C O R P O R A T I O N
Measuring the Resilience of Energy Distribution Systems
Henry H. Willis and Kathleen Loa
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iii
Preface
As policymakers continue to consider the complex risks from natural disasters, terrorism, aging infrastructure, and climate change, resilience is a topic that is likely to receive increasing atten-tion. If energy infrastructure’s resilience is to improve, better use of metrics will be crucial to guiding planning and evaluating progress. This report reviews literature on metrics for energy system resilience to help the U.S. Department of Energy develop a framework for evaluating and improving the resilience of energy systems for use in its ongoing efforts to draft the first Quadrennial Energy Review.
The report was sponsored by the U.S. Department of Energy, Office of Energy Policy and Systems Analysis. It should be of interest to policymakers, energy industry professionals, and researchers interested in understanding how to manage resilience of infrastructure systems.
The RAND Environment, Energy, and Economic Development Program
The research reported here was conducted in the RAND Environment, Energy, and Economic Development Program, which addresses topics relating to environmental quality and regula-tion, water and energy resources and systems, climate, natural hazards and disasters, and eco-nomic development, both domestically and internationally. Program research is supported by government agencies, foundations, and the private sector.
This program is part of RAND Justice, Infrastructure, and Environment, a division of the RAND Corporation dedicated to improving policy and decisionmaking in a wide range of policy domains, including civil and criminal justice, infrastructure protection and homeland security, transportation and energy policy, and environmental and natural resource policy.
Questions or comments about this report should be sent to the project leader, Henry H. Willis ([email protected]). For more information about the Environment, Energy, and Economic Development Program, see http://www.rand.org/energy or contact the director at [email protected].
v
Acknowledgments
The authors wish to thank Debra Knopman (RAND Corporation), Keith Crane (RAND Cor-poration), Eric Vugrin (Sandia National Laboratory), and Ross Guttromson (Sandia National Laboratory) for the discussions and suggestions they provided while this work was completed.
vii
Contents
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iiiAcknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vFigures and Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
CHAPTER ONE
Measuring the Resilience of Energy Distribution Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
CHAPTER TWO
Defining Resilience for Infrastructure Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
CHAPTER THREE
A Framework for Organizing Resilience Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
CHAPTER FOUR
Existing Metrics for Resilience of Electricity, Refined Oil, and Natural Gas Systems . . . . . . . . . . . . 9
CHAPTER FIVE
Developing Metrics for Energy Resilience . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23Improve Collection and Management of Data on Inputs and Capacities at the Facility and
System Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23Develop Better Measures of Capabilities at the System and Regional Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . 23Improve Understanding of How Capabilities and Performance Translate to Outcomes at
the Regional and National Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
ix
Figures and Tables
Figures 2.1. Resilience Describes the State of Service from a System in Response to a Disruption . . . . . 4 2.2. Different Systems Will Have Different Resilience to the Same Disruption . . . . . . . . . . . . . . . . . 5 2.3. Different Responses Will Lead to Different Resilience at Different Costs . . . . . . . . . . . . . . . . . . . 5 2.4. Resilience of a System Also Depends on the Timescale Considered . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.1. Metrics Can Serve Both Operational and Strategic Decisionmaking . . . . . . . . . . . . . . . . . . . . . . . . 8 4.1. Summary of Reviewed Literature on Energy Resilience Metrics, by Sector . . . . . . . . . . . . . . . 10 4.2. Summary of Metrics Identified, by Resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 4.3. Summary of Facility/System Metrics Identified, by Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 4.4. Summary of System/Region/Nation Metrics Identified, by Type . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Tables 4.1. Overview of Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 4.2. Energy Resilience Metrics for Electricity Systems at the Facility/System Level . . . . . . . . . . . . 14 4.3. Energy Resilience Metrics for Electricity Systems at the System/Region Level . . . . . . . . . . . . 17 4.4. Energy Resilience Metrics for Electricity Systems at the Region/Nation Level . . . . . . . . . . . . 19 4.5. Energy Resilience Metrics for Oil and Natural Gas Systems at the Facility/System
Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 4.6. Energy Resilience Metrics for Oil and Natural Gas Systems at the System/
Region Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 4.7. Energy Resilience Metrics for Oil and Natural Gas Systems at the Region/Nation
Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
1
CHAPTER ONE
Measuring the Resilience of Energy Distribution Systems
The U.S. economy depends on reliable and affordable distribution of energy. However, energy distribution systems are vulnerable to a diverse and dynamic set of disruptions. Sev-eral events over the past few years highlight the range of challenges that energy distribution systems need to address and how those challenges are evolving due to climate change and new technologies.
In 2012, Superstorm Sandy left more than 8.5 million customers without power, with out-ages persisting more than one week (U.S. Department of Energy, 2012a). While communities recovered, residents faced shortages of gasoline that persisted during the same period (National Association of Convenience Stores, 2013). Extreme cold spells in the Northeast during the winter of 2014 sharply increased demand for natural gas, leading the prices of gas and elec-tricity to rise (U.S. Energy Information Association, 2014). Furthermore, in 2013, Pacific Gas and Electric Company’s Metcalf transmission substation in San Jose, California, suffered a complex attack involving the physical damage of transformers and the systematic disabling of both emergency response communications and supervisory control and data acquisition systems, highlighting the vulnerability of the power grid to both physical and cyber sabotage ( Memmott, 2014).
Events like these have motivated the federal government to develop a coordinated strat-egy to improve infrastructure performance, security, and resilience. Specifically, President Barack Obama has called upon the federal government to (1) advance a national unity of effort to strengthen and maintain secure, functioning, and resilient critical infrastructure (White House, 2013) and (2) strengthen U.S. energy policy by addressing challenges faced by the nation’s energy infrastructure (White House, 2014).
As part of the response to these mandates and as part of the 2014 Quadrennial Energy Review, the Department of Energy asked the RAND Corporation to develop a framework for measuring the resilience of energy distribution systems and to summarize the state of metrics for resilience of the electric power, refined oil, and natural gas distribution systems.
