Future electric power technology choices of Brazil:

Energy Policy 29 (2001) 355}369

Future electric power technology choices of Brazil: a possible con#ict between local pollution and global climate change Roberto Schae!er *, Alexandre Salem Szklo
Energy Planning Program, COPPE/UFRJ, Centro de Tecnologia, Sala C-211, Cidade UniversitaH ria, Ilha do Funda o, C.P. 68565, 21945-970, Rio de Janeiro, RJ, Brazil Received 30 August 2000

Abstract This study aims to identify and discuss the main issues and uncertainties a!ecting electricity demand and supply in Brazil, and their consequent environmental burdens, over the period to the year 2020. It does so in the framework of two policy scenarios to test economic and environmental policy measures against a business as usual projection, which assumes energy policies existing in Brazil today remain in place and that no new major policies are adopted to reduce energy-related GHG emissions. It provides results from an analysis using a linear programming model that simulated scenarios through changes in emissions fees and caps, costs for technologies (including clean energy supplies) and demand side e$ciency, to determine least-cost combinations of power supply technologies that meet projected power demand. Results show that electricity demand in Brazil will continue to grow vigorously over the next two decades, and that the institutional reforms under way in the domestic power sector have the potential to a!ect the future electric power technology choices to meet this rising demand. Also, the analysis suggests that, depending on how priorities are set, some con#ict between local atmospheric pollution problems and global climate change issues may arise.  2001 Elsevier Science Ltd. All rights reserved. Keywords: Electricity supply and demand; Least-cost planning; Atmospheric emissions

1. Introduction Restructuring and deregulation of the power industry world-wide is radically changing the pro"le of investments in the electricity sector of developing countries, with growing participation of private capital. This fact alone, together with the Kyoto Protocol entering into force, may have, in the short to medium terms, profound implications over both the global and local environments. With Annex B countries (38 nations and the European Union) having obligations to comply with the quantitative limitations of greenhouse gas (GHG) emissions, and as such considering the utilization of the #exible mechanisms agreed upon in Kyoto to help achieve their emissions reduction targets and putting pressure on developing nations to adopt voluntary agreements on GHG emissions reductions, developing countries may

* Corresponding author. Tel.: #55-21-562-8760; fax: #55-21-2906626. E-mail address: [email protected] (R. Schae!er).

have to take important energy policy decisions in the short term concerning their future electric power technology choices. In the case of Brazil, of particular interest will be how to better adapt the power generation sector to deal simultaneously with the supply of the country's fastest growing component of energy demand, and issues and uncertainties a!ecting domestic policies with respect to local pollution problems and GHG emissions. With over 90 percent of its electricity generation currently coming from hydroelectric power plants (MME, 1999), the country is now in a process of embarking in a major thermal power generation program. Current reforms in the sector have been designed mainly to reduce government investment in power plant construction, the risk of power shortages, and cut costs by introducing competition in electricity generation (Rosa et al., 1998). From the perspective of private investors, hydroelectricity is seen as being increasingly expensive, controversial and risky (Schae!er et al., 2000a).

0301-4215/01/$ - see front matter  2001 Elsevier Science Ltd. All rights reserved. PII: S 0 3 0 1 - 4 2 1 5 ( 0 0 ) 0 0 1 3 0 - 0

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This study aims to identify and discuss the main issues and uncertainties a!ecting electricity demand and supply in Brazil, and their consequent environmental burdens, both local and global, over the period to the year 2020, should power demand grow at high rates in the period. It does so in the framework of two policy scenarios to test economic and environmental policy measures against a business as usual projection, which assumes energy policies existing in Brazil today remain in place and that no new major policies are adopted to reduce energyrelated GHG emissions. It provides results from an analysis using a linear programming model that simulated scenarios through changes in emissions fees and caps, costs for technologies (including clean energy supplies) and demand side e$ciency, to determine least-cost combinations of power supply technologies that meet projected power demand.

2. Methodology The authors modi"ed and adapted a simple linear programming (LP) model originally developed by researchers from the Battelle Memorial Institute, Paci"c Northwest National Laboratory, USA, to the power sector of China (Chandler et al., 1998), to analyze leastcost power options in Brazil (see the structure of the LP model in Appendix A). This modi"ed and adapted model was already used to forecast Brazil's electric power choices between 1995 and 2015 elsewhere (Schae!er et al., 2000a, b). It allows analysts to capture detailed characteristics of the technologies used in the power sector, an important consideration over the relatively short-time scale considered in this study. Power planners and electric utilities use LP models to determine the types of power plants required to meet least-cost power demand over time while considering pollution emissions caps, energy sources availability and costs, and manufacturing capacity. The LP model "rst calculates levelized costs for each type of power generation option based on capital, fuel, operation and maintenance, and, if applicable, environmental costs. The model then determines, among 17 di!erent types of power plants, the optimal combination of new plants needed to meet, at the minimum cost, given levels of power demand, which is entered exogenously (from outside sources). The model also allows constraints that mimic policy measures and set limits over which values can be obtained.

 LP models are often called `bottom-upa models because they contain detailed information about technology and costs.  Levelized cost analysis, also referred to as lifecycle costing, spreads costs out over the economic lifetime of a plant, allowing direct comparisons of cost per kilowatt-hour of delivered electricity.

Nevertheless, optimization models like this have "nite ability to mirror the reality of consumer behavior. Furthermore, although they provide realistic technical and performance characteristics, they tend to overestimate the impact of the single cheapest alternative. Also, the LP model can neither account for investor preference, such as risk mitigation or "nancial guarantees, nor ensure that energy security and diversity issues are addressed without input from the modeler. Finally, due to a large number of assumptions required by this type of model, not mandatorily its results will materialize under real-life conditions. Still, the model can be a useful tool to weight policy alternatives. Models can help planners analyze alternatives, but not-so-easily-quanti"ed factors must also be considered to calculate the amount of new capacity, electricity generated and the fuel consumed by type of plant in practice. The model divides the country into as many as "ve regions (South, Southeast, Mid-West, North and Northeast) to capture the variation in energy availability, fuel cost, and environmental limitations. Simulation begins with a base year and then determines the amount of new capacity from each type of power plant needed to meet demand over 5-year intervals for the "ve regions. Comparing alternative sources of power generation is done in four steps. First, the analysis develops a framework that includes a baseline projection of power demand and a model to integrate supply and demand to evaluate costs. Second, the model reviews power generation technologies for capital, fuel, operations, and associated environmental costs, and converts these to costs per kilowatt-hour. Third, the analysis tests alternative policies for their impact on average generation costs and especially for changes in greenhouse gas emissions relative to the present and to the baseline. The results indicate increased or reduced economic cost compared to the baseline, along with changes in power plant capacity, utilization, and emissions. The electric generation technologies assessed include natural gas and ethyl alcohol fuel cells, thermo-solar power and wind-power plants, sugar-cane bagasse gasi"cation and burning in aeroderivative turbines, conventional burning of sugar-cane bagasse, pulverized coal combustion, atmospheric circulating #uidized-bed combustion (ACFBC), conventional burning of residual fuel oil or oily wastes, combined cycle for natural gas and lique"ed natural gas, hydropower generation at plants with installed power of over 600 MW (large hydro), hydropower generation at plants with installed power of 30 and 600 MW (medium hydro), hydropower

 Arbitrary value re#ecting the average reference power for the current Brazilian situation of 60 GW installed and 100 hydroelectric power plants in operation.  Covers an appreciable number of fairly heterogeneous plants.

