CHINA'S ENERGY FUTURE: LEAP TOOL APPLICATION IN CHINA

Transcription

1 CHINA'S ENERGY FUTURE: LEAP TOOL APPLICATION IN CHINA Prepared by: Baolei GUO, Yanjia WANG, and Aling ZHANG For the East Asia Energy Futures (EAEF)/Asia Energy Security Project Energy Paths Analysis/Methods Training Workshop 4 to 7 November, 2003 Vancouver, British Columbia, Canada 1. GENERAL INTRODUCTION Funded by the Nautilus Institute for Security and Sustainable Development, the use of the LEAP (Long-range Energy Alternatives Planning) model at Tsinghua University in China started in 2001 as part of the larger EAEF (East Asia Energy Futures) regional project. The Tsinghua University LEAP modeling effort proceeded in two stages: assembling a China dataset for LEAP, and LEAP scenario (energy paths) analysis. This paper is based on the dataset assembled as a part of the Nautilus-funded project, and the Chinese version also served in partial fulfillment of requirements for a degree paper prepared by one of the authors (Guo Baolei) at Tsinghua University. Guo Baolei - 1 -

2 wishes to note that Professor Yanjia Wang, Professor Aling Zhang, and Dr. David Von Hippel have been of great help in the completion of the Chinese version of this paper. This paper starts with a discussion of the steps required to develop future scenarios for China s energy system, followed by a detailed introduction to the LEAP modeling process used. The assumptions of the scenarios developed are then summarized, and an analysis of the modeling results is presented. The last section of this paper presents the implications of the results of the China energy scenario analyses. 2. DEVELOPING FUTURE SCENARIOS FOR CHINA The development of quantitative future scenarios for China started with the preparation of a set of internally consistent stories, or qualitative scenarios, on which to base LEAP models of China s energy future. The section of this report that follows describes the methods used to develop the qualitative scenarios of China s energy future on which the LEAP scenarios (or paths) presented in section 3 are based. 2.1 Step I: Define a Focal Issue Scenario development begins by identifying a unifying question or idea to be used in defining what the scenarios will explore. The unifying question, or focal issue, is the topic that you want the scenarios to help you to address. The focal issue therefore provides an organizing lens for evaluating and assembling relevant information (Schwartz, 1992). The focal issue can be specific or broad, depending on the objective of the scenario analysis. In the authors opinion, in the context of people s increasing concern for the environment, improving the Chinese energy supply structure and providing safe and clean energy supply have become China s primary concern. This priority will surely emerge and become China s focal issue in considering regional energy cooperation opportunities, namely: can the objective of clean and safe energy supply for China be achieved, at least in part, through regional cooperation? China is cautious, however, of the risk arising from multi-party cooperation. Issues such as the possibility of the abrupt withdrawal of some party from an energy cooperation agreement and thereby posing a threat to China s energy security must be considered. The focal issue chosen for this China energy futures analysis is an inquiry about clean and diversified energy supply. China Energy Future Scenario Focal Issue How will diversified and clean energy supply be realized in the next 30 years? Will new priorities emerge from regional cooperation? What impact will these new factors have on China's energy pathway? - 2 -

3 2.2 Step II: List Important Factors Affecting China s Energy Future When listing the important forces affecting China energy system, we take the following facts and situations into account: regional economic cooperation, political relationships (both between countries and internal), social development (including population increase, education, government deregulation, and other related issues), and technological progress. In addition, the energy demand and supply situation, the possibilities for regional cooperation on energy issues, and the energy policies of other countries in NE Asia are considered to be factors affecting China s energy future. Some specific energy projects are also listed as important factors in their own right, including power network projects (for example, enhancing the connections among China s regional grids), and international gas and oil pipelines. Table 2-1 provides a summary overview of the factors affecting China s energy future

4 - 4 - Table 2-1: Factors Affecting China's Energy Future Geopolitics and Energy Import electricity from Russia Gas and oil pipelines in the region The availability of Middle East and Central Asian oil Unstable political relations: Political crisis and energy crisis Regional energy linkages and understanding Understanding of national security and energy linkages Undrstanding the impacts of energy cooperation arrangements The founding of a regional energy union Government Government control of energy industry and deregulation Different priorities between local and central goverment International pressure for better environmental performance Population and the public Increasing population and gap between the income of rich and poor Change of household scale, and the saturation of home appliances People's concerns of energy policy Increasing influence of Non-Governmental Organizations and communities People's choices and preferences of transport forms Economy Global and regional economic development Influence of economy growth on environment Regional economic cooperation Strength of private sector industry in influencing policy Investment and infrastructure construction Conditions and sources of investment finance Private interest in investing in infrastructure Infrastructure technology Power network improvement and natural gas transimission Technology Benchmarks for designing products: efficiency, convenient and environment-friendly, etc. Targets for technology support research and development, demonstration projects, market pull/push, institutional innovation Commercialization of new energy technologies Costs of new energy technologies Nuclear waste disposal technology Fuel and resources Fluctuation of fuel prices Limited oil and NG reserves Rely on NG Oil products' dominance as a fuel type in tranport sector Government's policy prorities Support for research and development on new and renewable energy Development of public transport Diversified energy supply Choice between independence and dependence in energy supply Attitude on global climate change

