Transcript Baseline Methodology for Energy Sector CDM Projects Dr. Govinda R. Timilsina

Baseline Methodology for Energy
Sector CDM Projects
by
Dr. Govinda R. Timilsina
Energy & Climate Change Specialist
Regional Workshop on Capacity Building for CDM
24-26 March 2004
Siem Reap, Cambodia
Presentation Outline
• Introduction
• New Baseline Methodologies (Submitted and
Approved)
• Steps to adopt and develop baseline
methodologies
• Examples of Baseline Methodology for Energy
Sector CDM Projects
• Models for Baseline Emission Estimation
INTRODUCTION
• What is a baseline?
The Paragraph 5c of the Article 12 of the Kyoto Protocol states that
emission reductions from a CDM project should be additional to any
that would occur in the absence of such activities.
The best guess as to what would have happened in the absence of a
CDM project activity is referred to as baseline for the project.
The Marrakech Accord defines the baseline as the scenario that
reasonably represents the anthropogenic emissions by sources of
greenhouse gases that would occur in the absence of the proposed
project activity.
INTRODUCTION (Cont..)
The paragraph 48 of the modalities and procedures for the clean
development mechanism suggests the following three approaches for
choosing a baseline methodology for a CDM project activity:
• Existing actual or historical emissions, as applicable;
• Emissions from a technology that represents an economically
attractive course of action, taking into account barriers to
investment;
• The average emissions of similar project activities undertaken in the
previous five years, in similar social, economic, environmental and
technological circumstances, and whose performance is among the
top 20 per cent of their category.
NEW BASELINE METHODOLOGIES
Since January 2003 to February 2004, a total 45 new baseline
methodologies have been submitted to the CDM EB.
Of which nine are approved, nine are not approved and the rest 27 are
under various stages of review process.
Types of Projects for New Baseline Methodologies Submitted:
Biomass Fired Co-generation
Landfill Gas Capture
Wind Power
Hydropower
Biomass Fired Power generation
Fuel Switching
Energy Efficiency
Waste to Energy
Technology Upgrading in Cement Industry
HFC Control
APPROVED BASELINE METHODOLOGIES
Landfill Gas Capture
- Vale do Rosario Bagasse Cogeneration (VRBC) Project, Brazil
- Salvador Da Bahia Landfill Gas Project, Brazil
- Nova Gerar landfill gas to energy project, Brazil
- CERUPT Methodology for Landfill Gas Recovery Brazil
- Durban landfill-gas-to-electricity project, South Africa
Biomass Power
- Grid-connected Biomass Power Generation, Thailand
Hydropower
- Mexico- El Gallo hydro power project, Mexico
HFC Control
- HFC incineration in HCFC production Facilities, Republic of Korea
Fuel Switching
- Graneros plant coal to gas fuel switching project, Chile
BASELINE METHODOLOGY OPTIONS
CDM Project developers have the following two options:
• Select a baseline methodology from the list of existing
baseline methodologies maintained by the UNFCCC
Secretariat
• Propose a new baseline methodology
STEPS TO ADOPT EXISTING BASELINE
METHODOLOGY
Justification of the choice of the methodology
Description of how the methodology is applied in the context of the
project activity
Demonstration of emission reductions below that would occur in the
absence of the CDM project
Defining system boundary
Assessment of the additionality
STEPS TO DEVELOP NEW BASELINE
METHODOLOGY
- Title of the proposed methodology
- Description of the methodology and its applicability
- Key parameters/assumptions and data sources
- Definition of the system boundary
- Assessment of uncertainties
- Calculation of baseline emissions and the determination of project
additionality
- Address any potential leakage of the project activity
- Transparency and conservatism
- Assessment of strengths and weaknesses of the baseline methodology
- National and Sectoral Policies
EXAMPLES OF BASELINE METHODOLOGY
AM0004: Grid-connected Biomass Power Generation that avoids
Uncontrolled Burning of Biomass, Thailand
•
This methodology is based on the A.T. Biopower Rice Husk Power Project
in Pichit, Thailand whose Baseline study, Monitoring and Verification Plan
and Project Design Document were prepared by Mitsubishi Securities.
