Article

The Role of Firm Low-Carbon Electricity
Resources in Deep Decarbonization of Power
Generation
Nestor A. Sepulveda, Jesse D.
Jenkins, Fernando J. deSisternes, Richard K. Lester
nsep@mit.edu (N.A.S.)
rklester@mit.edu (R.K.L.)

HIGHLIGHTS
Firm low-carbon resources
consistently lower decarbonizedelectricity system costs
Availability of firm low-carbon
resources reduces costs 10%–62%
in zero-CO2 cases
Without these resources,
electricity costs rise rapidly as CO2
limits near zero
Batteries and demand flexibility
do not substitute for firm lowcarbon resources

Full decarbonization of the electricity sector is critical to global climate mitigation.
Across a wide range of sensitivities, firm low-carbon resources—including nuclear
power, bioenergy, and natural gas plants that capture CO2—consistently lower thecost of decarbonizing electricity generation. Without these resources, costs rise
rapidly as CO2 limits approach zero. Batteries and demand flexibility do not
obviate the value of firm resources. Improving the capabilities and spurring
adoption of firm low-carbon technologies are key research and policy goals.

Sepulveda et al., Joule 2, 2403–2420
November 21, 2018 ª 2018 Elsevier Inc.
https://doi.org/10.1016/j.joule.2018.08.006

Article

The Role of Firm Low-Carbon
Electricity Resources in Deep
Decarbonization of Power Generation
Nestor A. Sepulveda,1,2,4,* Jesse D. Jenkins,2 Fernando J. de Sisternes,3 and Richard K. Lester1,*

SUMMARY

Context & Scale

We investigate the role of firm low-carbon resources in decarbonizing power
generation in combination with variable renewable resources, battery energy
storage, demand flexibility, and long-distance transmission. We evaluate nearly
1,000 cases covering varying CO2 limits, technological uncertainties, andgeographic differences in demand and renewable resource potential. Availability of firm low-carbon technologies, including nuclear, natural gas with carbon
capture and sequestration, and bioenergy, reduces electricity costs by 10%–62% across fully decarbonized cases. Below 50 gCO2/kWh, these resources
lower costs in the vast majority of cases. Additionally, as emissions limits
decrease, installed capacity of several resources changes non-monotonically.
This underscores the need to evaluate near-term policy and investment decisions based on contributions to long-term decarbonization rather than interim
goals. Installed capacity for all resources is also strongly affected by uncertain
technology parameters. This emphasizes the importance of a broad research
portfolio and flexible policy support that expands rather than constrains future
options.

Mitigating climate change while
fueling economic growth requires
decarbonizing the electricity
sector at reasonable cost. Somestrategies focus on wind and solar
energy, supported by energy
storage and demand flexibility.
Others also harness ‘‘firm’’ lowcarbon resources such as nuclear,reservoir hydro, geothermal,
bioenergy, and fossil plants
capturing CO2. This paper
presents a comprehensive
techno-economic evaluation of
two pathways: one reliant on
wind, solar, and batteries, andanother also including firm lowcarbon options (nuclear,bioenergy, and natural gas withcarbon capture andsequestration). Across all cases,
the least-cost strategy todecarbonize electricity includes
one or more firm low-carbon
resources. Without theseresources, electricity costs rise
rapidly as CO2 limits approachzero. Batteries and demand
flexibility do not substitute for firm
resources. Improving thecapabilities and spurring
adoption of firm low-carbon
technologies are key research andpolicy goals.

INTRODUCTION
Full decarbonization of the electric power sector will be pivotal to global climate
mitigation efforts. The Paris Climate Agreement of 2015—ratified by 176 countries
to date—declares the need to hold increases in global average temperatures to‘‘well below’’ 2 C and to achieve a net balance of anthropogenic sources and sinksof greenhouse gases by the second half of this century.1,2 To reach these goals,
recent studies have concluded that CO2 emissions from electricity generationmust fall nearly to zero3–5 or even below zero6–8 by mid-century, even as electricity
generation expands to supply a greater share of transportation, heating, and industrial energy use.3,9–11
Despite general agreement on the need for deep decarbonization of the electric power sector, views differ as to the relative importance of various low-carbon electricity
resources in near-zero-emissions power systems.
Technological developments have enlarged the array of low-carbon electricity generation resources to include solar, wind, hydro, biomass, nuclear, geothermal, andfossil energy with carbon capture and sequestration (CCS). Technologies for energy
storage and for managing electricity demand are also available. The economic andoperational characteristics of these resources vary, as does their ability to contributeto meeting electricity demand reliably. As a result of this diversity, power systems are