5 2.3 Step III: Evaluate Factors and Driving Forces Based on Importance and Uncertainty In elaborating the list of important factors and establishing broader categories of elements to include in scenarios, it becomes apparent that certain critical topics thread between the lists of factors affecting the Chinese energy system. These unifying topics can be called driving forces. They represent central points of interconnection between classes of factors affecting the energy system, and are particularly important in thinking about critical areas of change within energy systems. The analysis of unifying topics among the factors described in Table 2-1 identifies 9 key driving forces, which are presented within the rounded rectangles in the figure below (Figure 2-1). Evaluating the relative importance and uncertainty associated with each driving force, certain elements emerge as both highly important and uncertain. These driving forces can be considered critical uncertainties. They are the factors in China s energy system with the greatest potential to motivate fundamental changes and/or deviations from current trends. IMPORTANCE Economy Technology development Government's Role Government s Policy priorities Geopolitics and Energy Population Fuel and resource Public choice Investment and Infrastructure construction Figure 2-1: Identifying key driving forces UNCERTAINTY Listed in Figure 2-1 are the key factors or driving forces that, in the authors opinion, will have the greatest impact on China s energy future. The Geopolitics and Energy and Government s Policy priorities categories, located in the upper right corner of the figure, are the most important and uncertain factors, and as such are most likely to cause dramatic change in China s energy system. As to energy policy priorities, the Chinese government has many alternatives. In the authors view, however, a diversified supply approach will do the most to address the problems of environment protection and sustainability. The government s willingness or unwillingness to set the objective of diversified energy supply as a high priority will lead to different pathways of energy development in China. In addition, China s increasing - 5 -

6 dependence on oil imports from the Middle East over the last 10 years, coupled with the turbulent regional situation there, means that China has to consider seriously the problem of geopolitics and energy security. A choice between a largely self-sustained energy supply policy and an import-oriented policy will also result in different energy pathways. So the following two questions apply to the development of scenarios: How does China ensure energy security? Will the objective of developing a diversified energy supply be China s primary choice are going to be the key questions facing China as it develops its strategic energy policy over the coming years. 2.4 Step IV: Select Scenario Logic Figure 2-2, below, presents the decision logic used to create four candidate scenarios based on the two key questions identified above. The initial question posed is whether China will place a higher priority on diversification of energy supply than in recent years. A No answer to this question would lead to the scenario described as L in Figure 2-2, but as this scenario seems neither likely nor particularly illuminating to evaluate, it was dropped from further consideration. A Yes answer to the initial question leads to a second question, which is how to diversify in a way that best meets energy security goals. Diversification that is import oriented leads to a H-External scenario, diversification with a goal of using mostly domestic resources leads to a H-Internal scenario, while a combination of the two approaches ( Middle of the road ) yields the BAU scenario. H-Internal A higher priority on the object of a diversified energy supply Y N Self-susatained Middle of the road BAU How to ensure energy security Import-oriented L H-External Figure 2-2: Select scenario logic 2.5 Step V: Develop Scenarios around Critical Uncertainties The China EAEF team developed scenarios based on the logical structure outlined above. Figure 2-3 shows the two-axis scenario matrix used to identify and orient the four overall scenarios used in the China LEAP analysis. Each of these four scenarios is outlined below, and the input assumptions for each are described in more detail in the next three sections of this paper

7 How to ensure energy security? Self-sustained H-I Low L BAU The object of High a diversified energy supply H-E Imported-oriented Figure 2-3: Scenario matrix The Base Case Scenario: Business-as-usual In the Business-as-usual, or BAU scenario, China s economy is still growing at a relatively high rate, but China remains the largest developing country in the world. No dramatic breakthrough takes place in regional political relations or in regional economic cooperation. The energy sector develops well under the guidance of the energy policies and various social development objectives set by the central government. Natural gas and hydro power are increasingly widely used as a result of the promotion programs carried out by the government, as well as the completion of the West gas to East, and West electricity to East projects. The urbanization process accelerates, creating high pressures to solve both fuel supply and environment problems in big cities. More people are educated, and the travel industry grows fast. The industrial structure gradually undergoes a transformation toward more high-valued-added industries. The government chooses to develop electricity generation technologies centered on clean coal and natural gas (NG), with a moderate renewable energy program Alternative Scenario: High priority-external The fast-growing economy in the middle and west parts of China leads to increasing demand for electricity and for more clean energy. Regional cooperation brings new opportunities to all of the countries concerned. With the unification of the Korean peninsula, power network and international pipelines are constructed. An energy charter is drafted to promote further cooperation in the region, including the free transfer of new energy technologies and a common benchmark concerning energy efficiency to be used in the design of energy-using products. More natural gas is used in China s economy as a whole in this H-E scenario Alternative Scenario: High priority-internal The fast-growing economy of China and China s increasing dependence on imported fuel makes - 7 -