R. Schaewer, A. Salem Szklo / Energy Policy 29 (2001) 355}369

357

Table 1 Electricity generation in Brazil * 1990}1998 (GWh)

1990

1991

1992

1993

1994

1995

1996

1997

1998

Total

222,820

234,366

241,731

251,973

260,041

278,622

291,244

307,986

321,588

Natural gas Steam coal Diesel oil Residual fuel oil Fuelwood Cane bagasse Black liquor Other wastes Cooking gas Other sources Uranium Hydropower

666 2814 1898 2834 622 1794 1144 1690 445 256 2237 206,707

743 3430 1929 2894 571 1875 1357 1901 525 273 1442 217,782

390 3322 2290 3162 790 2066 1800 1443 487 881 1759 223,342

388 3123 2113 3168 864 2022 1672 1662 515 936 442 235,066

479 3393 2203 3270 666 2348 2166 1516 305 970 55 242,704

560 3926 3096 3415 646 2574 2195 1373 304 1065 2519 253,928

973 4374 3112 5101 669 3593 2273 1406 429 1115 2429 265,769

1107 5588 4187 4418 692 4080 2420 1563 402 1298 3169 279,064

5806 4902 5211 4863 687 3979 2526 1947 440 1226 3265 291,371

Source: MME (1999).

generation at plants with installed capacity of under 30 MW (small hydro), nuclear power generation, and energy conservation. Brazil is also expected to make greater use of combined heat and power (CHP, or cogeneration) in the future, so a separate module was created for this alternative. Finally, in terms of the existing plants or those being built, as Brazil is a nation whose power generation is still predominantly hydro-based, it has historically required medium- to long-term planning for its installed capacity. As such, Brazil's power sector planning is still heavily in#uenced by this fact: over the short to medium terms a reasonable number of medium and large hydropower plants should start-up operations, which are already being built, in addition to Angra II nuclear power station, which started operation as of July 2000. These plants planned before 2000 reduce the amount of power to be provided by projects simulated in the LP model.

3. Outlook for the power generation sector Electricity generation in Brazil is predominantly hydro-based. This alternative represents some 91.4 percent of the installed power generation capacity in Brazil for December 1998. The nation's inventoried and estimated hydropower potential reaches some 270 GW, equivalent to 1130 TWh/year of "rm energy (EletrobraH s, 1999). In terms of electricity production (Table 1), hydropower generation accounts for some 97 percent, with thermal

 These plants form part of the Brazilian Expansion Plan based on distributed generation, with low non-recoverable "xed costs (or needing lower investments at the start of the project than other power plants).  Energy conservation is dealt with in the study as an energy `supplya option.

Table 2 Electricity losses in Brazil * 1970}1997 Year

Losses (%)

1970 1980 1990 1998

16.3 13.0 13.1 15.6

Source: EletrobraH s (1999).

power supplementing market services during the dry season for the part of the system that is interconnected, and servicing the remainder of the market in the isolated systems. Thermal power generation is also used for local services in case of power transmission constraints. A heavy reliance on hydropower also results in striking seasonal variation in power availability. Transmission grids thus play an important role in helping balance supply and demand. Finally, it is important to notice the growth in electricity generation from natural gas between 1997 and 1998. Losses due to electrical resistance in the two transmission grid systems remain signi"cant (Table 2). However, three important aspects should be stressed: Brazil is a continent-sized country; the predominance of hydropower generation frequently requires lengthy transmission systems, as power plants are not necessarily located close to consumption centers; and commercial losses are still high due to high levels of theft and illegal connections, which can be explained, in part, by social inequalities (Abbud, 1999). In terms of electricity demand, growth in electricity demand grew much faster than the economy and the energy demand (Fig. 1). The income elasticity of demand for energy (the ratio of growth in energy consumption to

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R. Schaewer, A. Salem Szklo / Energy Policy 29 (2001) 355}369

Fig. 1. Brazilian economic and energy growth, 1980}1998. Source: MME (1999).

growth in the economy) averaged 1.5 between 1980 and 1998, while the elasticity of electricity demand averaged 2.7 in the period. In fact, we shall see the signi"cant growth of electricity consumption, despite Brazilian economic crises. Two major factors explain this latter "gure: E An important share of Brazilian industrial production is based on electric-intensive industries, like aluminum, chemicals and iron & steel. These electricityintensive sectors account for much of Brazil's industrial consumption, being, also, important exporting segments of Brazilian industry (Table 3). E The residential sector consumption grew in this period at large rates, meaning that there was a potential demand not covered by the electricity sector at the beginning of the 1980s. This potential demand remained at the 1990s with marked regional disparities and a growth potential of the electric demand among many regions of the country (Table 4). It is important to notice, also, that electricity consumption, especially in developing nations like Brazil, is relatively inelastic to changes in GDP growth.

4. Power generation scenarios This study analyzes the options for meeting electricity demand in the Brazilian power sector through the year 2020. Meeting this demand at least cost * including environmental impacts * is a topic of great concern for decision makers in the power industry and government. The authors constructed two policy cases to test economic and environmental policy measures against a Baseline Scenario (BASE): Environmental Scenario (ENV) and Environmentally Desirable Technologies Scenario (EDTS). For all scenarios a single discount rate of 15 percent per annum (p.a.) is assumed. Least-cost modeling simulated these scenarios through changes in

 For Brazil as a whole, per capita consumption is close to 1800 kWh, about one-seventh of the average consumption in the United States.

emissions fees and caps, costs for advanced technologies, demand side e$ciency, and clean energy supplies. For the three scenarios established, it was considered power transmission between Argentina and Brazil, and Venezuela and Brazil. Transmissions capacity grows steadily to over 2.7 GW via Argentina and 200 MW via Venezuela. Also, the model includes a cogeneration module that can assess the portion of the electric power market according to a pre-de"ned potential, which could be serviced by an independent producer, provided that it is remunerated at the marginal expansion cost avoided by the system. The estimated remainder market potential for cogeneration just exceeds 10 GW by 2020, about 10 percent of the total system capacity at that time. Levelized costs range from $26.5/MWh for cogeneration using black liquor to $44/MWh for cogeneration using gas turbines. Finally, it is important to notice that most of the power capacity expansion will still rely on long-term planning planned before 2000, since hydropower plants already planned have long construction periods. Thus, plants already in the planning pipeline or under construction are not included in the least-cost calculations, although their costs and future generation counts in the results which follow. Angra III, a nuclear power plant under construction, is also placed outside the least-cost analysis. 4.1. Baseline scenario (Base) In this scenario, it is assumed that current government policies in Brazil concerning the privatization of the power sector will continue, meaning that most of the expansion of the sector will come from power plants with low capital costs. These plants have to be built in a short time, in order to meet Brazilian electricity consumption growth and face the current high risk of electricity shortfalls. Contrary to the situation of thermal power plants in Brazil today, operating with very low capacity factors (meaning that they supplement the base-load hydroelectric plants), the new thermal plants will operate with high-capacity factors. Also, in this scenario, it is assumed that the market does not perceive substantial gains in

