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Very Large-Scale Deployment of 

Grid-Connected Solar 

Photovoltaics in the United 

States: Challenges and 

Opportunities 

Preprint 

P. Denholm and R. Margolis

To be presented at Solar 2006 

Denver, Colorado 

July 8–13, 2006 

Conference Paper 

NREL/CP-620-39683 

April 2006 
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VERY LARGE-SCALE DEPLOYMENT OF GRID-CONNECTED SOLAR PHOTOVOLTAICS 

IN THE UNITED STATES: CHALLENGES AND OPPORTUNITIES 

Paul Denholm 

National Renewable Energy Laboratory 

1617 Cole Blvd 

Golden, CO 80401 

paul_denholm@nrel.gov 

Robert M. Margolis 

National Renewable Energy Laboratory 

901 D. Street SW, Suite 930 

Washington, D.C. 20024 

robert_margolis@nrel.gov 

ABSTRACT 

In this paper, we analyze the potential for solar 

photovoltaics (PV) to be deployed on a very large scale 

and provide a large fraction of a system’s electricity. We 

explicitly examine how the hourly availability of PV 

interacts with the limited flexibility of traditional 

electricity generation plants. We find that under high 

penetration levels and existing grid-operation procedures 

and rules, the system will have excess PV generation 

during certain periods of the year. This excess PV 

generation results in increased costs, which can increase 

dramatically when PV provides on the order of 10%-15% 

of total electricity demand in systems that are heavily 

dependent on inflexible baseload steam plants. Measures 

to increase penetration of PV are also discussed, including 

increased system flexibility, increased dispatchable load, 

and energy storage. 

1. INTRODUCTION

The technical potential of the grid-connected solar PV 

market in the United States is enormous – potentially 

more than 500 GW in rooftop applications, or many TW, 

including ground-based systems [1]. Not only does PV 

have a larger technical potential than any other renewable 

energy technology, it also is not as geographically 

constrained as other renewables. In theory, PV has the 

potential to supply all of the electricity demand in the 

United States, and to virtually eliminate carbon emissions 

from the electric power sector. The intermittency of solar 

PV, however, presents a set of critical challenges with 

respect to integrating PV on a very large scale into the 

electricity grid. Ultimately, this intermittency may limit 

the potential contribution of PV to the electricity sector. 

In this paper, we examine the potential technical limits on 

PV penetration, considering not only the limitations of the 

solar resource, but also the limitations of existing 

generators to accept the variation in PV generator output. 

2. INTERACTION OF PV WITH ELECTRIC POWER 

SYSTEMS

Traditional electric power systems use a combination of 

generator technologies to meet the system’s total 

electricity demand. In the United States, a large fraction 

of total demand is met by large baseload plants. These 

plants are typically in excess of 500 MW each and 

generate electricity using steam created by coal or nuclear 

fuels. The daily variations in demand are met largely by 

cycling plants, typically smaller coal plants, steam or gas 

turbine plants fueled by natural gas, and hydroelectric 

plants [2]. 

Solar PV is not dispatchable in a traditional sense, 

meaning its output cannot be controlled and scheduled to 

respond to the variable consumer demand for electricity. 

It does, however, have the advantage of providing output 

that has considerable coincidence with natural demand for 

electricity, driven largely by daytime activities – 

particularly in the summer when a large amount of 

electricity is used for air conditioning [3]. Deploying 

solar PV effectively reduces the amount of 

“conventional” generation required from traditional 

generation plants. 

Figure 1 demonstrates the potential impact of this 

effective demand reduction on the total generation 

requirements of an electric power system. In this case, we 

have superimposed the simulated output of a large PV 

system on the actual recorded load for the Electric 

Reliability Council of Texas (ERCOT) system in the year 

2000 [4]. The PV system is ~16 GW (peak AC output) , 

and would provide about 11% of the total system demand, 

1
strictly on an energy basis. The two days shown in Figure 

1 (June 1 and 2) indicate significant benefits and 

“usefulness” of PV. There is a large amount of energy 

produced by PV on these days, and this production is 

highly coincident with demand – the PV output has 

occurred near the peak demand, reducing both the need 

for capacity, as well as the emissions and fuel use 

associated with lower efficiency peaking plants. 

