Valuing the Contribution of 

Energy Efficiency to 

Avoided Marginal Line Losses 

and Reserve Requirements

Principal authors

Jim Lazar and Xavier Baldwin

August 2011
Electronic copies of this paper and other RAP publications 

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1

Valuing the Contribution of Energy Efficiency to Avoided Marginal Line Losses and Reserve Requirements

Valuing the Contribution of 

Energy Efficiency to 

Avoided Marginal Line Losses 

and Reserve Requirements

by Jim Lazar, RAP Senior Advisor

Xavier Baldwin, P.E., Principal Electrical Engineer, Burbank Water and Power1

Introduction

Utilities and their regulators have become 

familiar, comfortable, and sometimes 

enthusiastic about the energy savings that 

energy efficiency measures provide. These 

savings reduce fuel usage, reduce air pollution, and reduce 

consumer bills. 

Energy efficiency measures also provide very valuable 

peak capacity benefits in the form of marginal reductions 

to line losses that are often overlooked in the program 

design and measure screening. On-peak energy efficiency 

can produce twice as much ratepayer value as the average 

value of the energy savings alone, once the generation, 

transmission, and distribution capacity, line loss, and 

reserves benefits are accounted for. Geographically or 

seasonally targeted measures can further increase value.

This paper is one of two that the Regulatory Assistance 

Project (RAP) is publishing on this topic; the second 

looks in a more detailed fashion at the transmission and 

distribution system benefits of energy efficiency.2

Principal Conclusions

The line losses avoided by energy efficiency measures 

are generally underestimated. Most analysts who consider 

line losses at all use the system-average line losses, not the 

marginal line losses that are actually avoided when energy 

efficiency measures are installed. Generally this is because 

average line losses are a measured and published figure, 

while determining marginal line losses requires more 

information and more detailed calculations. 

Because losses grow exponentially with load, the 

marginal losses avoided are much greater than the average 

losses on a utility distribution system. As calculated in 

Figure 4, marginal line losses at the time of the system peak 

of 20% are entirely consistent with average line losses of 

7% on a utility distribution system. 

Because energy efficiency measures reduce loads at the 

customer premises, they also avoid the associated marginal 

line losses. As a result, the utility avoids the need for as 

much as 120% of the generating capacity needed to serve 

the avoided load.

1 This paper builds on work originally presented to the Northwest Power and Conservation Council’s Regional Technical Forum 

(RTF); it has benefited greatly from the contribution of Charlie Grist of the Council staff and Adam Hadley, P.E., a consultant to the 

RTF. See: http://www.nwcouncil.org/energy/rtf/meetings/2008/09/Marginal%20Distribution%20System%20Losses%203.ppt 

http://www.nwcouncil.org/energy/rtf/meetings/2008/09/Marginal%20Distribution%20System%20Losses%20Illustration%20v.xls

2 US Experience with Efficiency as a Transmission and Distribution System Resource, Chris Neme, Regulatory Assistance Project, 

November 2011. http://www.raponline.org/docs/
2

Valuing the Contribution of Energy Efficiency to Avoided Marginal Line Losses and Reserve Requirements

about the same load shape as the loads themselves – rising 

at peak hours and declining at night. Therefore, efficiency 

measures generally contribute more to the reduction of 

peak demands than they do on average. They have a better 

“load shape” than baseload power plants, and the savings 

are consequently more valuable.

This load shape is not uniform from measure to 

measure. Some types of efficiency, such as Energy Star 

air conditioners, provide very large peak demand savings 

relative to the energy savings. Others, like more efficient 

street lights, may only reduce demand during shoulder or 

off-peak hours. 

Analysis is required to determine the peak demand of 

various efficiency measures. This is measured by the typical 

load factor of the individual measure (ratio of average to 

peak demand reduction) and the coincidence factor of the 

measure (the portion of the demand reduction of the 

individual measure that will occur at the time of the system 

peak demand). Measures that provide most of their savings 

during the high-load hours are said to have a favorable load 

shape. All three of these measures are important to valuing 

the energy savings from efficiency measures.