 It is possible to undertake two simulations: one ignoring the arrival of the independent producer in Brazil's generation grid, the other excluding the portion of the market to be serviced by CHP.  Some noteworthy projects among those under way at the motorization stage are: the ItaH hydropower plant (1450 MW), scheduled to start up operations in 2000, and the Machadinho hydropower plant (1140 MW), scheduled to start up operations in 2003. Projects for which the entrepreneurs already have concessions/licenses include: the expansion of Itaipu (1400 MW), scheduled for 2001, and the Lajeado hydropower plant (850 MW), scheduled for 2004.  The estimated loss of load probability for the South, Southeast and Mid-West regions in 2000 and 2001 is about 12 percent.

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Table 3 Industrial electricity consumption Share (%)

1970 1980 1990 1998

Major consumers
(TWh)

Major consumers/industrial power consumption

Major consumers/Brazilian power consumption

Industrial consumption/ Brazilian power consumption

6.7 28.0 50.0 69.0

34.1 41.0 44.5 48.3

16.8 22.8 23.0 22.6

49.2 55.6 51.6 46.8

Source: EletrobraH s (1999).
Includes self-production. Major consumers include: aluminum, ferroalloys, cement, soda-chlorine, petrochemicals, pulp and paper.

Table 4 Electricity consumption by region (TWh) * 1970}1998 


North Northeast Southeast South Mid-West Brazil

1970

1980

1990

1997

1998

1970}1980 (% p.a.)

1980}1990 (% p.a.)

1990}1998 (% p.a.)

0.4 3.1 28.4 3.6 0.6 36.1

1.9 14.1 80.7 14.1 3.4 114.2

8.8 31.4 124.0 28.2 8.4 200.8

13.9 42.9 160.9 41.9 13.8 273.4

14.3 46.1 165.7 43.8 14.8 284.7

16.9 16.4 11.0 14.6 18.9 12.2

16.6 8.3 4.4 7.2 9.5 5.8

6.3 4.9 3.7 5.7 7.3 4.5

Source: EletrobraH s (1999).
Do not include self-production.

terms of reduction in the costs of alternative technologies (solar, wind, fuel cells and biomass gasi"cation) and the existing diesel and residual fuel oil-"red plants receiving subsidies to operate in the isolated systems are not discontinued. No restrictions on CO emissions and no  external environmental factors are imposed in this scenario, meaning that the main objective of the Baseline Scenario is to promote the power capacity expansion with private investments and in a short time. Thus, it is assumed a pay-back period of 10 years, re#ecting that investments channeled to generation technologies must be paid o! rapidly. 4.2. Environmental scenario (ENV ) In this scenario, it is assumed that environmental restrictions determine the technologies employed, to a great extent. The costs of alternative energy sources drop substantially over time (technological progress plus government incentives). Also, gains are assumed in conventional technology e$ciencies, such as coal and natural gas (in the case of coal, the new plants might be based on ACFBC).

 Diesel power generation depends on subsidies credited to the Fuel Compensation Account.

Table 5 External environmental factors USD/t of pollutant Sulfur dioxide (SO )  Nitrogen oxide (NO ) V Particulate matter (PM )  Carbon dioxide (CO ) 

3770
2010
1450
120

These factors concern all impacts both direct and indirect associated with atmospheric pollution (health, material, building and forestry impacts).
These values are based on Hamilton and Gilles (1996). This is the upper value of climate change impact considered by ExternE project (1998).

In terms of external environmental factors, the scenario incorporates shadow costs for the estimated environmental damage done by sulfur dioxide (SO ), nitrogen  oxide (NO ), particulates (PM ), and carbon dioxide V  (CO ) (Table 5). These emissions harm human health,  agriculture, and infrastructure in Brazil, as well as degrade the quality of life in other ways. No restriction on CO emissions are imposed in this scenario.  Also, a pay-back period of 10 years for the conventional technologies and a pay-back of 30 years for the alternative and cleanest technologies (solar, wind, fuel

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Table 6 Electricity and #ooded area vs. hydropower plants in Amazonia Power plant

Electricity (MW)

Flooded area (km)

Power density (W/m)


Balbina Samuel TucurumH Belo Monte

250 217 3960 11,000

2346 560 2430 1100

0.10 0.39 1.63 10.00

Source: Rosa et al. (1996).
Theoretically speaking, the lower this "gure, the worse the use made of the #ooded area. Estimated "gures.

cell, hydro plants, biomass gasi"cation) are assumed, meaning that the new technologies will receive some incentives to be implemented. The existing diesel and residual fuel oil plants receiving subsidies to operate in the isolated systems are discontinued by 2005. 4.3. Environmentally desirable technologies scenarios (EDTS) It is assumed that Brazil will install only electric power generation technologies which have no net CO emis sions, no net impact on local or regional air quality, only minor impacts on watersheds or landscapes, and no contribution to toxic waste buildup. This uses more radical assumptions by assuming that even plants planned or under construction that do not meet the stringent environmental constraints of this scenario are shelved. Also, for the least cost optimization, some hydro, nuclear, coal and natural gas-based plants are not considered as technological options. In the case of the hydroelectricity, this scenario assumes that certain hydropower plants have adverse e!ects due to their low power density/ #ooded area ratio. This indicator (W/m reservoir) thus establishes a basis for analysis. Table 6 presents some "gures of Brazilian hydro plants. The national average for power plants in operation hovers around 6.3 W/m. Therefore, it is assumed that only plants with power densities higher than 6.5 W/m might be built, consequently reducing the hydropower potential available under this scenario

 When the dam of a hydropower plant is built, the submerged biomass undergoes a process of decomposition, emitting greenhouse gases, particularly carbon dioxide and methane (produced by aerobic and anaerobic decomposition of submerged organic materials, respectively), and nitrous oxide, which has been measured at some hydropower projects studied in Brazil (Santos, 2000; Rosa and Schae!er, 1994, 1995). In general, the lower the power density of the hydroelectric reservoir the higher the level of carbon emissions per unit of electricity produced.