This report summarizes the concepts addressed by measures of resilience (Chapter Two), describes a framework for organizing alternative metrics used to measure resilience of energy distribution systems (Chapter Three), and reviews the state of metrics for resilience of such systems (Chapter Four).
3
CHAPTER TWO
Defining Resilience for Infrastructure Systems
Resilience has been defined many ways. Consider, for example, the following definitions from engineering literature, policy directives, and the academic community:
Resilience is the ability of the system to withstand a major disruption within acceptable degradation parameters and to recover within an acceptable time and composite costs and risks. (Haimes, 2009)
Resilience is the ability to prepare for and adapt to changing conditions and withstand and recover rapidly from disruptions. . . . [It] includes the ability to withstand and recover from deliberate attacks, accidents, or naturally occurring threats or incidents. (White House, 2013)
Resilience is the ability to prepare and plan for, absorb, recover from, and more success-fully adapt to adverse events. (Committee on Increasing National Resilience to Hazards and Disasters; Committee on Science, Engineering, and Public Policy; and The National Academies, 2012)
While distinctions exist among definitions, comparing them reveals four aspects of the system being addressed.
First, resilience describes the state of service being provided by a system in response to a disruption. When assessing resilience, key questions would be whether the service has been degraded, how much of the service has been degraded, how quickly the service has been restored, and how completely the service has been restored. Therefore, resilience does not describe a dichotomous state of whether or not a disruption has occurred. Rather, resilience describes the degree of disruption across multiple dimensions, which could include type, qual-ity, time, and geography of service provision. Figure 2.1 illustrates a notional response of an energy system to a disruption. Percentage of service provided, reflected along the y-axis, could be measured in terms of electricity delivered, gallons of fuel shipped, economic output gener-ated by energy, or other metrics that will be discussed in subsequent chapters. The disruption could be a natural disaster, industrial accident, or terrorist attack. The time of disruption and rate of service decline would depend on the nature of the event, design of the system, and mode with which the system is operated. The duration of disruption (measured in time and reflected along the x-axis), along with the rate and extent of recovery, would depend on these same fac-tors. Recovery may not be complete, as illustrated in the Figure 2.1 example, in which service delivery only recovers to 90 percent of its original level.
4 Measuring the Resilience of Energy Distribution Systems
Second, the state of a system depends on how it was designed and how it is operated. These choices influence whether and how service is degraded during a disruption, how quickly it recovers, and how completely it recovers. For example, an electricity grid system that is designed with more redundancy, operated with more contingencies for backup, and designed with recovery in mind (Figure 2.2, System B) might experience a lesser and briefer disruption and, if so, would be more resilient than a system that has less redundancy, has fewer backups, and is more difficult to rebuild (Figure 2.2, System A).
Third, different responses will lead to different resilience at different costs. For example, with additional resources, it may be possible to rebuild an electricity grid after a disaster with more-efficient equipment, and as a result, the quality of service provided after recovery could exceed the original level of service provided (Figure 2.3, System B, Response 2).
Finally, resilience of a system also depends on the timescale. If recovery of a grid places equipment where it was and as it was designed, over a period of years, the system may expe-rience repeated disruptions if climate change leads to greater frequency of intense flooding (Figure 2.4, Response 1). If the system is continually maintained and upgraded, the service provided could improve, but at a cost (Figure 2.4, Response 2). However, if maintenance and upgrades are not made, operations might be cheaper but service could be expected to decline in the future (Figure 2.4, Response 3).
Figure 2.1Resilience Describes the State of Service from a System in Response to a Disruption
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Defining Resilience for Infrastructure Systems 5
Figure 2.2Different Systems Will Have Different Resilience to the Same Disruption
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Figure 2.3Different Responses Will Lead to Different Resilience at Different Costs
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6 Measuring the Resilience of Energy Distribution Systems
Our review of definitions finds additional concepts that are sometimes included in definitions of resilience. Some of these are redundant; others distinguish important system characteristics. Examples are reliability, robustness, recoverability, sustainability, hardness, vulnerability, fault tolerance, and redundancy. While relevant, these additional terms are not used consistently. Reconciling the competing definitions of resilience in the literature is a dif-ficult and not terribly productive task. Instead, when attempting to define metrics of resilience in the context of the Quadrennial Energy Review, it is more important to capture the relevant aspects of service delivery, system design, system operations, disruptions, costs, and timescale.
Figure 2.4Resilience of a System Also Depends on the Timescale Considered
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CHAPTER THREE
A Framework for Organizing Resilience Metrics
We track metrics to be able to keep score, to tell whether goals have been met or whether success has been achieved. We track metrics to improve quality, to tell where improvements are possible and whether progress is being made. We also track metrics simply to account for resources, to tell whether budgets are being met and to know where assets reside.
Metrics of resilience are used for many purposes and at many levels. Some of the reasons for metrics are more relevant to a federal perspective and others to a local or facility perspec-tive. For example, at a national or regional level, it may be important to know how resilience affects economic output or economic damage stemming from disasters. For a refinery operator, it may be more important to know how many spare parts are in stock and what options exist for backup power generation.
There is no single set of metrics that supports all decisionmaking needs; rather, each purpose may need a unique set of metrics. But across levels of decisionmaking, the metrics ought to be organized within a consistent measurement framework. Logic models provide a consistent framework for organizing metrics in the fields of program evaluation and qual-ity improvement (Rogers et al., 2000; Greenfield, Williams, and Eiseman, 2006). From an operational perspective, a logic model explains how activities, budgets, and people (i.e., inputs) ultimately contribute to desired outcomes. From a strategic perspective, a logic model explains which inputs are needed to support strategy. From either perspective, a hierarchy of metrics exists to connect inputs to outcomes and improve understanding about how to achieve out-comes more effectively and efficiently (Figure 3.1).
The building blocks of resilience are inputs, which define what is available to support resil-ience. In the context of energy systems, examples of inputs include budgets, equipment, spare parts, and personnel to support recovery operations. On their own, these inputs do not provide resilience unless they are organized to support functions or tasks.