8 the countries in the NE Asia region struggle to get more energy supply from the region. Competition for energy supplies among the countries results in the suspension of regional cooperation. The higher cost and difficulty of finding other cost-efficient sources of clean energy supply cause the Chinese government to choose to start a program of relying as fully as possible on domestic energy resources, with no additional increase in energy imports from outside except for oil, which is an inevitable trend. As a results, new and renewable energy programs, public transport initiatives, electric car programs, nuclear power programs, and other domestic-resource-oriented policies are advocated and pursued under the H-I scenario. 3. MODELING SCENARIOS To structure and to estimate the impacts of the scenarios outlined above, the China EAEF team used the LEAP2000 (now LEAP2003) version of the LEAP software system as a modeling tool, creating a LEAP-China database and framework for scenario analysis. LEAP-China is a multi-sector end-use model characterizing energy and fuel use in China, as well as greenhouse gas emissions and other pollutant emission characteristics, for the modeling period 1999 through LEAP 2000/2003 is a powerful tool for scenario analysis, and LEAP s scenario management features make the comparison and development of alternative scenarios easy and convenient. Assembling data: It is clear that a good description of China s energy system must be based on accurate and detailed historical data. Statistical data in China, however, is scattered among many reports and statistical yearbooks, which made data assembly harder and more time consuming than expected. Some of the data sources used for the LEAP-China database are listed as follows: China Statistical Yearbooks of various years, Energy Statistical Yearbooks of , the Transport Statistical Yearbook, the Statistical Yearbook of the Power Industry, the China Energy Data Book (version 5.0), and some additional data compiled by David Von Hippel in his work done in 1999 to assemble a LEAP-China database (as used in Modeling of Clean-Coal Scenarios for China: Progress Report and Initial Results). Some additional reports were used as reference materials as well, such as Demand Data Development for China MARKAL Model, , Appendix to Future Implications of China s Energy-Technology Choices by Zongxin Wu et al., Development of Renewable Energy in China: Potential and Challenge by Zhang Zhengmin, Dr. Jan Hamrin et al. The Role of Renewable Options in China's Present and Future Energy System 2000 by Gu Shuhua, Conversion and Process Technology Data for China MARKAL Model, , Appendix B to Future Implications of China s Energy-Technology Choices by Zongxin Wu. Articles from various magazines and journals were also used as data sources, such as NO x Emissions Arising from Commercial Energy Consumption in China (Tian Hezhong, Hao jiming, 2001), and Forecast of China s Urbanization Process (Guan Ke, etc., 2000). Some articles and reports from the Internet are also taken as data source, such as Future Population Projection by China Population Information Center, from Major data gaps include data needed to develop a system load curve for the electricity generation sector (it has been - 8 -

9 necessary to invent one based on the average load factor). Additional details on the reference documents described above can be found in the References section to this paper. Constructing base year: The LEAP-China model characterizes the structure of China s energy for each year between 1999 and The first year used in the model, or the base year, was developed from existing national-level data. Each of the scenarios begins with a 1999 base year. Organizing the model structure: Based on the data available as described above, the structure of the LEAP-China model has three key sectors--resources, Transformation, and Demand. The Demand sector is further disaggregated into five end-use sub-sectors: Residential, Industry, Transport, Commerce and Agriculture. In the Transformation sector, the power generation sub-sector is treated in some detail, and several other transformation sub-sectors, including oil refining, coal washing, and gas making, are also addressed. The detailed structure of the China LEAP model is shown in Figures 3-1, 3-2, and 3-3. Figure 3-1: LEAP-China Model Structure - 9 -

10 Figure 3-2: Tree structure of demand sector in LEAP China Model (only selected details are shown)

11 Figure 3-3: Tree Structure of Power Generation Sub-sector in China LEAP Model Demand and supply sector: Each individual supply and demand sub-sector is disaggregated into end-uses and technologies that consume, generate, or transform fuels. The structure of each sector and sub-sector accommodates policies and changes associated with the scenarios, and these changes are reflected through changes in parameters, over time, in specific technologies and end-uses. The model structure used also depended on the data available for each sector and sub-sector. Technologies and/or end uses are characterized by sets of specific parameters, including market or household saturation, fuel consumption, energy efficiency, energy intensity, and demographic and/or activity drivers. Modeling scenarios: Scenarios are represented in the energy system model through explicit

