U.S. Energy Information Administration Independent Statistics & Analysis www.eia.gov

Overview of renewable technologies in the National 

Energy Modeling System (NEMS)

For

Workshop:

March 7, 2017 | Washington, D.C.

By

Cara Marcy

Renewable Electricity Analyst
• Renewable electricity technologies 

represented in NEMS include:

– Biomass-Wood

– Biomass-Municipal solid waste/ 

Landfill gas

– Geothermal

– Conventional hydropower

– Solar‐thermal

– Solar‐photovoltaic

– Wind-onshore

– Wind-offshore

Eight different utility-scale renewable electricity technologies are 

represented in the model

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non-dispatchable, 

e.g. intermittent 

or variable

seasonal/

energy limited
• Can be used in dedicated, direct-fired biomass plants or cofired with coal

– Much biomass generation comes from the pulp/paper industry

– This cogeneration is accounted for in the industrial sector

• Previous AEOs saw a lot of cofiring, but several factors make this less 

attractive now, including lower cost alternatives and pressure on existing coal 

plants

• Fuel derived from urban wood waste, forestry residues, agricultural residues, 

and energy crops

– Urban wastes and forestry are the lowest-cost resources

• MSW/LFG model is dated and currently under revision

Biomass

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Conventional Hydropower

• Provides available supply of new conventional hydroelectric generating capacity 

that can be built at known and well-characterized sites

– > 1 MW, < $0.10/kWh

– Based on list of known conventional hydro sites – 1299 sites, 22 GW potential

– 3-step supply function – by year, region

• Average cost

• Performance characteristics

• Aggregate capacity

• Hydro is dispatched on an energy-constrained basis

– Dispatches at full capacity into the highest-value period within a season

– Dispatches into the next highest-value period until seasonal energy is exhausted

Cara Marcy, Washington D.C. 

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Geothermal

• Like hydro, geothermal supply is described by a list of specific, known sites

– Least-cost sites are high-quality hydrothermal resources using dual flash or binary turbines

– “Near-field” sites are extensions of existing resource areas that may require engineering of 

rock to stimulate flow (such as through hydraulic fracturing)

• Based on historic experience, the build-out of any given site is limited to 25 

MW per year

– Helps developers better manage the resource

– Results in slow build-out, despite sometimes favorable economics

• With high availability and low variable cost, geothermal is dispatched as 

baseload

Cara Marcy, Washington D.C. 

March 7, 2017 5
• Wind and solar technologies are 

non-dispatchable and therefore are 

dependent on the availability of the 

resource by: – location – time

• However the model’s representation of 

regions and time for capacity planning 

decisions is limited – 22 regions – 9 time slices

Wind and Solar

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March 7, 2017 

6
• NREL supplied EIA with 335 locations, 5 

randomly selected for each 1⁄2 kWh class 

in each NEMS region

• EIA used SAM to calculate the hourly 

capacity factor for each location

• The locational 8760 capacity factors 

were averaged by NEMS region and the 

hourly values were aggregated into a 

12X24 (month/hour) matrix

Site specific solar resource data was averaged to develop 

capacity factors for each of the 22 regions in NEMS

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• Each NEMS region represents 4 wind 

resource classes (6&7 are combined):

• Each sub-category 

(NEMS region / wind resource class) 

contains 5 cost multipliers, ranging from 

1 to 2, representing the cost integration 

challenges, e.g. dist. to transmission

U.S. available wind capacity by resource class

gigawatts (GW)

Similar for wind, but the 22 regions contains a supply curve that 

breaks out the wind resource into 4 representative wind classes

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March 7, 2017 

0

1000

2000

3000

4000

5000

6000

3 4 5 6 7

wind classes

Wind Class Average Annual Wind

Speed (mph)

7 19.6 +

6 17.9 – 19.6

5 16.8 – 17.9

4 15.7 – 16.8

3 14.3 – 15.7

8
• Loads is computed for 864 time slices 

(24 hours X 12 months X 3 day types)

• PV and wind capacity factors are 

provided by 24 hours X 12 months

• A minimum level of generation from 

nuclear and coal is established

• Excess solar generation is evaluated 

counts against future planning decisions

0

10

20

30

40

50

60

70

80

0 6 12 18 0 6 12 18 0 6 12 18

hours (3 day types in June)

load

solar

coal and nuclear

generation profile for estimated curtailments, example

gigawatthours (GWh)

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Curtailments are estimated based on hourly load, non-dispatchable 

generation, and minimum generation levels from coal and nuclear

9
• For conventional technologies, the 

amount of capacity available at peak is a 

function of their forced outage rates

• Even though wind and solar technologies 

are intermittent, they still contribute to 

regional effective load carrying capacity

• However as the penetration of intermittent 

technologies increase, their marginal 

contribution towards regional reliability 

reserves declines

Decline in wind’s marginal capacity value, example

percent

Cara Marcy, Washington D.C. 

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Declining marginal capacity value for intermittent generation accounts 

for inherent intermittency affects

10

0%

5%

10%

15%

20%

25%

30%

35%

40%

0% 5% 10% 15% 20%

marginal capacity value

wind penetration
Looking forward

• Other enhancements for the model that address intermittency of renewable 

technologies include:

– Developing curtailment using 864 time slides for wind

– Integrating energy storage

– Estimating the marginal capacity value using 864 time slices

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For more information

Assumptions Document | http://www.eia.gov/forecasts/aeo/assumptions/

Model Documentation | http://www.eia.gov/outlooks/aeo/nems/documentation/ 

Annual Energy Outlook | www.eia.gov/aeo

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• Because the variance of wind is 

larger than the variance of 

conventional generation, it 

increases the “spread” of the 

availability distribution

• The tails increase in height, so the 

critical “Z” value doesn’t increase 

proportionate to the average

Wind (or solar) increases the average availability, but 

reliability is determined at the lower tail of the distribution

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4 4 4 6 4 8 5 0 5 2 5 4

Capacity (GW)

Probability of Output

Lower 99.9% of Availability

Avg. Availability (no wind)

Avg. Availability (+2.5% wind)

Avg. Availability (+5% wind)

Avg. Availability (+7.5% wind)