In a logic model framework, the ways in which inputs are organized to support resil-ience are called capacities. Examples of capacities for energy systems include response teams capable of repairing equipment, recovery plans that can be implemented following a disaster, or advanced technologies that can be used to reroute power and reconstitute portions of a grid during disruptions. Having these capacities in place is not the same thing as being able to use them, however.
Capability metrics reflect how well capacities can serve a system when they are needed. Ultimately, capability metrics describe how proficiently tasks can be performed. Examples include the ability to detect leaks or outages, to repair damaged power lines or pipelines, or to restore power outages.
8 Measuring the Resilience of Energy Distribution Systems
Capabilities are ultimately desired because they improve system performance. Performance metrics describe what is produced by an engineered system. In the context of energy systems, examples of metrics include the amount of energy delivered or operating characteristics of the system, such as efficiency, reliability, fault tolerance, sustainability, or robustness.
In the end, the performance of energy systems depends on how the systems generate the outcomes that society is seeking to achieve. Resilience of energy systems can be measured by many outcomes, such as reduced damage from disasters, increased economic activity, or reduced deaths and injuries from disasters.
The literature on measuring resilience contains examples of metrics from each of these categories: inputs, capacities, capabilities, performance, and outcomes. When selecting metrics for resilience, it is useful to understand the availability and maturity of metrics that exist across these categories.
Figure 3.1Metrics Can Serve Both Operational and Strategic Decisionmaking
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PerformanceCapabilitiesCapacitiesInputs Outcomes
What is produced?
What tasks can be performed?
How are inputs organized?
What is available?
What is achieved?
Examples• Energy delivery• Ef�ciency• Reliability• Hardness• Robustness• Sustainabiity
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economic activity
• Reduced costs and damage
• Improved human welfare
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CHAPTER FOUR
Existing Metrics for Resilience of Electricity, Refined Oil, and Natural Gas Systems
To better understand how industry, governments, and communities assess the resilience of energy systems, we reviewed published reports and peer-reviewed journal articles to find exam-ples of metrics that are being discussed and used. We analyzed studies from 1997 to 2014, identified by searching several commonly used databases for terms related to measurement, resilience, and energy (see Table 4.1).
The literature search identified 58 papers and reports related to measuring energy system resilience (see Figure 4.1), and we reviewed each paper to identify resilience metrics. Tables 4.2, 4.3, and 4.4 list examples of metrics that were discussed in these papers.1 The 154 metrics that we identified illustrate the types of resilience metrics that are used across the energy industry. The units used and concepts tracked by metrics vary at each level of the hierarchy. At the input level, metrics tend to describe the amount of energy produced, transmitted, or stored or the number of people, facilities, or equipment available to support these activities. At the capacity level, metrics describe the existence and extent of systems, policies, and organizations in place to support energy capabilities. At the capability level, metrics describe the potential for energy systems to provide sources or factors that determine that capability. At the performance level, metrics describe the quality, amount, and efficiency of the services being provided by energy systems. Finally, the outcome level describes how energy influences aspects of societal welfare through health, safety, and the economy. Examples and descriptions of specific metrics can be found in the literature cited for each exemplary metric.
1 The citations listed in Tables 4.2, 4.3, and 4.4 are instances where the metric can be found in the literature. In some cases, the same metric was listed in several papers. We did not attempt to catalog all citations for each metric. As a result, we have also not cited in these tables every paper that was reviewed as part of this study. The full list of papers reviewed is included in the bibliography.
Table 4.1Overview of Literature Review
Criteria Details of Literature Review
Databases searched Web of Science, GreenFile, Science.gov, Google, Google Scholar
Years included 1997–2014
Search terms used distribution, electrical power, electricity, energy, fuel, gasoline, generation, grid, indicator, index, measure, metric, natural gas, nuclear, petrochemical, petroleum, pipelines, power, production, redundancy, reliability, resilience, transmission, vulnerability
10 Measuring the Resilience of Energy Distribution Systems
The review of metrics provides examples of the many approaches that are being used to measure the resilience of energy systems. To better understand the range of metrics that exist for energy resilience, we categorized metrics by three dimensions: resolution, type, and maturity.
Resolution refers to the scale of the system being described. Metrics are collected at differ-ent resolutions based on who is monitoring them and why. The literature we reviewed focused on metrics for individual facilities, for systems owned by single firms,2 and for regions in which several systems exist, as well as from a national perspective. In practice, there is some semantic ambiguity about whether a metric provides perspective for a facility or a system, a system or a region, or a region or the nation. To reflect this ambiguity, our categorizations in Tables 4.2, 4.3, and 4.4 present metrics for electricity systems at a facility/system level, system/region level, and region/nation level, respectively. Tables 4.5, 4.6, and 4.7 present metrics for oil or gas sys-tems at the same levels.
The second dimension, type, refers to where the metric fits within the organizing frame-work described in Chapter Three. The extent to which measures exist for inputs, capacities, capabilities, performance, and outcomes also depends on how measures are being used. While planning and evaluation efforts are most interested in capabilities, performance, and out-comes, resource allocation and accountability efforts also need to track the status of inputs and capacities.
2 In this context, we are using the word system to refer to a collection of infrastructure that operates together to provide a coordinated service. Examples of systems are portions of the electricity grid, pipeline networks, or railway networks. Depending on the context, a system could be operated by a single company or authority. In other contexts, systems could be operated through coordination by multiple firms.
Figure 4.1Summary of Reviewed Literature on Energy Resilience Metrics, by Sector
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Maturity refers to how well defined the metrics are, how systematically they are collected, and how well they are organized. Our assessment of maturity reflects the practical challenges that extend beyond defining metrics and that can arise when collecting and managing data. We categorized metrics into three levels of maturity:
• Low—Metrics are mentioned in the literature but not consistently defined, and, if col-lected, only sporadically or inconsistently.
• Medium—Metrics are collected using well-defined methods but collected sporadically.• High—Metrics are collected using well-defined methods and collected at the appropriate
timescale.
By categorizing the metrics in this way, we drew three observations about the state of measur-ing resilience of energy systems.