Joule 2, 2403–2420, November 21, 2018 ª 2018 Elsevier Inc. 2403

likely to benefit from harnessing a blend of resources, with the various resource types
playing complementary roles and adding distinct value to the overall mix of energy
services.
Electricity generation technologies have traditionally been classified based on theirrelative variable costs and the resulting frequency with which they are called upon tomeet electricity demand or ‘‘load’’; e.g., ‘‘baseload,’’ ‘‘load-following,’’ and ‘‘peaking’’ resources. This classification is no longer meaningful in power systems with substantial penetration of wind and solar energy, since dispatch of each technology isalso driven by the irregular variability of these renewable resources. Moreover,most available low-carbon technologies are capital intensive and have very low
variable costs. In this context, the distinguishing attributes of electricity technologies
relate more to their resource availability and ability to adapt production output inorder to meet instantaneous demand. We therefore propose a new taxonomy that
divides low-carbon electricity technologies into three different sub-categories (seeFigure S1):
1. ‘‘Fuel-saving’’ variable renewable energy (VRE) resources. These include wind
power, solar photovoltaics (PV), concentrating solar power, and run-of-riverhydropower. They harness renewable energy inputs (wind, solar insolation,water) that vary on timescales ranging from seconds to hours to seasons,have zero (or near-zero) variable costs, and have no fuel costs. At lower penetration levels, they may displace the need for firm capacity, but, at higher
shares, capacity needs are driven by periods with low VRE availability. At
high energy shares, these technologies therefore contribute value primarily
by displacing other higher variable cost generating technologies wheneveravailable and reducing the total fuel consumption and variable costs of thesystem.
2. ‘‘Fast-burst’’ balancing resources. These include short-duration energy
storage (e.g., Li-ion batteries), flexible demand (or schedulable loads),
and demand response (or price-responsive demand curtailment). They
are either energy constrained (storage, demand flexibility) or have very
high variable cost (demand curtailment). These technologies are therefore
poorly suited to operating continuously over long periods of time andare better used during high-value periods when relatively fast bursts ofpower or quick demand adjustments are needed to balance supply anddemand.
3. ‘‘Firm’’ low-carbon resources. These are technologies that can be counted on
to meet demand when needed in all seasons and over long durations (e.g.,weeks or longer) and include nuclear power plants capable of flexible operations,12–15 hydro plants with high-capacity reservoirs, coal and natural gas
plants with CCS and capable of flexible operations,16,17 geothermal power,
and biomass- and biogas-fueled power plants.7
In light of recent cost improvements and the rapid expansion of wind power andsolar photovoltaics, many recent papers have explored opportunities and challenges associated with achieving very high shares of these VRE resources in powersystems.18–33 Much of this work has focused on how to provide the enhanced operational flexibility on various time scales (from seconds to seasons) needed to balancevariable output from high shares of wind and solar energy,21–23,28 including thepotential role of energy storage,24,29,34,35 demand-side flexibility,20 and long-distance transmission expansion to smooth variability of renewable output across wider
geographic areas.20,27,312404 Joule 2, 2403–2420, November 21, 2018

1Department of Nuclear Science andEngineering, Massachusetts Institute ofTechnology, Cambridge, MA 02139, USA

2Institute for Data, Systems, and Society,

Massachusetts Institute of Technology,
Cambridge, MA 02139, USA

3Center for Energy and Environmental Policy

Research, Massachusetts Institute of Technology,
Cambridge, MA 02139, USA

4Lead Contact*Correspondence: nsep@mit.edu (N.A.S.),
rklester@mit.edu (R.K.L.)
https://doi.org/10.1016/j.joule.2018.08.006

Some of this work has excluded firm low-carbon resources ex ante, in part because of
the societal challenges or current costs associated with some of these resources.
Other research17,23,34–36 has found that harnessing firm low-carbon resources
capable of responding to variations in both demand and renewable energy output
can lower the cost of low-carbon power systems by reducing the amount of needed
generating and storage capacity, improving asset utilization, and avoiding substantial curtailment of renewable energy output. These studies have typically focused on
the role of a specific resource (e.g., energy storage34,35 or CCS17) and have exploreda relatively narrow range of possible uncertainties.23
Global deployment of nuclear and CCS is lagging well behind the pace envisioned
by scenarios to limit global warming to 2 C in the 2014 Intergovernmental Panel on
Climate Change assessment report.37 Both technologies face a range of challenges
to greater adoption, including high construction costs and financial risks, technology
immaturity (in the case of CCS and next-generation nuclear designs), and risk (bothreal and perceived). Use of biomass for energy is currently on pace with global 2 C
scenarios,37 but large-scale reliance on bioenergy for power generation competes
with other land uses, including food and environmental conservation, as well asother uses for bioenergy in transportation, heat, and industrial sectors. Other firm
low-carbon resources are constrained to specific favorable geographies (conventional geothermal, reservoir hydropower), entail significant environmental impacts(reservoir hydro), or remain pre-commercial (enhanced geothermal energy systems).
Overcoming challenges to large-scale use of these firm low-carbon resources may
prove difficult. Whether it makes sense to take on this task depends partly on thebenefits associated with having one or more viable firm low-carbon resources available to contribute to power sector decarbonization.
In this paper we provide a more comprehensive evaluation of the economic andoperational benefits of firm low-carbon technologies in achieving deep decarbonization targets, with a focus on nuclear, natural gas with CCS, biogas, and biomass.
The analysis examines the interactions between these firm low-carbon resources;
fuel-saving variable renewable resources; and fast-burst resources, including
short-duration battery energy storage and demand-side flexibility. It also investigates the impact of long-distance transmission interconnections.
We use an advanced electric power system investment and operations model38 tocompare, under several increasingly ambitious decarbonization targets, the economic performance of two kinds of power systems: those that include firm low-carbon technologies among the available resources, and those that exclude these firm
resources ex ante. Operational details captured by the model include a full year ofhourly chronological variability in both renewable energy output and electricity
demand and detailed power system operating constraints such as integer power
plant start-up and shut-down costs, minimum stable output limits for thermal power
plants, and limits on hourly changes in power plant output. Commonly used but
simpler models can result in significant errors due to abstraction of relevant powersystem details and the failure to account for the full variability of renewable
resources and inter-temporal constraints on energy storage and thermal power
plants.26,39–42
A large number of scenarios are analyzed. First, we account for geographic differences in renewable resource potential and patterns of demand using data fromtwo dissimilar US regions: a ‘‘northern’’ system with the demand profile and relatively
modest renewable resource potential typical of New England (peak demand of