12 assumptions of how energy, technology, and activity parameters for some or many demand and supply branches (for example, demand end-uses or technologies) or processes (for example, power plant types) in the energy system model change over time. The base year provides a common starting point, and each scenario explicitly includes assumptions as to how the composition and attributes of the energy supply and demand structure will change over time. The BAU scenario is based on national policies and plans, as well as the projection of historical data. The BAU scenario therefore reflects official expectations or the most possible projections for the future based on current trends. The BAU scenario serves as a reference scenario and point of comparison for the alternative scenarios. Other scenarios are based on sets of policy or technology choices that are reflected in the scenario stories, as described above. The policy or technology choices are simulated within the LEAP-China model through assumptions regarding future changes in parameters such as activity level, saturation, energy intensity, and others. Calculating energy and fuel demand: Energy demand and supply for each sector is calculated using a simple set of equations built around technology energy intensities, saturation data, and activity drivers within each sector. The table below summarizes the generalized equations used to calculate energy supply, demand, and fuel consumption for each year, sector, and scenario. Table 3-1: General Energy Demand Calculations ENERGY DEMAND RESIDENTIAL= (#hh) * (end use %saturation) * (technology %saturation) * (UEC) TRANSPORT: PASSENGER TRANSPORT= (PKT/yr) * (vehicle% PKT share) * (technology% vehicle share) * (fuel use/pkt) FREIGHT TRANSPORT=( TKT/yr) * (Vehicle %TKT share) * (technology% vehicle share) * (fuel use/tkt) COMMERCE=(Floor space) * (Fuel use/m 2.yr) * (fuel share/%) INDUSTRY=(Industrial physical production or value added) * (Sub-sector% share of physical production or RMB) * (fuel use/ton*yr or fuel use/rmb*yr) Note:#hh = number of households; UEC = unit energy consumption; PKT = passenger kilometers traveled( passenger-km); TKT = ton-kilometers carried (ton-km) ENERGY SUPPLY POWER GENERATION: Capacity, efficiency, merit order, load curve Residential Sector: The residential sector is organized into two sub-sectors in LEAP-China: Urban and Rural, each of which includes four end-uses, including: space heating, cooking, lighting, and home appliances. Each end-use in turn is made up of different technologies that provide end use

13 services. The energy consumption of a given technology in any given year is calculated as the product of the total number of households, the saturation of the end use in residential households, the technology share of the end use, and the unit energy consumption of the given technology. Total energy consumption is the sum of the different technology categories. Industrial Sector: The industry sector is made up of four key sub-sectors: Manufacturing industry (including 11 sub-industries), Mining and Quarrying industry, Construction industry, and the Gas&Water Supply industry. The energy consumption calculations in these subsectors are based either on the physical production of industrial products or on value added, depending on the subsector. Transport Sector: The transportation sector is organized into two large categories. Passenger transport includes transport by railway, highway, airway and waterway. Freight travel includes rail, water shipping, highway, air shipping, and pipeline transport. Each sub-category is comprised of specific technology types, for example, gasoline, diesel, and electric cars in the road passenger transport subsector. Energy consumption is calculated based on the total volume of passengers and/or freight transported, on the share of different forms of transit, and on the energy consumed by each specific technology type per unit volume (in passenger-km or ton-km) of transport services provided. Commerce Sector and Agriculture Sector: The organization of the commerce and agriculture sectors in the China LEAP model reflects the structure of existing data for these sectors. Total commercial building floor area and the gross domestic product of agriculture industry are the two key activity parameters used, respectively, in these demand sectors. Electricity Generation: Electricity generation calculations depend in part on the demand sector calculations for total electricity demand, which sets the amount of electricity that the electricity sector must supply in each year. The descriptions of the electricity-generating processes in the electricity portion of the China LEAP model specifies the technology attributes, merit order of dispatch of generation processes, and annual system load curve shape for the electricity generation sector. Actual electricity generation in any given model year depends on the level of electricity consumption generated by the five demand sectors and the level of imports, and any internal electricity use in transformation sectors. The model structure characterizes the generation sector, and then based on the level of electricity required to meet the annual demand requirements, it dispatches electricity generation technologies (processes) to produce the needed electricity. In LEAP-China, parameters such as merit order (specifying which plants will run first, which second, and which for peaking, for example), efficiency, base year installed capacity, and maximum capacity factor are used to describe each electricity generation technology. Also, in LEAP-China, an approximate system load curve was estimated, although it is admittedly very difficult in practice to determine a national-level system load curve, since a integrated electricity network does not yet exist in China. The use of an invented load curve for this modeling effort, however, using the historical average load factor as a starting point, is useful for to help modelers obtain insights into the future characteristics of the electricity system. Altogether,

