generating capacity expansion and system interconnections g rid s chool 2010 m arch 8-12, 2010 r...
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Generating Capacity Expansion and System Interconnections
GRIDSCHOOL 2010MARCH 8-12, 2010 RICHMOND, VIRGINIA
INSTITUTE OF PUBLIC UTILITIESARGONNE NATIONAL LABORATORY
Vladimir KoritarovCenter for Energy, Economic, and Environmental Systems Analysis
Decision and Information Sciences DivisionARGONNE NATIONAL LABORATORY
[email protected] 630.252.6711
Do not cite or distribute without permission
MICHIGAN STATE UNIVERSITY
Koritarov - 02GridSchool 2010
Planning Should Lead to Specific Actions
The ANALYSIS provides information to decision-makers. The PLAN is a statement of the choices made. Planning is a continuous activity.
DataCollection
Decision-Making
InformationAnalysis
Projects
Policies
FurtherStudy
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There are 7 Key Steps in the Planning Process
1. DEFINEOBJECTIVES
1. DEFINEOBJECTIVES
2. DEFINEAPPROACH
2. DEFINEAPPROACH
3. DETERMINEINFORMATION
NEEDS
3. DETERMINEINFORMATION
NEEDS
6. PRESENTRESULTS
6. PRESENTRESULTS
5. CONDUCTANALYSIS
5. CONDUCTANALYSIS
4. CHOOSEANALYSISPROCESS
4. CHOOSEANALYSISPROCESS
7. PREPAREPLAN
7. PREPAREPLAN
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An Important Part of the Planning Process is the Presentation of Results to Decision-Makers
The results should be presented in the form of decision-making information:
CASE
1 2 3CASE
IMPORTS
ENVIRONMENTALEFFECTS
1 2 3CASE
COST
1 2 3
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Integrated Resource Planning (IRP) Perspective for Long-Term System Expansion Is Important
IRP is a planning methodology that integrates both supply and demand-side options for developing the least-cost expansion strategy
IRP produces a long-term resource strategy by considering all available supply and demand-side options: Generating technologies (conventional thermal and hydro power plants,
renewable technologies, etc.) Distributed energy resources (e.g., distributed generation) Energy efficiency resources (e.g., conservation) Demand-side management programs (e.g., shaping electricity demand) Long-term power purchase contracts
The objective of IRP is to determine the least-cost resource strategy by evaluating the cost-effectiveness of all available resource options on a consistent, integrated basis
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Strategic Resource Planning Primarily Deals with Medium and Long-Term Time Horizons
PLANNING HORIZON
Increasing Time
Primary Area of Interest
Demand
Generation
Transmission
Distribution
Implies Intercellular Ineractions to be Addressed
CA
TE
GO
RY
OF
EL
EC
TR
IC S
YS
TE
M P
LA
NN
ING
Short(<5 years)
Medium(5-10
years)
Long(>10 years)
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Various Types of Planning Require Different Time Horizons
Strategic Planning
0 1 2 3 4 5 6 7 8 9 10 11 12 Years
Distribution
Transmission
Peaking Cycling
Base Fossil
Hydroelectric
Nuclear
Load Dispatcher
Gen
erat
ing
S
yste
m
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Investment Decisions in Traditional vs. Deregulated Electricity Markets
Generating system expansion analysis in regulated power systems must address a number of critical issues:
Long-term demand forecasts and changes of load profiles over time
Long lead times for the construction of new generating units
Reliability of power system operation (unit outages, hydro inflows, etc.)
Large variety of candidate technologies (e.g., plant types and unit sizes)
Economic uncertainties (fuel prices, investment costs, etc.)In deregulated power systems, the analysis must also
consider: Long-term projections of electricity prices in the market Actions and investment decisions of competing generating
companies, IPPs, and new market entrants
Koritarov - 09GridSchool 2010
The Traditional Resource Planning Method in Regulated Utilities Is to Find the Optimal Construction Plan for the Entire System
Objective: Identify the generating system expansion plan that has the minimum net present value of all operating and investment costs during the study period
Time Years
State
(Expansion O
ption)
“Best” Plan Over Time
One Generation Company
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Objectives for Constructing New Capacity in Restructured Markets Differ from those under Vertically Integrated Systems
Multiple competing market participants instead of single decision maker:
Each market player makes its own independent investment decisions
Players have only limited information about the competition
Ideally an individual player cannot control the market
Market participants face multiple uncertainties
Expansion investments are based on financial considerations, not lowest societal cost or energy security concerns:
Profits are often the main driving force behind the decision making process
Financial decision criteria are typically based on measures such as rate of return on investment, payback period, and risk indicators
Other factors such as market share may influence the decision making process
Capacity expansion by competitors and new market entrants are uncertain
Emphasis is on the risk and risk management for corporate survival versus guaranteed rate of return under the traditional regulatory structure
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In an Open Market, An Individual GenCo Will Make Investment Decisions That it Perceives Are “Best for the Company”
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The Sum of Independent Investment Decisions May Be Very Different from the Least-Cost System Expansion Plan
0
10
20
30
40
50
60
70
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Ge
ne
rati
ng
Ca
pa
cit
y (
GW
)
Natural Gas
Other
U.S. Annual Capacity Additions (GW)
Source: EIA, 2006
Open electricity market includes existing GenCos as well as new entrants!