Joule 2, 2403–2420, November 21, 2018 2405

Table 1. Technological Assumptions
Technology

ConservativeMid-range

Very Low

Solar ($/kW-AC)

1,800a900b

670c

Wind ($/kW)

1,455d

1,091e927f

4-hr Li-ion battery ($/kWh)

440g

220h

110i

6-hr Li-ion battery ($/kWh)

420

i

j

105i

Natural gas CCGT with CCS($/kW) (CO2 capture rate)NA1,720 (90%)k

1,050 (100%)l

Nuclear ($/kW) (size)

7,000 (1,000 MW)m

4,700 (1,000 MW)n4,200 (300 MW)o

Biomass ($/kW) (maximum
energy share) ($/MMBTU)

3,800 (5%) (3)p3,800 (5%) (3)p3,400 (35%) (7)q

Biogas ($/kW) (maximum
energy share) ($/MMBTU)

NA

890 (2%) (7.5)r790 (10%) (15)r

210

CCGT, combined-cycle gas turbine; NA, not available.
aFrom NREL43 2017 ‘‘Utility PV - Low.’’b
50% cost reduction from conservative.
c
From NREL43 2047 ‘‘Utility PV - Low.’’d
From NREL43 2017 ‘‘Land Base Wind, TRG 1 - Low.’’e
25% cost reduction from conservative.
f
From NREL43 2047 ‘‘Land Base Wind, TRG 1 - Low.’’g
From Lazard44 ‘‘Li-ion Peaker Replacement.’’h50% cost reduction from conservative.
i
75% cost reduction from conservative.
j
From Lazard44 ‘‘Distribution Substation.’’k
From NREL43 2047 ‘‘Gas-CC-CCS - Mid.’’l
Net power Nth of a kind plant, May 2015 briefing.
m
Based on Georgia Public Service Commission.45
nFrom NREL43 2047 ‘‘Nuclear.’’o
From IEA and NEA46 assuming modular reactor.
p
From NREL43 2017 ‘‘Biopower Dedicated - Mid.’’q
From NREL43 2047 ‘‘Biopower Dedicated - Mid.’’r
From NREL43 same as gas CT.

34 GW at 4:00 pm on a July weekday), and a ‘‘southern’’ system with the demand
profile and higher renewable resource availability characteristic of the Electricity
Reliability Corporation of Texas region (peak demand of 94 GW at 4:00 pm on an
August weekday).
Second, we account for uncertainties surrounding future technology costs and availabilities by introducing discrete cost assumptions (‘‘conservative,’’ ‘‘mid-range,’’and ‘‘very low’’; see Table 1) for each of three groupings of technologies: (1) VRE
resources (onshore wind and solar PV) and Li-ion battery energy storage (with 4
or 6 hr of output at maximum discharge rate; see footnotes in Table 2). (2) Light-water nuclear reactors and natural gas plants with CCS. (3) Biogas- and solid biomassfueled plants (see footnotes in Table 2). Using these cost assumptions, we construct
and analyze 19 technology cost and availability scenarios (see Table 2). Additionally, we analyze the impact of increasing flexibility in demand scheduling andprice-responsive demand curtailment, as well as the effect of increasing long-distance transmission interconnection capacity between the northern and southernsystems.
Third, we analyze the economic impact of different emissions reduction targets bymodeling each technology and regional scenario subject to seven progressively
more stringent CO2 emissions limits, from 200 gCO2/kWh down to zero emissions.
For context, the direct emissions rate of CO2 from power generation in the United

