nexo agua energía en brasil
TRANSCRIPT
Nexo Agua Energía en Brasil
Prof. Roberto SchaefferFederal University of Rio de Janeiro
Pontificia Universidad Católica de Chile
Jueves 24 de noviembre de 2011
How presentation is organized
• RE and climate change: The water – energy nexus
• Key questions in the relationship RE and climate change
• Hydro vs climate change
• Biofuels vs climate change
• Adaptation
• Conclusions
Introduction
• RE will play a fundamental role in a future low-carbon
emissions economy (IPCC SRREN)
Introduction
• Mainly because technical potentials do not seem to
constrain future deployments of RE (IPCC SRREN)
Introduction
• However, because of its dependence on climate
conditions, RE is most vulnerable to climate change
Energy Sector Climate Variables Related Impacts
Thermoelectric Power Generation (natural gas, coal and nuclear)
air/water temperature cooling water quantity and quality
air/water temperature, wind and humiditycooling efficiency and turbine operational
efficiency
extreme weather events
erosion in surface mining
disruptions of off-shore extraction
Oil and Gas
extreme weather events disruptions of off-shore extraction
extreme weather events, air/water temperature, flooding
disruptions of on-shore extraction
extreme weather events, flooding, air temperature
disruptions of production transfer and transport
extreme weather events disruption of import operations
flooding, extreme weather events and air/water temperature
downing of refineries
cooling water quantity and quality in oil refineries
Biomass
air temperature, precipitation, humidityavailability and distribution of land with
suitable edaphoclimatic conditions (agricultural zoning)
extreme weather events desertification
carbon dioxide levels bioenergy crop yield
Energy Sector Climate Variables Related Impacts
Hydropowerair temperature, precipitation,
extreme weather events
total and seasonal water availability (inflow to plant's reservoirs)
dry spells
changes in hydropower system operation
evaporation from reservoirs
Wind Powerwind and extreme weather
events
changes in wind resource (intensity and duration), changes in wind shear, damage
from extreme weather
Solar Energyair temperature, humidity and
precipitation
insolation changes (clouds)
decrease in efficiency due to decrease in radiation
decrease in efficiency due to ambient conditions
Geothermal air/water temperature cooling efficiency
Wave Energywind and extreme weather
eventschanges in wave resource
Demand air temperature, precipitation
increase in demand for air conditioning during the summer
decrease in demand for warming during the winter
increase in energy demand for irrigation
Climate Impacts on Energy Systems
Other studies:
CCSP, 2007: Effects of Climate Change on Energy Production and Use in the United States. A Report by the U.S. Climate Change Science Program and the subcommittee on Global Change Research. Washington, DC., USA, 160 pp.
SATHAYE, J.A., DALE, L.L., LARSEN, P., LUCENA, A.F.P., 2009, Quantifying risk to California’s energy infrastructure from projected climate change. Public Interest Energy Research (PIER) Program – White Paper CEC.
MARGULIS, S., MARCOVITCH J., DUBEAUX, C.B.S. (org), 2009, Economia das Mudanças do Clima no Brasil: custos e oportunidades(www.economiadoclima.org.br)
The Paradox
• The first part of this “paradox” has been thoroughly studied
• But only recently the international scientific community has
started to investigate the impacts that climate change may
have on RE itself
• More commonly, information from weather forecasts is
being employed in the energy sector to assist in decision
making by producers, network operators, traders,
regulators
• Such information has been used for operational
forecasting, direct pricing of energy, trading of energy and
financial contracts
Objetive: to try to answer ...
• With the threat of Climate Change, should the energy
decision process now turn also to other meteorological
information:
– Seasonal
– Decadal
– Climate change forecasts?
• Are REs (more) vulnerable to Climate Change?
• Are countries that rely heavily on RE more vulnerable to
Climate Change?
• Is the water-energy nexus key with in this respect?
Objetive: to try to answer ...
