

    4 Lao PDR Development Scenarios 33

    4.1 Scenarios 33 4.2 Technology Cost Assumptions 36 4.3 Fuel Pricing Outlook 38 4.4 Lao PDR Real GDP Growth Outlook 39 4.5 Population Growth 41 4.6 Committed Generation Projects in BAU, SES and ASES Scenarios 41 4.7 Regional Transmission System Integration 42 4.8 Imports and Exports 43 4.9 Technical Economic Power System Modelling 43

    5 Business as Usual Scenario 46

    5.1 Business as Usual Scenario 46 5.2 Demand Growth 46 5.3 Installed Capacity Development 48 5.4 Projected Generation Mix 51 5.5 Grid to Grid Power Flows 54 5.6 Generation Fleet Structure 54 5.7 Reserve Margin and Generation Trends 56 5.8 Electrification and Off Grid 58

    6 Sustainable Energy Sector Scenario 59

    6.1 Sustainable Energy Sector Scenario 59 6.2 Demand Growth 59 6.3 Installed Capacity Development 61 6.4 Projected Generation Mix 64 6.5 Grid to Grid Power Flows 67 6.6 Generation Fleet Structure 67 6.7 Reserve Margin and Generation Trends 69 6.8 Electrification and Off-Grid 71

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    Intelligent Energy Systems IESREF: 5973 vi

    7 Advanced Sustainable Energy Sector Scenario 72

    7.1 Advanced Sustainable Energy Sector Scenario 72 7.2 Demand Growth 72 7.3 Installed Capacity Development 74 7.4 Projected Generation Mix 77 7.5 Grid to Grid Power Flows 80 7.6 Generation Fleet Structure 80 7.7 Reserve Margin and Generation Trends 82 7.8 Electrification and Off-Grid 84

    8 Analysis of Scenarios 85

    8.1 Energy and Peak Demand 85 8.2 Energy intensity 87 8.3 Generation Mix Comparison 88 8.4 Carbon Emissions 90 8.5 Hydro Power Developments 91 8.6 Analysis of Bioenergy 91 8.7 Security of Supply Indicators 93 8.8 Interregional Power Flows 95

    9 Economic Implications 97

    9.1 Overall Levelised Cost of Electricity (LCOE) 97 9.2 LCOE Composition 98 9.3 Cumulative Capital Investment 100 9.4 Operating, Amortised Capital and Energy Efficiency Costs 105 9.5 Fuel Price Sensitivity 110 9.6 Impact of a Carbon Price 110 9.7 Renewable Technology Cost Sensitivity 111 9.8 Jobs Creation 112

    10 Conclusions 115

    10.1 Comparison of Scenarios 115 10.2 Economic Implications 116 10.3 Identified Barriers for the SES and ASES 117 10.4 Recommendations 118

    Appendix A Technology Costs 120

    Appendix B Fuel Prices 124

    Appendix C Methodology for Jobs Creation 125

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    Intelligent Energy Systems IESREF: 5973 7

    1 Introduction

    Intelligent Energy Systems Pty Ltd (“IES”) and Mekong Economics (“MKE”) have been

    retained by WWF – Greater Mekong Programme Office (“WWF-GMPO”) to undertake a

    project called “Produce a comprehensive report outlining alternatives for power generation

    in the Greater Mekong Sub-region”. This is to develop scenarios for the countries of the

    Greater Mekong Sub-region (GMS) that are as consistent as possible with the World Wildlife

    Fund’s Global Energy Vision to the Power Sectors of all Greater Mekong Subregion countries.

    The objectives of WWF’s vision are: (i) contribute to reduction of global greenhouse

    emissions (cut by >80% of 1990 levels by 2050); (ii) reduce dependency on unsustainable

    hydro and nuclear; (iii) enhance energy access; (iv) take advantage of new technologies and

    solutions; (v) enhance power sector planning frameworks for the region: multi-stakeholder

    participatory process; and (vi) develop enhancements for energy policy frameworks.

    The purpose of this report is to provide detailed country-level descriptions of three scenarios

    for the power sector of Lao People’s Democratic Republic (Lao PDR):

    Business as Usual (BAU) power generation development path which is based on current

    power planning practices, current policy objectives;

    Sustainable Energy Sector (SES) scenario, where measures are taken to maximally

    deploy renewable energy1 and energy efficiency measures to achieve a near-100%

    renewable energy power sector; and

    Advanced Sustainable Energy Sector (ASES) scenario, which assumes a more rapid

    advancement and deployment of new and renewable technologies as compared to the

    SES.

    The scenarios were based on public data, independent assessments of resource potentials,

    information obtained from published reports and power system modelling of the GMS region

    for the period 2015 to 2050. All projections presented in this report commence in the year

    2015.

    1.1 Report Structure

    This report has been organised in the following way:

    Section 2 sets out recent outcomes for Lao PDR’s electricity industry;

    Section 3 summarises the main development options covering both renewable energy

    and fossil fuels;

    Section 4 provides a brief summary of the scenarios that were modelled and a summary

    of the assumptions in common;

    Section 5 sets out the key results for the business as usual scenario;

    1 Proposed but not committed fossil fuel based projects are not developed. Committed and existing fossil fuel based projects are retired at the end of their lifetime and not replaced with other fossil fuel projects. A least cost combination of renewable energy generation is developed to meet demand.

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    Intelligent Energy Systems IESREF: 5973 8

    Section 6 sets out the key results for the sustainable energy sector scenario;

    Section 7 sets out the key results for an advanced sustainable energy sector scenario;

    Section 8 provides comparative analysis of the three scenarios based on the

    computation of a number of simple metrics that facilitate comparison;

    Section 9 provides analysis of the economic implications of the scenarios; and

    Section 10 provides the main conclusions from the modelling.

    The following appendices provide some additional information for the scenarios:

    Appendix A contains the technology cost assumptions that were used;

    Appendix B provides the fuel price projections that were used; and

    Appendix C sets out information used to estimate jobs creation potential for each

    scenario.

    Note that unless otherwise noted, all currency in the report is Real 2014 United States Dollars

    (USD).

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    Intelligent Energy Systems IESREF: 5973 9

    2 Background: Lao PDR Electricity Sector

    2.1 Industry Structure

    The governance structure of Lao PDR’s electricity industry is illustrated in Figure 1.

    Figure 1 Lao PDR Electricity Industry Governance Structure2

    Source: Power to the People: Twenty Years of National Electrification, World Bank, 2012

    The Ministry of Energy and Mines (MEM) under the Prime Ministry’s Office is the central

    agency in charge of the energy sector and of renewable energy, and has the leading role in

    preparing the country's renewable energy strategy. The MEM manages the electricity sector

    through the Department of Electricity. A more specific statement of the policy objectives is:

    Expand and improve the main grid supplies;

    Expand and improve rural electrification;

    Increase energy self-sufficiency and security;

    Implement power projects that maximise long-term sustainability;

    Develop power trade with GMS countries;

    Develop IPP project selection and implementation procedures;

    2 The Department of Energy Business, not shown in the chart, sits under the MEM and was established to share information on the Lao Government’s hydro power development plan and took over the role of Department of Energy promotional development since 2006. The Institute of Renewable Energy Promotion under MEM oversees the implementation of renewable energy, energy efficiency and rural electrification programs in Lao PDR.

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    Intelligent Energy Systems IESREF: 5973 10

    Maximise the benefits to Lao PDR from IPP developments; and

    Develop transmission infrastructure for regional power trade.

    Electricité du Laos (EDL) is wholly-owned by the government and owns and operates

    vertically integrated generation, transmission and distribution assets in Lao PDR. EDL is

    responsible for developing generation, transmission and distribution projects to meet policy

    directives. As such they also perform system planning and manage electricity imports to and

    electricity exports from the Lao PDR grid.

    2.2 Power System

    A representation of Lao PDR’s generation and transmission systems is shown in Figure 2. The

    diagram highlights the present statehood of the country's national system in terms of the

    main hydropower generation resources and 115 kV transmission lines that are used in the

    power system and their locations within the country. We have also indicated the installed

    capacity of each generator and highlighted whether the electricity is delivered for meeting

    domestic demand or for exporting.

    EDL operates the transmission and distribution network in the three regions of central,

    northern and southern Lao PDR covering the 17 provinces. The Central 1 and Central 2

    regions were integrated into a single region in 2011, however the three regions (115 kV

    systems) remain isolated from each other. In addition to the main grid operated by EDL,

    provincial authorities operate some 85 mini grids that are supplied by diesel generators or

    small-scale hydro power stations in remote areas. These facilities primarily serve remote

    areas that are not yet part of the national grid.