14 electricity-generating technologies are modeled in LEAP-China, including large coal-fired plants (installed capacity larger than 300MW), small- and medium-scale coal-fired plants (installed capacity below 300MW), large hydro power plants, nuclear power plants, wind power, geothermal power, solar PV (photovoltaic), oil- and gas-fired internal-combustion power plants, biomass gasification power plants, landfill gas-fired turbines, CCGT (combined-cycle gas turbines), IGCC (integrated gasification combined-cycle plants), and others. All of the generation technologies are assigned merit orders, capacity values, efficiencies, and base year exogenous capacity (capacity explicitly specified for the model). In modeling the electricity sector, the China LEAP model also explicitly sets a planning reserve margin and a level of transmission and distribution losses. For these analyses the planning reserve margin is set at 30% throughout the study period and the level of transmission and distribution losses is fixed at 6.9%. New capacity additions are added either exogenously or endogenously in modeling the growth of the electricity generation sector. Exogenous capacity additions are planned additions with a specific quantity and type of capacity added at a specific time in the future. Endogenous capacity additions are specific technologies that are built as needed to meet the electricity consumption requirements as specified by the demand sectors. Other transformation sectors: Other transformation sectors include district heating, gas making, coking, coal washing, briquette making, and oil refining. It is assumed that future capacity of these processes simply increases to meet demand. Greenhouse Gas Emission and NO x, SO 2 Pollutants Calculation: Using the China scenarios framework for energy supply and demand, a set of simple calculations was carried out to estimate greenhouse gas emissions and NO x, SO 2 emission for each scenario. These calculations provide a basis for comparing the potential magnitudes of pollutant emissions for each scenario over the modeling period. The greenhouse gas emissions associated with fuel consumption in China were estimated using generally- accepted average emissions factors for each sector and fuel type. Total greenhouse gas emissions and other pollutant emissions are calculated by multiplying the primary energy demand from each non-electric end-use device and each transformation process by corresponding average emission factors. The TED (Technology and Environment Database) feature of the LEAP model was not used in the current version of the China LEAP model, due to lack of time, to date, to incorporate this means of emissions estimation. The energy system model developed in this project provides a comprehensive and flexible tool for exploring future energy scenarios in China. The model is grounded in the existing structure and composition of the State s energy system. The base year data used in the model, and the base year results, reflect the existing energy system. The Business-as-usual scenario represents current forecast assumptions about the future. The alternative scenarios explore alternative pathways for how the future may unfold

15 4. ASSUMPTIONS FOR THE BAU AND ALTERNATIVE SCENARIOS 4.1 Energy Situation in the Base Year In the base year (1999), according to statistics from the National Statistics Bureau (NSB), China s total primary energy consumption was Mtce, with coal accounting for 68%, or 885 Mtce, oil accounting for 23.2% of the total, and NG 2.2%, with nuclear power and hydro providing the remaining 6.6%. According to the State Power Corporation, by the end of 1999, the total installed capacity of power plants reached GW, GW of which was hydro power, and 2.1 GW was nuclear power (the rest was fossil fuel-fired thermal generation). The total electricity generated rose to TWh in 1999, with hydropower producing TWh, nuclear power producing 14.8 TWh, and thermal generation (mostly coal) accounting for the remainder. The average coal consumption to produce 1kWh of electricity was 369 g. The output mix of electricity generating sector as of 2000 is shown in Table 4-1. Table 4-1: Year 2000 Output (TWh) and Mix (%) for China s Electricity Generating Sector Output, TWh Mix Total coal oil gas nuclear hydro other renewables The energy import and export situation in China as of 2000 is shown in Table 4-2. By 2000, China was already a net importer of crude oil and oil products, though it continued to be a net exporter of coal

16 Table 4-2: Year 2000 Energy Import and Export Situation in China million ton 2000 crude oil import export oil products import export 8.27 coal import 2.02 export Source: Statistics of China Customs 4.2 Existing Forecasts of China s Primary Energy Demand Tables 4-3 and 4-4 present two existing forecasts one from the research group that prepared the China Energy Strategy report, and one from the International Energy Agency. The China Energy Strategy report also included an Ecologically Driven (ED) scenario. Both the IEA forecast and the BAU case in the China Energy Strategy report show average annual growth in energy demand of roughly 3 percent for 2000 through 2020, with the growth in the ED case being somewhat lower

17 Table 4-3: Forecast of Future Energy Demand by the Research Group of China Energy Strategy 1 Unit: Mtce real demand 2010 BAU ED BAU ED Coal Oil NG Nuclear Renewables #Hydro ## small hydro #biomass #new renewables Total Note:1. Except Oil and NG, the demand of each fuel type is equal to domestic supply capacity 2. BAU=Business-as-usual, ED=Ecology Driven 3. Export not included in coal demand. 4.new renewables include small hydro, new biomass technology,windpower, solar, geothermal, tide power 5.For nuclear and renewable power plants, 1 kwh=373 gce in 1998, and that figure changes to 330, 20, and 300 respectively in 2010, 2020 and Table 4-4: Future Energy Demand as Forecast by the IEA, (units: Mtoe) Annual growth rate, % Coal Oil NG Nuclear Hydro Other renewables Total Source: IEA, World Energy Outlook Data in this table were compiled from a number of sources, including: 1) Research Group, China Energy Strategy Research ( ), China Power Press, ; 2) Chinese Academy of Engineering, Sustainable Energy Strategy Research for China, ; 3) National Planning Committee (now China Development and Reform Committee), Joint Survey Team of former Department of Coal Industry, Investigation and Forecast of National Coal Consumption, 1999; 4) Zhou Xiaoqian, Prospects for China Power Industry, China Power, No.10, 1999; 5) China Rural Energy Statistical Yearbook, China Agriculture Press, ; and 6) National Statistic Bureau