The peaking capacity value of different measures varies 

by region of the country, depending both on climate and 

on whether the local utility system is summer-peaking or 

winter-peaking. A summer-peaking region, like Texas or 

Florida, will value the capacity benefits of air conditioning 

savings, but will derive much less capacity value from 

electric space-heating savings. Winter-peaking regions will 

have the opposite perspective. Utilities with dual peaks 

will generally assign a greater value to measures other than 

space conditioning (i.e., that reduce peak demand in both 

seasons) compared to regions with a strong peak demand 

in one season or the other. 

Figure 2 shows the relative onpeak summer and winter savings 

of some typical energy efficiency 

measures as evaluated in the Pacific 

Northwest, a winter-peaking 

region. 

Daily Load Shape of Example Utility

3500

3000

2500

2000

1500

1000

500

0

Midnight 6 Noon 6 Midnight

Demand (MW)

Utilities maintain generating reserves so that when one 

generating unit goes out of service, customers continue to 

receive service. Because energy efficiency reliably reduces 

energy loads and avoids marginal line losses, thus achieving 

reliable reductions in loads to be served at the generation 

level, the utility avoids the need for expensive reserves 

to assure reliable service. When compounded with the 

avoided marginal line losses, energy efficiency measures 

can save about 1.4 times as much capacity at the generation 

level as is measured at the customer’s meter. While the 

energy benefit of line loss avoidance by investment in 

energy efficiency is relatively well-understood, the capacity 

benefit is a separate and additional benefit that is seldom 

quantified by efficiency analysts.

Efficiency Has a Favorable Daily and 

Seasonal Resource Shape

Most electric utilities have loads that rise during the day 

and decline at night. They also have seasonal increases in 

the summer, winter, or both, compared with the spring and 

autumn seasons. This variation is caused by people waking 

up and turning on appliances, going to work and turning 

on lights and office equipment, and using air conditioners 

following the heat of the afternoon. 

A typical utility will have an on-peak demand during 

the peak season that is twice as high as the average demand 

over the year. The ratio of average demand to peak demand 

is called the system load factor, and in this example, would 

be 50%. Figure 1 shows a typical utility daily load shape.

Because investments in energy efficiency reduce the very 

loads that cause the overall system load, they generally have 

Figure 1: 
3

Valuing the Contribution of Energy Efficiency to Avoided Marginal Line Losses and Reserve Requirements

Figure 2

Ratio of Coincident Peak Savings to 

Average Annual Energy Savings 3

step-up transformers to get the power onto the transmission 

system, long transmission lines, transmission substations, 

step-down transformers to distribution voltages, distribution 

lines, and distribution line transformers. 

Losses occur at each of these steps of the transmission 

and distribution system. Typical utility-wide average annual 

losses from generating plants to meters ranges from 6% 

to 11%, depending on the transmission distances, system 

density, distribution voltages, and the characteristics of 

transmission and distribution system components.5

Energy efficiency is often credited with avoiding these 

average losses when regulators and utilities value efficiency 

investments and set the program cost-effectiveness 

thresholds based on avoided cost. However, the losses 

on utility transmission and distribution systems are not 

uniform through the day and the year, and the peak 

capacity savings from energy efficiency are typically much 

greater than the average savings. 

Line Losses on a Distribution System

Many utility conservation programs credit efficiency 

measures with line loss reduction, but most of these 

calculations are based on the average losses, not the 

marginal losses avoided by efficiency measures. 

There are two types of losses on the transmission and 

distribution system. The first are no-load losses, or the 

losses that are incurred just to energize the system – to 

create a voltage available to serve a load. Nearly all of these 

occur in step-up and step-down transformers. The second 

are resistive losses, which are caused by friction released 

as heat as electrons move on increasingly crowded lines 

and transformers. Typically, about 25% of the average 

3 Northwest Power and Conservation Council Regional Technical Forum, 2001; see: http://www.nwcouncil.org/energy/rtf/measures/

support/procost/MC_AND_LOADSHAPE_6P.XLS

4 Water heat usage is concentrated in the early morning and early evening hours, when households are beginning and ending their 

day. System peaks typically occur when residential and commercial loads overlap – in the morning around 8 a.m. and the evening 

around 5 p.m.; therefore electric water heat usage is highly peak-coincident at least for a winter-peaking system. By contrast, while 

gas water heat usage occurs in the same hours, water heat is a very high load factor usage on gas systems, because in the natural 

gas industry, peak demand is measured on a daily basis, not an hourly (or sub-hourly) basis as is the standard for the electricity 

sector. Prior to the 1960s, timers were common on electric water heaters to keep them from contributing to peak demand; with the 

advent of smart grid resources, electric water heaters are now being looked to for demand response and to complement intermittent 

generation from wind.