    There is a significant amount of power exchange between Lao PDR and neighbouring

    countries. Power is imported at a number of border points to meet local demand and

    exported from dedicated hydro plants at other points. The largest exporter to Lao PDR is

    neighbouring Thailand; however, some provinces receive power from Vietnam. On the other

    hand, there are generation plans that largely export their electricity to Thailand, Viet Nam,

    People’s Republic of China (PRC) and Cambodia. EDL effectively acts as a single buyer and

    negotiates the terms and conditions for power imports and exports. To provide an indication

    of the location of current installed capacity of hydro plants and whether the hydros are

    geared towards serving Lao PDR’s national electricity system or for export, Figure 3 shows

    installed capacity statistics by region and by type (whether export-oriented hydro or not).

    Pertinent features of the Lao PDR power system as at 2013 are summarised below:

    State-owned generation and network managed by a central electricity authority (EDL);

    Generation capacity mostly owned by independent power producers (IPPs);

    Total energy final demand of 3,381 GWh;

    Low per capita consumption of 500 kWh per year;

    High transmission and distribution losses;

    Network connections with Thailand, China and Vietnam;

    Imports of around one-third of its total electricity requirements and exported 690

    GWh; and

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    Intelligent Energy Systems IESREF: 5973 11

    Household electrification ratio was 87%.

    Figure 2 Map of Lao PDR Generators Map (2014)

    Source: EDL

    Nam Nhon

    Nam Dong

    Nam Ngay

    Nam Ngum 5

    Nam Long

    Nam Ko

    Nam Tha 3

    Tad Salen

    Nam Lik Nam Ngum 2

    Nam Phao

    Selabam

    Nam Ngum 1

    Theun HinbounNam Mang 3

    Nam Theun 2

    Nam Song

    Xe Kaman 3Xe Set 1

    Xe Set 2

    Houay Ho

    Nam Leuk

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    Intelligent Energy Systems IESREF: 5973 12

    Figure 3 Installed Hydro Capacity by Region and Type

    2.3 Installed Capacity

    All of the generation projects in Lao PDR were traditionally based on hydro power although

    this has recently changed with the commissioning of the first 626 MW unit of the Hong Sa

    Lignite Power Project in Xayaboury province early 2015.

    As of 2014, 3,058 MW has been developed with most of this exported into Thailand and to a

    smaller extent Vietnam. The levels of export into Thailand and Vietnam is set to increase with

    the Government of Lao PDR signing MOUs that commit to the export of up to 7,000 MW to

    Thailand and 5,000 MW to Vietnam by 20203. By March 2016 the coal-fired Hong Sa Lignite

    Power Project will have a total of capacity of 1,878 MW, with some 1,473 MW having already

    been sold to the Electricity Generation Authority of Thailand (EGAT). At present, there are

    more than 50 hydropower sites planned to achieve the 2020 export target. The Lao PDR

    Government and foreign investors jointly develop most of these exporting projects.

    The current generation fleet in Lao PDR is shown in Table 1 and comprises of 610 MW owned

    by EDL and 3,211 MW owned by independent power producers.

    3 Lao PDR Country Report, Department of Energy Policy and Planning Ministry of Energy and Mines, 2013

    13

    228

    - 8 -

    870

    1,588

    523

    -

    200

    400

    600

    800

    1,000

    1,200

    1,400

    1,600

    Northern Central 1 Central 2 Souith

    MW

    Lao Hydro Export Hydro

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    Intelligent Energy Systems IESREF: 5973 13

    Table 1 Existing Large-scale Generators in Lao PDR

    Generator Type Owner Capacity (MW)

    Nam Ngum Hydro EDL 155

    Nam Dong Hydro EDL 1

    Xelabam Hydro EDL 5

    Xeset 1 Hydro EDL 45

    Nam Leuk Hydro EDL 60

    Nam Ngay Hydro EDL 1.2

    Nam Mang 3 Hydro EDL 35

    Nam Ko Hydro EDL 1.5

    Xeset2 Hydro EDL 76

    Nam 1-2 Hydro EDL 100

    Nam Ngum 5 Hydro EDL 120

    Nam Nhone Hydro EDL 3

    Tatsalen Hydro EDL 3

    Nam Long Hydro EDL 5

    Houay Ho Hydro IPP 150

    Theun Hinboun Hydro IPP 490

    Nam Theun 2 Hydro IPP 1,080

    Nam Ngum 2 Hydro IPP 615

    Xekaman 3 Hydro IPP 250

    Hong Sa Lignite #1 Lignite IPP 626

    Source: Various – as Compiled by Consultant

    2.4 Electricity Demand

    Figure 4 shows Lao PDR’s total final electricity consumption and the annual growth rates from

    1996 to 2013. It indicates domestic demand has been growing rapidly; in particular, annual

    electricity consumption increased at an average rate of 14.5% per annum over 10 years from

    903 GWh in 2004 to 3,381 GWh in 2013. Electricity consumption has been traditionally

    dominated by residential consumption, which made up 42% in 2010 dropping to 38% in 2013

    (Figure 5). Industry consumption as at 2013 accounted for 33% of total electricity

    consumption. This trend is expected to continue with additional industrial load to come

    online over the next few years as part of the Government’s industrial development plans.

    By 2013, the power system had a peak demand of 649 MW, which has been growing 12.5%

    per annum over a 10 year period, and nearly doubled since 2008. Figure 6 indicates the

    locations of main load centres, which include Vientiane capital city, Vientiane province,

    Savannakhet, Khammouane and Champasak provinces.

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    Intelligent Energy Systems IESREF: 5973 14

    Figure 4 Electricity Demand Growth (1996-2013)

    Source: Electricity Statistics 2013, Electricite Du Laos, 2014

    Figure 5 Electricity Demand Shares by Category (2013)

    0%

    5%

    10%

    15%

    20%

    25%

    -

    500

    1,000

    1,500

    2,000

    2,500

    3,000

    3,500

    4,000

    An

    nu

    al A

    vera

    ge G

    row

    th (

    %)

    Dem

    and

    (G

    Wh

    )

    Total Electricity Consumption Annual Average Growth Rate

    Residential37.8%

    Commercial21.7%

    Entertainment0.3%

    Gov. office5.6%

    Irrigation1.0%

    Int. Orgs0.3% Industry

    33.1%

    Edu. & Sport0.2%

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    Intelligent Energy Systems IESREF: 5973 15

    Figure 6 Main Load Centres (2013)

    2.5 Generation Supply

    Figure 7 shows annual statistics generation, import and export of electricity from 1991 to

    2012. It indicates that while it had significantly increased its own generation supply (which

    was entirely from hydropower), Lao PDR also had to import more electricity to meet the

    domestic demand.

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    Intelligent Energy Systems IESREF: 5973 16

    Figure 7 Generation, Imports and Exports (1991-2012)

    2.6 Exports and Imports

    With many hydropower projects having been proposed, Lao PDR is expected to increase

    electricity exports to neighbouring Thailand, and Vietnam to a lesser extent. The export of

    energy via wider electricity trading arrangements in the surrounding regions is viewed by the

    government as an opportunity to improve EDL’s financial position, foster economic growth

    and over the longer-term reduce poverty.

    The Lao PDR has various cross-border connections with other GMS neighbouring countries.

    The numbers of agreed MOU interconnections and capacities between Lao PDR and each

    country as at 2014 are4:

    Thailand: 23 interconnections, 10,000 MW;

    Vietnam: 7 interconnections, 5,000 MW; and

    Lao PDR: 2 interconnections, 2,000 MW.

    Dedicated transmission lines link each of the export IPP power plants into the respective off-

    take countries. Links as at 2014 are:

    Theun Hinboun to Sakhonnakhon (Electricity Generating Authority of Thailand - EGAT)

    230 kV, 176 km, 440 MW (includes power station expansion);

    Houay Ho to Ubon 2 (EGAT) 230 kV, 230 km, 150 MW;

    4 IFC Workshop on Sustainable Hydropower & Regional Cooperation, Viravong, 2015

    -

    200

    400

    600

    800

    1,000

    1,200

    1,400

    1,600

    1,800

    2,000

    2,200

    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

    GW

    h

    Generation Imports Exports

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    Intelligent Energy Systems IESREF: 5973 17

    Nam Theun 2 to Roi Et (EGAT) 500 kV, 300 km, 1,000 MW;

    Na Bong to Udon 3 (EGAT), 500 kV, 100 km, 615 MW; and

    Xekaman 3 to Thanh My (Electricity of Vietnam - EVN) 230 kV, 150 km, 250 MW.

    Lao PDR exports a large amount of hydropower to Thailand, but in exchange imports

    electricity to supply provinces that are not connected to the national power grid. These

    demand points include copper and gold mining operations, which consume significant

    amounts of power.