Finally, in this scenario, a new technology * the alcohol-based fuel cell * is introduced. Also, a pay-back period of 10 years for the conventional technologies and a pay-back period of 30 years for the alternative and cleanest technologies (solar, wind, fuel cell, hydro plants, biomass gasi"cation) are assumed, meaning that the new technologies will receive some incentives to be implemented. The existing diesel and residual fuel oil plants receiving subsidies to operate in the isolated systems are discontinued by 2005. Appendix B presents the technological evolution of the electric power supply options considered in this study. Appendix C presents the estimated energy source prices.

5. The e7cient use of electricity This analysis introduces electricity conservation as an alternative type of power supply. This is because, the electricity conservation potential in the country is extremely high, as shown by some recent studies (Almeida et al., 2000). There is even a new regulation in the country that obliges recently privatized power distribution companies to invest at least 1 percent of their total revenues (of which at least one-fourth of that on end-uses) on electricity e$ciency, which may boost electricity conservation in the near future. In the study, levelized costs for e$ciency and conservation are assumed as $30/MWh, based on Geller (1991). Although some case studies have even shown e$ciency improvements with negative costs, this modeling exercise assumes expenditures to overcome non-market barriers in implementing the savings (Geller et al., 1998). Electricity e$ciency savings are assumed in all scenarios. For the Baseline Scenario, it is assumed that 10 percent of the electricity consumption in 2020 could be reduced by energy e$ciency measures. For the two other scenarios, this potential increases to 20 percent, meaning that market barriers could be overcome more easily, if appropriate measures are taken. In all three scenarios e$ciency gains from the industrial sector account for half of the total electricity savings, with the remainder coming from the residential and services sectors (Schae!er et al., 1998). Given the uncertainties associated with these assumptions, a sensitivity analysis with the savings potentials is also performed.

Table 7 GDP growth rate (% p.a.) 2000}2005

2005}2010

2010}2015

2015}2020

2000}2020

4.7

4.9

5.6

7.0

5.5

R. Schaewer, A. Salem Szklo / Energy Policy 29 (2001) 355}369

6. Power demand forecasts Power demand is forecast based on economic growth rates and on the GDP-elasticity of power demand. The electric power market is projected for a high GDP growth scenario so as to identify the electric power choices available to meet high-growth rates in electricity demand in Brazil and, as such, call to the attention the advantages and disadvantages, with respect to the environment, of di!erent kinds of power generation technologies available in the country in the short to medium terms. A more likely, medium growth scenario would have not explicited all the constraints imposed to the country's power sector should the power demand grow at high rates * as it has happened historically for almost three decades, averaging 7.7 percent p.a. from 1970 to 1998 (MME, 1999), for example if some of the many still isolated regions of the country are connected to the national grid, or also if part of the great disparities between per capita electricity consumption of the di!erent regions of the country is reduced over time. The GDP growth adopted in this study, based on recent projections made for the Brazilian economy, is presented in Table 7. For the "rst two periods (2000}2005 and 2005}2010), GDP growth rates are adapted from the high-growth scenario for Scenarios 2 and 3 of the EletrobraH s Expansion Plan 1997/2008 (EletrobraH s, 1998). For the "nal two periods (2010}2015 and 2015}2020), GDP growth rates are adapted from the high-growth scenario for the economy drawn up by the Institute for Applied Economic Research (IPEA), within a context of political and "nancial stability for the country in the years to come (IPEA, 1997). Projected growth for the power market takes into account the GDP-elasticity of electricity consumption, with this-elasticity dropping within the time horizon considered (Table 8). The results show very di!erent development rates for the electric power market in Brazil (Table 9). The total average annual growth rates of these forecasts are higher than the 4.2 percent annual growth forecast for the electricity consumption of South America between 1995 and 2020, according to some recent studies (EIA, 1999). Nevertheless, it is almost equal to the rate estimated by EletrobraH s for the 1997}2008 period in a recent forecast (EletrobraH s, 1998).

 Use of the elasticity in electric power consumption/GDP for the market forecast is somewhat problematical, as there is an inertial component in electric power consumption that prompts growth even at times of crisis or low economic growth. It should thus be recalled that, in Brazil, there is still a reasonable percentage of homes not serviced by the electricity network, with repressed demand for household appliances engendering high-consumption growth rates for the residential sector, regardless of the variation in the GDP.

361

Table 8 GDP-elasticity of electricity consumption Region of the country

2000}2005 2005}2010 2010}2020

South/Southeast/Mid-West North/Northeast North isolated systems

1.16 1.57 2.73

0.87 1.14 1.91

0.87 1.14 1.91

7. Atmospheric emissions from power generation Electric power generation can produce environmental impacts at both the local level, related to certain gas emissions and normally circumscribed to speci"c regions where those direct and indirect e!ects can be noticed, and the global level, related to GHG emissions. Some gases have negative impacts at both levels, such as nitrogen oxides that, depending on their dispersion in the atmosphere, react forming nitric acid * which has a local e!ect, causing, in special, acid rain * or tropospheric ozone, a GHG gas (Ravishankara, 1997). Other gases have positive global e!ects and negative local e!ects; sulfur oxides, for example, form, during their dispersion in the atmosphere, sulfur aerosols, which, because of their negative radiative e!ect, have a cooling e!ect on the global climate (Charlson, 1997), but, at the same time, are very damaging to the local environment. The acid rain related to the precipitation of sulfur aerosols can result in serious damages to human health (Dockery et al., 1992), fauna, #ora and human-made materials in general (Gregory et al., 1996). Finally, other pollutants, such as CO , have global e!ects only, being the local impacts of  their emissions nil. Two distinctions are important to be made between global and local environmental impacts: E due to their distinct spatial, and some times temporal, scales, the level of concern and the interest groups involved with environmental issues change both qualitatively and quantitatively as the analysis moves from the local to the global level; E a direct relationship between local and global environmental problems not necessarily does hold. For instance, while CO emissions from power generation  are mostly a function of the carbon content of the energy source deployed, atmospheric emissions of other pollutants, such as sulfur oxides and nitrogen oxides, depend very much as well on the burning technology, the emissions control technology and on atmospheric dispersion conditions. In fact, there exists a series of factors that a!ect the atmospheric emissions of power generation and their concentrations in the atmosphere and those factors are not necessarily correlated.

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Table 9 Electric power market plus distribution losses * 2000}2020 (TWh) Region of the country

2000

2005

2010

2015

2020

S/SE/MW N/NE North isolated systems Total Brazil

239.1 59.7 5.7 304.6

310.8 83.9 9.8 404.5

383.7 109.9 14.9 508.4

487.9 149.2 23.8 660.9

620.5 202.7 38.0 861.2

% p.a. (2000}2020) 4.9 6.3 9.9 5.3

Losses due to electrical resistance in the two transmission grid systems decreases from 10% in 2000 to 5% in 2020.

Therefore, it is interesting to investigate to what extent possible restrictions on atmospheric emissions of GHG, mainly CO , can a!ect the emission patterns of other air  pollutants of local relevance, due to changes in the power generation mixes decided based on least-cost planning. The speci"c air emissions of di!erent power generation technologies considered in this study are shown in Table 10.