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Capacity Expansion Planning in Restructured Power Markets
In restructured electricity markets there are multiple entities involved at different levels:
Policy Makers (Government/Ministry) Energy Regulatory Agency Market Operator(s) Transmission System and Dispatch Operators Load Serving Entities/Consumers:
Distribution companies Retail market aggregators Direct consumers (large industry, commercial, etc.)
Generation Companies Individual Investors/IPPs
All of these entities have an interest in system planning, but from different angles.
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Electric System Resource Planning Is Linked to the Overall Energy Planning
Primary connection is through the demand forecast
Additional connections: Resource utilization policies Energy sector deregulation and restructuring
policies Environmental policies
Benefits of linkage: Avoids duplication of effort (e.g., for demand
forecasting) Provides consistent assumptions for major
independent variables, such as population growth Develops good understanding of forecast
assumptions
Energy Demand Forecasting
Electricity Demand Forecasting
Generating System Expansion Planning
T&D Planning
Koritarov - 014GridSchool 2010
Electricity Demand Forecast Is One of the Most Important Parts of Analysis
Electricity demand forecasting analysis should address:
Peak loads (MW)
Energy demand (GWh)
Seasonal load variations
Changes in demand shape (load profiles) over time
Errors in future estimated demand
Koritarov - 015GridSchool 2010
There Are Numerous Techniques for Forecasting Electrical Loads and Energy Demand
Different techniques are used for short-term and for long-term time horizons Short-term operation planning is more concerned with forecasting hourly loads
Weather plays a great role in short-term load forecasting models Long-term expansion planning deals with the growth rates of electricity consumption
and changes in peak loads from year to year Population and economic growth are some of key drivers in the long term
Common demand forecasting approaches: Time series analysis Econometric models End-use models
Historical
Projected
Electricity Consumption
Years
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Four Basic Questions Must Be Answered in the Capacity Expansion Planning Process
1. WHAT capacities to install to ensure an appropriate level of reliability?
2. HOW to pick the best combination of different generatingtechnologies available now and in the future?
3. WHERE to locate this new capacity?
4. WHEN is the proper time to incorporate new capacity additions into the system?
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Various Technologies Are Currently Available as Candidates for Expansion
Steam fossil Hydroelectric Combustion turbines Diesel engines Combined cycle Pumped storage Nuclear Wind Solar Biomass Geothermal Distributed and demand-side
resources Etc.
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The Planner Must Also Consider Potential Future Options
Fuel cells Photovoltaic Ocean thermal energy conversion Wave and tidal power Storage technologies:
Batteries (including flow batteries) Compressed air energy storage
(CAES) Flywheels Superconducting magnetic energy
storage (SMES) Super-capacitors Distributed storage (e.g., V2G
technologies)
Koritarov - 019GridSchool 2010
A Fundamental Aspect of Any Economic Evaluation Is the Time Element The system expansion analysis is typically performed for a period of 20-30 years
Time value of money Inflation (deflation) changes the buying power of money Real changes over time (real escalation) due to factors such as resource depletion,
increased demand, improvements in design and manufacturing, etc.
The annual factor that accounts for the time value of money independently of inflation is called the real discount rate (or real present worth rate)
Discount rate: Necessary for comparing alternatives Results are clearly sensitive to the choice of discount rate
Selected discount rate should be appropriate for electric utilities and may reflect: Average cost of capital Scarcity of capital Opportunity cost of capital, etc.