    Lao PDR also has 4 interconnections with China, with capacity of 2,000 MW to ensure

    adequate power supplies in Luang Prabang and the Northern provinces. The interconnection

    allows for power imports from China due to lower river levels up north and would indirectly

    relieve pressure on the central Lao PDR hydro plants.5

    The shares of neighbouring countries in Lao PDR exports and imports of electricity for 2013

    are presented in Figure 8 and Figure 9. The approximate geographical representation of

    power exchanges is shown in Figure 10.

    Figure 8 Export and Import Shares by Country (2013)

    Figure 9 Historical Annual Exports (2010-13)

    5 http://www.vientianetimes.org.la/FreeContent/FreeConten_Laos%20imports.htm, accessed 20 May 2015

    Exports to Thailand

    71%

    Exports to Cambodia

    29%

    Thailand (EGAT)

    73%

    Thailand (PEA)

    7%

    Vietnam2%

    China18%

    -

    200

    400

    600

    800

    2010 2011 2012 2013

    GW

    h

    Exports to Thailand Exports to Cambodia

    Imports Exports

    http://www.vientianetimes.org.la/FreeContent/FreeConten_Laos%20imports.htm

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    Intelligent Energy Systems IESREF: 5973 18

    Figure 10 Illustrative Flows of Cross Border Exports (2013)

    Source: EDL

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    Intelligent Energy Systems IESREF: 5973 19

    Figure 11 Illustrative Flows of Cross Border Imports (2013)

    Source: EDL

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    Intelligent Energy Systems IESREF: 5973 20

    3 Development Options for Lao PDR Electricity Sector

    3.1 Natural Gas Resources

    Lao PDR has no confirmed reserves of oil or gas, however, the Government has issued two

    exploration concessions in central and southern Lao (Salamander Energy Group and Petro

    Vietnam respectively)6. Significant work remains to be done to determine the results.

    Based on this the likelihood of indigenous oil or gas reserves making an impact to the

    electricity sector development in the next 10-20 years is low.

    Consequently, Lao PDR imports petroleum products from other countries, with these

    products being used approximately as follows:

    88% used in transport sector;

    11% used in the commercial sector; and

    The remainder for residential, industry and agriculture.

    3.2 Coal Resources

    Lao PDR has coal reserves estimated at approximately 900 million tons7, comprising mostly

    of lignite, and anthracite to a much smaller extent at various sites. Figure 12 shows the

    location of coal deposits and occurrences in Lao PDR. Main lignite basins lie in Hong Sa,

    Viengphoukha and Khangphaniang. Located in the northwestern region, Hong Sa is the

    largest known reserve of lignite, with 400-700 million tons being reserved for power

    generation. The country’s first coal-fired power plant - 1,878 MW Hong Sa Lignite Power

    Project - would be completed by 2016 with 1,473 MW already sold to EGAT.

    Anthracite (and bituminous) can be found at various sites, including Saravan and PHong

    Saly provinces, with the total proven resource at approximately 100 million tons. Currently

    130,000 tons of production is used for local factories and export purposes and the

    government has a plan to support a 500 MW coal unit depending on further exploration

    success.

    6 Energy Sector Development in Lao PDR, Vongsay, 2013

    7 Energy Sector Development in Lao PDR, Vongsay, 2013

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    Intelligent Energy Systems IESREF: 5973 21

    Figure 12 Location of Coal Deposits and Occurrences

    3.3 Hydro Power

    Hydropower is the most abundant energy resource in Lao PDR. There is an estimated

    potential of 23,000 MW along the Mekong River and its sub-basins. By 2014, around 3,200

    MW has been developed and is supplying domestic demand and neighbouring countries.

    Table 2 below shows the hydro expansion plan to 2020. There is currently 6,000 MW of

    committed projects in the pipeline with 75% of it planned for export. For implementation of

    this plan, the Lao Government has opened up development opportunities to the

    neighbouring governments (Thailand, Lao PDR, and Vietnam) and foreign companies.

    The country’s small hydropower potential is also substantial, estimated to be around 2,000

    MW. The development of small hydropower (capacity up to 15 MW) could also play an

    important role in meeting the country’s objectives of increasing rural electrification coverage

    from the current level of 70% to 90% in 20208. There are 75 smaller hydro projects as at the

    8 Note that we refer to rural coverage in these statistics, the earlier stated “87%” relates to rural and urban.

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    Intelligent Energy Systems IESREF: 5973 22

    end of 2013 at various stages. There are also approximately 60,000 micro units installed in

    Lao PDR servicing 90,000 households.

    Figure 13 summarises the information about capacity of the existing, committed and

    considered projects in Lao PDR.

    Table 2 Hydroelectric Power Development Plan (2016-20)

    Region No. Projects Capacity (MW) Production (GWh/yr)

    Northern 31 1,623 7,783

    Central 19 323 1,524

    Southern 27 905 4,729

    Total 77 2,851 14,036

    Source: Electricite du Lao, 2011

    Figure 13 Lao PDR Hydro Projects: Existing, Committed and Considered (2014)

    Source: Compiled by Consultant

    3.4 Wind Power

    Lao PDR has a wind potential estimated at approximately 26,000 square kilometres with

    wind speeds between 7-9 m/s. Table 3 shows the wind resource available in Lao PDR and

    some of the other GMS countries. The resource mapping shows approximately 2,800 MW

    2,426

    1,635

    3,632

    1,288

    2611.8

    611

    2,335

    250

    - 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000

    Other Considered (Potential Thailand Export)

    Other Considered (Potential Vietnam Export)

    Considered on Mekong (Potential Thailand Export)

    Considered on Mekong (Potential Vietnam Export)

    Committed (2020)

    Existing (Lao PDR)

    Existing (Export - Thailand)

    Existing (Export - Vietnam)

    MW

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    Intelligent Energy Systems IESREF: 5973 23

    at ‘very good’ and ‘excellent’ wind speeds and 24,280 MW at locations with ‘good’ wind

    speeds.

    Table 3 Wind Resource Potential in Lao PDR9

    Poor Fair Good Very Good Excellent

    Parameter Unit < 6 m/s [6, 7) m/s [7, 8) m/s [8, 9) m/s >= 9 m/s

    Land Area km^2 184,511 38,787 6,070 671 35

    % total % 80.2% 16.9% 2.6% 0.3% 0.0%

    Potential MW na 155,148 24,280 2,684 140

    Source: Wind Energy Resource Atlas of Southeast Asia, TrueWind Solutions, 2001

    Lao PDR wind power potential has also been estimated in a recent ADB study entitled

    “Renewable Energy Developments and Potential in the Greater Mekong Subregion” (2015).

    According to this study, Lao PDR has a theoretical wind energy potential of 455 GW and a

    potential production capacity of about 1,112 TWh/yr. To obtain these estimates, the land

    area suitable for wind power result was multiplied by the average amount of wind power

    capacity that can be installed in a given area (assumed to be 10 MW/km2). However, the

    technical wind energy potential would be much less due to the limitations of the overall

    power generation and transmission grid systems.

    An illustration of the dispersion of wind potential is charted in Figure 14. This shows 3TIER’s

    Global Wind Dataset10 , which provides average annual wind speed at 80 meters above

    ground level. This illustrates regions of high potential along the border with Vietnam and in

    the south of the country, as well as pockets of 6 to 7 m/s potential in the north. Figure 15

    shows the DTU Global Wind Atlas11 onshore and 30 km offshore wind climate dataset which

    accounts for high resolution terrain effects for 100 m above ground level. According to the

    IRENA global atlas description: “this was produced using microscale modelling in the Wind

    Atlas Analysis and Application Program and capture small scale spatial variability of winds

    speeds due to high resolution orography (terrain elevation), surface roughness and surface

    roughness change effects. The layers shared through the IRENA Global Atlas are served at

    1km spatial resolution.”

    The Government is planning to develop 50 MW of wind power by 2025 to promote the

    development of wind energy in the country.

    9 For large wind turbines only. Potential MW assumes an average wind turbine density of 4 MW per square kilometre and no exclusions for parks, urban, or inaccessible areas. Wind speeds are for 65 m height in the predominant land cover with no obstructions.

    10 Source: 3TIER data set was accessed via the IRENA Global Atlas Server: http://irena.masdar.ac.ae/.

    11 See: http://globalwindatlas.com/.

    http://irena.masdar.ac.ae/http://globalwindatlas.com/

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    Figure 14 3TIER’s Global Wind Dataset 5km onshore wind speed at 80m height12

    Source: 3TIER’s Global Wind Dataset (accessed via IRENA Global Atlas)

    12 Average for period from 1980 to 2011.

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    Figure 15 Average Wind Speed 1km at 100 m AGL DTU (2015)

    Source: IRENA Global Atlas and Global Wind Atlas (2015)

    3.5 Solar Power

    Solar energy is an abundant energy resource in Lao PDR. The southern part of the country

    experiences slightly higher irradiation levels and would be suitable for the deployment of

    solar technologies (see Figure 16).