0

10

20

30

40

50

0 12 24 36 4

Hour

Load (GW)

8

Normal Load Net Load with PV PV Output

Fig. 1: System Load With and Without a Large (16 GW) 

PV System on Two Summer Days 

Examining another period of the same year with the same 

simulated PV system yields different results. As shown in 

Figure 2, on these two days (March 11 and 12), moderate 

temperatures reduce total HVAC electricity demand; 

neither large amounts of space heating nor cooling is 

required. Moderate electricity loads and excellent solar 

insolation, particularly on March 11, produce a dramatic 

drop in the net demand for electricity. The minimum net 

demand of ~10 GW in the simulated system is well below 

the normal annual minimum demand of ~18GW. 

0

5

10

15

20

25

30

0 12 24 36 4

Hour

Load (GW)

8

Normal Load Net Load with PV PV Output

Fig. 2: System Load With and Without a Large (16 GW) 

PV System on Two Spring Days 

The drop in demand in the middle of the day presents 

specific technical challenges for a utility operator. First, 

all generators, especially large baseload plants, have 

limits to the rate at which they can ramp up or down. 

Even ignoring this constraint, there are fundamental limits 

to how much baseload plants can reduce output, 

particularly if they need to increase output a few hours 

later. Nuclear plants are particularly limited by long 

ramping times and limited ability to reduce output [5]. 

Coal plants are generally more flexible, but still have 

minimum output requirements due to flame stability and a 

number of other operational issues [5]. If plant output 

needs to be reduced below this minimum load, it may 

need to be completely shut down, requiring a costly and 

potentially lengthy restart process. Given the relatively 

short window of high PV output, it is unlikely that these 

plants will be able to respond to the reduced demand 

illustrated in Figure 2. 

Each individual plant has its own maximum “turndown” 

flexibility, and the overall system minimum output is the 

aggregated minimum output of each individual plant. We 

are aware of no firm guidelines establishing the minimum 

turndown rate on individual plants or utility fleets; but an 

examination of wholesale prices provides some insight 

into when minimum loading conditions occur in electric 

power systems. Several regions of the United States have 

established wholesale energy markets, with historical data 

now available [6,7]. Prices are typically correlated with 

load, largely reflecting the variable cost of fuel and 

efficiency of units “at the margin.” (This is a greatly 

oversimplified explanation, but discussion of wholesale 

power markets is beyond the scope of this paper.) 

Examining prices during periods of low demand reveals 

that prices can fall below the variable operational cost of a 

coal-fired power plant; prices can even fall to below zero 

during periods near the annual system minimum demand. 

There are a number of reasons why the price of electricity 

can drop below the actual cost of generating electricity, 

depending on both the location and current system 

conditions – but one important reason is based on 

minimum loading. Utilities are strongly motivated to 

keep plants above their minimum load levels and keep 

plants running to avoid costly shutdown and start-up 

expenses [8]. The costs of selling electricity below the 

costs of producing it (and even paying consumers to take 

it sometimes) reflects these technical limitations on large 

baseload plants. 

To avoid interference with baseload plant operations, 

utilities would likely reject the output from PV 

generators. This situation is similar to the manner in 

which wind turbines are occasionally shut down during 

periods of low demand and high winds in the Danish 

electric power system. Otherwise, utilities would need to 

2
find some other use for this energy, or change the 

fundamental operation of their power system to 

accommodate PV generation. To consider how much PV 

could be used in a traditional system, and to evaluate 

options for increasing PV penetration, we developed a 

model to analyze the impacts of large-scale PV 

deployment. 