• To answer those questions we will use Brazil as a case
study
• We will focus on the water-energy nexus for:
– Power generation from hydroelectricity
– Biofuels production
• But the answer to these questions are relevant to any
economy of the world
In Sum ...
• RE represents an important alternative for mitigating global
climate change
• RE also represents an important alternative for increasing
a country’s energy security by reducing its fossil fuel
production and/or importing needs
• But, because they are strongly dependent on climate
conditions, REs may be vulnerable to climate change
themselves, making them less reliable than otherwise
expected
• But, how vulnerable are hydro and wind and what is the
role for water-energy nexus in this?
Brazil: a case study
Why Brazil?
– Strong dependence on RE
– RE responsible for more than 45% of all energy
consumed in the country
– Hydro responsible for more than 85% of all electricity
generated
– Ethanol already surpassed gasoline as a motor fuel
http://www.ons.org.br/
What are the likely impacts of climate change on energy security in Brazil?
• On hydro?
• On biofuels production?
• What kind of adaptation strategies may be required?
Impacts of GCC on the Supply and Demand of Energy in Brazil
• GCC can affect the production/consumption of energy by
changing:
– Precipitation regimes – hydro and biofuels production
– Temperature – hydro (due to higher evaporation in
reservoirs and greater competition for water use),
thermal electricity efficiency, biofuels production and
energy demand
– Wind regimes – wind power potential
• What would be, then, the impact of GCC on the Brazilian
energy system by 2035?
GCC Scenarios Utilized
• IPCC A2 and B2 emission scenarios
• Transformed in long-term climate projections by
CPTEC/INPE
Hydro - Methodology
• A2 and B2 climate scenarios:
– Precipitation and temperature → Natural water flows to the hydro reservoirs
• New group of water flow series
– Monthly series for 2025-2100
– Future flows for 195 hydro plants were estimated using univariate time-series models
• Operation model of the hydro system in the country – SUISHI-O
– Firm energy (guaranteed) → Capacity factor
– Average energy (average generation over time)
Methodological Procedures for Impact Projections
GHG emission/ concentration scenarios
General CirculationModels (GCM)
Downscaling
Impact modeling:
biophysical/economic/
energy models
Adaptation modeling:
biophysical/economic/ energy models
Methodological Procedures for Impact Projections
GHG emissionscenarios
General CirculationModels (GCM)
Downscaling
Impact modeling:
biophysical/economic/ energy models
Adaptation modeling:
biophysical/economic/ energy models
Cumulativeuncertainties
Methodological Procedures for Impact Projections
• Future climate scenarios
– A2 and B2 emission scenarios (IPCC SRES)
– GCM – HadAM3P (UKMO)
– Downscaling – PRECIS (INPE)
• We are fully aware of the fragilities of this
approach
• We are begining to work with various CGMs
Climate models uncertainties:Temperature (oC)
INPE (2007)
Climate models uncertainties:Precipitation (mm/day)
INPE (2007)
Methodological Approach for Hydro
Climate Projections(GCM + downscaling)
Hydrological Model
Hydropower Model
Temperature and Precipitation
Water Inflow to Hydropower plants reservoirs
Firm Capacity Factor
Least cost integrated adaptation modeling