5 Page 401a of the FERC Form 1 shows system losses and system retail sales, and generally fall in this range for vertically integrated utilities. Line losses attributable to wholesale sales and wholesale purchases are typically reported in part by the seller and in part by the 

buyer – and therefore the losses reported in the Form 1 may not reflect all losses attributable to retail sales by the reporting utility.

Measure Summer Peak Winter Peak 

Residential Lighting 0.90 1.37

Residential Water Heat 0.94 2.63

Residential Space Heat 0.28 4.00

Residential Air Conditioning 1.72 0.08

Residential Refrigerators 1.11 0.87

Commercial Lighting 2.17 2.00

Commercial Air Conditioning 2.86 0.08

As is evident in a winter-peaking region like the Pacific 

Northwest, investments in space heating conservation 

(floor, ceiling, and wall insulation) will provide very 

large peak demand benefits, whereas in summer-peaking 

regions, it is natural that air conditioning measures are 

most valuable. One of the more interesting findings of 

this particular analysis, however, was the relatively high 

winter-peak coincidence factor of residential water heating 

consumption.4

 This might be very different on a summerpeaking system.

Energy Efficiency Provides Significant 

Distribution and Transmission Loss Savings at 

the Time of Critical System Peak Demands

Because energy efficiency reduces loads at the customer 

premises, the utility does not have to supply these avoided 

demands with generating facilities. Generating facilities are 

often located at great distances from customers and require 
4

Valuing the Contribution of Energy Efficiency to Avoided Marginal Line Losses and Reserve Requirements

annual losses are no-load or core losses, and about 75% are 

resistive losses. Utility loss studies generally separate the 

core losses from the resistive losses.6

Losses increase significantly during peak periods. The 

mathematical formula for the resistive losses is I2

R, where 

“I” is the amperage (current) on any particular transformer 

or distribution line, and “R” is the resistance of the 

wires through which that current flows. While the “R” is 

generally constant through the year, since utilities use the 

same wires and transformers all year long, the “I” is directly 

a function of the demand that customers place on the 

utility. Thus, resistive losses increase with the square of the 

current, meaning losses increase as load increases.

Let’s start with a very simple calculation: the load (current 

times voltage) of a utility during the highest on-peak hours 

is two times the average load for the year, a system load 

factor of 50%. Because the voltage is constant, losses are a 

function of the square of the load, and that load is two times 

as high on-peak as the average, the total resistive losses are 

four times as great during the summer afternoon peak as 

they average over the year. It’s a bit more complicated than 

that, but this example gives a general idea.

Depending on the load shape of the utility (how sharp the 

“needle peak” is), the percentage of generation that is “lost” 

before it reaches loads are typically at least twice as high as 

the average annual losses on the system. During the highest 

critical peak hours (perhaps 5-25 

hours per year) when the system 

is under stress, the losses may be 

four to six times as high as the 

average. 

There are many tools available 

to utilities for line loss reduction, including voltage upgrades, 

reconductoring, and improved 

transformers. While these are 

valuable and may often be costeffective, the focus of this paper is 

on the avoidable marginal losses 

as a result of load reductions from implementation of energy 

efficiency measures.

Marginal Losses Are Greater Than Average Losses

Important to valuing any investment is how much the 

incremental cost of the measure is, and what the incremental 

savings are.7

 Because the average losses increase with the 

square of the load, the marginal line losses at any point are 

significantly higher than the average losses at that same point 

on the load curve. It turns out that the incremental system 

losses during the peak hours are much greater than the 

average losses during these hours. As noted above, this is due 

to the total losses growing with the square (I2

R) of the load in 

response to linear growth in the loads, and the incremental 

losses (the change in losses with respect to the change in 

loads) are therefore more than exponential.

The graph below shows the average losses at various 

load levels for a hypothetical small utility with an average 

annual resistive loss of 7% on its system. It also shows the 

incremental losses sustained as load increased from the 

minimum level of about 100 megawatts to the system record 

peak demand of nearly 300 megawatts for this utility. 