Koritarov - 020GridSchool 2010
The Primary Objective of an Electric Power System Is to Adequately Meet the Demand at Minimum Cost
Meaning of “adequately”
Costs of different reliability levels
Numerous factors are affecting system reliability Random unit breakdowns Demand variations Hydroelectric variations Scheduled maintenance Nuclear refueling Cancellations and delays in the
construction of new capacity
Koritarov - 021GridSchool 2010
The Reliability of Supply is an Important Issue in Electric Power Systems Expansion Planning
Utilities use a number of parameters to estimate expected reliability of supply: Reserve margins Loss-of-Load Probability (LOLP) Loss-of-Load Expectation (LOLE) Expected Unserved Energy (EUE), etc.
These are either used as constraints in the planning process or as targets for desired reliability levels
In the United States power systems are typically planned for 99.97% reliability. This corresponds to the LOLE of 1 day in 10 years (LOLP=0.0274%)
In developing countries, the power systems are typically planned for 99.7% reliability. This corresponds to the LOLE of 1 day per year (LOLP=0.274%)
Koritarov - 022GridSchool 2010
A Development Philosophy Should Be Clearly Stated
Use of primary energy resources Long-term fuel supply availability Domestic vs. imported fuels Fuel dependency
Energy efficiency Environmental protection Isolated vs. interconnected operations
Emergency supply Interruptible exchange Joint planning Short-term purchases/sales Joint ownership
Market orientation Etc.
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Once a Potential Generation Expansion Solution Is Found, Other Constraints Must Be Considered
Transmission planning and analysis Unit size Fuel supply Manpower requirements and training Financial Environmental impacts Infrastructure needs Plant location (siting analysis) Etc.
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Schematic Representation of the Planning Process and Consideration of Constraints
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Regional Perspective in Resource Planning Historically, electric utilities served a defined geographical service territory Utilities were constructing new generating capacity almost exclusively on
their service territory With wider integration of utility systems into larger interconnections, it was
possible to construct new capacity in other areas and transfer power via transmission lines (e.g., joint ownership)
Deregulation and restructuring of power sector allows consumers to choose their suppliers (e.g., green power suppliers)
Except for the distribution companies, the service territory boundaries are largely disappearing
Also, new market entrants can come into open markets (e.g., merchant power plants, load aggregators, etc.)
In competitive electricity markets, the investors are trying to construct new generating capacity in most profitable locations or areas
Koritarov - 026GridSchool 2010
Electricity Markets in North America The trend is toward establishing large electricity markets Large interconnections in a competitive environment should provide
positive pressure leading to: Increased efficiency of system operation Lower average market prices of electricity
Koritarov - 027GridSchool 2010
Economic and Reliability Benefits of Large System Interconnections
Lower operating costs Higher utilization of most economical units Large pool of available generating units provides more flexibility in scheduling and dispatch
Demand diversity Simultaneous peak load of several interconnected systems is usually lower than the sum of
individual (non-coincidental) peak loads Merit order investments into new projects
Most economical new projects are built first Better utilization of renewable sources
Overcome uneven geographical distribution of renewable resources Allow for higher penetration of renewable resources
Economy of scale and joint ownership Some projects may be too big for individual systems
Lower total investment costs Larger units have lower specific costs per kW Lower total reserve margin requirements
Lower total contingency reserve requirement Shared spinning reserve
Power exchanges and emergency supply
Koritarov - 028GridSchool 2010
The Peak Load for Interconnected System is Usually Smaller than the Sum of Individual Peak Loads
Combined system peak: 7400MW
Combined system peak: 7400MW
Individual peaks: 3300 + 4500 = 7800 MW
Individual peaks: 3300 + 4500 = 7800 MW
4,500 MW
3,300 MW
7,400 MW
Benefits:Build less capacityBuild bigger units
Koritarov - 029GridSchool 2010
Reserve Sharing
Contingency reserve sharing agreements reduce operating costs The system needs to maintain enough reserve to cover the largest
single hazard Typically, the system should be able to cover the demand even if an
outage of the largest unit in operation should occur
ASystem ALargest Unit =
600 MW
System BLargest Unit =
600 MW
Both systems maintain contingency reserve of 600 MW each
A. Independent operation B. Interconnected operation
System ALargest Unit =
600 MW
System BLargest Unit =
600 MW
Total contingency reserve required for both systems is 600 MW
CR=600 MW
CR=600 MW
CR=300 MW
CR=300 MW
Koritarov - 030GridSchool 2010
Regional Transmission Planning for Better Utilization of Renewable Energy Resources
JCSP’08: 20% Wind ScenarioJCSP’08: 20% Wind Scenario
Wind PowerWind Power
Koritarov - 031GridSchool 2010
Case Study: Where to Locate the First Nuclear Plant in Poland? The expansion analysis
determined that nuclear power in Poland will be needed from 2017
The locational analysis was performed using simplified zonal representation of the Polish power grid and interconnections with neighboring countries
5 potential locations in zones/regions of Poland were considered
1 potential location outside of Poland (in Lithuania) was also considered
Legend:Transmission NodesThermal UnitsHydro UnitsNon-Dispatchable Units
New interconnectionLegend:
Transmission NodesThermal UnitsHydro UnitsNon-Dispatchable Units
New interconnection
Koritarov - 032GridSchool 2010
Analysis Showed that Nuclear Plant Should Be Constructed in the Northern or Western Regions of Poland
In a completely deregulated market, locational marginal prices (LMPs) show the economic strain on the grid. The analysis examined the impacts on LMP electricity prices resulting from different zonal locations of new nuclear plant.