Impacts on Energy ProductionAverage energy
Firm energy
Direct EffectsIndirect EffectsSUISHI-O
Example for 2071-2100: A2 scenario –variation in relation to reference projections
Example for 2071-2100: B2 scenario –variation in relation to reference projections
Or a different picture for river flows: Annual variations (Salati et al., 2009; baseline = 100)
0
20
40
60
80
100
120
140
160
bas
elin
e
2011
-201
52
016
-202
02
021
-202
52
026
-203
02
031
-203
52
036
-204
02
041
-204
52
046
-205
02
051
-205
52
056
-206
02
061
-206
52
066
-207
02
071
-208
02
076
-208
02
081
-208
52
086
-209
02
091
-209
52
096
-210
0
At. Sudeste
B2 A2
0
20
40
60
80
100
120
140
160
180
base
lin
e
2011
-…
2016
-…
2021
-…
2026
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2031
-…
2036
-…
2041
-…
2046
-…
2051
-…
2056
-…
2061
-…
2066
-…
2071
-…
2076
-…
2081
-…
2086
-…
2091
-…
2096
-…
Paraná
B2 A2
0
20
40
60
80
100
120
140
160
180
200
ba
seli
ne
20
11
-…
20
16
-…
20
21
-…
20
26
-…
20
31
-…
20
36
-…
20
41
-…
20
46
-…
20
51
-…
20
56
-…
20
61
-…
20
66
-…
20
71
-…
20
76
-…
20
81
-…
20
86
-…
20
91
-…
20
96
-…
Paraguai
B2 A2
0
20
40
60
80
100
120
140
160
baselin
e
2011-…
2016-…
2021-…
2026-…
2031-…
2036-…
2041-…
2046-…
2051-…
2056-…
2061-…
2066-…
2071-…
2076-…
2081-…
2086-…
2091-…
2096-…
Uruguai
B2 A2
0
20
40
60
80
100
120
140
160
baselin
e
2011-…
2016-…
2021-…
2026-…
2031-…
2036-…
2041-…
2046-…
2051-…
2056-…
2061-…
2066-…
2071-…
2076-…
2081-…
2086-…
2091-…
2096-…
At. Sul
B2 A2
• South/Southeast Basins
49.604 MW = 45,1% 4.198 MW = 3,8% 4.149 MW = 3,8%
660 MW = 0,6% 4.561 MW = 4,1%
Note: Install capacities in
2015, according to PDE
(2015)
Or a different picture for river flows: Annual variations (Salati et al., 2009; baseline = 100)
• North/Northeast Basins
0
20
40
60
80
100
120
ba
se
lin
e
201
1-
201
5
201
6-
202
0
202
1-
202
5
202
6-
203
0
203
1-
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203
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1-
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5
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6-
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1-
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1-
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6-
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1-
208
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207
6-
208
0
208
1-
208
5
208
6-
209
0
209
1-
209
5
209
6-
210
0
Amazônia
B2 A2
0
20
40
60
80
100
120
baselin
e
2011-
2015
2016-
2020
2021-
2025
2026-
2030
2031-
2035
2036-
2040
2041-
2045
2046-
2050
2051-
2055
2056-
2060
2061-
2065
2066-
2070
2071-
2080
2076-
2080
2081-
2085
2086-
2090
2091-
2095
2096-
2100
Tocantins Araguaia
B2 A2
0
20
40
60
80
100
120
baselin
e
2011-
2015
2016-
2020
2021-
2025
2026-
2030
2031-
2035
2036-
2040
2041-
2045
2046-
2050
2051-
2055
2056-
2060
2061-
2065
2066-
2070
2071-
2080
2076-
2080
2081-
2085
2086-
2090
2091-
2095
2096-
2100
São Francisco
B2 A2
0
20
40
60
80
100
120
baselin
e
2011-…
2016-…
2021-…
2026-…
2031-…
2036-…
2041-…
2046-…
2051-…
2056-…
2061-…
2066-…
2071-…
2076-…
2081-…
2086-…
2091-…
2096-…
At. Leste
B2 A2
0
20
40
60
80
100
120
baselin
e
2011-…
2016-…
2021-…
2026-…
2031-…
2036-…
2041-…
2046-…
2051-…
2056-…
2061-…
2066-…
2071-…
2076-…
2081-…
2086-…
2091-…
2096-…
Parnaíba
B2 A2
16.971 MW = 15,4% 17.280 MW = 15,7% 10.652 MW = 9,7%