    Lao PDR solar power potential has also been estimated in a recent ADB study entitled

    “Renewable Energy Developments and Potential in the Greater Mekong Subregion” (2015).

    According to this study, Lao PDR has a potential of 8,812 MW of combined peak solar

    capacity, which far exceeds the earlier estimates 13 . The details of estimates of solar

    potential are in Table 4. Lao PDR has GHI levels ranging between 1,200 and 1,800 kWh/m2

    13 Based on analysis of high resolution measurements and comparisons of Lao PDR solar maps to other countries, IES views solar potential in Lao PDR to be at least 11,000 MW.

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    pa and average DNI levels around 1,350 kWh/m2 per annum14, however, the hotter regions

    in Lao PDR have DNI levels between 1,600 to 1,800 kWh/m2 pa which can accommodate

    CSP technology.

    Figure 16 Lao PDR DNI Solar Resource Map (kWh/m^2 per day)

    Source: Solar and Wind Energy Resource Assessment, accessed 15 April 2015

    14 Source: ADB, “Renewable Energy Developments and Potential in the Greater Mekong Subregion”, 2015.

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    Table 4 Lao PDR Solar Power Technical Potential

    Solar Irradiation

    Level, kWh/m2

    Suitable Land Areas,

    thousand km2

    Technical Capacity

    Potential, MW

    Technical Production

    Potential, MWh/yr

    Less than 1,200 - - -

    1,200–1,300 0.09 5 5,613

    1,300–1,400 1.88 113 125,148

    1,400–1,500 12.84 770 918,500

    1,500–1,600 41.02 2,461 3,137,931

    1,600–1,700 69.14 4,149 5,630,307

    1,700–1,800 21.89 1,313 1,890,265

    Over 1,800 - - -

    Total 146.9 8,812 11,707,764

    Source: Renewable Energy Developments and Potential in the Greater Mekong Subregion, ADB, 2015

    Figure 17 plots the monthly average irradiation levels for a number of selected sights with

    the highest annual average irradiation levels based on SWERA data. This shows the monthly

    variation throughout the year for solar irradiation and hence generation. This highlights

    November through to March exhibit excellent solar conditions. The map shading the

    locations of solar for Lao PDR is provided in Figure 18. This also highlights that the greatest

    potential for solar lies in the central region of the country, covering the main load centre of

    Vientiane.

    Figure 17 Monthly DNI Levels for Selected Locations in Lao PDR

    Source: NASA Atmosphere Science Data Centre, obtained via the SWERA Geospatial Toolkit

    0

    1

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    Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

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    Figure 18 Main Locations with DNI Solar Power Potential in Lao PDR

    Source: Developed by Consultant based on Information from EDL and SWERA

    Figure 19 plots measurements of Global Horizontal Irradiance (GHI) based on the 3TIER high

    resolution dataset accessed via the IRENA Global Atlas. This map shows that the GHI

    potential is significant throughout the entire country.

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    Figure 19 3TIER’s Global Solar Dataset (3km in W/m^2) for GHI

    Source: 3TIER’s Global Solar Dataset (accessed via IRENA Global Atlas)

    3.6 Geothermal Energy

    According to a recent study15, 11 geothermal resources have been identified in a study in the

    country’s northern mountainous areas. These sources are believed to be of the low

    temperature type and unlikely to support power projects on a large scale. The Asian

    Development Bank (ADB) has however reported that some 59 MW of geothermal generation

    capacity could be developed in Lao PDR.

    3.7 Biomass and Biogas

    Lao PDR has vast forest coverage around 100,000 square kilometres or about 45% of its

    land. In addition, a large amount of agricultural residues representing significant energy

    potential can be harvested. The total electricity potential from biomass is estimated at 938

    MW16. Table 5 shows the biomass source and energy potential. IES projected estimates

    15 Nguyen Tien Hung et al, “Overview of geothermal resources in North Part of Laos”, Proceedings World Geothermal Congress 2015, Melbourne, Australia

    16 Renewable Energy Development Strategy in Lao PDR, 2011

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    based on the ADB study “Renewable Energy Developments and Potential in the Greater

    Mekong Subregion” suggest an energy potential of around 17,000 GWh/yr or up to 2,300

    MW.

    Table 5 Energy Potential from Agriculture and Forestry Residues

    Biomass sources Type of fuel Equivalent energy (GWh/yr)

    Rice husk Combustive 2,108

    Rice straw Biogas 1,030

    Husbandry Biogas 3,269

    Forest residues Combustive 12,500

    Total Various 18,907

    Source: Rural Electrification in Lao PDR and Lao PDR, Innovation Energie Developpement, 2007

    Biogas energy technical potential from livestock manure has been estimated at around

    8,540 MWh per day according to ADB 2015 study. Details are in Table 6 below.

    Table 6 Lao PDR Biogas Technical Potential

    Livestock Net Dry Matter

    Available

    (kg/day)

    Mean Biogas Yield Factor

    (m3/kg)

    Daily Biogas

    Production

    (m3/day)

    Energy Content

    per Day

    (kWh/day)

    Buffalo 1,094.337 0.25 273,584 1,641,505

    Cows 1,359,147 0.25 339.787 2,038,721

    Pigs 192.835 4.20 809,908 4,859,448

    Total 2,646,319 1,423,279 8,539,674

    Source: Renewable Energy Developments and Potential in the Greater Mekong Subregion, ADB, 2015

    Figure 20 shows the existing biomass capacity installed and 2025 targets. There are

    currently two large-scale biomass projects operating in the central and south region. The

    Hoang Anh Sugar Mill has a capacity of 30 MW in the Attapeau province and the Mit Lao

    Sugar Mill is located in the Savannakhet province with a capacity of 9.7 MW.

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    Figure 20 Current Biomass and Biogas Developments and Targets (MW)

    Source: Country Presentation on Status of Bioenergy Development in Lao PDR, IEA, IRENA, FAO, 2014

    3.8 Renewable Energy Potential and Seasonal Diversification

    In summary, the renewable energy potential for Lao PDR is provided in Table 7. The

    numbers presented here have been drawn from multiple sources and informed by analysis

    of the IRENA Global Atlas data. Figure 21 plots the monthly capacity factors for solar, wind

    and hydro against the normalised average monthly demand. The chart shows that there is

    some natural seasonal / monthly diversification between resources: demand in Lao PDR is

    highest peaking between March to May which coincides with reduction in wind speeds in

    Lao PDR. There is a clear diversification benefit as the solar intensity drops towards the

    middle of the year and wind speeds and hydro inflows start to increase.

    It should be noted that the key issue in the charts is correlation but not amplitude, and

    furthermore, that the hydro inflows fall into reservoirs, some with significant amount of

    storage, which enables smoothing out generation throughout the year (within the limits of

    the storage capacity of the reservoirs), thus there is some scope for the role / operation of

    hydro power stations to change in Lao PDR to accommodate high levels of renewable energy.

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    Table 7 Summary of Estimated Renewable Energy Potential (Compiled from

    Various Sources and Analysis)

    Resource Potential (MW)

    Source and comments

    Hydro (Large) 23,000 Lao hydropower potential and policy in the GMS context (EDL)

    Hydro (Small) 2,000 Sites smaller than 15 MW. The Need for Sustainable Renewable Energy in Lao PDR (Vongchanh)

    Pump Storage - Given the abundance of conventional hydro potential there has been little focus in Lao PDR to assess the potential of this technology.

    Solar At least 11,000

    IES assessment based on various sources set out in 3.5.

    Wind Onshore 27,104 Resource above 7m/s. Wind Energy Resource Atlas of Southeast Asia (TrueWind Solutions, 2001)

    Wind Offshore 0 Not applicable

    Biomass 1,271 IES projections based on data from Renewable Energy Developments and Potential in the Greater Mekong Subregion (ADB, 2015)

    Biogas 1,146 IES projections based on data from Renewable Energy Developments and Potential in the Greater Mekong Subregion (ADB, 2015)

    Geothermal 59 Lao PDR Energy Sector Assessment, Strategy, and Road Map (ADB, 2013)

    Ocean - Not applicable

    Figure 21 Seasonality in Renewable Resource Profiles and National Demand

    Source: Consultant analysis

    0%

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    20%

    30%

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    70%

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    Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

    Hydro Wind Solar Demand

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    4 Lao PDR Development Scenarios

    In this section, we define the three scenarios for Lao PDR’s electricity sector that we have

    modelled: the Business as Usual (BAU), Sustainable Energy Sector (SES), and Advanced SES

    (ASES) scenarios. We also set out the assumptions made for technology costs (section 4.2)

    and fuel prices (section 4.3) before providing the details for a number of Lao PDR specific

    assumptions – in particular: our assumed economic outlook for Lao PDR, a list of generation

    projects that we consider committed 17 and comments on the status of power import

    projects. Further assumptions for each scenario are provided in Section 5, Section 6 and

    Section 7.