2406 Joule 2, 2403–2420, November 21, 2018

Table 2. Technological Scenarios
Scenario

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

VRE and storagea,b

C

M

M

M

L

L

L

M

M

M

L

L

L

M

M

M

L

L

L

b

Nuclear and CCS

C

C

C

C

C

C

C

M

M

M

M

M

M

L

L

L

L

L

L

Biomass andbiogasb

C

C

M

L

C

M

L

C

M

L

C

M

L

C

M

L

C

M

L

C, conservative; M, mid-range; L, very low technology cost assumptions (Table 1).
This analysis is limited to lithium-ion battery energy storage systems, which are currently widely scalable, face no geographic constraints, and are expected tobenefit from further cost reductions due to economies of scale, learning-by-doing, and spillovers from battery production for electric vehicles. Longer-duration
pumped-hydro storage resources are difficult to expand due to siting challenges, and medium- and long-duration energy storage options that may provide
longer-duration storage capacity (e.g., days rather than hours) are currently too costly or face scalability challenges. However, if a storage technology capableof supplying several days or more of sustained power output becomes economically and technically viable, this technology could serve as a firm low-carbon
resource (unlike shorter-duration battery storage). It would be productive for future research to explore the impact of long-duration energy storage options
on deep decarbonization and the cost and performance parameters necessary for very-long-duration storage to cost-effectively contribute to decarbonization.
b
These resources are grouped in order to keep the number of scenarios manageable. Solar, wind, and battery storage are grouped to reflect the more rapid paceof likely cost declines for these technologies. Nuclear and gas with CCS are likewise grouped based on their relatively high costs and slower rate of likely costdeclines. Finally, biomass and biogas resources are grouped to reflect their common feedstocks, with the three technology cases reflecting increasing levels offeedstock supply.
aStates in 2017 was 436.6 g/kWh. Emissions reductions pledged by the United States
under the Paris Agreement use 2005 as a baseline year, in which the CO2 emissions
rate from power generation was 595.8 g/kWh.47,48
Altogether we evaluate 912 distinct scenarios. A ‘‘core’’ set of 532 scenarios
comprises the 19 technology availability and cost scenarios in each of the two powersystems, subject to seven different decarbonization targets with and without firm
low-carbon resources. We also consider 380 ‘‘sensitivity’’ scenarios that explore
the effects of five different levels of demand-side resource availability and two levelsof long-distance transmission capacity linking the two power systems.
To our knowledge, this is the first work to systematically explore the feasibility
and cost of achieving deep decarbonization goals (up to 100% reductions in power sector CO2 emissions) across such a wide range of conditions and technology cost projections. This comprehensive analysis increases the robustness of
our findings.
The next two sections of the paper present the results of our analysis, focusing firston our core scenarios and subsequently on the impact of demand-side flexibility andincreased regional interconnections. This is followed by a discussion of the policy implications and recommendations, and a description of the experimental procedure
and assumptions used in our work.

RESULTS
Core Cases
Across the wide range of technology assumptions and power system characteristics
considered in our core scenarios, we find that the availability of firm low-carbon resources consistently reduces the system cost of decarbonizing power generation
relative to scenarios in which these resources are excluded from the eligible resource
mix. As Figures 1 and S2 illustrate, in the absence of firm low-carbon resources, thecost of decarbonizing power generation rises very rapidly as the emissions limit approaches zero. The cost of full decarbonization (zero CO2 emissions) without firm resources is from 42% to 163% higher in the northern system, and from 11% to 105%higher in the southern system, relative to cases in which firm low-carbon resources
are available. The precise difference in cost depends on specific technology cost

Joule 2, 2403–2420, November 21, 2018 2407

Figure 1. Average Cost of Electricity under Different Technology Assumptions and CO2 Emission Limits for the Northern and Southern Systems
For cost comparisons, compare visually each of the green (or orange or blue, depending on the VRE and storage cost assumptions) cases in the firstpanel (where firm resources are included) with the green case in the second panel (where firm resources are excluded). In the ‘‘very low’’ cost projection(green), wind and solar fall by roughly one-third and two-thirds relative to 2017 costs, respectively, and battery costs decline by roughly three-quarters(see Table 1).

2408 Joule 2, 2403–2420, November 21, 2018and availability assumptions. Even with very-low-cost projections for wind, solar, andenergy storage and conservative assumptions for firm low-carbon resources (i.e., thecosts of nuclear, natural gas with CCS, biomass, and biogas resources remain unchanged relative to their current levels), the cost of achieving zero carbon emissions
in each region is lower when firm resources are available than when they are not (seeFigure 1 legend).
These results suggest that firm low-carbon resources are particularly valuable in regions with more modest renewable energy potential (e.g., the northern system) andthat these technologies provide an effective hedge against the risk that additional
steep reductions in the cost of variable renewables may not be achieved. Moregenerally, the results indicate that including firm resources in the portfolio of available low-carbon technologies is a more robust strategy for achieving affordable
deep decarbonization of power generation.
The rapid increase in system cost as the emission limit approaches zero when firm
low-carbon resources are excluded contrasts with the much more gradual increase
when firm resources are available (Figure 1). The former behavior is explained by
the sharp decline in the marginal energy and marginal capacity substitution valueof VRE49,50 and battery storage35,36 technologies at high penetration levels. As Figure 2 demonstrates, VRE and batteries are only weak-capacity substitutes for firm
low-carbon resources, and significantly more than one megawatt of combined VRE
and storage capacity is required to replace one megawatt of firm low-carbon capacity
in equally reliable systems achieving the same CO2 emission reductions. To meet demand reliably during periods of low wind and solar availability, large amounts of VRE
capacity must be deployed, along with energy storage to shift available supply fromhigh to low VRE output periods. For zero emissions cases without firm resources, thetotal required installed generation and storage power capacity in each system would
be five to eight times the peak system demand, compared with 1.3–2.6 times peakdemand when firm resources are available (see Figure 2 legend). For example, inthe northern system assuming mid-range costs for all technologies, the total installed
power capacity with firm resources available is 48 GW, including 16 GW of VRE and 4
GW of storage capacity. In the absence of firm resources, the installed capacity of VRE
and storage would increase to 130 GW and 47 GW respectively. Additionally, fully
decarbonized cases without firm resources feature 320–1,160 GWh of installed energy storage capacity, versus 29–380 GWh when firm resources are available (Figure S15). We also demonstrate the robustness of our findings to the availability of
longer-duration storage technologies (see Figures S16–S18).
As VRE penetration increases, a growing share of annual VRE generation occurs during periods when a zero marginal cost resource (e.g., wind, solar) is the marginal
generator, reducing the energy substitution or fuel-saving value of VRE. In addition,
during periods of abundant wind and solar insolation, large installed VRE capacities
produce significant excess supply, and it is not cost-effective to build enough energy
storage capacity to accommodate all of this surplus. For example, in a fully decarbonized power system, the amount of available wind and solar output that would
be wasted due to curtailment in VRE-dominated scenarios would be sufficient to
supply 60%–130% of total annual electricity demand (Figure S3). In contrast, whenfirm low-carbon capacity can be deployed, wind and solar curtailment is reduced
to 0%–14% of total annual demand.
As the CO2 emissions limit grows more stringent, the energy share of high-carbon
resources in the least-cost resource portfolio declines monotonically, as expected.