18 4.3 General Introduction to Scenario Assumptions The most important features of all of the scenarios explored by the authors are an expectation of increases in population (though population growth slows over time), steady economic growth, continuing of the urbanization process, increasing transportation sector activity (in both the passenger and freight subsectors), increasing commercial floor space and residential living space, and significant power sector capacity additions. These features are activity drivers that account in large part for the observed scenario results. Some of the general assumptions regarding changes over time in population and the Chinese economy are shown in Table 4-5. Other important features of all scenarios include increasing saturation of home appliances and gas use, decreasing use of biomass as a fuel type in residential sector, and changing shares of different transit forms as a fraction of total transport turnover (tonne-km and passenger-km, as is shown in Table 4-6). The main differences between Business-As-Usual scenario and the alternative scenarios explored are the technological and policy choices concerning difference fuel promotion programs, as is shown in Table 4-7. Table 4-5: Assumptions Regarding Population and GDP Growth, All Scenarios Population: 100 million Urbanization rate: % 37.70% 40.89% 49.34% 57.82% GDP growth rate: % 7.00% 7.00% 7.00% 5.50%

19 Table 4-6: Assumptions on Turnover and Fraction of Various Transit Forms in the Transport Sector Freight: tonne.km (trillion) Fraction of Freight by: Growth as (GDP, 0.4) Railway 31.80% 28% 27% 27% Roal 14.10% 16% 17% 17% Waterway 52.50% 54.50% 54.50% 54.50% Airway 0.10% 0.15% 0.18% 0.18% Pipeline 1.50% 1.35% 1.32% 1.32% Passenger: passenger.km (trillion) 1.13 Growth as (GDP, 0.75) Fraction of Passenger by: Railway 36.60% 31.69% 29.20% 27.82% Road 54.86% 59.89% 62.30% 63.90% Waterway 0.95% 0.75% 0.68% 0.45% Airway 7.59% 7.67% 7.75% 7.83% Note: Growthas(GDP,0.4) means that the tonne-km of freight transported is assumed to grow as GDP grows, but with an income elasticitiy of demand of 0.4. A similar relationship, except with an elasticity of 0.75, is assumed to apply to growth in passenger-kilometers travelled. Table 4-7: Technological and Policy Choices in Different Scenarios BAU H-I H-E Large coal-fired plants Moderate renewable energy development program Moderate NG utilization program Moderate new fuel car development program Clean coal techniques Nuclear power program Large promotion of renewable energy program Electric car program NG imports used for electricity generation NG car program Power grid interconnection Oil pipeline in NE Asia Energy efficiency improvement program Promotion of NG use in residential and industrial sectors 4.4 Assumptions in the Business-As-Usual Scenario The BAU scenario is based on a set of assumptions derived either directly from or through interpretation of official state-level forecasts and plans. Detailed assumptions include: In the

20 residential sector, the population and economy continue to grow, the urbanization process continues, and more households can afford to buy home appliances. City gas (both coal gas and natural gas) is used by more households, while at the same time in the urban household sub-sector coal is used by gradually fewer and fewer households. In the rural households sub-sector, coal and LPG gradually take the place of biomass. Both in the urban and rural sub-sectors, solar water heaters become popular. In the industrial sector, the production of all industrial products continues to grow, but the rate of growth gradually decreases over time. In the transport sector, both GDP and per capita GDP serve as key driving forces of the increase in transport turnover, the share of road and air transport increases while that of railway transport decreases, and more diesel (as opposed to gasoline) cars and trucks are used in transport. In the commercial sector, building floor space continues to increase, with gas and electricity fuel shares increasing. In the agricultural sector, the share of GDP accounted for by agriculture decreases, although the total value-added of the agriculture industry increases. In the transformation sector in the BAU scenario, power plant construction continues. Large coal-fired plants and NG turbine power plants are constructed as endogenous capacity additions for base load and peaking power, respectively, within the LEAP model 2. The use of renewable energy develops slowly, but the installed capacity of small hydro plants grows dramatically. No further nuclear power plants are constructed except those already planned. The capacity of other transformation processes within the transformation sector simply grows to meet demand except for NG extraction and oil refining, which do not grow at the rate of demand due to the restriction in the amount of available resources. 4.5 Assumption for Alternative Scenarios The alternative LEAP scenarios (or energy paths ) are based on a set of assumptions about future national technology choices that are derived from the narrative scenario context described in section 2 of this paper. In the H-E scenario, more natural gas is widely used in almost all demand sectors and in electricity generation, while the use of coal is further decreased. No further efforts are made to promote the use of renewable energy and nuclear power. In the H-I scenario, the program of renewable energy utilization means that biomass remains an important fuel type in residential sector. Nuclear power is widely used in electricity generation. More new power plants featuring high energy-efficiency are used. Coal still plays an important part in almost all demand sectors. Details of key assumptions for all three scenarios are shown in Table In LEAP, Endogenous capacity additions are made automatically by the model (based on rules that the modeler specifies) when new capacity is needed. For Exogenous capacity additions, on the other hand, the modeler explicitly enters how much capacity of a specific type of plant is to be added in a specific year