8. Results Two factors seem to be of far most importance in this modeling exercise (Table 11). First, the institutional reforms underway in the power sector of Brazil show to have a very strong in#uence on how electricity demand is met and the resulting emissions. Carbon emissions more than quintuple in the Baseline Scenario, although remaining low, in absolute terms, when compared to emissions of other countries with power sectors of comparable size. In the absence of alternative policies, future electric power technology choices shift rapidly from hydroelectricity to combined-cycle natural gas plants. Contrary to the current situation in the country, with fossil-fueled power plants operating primarily as peaking units, future thermal power plants start to operate in a baseload con"guration. Also, #uidized-bed coal plants are installed in the Baseline Scenario, with less atmospheric emissions than traditional pulverized coal plants. Nevertheless, even in this scenario hydropower still plays a dominant role in the total installed capacity in 2020. The second factor has to do with the sensitivity of the LP model simulations to variations in the potential for electricity conservation. In fact, all savings potential estimated for the various scenarios, all of them with a highcapacity factor, have been `installeda in its totality in the simulations. Electricity conservation through increased e$ciency o!sets the needs for new supply, specially in the two last scenarios, where higher "gures are proposed for the savings potential. Energy e$ciency also reduces the environmental burden associated with electricity production and transmission (most likely, in a business as usual scenario, via natural gas combined cycle plants) without compromising the quality of the services demanded by end users.

When environmental externalities are considered, the least-cost mix of electric power generation technologies changes in other ways. Natural gas-fueled fuel cells, biomass-"red thermal plants and wind power plants might play a larger role in Brazil's future electric power technology choices if full account for the costs of the environmental impacts are made, or if government incentives for developing advanced energy technologies are provided. The "rst technology is used as a substitute for gas-"red thermal plants in the ENV scenario, and the two latter technologies play a larger role in the EDTS scenario. In all three scenarios, on the other hand, cogeneration plays an important role in the least-cost power solution, specially cogeneration units installed in re"neries, pulp and paper production plants and iron and steel industry. With respect to the total full costs, these do not include externalities, be they environmental externalities be they "nancial subsidies provided by the state. According to the results, the BASE scenario has both the higher total full cost and the higher environmental externalities. This is due, mostly, to the lower savings potential accounted for in this scenario by the energy-e$ciency programs. Nevertheless, this higher total full cost "gure for the BASE scenario does not mean that it is a less probable scenario for the power sector. On the contrary, from the standpoint of the private investor, technologies with lower investment (up-front) costs are almost always preferable, even if, in the long term, in a total full-cycle cost accounting, they are compared to least-cost technologies. The BASE scenario has a total cost similar to the total cost of the EDTS scenario, which costs round US$ 20 billion more than the ENV scenario. CO emissions in  2020 from the ENV scenario are still extremely low (66 percent lower than the CO emissions of the power  sector in 2000) by any standard. Thus, the CO emissions  reduction promoted by the EDTS scenario in 2020 is not very cost-e!ective, meaning that, in the case of the Brazilian power sector, including environmental externalities in the least-cost planning is better than restricting CO emissions exogenously by any kind of  command and control measures. Also, due to a greater use of biomass-"red plants in the EDTS scenario, atmospheric emissions that have local impacts increase in this scenario compared to emissions in the ENV scenario. Thus, the carbon elimination

R. Schaewer, A. Salem Szklo / Energy Policy 29 (2001) 355}369 Table 10 Speci"c emissions Pulverized Brazilian coal

Imported coal}ACFBC

Diesel-engine

Residual fuel oil}Rankine cycle

Natural gas}CCGT

Natural gas}fuel cell

Sugar cane bagasse} Rankine cycle

Sugar cane bagasse}BIG/STIG

Ethanol}fuel cell

Carbon (tC/TJ) Sulfur content (%) RO (g/kWh) V NO (g/kWh) V Carbon (tC/TJ) Sulfur content (%) RO (g/kWh) V NO (g/kWh) V Carbon (tC/TJ) Sulfur content
(%) Baseline scenario Other scenarios RO (g/kWh) V NO (g/kWh) V Carbon (tC/TJ) Sulfur content (%) RO (g/kWh) V NO (g/kWh) V Carbon (tC/TJ) Sulfur content (%) RO (g/kWh) V NO (g/kWh) V Carbon (tC/TJ) Sulfur content (%) RO (g/kWh) V NO (g/kWh) V Carbon (tC/TJ) Sulfur content (%) RO (g/kWh) V Baseline scenario * 2000}2005 Baseline scenario * 2005}2015 Other scenarios * 2000}2015 NO (g/kWh) V Carbon (tC/TJ) Sulfur content (%) RO (g/kWh) V NO (g/kWh) V Carbon (tC/TJ) Sulfur content (%) RO (g/kWh) V NO (g/kWh) V

25.7 1.7 0.35 2.1 25.3 0.8 0.01 0.24 20.0 1.0 0.3 0.032 4.68 20.9 1.0 0.032 0.72 15.2 Nil Nil 0.68 15.2 Nil Nil 0.01 Nil 0.2

363

scenario (the EDTS scenario) forces the use of some power-generation technologies that, although are bene"cial for the global environment, clearly have local impacts. In other words, if Brazil, for some reason, agrees to some binding commitments with respect to reducing carbon emissions from its power sector in the near to medium terms, gains for the global environment may not be able to o!set losses for the local domestic environment. Add to that the high level of government subsidies necessary to implement the EDTS scenario, more than twice as much the total externalities of each one of the two other scenarios. This high "gure obviously contradicts the current restructuring of the power sector in Brazil, which aims at modifying the role played by government in the sector from an entrepreneur to a regulator. Currently, Brazil's electric power sector, as is, does not emit large amounts of atmospheric pollutants, and this situation will not change much in the decades to come. As such, stringent CO emissions constrains imposed on  the country's power sector will most likely impact negatively the local environment. The eminently hydroelectric nature of Brazil's electricity sector guarantees that, over the short to medium terms, GHG emissions from the country's power sector, particularly CO emissions, will  continue to be relatively low.

0.80 0.48 0.16 0.32 Nil 0.2 Nil 0.48 Nil 0.2 Nil 0.05

Although carbon (in the form of both CO and CH ) is also emitted   from hydroelectric reservoirs with the degradation of #ooded biomass (Rosa and Schae!er, 1994, 1995), this is not being taken under consideration in this paper due to a lack of reliable "gures available for use. Additionally, the amount of these emissions seem to be low compared to the emissions from fossil-fueled power plants (Santos, 2000).
The "gure of 1.0 percent corresponds to a heavy diesel fuel already used in power generation; the "gure of 0.3 percent corresponds to a light diesel fuel. Sulfur's retention in bottom ashes is almost nil for liquid fuels. Net carbon emissions. In the case of renewable biomass, sugar cane bagasse and ethyl alcohol, these emissions are considered as nil (Schechtman et al., 1998). For the CEST system (condensation-extraction steam turbine), the emission intensity and the particulate matter's composition are extremely variable due to sugar-cane bagasse properties and the boiler's operation conditions. Three systems of control were analyzed: cyclones designed for two steps with low inlet gas #ow; high-performance cyclones with high-pressure drop; scrubbers with high-pressure drop (Cortez, 1997).