First, there are more metrics for electricity systems (105 in the reviewed literature) than for systems for oil or natural gas (67 metrics).3 The difference in numbers of metrics is a result of two factors. First, as Figure 4.1 illustrates, we identified fewer papers about oil and gas systems than about electricity systems. Second, the papers about electricity systems covered more aspects of resilience than the papers about oil and gas systems. Greater attention to the resilience of electricity systems is not surprising, given that the electricity grid infrastructure (e.g., transmission and distribution lines) is more exposed and vulnerable to disruptions than oil and gas infrastructure (e.g., pipelines and storage tanks).
Second, the literature pays more attention to metrics for the more detailed levels of facili-ties and systems. Almost half of the metrics identified (70 of 154) describe aspects of systems at the facility and system levels (see Figure 4.2). Many more types of inputs and capacities are measured as part of inventory and accounting processes across the energy industry than were identified in the literature.
While there is greater attention to metrics at the facility/system level, these metrics pre-dominantly described inputs, capabilities, and performance (63 of 70 shown in Figure 4.3). Only one outcome metric was identified for the facility/system level, a component of a loss damage index describing damage caused by fire. Furthermore, most of these metrics (53 of 70) were judged to be of low or medium maturity. One possible explanation for this is that metrics at the facility and system levels are collected and managed by different entities that are more directly responsible for managing resources to improve performance than for support-ing broader societal outcomes. In addition, each entity may have its own reasons for collecting metrics and may have crafted definitions of metrics that most suit its own needs. Therefore, there may be opportunities to standardize definitions of metrics collected at the facility and system levels and potentially create a systematic means of collecting and aggregating data across facilities and systems if efficient means of doing so can be implemented.
3 Although only 154 metrics were identified, some metrics are relevant to more than one sector. Thus, the total mentioned here is 172.
12 Measuring the Resilience of Energy Distribution Systems
Figure 4.2Summary of Metrics Identified, by Resolution
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Figure 4.3Summary of Facility/System Metrics Identified, by Type
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Existing Metrics for Resilience of Electricity, Refined Oil, and Natural Gas Systems 13
Third—and in contrast to the facility/system level—regional and national metrics focus more on aspects of performance and outcomes. We identified 50 performance and outcome metrics at these levels, and 22 of the 23 outcome metrics were at the system/region/nation level (see Figure 4.4). Generally, performance measures existed at the system/region level and were of medium to high maturity. In comparison, outcome measures were identified at both the system/region and region/nation levels, but they were judged to be of low or medium maturity. Furthermore, the literature did not clearly describe how the performance of systems contributed to changes in outcomes. This raises questions about whether it is possible to effec-tively manage energy systems to achieve desired outcomes by tracking performance metrics. As a result, understanding how infrastructure performance contributes to societal outcomes remains an active area of research. This suggests that opportunities may exist to improve track-ing and use of outcome data.