    4.1 Scenarios

    The three development scenarios (BAU, SES and ASES) for Lao PDR are conceptually

    illustrated in Figure 22.

    Figure 22 GMS Power Sector Scenarios

    The BAU scenario is characterised by electricity industry developments consistent with the

    current state of planning within the GMS countries and reflective of growth rates in electricity

    demand consistent with an IES view of base development, existing renewable energy targets,

    where relevant, aspirational targets for electrification rates, and energy efficiency gains that

    are largely consistent with the policies seen in the region.

    17 That is, construction is already in progress, the project is near to commissioning or it is in an irreversible / advanced state of the planning process.

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    In contrast, the SES seeks to transition electricity demand towards the best practice

    benchmarks of other developed countries in terms of energy efficiency, maximise the

    renewable energy development, cease the development of fossil fuel resources, and make

    sustainable and prudent use of undeveloped conventional hydro resources. Where relevant,

    it leverages advances in off-grid technologies to provide access to electricity to remote

    communities. The SES takes advantage of existing, technically proven and commercially

    viable renewable energy technologies.

    Finally the ASES assumes that the power sector is able to more rapidly transition towards a

    100% renewable energy technology mix under an assumption that renewable energy is

    deployed more than in the SES scenario with renewable energy technology costs declining

    more rapidly compared to BAU and SES scenarios. A summary of the main features of the

    three scenarios are summarised in Table 818.

    Table 8 Key Features of BAU, SES and ASES

    Scenario Demand Supply

    BAU Demand was forecast to grow in line

    with historical electricity consumption

    trends and projected GDP growth rates

    using techniques that are largely the

    same as what is typically done in

    government plans. Electric vehicle

    uptake was assumed to reach 10%

    across all cars and motorcycles by 2050.

    Generator new entry follows that of power

    development plans for the country

    including limited levels of renewable

    energy but not a maximal deployment of

    renewable entry.

    SES Assumed a transition towards

    energy efficiency benchmark for the

    industrial sector of Hong Kong19 and

    of Singapore for the commercial

    sector by year 2050.

    For the residential sector, it was

    assumed that urban residential

    demand per electrified capita grows

    to 800 kWh pa by 2050, 40% less

    than in the BAU.

    Demand-response measures were

    assumed to be phased in from 2021

    with some 15% of demand being

    flexible20 by 2050.

    Assumed no further coal and gas new

    entry beyond what is already

    understood to be committed.

    A modest amount of large scale hydro

    (between 4,000 to 5,000 MW) was

    deployed in Lao PDR and Myanmar

    above and beyond what is understood

    to be committed hydro developments

    in these countries21.

    Supply was developed based on a least

    cost combination of renewable

    generation sources limited by

    estimates of potential rates of

    deployment and judgments in on

    18 Note that we summarise the key drivers here. For further details, please refer to the separate IES assumptions document.

    19 Based on our analysis of comparators in Asia, Hong Kong had the lowest energy to GDP intensity for industrial sector while Singapore had the lowest for the commercial sector.

    20 Flexible demand is demand that can be rescheduled at short notice and would be implemented by a varie ty of smart grid and demand response technologies.

    21 This is important to all countries because the GMS is modelled as an interconnected region.

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    Slower electrification rates for the

    national grids in Cambodia and

    Myanmar compared to the BAU, but

    deployment of off-grid solutions

    that achieve similar levels of

    electricity access.

    Mini-grids (off-grid networks) were

    assumed to connect to the national

    system in the longer-term for

    reliability / mutual support reasons.

    Electric vehicle uptake was as per

    the BAU.

    when technologies would be feasible

    for implementation to deliver a power

    system with the same level of

    reliability as the BAU.

    Technologies used include: solar

    photovoltaics, biomass, biogas and

    municipal waste plants, CSP with

    storage, onshore and offshore wind,

    utility scale batteries, geothermal and

    ocean energy.

    Transmission limits between regions

    were upgraded as required to support

    power sector development in the GMS

    as an integrated whole, and the

    transmission plan allowed to be

    different compared to the

    transmission plan of the BAU.

    ASES The ASES demand assumptions were

    essentially done as a sensitivity to the

    SES:

    An additional 10% energy efficiency

    was applied to the SES demands

    (excluding transport).

    Flexible demand was assumed to

    reach 25% by 2050.

    Uptake of electric vehicles doubled by

    2050.

    ASES supply assumptions were also

    implemented as a sensitivity to the SES,

    with the following the main differences:

    Allow rates of renewable energy

    deployment to be more rapid compared

    to the BAU and SES.

    Technology cost reductions were

    accelerated for renewable energy

    technologies.

    Implement a more rapid programme of

    retirements for fossil fuel based power

    stations.

    Energy policy targets of 70% renewable

    generation by 2030, 90% by 2040 and

    100% by 2050 across the region are in

    place.

    Assume that technical / operational

    issues with power system operation and

    control for a very high level of

    renewable energy are addressed22.

    22 In particular: (1) sufficient real-time monitoring for both supply and demand side of the industry, (2) appropriate forecasting for solar and wind and centralised real-time control systems in place to manage a more distributed supply side, storages and flexible demand resources, and (3) power systems designed to be able to manage voltage, frequency and stability issues that may arise from having a power system that is dominated by asynchronous technologies.

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    4.2 Technology Cost Assumptions

    Technology capital cost estimates from a variety of sources were collected and normalised

    to be on a consistent and uniform basis23. Mid-points were taken for each technology that is

    relevant to the GMS region. The data points collated reflect overnight, turnkey engineering

    procurement construction capital costs and are exclusive of fixed operating and maintenance

    costs, variable operating and maintenance costs and fuel costs. The capital costs by

    technology assumed in the study are presented in Figure 23 for the BAU and SES scenarios.

    For the ASES scenario, we assumed that the technology costs of renewable technologies

    decline more rapidly. These technology cost assumptions are listed in Figure 24. Note that

    the technology capital costs have not included land costs, transmission equipment costs, nor

    decommissioning costs and are quoted on a Real USD 2014 basis.

    Comments on the various technologies are discussed below in relation to the BAU and SES

    technology costs:

    Conventional thermal technology costs are assumed to decrease at a rate of 0.05% pa

    citing maturation of the technologies with no significant scope for cost improvement.

    Onshore wind costs were based on the current installed prices seen in China and India

    with future costs decreasing at a rate of 0.6% pa. Future offshore wind costs were

    developed by applying the current percentage difference between current onshore and

    offshore capital costs for all future years.

    Large and small-scale hydro costs are assumed to increase over time reflecting easy

    and more cost-efficient hydro opportunities being developed in the first instance.

    IRENA reported no cost improvements for hydro over the period from 2010 to 2014.

    Adjustments are made in the case of Lao PDR and Myanmar where significant hydro

    resources are developed in the BAU case24.

    Solar PV costs are based on the more mature crystalline silicon technology which

    accounts for up to 90% of solar PV installations (IRENA, 2015), and forecast to continue

    to drop (2.3% pa) albeit at a slower pace than in previous years.

    Utility scale battery costs are quoted on a $/kWh basis, and cost projections based on

    a report by Deutsche Bank (2015) which took into account several forecasts from BNEF,

    EIA and Navigant.

    Solar thermal (CSP) capital costs are projected to fall at 2.8% pa on the basis of the

    IRENA 2015 CSP LCOE projections. While globally there are many CSP installations in

    place, the technology has not taken off and the cost of CSP technology over the past 5

    years has not been observed to have fallen as rapidly as solar PV.

    Biomass capital costs are based on costs observed in the Asia region which are

    significantly less than those observed in OECD countries. Capital costs were assumed

    to fall at 0.1% pa. Biogas capital costs were based on anaerobic digestion and assumed

    to decline at the same rate as biomass.

    23 We standardised on Real 2014 USD with all technologies costs normalised to reflect turnkey capital cost s.

    24 Capital costs for large scale hydro projects are assumed to increase to $3,000/kW by 2050 consistent with having the most economically feasible hydro resources developed ahead of less economically feasible resources.

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    Ocean energy (wave and tidal) technologies were based on learning rates in the ‘Ocean

    Energy: Cost of Energy and Cost Reduction Opportunities’ (SI Ocean, 2013) report

    assuming global installation capacities increase to 20 GW by 205025.