•
It follows Approach “B” stated in Paragraph 48 of the CDM M&P-emissions from a technology that represents an economically attractive
course of action, taking into account barriers to investment--.
EXAMPLES OF BASELINE METHODOLOGY
AM0004: Grid-connected Biomass Power Generation that avoids
Uncontrolled Burning of Biomass, Thailand (Cont…)
•
This methodology is applicable to biomass-fired power generation project
displacing grid electricity in the following conditions:
– Use of biomass that would otherwise be dumped or burned in an uncontrolled
manner
– Have an access to an abundant supply of biomass that is unutilized and is too
dispersed to be used for grid electricity generation under business as usual
(BAU)
– Have a negligible impact on plans for construction of new power plants
– Not be connected to a grid with suppressed demand
– Have a negligible impact on the average grid emissions factor
– Where the grid average carbon emission factor (CEF) is lower (and therefore
more conservative) than the CEF of the most likely operating margin
candidate
EXAMPLES OF BASELINE METHODOLOGY
AM0004: Grid-connected Biomass Power Generation that avoids
Uncontrolled Burning of Biomass, Thailand (Cont…)
Emissions Accounted for:
• Direct on site emissions:
– Emissions within the physical boundary of the project in the baseline that
–
•
Direct off site emissions:
– Emissions outside the physical boundary of the CDM project but within its
–
•
would be affected by the CDM project activities
Emissions within the physical boundary of the actual CDM project activities
system boundary in the baseline that would be affected by the CDM project
activities
Emissions beyond the physical boundary of the actual CDM project but within
its system boundary
Leakage:
– Increase in emissions outside the system boundary due to the CDM project
activities
EXAMPLES OF BASELINE METHODOLOGY
AM0004: Grid-connected Biomass Power Generation that avoids
Uncontrolled Burning of Biomass, Thailand (Cont…)
Direct On Site Emissions
Direct Off Site Emissions
Baseline
CO2 from grid electricity generation and CH4 emissions
from Open air burning of surplus rice husk
N2O emissions from grid as well as from open air burning
of surplus rice husk are not accounted for purpose of
simplification and in favor of conservative baseline.
CO2 emissions from transportation of
rice husk in the disposal site not
accounted for purpose of simplification
and in favor of conservative baseline.
Project
CH4 emissions from rice husk-fuelled electricity CO2, CH4 and N2O from
generation
transportation of rice husk from rice
N2O emissions from rice husk-fuelled electricity
mill to project site
generation are not accounted
CO2, CH4 and N2O from Transportation of rice husk in
the project site
CO2, CH4 and N2O from Start-up/auxiliary fuel
EXAMPLES OF BASELINE METHODOLOGY
AM0004: Grid-connected Biomass Power Generation that avoids
Uncontrolled Burning of Biomass, Thailand (Cont…)
Determination of Baseline
• The baseline assumes continued open air burning of the biomass used by
the project activity and generation of electricity supplied by the project
activity by other facilities.
•
Since open air burning results in lower GHG emissions than decay of
biomass, it is assumed for the baseline confirming that the baseline is
conservative one.
•
The baseline emissions (BLGHGy ) are then calculated as:
BLGHGy = BBCH4y + EGCO2y
BBCH4y =
EGCO2y =
CH4 emissions during the year due to open air burning of the
biomass used for electricity generation
CO2 emissions during the year due to generation of the electricity
by other sources.
EXAMPLES OF BASELINE METHODOLOGY
AM0004: Grid-connected Biomass Power Generation that avoids
Uncontrolled Burning of Biomass, Thailand (Cont…)
Determination of Baseline (Continue)
BBCH4y = BFy * BCF * CH4F * CH4C * GWPCH4
BFy
= biomass used as fuel during the year (metric tonnes)
BCF
= carbon fraction of the biomass fuel (tonnes of carbon/tonne of biomass)
CH4F = fraction of the carbon released as CH4 in open air burning
CH4C = mass conversion factor of CH4 (16/12)
EGCO2y = EGy * CEFy
EGy = electricity supplied to the grid by the project during the year (MWh)
CEFy = CO2 emission factor for the electricity grid during the year (tCO2e/MWh)
EXAMPLES OF BASELINE METHODOLOGY
AM0004: Grid-connected Biomass Power Generation that avoids
Uncontrolled Burning of Biomass, Thailand (Cont…)
Determination of Baseline (Continue)
•
The CEFy is the lower of the grid average CO2 emission factor or the
operating margin CO2 emission factor calculated ex post for the year
•
If the project is located in a country/region with suppressed demand, the
project participants may use a CO2 emission factor based on the “build
margin”
•
For simplification and favoring conservative baselines, N2O emissions
from open air burning of surplus biomass is excluded.