This utility’s average resistive losses on their distribution 

system are only about 7% over the course of the year. 

At their system extreme peak, the estimated total losses 

Average and Marginal Line Losses

Assumes 7% average losses; 25% No-load, 75% I2

R

Figure 3 Losses as percentage of load (incremental load)25%

20%

15%

10%

5%

0%

33% 42% 50% 58% 67% 75% 83% 92% 100%

Percent of Maximum System Load

Average Losses

Marginal Losses

6 In preparing this paper, the authors reviewed line loss studies for several utilities; they indicated no-load losses ranging from 18.5% to 

30% of total annual losses. A mean figure of 25% is used for simplicity in illustrating the principle of marginal line loss calculation.

7` The most comprehensive and most commonly accepted cost-effectiveness test is the Total Resource Cost (TRC) test, which, when 

properly applied, measures both energy and non-energy benefits; but the principles in this analysis apply equally to the Program 

Administrator Cost (PAC) test used by some utilities and regulators to value energy efficiency investments.
5

Valuing the Contribution of Energy Efficiency to Avoided Marginal Line Losses and Reserve Requirements

losses are no-load losses, meaning that about 75% are resistive losses. Therefore this paper uses a rule of thumb that 

marginal losses are about 1.5 times average losses (it’s actually a bit lower at low loads, and a bit higher at high loads 

where the no-load losses are a smaller part of total losses.)

This means that a conservation measure that saved 

1 kilowatt at the time of the system peak measured at 

the customer’s meter would save about 1.25 kilowatts 

measured at the generation level.8

 The critical peak-period 

marginal line-loss savings of energy efficiency therefore 

adds another 25% to the value of the load reduction itself, 

in determining the amount of generating capacity required 

to meet critical peak period demand. If the utility has 1.25 

kW of generating capacity, and loses at the margin 20% of 

this capacity during the highest peak hours, it has 1 kW 

available to serve the load.

The hypothetical analysis may not be universally 

applicable, but the principles are universal: losses increase 

with the square of the demand, and incremental losses 

during the critical peak period are much larger than the 

average losses over the year. 

Avoidable Transmission and Distribution 

Capacity Costs Are Significant

In addition to the avoided losses and the reduced need 

for generating capacity that can be achieved through 

reached about 11%, one and one-half times the average 

losses for the year. At that extreme peak, however, the 

marginal resistive losses – those that would be avoided if 

load had been a little bit lower if an efficiency measure were 

installed – were 20%. 

The graphic in Figure 3 is derived from the calculations 

above in Figure 4.

Few utilities or regulators have studied the marginal 

losses that can be avoided with incremental investment 

in efficiency measures that provide savings at the time of 

extreme peak demands. This type of analysis suggests a 

very significant benefit from measures that reduce peak 

demand, including energy efficiency, demand response, and 

use of emergency generators located at customer premises.

Mathematically, the formula I2

R reduces the marginal 

resistive loses to a calculation. At any point on the load 

duration curve, marginal resistive loses are two-times 

the average resistive losses at that same point on the load 

duration curve. During off-peak hours, when average 

resistive losses may be only 3%, the marginal losses are 

6%. During the highest peak hours, when average resistive 

losses may be 10%, the marginal losses are 20%. 

However, because part of the overall losses at every hour 

are (no-load) losses, the marginal losses are not two times 

the total losses – only two times the resistive losses. The noload losses are not reduced by energy efficiency measures. A 

variety of utility loss studies indicate that 20%-30% of total 

Load 

Level 

100

125

150

175

200

225

250

275

300

No-Load 

Losses 

MW

2.625

2.625

2.625

2.625

2.625

2.625

2.625

2.625

2.625

Resistive 

Losses 

MW

 3.5 

 5.5 

 7.9 

 10.7 

 14.0 

 17.7 

 21.9 

 26.5 

 31.5

Square 

of 

Load

 10,000 

 15,625 

 22,500 

 30,625 

 40,000 

 50,625 

 62,500 

 75,625 

 90,000

Loss 

%

6.1%

6.5%

7.0%

7.6%

8.3%

9.0%

9.8%

10.6%

11.4%

Total 

Loss 

MW

6.1

8.1

10.5

13.3

16.6

20.3

24.5

29.1

34.1

Incremental 

Load

25

25

25

25

25

25

25

25

Incremental 

Loss

2.0

2.4

2.8

3.3

3.7

4.2

4.6

5.0

Marginal 

Loss 

%

8%

10%

11%

13%

15%

17%

18%

20%

Figure 4: 