9. Sensitivity analysis Variations in the potential for electricity conservation across the di!erent scenarios a!ect dramatically the results of the simulations (Table 12). In the BASE scenario, the reduction in the savings potential in 2020 from 10 percent of the market that year to only 5 percent means that more ACFBC plants are installed, resulting in higher CO emissions.  In the case of the ENV scenario, the reduction in the savings potential from 20 percent of the market to 10 percent implies that the additional electricity demand * i.e. the demand previously `supplieda by the energye$ciency savings * is met by new hydroelectric power plants, mostly medium-size (30}600 MW) hydroelectric plants, and gas-"red thermal plants. This increases the total CO emissions and the total full cost of the scen ario, but still keeps its cost lower than the total full cost of the BASE scenario. The EDTS scenario also shows a high sensitivity to the level of electricity savings potential considered. A reduction, in 2020, for the savings potential from 20 to 10 percent of the market that year increases substantially the needs for new expensive power plants, mostly biomass-gasi"ed-"red plants and wind power plants. Thus, the total full cost of the EDTS scenario in this simulation is 16 percent higher than in the original simulation. Also, US$ 63 billion of subsidies are necessary to guarantee the

364

R. Schaewer, A. Salem Szklo / Energy Policy 29 (2001) 355}369

Table 11 Final results Installed capacity (GW)

2000

BASE

ENV

EDTS

Pulverised coal ACFBC Fuel oil-"red plants and diesel engines Biomass Large and medium hydro Small hydro E$ciency program savings Natural gas-"red thermal generation Liqui"ed natural gas-"red thermal generation Nuclear Wind Fuel cell Cogeneration Transmission (Argentina}Brazil/Venezuela}Brazil) Total (wo/conservation and transmission)

1.4 * 3.2 1.0 61.0
* * * * 2.0 * * 1.8 * 69.1

1.4 1.9 3.2 5.3 93.0 0.5 18.2 12.2 4.7 2.6 0.4 0.0 11.0 2.3 136.1

1.4 0.0 1.7 5.3 92.2 0.5 36.8 1.0 0.0 2.6 1.7 11.9 9.2 2.3 127.5

0.0 0.0 0.0 10.7 84.9 0.7 36.8 0.0 0.0 2.6 11.0 0.0 8.7 2.3 118.6

BASE

ENV

EDTS

14.8 25.8 59.4

13.1 22.5 64.4

12.2 6.3 81.5

BASE

ENV

EDTS

215.7 20.8 78.9 116.0 39.2 39.2 0.0

195.2 17.5 73.3 104.4 35.6 14.4 21.2

213.3 15.6 38.7 159.0 100.8 12.5 88.3

BASE

ENV

EDTS

22.3 524.0 148.0 81.9

2.8 80.9 29.4 28.8

0.0 106.0 68.5 44.1

Electric generation (%) Cogeneration Planned before 2000 New additions

* * *

Cumulative costs (10 US$) Total (externalities excluded) Cogeneration Planned before 2000 New additions Externalities Environmental externalities Financial subsidies

* * * * * * *

Emissions CO (MtC)  SO (kt)  NO (kt) 6 PM (kt) 

4.2 206.0 28.8 14.9

Estimated values.
This "gure includes small, medium and large hydro plants.

feasibility of this scenario. Finally, the atmospheric emissions of pollutants with local impacts are much higher in the EDTS scenario than those projected for the ENV scenario, meaning that a carbon elimination scenario applied to Brazil's electric power sector implies in higher burdens for the local environment. These results clearly show the important role electricity conservation programs can play in the expansion of the power sector in Brazil in the future. Electricity savings can lower the full costs of the expansion of the sector and, at the same time, lower atmospheric emissions with no side e!ects. Electricity conservation is the most coste!ective way of both reducing generation costs and reducing environmental impacts at the local and global environments alike, reducing the needs of government subsidies for promoting clean technologies.

The comparison between the two last scenarios reveals that, even adopting the high environmental externality factors presented in Table 5, specially those for CO  emissions, the total full cost of the ENV scenario is still  The adopted value of US$ 120/t C, for example, is much higher than the US$ 28/t C estimated by Baron (1999) for carbon emissions trading between Annex B and non-Annex B countries. But even if this latter value were used in the simulations performed, results would not have changed signi"cantly. For example, for 2020, the new carbon cost would reduce the externality cost of the ENV scenario only slightly. The reduction in the cost per ton of carbon is compensated, partially, by an increase in carbon emissions due to a higher participation of natural gas-"red thermal plants in the total generation and a lower participation of large and medium hydroelectric plants. By de"nition, a carbon cost reduction would have no e!ect on the costs of the EDTS scenario and, as such, the ENV scenario continues to be cheaper than the EDTS scenario.

R. Schaewer, A. Salem Szklo / Energy Policy 29 (2001) 355}369

365

Table 12 Figures for 2020 * sensitivity analysis Installed capacity (GW)

2000

BASE

ENV

EDTS

Pulverised Coal ACFBC Fuel oil-"red plants and diesel engines Biomass Large and medium hydro Small hydro E$ciency program savings 2 Natural gas-"red thermal generation Liqui"ed natural gas-"red thermal generation Nuclear Wind BIG/STIG Fuel cell Cogeneration Transmission (Argentina}Brazil/Venezuela}Brazil) Total (wo/conservation and transmission)

1.4 * 3.2 1.0 61.0
* * * * 2.0 * * * 1.8 * 69.1

1.4 8.9 3.2 5.3 96.3 0.5 9.1 12.2 4.7 2.6 0.4 0.0 0.0 11.8 2.3 149.7

1.4 0.0 1.7 5.3 106.8 0.5 18.4 3.8 0.0 2.6 1.7 0.0 8.3 9.5 2.3 141.6

0.0 0.0 0.0 14.4 89.7 0.6 18.6 0.0 0.0 2.6 28.4 7.4 0.0 8.7 2.3 151.9

BASE

ENV

EDTS

226.5 23.2 78.9 124.4 47.5 47.5 0.0

210.4 17.8 73.3 119.3 75.9 21.2 54.7

248.4 14.3 38.7 195.4 76.2 13.2 63.0

BASE

ENV

EDTS

38.9 805.0 165.0 94.0

11.5 80.9 45.4 28.8

0.0 144.1 57.2 64.6

Cumulative costs (10 US$) Total (wo/ externalities) Cogeneration Planned before 2000 New additions Externalities Environmental Externalities Financial subsidies

* * * * * * *

Emissions CO (MtC)  SO (kt)  NO (kt) V PM (kt) 

4.2 206.0 28.8 14.9

Estimated values.
This "gure includes small, medium and large hydro plants.

lower than the total full cost of the EDTS scenario. In other words, a possible commitment to reduce CO  emissions in Brazil's power sector seems less cost-e!ective than the adoption of environmental taxes.