Joule 2, 2403–2420, November 21, 2018 2409

Figure 2. Least-Cost Capacity Mix in the Northern and Southern Systems for Different Carbon Emission Limits
For each system, the plot shows the least-cost capacity mix for the technology scenario combinations of all conservative, all mid-range, and all very low costs for all
three groupings of resources, with the northern system on the left and southern system on the right. The top portion of the plot shows the resulting mix when firm lowcarbon capacity can be deployed, while the bottom portion shows the resulting mix when these resources are excluded. Note that the y axis has been re-scaled oneach sub-plot and a dotted line representing the peak demand of each system has been added as a visual reference. Battery storage capacity has been plotted ininstant capacity (MW) instead of energy capacity (MWh) for consistency with generation resources. See Figures S4 and S5 for the capacity mix under the full range ofdifferent scenario combinations. CCGT, combined-cycle gas turbine; OCGT, open-cycle gas turbine.
For the cases without low-carbon firm capacity, the outsized installed capacity is driven both by the oversizing of wind and solar capacity and the large volume ofenergy storage capacity needed to provide sustained energy output during periods of low VRE availability. Commercially available energy storage options such as
Li-ion batteries are ill suited to these long-duration storage needs. If firm low-carbon resources are to be eschewed, energy storage resources capable of bothsustained output over dozens of hours or longer and very low costs of energy storage capacity suited to low annual utilization rates would be needed.

However, in many scenarios, the energy share of wind and solar in the least-cost
portfolio also declines as the emission limit continues to tighten (Figure 3). As thepenetration of VRE resources increases, the marginal value of additional VRE capacity is linked to its fuel-saving role; that is, to its ability to displace fuel-based generation and thereby to reduce system variable costs. Accordingly, if fossil-fueled generation is replaced by low-carbon firm resources with zero or near-zero marginal
costs (i.e., nuclear, hydro, geothermal) as the emission limit tightens, the energy substitution value of wind and solar declines as well (Figure S9). As a result, the energy
shares from wind or solar in the least-cost portfolio may fall as the emissions limit

2410 Joule 2, 2403–2420, November 21, 2018

Figure 3. Energy Shares of Least-Cost Portfolio in the Northern and Southern Systems by
Technology Group under Different Carbon Emissions Limits
For each system, the plot shows the energy shares of the least-cost mix for the technologicalscenario combinations of all conservative, all mid-range, and all very low, with the northern systemon the left and southern system on the right. The energy shares are calculated as the quotient of thetotal energy injected into the system by each technology over the total demand of the system plus
energy storage losses. See Figure S8 for energy shares under different scenario combinations.

approaches zero. In contrast, if fossil-fueled generation is replaced by firm low-carbon resources with higher fuel costs (e.g., biomass, biogas, natural gas with CCS),
the fuel-saving value of wind and solar is preserved and the least-cost energy sharesof VRE increase asymptotically as the emissions target goes to zero.
Similar non-monotonic behavior in the energy shares of natural gas with CCS can beobserved for the mid-range technology case in which the CO2 capture rate is
assumed to be 90% (Figure S9). Without complete CO2 capture, the energy sharefrom natural gas plants with CCS shrinks as the emission limit approaches zero. In
contrast, natural gas with CCS increases its energy share monotonically when a
100% capture rate is assumed.
The non-monotonic changes in the least-cost share of both VREs and natural gas power plants with 90% CO2 capture rate indicate that assets that may be optimal undermore modest emissions limits may become stranded in a deeply decarbonized power system. Both low-carbon technology investments and near-term policies should
therefore be evaluated in light of their potential contributions to eventual deep decarbonization goals and not solely on their more immediate impacts.
Finally, we find that firm low-carbon resources operate in two different modes, depending on technology type and the specific case.

Joule 2, 2403–2420, November 21, 2018 2411

First, firm resources may operate in a ‘‘flexible base’’ mode, in which they provide areliable base of power throughout the year, infrequently cycle off entirely, and are
flexible enough to modulate output between their minimum stable output andmaximum rated capacity to integrate variable renewable resources when economically advantageous for the system. We define here the ‘‘annual commitment factor’’(ACF) for a given resource i as
ACFi =