1.175 MW = 1,1% 842 MW = 0,8%
Note: Install capacities in
2015, according to PDE
(2015)
Hydrological Seasonality in Brazil
ONS (2008)
Impacts on Average Energy
A2 scenario B2 scenario
percentage variation
(-20)-(-4
0)
0-(-2
0)
0-2
0
(-40)-(-6
0)
<(-6
0)
20
-40
40
-60
>6
0
Impacts on Firm Energy
A2 scenario B2 scenario
percentage variation
(-20)-(-4
0)
0-(-2
0)
0-2
0
(-40)-(-6
0)
<(-6
0)
20
-40
40
-60
>6
0
Hydro – Results SUISHI-O
Bacia Histórico Variação em Relação ao Cenário Referência
MWmédio* A2 B2
E. Firme E. Média E. Firme E. Média E. Firme E. Média
Amazonas 9425 10628 -36% -11% -29% -7%
Tocantins Araguaia 7531 10001 -46% -27% -41% -21%
São Francisco 5026 5996 -69% -45% -77% -52%
Parnaiba 236 293 -83% -83% -88% -82%
At. Leste 496 565 -82% -80% -82% -80%
At. Sudeste 1937 2268 -32% 1% -37% -10%
At. Sul 1739 2037 -26% 8% -18% 11%
Uruguai 1715 1996 -30% 4% -20% 9%
Paraguai 375 426 -38% 4% -35% -3%
Paraná 22903 29038 -8% 43% -7% 37%
TOTAL 51382 63247 -31,5% 2,7% -29,3% 1,1%
Nota: Com base na configuração do sistema projetada para 2016 (EPE, 2007b).
*: MWmédio indica a quantidade de energia gerada supondo o fator de capacidade médio.
Projected Firm Capacity Factors by Plant Size and Sub-system
Capacity Factor
Sub-System Historical A2 B2
S/SE/MW
<30MW 58.0% 40.2% 39.7%
>30; <300MW 48.5% 31.6% 32.1%
>300MW 44.6% 38.7% 39.5%
N/NE
<30MW 58.0% 43.4% 48.8%
>30; <300MW 42.4% 21.5% 23.3%
>300MW 49.6% 25.5% 26.8%
Vulnerability of Liquid Biofuels Production
• Biodiesel – two crops examined
– Soya
– Sunflower
• Ethanol – one crop
– Sugarcane
Bio-fuels in Brazil: a parenthesis
Henry Ford, ethanol
vehicle (1896)
Bio-fuels use are, in no way, a new idea
First pure-ethanol Brazilian vehicle (1931)
Ethanol Addition into Gasoline
35
2
3
4
5
6
7
1975 1980 1985 1990 1995 2000
m3/ha
Main factors: • Gains in the agricultural phase• Extended harvest season• Integration and flexibilization of processes
(sugar + ethanol + electricity + others)Source: L.A. Horta Nogueira
Ethanol Productivity in Brazil
Possible Gains in Productivity
Sugarcane for Ethanol in Brazil
• Some 8 million ha planted with sugarcane (10% of the
area under agriculture)
• 55% processed for ethanol in some 400 plants, with some
40 new plants under construction
• More than 600,000 people working directly in the sugar
and ethanol industry in Brazil (plus other indirect jobs)
(Source: MME, 2005)
NORTH-NORTHEAST REGION 87 INDUSTRIAL UNITS:
• SUGAR MILLS 9• ETHANOL PLANTS 28• ETHANOL AND SUGAR 50
SOUTH-CENTRE REGION 217 INDUSTRIAL UNITS:
• SUGAR MILLS 4• ETHANOL PLANTS 60• ETHANOL AND SUGAR 153
SUGAR CANE INDUSTRIAL PLANTS
Localization of Ethanol Destileries
More than 90% of new LDV vehicles sold today are FFV (3 million/yr)
Soya harvesting in Mato Grosso state, 2004
Castor harvesting in the semi-arid of Piaui
state, 2005
Models for Bio-diesel Production
(Source: L. A. Horta Nogueira)
Water analysis
Junho / 2010
� Even though Brazil enjoys a comfortable situation in relation to waterresources when compared to other countries’ figures, there is anunequal spatial distribution of these resources within the Brazilianterritory
• About 80% of the water available is concentrated in the Amazon HydrographicRegion, where the population density is lowest and the figures for consumptivedemand are also low