In summary, the metrics from our literature review, presented in Tables 4.2 through 4.7, present a complex picture of how resilience is managed and measured in energy systems. While many metrics exist, there is no single metric or set of metrics for each purpose. Different met-rics are needed to understand resilience at different levels of energy systems, and opportunities exist to improve metrics for each purpose.
Figure 4.4Summary of System/Region/Nation Metrics Identified, by Type
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14 Measuring the Resilience of Energy Distribution Systems
Tab
le 4
.2En
erg
y R
esili
ence
Met
rics
fo
r El
ectr
icit
y Sy
stem
s at
th
e Fa
cilit
y/Sy
stem
Lev
el
Inp
uts
Cap
acit
ies
Cap
abili
ties
Perf
orm
ance
Ou
tco
mes
Ener
gy
feed
sto
ck (
H)
(McC
arth
y, O
gd
en, a
nd
Sp
erlin
g, 2
007
)
Ener
gy
no
t su
pp
lied
(L)
(B
ran
cucc
i Mar
tín
ez-
An
ido
et
al.,
2012
)
Ener
gy
sto
rag
e (L
) (B
hat
nag
ar e
t al
., 20
13)
Gen
erat
ors
ava
ilab
le (
#)
(H)
(Ro
e an
d S
chu
lman
, 20
12)
Hyd
rop
ho
bic
co
atin
g o
n
equ
ipm
ent
(L)
(Keo
gh
an
d C
od
y, 2
013)
Key
rep
lace
men
t eq
uip
men
t st
ock
pile
(L)
(K
eog
h a
nd
Co
dy,
201
3)
Red
un
dan
t p
ow
er li
nes
(L
) (K
eog
h a
nd
Co
dy,
20
13)
Rei
nfo
rced
co
ncr
ete
vers
us
wo
od
en
dis
trib
uti
on
po
les
(L)
(Keo
gh
an
d C
od
y, 2
013)
Siti
ng
infr
astr
uct
ure
(L)
(K
eog
h a
nd
Co
dy,
201
3)
Un
der
gro
un
d, o
verh
ead
, u
nd
erse
a d
istr
ibu
tio
n/
cab
le li
nes
(M
) (D
ou
kas
et
al.,
2011
; Ro
use
an
d K
elly
, 20
11)
Un
iqu
e en
cryp
ted
p
assw
ord
s fo
r u
tilit
y “s
mar
t” d
istr
ibu
tio
n (
L)
(Keo
gh
an
d C
od
y, 2
013)
Wo
rker
s em
plo
yed
(#)
(H
) (M
cCar
thy,
Og
den
, an
d
Sper
ling
, 20
07; K
eog
h
and
Co
dy,
201
3)
Co
mm
un
icat
ion
/co
ntr
ol s
yste
ms/
con
tro
l cen
ters
(L)
(W
ard
, 201
3)
Elec
tric
al p
rote
ctio
n a
nd
met
erin
g
(L)
(War
d, 2
013)
Equ
ipm
ent
po
siti
on
ing
(L)
(K
eog
h
and
Co
dy,
201
3)
Flo
w p
ath
s, li
ne
flo
w li
mit
s (L
) (B
om
par
d, N
apo
li, a
nd
Xu
e, 2
010)
Gen
/lo
ad b
us
dis
trib
uti
on
(L)
(B
om
par
d, N
apo
li, a
nd
Xu
e, 2
010)
Res
erve
/sp
are
cap
acit
y (M
) (W
illis
an
d G
arro
d, 1
997;
Mo
lyn
eau
x et
al
., 20
12)
Sub
stat
ion
s (s
wit
chya
rds)
—o
verh
ead
lin
es a
nd
un
der
gro
un
d
cab
les
are
inte
rco
nn
ecte
d (
L)
(War
d, 2
013)
An
cilla
ry s
ervi
ce (
L) (
Bh
atn
agar
et
al.,
201
3)
Haz
ard
rat
e re
lati
ng
fu
nct
ion
—al
tere
d h
azar
d r
ate
of
com
po
nen
t af
ter
a ce
rtai
n
mai
nte
nan
ce (
M)
(Wan
g a
nd
G
uo
, 201
3)
Lin
e m
itig
atio
n—
rero
ute
el
ectr
ical
flo
ws
du
e to
lin
e o
verl
oad
ing
or
“co
ng
esti
on
” (L
) (R
oe
and
Sch
ulm
an, 2
012)
Load
bia
sin
g—
maj
or
adju
stm
ents
in a
uto
mat
ed
dis
pat
chin
g s
oft
war
e (L
) (R
oe
and
Sch
ulm
an, 2
012)
Net
-ab
ility
—m
easu
res
the
apti
tud
e o
f th
e g
rid
in
tran
smit
tin
g p
ow
er f
rom
g
ener
atio
n t
o lo
ad b
use
s ef
fici
entl
y (L
) (B
om
par
d, N
apo
li,
and
Xu
e, 2
010)
Path
red
un
dan
cy—
asse
sses
th
e av
aila
ble
red
un
dan
cy in
ter
ms
of
pat
hs
in t
ran
smit
tin
g p
ow
er f
rom
a
gen
erat
ion
to
a lo
ad b
us
bas
ed
on
en
tro
py
(L)
(Bo
mp
ard
, Nap
oli,
an
d X
ue,
201
0)
Pro
tect
ive
and
sw
itch
ing
d
evic
es—
mea
n t
ime
to r
epai
r (M
) (Y
edd
anap
ud
i, 20
12)
Pro
tect
ive
and
sw
itch
ing
d
evic
es—
swit
chin
g r
elia
bili
ty (
M)
(Yed
dan
apu
di,
2012
)
Pro
tect
ive
and
sw
itch
ing
d
evic
es—
mea
n t
ime
to s
wit
ch
(M)
(Yed
dan
apu
di,
2012
)
Via
bili
ty o
f in
vest
men
ts (
L)
(McC
arth
y, O
gd
en, a
nd
Sp
erlin
g,
2007
)
Co
effi
cien
t o
f va
riat
ion
of
the
freq
uen
cy in
dex
of
sag
s (M
) (S
hu
n e
t al
., 20
12)
Co
ntr
ol P
erfo
rman
ce S
tan
dar
d 2
vi
ola
tio
ns—
on
e o
f th
e C
alif
orn
ia
Ind
epen
den
t Sy
stem
Op
erat
or
CII
SO
pri
nci
pal
rel
iab
ility
sta
nd
ard
s (H
) (R
oe
and
Sch
ulm
an, 2
012)
Bu
lk e
lect
ric
syst
em r
elia
bili
ty
per
form
ance
ind
ices
(M
) (B
illin
ton
an
d
Wan
gd
ee, 2
006
)
Der
ated
po
wer
—ra