XH
h=1


Ci;h ðgi $HÞ

where ci,h is the number of generating units of resource type i committed in eachhour h, gi is the total number of generating units of resource i installed, and H isthe total number of hours in the year. We consider a technology with an
ACF >50%—meaning that the technology is online and generating more often
than not—as operating in a flexible base manner in that case. Nuclear power plants
most consistently operate in flexible base mode in our results, as do natural gas
plants with 100% CO2 capture rate (see Figures S6 and S14). Gas plants with a lower
capture rate and biomass power plants occasionally operate in a flexible base mode
but cycle more frequently in other cases.
Notably, in more than three-quarters of cases (122 of 152) with emissions limits lessthan 10 gCO2/kWh, the least-cost resource mix includes at least one technology that
operates in a flexible base mode. In higher carbon cases, combined-cycle natural
gas plants operate as flexible base but emit too much CO2 to continue in this roleat low emissions limits. The availability of a cost-effective low-carbon alternative
to combined-cycle natural gas plants substantially reduces average electricity costs
as the emissions limit approaches zero (Figure S2). Even a relatively modest amountof low-carbon firm capacity operating in flexible base mode can have a substantial
effect on total power system costs (Figures S4 and S5).
In a smaller number of cases, firm low-carbon resources are too costly relative to variable renewables to warrant operation as flexible base resources, and wind and solar(complemented by battery energy storage) dominate the energy supply (Figures 3
and S8; this includes all cases under 10 gCO2/kWh with very low VRE and storage
cost assumptions and, in the northern system, conservative costs for nuclear and natural gas with CCS, or, in the southern system, conservative or mid-range costs forthese firm resources). Any firm resources deployed in these cases (e.g., biomass
and biogas, or natural gas plants with a 90% CO2 capture rate) operate as ‘‘firm cyclers.’’ This operating mode is characterized by prolonged periods in which all
generating units of this type are cycled off entirely and where these units primarily
contribute valuable power output during prolonged periods of low solar and windavailability in which energy storage becomes insufficient to meet demand reliably.
Firm cyclers are indicated by low values (generally less than 35%) for both commitment factor and capacity factor (Figures S6 and S7). Firm cyclers also reduce total
system costs in these cases relative to cases that entirely exclude firm resources(Figure S2).
Demand-Side Resource and Transmission Interconnection Cases
We next consider the role of demand-side flexibility, in the form of reschedulable
loads and price-responsive or curtailable loads. Table 3 summarizes five scenarioswith progressively increasing demand-side flexibility of each type.
As Figure 4 indicates, firm low-carbon resources (the cases labeled in the figure as‘‘firm allowed’’) continue to play an important role in containing the cost of deep

2412 Joule 2, 2403–2420, November 21, 2018

Table 3. Demand-Side Resource Scenarios
1

2

3

4

5

Percentage of hourly demand thatcan be re-scheduled

5

10

15

20

20

Maximum time to serve re-scheduled
demand (hr)

6

6

6

6

6

Number of price-responsive demand
segments

1

2

3

4

5

Marginal cost of demand curtailment ineach demand segment as a percentageof the value of lost load ($15,000/MWh)

70

70–50

70–50–20

70–50–
20–10

70–50–20–
10–5

Size of each demand segment as apercentage of hourly demand

5

5

5

5

5

Total price-responsive demand as apercentage of hourly demand

5

10

15

20

25

decarbonization even with significant demand flexibility (i.e., when up to 20% of
demand is reschedulable at no cost for up to 6 hours and up to 25% of demand is
price responsive). Across the range of demand-side flexibility cases, it is 30%–83%
more expensive to fully decarbonize electricity generation without low-carbon firm
resources in the southern system and 74%–130% more expensive in the northernsystem.
In cases that exclude firm low-carbon resources, demand-side flexibility plays animportant role in reducing the costs of deep decarbonization (Figure 4). However,
the marginal value of each increment of demand flexibility declines as VRE and energy storage costs fall (indicated by the tighter spread of system-wide costs in thevery low VRE and storage cases). Figure 5 shows how increased demand-side flexibility affects the capacity mix and energy shares in the least-cost power systems.
When firm low-carbon resources are excluded, greater demand flexibility lowers
average costs by substantially reducing required energy storage and VRE capacity.
In effect, greater demand flexibility reduces (but does not eliminate) the need forexcess installed VRE and storage capacity to reliably meet demand.
With firm low-carbon resources, however, increased demand flexibility has a moremodest effect on total cost and total installed capacity in decarbonized power systems. In these cases, demand flexibility acts most directly as a substitute for energy
storage, an indication of their competing roles in the fast-burst balancing resources
category (see Figure 5). Increased demand flexibility also has secondary and more
ambiguous effects on capacity and energy shares of VRE and firm resources, generally reducing the capacity of the most expensive resources and increasing utilizationof lower-cost resources in each case.
We also find that reschedulable or ‘‘shiftable’’ demand is utilized more significantly
in cases when firm low-carbon capacity is allowed in the system (see Figure S10). In
these cases, demand is regularly shifted in order to optimize the utilization of the firm
resource with the highest variable cost (e.g., biomass or natural gas with CCS; Figures S11 and S12). Rather than act as a strong substitute for firm low-carbon resources, demand flexibility instead optimizes their utilization and increases their
marginal value.
We also analyzed the potential gains from adding long-distance transmission
capacity between the northern and southern systems. Fixed line capacities

Joule 2, 2403–2420, November 21, 2018 2413

Figure 4. Average Cost of Electricity under Different Technological Assumption Scenarios, and CO2 Emissions Limits for the Northern and Southern
Systems with Different Demand-Side Resources Scenarios and the Interconnected System
The plots show the average cost of electricity for the northern and southern systems under different demand-side resource (DSR) scenarios and theinterconnected system under different interconnection capacity scenarios. For each system, results are shown when low-carbon firm capacity is allowed
and when it is not. Different colors distinguish scenarios with conservative, mid-range, and very-low-cost projections for all technologies.