Calculation of Average and Marginal Line Losses

8 [1.25 – (.20 x 1.25) = 1.0]; If the utility must serve a 1 kW incremental load on-peak, it needs 1.25 kW of additional generating 

capacity to feed the transmission and distribution system.
6

Valuing the Contribution of Energy Efficiency to Avoided Marginal Line Losses and Reserve Requirements

energy efficiency investment at the distribution level, the 

peak load reduction from energy efficiency investment 

also reduces transmission and distribution capacity costs. 

Recognizing this value may be especially important for 

those jurisdictions that actually review T& D investments 

against targeted energy efficiency program opportunities.9

Transmission and distribution systems must be designed 

to carry extreme peak demands. The costs of oversizing 

systems for these demands are quite significant. In states 

where marginal cost of service studies are used to set rates, 

utilities regularly examine the cost of adding capacity to 

their transmission and distribution grids. The results of 

these studies vary widely, in part due to regional conditions 

and in part due to a lack of standardized methodologies. 

The capital cost of augmenting transmission capacity 

is typically estimated at $200 to $1,000 per kilowatt, 

and the cost of augmenting distribution capacity ranges 

between $100 and $500 per kilowatt.10 Annualized values 

(the average rate of return multiplied by the investment 

over the life of the investment) are about 10% of these 

figures, or $20 to $100 per kilowatt-year for transmission 

and $10 to $50 per kilowatt-year for distribution. There 

are also marginal operations and maintenance costs for 

transmission and distribution capacity, but these are modest 

in comparison to the capital costs. 

In valuing energy efficiency investments, it is important 

to consider the avoided energy and capacity not only at the 

generation level, but also at the transmission and distribution 

levels. Inclusion of these values, particularly considering 

the marginal capacity benefits from incremental efficiency 

investments, can greatly increase the value of these measures, 

and therefore the level of financial assistance or incentives 

that utilities may offer to encourage implementation.

Another important benefit of increased energy efficiency 

at the distribution/customer level is the significant 

extension in useful life of distribution system components 

and the resulting deferral of capital expenditures for 

upgrade or replacement of electrical equipment, including 

conductors, transformers, etc. In effect, energy efficiency 

allows the system to absorb additional load growth 

without the need to upgrade system components as soon. 

This capital deferral translates more or less directly into 

avoided distribution-capital investment costs for capacity 

expansion. A prudent assumption is that the avoided 

capacity benefits are at least one-half of the utility’s 

estimated marginal transmission and distribution capacity 

costs, based on their most recent cost-of-service analysis.11

Another benefit of reducing marginal losses is lower 

loss of service life due to a reduction in winding and 

insulation temperatures in distribution transformers, which 

are normally operated at up to 200% of their nameplate 

rating during peak load periods, a condition that causes 

accelerated aging of these components. 

Efficiency Reduces System Generating 

Reserve Requirements

Utilities must provide reserves of generating facilities in 

order to ensure that service is not interrupted if (and when) 

generating units fail to operate as planned. Generating 

reserve requirements in the United States range from as low 

as 7% on hydro-rich utilities to as much as 25% for isolated 

small utilities in Alaska and Hawaii. Ten to fifteen percent is 

typical for large thermal-based systems.12

Efficiency investments reduce loads at the customer’s meter, and, as we have seen, provide even larger reductions at 

the generation level during system peak periods when losses 

skyrocket and capacity/reserve requirements are greatest. 

Since the reserve requirement is tied to the amount 

of generation required to serve load, efficiency reduces 

the reserve requirement not only by a percentage of the 

9 Id footnote 2. 

10 These wide ranges reflect the wide possible range of outcomes for distance, topography, real estate costs, and construction costs 

that may be incurred.

11 The capacity benefit may not be monetized immediately, due to temporary excess capacity; but over the life of a distribution circuit, 

eventually components will need to be replaced due to age or upsized due to growth. Using one-half of marginal cost implies that, 

on average, the capacity benefits will be realized within a half-lifetime of the circuit components.