ted
po
wer
mu
ltip
le
wit
h t
he
relia
bili
ty o
f th
e p
lan
t (M
) (V
oo
rsp
oo
ls a
nd
D’H
aese
leer
, 20
04)
Dro
pp
ed/l
ost
ph
ase
—p
ow
er q
ual
ity
met
ric
(M)
(Ro
use
an
d K
elly
, 201
1)
Edg
e re
silie
nce
tra
ject
ory
—re
lati
on
ship
bet
wee
n r
elia
bili
ty a
nd
re
silie
nce
tra
ckin
g a
mo
vin
g r
ang
e o
f R
2 fo
r th
e C
on
tro
l Per
form
ance
St
and
ard
2 (
H)
(Ro
e an
d S
chu
lman
, 20
12)
Ener
gy
effi
cien
cy/i
nte
nsi
ty (
H)
(Gn
anso
un
ou
, 20
08; M
oly
nea
ux
et a
l.,
2012
; Wan
g e
t al
., 20
12)
Failu
re r
ate
(M)
(Wan
g a
nd
Gu
o, 2
013)
Flic
ker—
po
wer
qu
alit
y m
etri
c (M
) (R
ou
se a
nd
Kel
ly, 2
011)
Har
mo
nic
dis
tort
ion
s—p
ow
er q
ual
ity
met
ric
(M)
(Ro
use
an
d K
elly
, 201
1)
Ove
rhea
d a
nd
un
der
gro
un
d li
ne
seg
men
ts—
mea
n t
ime
to r
epai
r (L
) (Y
edd
anap
ud
i, 20
12)
Ove
rhea
d a
nd
un
der
gro
un
d li
ne
seg
men
ts—
per
man
ent
failu
re r
ate
(L)
(Yed
dan
apu
di,
2012
)
Load
loss
dam
age
ind
ex—
dam
age
cau
sed
by
fire
to
th
e el
ectr
ical
sys
tem
(M
) (L
uci
a,
2012
; Bag
chi,
Spri
nts
on
, an
d
Sin
gh
, 201
3)
Existing Metrics for Resilience of Electricity, Refined Oil, and Natural Gas Systems 15
Inp
uts
Cap
acit
ies
Cap
abili
ties
Perf
orm
ance
Ou
tco
mes
Ove
rhea
d a
nd
un
der
gro
un
d li
ne
seg
men
ts—
tem
po
rary
fai
lure
rat
e (L
) (Y
edd
anap
ud
i, 20
12)
Peak
-to
-pea
k vo
ltag
e—
po
wer
qu
alit
y m
etri
c (M
) (R
ou
se a
nd
Kel
ly, 2
011)
Phas
e im
bal
ance
—p
ow
er q
ual
ity
met
ric
(M)
(Ro
use
an
d K
elly
, 201
1)
Pro
tect
ive
and
sw
itch
ing
d
evic
es—
pro
bab
ility
of
failu
re (
M)
(Yed
dan
apu
di,
2012
)
Pro
tect
ive
and
sw
itch
ing
d
evic
es—
pro
tect
ion
rel
iab
ility
(M
) (Y
edd
anap
ud
i, 20
12)
Pro
tect
ive
and
sw
itch
ing
dev
ices
—R
eclo
se r
elia
bili
ty (
M)
(Yed
dan
apu
di,
2012
)
Rap
id v
olt
age
chan
ges
—p
ow
er
qu
alit
y m
etri
c (M
) (R
ou
se a
nd
Kel
ly,
2011
)
Res
ilien
ce in
dex
(1)—
par
amet
er t
hat
q
uan
tifi
es t
he
po
ten
tial
pro
bab
ility
fo
r th
e m
alfu
nct
ion
of
the
syst
em (
M)
(Afg
an a
nd
Cve
tin
ovi
c, 2
010)
Res
ilien
ce in
dex
(2)
—d
eriv
ed f
rom
ro
bu
stn
ess,
res
ou
rcef
uln
ess,
an
d
reco
very
; ran
ge
fro
m 0
(lo
w r
esili
ence
) to
10
0 (h
igh
res
ilien
ce)
(M)
(Fis
her
et
al.,
2010
; Car
lso
n e
t al
., 20
12; A
fgan
an
d C
veti
no
vic,
201
3)
Surv
ivab
ility
—ev
alu
ate
the
apti
tud
e o
f th
e n
etw
ork
in a
ssu
rin
g t
he
po
ssib
ility
to
mat
ch g
ener
atio
n a
nd
d
eman
d in
cas
e o
f fa
ilure
s o
r at
tack
s (L
) (B
om
par
d, N
apo
li, a
nd
Xu
e, 2
010)
Syst
em a
vera
ge
inte
rru
pti
on
du
rati
on
in
dex
—su
stai
ned
ou
tag
e m
etri
c;
mea
sure
s an
nu
al s
yste
mw
ide
ou
tag
e d
ura
tio
n f
or
sust
ain
ed o
uta
ges
(H
) (L
ayto
n, 2
00
4; E
to a
nd
LaC
om
mar
e,
2008
; Ro
use
an
d K
elly
, 201
1)
Tab
le 4
.2—
Co
nti
nu
ed
16 Measuring the Resilience of Energy Distribution Systems
Inp
uts
Cap
acit
ies
Cap
abili
ties
Perf
orm
ance
Ou
tco
mes
Syst
em a
vera
ge
inte
rru
pti
on
fr
equ
ency
ind
ex—
sust
ain
ed o
uta
ge
met
ric;
mea
sure
s sy
stem
wid
e o
uta
ge
freq
uen
cy f
or
sust
ain
ed o
uta
ges
(H
) (L
ayto
n, 2
00
4; E
to a
nd
LaC
om
mar
e,
2008
; Ro
use
an
d K
elly
, 201
1)
Un
sch
edu
led
gen
erat
or
ou
tag
es (
L)
(Ro
e an
d S
chu
lman
, 201
2)
Vo
ltag
e d
ips—
po
wer
qu
alit
y m
etri
c (M
) (R
ou
se a
nd
Kel
ly, 2
011)
Vo
ltag
e le
vel/
sup
ply
vo
ltag
e va
riat
ion
s—p
ow
er q
ual
ity
met
ric
(M)
(Ro
use
an
d K
elly
, 201
1)
Vo
ltag
e sa
gs/
swel
ls—
po
wer
qu
alit
y m
etri
c (M
) (R
ou
se a
nd
Kel
ly, 2
011)
Vo
ltag
e u
nb
alan
ce—
po
wer
qu
alit
y m
etri
c (M
) (R
ou
se a
nd
Kel
ly, 2
011)
NO
TE: M
etri
c ap
pea
rs in
bo
ld. M
atu
rity
leve
l ap
pea
rs in
par
enth
eses
: H =
hig
h; M
= m
ediu
m; a
nd
L =
low
. Th
e ci
tati
on
s in
clu
ded
in t
his
tab
le a
re in
stan
ces
wh
ere
the
met
ric
can
be
fou
nd
in t
he
liter
atu
re, b
ut
they
are
no
t n
eces
sari
ly e
xhau
stiv
e.