� For this reason, the impact of the increase in the production of biofuelson water availability in the 2011-2019 period, in regions that havegreater demand for water in view of both population density andproduction processes, should be verified
� The demand for water per hectare of sugarcane and soybean producedin the states of SP and MT, respectively, in the year 2010, was modeledin the CROPWAT 8.0 software
Water analysis
� Thus, in view of the crops, soil and climate for SP and MT, which wereobtained from CONAB, EMBRAPA and FAO for the year 2010, anaverage demand of 16,991 m3 and 6,440 m3 of water per hectarecultivated was obtained, respectively, for sugarcane and soybean
� Therefore, considering the benchmark productivities of 86.4 tons perhectare for sugarcane in SP, and 3.0 tons per hectare for soybeans inMT, one arrives at an average demand of:
• 197 m3 of water for the production of 1 ton of sugarcane in SP
• 2,147 m3 of water for the production of 1 ton of soybean in MT in 2010
� To estimate the demand for water per crop in 2019, an average growthin productivity of 1.5% per year, from 2011 on, was initially consideredfor both sugarcane and soybean
� Therefore, in the 2010-2019 period, there would be a 64% increase insugarcane production, and 75% in soy production
Water analysis
� In view of these assumptions, taking into account the projectedincrease in ethanol and biodiesel production, our results show, for thesugarcane and soy crops in SP and MT, a total water demand of108,638 and 67,509 million m3, respectively, in 2019
� It is now necessary to verify whether the total amount of water requiredfor the expansion of the sugarcane and soybean crops in SP and MT, inthe year 2019, would be limited by the availability of water resources inthe Paraná and Amazon basins, respectively
� It was considered that the surface water availability in Brazil in the year2010 would be maintained. In this case, considering all Brazilianbasins, with 95% permanence, this availability amounted to 5,658,599million m3
� In addition, the surface water availability of the Amazon and Paranáhydrographic basins, which supply the states of MT and SP, wasconsidered constant
Water analysis
� The demand for water in 2010 and 2019 for both sugarcane andsoybean production was obtained, and refers to the amount of waterneeded for the expansion of biofuels production based on these crops
� Moreover, water availability should also take into account other wateruses, namely industrial use, urban and rural use for humanconsumption, and use for cattle raising
� Based on the consideration of these different demands, we arrive at:
Water analysis
Water availability in the Amazon and Paraná basins,
considering the different demands for water in 2010 and
2019
Amazon Basin Paraná Basin
Water Availability (106 m3/year)*
4,161,081 361,182
Water Demand for Sugarcane / SP
(106 m3)
2010 N.A. 69,687
2019 N.A. 108,638
Water Demand for Other Uses / SP (106 m3)
2010 N.A. 15,058
2019 N.A. 19,124
% of Water Available
2010 N.A. 76%
2019 N.A. 65%
Water Demand for Soy / MT (106 m3)
2010 40,151 N.A.
2019 67,509 N.A.
Water Demand for Other Uses / MT (106 m3)
2010 1,476 N.A.
2019 1,874 N.A.
% of Water Available
2010 98% N.A.
2019 97% N.A.
* Water availability is composed of the average annual flow of the rivers in the hydrographic basin.
N.A.: not applicable.