12 The level of required reserves is a function of the size of the total system, the size of the largest single generating units, and the 

reliability of the various generating units. Because hydro units are generally relatively small and extremely reliable, utilities that rely 

on hydro for reserves have the lowest reserve requirements. Small island systems, like those in Hawaii, with a few relatively large 

generating units typically have the highest reserve requirements.
7

Valuing the Contribution of Energy Efficiency to Avoided Marginal Line Losses and Reserve Requirements

thousands of small, distributed units, each of which saves 

anywhere from a few watts (e.g., a compact fluorescent 

lamp) to a few kilowatts (e.g., a high-efficiency commercial 

air conditioning unit). 

It has long been recognized that a utility network 

made up of a large number of small generating units 

provides a more reliable system simply because they will 

not all fail simultaneously. The same principle applies to 

energy efficiency investments, which are a large number 

of small energy-saving devices. But these go beyond this 

mathematical advantage in at least two ways: 

First, the individual units (efficient light bulbs, 

refrigerators, and air conditioners) are, as a population, 

extremely reliable, far more so than any type of generating 

plant.13 Energy Star windows, attic insulation, or variable 

speed drive in a commercial HVAC system are almost 

certainly not going to “fail” during a heat wave. Conversely, 

generating plants, transmission lines, and even distribution 

transformers are most susceptible to failure when under 

stress. Even the most reliable type of generating units 

(hydro turbines) have higher “forced outage rates” than 

energy savings devices. 

Second, if one energy efficient unit does fail, such a 

“failure” often actually reduces electric demand (i.e., when 

a high-efficiency air conditioner breaks, the customer may 

be entirely without air conditioning – uncomfortable, but 

using less energy). The utility loses an “efficient” load, 

but nonetheless, the load goes down when the unit fails, 

generally reducing the load-related stress and threats 

to reliability on the system. When a generating plant or 

transmission line fails, it leaves the utility with the same 

load, and less ability to 

serve that load and with 

increased risk of a system 

outage affecting hundreds, 

thousands, or even millions 

of consumers.

savings that customers enjoy, but also by a percentage 

of the incremental peak losses on the transmission and 

distribution system that reduce the utility’s generation 

requirements. The reserve requirement is measured against 

the amount of generation needed – including that needed to 

cover line losses. Therefore, the avoided reserves resulting 

from efficiency investments are increased in value by the 

avoided marginal line losses. 

The table below looks at the capacity savings during an 

off-peak period and an on-peak period for two hypothetical 

resources, one with a low coincidence factor relative to 

the system peak (efficient lighting), and one with a high 

coincidence factor, efficient air conditioning. The table 

shows that after considering the coincidence of different 

loads to the system peak, the marginal line losses, and 

the avoided reserve requirement, the capacity benefit of 

energy efficiency measures increases significantly from that 

measured at the customer’s meter.

As is evident, the total capacity benefit of each of 

these measures is 1.44 times the capacity savings at the 

customer’s meter, because of the value of the marginal line 

losses and avoided reserves during peak periods (line 8 

divided by line 3). Thus the generation capital cost savings 

are significantly higher than if only average line losses were 

used and if the reserves benefits were not included.

Efficiency Is The Most Reliable Resource

Energy efficiency is the most reliable resource in which 

a utility can invest. Unlike any type of generating unit, 

efficiency investments are composed of hundreds or 

Air 

Line Lighting Conditioning 

1 kW Savings at Customer Meter 10 10

2 Coincidence Factor 0.25 0.75

3 kW Savings at Customer Meter at Peak (1 X 2) 2.5 7.5

4 Marginal Line Losses At Peak @ 20% (3 / (1 - 20%) -3) 0.625 1.875

5 kW Savings at Busbar (3 + 4) 3.125 9.375

6 Reserve Margin Requirement 15% 15%

7 Avoided Reserve Capacity (@ 15%) 0.47 1.41

8 kW Savings At Generation Level (5 + 7) 3.59 10.78

Figure 5: 

Peak Capacity Savings from Energy Efficiency Investments

13 The most reliable peaking 

units have on-peak 

availability of about 95%, 

and forced outage rates of 

about 5%.
8

Valuing the Contribution of Energy Efficiency to Avoided Marginal Line Losses and Reserve Requirements

How the Smart Grid Can Enhance the Application 

of Energy Efficiency Measures

At the time of the system peak demand, line losses are 

highest and marginal line losses may be 20% or higher. 