equivalent to 10% and 20% of the northern system’s peak demand were each considered (see Table 4).
When firm resources are available, connecting the two regions with transmission capacity equal to 10% of the northern system’s peak demand has a modest effect on
the cost of full decarbonization in each region. In the northern system, the average
electricity cost is reduced by between 8.5% (in the conservative case) and 9% (in thevery low case) relative to the cost without interconnection, while in the southern system the average electricity cost is reduced by between 2% (in the conservative case)and 0.5% (in the very low case). The marginal benefit of additional interconnection
capacity is effectively zero (Figure 4). The first increment of capacity allows for
optimal placement of VRE (solar capacity shifts to the southern system; see Figure S14) and better usage of VRE generation due to reduced output variability(with some solar capacity being replaced by wind generation; see Figure S9). These
effects enable VRE to substitute to some degree for more expensive technologies,
such as energy storage or firm low-carbon resources, in certain scenarios (seeFigure 5).

2414 Joule 2, 2403–2420, November 21, 2018

Figure 5. Effect on Capacities and Energy Shares of DSRs (DSR 5 versus DSR 1) and Interconnection (20% versus 10%) as a Function of Emissions Limit
Effect of flexible demand and transmission interconnection on the capacities (top) and energy shares (bottom) of different resources. The effects areshown as the difference between scenarios DSR 5 versus DSR 1 for the impact of demand flexibility (left) and the difference between the 20% and 10%
interconnect scenarios for the impact of transmission interconnection (right). Different technologies are shown with different data markers and different
technological scenario combinations are shown in different colors. Battery storage capacity differences have been plotted in power capacity (MW)instead of energy capacity (MWh) for consistency; this is done by dividing the total energy capacity by the storage time constant (4 and 6 hr).

If firm resources are not available, transmission interconnection has a greater
economic benefit. As Figure 4 illustrates, the first increment of transmission capacity (10% of the northern system peak) reduces the average cost of the combined system to 68%–75% of the cost of the northern system in isolation (and toroughly the level of the average cost of the southern system in isolation). The
benefit of the next increment of transmission capacity (increasing to 20% of
the northern system peak) is also noticeable, with average electricity costs inthe combined system falling below those of either individual system in isolationin all cases.
Finally, Figure 4 shows that, even when zero-cost, zero-loss transmission capacity
is available to connect the two regions, the cost of achieving deep decarbonization

Joule 2, 2403–2420, November 21, 2018 2415

Table 4. Interconnection Scenario Assumptions

Line capacity (MW)a

10% Case

20% Case

3,400

6,800

a

The two systems are assumed to be interconnected at zero cost, with no transmission losses, i.e., transmission costs and losses are not included in the capacity expansion optimization. Instead, transmissioninterconnection capacity between the two regions is exogenously increased and the effects on other decision variables and costs are analyzed. Figure S13 shows the interconnection usage as function of emissions limit for the different scenarios.

is at least 35% higher in the absence of firm low-carbon resources, providing
further evidence of the broad value of these firm resources for cost-effective
decarbonization.

DISCUSSION
The availability of firm low-carbon resources is an important factor in containing thecost of power sector decarbonization and thus the overall cost of climate mitigation
efforts. This finding appears robust in the face of uncertainties in future technology
costs, in the scale of adoption of demand-side flexibility services, and in the availability of long-distance transmission interconnections. The cost-containing role offirm resources is particularly important where solar or wind resources are of lower
quality, and will also be especially valuable if solar, wind, and storage costs do notcontinue to fall rapidly. However, even in regions with abundant renewable resources, firm low-carbon resources can lower the cost of deep decarbonization
significantly, even if the firm resources have much higher levelized costs than do variable renewables, and even if very-low-cost battery energy storage technologies areavailable. In the majority of scenarios analyzed here, firm low-carbon resources operate as a flexible base in decarbonized power systems, providing a steady supply of
reliable and adjustable power output throughout the year.
We find that in the absence of firm low-carbon resources, affordable decarbonization of the power sector would simultaneously require further steep reductions in
the cost of VRE and battery energy storage technologies, significantly oversizing
installed capacity relative to peak demand, significantly greater demand flexibility,and expansion of long-distance transmission capacity connecting wide geographic
regions. Development of energy storage resources capable of sustained output overdays or longer with very low energy capacity costs suited to low utilization rates
could also lower the costs of high VRE pathways, but this potential was not modeledin this study. Given large current uncertainties in all of these outcomes, our results
suggest that the availability of firm low-carbon resources—even if much costlier
than VRE resources in terms of overnight capital cost or levelized cost of energy—
will improve the robustness of decarbonization efforts.
The analysis shows that in decarbonized power systems, short-duration batteryenergy storage, and demand-side resources play a role (as fast-burst balancing
resources) that is distinct from firm low-carbon resources. We also show that firm
resources play a key role even with enhanced long-distance transmission interconnections. If fast-burst balancing resources or transmission interconnections are available and cost-effective, these options can help to optimize asset utilization andreduce electricity costs for systems without firm resources and for more balanced
systems alike.
Power system assets are long-lived investments, and capacity installed during
the next decade is likely to remain in operation until 2050. Recognizing the2416 Joule 2, 2403–2420, November 21, 2018