    Capital costs were discounted at 8% pa across all technologies over the project

    lifetimes. Decommissioning costs were not factored into the study.

    For technologies that run on imported coal and natural gas, we have factored in the

    additional capital cost of developing import / fuel management infrastructure in the

    modelling.

    For reference, Appendix A tabulates the technology cost assumptions that we have used in

    the modelling.

    Figure 23 Projected Capital Costs by Technology for BAU and SES

    * Battery costs are quoted on a Real 2014 USD $/kWh basis.

    25 Wave and tidal costs were averaged.

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    Figure 24 Projected Capital Costs by Technology for ASES

    * Battery costs are quoted on a Real 2014 USD $/kWh basis.

    4.3 Fuel Pricing Outlook

    IES has developed a global fuel price outlook which are based on short-term contracts traded

    on global commodity exchanges before reverting towards long-term price global fuel price

    forecasts based on the IEA’s World Energy Outlook (WEO) 2015 450 scenario26 and a set of

    relationships between different fuels that have been inferred from historical relations

    between different types of fuels. A summary of the fuel prices expressed on an energy-

    equivalent basis ($US/MMBtu HHV) is presented in Figure 25.

    The 30% fall from 2014 to 2015 for the various fuels was the result of a continued weakening

    of global energy demand combined with increased stockpiling of reserves. Brent crude prices

    fell from $155/bbl in mid-2014 to $50/bbl in early 2015. OPEC at the November 2014 meeting

    did not reduce production causing oil prices to slump. However, fuel prices are then assumed

    to return from the current low levels to formerly observed levels within a 10 year timeframe

    based on the time required for there to be a correction in present oversupply conditions to

    satisfy softened demand for oil and gas27.

    To understand the implications of a lower and higher global fuel prices we also perform fuel

    price sensitivity analysis. One of the scenarios is based on a 50% fuel cost increase28 to put

    26 The IEA’s 450 scenario is an energy pathway consistent with the goal of limiting global increase in temperature to 2°C by limiting the concentration of greenhouse gases in the atmosphere to 450 parts per million CO2; further information available here: https://www.iea.org/media/weowebsite/energymodel/Methodology_450_Scenario.pdf .

    27 Reference: Facts Global Energy / Australian Institute of Energy, F. Fesharaki, “A New World Oil Order Emerging in 2016 and Beyond?”, February 2016, suggest a rebound in prices levels over a 5 to 7 year period as the most “probabl e” scenario.

    28 Including biomass prices.

    https://www.iea.org/media/weowebsite/energymodel/Methodology_450_Scenario.pdf

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    the study’s fuel prices in the range of the IEA’s Current Policies scenario29 which could be

    argued to be closer to the fuel pricing outlook that could be anticipated in a BAU outlook,

    while the SES and ASES scenarios could be argued to have fuel prices more consistent with

    the IEA’s 450 scenario. We discuss the implications of fuel pricing on the BAU and SES within

    the context of electricity pricing in section 9.5.

    For reference, we provide the base fuel pricing outlook for each year that was used in the

    fuel price modelling in Appendix B. These fuel prices were held constant in the BAU, SES

    and ASES scenarios.

    Figure 25 IES Base Case Fuel Price Projections to 2050

    4.4 Lao PDR Real GDP Growth Outlook

    Real GDP growth was assumed to stay relatively high at the current GDP growth rates due to

    the focus on industrialisation in the region. Over time, GDP growth was assumed to decline

    towards 1.96%30 pa by 2050 as seen in Figure 26. The trend down was assumed to reflect

    the economic development outlook of the government to 2035, before there is a transition

    towards the world average GDP growth rate. GDP assumptions were kept constant between

    BAU, SES and ASES scenarios.

    29 The IEA’s current policies scenario assumes no changes in policy from the year of WEO publication.

    30 1.96% reflects the previous 5-year GDP growth of the top 10 GDP countries in the world excluding Brazil, China and Russia.

    0

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    Crude Oil Dated Brent Fuel Oil Diesel Oil Imported Coal Asian LNG Uranium

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    Figure 26 Lao PDR GDP Projection

    The industrial sector’s increasing importance has been driven by policy and significant foreign

    direct investments in the mineral and hydropower sectors. The GDP composition of Lao PDR

    is weighted towards industry in line with the gradual shifting away from agriculture. The

    industry share of GDP in Lao PDR was assumed to increase from 33% in 2014 to 60% in 2030,

    similar to a number of the other GMS countries. The GDP composition is shown in Figure 27.

    Note that this assumption was held constant in the BAU and SES.

    Figure 27 Lao PDR GDP Composition

    0.0%

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    2.0%

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    2014 2035 2050

    Agriculture Industry Services

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    4.5 Population Growth

    Population was assumed to grow in line with the UN Medium Fertility scenario and is held

    constant across all scenarios31.

    4.6 Committed Generation Projects in BAU, SES and ASES Scenarios

    Committed generation projects are the ones that are under construction or at a stage of

    development that is sufficiently advanced for decision for the project to come online to not

    be reversed. Table 9 lists Lao PDR’s committed generation projects in addition to the existing

    790 MW 32 of hydro generation projects. The capacity column reflects the net capacity

    available to the Lao PDR grid after exports to Thailand or Vietnam. Projects with links to other

    countries have been highlighted in either green or red corresponding to exports to Thailand

    or Vietnam, respectively. The export arrangements were assumed to continue throughout

    the modelling horizon.

    The Thailand export projects, Xayabouly (Xayaburi), Sepian-Xenamnoy and Nam Ngiep 1 are

    also included in the BAU but come online just after 2018.

    Table 9 Lao PDR Committed New Entry Assumptions

    No. Project Exports To Capacity (MW) Technology COD*

    1 Nam Ngiep 2 180 Hydro 2015

    2 Hong Sa Thailand 405 Coal 2015

    3 Nam Ou 2 120 Hydro 2015

    4 Nam Ou 5 240 Hydro 2015

    5 Nam Ou 6 180 Hydro 2015

    6 Nam Kong 2 66 Hydro 2015

    7 Xekaman 1 Viet Nam 64 Hydro 2016

    8 Nam Sim 8 Hydro 2016

    9 Nam Mang 1 64 Hydro 2016

    10 Nam Beng 34 Hydro 2016

    11 Nam Sane 3A 69 Hydro 2016

    12 Nam Sane 3B 45 Hydro 2016

    13 Nam Lik 1 61 Hydro 2017

    14 Nam Phay 86 Hydro 2018

    15 Nam Tha 1 (Nam Pha) 168 Hydro 2018

    16 Xekaman 4 Viet Nam 16 Hydro 2018

    * Commercial Operation Date

    31 UN Department of Economic and Social Affairs, World Population Prospects: The 2012 Re vision.

    32 The capacity quoted is net of export arrangements.

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    Intelligent Energy Systems IESREF: 5973 42

    4.7 Regional Transmission System Integration

    The modelling presented in this report assumes transmission in the GMS becomes more

    tightly integrated than at present. Given the modelling period is for 35 years, we use a

    regional model for the interconnections as illustrated in Figure 2633. The figure shows the

    assumed topology of the GMS as well as to countries outside the region (PRC and Malaysia).

    Initially, not all transmission connections shown in the diagram are in place. However, over

    the modelling period the transmission connections are expanded as required to allow power

    exchange between regions to minimise costs and take advantage of diversity in demand and

    resource availabilities. Each scenario therefore effectively has a different high-level

    transmission development plan34.

    Figure 28 Regional Transmission System Model of GMS

    33 Currently, there is minimal physical interconnection between each GMS country. The model shows the topology that we have used in the modelling in order to gain an understanding of interregiona l power flows and to develop a very simple high-level transmission development plan.

    34 We only consider a high-level transmission development plan based on the regional model shown in order to gain insight on interregional power flows.

    THAILAND

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    HanoiLuang Prabang

    Vientiane

    Mandalay

    Yangon

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    Phnom Penh

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    Siem Reap

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    Intelligent Energy Systems IESREF: 5973 43

    The main differences in the assumptions behind the transmission system enhancements in

    each scenario were:

    In the BAU, it was assumed that transmission developments occur slowly and a tightly

    integrated regional power system is in place from about 2030, but the power sectors

    are developed so that there is only a limited level of dependency on imports from

    neighbouring countries. This is consistent with power sector planning that seeks to not

    be overly dependent on power imports from neighbouring countries.

    In the SES and ASES, the transmission system evolves from 2025 and we allow the

    transmission system (based on a simplified model of the region) to expand as needed

    to optimise the use of a geographically disperse set of renewable energy resources. A

    consequence of this is that some countries become significant exporters of power

    while others take advantage of power imports from neighbouring countries. In

    particular Myanmar and Lao PDR become major power exporters with the beneficiaries

    being the other GMS countries.