3. MODELING THE IMPACTS OF LARGE-SCALE PV 

DEPLOYMENT

We developed a model (PVflex) that can compare 

simulated solar output to actual load, and calculate the 

“usable” PV generation under a user-specified level of 

system flexibility. The model requires both recorded solar 

insolation data and recorded load data for at least one 

year, preferably from a reasonably large utility region. We 

obtained recorded hourly load data from the ERCOT 

system, [4] which provides most of the electricity for the 

state of Texas. We also obtained hourly recorded global 

horizontal insolation data for nine spatially diverse sites in 

Texas for the same year (2000) [9]. In addition to data 

availability, ERCOT is a good case study due to its good 

solar resource, and the fact that it is an isolated electrical 

grid with limited capacity for imports or exports. The 

insolation data for each site was converted to AC 

electrical output using HOMER, a publicly available tool 

that contains an algorithm to convert global horizontal 

radiation measurements into PV output [10]. Large-scale 

PV deployment will likely require a variety of PV 

orientations (including utility-scale tracking arrays), so 

we assumed the following mix of systems: 15% flat, 10% 

south facing at 10-degree tilt, 15% south facing at latitude 

tilt, 10% southwest facing at 10-degree tilt, 10% 

southwest facing at latitude tilt, 20% single axis tracking, 

20% two-axis tracking. We also assumed a uniform 

distribution of PV systems among the nine sites. 

The total aggregated PV output from the 63 locationorientation combinations (9 sites x 7 orientations) was 

then scaled to produce a simulated PV output of any 

desired size. The PVflex tool iteratively steps through a 

series of net PV system sizes in an attempt to generate up 

to 50% of the system’s total energy from PV. For each 

PV system size, the hourly PV output is subtracted from 

the normal electricity load. If the net load with PV falls 

below the minimum loading point, all PV output that 

produces a net load less than the minimum loading point 

is considered “spilled” and effectively unusable. PVflex 

calculates both the average spilled PV, and the marginal 

spilled PV. 

We set the minimum system turndown rate for our base 

case simulation at 35% of peak load. This value is 

roughly equal to the annual minimum normal load for the 

ERCOT system in 2000. The wholesale price of 

electricity during hours of minimum load are often at or 

below the actual production cost of electricity, which 

implies a system at or near minimum turndown for the 

baseload generator fleet. This number (35%) is by no 

means definitive, and the sensitivity of PV penetration to 

minimum loading is discussed in Section 5. 

4. RESULTS

Using a minimum turndown rate equal to 35% of peak 

load, some PV generation becomes surplus when PV is 

providing about 4% of total annual electricity demand. 

This amount of “surplus PV” increases non-linearly with 

increasing PV deployment, and results in a reduced 

effective capacity factor (CF) for PV. The base capacity 

factor for the entire simulated PV system is 22.3%, based 

on the system’s peak AC rating. 

Figure 3 illustrates the drop in system capacity factor as a 

function of PV penetration on an energy basis. 

0%

5%

10%

15%

20%

25%

0% 5% 10% 15% 20% 25%

% System Energy from PV

PV Capacity Factor (%)

Average CF

Marginal CF

Fig. 3: PV System Capacity Factor as a Function of PV 

Energy Contribution 

The cost impacts of this reduced capacity factor can also 

be calculated because the levelized cost of energy from a 

PV system (excluding O&M) is proportional to 1/CF. 

Figure 4 illustrates the relative cost of PV for the 

simulated case. We have used relative cost here to 

emphasize the shape of the curve, rather than absolute 

values. If so desired, the reader may assume any “base” 

cost of PV generated electricity and simply multiply this 

“base” cost by the relative cost to estimate absolute costs 

at a given penetration level. 