importance of firm low-carbon resources to the cost of deep decarbonization thus
has immediate implications for climate change mitigation and electric powersystem planning, energy technology and climate policy, and energy research
prioritization.
First, although a wide range of public policies currently support the growth of variable renewable resources, policy support for firm low-carbon resources such as nuclear power, geothermal energy, biofuels, and CCS is modest in most jurisdictions.
Our results indicate that having one or more firm low-carbon resources available forwidespread deployment at reasonable cost will greatly improve the odds that zeroor near-zero power sector emissions can be achieved cost-effectively. At present,
available firm low-carbon resources face a variety of challenges that impede theirwidespread adoption, from cost to technology immaturity to risk. If these resources
are to be viable options when needed, greater policy support for demonstration,
deployment, and improvement of the existing portfolio of firm low-carbon resources
is needed today.
Second, further development and improvement of firm low-carbon technologies,
particularly those capable of operating as flexible base resources, should be a
research and innovation priority. An improved and expanded set of firm low-carbon
resources could have a substantial and positive impact on the eventual cost of deep
decarbonization of power generation.
Third, given the sensitivity of the least-cost mix of low-carbon electricity resources to
uncertain technology cost and performance trajectories, as well as large and potentially non-monotonic changes in the composition of the least-cost resource portfolio
as the emission limit is tightened, policies should internalize long-term decarbonization goals and should allow the flexibility to implement the most cost-effective combination of fuel-saving, fast-burst, and firm low-carbon resources to meet thosegoals. Such policies could include a long-term emissions limit trajectory, a steadily
increasing carbon price, or a technology-neutral low-carbon resource procurement
requirement. Alternatively, an expanded mix of technology-specific policies that includes significant support for investment in research, demonstration, and deployment of low-carbon firm resources could ensure that these resources would remain
a viable part of the climate mitigation portfolio.

EXPERIMENTAL PROCEDURES
Modeling TechniqueThis research uses the GenX model, an electric power system investment andoperations model described in detail in.38 In its application in this paper, the model
considers detailed operating characteristics such as thermal power plant cycling
costs (unit commitment), limits on hourly changes in power output (ramp limits),
and minimum stable output levels. The model also captures a full year of hourly chronological variability of electricity demand and renewable resource availability (seeFigures S19 and S20). The mixed integer linear programming model selects thecost-minimizing set of electricity generation and storage investments and operating
decisions to meet forecasted electricity demand reliably over the course of a future
year, subject to a specified CO2 emissions limit.
The GenX model can be configured to co-optimize several interlinked powersystems decision layers. Computational limitations entail tradeoffs along eachdimension or decision layer, so more detail in one dimension (e.g., time,

Joule 2, 2403–2420, November 21, 2018 2417

operational constraints, networks) typically means greater abstraction in otherareas. For this study, we configure GenX to deliver high accuracy in hourly operational and unit commitment decisions. This temporal resolution and operational
detail is important to capture the effects of chronological variability in renewableenergy availability and demand patterns on investment and operating decisions,particularly under scenarios with very high wind and solar energy penetrations.
Computational complexity is also increased by the inclusion of stringent annual
limits on total CO2 emissions. However, this level of detail comes at the expenseof other limitations that are important to note when interpreting the results ofthis work. See the Supplemental Experimental Procedures section for full discussion of the limitations of this modeling approach.
Cost and Availability Assumptions
Cost and availability assumptions describing the different analyses are shown in Tables
1, 2, 3, and 4. Economic and technical assumptions can be found in Tables S1–S3.

SUPPLEMENTAL INFORMATION
Supplemental Information includes Supplemental Experimental Procedures, 20 figures, and 4 tables and can be found with this article online at https://doi.org/10.
1016/j.joule.2018.08.006.

ACKNOWLEDGMENTS
N.A.S. would like to thank the Chilean Navy and MIT for their financial support, andto acknowledge Dr. Charles W. Forsberg for his advice in the thesis work thatevolved into this research. J.D.J. thanks the MIT Energy Initiative and the Martin
Family Society of Fellows for Sustainability for their financial support. The authors
would like to thank the Julia for Mathematical Programming (JuMP) team at MIT
for their support in developing the optimization programming package used inthis research. Significant computing resources at MIT’s Engaging Cluster at the Massachusetts Green High Performance Computing Center were used in this research.
Finally, we thank three anonymous reviewers for detailed and constructive comments on a prior version of this paper that helped us strengthen and refine the analysis and discussion herein.

AUTHOR CONTRIBUTIONS
N.A.S. performed the modeling, developed the initial experimental design, contributed to and coordinated the manuscript production, and produced the figures.
J.D.J. was lead editor of the manuscript. N.A.S. and J.D.J. jointly developed the capacity expansion model, refined the initial experimental design, and performed
analysis of results. R.K.L. and F.J.d.S. advised on experimental design and analysis
and reviewed and revised the manuscript.

DECLARATION OF INTERESTS
J.D.J. provides consulting and advisory services for the Clean Air Task Force, anonprofit environmental advocacy organization, and the Clean Energy Program at
Third Way, a nonprofit think tank. R.K.L. serves on the Scientific Advisory Councilof Engie.
Received: November 29, 2017
Revised: May 14, 2018
Accepted: August 15, 2018
Published: September 6, 20182418 Joule 2, 2403–2420, November 21, 2018

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