Tab
le 4
.2—
Co
nti
nu
ed
Existing Metrics for Resilience of Electricity, Refined Oil, and Natural Gas Systems 17
Tab
le 4
.3En
erg
y R
esili
ence
Met
rics
fo
r El
ectr
icit
y Sy
stem
s at
th
e Sy
stem
/Reg
ion
Lev
el
Inp
uts
Cap
acit
ies
Cap
abili
ties
Perf
orm
ance
Ou
tco
mes
Tran
smis
sio
n li
nes
av
aila
ble
(#)
(M
) (R
oe
and
Sch
ulm
an, 2
012)
Fun
ctio
nal
zo
nes
—g
ener
atio
n, t
ran
smis
sio
n, a
nd
d
istr
ibu
tio
n (
H)
(McC
arth
y,
Og
den
, an
d S
per
ling
, 20
07)
Hie
rarc
hic
al le
vels
(H
LI,
HLI
I, H
LIII
)—H
LI c
on
sid
ers
on
ly g
ener
atin
g f
acili
ties
, H
LII a
dd
s tr
ansm
issi
on
fa
cilit
ies,
an
d H
LIII
incl
ud
es
all t
hre
e fu
nct
ion
al z
on
es
(H)
(McC
arth
y, O
gd
en, a
nd
Sp
erlin
g, 2
007
)
Op
erat
or
trai
nin
g (
L) (
Keo
gh
an
d C
od
y, 2
013)
Mu
tual
ass
ista
nt
agre
emen
ts
(L)
(Keo
gh
an
d C
od
y, 2
013)
Tran
sfo
rmer
s—co
nn
ecti
ng
p
arts
of
the
net
wo
rk
op
erat
ing
at
dif
fere
nt
volt
ages
(L)
(W
ard
, 201
3)
Tree
tri
mm
ing
met
rics
(L)
(K
eog
h a
nd
Co
dy,
201
3)
Ad
equ
acy—
the
abili
ty o
f th
e sy
stem
to
su
pp
ly c
ust
om
er
req
uir
emen
ts u
nd
er n
orm
al
op
erat
ing
co
nd
itio
ns
(H)
(McC
arth
y, O
gd
en, a
nd
Sp
erlin
g,
2007
)
Co
ng
esti
on
co
ntr
ol (
L) (
Car
valh
o
et a
l., 2
014)
Ave
rag
e Se
rvic
e A
vaila
bili
ty In
dex
(A
NSI
) (H
) (L
ayto
n, 2
00
4)
Ave
rag
e Se
rvic
e In
terr
up
tio
n D
ura
tio
n
Ind
ex (
H)
(Yed
dan
apu
di,
2012
)
Cu
sto
mer
Ave
rag
e In
terr
up
tio
n D
ura
tio
n
Ind
ex—
sust
ain
ed o
uta
ge
met
ric;
mea
sure
s av
erag
e d
ura
tio
n o
f su
stai
ned
ou
tag
e p
er c
ust
om
er (
H)
(Lay
ton
, 20
04;
Eto
an
d
LaC
om
mar
e, 2
008
; Ro
use
an
d K
elly
, 201
1)
Cu
sto
mer
To
tal A
vera
ge
Inte
rru
pti
on
D
ura
tio
n In
dex
(H
) (Y
edd
anap
ud
i, 20
12)
Cu
sto
mer
Ave
rag
e In
terr
up
tio
n F
req
uen
cy
Ind
ex—
mea
sure
s cu
sto
mer
ave
rag
e in
terr
up
tio
n f
req
uen
cy (
H)
(Lay
ton
, 20
04;
R
ou
se a
nd
Kel
ly, 2
011)
Cu
sto
mer
s ex
per
ien
cin
g lo
ng
est
inte
rru
pti
on
du
rati
on
s (C
ELID
-X;
CEL
ID-8
)—su
stai
ned
ou
tag
e m
etri
c;
mea
sure
s th
e p
erce
nta
ge
of
cust
om
ers
exp
erie
nci
ng
ext
end
ed o
uta
ges
last
ing
m
ore
th
an X
ho
urs
(H
) (R
ou
se a
nd
Kel
ly,
2011
)
Cu
sto
mer
s ex
per
ien
cin
g m
ult
iple
in
terr
up
tio
ns
(CEM
I-X
)—su
stai
ned
ou
tag
e m
etri
c; m
easu
res
the
per
cen
tag
e o
f cu
sto
mer
s w
ith
mu
ltip
le o
uta
ges
. Th
is
met
ric
hel
ps
to m
easu
re r
elia
bili
ty a
t a
cust
om
er le
vel a
nd
can
iden
tify
pro
ble
ms
no
t m
ade
app
aren
t b
y sy
stem
wid
e av
erag
es
(H)
(Ro
use
an
d K
elly
, 201
1)
Cu
sto
mer
s ex
per
ien
cin
g m
ult
iple
m
om
enta
ry in
terr
up
tio
ns
(CEM
MI-
X;
CEM
MI-
4)—
mea
sure
s th
e p
erce
nta
ge
of
cust
om
ers
wh
o e
xper
ien
ced
X m
om
enta
ry
inte
rru
pti
on
s (H
) (R
ou
se a
nd
Kel
ly, 2
011)
Cu
sto
mer
s in
terr
up
ted
per
inte
rru
pti
on
in
dex
(H
) (L
ayto
n, 2
00
4)
An
nu
al p
rice
cap
(H
) (B
illin
ton
an
d W
ang
dee
, 20
06)
An
nu
al a
llow
ed r
even
ue
(H)
(Bill
into
n a
nd
Wan
gd
ee, 2
006
)
Co
st o
f in
terr
up
tio
n—
soci
al,
com
mer
cial
, in
du
stri
al, e
tc. (
L)
(Do
uka
s et
al.,
201
1)
Imp
act
fact
or
on
th
e p
op
ula
tio
n—
shar
e o
f th
e p
op
ula
tio
n a
ffec
ted
by
the
po
wer
loss
(M
) (P
olja
nse
k,
Bo
no
, an
d G
uti
erre
z, 2
012)
Lon
g-d
ista
nce
tra
nsm
issi
on
co
sts
(M)
(Do
uka
s et
al.,
201
1)
No
ise
(L)
(Do
uka
s et
al.,
201
1)
Perf
orm
ance
-bas
ed r
egu
lati
on
re
war
d/p
enal
ty s
tru
ctu
re (
L)
(Bill
into
n a
nd
Wan
gd
ee, 2
006
)
Pric
e o
f el
ectr
icit
y (M
) (D
ou
kas
et a
l., 2
011)
Val
ue
of
lost
load
—va
lue
of
un
serv
ed e
ner
gy;
cu
sto
mer
s’
valu
e o
f th
e o
pp
ort
un
ity
cost
of
ou
tag