21 Table 4-8: Scenario Assumptions SCENARIO ASSUMPTIONS BAU H-I H-E Residential Population and Urbanization Refer to Table 4-5 Saturation of gas use in household (2010,78.13%, 2020,90.68%, 2030,100%) As in BAU As in BAU #Saturation of NG use Reaches 15% in As in BAU Reaches 38% in 2030 Urban Solar water heater Reaches 5% in Reaches 30% in 2030 Saturation of air conditioner (2010,41.87%, 2020,56.3%, 2030,62%) Saturation of refrigerator Reaches 100% in 2020 As in BAU Solar water heater Reaches 50% in 2030 Reaches 100% in 2030 Rural Energy intensity of wood stove Decrease 4% annually Keep at base year level As in BAU Synthetic Ammonia According to the tenth-five-year plan, the demand of synthetic ammonia will reach 3.6 million tons. And the forecast of Li zhidong shows the demand will reach 3.74million, 4.12 million and 4.98 million tons in 2010, 2020 and 2030 respectively. Industry Paper Industry Cement From 2000 to 2005, annual demand growth rate keeps at 6.8%, reaching 50 million tons, according to the tenth five year plan. Assume growth rate keeps at 5% from 2005 to 2030, with energy intensity decreasing to 1.0tce/ton paper. The total production of cement will keep relatively even, however the energy consumed per ton will decrease to 145Kgce in We assume the energy consuming level to reach that of Japan 1999, decreasing to 124.4Kgce/t. As BAU scenario Increase the fuel share of NG in Chemical industry, esp. in synthetic ammonia production. Steel Industry Physical production of steel keeps at an annual growth rate of 2% from , 1% from According to the Tenth Five Year Plan, to 2005, the energy intensity of large and medium scale steel enterprises will decrease to 0.8 tce/ton steel. Assume that to 2030, the energy intensity reach that of Japan 1999, decreasing to 0.68 tce/ton steel. Transport Other Industries Assumption on turnover and share of different transit forms Passenger Transport Energy intensity keeps unchanged over the period, but the value added will increase linearly. Refer to Table 4-6 railway: the fraction of internal combustion locomotives and electric locomotives account for 50% respectively. Road transport: the share of medium and small cars increase to 60% in 2030, of which gasoline cars' share decreases to 70%, diesel cars increasing to 20%, LPG cars reaching 10%. The share of large diesel bus increases to 40%. Air transport energy intensity decreases by 10% to Further decrease of small and medium sized gasoline cars, to 60% in 2030, while electric cars increasing to 10% and fuel cell cars to 5%, NG buses to 5%. Road transport: to 2030, small and medium sized gasoline cars decrease to 50%, while electric cars and NG cars reaching 10% each; in large passenger buses, NG and diesel buses take 50% each. Railway: to 2030, steam locomotives out of market, while internal combustion and electric locomotives take 50% each. Road: proportion of Light-duty and heavy-duty trucks reach 50% each, with fuel being diesel. As BAU scenario As BAU scenario Freight Transport

22 GDP growth Growth rate stays 7% annually from 1999 to 2020, and slowing down to 5.5% from 2020 to 2030 Agriculture Share of Agriculture in GDP decreasing from 17.7% in 1999 to 15%, 13% and 10% in 2010, 2020 and 2030 respectively, while at the same time the tertiary industry GDP share increasing from 33% in 1999 to 48% in As BAU scenario Commerce Floor space According to Prlf. Zongxin Wu, commercial floor spaces change with urban residential living space at a ratio of about 0.4, reaching 5.66 billion square meters. As BAU scenario 50% of the present coal-fired plants (with installed capacity larger than 300MW) will retire in2030. Installed capacity of new wind power plants will reach 10GW in Installed capacity of landfill gas power plants will reach 15GW in Accelerated retirement of small and medium scale coal fire plants No more gas and oil internal-combustion power plants. Exogenous Capacity 80% of the present gas and oil internal combustion plants will retire in Installed capacity of biogasification power plants will reach 3GW in 2010, 10-15GW in 2020, 20GW in Electricity Generation The installed capacity of wind power plants, geothermal power plants, solar power plants, and small hydro power plants will reach 1100 MW, 110MW, 320 MW, MW in CHP plants increase by 3000MW annually. Nuclear power plants capacity will reach 8700 MW in Installed capacity of large hydro power plants will reach 190 GW in As in BAU scenario As in BAU scenario Endogenous Capacity Addition order 1:100MW NG turbine Addition order 2:300MW new coal-fired plants. Addition order 1: 100MW NG turbine. Addition order 2: 300MW new coal-fired plants Addition order 1: 300MWCCGT-NG Addition order 3:300MW CCGT-NG Addition order 3: 900MW nuclear power plants. Addition order 2: 100MW NG turbine Imports when there is supply gap, import electricity. Small amount or no electricity imports Encouraging electricity imports 5. MODELING RESULTS 5.1 Overview of Final Energy Demand Spanning in Business-as-usual and Alternative Scenarios In the base year (1999), final energy demand in China as simulated by LEAP is Mtce, including biomass use. In 2030, total final energy demand reaches 2424 Mtce in the

