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National Energy 

Technology Laboratory

Characterizing and Modeling Cycling 

Operations in Coal-fired Units

June 2016

Chris Nichols

Systems Engineering & 

Analysis Directorate

EIA Modeling Meeting
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Technology Laboratory

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Average capacity factor (%)

Unit age in years

Average capacity factor by unit age for coal operations, 1998-2013

The “Over the Hill” plot - Examining 

Historic Coal Unit Capacity Factors

Data source and notes: Data from Ventyx's Energy Velocity. Unit age in each year was calculated then averaged

Many factors involved in capacity factor, but 

the sharp definition on the plot warranted 

investigation of possible age-related causes
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Technology Laboratory

Overview of current NETL work in this area

• Characterization of operating modes of retiring 

units

– Defining the modes of operation and classifying units

• Cycling impacts

– Literature review and technical discussion

– Model integration and preliminary results

• Future work
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Characterizing operating modes

• MS Access tool developed to view and sort units retiring 

between 2010 & 2020 by operating mode (~300 units total):
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Characterizing operating modes

• MS Access tool shows capacity factor by unit for specified 

time period:
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Technology Laboratory

Characterizing operating modes

Baseload

Two-shifting
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Technology Laboratory

Characterizing operating modes

LF1 LF2

LF3
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Technology Laboratory

Characterizing operating modes

2008 - Baseload 2009 – LF3/TS

Eastlake, Unit 5

Continued LF operations until retirement in 2010 
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Technology Laboratory

Characterizing operating modes

• Most Retiring Units Were Load Following in 2008-2014
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Cycling impacts – literature review and engineering analysis

Cycling I
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Technology Laboratory

Known Physical Processes that Increase Heat 

Rate and Cause Forced Outages

• Wear of seals and turbine blades

• Fouling and deposition on heat transfer surfaces and steam 

turbine blades

• Aging of refractories and structural shells, particularly boilers

• Component failure from corrosion, fatigue, and creep

• Interaction of fatigue and creep under cycling

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Forced outage rates higher for cycling units

• About 3% for baseload units

• About 7% for cycling units

Baseload Cycling

Age, service years 

Forced Outage Rate, %
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Technology Laboratory

Component Failure Impacts

• Failure of a boiler or condenser tube has very different 

impact than failure of a turbine or generator 

Source: Kumar, N., et al, Power 

Plant Cycling Costs, NREL/SR5500-55433

Most boiler tube failures 

cause about 100 hour 

outage, almost none 

more than 350 hours.

About 10% of generator 

failures cause > 1200 

hours outage.
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Technology Laboratory

Fleet Heat Rate Trends

(Data source: EIA Table A6. Approximate Heat 

Rates for Electricity, and Heat Content of 

Electricity, Published October 28, 2014)

Table 1. Existing Technology Comparison, 5 Year Average

Technology No. Units Total Capacity, 

MW

NFOM, 

$/MWh

EAF, 

%

Efficiency (HHV), 

%

Small Subcritical 228 49,686 14.54 82.7 31.8

Large Subcritical 65 40,111 9.09 85.1 33.0

Supercritical 85 66,469 11.69 79.6 34.4

Source: Table courtesy of Navigant Consulting, Inc., 

based on “Generation Knowledge Service”, 2010 -

2014

Empirical fleet data indicates persistent heat rate increases across 

technologies
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Technology Laboratory

Interaction of Creep and Fatigue

EPRI 2001 Report: “Where operational cycling is 

introduced on a former baseload unit, the 

residual life can be greatly reduced to between 

40% and 60% of the original design life because of 

the combined effects of creep and fatigue.”

Effect of temperature ramp 

rate

Source: Fleming and Foster, 

Aging of Coal Fired Power 

Plants

Typical plant 

metallurgy

Typical design 

basis of legacy 

CFPP
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Technology Laboratory

Boiler Material Failures

Boiler tube corrosion

Waterwall web 

cracking

Superheater tube 

attachment fatigue 

cracking

Source: Lefton, Power Plant 

Asset Management
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Technology Laboratory

Massive caustic attack

Caustic gouging. This cutaway view 

shows a tube that experienced 

caustic attack in a cyclone inlet roof 

tube. The plant commenced load 

cycling about one year prior to this 

failure. Courtesy: David N. French 

Metallurgists

This is from a supercritical unit where 

cyclones are in the steam path rather 

than a steam drum
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Technology Laboratory

Steam Turbine Failures

Source: Lefton, S., Power Plant Asset Management, Intertek AIM
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Cycling impacts – ESIM model integration and initial results

Cycling I
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Development of cycling Scenarios

• Heat rate guidance from EIA-923 (2014) and EIA-860

– Filtered data ranked into quintiles

– Midpoints of first, third, and fifth quintile taken to represent heat rates

• Operating periods based on literature and judgement

• Residual plant life in various operating modes taken to be 

reasonable

– Little hard data on this

– Known to be impacted by plant maintenance and investment

– External-to-plant factors impact retirement decisions

– Should not be taken to represent any specific plant
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Operating Modes in scenario Modeling

• Mode 1

– Runs 24 x 5 but does some load following, 85% effective capacity while 

running. One warm shutdown and startup per week. Annualized CF 51.6%, 

residual life 10 years

• Mode 2

– Runs 16 hours per weekday, averaging 85% effective capacity. Six warm 

shutdowns and startups per week. Annualized CF 34.4%, residual life 5 years

• Mode 3

– Runs 12 hours per weekday in two six hour periods, averaging 92 -95% 

effective capacity. Eleven warm shutdowns and startup per week. Annualized 

CF 28.8%, residual life 3 years

• All cases assume 85% availability and 30+ years of service at outset of 

cycling
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Developing the endogenous function

The model constructed a cycling damage function with 

interpolation between three operating modes.

Endogenous retirement occurs when a unit accumulates 300 points.

Penalty score 

assignment

Years to acquire 300 

points

Modest cycling 30 points/year 10

Medium cycling 60 points/year 5

Severe cycling 100 point/year 3
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Cycling damages eventually results in endogenous unit 

retirements
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Damages accumulate as Cycling continues and generally 

worsens over time Damage points
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Endogenous coal retirements accelerated 

by damage function

Model projected coal unit retirements
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Technology Laboratory

Calibrating the damage function will be 

key to assessing the impacts

Sensitivity of Existing CFPP US Generation to a plausible range 

of cycling damage assumptions
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Technology Laboratory

Next steps and future work

• Publication of cycling literature review and ESIM model 

integration late Summer

– Follow-on work pending to show benefits of sensors and controls 

(lower damage points) R&D

• Multi-scale modeling pilot effort (engineering to grid to 

market) underway to model cycling impacts

– Engineering models will generate data to feed to grid level model, 

market level model will generate scenarios

• Longer term, multi-year effort proposed to further develop 

data and create dynamic model linkages
NETL

the ENERGY lab

Delivering Yesterday and Preparing for Tomorrow

ut a Clean, Affordable Energy Future

For More Information, Contact:

Chris Nichols, 

Systems Engineering and Analysis Directorate

Christopher.nichols@netl.doe.gov

304 285 4172

National Energy 

Technology Laboratory 28