EXAMPLES OF BASELINE METHODOLOGY
AM0004: Grid-connected Biomass Power Generation that avoids
Uncontrolled Burning of Biomass, Thailand (Cont…)
Estimation of Emission Reductions
•
The project reduces CH4 emissions due to the decay or burning of the biomass as
well as CO2 emissions due to generation of the electricity by other sources.
•
The project activity generates CH4 emissions due to combustion of the biomass
as well as CO2, CH4 and N2O emissions due to transportation of the biomass to
the generation facility and on-site.
•
The emission reduction by the project (ERy) during a given year is:
ERy = BLGHGy - BBEGCH4y - BTGHGy - OTGHGy - FFGHGy
BLGHGy
BBEGCH4y
BTGHGy
OTGHGy
FFGHGy
=
=
=
=
=
Baseline GHG emissions during the year
CH4 emissions from biomass combustion for electricity generation
CO2, CH4 and N2O emissions from biomass transport to project site
CO2, CH4 and N2O emissions from on-site biomass transportation
CO2, CH4 and N2O emissions from auxiliary fuel consumption
EXAMPLES OF BASELINE METHODOLOGY
AM0004: Grid-connected Biomass Power Generation that avoids
Uncontrolled Burning of Biomass, Thailand (Cont…)
Estimation of Emission Reductions (Continue)
CH4 emissions from biomass combustion for electricity generation
(BBEGCH4y)
BBEGCH4y = BFy * BFHV * EFCH4 * GWPCH4
BFy
= biomass used as fuel (metric tonnes)
BFHV
= heat value of the biomass fuel used (TJ/tonne)
EFCH4 = CH4 emission factor for the biomass fuel (tonnes CH4/ TJ)
GWPCH4 = Approved Global Warming Potential value for CH4 (21)
EXAMPLES OF BASELINE METHODOLOGY
AM0004: Grid-connected Biomass Power Generation that avoids
Uncontrolled Burning of Biomass, Thailand (Cont…)
Estimation of Emission Reductions (Continue)
CO2, CH4 and N2O emissions from biomass transport to project site (BTGHGy)
BTGHGy =
BFy
TC
AVDy
VEFCO2
VEFCH4
VEFN2O
GWPN2O
BFy/TC * AVDy * [VEFCO2 + VEFCH4 * GWPCH4 +
VEFN2O * GWPN2O]
= biomass used as fuel (metric tonnes)
= truck capacity (tonnes of biomass)
= average return trip distance between the biomass fuel supply sites
and the electricity generating plant site (km)
= CO2 emission factor for the trucks (tCO2/km)
= CH4 emission factor for the trucks (tCH4/km)
= N2O emission factor for the trucks (tN2O/km)
= approved Global Warming Potential value for N2O (310)
EXAMPLES OF BASELINE METHODOLOGY
AM0004: Grid-connected Biomass Power Generation that avoids
Uncontrolled Burning of Biomass, Thailand (Cont…)
Estimation of Emission Reductions (Continue)
CO2, CH4 and N2O emissions from on-site biomass transportation
(OTGHGy)
OTGHGy = OFy * [VEFCO2 + VEFCH4 * GWPCH4 + VEFN2O * GWPN2O]
OFy = transportation fuel used on-site (kg)
VEFCO2 = CO2 emission factor for the transportation fuel (gCO2/kg)
VEFCH4 = CH4 emission factor for the transportation fuel (gCH4/kg)
VEFN2O = N2O emission factor for the transportation fuel (gN2O/kg)
FF_GHGy = FFy * [GEF_CO2 + GEF_CH4 * GWP_CH4 + GEF_N2O * GWP_N2O]
EXAMPLES OF BASELINE METHODOLOGY
AM0004: Grid-connected Biomass Power Generation that avoids
Uncontrolled Burning of Biomass, Thailand (Cont…)
Estimation of Emission Reductions (Continue)
CO2, CH4 and N2O emissions from auxiliary fuel consumption (FFGHGy)
FFGHGy = FFy * [GEFCO2 + GEFCH4 * GWPCH4 + GEFN2O * GWPN2O]
FFy = fossil fuel used by the electricity generating unit as start-up and auxiliary
fuel (TJ)
GEFCO2 = CO2 emission factor for the generating unit (tCO2/TJ)
GEFCH4 = CH4 emission factor for the generating unit (tCH4/TJ)
GEFN2O = N2O emission factor for the generating unit (tN2O/TJ)
N2O emission from grid electricity generation is excluded for simplification