� It is observed that the expansion ofagricultural production in SP andMT, with a view to supporting theexpansion of biofuels production inBrazil, would not encounterlimitations with regard to wateravailability
� In the case of SP, although theamount of water does not seem tobe of concern, about 80% of therivers are in critical, worrying orvery worrying conditions, regardingwater potability
� In this case, resources should bemanaged so that the potable waterresources are not fully used for theexpansion of the sugarcane crop,for which the quality of water is notfundamental, as it is in the case ofhuman consumption
Liquid Biofuels: Vulnerability Results
• The country’s main producing regions will continue to
be within the temperature limits for sugarcane. Even if
cultivation becomes unfeasible in some specific
regions, other regions can take up the slack, especially
the Midwest
• The production of biodiesels (soy and sunflower) can
be affected negatively by GCC, mainly in the
Northeast, with a shift of suitable growing zones for
oilseed crops to the South region
In sum, impacts on biofuels production ...
• Sugar cane should not be deeply affected by CC:
migration to the South
• Soy may be severely impacted by CC, loosing 40% of
suitable areas by 2070
• Sunflower production could loose 20% of suitable crop
areas by 2070
Adaptation of the energy system
A2A2-1: w/o GCC
A2-2: w/ GCC√
√
B2B2-1: w/o GCC
B2-2: w/ GCC√
√
Scenario A2 – variation in firm energy in 2035
Energy Capacity
TWh var % GW
Hydropower
Small (<30MW) -12 (↓) -30% (↓) 0.0
Medium (>30MW; <300MW) -63 (↓) -36% (↓) 0.0
Large (>300MW) -87 (↓) -28% (↓) 0.0
Sugar-cane Bagasse
BP 22 bar 0 0% 0.0
BP 42 bar 0 0% 0.0
Cascade Cogeneration -20 (↓) -57% (↓) -3.7 (↓) CEST 99 (↑) 143% (↑) 13.2 (↑) BIG-GT 0 0% 0.0
Municipal Solid Waste 0 0% 0.0
Wind Power 21 (↑) 39% (↑) 10.0 (↑) Natural Gas 133 (↑) 135% (↑) 32.9 (↑) Nuclear 45 (↑) 58% (↑) 6.1 (↑) Coal 0 0% 0.0
Diesel Oil 0 0% 0.0
Oil 0 0% 0.0
Scenario B2 – variation in firm energy in 2035
Energy Capacity
TWh var % GW
Hydropower
Small (<30MW) -12 (↓) -30% (↓) 0.0
Medium (>30MW; <300MW) -61 (↓) -35% (↓) 0.0
Large (>300MW) -80 (↓) -26% (↓) 0.0
Sugar-cane Bagasse
BP 22 bar 0 0% 0.0
BP 42 bar 0 0% 0.0
Cascade Cogeneration -12 (↓) -100% (↓) -2.3 (↓) CEST 77 (↑) 49% (↑) 10.3 (↑) BIG-GT 0 0% 0.0
Municipal Solid Waste 0 0% 0.0
Wind Power 24 (↑) 26% (↑) 11.5 (↑) Natural Gas 124 (↑) 147% (↑) 30.2 (↑) Nuclear 0 0% 0.0
Coal 53 (↑) 134% (↑) 8.6 (↑) Diesel Oil 0 0% 0.0
Oil 0 0% 0.0
Results – Adaptation - 2035
• Brazil’s electric power system will need to expand its
installed capacity by some 60 GW to cope with the loss
of firm energy from the hydropower system
• This additional installed capacity will require extra 90-
120 billion dollars in new investments
• On average, especially for natural gas-fired plants, this
additional capacity will not be used. It will be an
insurance against the loss of reliability from the system
• Under critical conditions, natural gas compensates for
hydro losses, but GHG emissions from power
generation increases
Conclusions
• RE presents a substantial economic potential for
mitigating GHG emissions over the coming decades
• At the same time, RE is increasingly seen as a
fundamental pillar for improving a country’s energy
security
• On the other hand, because it is strongly dependent on
climate conditions, RE may be vulnerable to the very
problem it tries to fight
• As a consequence, RE may not contribute to mitigating
climate change and to improving energy security as
much as it promises, or as much as it is expected from it
• The water-energy nexus is key in this respect
Prof. Roberto Schaeffer
Energy Planning Program, COPPE
Federal University of Rio de Janeiro