Average LMP price reduction for different locations of new nuclear plant:
Koritarov - 033GridSchool 2010
A Nuclear Plant Located in the Northern or Western Regions Also Reduces Volatility of Electricity Prices
Average monthly LMP price volatility index by zone for different locations of new nuclear plant:
Without Northern Western Central Eastern Southern
Nuclear Zone Zone Zone Zone Zone LithuaniaZone (%) (%) (%) (%) (%) (%) (%)
North 621.10 7.49 47.56 618.39 570.95 356.68 688.61
West 289.11 5.88 34.30 278.21 229.43 143.89 283.27
Central 274.60 2.55 3.09 61.71 65.32 5.58 41.10
East 93.09 1.60 4.19 24.67 38.07 16.16 26.35South 115.37 1.73 10.43 63.70 68.23 38.91 66.02
Poland 213.29 3.02 26.18 201.95 173.78 111.15 207.29
Koritarov - 034GridSchool 2010
Argonne’s Approach for Optimal Zonal Locations of New Capacity Additions in Interconnected Power Systems Locational analysis can be applied to several interconnected
systems or to a single system consisting of several zones. Each system or zone may have a number of generating units,
loads, or both. Firm bilateral contracts or exchanges can also be taken into
account when calculating available transfer capabilities.
A
FE
DCB
A B
DC
E F
Koritarov - 035GridSchool 2010
Decision Parameters Are Calculated for Each System or Zone
A
FE
DC
B
0.0
10.0
20.0
30.0
40.0
50.0
60.0
0 10000 20000 30000 40000 50000
Capacity [MW]
Pri
ce [$
/MW
h]
0.0
10.0
20.0
30.0
40.0
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60.0
0 10000 20000 30000 40000 50000
Capacity [MW]
Pri
ce [$
/MW
h]
0.0
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20.0
30.0
40.0
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60.0
0 10000 20000 30000 40000 50000
Capacity [MW]
Pri
ce [$
/MW
h]
0.0
10.0
20.0
30.0
40.0
50.0
60.0
0 10000 20000 30000 40000 50000
Capacity [MW]
Pri
ce [$
/MW
h]
0.0
10.0
20.0
30.0
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0 10000 20000 30000 40000 50000
Capacity [MW]
Pri
ce [$
/MW
h]
0.0
10.0
20.0
30.0
40.0
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0 10000 20000 30000 40000 50000
Capacity [MW]
Pri
ce [$
/MW
h]
RM =
LOLP =
ENS =
MCP =
Economic
Resource
Environmental
Status in 2007 (Base Year)
RM =
LOLP =
ENS =
MCP =
Economic
Resource
Environmental
RM =
LOLP =
ENS =
MCP =
Economic
Resource
Environmental
RM =
LOLP =
ENS =
MCP =
Economic
Resource
Environmental
RM =
LOLP =
ENS =
MCP =
Economic
Resource
Environmental
RM =
LOLP =
ENS =
MCP =
Economic
Resource
Environmental
Koritarov - 036GridSchool 2010 36
Decision Parameters Change over Time
A
FE
DC
B
0.0
10.0
20.0
30.0
40.0
50.0
60.0
0 10000 20000 30000 40000 50000
Capacity [MW]
Pri
ce [$
/MW
h]
0.0
10.0
20.0
30.0
40.0
50.0
60.0
0 10000 20000 30000 40000 50000
Capacity [MW]
Pri
ce [$
/MW
h]
0.0
10.0
20.0
30.0
40.0
50.0
60.0
0 10000 20000 30000 40000 50000
Capacity [MW]
Pri
ce [$
/MW
h]
0.0
10.0
20.0
30.0
40.0
50.0
60.0
0 10000 20000 30000 40000 50000
Capacity [MW]
Pri
ce [$
/MW
h]
0.0
10.0
20.0
30.0
40.0
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60.0
0 10000 20000 30000 40000 50000
Capacity [MW]
Pri
ce [$
/MW
h]
0.0
10.0
20.0
30.0
40.0
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0 10000 20000 30000 40000 50000
Capacity [MW]
Pri
ce [$
/MW
h]
New line from 2012!