and to favor the conservative baseline
EXAMPLES OF BASELINE METHODOLOGY
AM0004: Grid-connected Biomass Power Generation that avoids
Uncontrolled Burning of Biomass, Thailand (Cont…)
Additionality Testing
Barrier Analysis: The project could not be materialized in the absence of
CDM due to the presence of following barriers:
Investment barriers
Technological barriers
Barriers due to prevailing practice
Other barriers
EXAMPLES OF BASELINE METHODOLOGY
AM0004: Grid-connected Biomass Power Generation that avoids
Uncontrolled Burning of Biomass, Thailand (Cont…)
Additionality Testing (Continue)
Investment barriers
– Return on equity is too low as compared to conventional projects
– Real and/or perceived risk associated with the unfamiliar technology
or process is too high to attract investment
– Funding is not available for innovative projects
Technological barriers
– The project represents one of the first applications of the technology
in the country, leading to technological concerns even when the
technology is proven in other countries
– Skilled and/or properly trained labor to operate and maintain the
technology is not available
EXAMPLES OF BASELINE METHODOLOGY
AM0004: Grid-connected Biomass Power Generation that avoids
Uncontrolled Burning of Biomass, Thailand (Cont…)
Additionality Testing (Continue)
Barriers due to prevailing practice
– There is a lack of will to change the current biomass disposal practice
with or without regulations
– Developers lack familiarity
reluctant to use them
with state-of-the-art technologies and are
Other barriers
– Management lacks experience using state-of-the-art
technologies, so
such projects require too much management time and receive low
priority by management
– The
local community may fail to see the environmental benefits of
biomass power generation and so may oppose the project
MODELS FOR BASELINE EMISSION
ESTIMATIONS
•
A large number of commercially available energy models (e.g., MARKAL,
ENPEP LEAP) are now adopted to estimate GHG emissions resulted from
energy supply and demand activities.
•
These models could be applicable in estimating baseline emissions in
various types of CDM projects (e.g., . ENPEP for power sector projects;
LEAP for demand side or energy efficiency improvements projects;
MARKAL for supply side projects)
•
These models are, however, more appropriate in setting baselines at the
sectoral and national levels; their use for estimating baselines for a
particular CDM project activity (or setting project specific baseline)
depends on size of the project.
(GHG emissions from a CDM project activity could be negligible compared to
sectoral or national level emissions)
MODELS FOR BASELINE EMISSION
ESTIMATIONS (MARKAL)
•
MARKAL (acronym for MARKet ALlocation) is a bottom-up type model
developed by the Energy Technology Systems Analysis Program (ETSAP)
of the International Energy Agency (IEA)
•
It is a linear programming type optimization model and based on
Reference Energy System (RES) energy system from primary energy
resources through conversion processes, to transport, distribution and
end - use devices.
Demand and supply are balanced through optimization
Detailed modeling of energy supply side
Detailed representation of resources is possible
Electricity sector is modeled (generation and transmission system expansion)
MODELS FOR BASELINE EMISSION
ESTIMATIONS (MARKAL Cont…)
The MARKAL Energy Perspective
Primary Energy
Supply
Conversion
Technologies
End-Use
Technologies
(Final Energy)
Renewables e.g.
-Biomass
-Hydro
Mining e.g.