10. Conclusion This paper has identi"ed and discussed some of the main issues and uncertainties a!ecting electricity demand and supply in Brazil, and their corresponding environmental implications, up to year 2020. Assuming a high growth rate for electricity consumption in the country in the next two decades, this analysis suggests that, in the case of Brazil, at least, some con#ict between local atmospheric pollution problems and global climate change may arise if the country decides to adopt binding commitments with respect to GHG emissions. With over 90 percent of its electricity market currently being supplied with hydroelectricity, institutional re-

forms under way will most likely direct a growing share of the new investments in the sector to fossil-fueled power plants, with all environmental implications, both local and global, that such a move may imply. When environmental externalities are considered, however, the high costs to the environment of fossilfueled technologies may convince the government to act to facilitate, through some kind of "scal mechanisms, for example, the adoption, by the power sector, of environmentally desirable, cleaner generation technologies. Add to that not only that the Kyoto agreement allows the Annex B countries credit for GHG emissions reductions through, for example, climate mitigation projects with developing countries, but that the Brazilian government may decide, sometime in the future, to consider some kind of voluntary agreement with respect to GHG emissions reduction. Nevertheless, in such a case, with the sole exception of electricity conservation and cogeneration technologies, a con#ict of interests may arise because some of the most environmentally-friendly

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power generation technologies for the global environment, such as biomass-"red of even some hydroelectric power plants, may not be so for the local environment (due to SO , NO and particulate emissions in former  V case, and #ooded areas and their consequences in the latter). And vice versa, some of the most environmentally friendly power generation technologies for the local environment, such as natural gas "red-thermal plants and natural gas fueled-fuel cells may not be so for the global environment (due to their low, but existing, carbon emissions). This rather curious situation lead us to re#ect, and to suggest further studies, on the increasingly important subjects of local environmental priorities, global environmental matters, intergeneration responsibilities and equity issues.

conditions. Still, the conclusions of this study can be a useful tool for policy purposes.

Acknowledgements We thank Joa o Carlos de Souza Marques for some information and assistance provided in early stages of this paper. We are also grateful to the "nancial support that was provided, in part, by CNPq, Ministry of Science and Technology, Brazil, to develop this work. The views expressed in this article are solely of the authors.

Appendix A. The least-cost model

Appendix B Finally, it is important to stress that, due to a large number of assumptions made along this work, not mandatorily all the results will materialize under real life

The technology and economic characteristics are given in Table 13.

Table 13 Technology and economic characteristics 


Fuel cell

2005

2010

2015

2020

Capital cost ($/kW) Capacity factor (%) O&M ($/MWh)

1400 (1 and 2)

1250 (1 and 2)

85 (1 and 2)

85 (1) 90 (2) 5.5 (1 and 2)

E$ciency (%)

45 (1 and 2)

1200 (1) 1100 (2) 85 (1) 92 (2) 5.5 (1) 4.5 (2) 50 (1) 55 (2)

1000 (1) 900 (2) 85 (1) 95 (2) 5.0 (1) 4.0 (2) 53 (1) 60 (2 and 3)

6.5 (1 and 2)

45 (1) 53 (2)

R. Schaewer, A. Salem Szklo / Energy Policy 29 (2001) 355}369

367

Table 13. (Continued )

¹hermo-solar generation

Wind generation

Biomass generation rankine cycle

Biomass integrated gasi"cation

Pulverized coal "red-plant

2005

2010

2015

2020

3500 (1 and 2)

3200 (1 and 2)

3000 (1 and 2)

25 (1 and 2)

25 (1 and 2)

25 (1 and 2)

3000(1) 2500(2) 25 (1 and 2)

15 (1 and 2)

13 (1 and 2)

10 (1 and 2)

10 (1 and 2)

Capital cost ($/kW) Capacity factor (%) O&M ($/MWh)

1000 (1 and 2)

950 (1 and 2)

900 (1 and 2)

800 (1 and 2)

30 (1 and 2)

30 (1 and 2)

35 (1 and 2)

35 (1 and 2)

10 (1 and 2)

10 (1 and 2)

10 (1 and 2)

10 (1 and 2)

Capital cost

1100 (1)

1100 (1)

1100 (1)

1100 (1)

(US$/kW) Capacity factor (%) O&M ($/MWh) E$ciency (%) PM removal (%)

1050 (2) 80 (1 and 2)

1000 (2) 80 (1 and 2)

950 (2) 80 (1 and 2)

900 (2) 80 (1 and 2)

10 25 90 98

10 25 94 98

10 25 94 98

10 (1 and 2) 25 (1 and 2) 98 (1 and 2)

Capital cost ($/kW) Capacity factor (%) O&M ($/MWh)

Residual oil-"red plants

Gas turbines

(1 and 2) (1 and 2) (1) (2)

2200 (1)

2100 (1)

2000 (1)

1900 (1)

($/kW) Capacity factor (%) O&M ($/MWh) E$ciency (%)

2100 (2) 80 (1 and 2)

2000 (2) 80 (1 and 2)

1700 (2) 80 (1 and 2)

1500 (2) 80 (1 and 2)

12 (1 and 2) 35 (1 and 2)

12 (1 and 2) 35 (1 and 2)

12 (1 and 2) 35 (1 and 2)

12 (1 and 2) 35 (1 and 2)

Capital cost (US$/kW) Capacity factor (%) O&M ($/MWh)

PM removal (%)

1.040 (1) 1190 (2) 80 (1) 85 (2) 9.0 (1) 14.0 (2) 37 (1) 36 (2) 99.5 (1 and 2)

1.040 (1) 1190 (2) 80 (1) 85 (2) 9.0 (1) 14.0 (2) 37 (1) 36 (2) 99.5 (1 and 2)

1.040 (1) 1190 (2) 80 (1) 85 (2) 9.0 (1) 14.0 (2) 37 (1) 36 (2) 99.5 (1 and 2)

1.040 (1) 1190 (2) 80 (1) 85 (2) 9.0 (1) 14.0 (2) 37 (1) 36 (2) 99.5 (1 and 2)

Capital cost

1200 (1 and 2)

1150 (1 and 2)

1100 (1 and 2)

1050 (1 and 2)

85 (1, 2)

85 (1, 2)

85 (1, 2)

85 (1, 2)

10 (1 and 2) 39 (1 and 2) 99.9 (1 and 2)

10 (1 and 2) 39 (1 and 2) 99.9 (1 and 2)

10 (1 and 2) 39 (1 and 2) 99.9 (1 and 2)

10 (1 and 2) 39 (1, 2) 99.9 (1 and 2)

Capital cost (US$/kW) Capacity factor (%) O&M ($/MWh) E$ciency (%)