    4.8 Imports and Exports

    Lao PDR power exports to neighbouring countries are mainly in the form of projects that are

    dedicated35 as noted in 4.5. In addition to these projects, Lao PDR also exports smaller

    quantities of power into Thailand and Vietnam via Thakhek and Champasak respectively

    (power flows totalling approximately 12 GWh in 2014).

    Lao PDR have importing arrangements with Thailand, Vietnam and China. Flows from

    Vietnam (34 GWh in 2014) and Thailand (1,137 GWh) provide electricity to areas in Lao PDR

    not connected to the grid. The significant flows from Thailand support remote mines such as

    the Sepon gold and copper mines, which are not connected to the main Lao PDR grid.

    The flows from China totalled 239 GWh in 2014 or the equivalent of 27 MW average demand

    and connected to the Luang Prabang and Northern provinces to relieve the pressure of

    central Lao PDR plants. Power flows from China were assumed constant throughout the

    modelling period.

    4.9 Technical Economic Power System Modelling

    Technical and economic modelling of the GMS was done in the PROPHET electricity planning

    and simulation models. It develops a least cost generation based plan and was used to

    simulate the operation of the GMS region as an integrated power system.

    A brief overview of the various aspects is provided below:

    Planning Module: The Planning Module of Prophet allows for intertemporal

    constraints such as energy limits to be preserved when simulating the power system

    and developments. It also develops a least cost set of new entrants to satisfy demand

    over the 35 year modelling horizon.

    35 That is the project is connected to the national grid of the neighbouring country.

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    Intelligent Energy Systems IESREF: 5973 44

    Transmission: The power system was modelled based on the configuration as per

    Figure 28 with fixed / scheduled flows (red lines) to power systems outside the GMS

    not being explicitly modelled while power transfers within the GMS countries were

    optimised as needed to allow supply and demand to balance. This is important with

    respect to modelling diversity in demand in the different regions and geographical

    variation in generation patterns from supply-driven renewable energy (solar and wind)

    and seasonal variation of inflows into the hydro storages (see Figure 28).

    Economics: Capital and operating costs relating to generation plants as per the

    assumptions covered in this report allow the Planning Module to model generation and

    transmission development in a least cost manner. On top of this, resource constraints

    had to be formulated to reflect actual limits such as the maximum renewable resource

    and development rates available to each country.

    Demand: Demand profiles were constructed from energy and peak demand forecasts

    for electricity based on regression models that were developed for each sector of the

    electricity industry (commercial, industrial, residential, agricultural and transport). The

    monthly and intraday construction of the profiles were performed in Prophet based on

    historical data and/or external data sources indicating the seasonal profile of demand

    for each country.

    Flexible demand: was modelled as MW and GWh/month quantities that can be

    scheduled as necessary to reduce system costs. This means that demand tends to be

    shifted from periods when supply and demand would otherwise be tight to other times.

    The technology for rescheduling demand was assumed to be in place from 2020 in the

    SES and ASES scenarios.

    Supply: The approach taken for modelling generation supply technologies varied

    according to the technology type. This is discussed further below:

    - Conventional thermal plant: is modelled as capacity limited plants, with fuel take

    or pay contracts applied to generators where relevant and other fuel supply

    constraints in place also where relevant – for example, gas supply limits applied to

    LNG facilities or offshore gas fields. Examples of such plants include coal, biomass,

    gas, and diesel generators.

    - Energy limited plants: such as large-scale hydros with reservoirs / storages and CSP

    have monthly energy limits corresponding to seasonal variations in energy inflows.

    The equivalent capacity factors are based on external reports for hydro and

    resource data for CSP (see next point).

    - Supply-driven generation forms: Seasonal profiles for wind, solar and run of river

    hydros without reservoirs were developed on an hourly basis. For wind and solar

    they were derived from monthly resource data collected from a variety of sources

    including NASA, NREL36 and accessed via the Solar and Wind Energy Resource Atlas

    (SWERA) Toolkit and IRENA Global Atlas. Resource amounts were matched against

    actual generation data for known plants to develop equivalent monthly capacity

    36 DNI and Wind NASA Low Resolution and NREL DI Moderate Resolution data.

  • FINAL

    Intelligent Energy Systems IESREF: 5973 45

    factors at various high resource pockets in each country. Several traces were built

    from known generation traces to provide diversification benefits.

    - Pump Storage and battery storage: these are modelled in a similar way to flexible

    demand in that demand can be shifted with a capacity and energy limit but the

    scheduled demand is stored for generation later with an appropriate energy

    conversion efficiency (pumped storages assumed to be 70% and battery storage

    systems at 85%).

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    Intelligent Energy Systems IESREF: 5973 46

    5 Business as Usual Scenario

    5.1 Business as Usual Scenario

    The BAU scenario assumes industry developments consistent with the current state of

    planning in Lao PDR and reflective of growth rates in electricity demand consistent with an

    IES view of base development, existing renewable energy targets, where relevant,

    aspirational targets for electrification rates, and energy efficiency gains that are largely

    consistent with the policies seen in the region.

    5.2 Demand Growth

    Lao PDR’s on-grid electricity demand (including transmission and distribution losses37) is

    plotted in Figure 29. Lao PDR’s electricity demand is forecast to increase at a rate of 7.0% pa

    over the 35-year period to 2050 with higher growth rates in the earlier years relating to

    mining projects followed by a slowdown post-2040 as the economy trends towards long-term

    global GDP growth rates.

    The industrial sector is forecast to grow the fastest at 8.5% followed by the residential sector

    at 5.6%, commercial sector at 5.1% and agriculture at 0.8% per annum as the GDP

    composition shifts towards commerce/services and industry with increases in residential

    electricity consumption. The transport sector is forecast to hit 800 GWh by 2050 as the

    number of cars and uptake of electric cars and motorbikes increase to 15% uptake. Lao PDR

    electricity demand is forecast to reach 55 TWh by 2050. Peak demand is plotted below in

    Figure 30 and shows peak demand growing at 6.6% pa reaching 8 GW by 2050. The load

    factor is assumed to trend towards 75% by 2040 mainly driven by additional industrial loads

    impacting the demand base.

    The key drivers for demand growth and the demand projections are summarised in Table 10.

    37 Note that unless otherwise stated, all other demand charts and statistics include transmission and distribution losses.

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    Intelligent Energy Systems IESREF: 5973 47

    Figure 29 Lao PDR Projected Electricity Demand (2015-50, BAU)

    Figure 30 Lao PDR Projected peak Demand (BAU)

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    Intelligent Energy Systems IESREF: 5973 48

    Table 10 Lao PDR Demand and Demand Drivers (BAU)

    No. Aspect 2015-30 2030-40 2040-50

    1 Demand Growth (pa) 9.7% 5.5% 3.1%

    2 GDP Growth (Real, pa) 7.0% 6.5% 3.5%

    3 Electrification Rate (Population) 62.6% 97.0% 98.8%

    4 Population Growth 1.54% 1.07% 0.78%

    5 Per Capita Consumption (kWh) 1,322 3,009 3,995

    6 Electricity Elasticity* 7.70 2.28 1.33

    7 Electricity Intensity (kWh/USD) 0.337 0.454 0.464

    * Electricity elasticity is calculated as electricity demand growth divided by the population growth over the same period

    5.3 Installed Capacity Development

    The BAU installed capacity (MW) for Lao PDR is plotted in Figure 31 and Figure 32 by

    capacity shares for selected years: 2010, 2015, 2020, 2030, 2040 and 2050. The former

    shows installed generation capacity by the main generation type categories. We provide

    corresponding statistics in Table 11 and

    Table 12. Note that the installed capacity numbers exclude currently dedicated generation

    that is effectively available to its neighbouring countries as imports and where appropriate

    this has been de-rated to reflect supply agreements.

    Installed capacity in 2014 increases from 791 MW to 14,000 MW with large-scale hydro

    generation accounting for 71% of total installed capacity in 2050. Coal-fired capacity

    increases to 405 MW in 2015 with the commissioning of the Hong Sa coal plant and increases

    to 1,905 MW by 2050. From 2020, additional renewable capacity is developed to achieve a

    10% generation share (excluding large hydro) by 2050 comprised of solar PV, onshore wind,

    biomass and run-of-river hydro accounting for 14% capacity share in 2050.