-Crude oil
-Natural gas
-Coal
Imports e.g.
-crude oil
-oil products
Exports e.g.
-oil products
-coal
Stock changes
Fuel processing
Plants e.g.
-Oil refineries
-Hydrogen prod.
-Ethanol prod.
Power plants e.g.
-Conventional
Fossil Fueled
-Solar
-Wind
-Nuclear
-CCGT
-Fuel Cells
-Combined Heat
and Power
(Useful Energy)
Industry, e.g.
-Steam boilers
-Machinery
Services, e.g.
-Air conditioners
-Light bulbs
Households, e.g.
-Space heaters
-Refrigerators
Agriculture, e.g.
-Irrigation pumps
Transport, e.g.
-Gasoline Car
-Fuel Cell Bus
Demand for
Energy Service
Industry, e.g.
-Process steam
-Motive power
Services, e.g.
-Cooling
-Lighting
Households, e.g.
-Space heat
-Refrigeration
Agriculture, e.g.
-Water supply
Transport, e.g.
-Person-km
Source: Tseng, p. (2002), An Overview of US MARKAL-MACRO Model, US Department Of Energy,
Washington
MODELS FOR BASELINE EMISSION
ESTIMATIONS (ENPEP)
ENPEP MODEL
•
ENPEP (Energy and Power Evaluation Program) is a set of 10 integrated energy,
environmental, and economic analysis tools (developed for IAEA).
MACRO-E
Economic impacts
MAED
Energy demand forecasting
LOAD
Hourly load profiles and load duration curves
PC-VALORAGUA
Optimal generating strategy for hydro-thermal systems
WASP-IV
Least-cost generating system expansion path
GTMAX
Generation and transmission maximization module
ICARUS
Costs and reliability in utility systems module
IMPACTS
Physical and economic damages from air pollution
BALANCE
Demand respond to price changes
DAM
Decision analysis for technical, economic, and environmental
tradeoffs
MODELS FOR BASELINE EMISSION
ESTIMATIONS (ENPEP Cont…)
•
Detailed evaluation of the sectoral energy demands by sector, sub-sector,
fuels and useful energy
•
•
Representation of resource availability and costs
•
Equilibrium solution for total energy system, energy policy constraints can
be imposed
•
Environmental impacts under baseline and environmental scenarios
Detailed evaluation of the power system configurations both current and
future
MODELS FOR BASELINE EMISSION
ESTIMATIONS (ENPEP Cont…)
MAED
MACRO-E
LOAD
WASP IV
WASP IV
Capacity
Expansion Plan
Load Dispatching
BALANCE
Energy Demand
(excluding
electricity)
Electricity
Generation
Fuel
Consumption
Emissions
Emissions
Emission Estimation Using ENPEP
MODELS FOR BASELINE EMISSION
ESTIMATIONS (LEAP)
•
LEAP (Long Range Energy Alternatives Planning System) is developed by
Stockholm Environmental Institute - Boston, USA.
•
In contrast to MARKAL and ENPEP, LEAP is not an optimization model,
rather it is a scenario-based energy accounting model.
•
Detailed evaluation of the sectoral energy demands by sectors, subsectors end-uses and equipment.
•
Simulation of any energy conversion sector (e.g., electric generation, oil
refining, charcoal making)
•
Detailed evaluation of supply configurations both current and future
periods
•
•
Iterative calculation of demand/supply balance
It accommodates a Technology and Environmental Database
MODELS FOR BASELINE EMISSION
ESTIMATIONS (LEAP Cont..)
M a c ro E c o n o m ic s
( P o llu t a n t E m is s io n s )
D e m a n d
A n a ly s is
S t a t is t ic a l
D if f e r e n c e s
T r a n s f o r m a t io n
A n a ly s is
S to c k
C h a n g e s
R e s o u rc e
A n a ly s is
N o n -E n e rg y S e c to r
E m is s io n s A n a ly s is
E n v ir o n m e n t a l
E x t e r n a lit ie s
I n t e g r a t e d C o s t - B e n e f it A n a ly s is
E n v ir o n m e n t a l L o a d in g s
D e m o g r a p h ic s
THANK
YOU !