generating capacity expansion and system interconnections g rid s chool 2010 m arch 8-12, 2010 r...

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Do not cite or distribute without permission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


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


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


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


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)


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


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


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


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


In an Open Market, An Individual GenCo Will Make Investment Decisions That it Perceives Are “Best for the Company”

-10-5

05

10

xi1

-10

-50

510

xk1

-4000

-3000

-2000

-1000

0

QP

-4000

-3000

-2000

-1000

0

QP

-10-5

05

10

xi1

-10

-50

510

xk1

-4000

-3000

-2000

-1000

0

QP

-4000

-3000

-2000

-1000

0

QP

-10-5

05

10

xi1

-10

-50

510

xk1

-4000

-3000

-2000

-1000

0

QP

-4000

-3000

-2000

-1000

0

QP

-10-5

05

10

xi1

-10

-50

510

xk1

-4000

-3000

-2000

-1000

0

QP

-4000

-3000

-2000

-1000

0

QP

-10-5

05

10

xi1

-10

-50

510

xk1

-4000

-3000

-2000

-1000

0

QP

-4000

-3000

-2000

-1000

0

QP

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!


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.


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


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


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


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?


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.


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)


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.


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


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%)


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.


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.


Schematic Representation of the Planning Process and Consideration of Constraints


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


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


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


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


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


Regional Transmission Planning for Better Utilization of Renewable Energy Resources

JCSP’08: 20% Wind ScenarioJCSP’08: 20% Wind Scenario

Wind PowerWind Power


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


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:


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


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


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

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

50.0

60.0

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

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]

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


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):


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


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


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

generating capacity expansion and system interconnections g rid s chool 2010 m arch 8-12, 2010 r...

Documents

planning process

system slide

system expansion analysis

strategic resource planning

planning methodology

analysis process

plan slide

longterm system expansion