23 Business-as-usual scenario, for an average annual growth rate of 2.17%. For the H-E scenario, total year 2030 final energy demand is 2371 Mtce, and the corresponding figure is 2492 Mtce for the H-I scenario. The reason for the difference in final energy demand between the Business-as-usual and alternative scenarios is that in the H-I scenario residential biomass use has not been substituted for by coal as much as in the other two scenarios; rather, solar energy and biomass use are encouraged under the government policies assumed in the H-I scenario. Despite the relatively small difference in the amount of total final energy demand between the scenarios, the fuel mix does vary considerably among scenarios. As is shown in Table 5-1, biomass and renewable fuel shares total more than 10% by 2030 in the H-I scenario, while the biomass/renewable share is 6.5% in the other scenarios. And in H-E scenario, the share of final demand in 2030 provided by NG is far larger than in the other scenarios. Table 5-1: Final Energy Demand and Fuel Mix in Each Scenario China: Final energy demand in final energy units: demand Units: million tonne of coal equivalent FUEL Base year Fuel Mix BAU 2030 Fuel Mix H-E 2030 Fuel Mix H-I 2030 Fuel Mix Biomass % % % % Coal % % % % Electricity % % % % Heat % % % % NG % % % % Oil products % % % % Other fuels % % % % Renewables % % % % Note: "Fuel Mix" columns do not add to 100% because a small amount of fuel demand is not included in any of the categories shown. 5.2 Overview of Business-as-usual Scenario: Final Energy Demand and Sector Energy Demand The annual final energy demand growth rates for the different fuel types in the Business-as-usual scenario are shown in Table 5-2. Renewable energy use rises rapidly, due to the increasing use of solar water heaters in the residential sector

24 Table 5-2: Final Energy Demand in the BAU Scenario China: Net final energy demand in final energy units: demand Scenario: Business-as-usual Units: million tonne of coal equivalent FUEL CATEGORY Avg Growth Rate Renewables % Other fuels % Oil Products % Natural Gas % Heat % Electricity % Coal, Coke and Peat % Biomass % Sector-level analysis of the Business-as-usual scenario shows that the transport sector energy demand grows the fastest, with an annual growth rate of 4%, and the transport sector s share of total final energy demand has increased from 11.4% in the base year to 20% in 2030, reaching 485 Mtce, or 14.2 billion GJ. Table 5-3: Sector Energy Demand in the BAU Scenario China: Net final energy demand in final energy units: demand Scenario: BAU Reference, Fuel: All Fuels Units: million tonne of coal equivalent SECTOR Avg Annual Growth Rate Households % Industry % Commerce % Transport % Agriculture % Total 1, , , , , , , % 5.3 Overview of Sectoral Energy Demand in All Scenarios Household/Residential sector The residential sector accounts for much of the difference in energy demand and fuel mix between the scenarios. The less-efficient biomass and the more efficient NG energy use, particularly for cooking and heating, combine to make residential sector look different from the other demand sectors

25 The use of solar energy and biomass in the H-I scenario makes total residential final energy demand exceed that in the Business-as-usual and H-E scenarios due to the high energy intensity of biomass stoves. In the H-E scenario, the use of more efficient NG stoves doesn t decrease final energy demand; on the contrary, the demand figure increases relative to that in Business-as-usual scenario, as a combined result of higher energy intensity NG stoves and fuel efficiency. The reason for this is that households that switch to natural gas stoves are generally more affluent, and take advantage of the convenience of natural gas (relative to solid fuels) to adopt a more comfortable lifestyle, including, for example, cooking more complex meals (more different dishes), and using more hot water for bathing. Table 5-4 shows this pattern. Table 5-4: Residential Sector Final Energy Demand by Fuel China: Final energy demand in final energy units: households Fuel: All Fuels Units: million tonne of coal equivalent 1999 BAU2030 H-E2030 H-I2030 Biomass Coal Electricity Heat NG Oil Products Solar Energy Total On the whole, energy demand in rural areas in the Business-as-usual scenario increases slowly, and the share of total residential energy demand accounted for by the rural sub-sector drops as a result of the accelerating urbanization process. In the Business-as-usual scenario, energy demand for urban heating increases the fastest, with home appliances following closely behind, indicating the improvement of living standards, as is shown in Table

26 Table 5-5: Business-as-usual Scenario: Household Sector Final Energy Demand by Activities Annual Growth Rate Rural Total % Cooking and Hot water % Heating % Home Appliances % Lighting % Urban Total % Cooking and Hot water % Heating % Home Appliances % Lighting % Household Total % Industrial sector Final energy demand in the industrial sector reaches million tons of coal equivalent in the Business-as-usual and H-I scenarios by 2030, while in the H-E scenario, due to the expanded use of natural gas in the chemical industry, the energy intensity drops slightly, so that year 2030 overall industrial energy demand decreases to million tons of coal equivalent, as is shown in Figure Mtce BAU Reference High priority-external High priority-internal BAU and H-I Figure 5-1: Final Energy Demand in the Industrial Sector