For this reason, actions that reduce load at the time of the 

system peak are extremely valuable. As utilities invest in 

smart grid assets and learn to deploy them, avoidance of 

expensive peak load related costs becomes more feasible. 

The application of smart grid technology will enhance the 

application of energy efficiency measures by:

•	 Accurately measuring conditions on the

distribution system before and after the application 

of load management tools, so that the value can be 

accurately known.

For the first time utilities will be able to accurately 

measure voltage, load, and reactive power at the 

distribution level down to individual customers. 

Data will be available to determine the level of losses 

occurring on a circuit and what control actions are 

needed. For example, the data will show when and 

how to optimally adjust circuit voltage level to reduce 

demand or save energy. 

•	 Providing the ability to control or shift demand at

peak times

Customer load can be reduced or shifted by application 

of smart thermostats, pool pump controls, water heater 

controls, appliance controls, etc. This is most valuable 

during peak load events when the combination of energy 

savings and peak capacity savings is at its highest.

•	 Providing the ability to utilize/control distributed

generation (i.e. fuel cells, batteries, solar arrays, 

PHEV’s etc.) as needed.

Customers may invest in distributed resources and 

energy storage to reduce their peak demand as measured 

by their electric meters, which typically measure noncoincident peak demand. With smart grid tools, the 

energy control center can interface with distributed 

generation to provide additional capacity at the utility’s 

peak time or store renewable energy during off-peak 

periods, both of which benefit the system, but might not 

be apparent to the individual customer. 

These types of control may enable the utility to avoid 

load during the needle peak hours – when marginal line 

losses may exceed 20%, and when generation reserves are 

stretched thin at a much lower cost than building additional 

generation, transmission, and distribution capacity. This 

will have a small effect on the value of energy conservation 

measures, such as those described here, which provide 

savings for thousands of hours per year. However, it may 

provide significant cost relief to the utility and its consumers 

in avoiding the cost of seldom-used capacity, thereby adding 

great value to the types of measures that provide savings 

concentrated at the time of the system peak demand. 

The measures mentioned above are part of the emerging 

demand response capability of smart grid, which promises 

to provide a verifiable virtual reserve of reliable capacity 

directly equivalent to a spinning reserve but at a much lower 

cost. 

Summary: The Avoided Line Losses and 

Avoided Reserves Benefits of Energy 

Efficiency Are Very Important

This paper has attempted to highlight two oftenoverlooked attributes of energy efficiency investments. 

First, energy efficiency measures typically provide 

significant savings at the time of the system peak demand, 

and that time occurs when the line losses are highest. The 

avoided line losses can add as much as 20% to the capacity 

value measured at the customer meter.

Second, because they are reducing loads, including 

marginal line losses, energy efficiency measures also reduce 

the level of required generating reserves. 

Each of these benefits increases the economic 

savings provided by energy efficiency investments. The 

compounding of a 20% marginal line loss savings and a 

15% reserves savings can produce a 44% total generating 

capacity benefit, over and above the peak load reduction 

measured at the customer’s meter.

For peak-oriented loads like air conditioning, the annual 

capacity cost of generation, transmission, and distribution 

capacity needed to assure reliable service can equal or 

exceed the cost of the energy used during the year. 

Add it all together, and the total capacity value of energy 

efficiency investments in peak-oriented loads like space 

conditioning can be as valuable as the energy savings are.

Marginal line loss calculations and avoided reserve 

requirements should be an integral part of any evaluation of 

the benefits of energy efficiency measures.
The Regulatory Assistance Project (RAP) is a global, non-profit team of experts focused on the 

long-term economic and environmental sustainability of the power and natural gas sectors. We provide 

technical and policy assistance on regulatory and market policies that promote economic efficiency, 

environmental protection, system reliability and the fair allocation of system benefits among consumers. We 

have worked extensively in the US since 1992 and in China since 1999. We added programs and offices in 

the European Union in 2009 and plan to offer similar services in India in the near future.

Visit our website at www.raponline.org to learn more about our work.
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