3
1.0

1.5

2.0

2.5

3.0

0% 5% 10% 15% 20% 25%

% System Energy from PV

PV Electricity Relative Cost

Marginal Cost

Average Cost

Fig. 4: Relative Cost of PV Generated Electricity as a 

Function of PV Energy Contribution 

Based only on minimum loading constraints, it is not 

possible to define a “maximum” penetration of PV. The 

limits on PV will be determined by economics, based on 

the value of PV to an individual, utility, or society as a 

whole. In Figure 3, we cut off the cost at 3 times the base 

cost, largely because the cost slope of PV is approaching 

vertical, implying very little additional system-wide 

benefits of further installed PV. For example, at a PV 

energy contribution of about 17%, the “spill rate” of the 

next unit of installed PV is above 75%, providing a 

relatively small amount of usable energy to the system. 

5. DISCUSSION: OPTIONS TO INCREASE PV 

PENETRATION

To move beyond the limits illustrated in Figures 3 and 4, 

we must investigate options to increase the usefulness of 

PV during periods of low normal demand. One obvious 

solution is to increase the overall flexibility of 

conventional generation. Figure 5 demonstrates the 

impact of increased system flexibility. Here, we repeated 

the analysis in Figure 4, but we decreased the system 

minimum loading from 35% to 20% and 0% of annual 

peak demand. 

1.0

1.5

2.0

2.5

3.0

0% 10% 20% 30% 40% 50%

% System Energy from PV

PV Electricity Relative Cost

20% Marginal

20% Average

0% Marginal

0% Average

Fig. 5: Effect of Increasing System Flexibility on the 

Relative Cost of PV 

By increasing the system flexibility, it now becomes at 

least theoretically possible to provide 50% of the system’s 

energy from PV – although this requires the ability to 

completely turn off all conventional generation for short 

periods of time without cost penalty. However, even in 

this extreme system flexibility scenario, the marginal cost 

of PV at 50% PV contribution is about 18 times that of 

the base cost. 

Increasing system flexibility is one of several possible 

approaches to increasing the economic penetration of PV. 

We can consider these other approaches under the context 

of the installed capacity needed to reach the limits of 

intermittent PV generation. 

Figure 5 illustrates the PV capacity required to achieve 

high levels of PV system contribution under a range of 

minimum system loading constraints. Three curves are 

shown, reflecting the three different system minimum 

loads considered in our analysis: 35%, 20%, and 0%. 

0

50

100

150

200

250

300

0% 10% 20% 30% 40% 50%

% System Energy from PV

PV Capacity (GW)

35%

20%

0%

Figure 6: PV Capacity Requirements to Achieve Large 

Contribution to Total Energy Demand 

4
In Figure 6, deviations from the linear relationship 

between PV capacity and PV energy contribution 

indicates the spilled energy and unusable capacity 

resulting from limited baseload-generator flexibility. The 

deviation at the low level of flexibility (35% minimum 

turndown) occurs at about 5 GW (this is the point where 

the capacity factor of PV begins to drop in Figure 3.) 

Given that global PV production in 2004 was roughly 1 

GW [11], it will clearly take decades to reach this level of 

market development in Texas and or other states in the 

United States. (Of course, load growth will require an 

even greater amount of PV before intermittency-related 

impacts are realized.) The amount of time needed to 

achieve this level of penetration may allow for 

appropriate changes in the electric power system. 

There are a number of possible technologies that would 

enable increased use of PV. Dispatchable load is one 

possibility, including “dual-fuel” appliances such as water 

heaters and space heaters. These appliances could switch 

from natural gas to electricity during times where the 

price of electricity drops due to a large surplus of PV 

generation. Another potential source of dispatchable load 

is “plug-in” hybrid electric vehicles, which could benefit 

from midday charging after morning commutes. Of 

course, energy storage represents the “ultimate” solution 

to the problems of intermittency. Not only could energy 

storage absorb the excess PV generation, but it could also 

aid in increasing the overall flexibility of electric power 

systems by decreasing dependence on traditional baseload 

generation. Ultimately, it is likely that a combination of 

technologies will provide the most economically 

attractive solution to address the limits of intermittent 

energy sources such as solar PV. 

6. CONCLUSIONS

Traditional electric power systems are designed in large 

part to utilize large baseload power plants, with limited 

ability to rapidly ramp output or reduce output below a 

certain level. The increase in demand variability created 

by intermittent sources such as PV presents new 

challenges to increase system flexibility. 