1000 (1 and 2)

1000 (1 and 2)

1000 (1 and 2)

1000 (1 and 2)

30 (1 and 2)

30 (1 and 2)

30 (1 and 2)

30 (1 and 2)

8 (1 and 2) 30 (1 and 2)

8 (1 and 2) 30 (1 and 2)

8 (1 and 2) 30 (1 and 2)

8 (1 and 2) 30 (1 and 2)

Capital cost (US$/kW) Capacity factor (%) O&M ($/MWh) E$ciency (%)

1070 (1 and 2)

1070 (1 and 2)

1070 (1 and 2)

1070 (1 and 2)

20 (1 and 2)

20 (1 and 2)

20 (1 and 2)

20 (1 and 2)

11 (1 and 2) 30 (1 and 2)

11 (1 and 2) 30 (1 and 2)

11 (1 and 2) 30 (1 and 2)

11 (1 and 2) 30 (1 and 2)

Capital cost (US$/kW) Capacity factor (%) O&M ($/MWh) E$ciency (%)

495 (1 and 2)

470 (1) 460 (2) 92 (1) 89 (2) 7 (1 and 2) 50 (1 and 2)

450 (1) 420 (2) 92 (1) 89 (2) 7 (1 and 2) 50 (1 and 2)

420 (1) 380 (2) 92 (1) 89 (2) 7 (1 and 2) 50 (1 and 2)

(US$/kW) Capacity factor (%) O&M ($/MWh) E$ciency (%) PM removal (%) Diesel engines

(1 and 2) (1 and 2) (1) (2)

Capital cost

E$ciency (%)

Advanced coal power generation * (ACFBC)

(1 and 2) (1 and 2) (1) (2)

92 (1) 89 (2) 7 (1 and 2) 50 (1 and 2)

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R. Schaewer, A. Salem Szklo / Energy Policy 29 (2001) 355}369

Table 13. (Continued)

Hydroelectricity

Capital cost (US$/kW) Capacity factor (%) O&M ($/MWh)

Construction period (year) Nuclear generation

Capital cost (US$/kW) Capacity factor (%) O&M "x ($/kW) O&M variable ($/MWh) E$ciency (%) Construction period (year)

2005

2010

2015

2020

1570 (3) 1230 (4) 815 (5) 63.5 (3) 55.0 (4) 53.5 (5) 4.41 (3) 1.54 (4) 1.29 (5) 2 (3) 4 (4) 7 (5)

1570 (3) 1230 (4) 815 (5) 63.5 (3) 55.0 (4) 53.5 (5) 4.41 (3) 1.54 (4) 1.29 (5) 2 (3) 4 (4) 7 (5)

1570 (3) 1230 (4) 815 (5) 63.5 (3) 55.0 (4) 53.5 (5) 4.41 (3) 1.54 (4) 1.29 (5) 2 (3) 4 (4) 7 (5)

1570 (3) 1230 (4) 815 (5) 63.5 (3) 55.0 (4) 53.5 (5) 4.41 (3) 1.54 (4) 1.29 (5) 2 (3) 4 (4) 7 (5)

1600 (1 and 2)

1600 (1 and 2)

1570 (1 and 2)

1570 (1 and 2)

75 (1 and 2)

75 (1 and 2)

75 (1 and 2)

75 (1 and 2)

56.3 (1 and 2) 0.41 (1 and 2)

56.3 (1 and 2) 0.41 (1 and 2)

56.3 (1 and 2) 0.41 (1 and 2)

56.3 (1 and 2) 0.41 (1 and 2)

33 (1 and 2) 5 (1 and 2)

33 (1 and 2) 5 (1 and 2)

33 (1 and 2) 5 (1 and 2)

33 (1 and 2) 5 (1 and 2)

Energy conservation

Levelized cost (US$/MWh)

30

30

30

30

Transmission

Capital cost (US$/kW/kkm) Capacity Factor (%) Lost (%)

180 (1 and 2)

200 (1 and 2)

200 (1 and 2)

220 (1 and 2)

60 (1 and 2)

60 (1 and 2)

60 (1 and 2)

60 (1 and 2)

5 (1 and 2)

5 (1 and 2)

5 (1 and 2)

5 (1 and 2)

Keys: (1) Baseline scenario; (2) Other scenarios; (3) Small hydro; (4) Medium hydro; (5) Large hydro.
Source: Adapted from Schae!er et al. (2000b).

Appendix C

References

The estimated energy source prices are given in Table 14.

Abbud, A., 1999. Desvio Informal * Uma AnaH lise das Perdas Comerciais de Energia EleH trica no Setor Informal da Economia e em Comunidades Faveladas no Brazil. M. Sc. Thesis. Federal University of Rio de Janeiro, Rio de Janeiro, Brazil. Almeida, M.A., Schae!er, R., Rovere, E.L., 2000. The potential of electricity conservation and peak load reduction in the residential sector of Brazil. Energy, submitted. Baron, R., 1999. Emission trading and the clean development mechanism: resource transfers, project costs and investment incentives. IEA, Bonn. Chandler, W., Guo, Y., Logan, J., Shi, Y., Zhou, D., 1998. China's electric power options: an analysis of economic and environmental costs. Technical Report, Pew Center on Global Climate Change, Arlington, VA. Charlson, R., 1997. Direct climate forcing by anthropogenic sulfate aerosol: the Arrhenius Paradigm a century later. Ambio 26(1), 24}31. Cortez, L., 1997. Sistemas EnergeH ticos * Tecnologias de Conversa o EnergeH tica da Biomassa. EDUA/EFEI, Manaus, Brazil. Dockery, D., Schwartz, J., Spengler, J., 1992. Air pollution and daily mortality: associations with particulates and acid aerosols. Environmental Research 59, 362}373. EIA, 1999. International Energy Annual 1999. Energy Information Administration, Washington, DC. EletrobraH s, 1998. Plano Decenal de Expansa o * 1998}2007. EletrobraH s, Rio de Janeiro, Brazil.

Table 14 Estimated energy source prices

Brazilian coal (US$/t) (1) Imported coal (US$/t) (2) Natural gas (US$/GJ) (3) LNG (US$/GJ) Uranium (US$/MWh) Diesel oil (US$/t) (4) Residual fuel oil (US$/t) (4) Ethanol * S/SE/MW (US$/m) Ethanol * N/NE (US$/m) Bagasse (US$/t) (5)

2000

2020

23 48 2.5 4.3 8.2 442.1 148.7 280 560 7

23 48 2.5 4.3 8.2 649.1 163.8 280 560 7

Notes: (1) Based on prices for coal from Candiota and Santa Catarina mines. (2) price of Colombian coal increased by the average transportation cost. (3) take-or-pay contract for Bolivia-Brazil pipeline. (4) US$(1997) 22.0/barrel of oil in 2020 according to Tolmasquim et al. (1999); (5) price based on Zylbersztajn and Coelho (1993) and used only in the EDTS scenario.

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