  • FINAL

    Intelligent Energy Systems IESREF: 5973 49

    Figure 31 Lao PDR Installed Capacity (BAU, MW)

    Figure 32 Lao PDR Installed Capacity Mix Percentages (BAU, %)

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    Intelligent Energy Systems IESREF: 5973 50

    Table 11 Lao PDR Capacity by Type (BAU, MW)

    Resource 2010 2015 2020 2030 2040 2050

    Coal 0 405 405 1,005 1,605 1,905

    CCS 0 0 0 0 0 0

    Diesel 0 0 0 200 200 200

    Fuel Oil 0 0 0 0 0 0

    Gas 0 0 0 0 0 0

    Nuclear 0 0 0 0 0 0

    Hydro 330 1,577 2,257 5,509 7,509 10,009

    Onshore Wind 0 0 77 377 527 677

    Offshore Wind 0 0 0 0 0 0

    Biomass 0 0 53 203 323 323

    Biogas 0 0 0 0 0 0

    Solar 0 0 120 220 320 520

    CSP 0 0 0 0 0 0

    Battery 0 0 0 0 0 0

    Hydro ROR 0 0 100 100 200 400

    Geothermal 0 0 0 0 0 0

    Pump Storage 0 0 0 0 0 0

    Ocean 0 0 0 0 0 0

    Off grid 0 0 0 0 0 0

    Table 12 Lao PDR Capacity Share by Type (BAU, %)

    Resource 2010 2015 2020 2030 2040 2050

    Coal 0% 20% 13% 13% 15% 14%

    CCS 0% 0% 0% 0% 0% 0%

    Diesel 0% 0% 0% 3% 2% 1%

    Fuel Oil 0% 0% 0% 0% 0% 0%

    Gas 0% 0% 0% 0% 0% 0%

    Nuclear 0% 0% 0% 0% 0% 0%

    Hydro 100% 80% 75% 72% 70% 71%

    Onshore Wind 0% 0% 3% 5% 5% 5%

    Offshore Wind 0% 0% 0% 0% 0% 0%

    Biomass 0% 0% 2% 3% 3% 2%

    Biogas 0% 0% 0% 0% 0% 0%

    Solar 0% 0% 4% 3% 3% 4%

    CSP 0% 0% 0% 0% 0% 0%

    Battery 0% 0% 0% 0% 0% 0%

    Hydro ROR 0% 0% 3% 1% 2% 3%

    Geothermal 0% 0% 0% 0% 0% 0%

    Pump Storage 0% 0% 0% 0% 0% 0%

    Ocean 0% 0% 0% 0% 0% 0%

    Off grid 0% 0% 0% 0% 0% 0%

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    Intelligent Energy Systems IESREF: 5973 51

    5.4 Projected Generation Mix

    Figure 33 plots the generation mix (on an as generated basis38) over time in the BAU case and

    Figure 34 plots the corresponding percentage shares. Coal-fired generation initially increases

    to 887 GWh with the commissioning of the Hong Sa coal-fired power station in 2015/16 with

    the remaining output exported to Thailand39, and grows to 15 TWh by 2050. Large-scale

    hydro initially supplied the majority of Lao PDR’s on-grid demand requirements but with the

    additional coal and renewable developments, declines to 64% by 2050. Renewable

    technologies account for 10% of generation by 2050.

    38 Unless otherwise stated, all generation charts and statistics in this report are presented on an “as generated” basis, meaning that generation to cover generator’s auxiliary consumption accounted for.

    39 Dedicated capacity to importing countries such as that relating to Hong Sa is no t reflected here.

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    Intelligent Energy Systems IESREF: 5973 52

    Figure 33 Lao PDR Generation Mix (BAU, GWh)

    Figure 34 Lao PDR Generation Mix Percentages (BAU, %)

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    Intelligent Energy Systems IESREF: 5973 53

    Table 13 Lao PDR Generation by Type (BAU, GWh)

    Resource 2010 2015 2020 2030 2040 2050

    Coal 0 887 1,927 8,161 13,036 15,402

    CCS 0 0 0 0 0 0

    Diesel 0 0 0 58 81 183

    Fuel Oil 0 0 0 0 0 0

    Gas 0 0 0 0 0 0

    Nuclear 0 0 0 0 0 0

    Hydro 2,093 4,211 8,698 21,229 28,936 38,569

    Onshore Wind 0 0 198 958 1,337 1,716

    Offshore Wind 0 0 0 0 0 0

    Biomass 0 0 0 1,332 2,126 2,120

    Biogas 0 0 0 0 0 0

    Solar 0 0 215 392 573 928

    CSP 0 0 0 0 0 0

    Battery 0 0 0 0 0 0

    Hydro ROR 0 0 388 385 775 1,541

    Geothermal 0 0 0 0 0 0

    Pump Storage 0 0 0 0 0 0

    Ocean 0 0 0 0 0 0

    Off grid 0 0 0 0 0 0

    Table 14 Lao PDR Generation share by Type (BAU, %)

    Resource 2010 2015 2020 2030 2040 2050

    Coal 0% 17% 17% 25% 28% 25%

    CCS 0% 0% 0% 0% 0% 0%

    Diesel 0% 0% 0% 0% 0% 0%

    Fuel Oil 0% 0% 0% 0% 0% 0%

    Gas 0% 0% 0% 0% 0% 0%

    Nuclear 0% 0% 0% 0% 0% 0%

    Hydro 100% 83% 76% 65% 62% 64%

    Onshore Wind 0% 0% 2% 3% 3% 3%

    Offshore Wind 0% 0% 0% 0% 0% 0%

    Biomass 0% 0% 0% 4% 5% 4%

    Biogas 0% 0% 0% 0% 0% 0%

    Solar 0% 0% 2% 1% 1% 2%

    CSP 0% 0% 0% 0% 0% 0%

    Battery 0% 0% 0% 0% 0% 0%

    Hydro ROR 0% 0% 3% 1% 2% 3%

    Geothermal 0% 0% 0% 0% 0% 0%

    Pump Storage 0% 0% 0% 0% 0% 0%

    Ocean 0% 0% 0% 0% 0% 0%

    Off grid 0% 0% 0% 0% 0% 0%

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    Intelligent Energy Systems IESREF: 5973 54

    5.5 Grid to Grid Power Flows

    Figure 35 plots the imports and exports in the BAU with the dotted line representing the net

    interchange. Flows reported are in addition to the dedicated plant output such as that from

    Hong Sa power plant. Overall flows in the BAU are relatively low up to 2029 when Lao PDR

    starts to export to Thailand up to 6,500 GWh a year driven by significant differences in the

    levelised cost of electricity – Thailand relies on gas compared to Lao PDR which has significant

    hydro resources. Flows into Viet Nam are minimal.

    Figure 35 Lao PDR Imports and Exports (BAU)

    5.6 Generation Fleet Structure

    Figure 36 shows the installed generation capacity by the main categories of generation:

    thermal, renewable and large-scale hydro, in order to provide greater insight into the basic

    structure of installed capacity under the BAU. This highlights that Lao PDR’s BAU projection

    is heavily dominated by hydro generation followed by coal-fired generation. Figure 37 shows

    the on-grid composition of generation by major categories of generation: thermal, large

    hydro and renewable. As could be anticipated, generation closely reflects the BAU’s installed

    capacity mix.

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    Intelligent Energy Systems IESREF: 5973 55

    Figure 36 Lao PDR Installed Capacity by Generation Type (BAU, MW)

    Figure 37 Lao PDR Generation Mix by Generation Type (BAU, GWh)

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    Intelligent Energy Systems IESREF: 5973 56

    To facilitate later comparison with the SES, Figure 38 plots installed capacity with capacity

    being distinguished between the following basic categories: (1) dispatchable capacity, (2)

    non-dispatchable capacity; and (3) semi-dispatchable capacity40. This provides some insight

    into the operational flexibility of the generation fleet to match demand uncertainty. The

    dispatchable category relates to generation that can be controlled and dispatched at short

    notice to ramp up or down, non-dispatchable means that the generation is not able to

    respond readily to dispatch instructions while the semi-dispatchable category means that the

    resource can respond within limits, and in particular is capable of being backed off should

    the need arise to for example, avoid overloading the network or “spill” energy in the event

    that an over generation situation emerges; solar photovoltaics and windfarms with

    appropriately installed control systems can be classified in this category. In the BAU, the

    dispatchable percentage starts at 100% with only coal and hydro then as renewables are

    added to the system, it still remains above 85% by 2050.

    Figure 38 Lao PDR Installed Capacity by Dispatch Status (BAU)

    5.7 Reserve Margin and Generation Trends

    Figure 39 plots the reserve margin based on nameplate capacity and annual peak demand.

    The Lao PDR reserve margin in the BAU hovers around 60% and is higher than the other GMS

    countries in the BAU case. This is driven by Lao PDR’s investment in hydro developments,

    40 Wind and solar is classified as semi-dispatchable, geothermal and hydro run-of-river is classified as non-dispatchable and all other technologies are classified as dispatchable.

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