Current electric power systems that are dominated by 

large baseload thermal-steam generators may require 

rejection of large amounts of PV generation when this 

intermittent source provides between 10-15% of a 

region’s electricity. However, the time required to 

achieve this level of PV penetration provides many 

opportunities for utilities to increase system flexibility or 

deploy PV-enabling technologies. We found that 

increasing the flexibility of the electric power system in 

the simulated system could increase the contribution of 

PV to perhaps 20%-30%. Beyond this contribution, 

enabling technologies such as fuel switching in “smart” 

appliances, dispatchable load from plug-in hybrid or other 

electric vehicles, or stationary energy storage would be 

required to enable very high levels of PV contribution to 

the electric power system. Given the long lifetimes of 

many electricity generation technologies, now is the time 

to begin thinking creatively about ways to begin moving 

toward a more flexible and PV-friendly electric power 

system. 

7. REFERENCES

(1) Chaudhari, M., Frantzis, L., and T. E. Hoff. “PV Grid 

Connected market Potential in 2010 under a Cost 

Breakthrough Scenario,” 2004. Via 

www.ef.org/documents/EF-Final-Final2.pdf

(2) Denholm, P., and T. Holloway. “Improved 

Accounting of Emissions from Utility Energy Storage 

System Operation,” Environmental Science and 

Technology. 2005. 39, 9016-9022 

(3) Wiser, R., Bolinger, M., Cappers, P., and R. Margolis. 

“Letting the Sun Shine on Solar Costs: An Empirical 

Investigation of Photovoltaic Cost Trends in California,” 

2006. LBNL-59282, NREL/TP-620-39300

(4) Federal Energy Regulatory Commission. “Form 714 - 

Annual Electric Control and Planning Area Report.” Via 

http://www.ferc.gov/docs-filing/eforms/form-714/data.asp

(5) Elliot, T. C., Chen, C., and R. C. Swanekamp (eds) 

Standard Handbook of Powerplant Engineering. New 

York: McGraw Hill, 1998 

(6) PJM Interconnection. Via 

http://www.pjm.com/markets/energy-market/realtime.html

(7) Electric Reliability Council of Texas (ERCOT). Via 

http://www.ercot.com/mktinfo/index.html

(8) Hirst, E. “Let's get real-time,” Electric Perspectives, 

 Jan/Feb 2002

(9) Personal correspondence, Steve Wilcox, National 

Renewable Energy Laboratory, 2005 

(10) National Renewable Energy Laboratory. “HOMER: 

The Optimization Model for Distributed Power,” 

http://www.nrel.gov/homer/ 

(11) BCC Research. Via 

http://www.bccresearch.com/editors/RE-038V.html

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Very Large-Scale Deployment of Grid-Connected Solar 

Photovoltaics in the United States: Challenges and Opportunities; 

Preprint 

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14. ABSTRACT (Maximum 200 Words)

This paper analyzes the potential for solar photovoltaics (PV) to be deployed on a very large scale and provide a 

large fraction of a system’s electricity. It explicitly examines how the hourly availability of PV interacts with the limited 

flexibility of traditional electricity generation plants. The authors found that, under high penetration levels and existing 

grid-operation procedures and rules, the system will have excess PV generation during certain periods of the year. 

This excess PV generation results in increased costs, which can increase dramatically when PV provides on the 

order of 10%-15% of total electricity demand in systems that are heavily dependent on inflexible baseload steam 

plants. Measures to increase penetration of PV are also discussed, including increased system flexibility, increased 

dispatchable load, and energy storage. 

15. SUBJECT TERMS

Solar photovoltaics; PV; large-scale PV; deployment; grid-connected PV; solar PV; electricity; carbon emissions; PV 

system; PV generation; HOMER; American Solar Energy Society; ASES; Solar 2006; Paul Denholm; Robert Margolis

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