~ ~
~
~
~~ ~ ~
New generating units built
between the base year and 2015! Reinforcement
of this line from 2009!
Updated parameters!
Updated supply and demand
curves!
Status in 2015
Updated environmental regulations!
Updated social parameters!
RM =
LOLP =
ENS =
MCP =
Economic
Resource
Environmental
RM =
LOLP =
ENS =
MCP =
Economic
Resource
Environmental
RM =
LOLP =
ENS =
MCP =
Economic
Resource
Environmental
RM =
LOLP =
ENS =
MCP =
Economic
Resource
Environmental
RM =
LOLP =
ENS =
MCP =
Economic
Resource
Environmental
RM =
LOLP =
ENS =
MCP =
Economic
Resource
Environmental
Koritarov - 037GridSchool 2010
The Approach Takes into Account Multiple Criteria for the Siting of New Capacity
A
C
B0.0
10.0
20.0
30.0
40.0
50.0
60.0
0 10000 20000 30000 40000 50000
Capacity [MW]
Pri
ce [$
/MW
h]
0.0
10.0
20.0
30.0
40.0
50.0
60.0
0 10000 20000 30000 40000 50000
Capacity [MW]
Pri
ce [$
/MW
h]
0.0
10.0
20.0
30.0
40.0
50.0
60.0
0 10000 20000 30000 40000 50000
Capacity [MW]
Pri
ce [$
/MW
h]
RM = 5%
RMi = 35%
ZP = 50$/MWh
Resource
Social, etc
RM = 10%
RMi = 18.3%
ZP = 30$/MWh
Resource
Social, etc.
RM = 10%
RMi = 27.5%
ZP = 45$/MWh
Resource
Social, etc.
L = 1000 MW
P = 1050 MW
L = 3000 MW
P = 3300 MW
L = 2000 MW
P = 2200 MW100
100
300
300
200 200
Max LUF[RM(x), RMi(x), ZP(x)] = f[a × RM(x), b × RMi(x), c × ZP(x)]subject to resource, social, and other constraints
RM = Reserve margin
RMi = Reserve margin with interties
ZP = Isolated zonal price
Case study: By varying the weight coefficients a, b, and c in the equation below, the user may put more or less importance on certain criteria that maximize the locational utility function (LUF):
Koritarov - 038GridSchool 2010
Resource, Social and Other Siting Constraints Are also Observed Some resource, social, environmental, and other constraints
may restrict the siting of certain generating technologies in some zones
A matrix of these exclusion constraints is provided to the model to take into account the zonal restrictions over the study period
Example:
0 = siting not allowed in this year1 = siting allowed
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020A 0 0 0 0 0 0 0 0 0 0 0 0 0 0B 1 1 1 1 1 1 1 1 1 1 1 1 1 1C 1 1 1 1 1 1 1 1 1 1 1 1 1 1A 1 1 1 1 1 1 1 1 1 1 1 1 1 1B 0 0 0 0 0 0 0 0 0 0 0 0 0 0C 1 1 1 1 1 1 1 1 0 0 0 0 0 0A 1 1 1 1 1 1 1 1 1 1 1 1 1 1B 1 1 1 1 1 1 1 1 1 1 1 1 1 1C 0 0 0 0 0 0 1 1 1 1 1 1 1 1
Imp. Coal
Nuclear
YEARTECHNOLOGY ZONE
Lignite
Koritarov - 039GridSchool 2010
The Results of the Analysis Provide Information on Zonal Locations of New Capacity Additions
The results of siting analysis are summarized in a table:
0, 1, 2,.. = Number of units commissioned in this year
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020AB 1 1C 2A 1 1 2 1BC 2AB 1 1C 1 1A 1BC 2 1A 2 2B 1 2C 3 2
NGCC
Gas Turbine
YEAR
Lignite
Imp. Coal
Nuclear
TECHNOLOGY ZONE
Koritarov - 040GridSchool 2010
In Conclusion, Resource Planning Is a Very Complex Process Coordination of system planning categories Coordination with overall energy system planning and macroeconomic
development Numerous uncertainties:
Demand forecast Technology performance Fuel availability and cost Financial conditions, etc.
Long time horizons Enormous number of alternative long-term expansion pathways or
scenarios For each particular generating system configuration, system operation
also must be optimized