es o
r b
enefi
ts
forg
on
e th
rou
gh
inte
rru
pti
on
s in
ele
ctri
city
su
pp
ly (
L) (
Will
is
and
Gar
rod
, 199
7; L
uci
a, 2
012)
18 Measuring the Resilience of Energy Distribution Systems
Inp
uts
Cap
acit
ies
Cap
abili
ties
Perf
orm
ance
Ou
tco
mes
Eco
no
my—
ach
ieve
th
e b
est
pro
fits
by
adju
stin
g t
he
po
wer
sys
tem
op
erat
ion
m
od
e to
min
imiz
e lin
e lo
sses
, mak
ing
fu
ll u
se o
f eq
uip
men
t, e
nsu
rin
g t
he
secu
rity
o
f th
e p
ow
er s
yste
m, a
nd
mee
tin
g u
tilit
y u
sers
’ dem
and
(M
) (W
ang
, 201
2)
Fair
nes
s—co
nsi
sts
of
the
fulfi
llmen
t ra
te o
f co
ntr
act
and
sta
nd
ard
dev
iati
on
ind
exes
(L)
(W
ang
, 201
2)
Inte
rru
pte
d e
ner
gy
asse
ssm
ent
rate
(M
) (B
illin
ton
an
d W
ang
dee
, 20
06)
Load
po
int
ind
ices
per
cu
sto
mer
—n
um
ber
o
f o
uta
ges
per
yea
r; d
ura
tio
n o
f o
uta
ges
p
er y
ear;
un
avai
lab
le/a
vaila
ble
ser
vice
(M
) (Y
edd
anap
ud
i, 20
12)
Loss
of
off
site
po
wer
(M
) (I
nte
rnat
ion
al
Ato
mic
En
erg
y A
gen
cy, 2
012)
Min
imu
m le
vel o
f se
rvic
e/ta
rget
s (M
) (R
ou
se a
nd
Kel
ly, 2
011)
Mo
men
tary
ave
rag
e in
terr
up
tio
n
freq
uen
cy in
dex
—m
om
enta
ry o
uta
ge
met
ric;
mea
sure
s fr
equ
ency
of
mo
men
tary
o
uta
ges
. Mo
men
tary
ou
tag
es a
nd
th
e p
ow
er s
urg
es a
sso
ciat
ed w
ith
th
em c
an
dam
age
con
sum
er p
rod
uct
s an
d h
urt
ce
rtai
n b
usi
nes
s se
cto
rs (
M)
(Lay
ton
, 20
04;
R
ou
se a
nd
Kel
ly, 2
011)
Secu
rity
—d
ynam
ic r
esp
on
se o
f th
e sy
stem
to
un
exp
ecte
d in
terr
up
tio
ns;
rel
ates
th
e sy
stem
’s a
bili
ty t
o e
nd
ure
th
em (
H)
(McC
arth
y, O
gd
en, a
nd
Sp
erlin
g, 2
007
)
Tran
smis
sio
n lo
sses
(M
) (D
ou
kas
et a
l.,
2011
)
NO
TE: M
etri
c ap
pea
rs in
bo
ld. M
atu
rity
leve
l ap
pea
rs in
par
enth
eses
: H =
hig
h; M
= m
ediu
m; a
nd
L =
low
. Th
e ci
tati
on
s in
clu
ded
in t
his
tab
le a
re in
stan
ces
wh
ere
the
met
ric
can
be
fou
nd
in t
he
liter
atu
re, b
ut
they
are
no
t n
eces
sari
ly e
xhau
stiv
e.
Tab
le 4
.3—
Co
nti
nu
ed
Existing Metrics for Resilience of Electricity, Refined Oil, and Natural Gas Systems 19
Tab
le 4
.4En
erg
y R
esili
ence
Met
rics
fo
r El
ectr
icit
y Sy
stem
s at
th
e R
egio
n/N
atio
n L
evel
Inp
uts
Cap
acit
ies
Cap
abili
ties
Perf
orm
ance
Ou
tco
mes
Sto
rm r
eser
ve f
un
ds
(L)
(Keo
gh
an
d C
od
y, 2
013)
Co
nce
ntr
atio
n o
f m
arke
t su
pp
liers
(M
) (B
lyth
an
d L
efev
re, 2
00
4)
Her
fin
dah
l-H
ersc
hm
ann
ind
ex—
use
d t
o
mea
sure
mar
ket
con
cen
trat
ion
ris
k; s
qu
are
of
each
par
tici
pan
t’s
mar
ket
shar
e ad
ded
to
get
her
acr
oss
all
par
tici
pan
ts w
ith
th
e la
rges
t sh
ares
(M
) (B
lyth
an
d L
efev
re, 2
00
4;
Rey
mo
nd
, 20
07)
Geo
po
litic
al m
arke
t co
nce
ntr
atio
n r
isk
(M)
(Bly
th a
nd
Lef
evre
, 20
04)
CO
2 em
issi
on
s (M
) (D
ou
kas
et a
l., 2
011)
Der
egu
late
d e
lect
rici
ty m
arke
ts—
allo
cati
on
o
f lo
sses
(L)
(D
ou
kas
et a
l., 2
011)
Pub
lic d
eath
s/in
juri
es (
du
e to
po
wer
in
terr
up
tio
ns)
(M
) (A
ust
ralia
n E
lect
rica
l R
egu
lato
ry A
uth
ori
ties
Co
un
cil,
2005
–20
06;
Ro
use
an
d K
elly
, 201
1)
Pub
lic d
eath
s/in
juri
es (
du
e to
inte
ract
ion
s w
ith
th
e d
istr
ibu
tio
n s
yste
m)
(M)
(Au
stra
lian
El
ectr
ical
Reg
ula
tory
Au
tho
riti
es C
ou
nci
l, 20
05–2
006
; Ro
use
an
d K
elly
, 201
1)
20 Measuring the Resilience of Energy Distribution Systems
Tab
le 4
.5En
erg
y R
esili
ence
Met
rics
fo
r O
il an
d N
atu
ral G
as S
yste
ms
at t
he
Faci
lity/
Syst
em L
evel
Inp
uts
Cap
acit
ies
Cap
abili
ties
Perf
orm
ance
Ou
tco
mes
Hu
bs—
no
des
wit
h t
he
mo
st li
nks
are
th
e m
ost
inte
rco
nn
ecte
d a
nd
ser
ve a
s h
ub
s (H
) (N
adea
u, 2
007
)
Lin
ks—
flo
w b
etw
een
no
des
tak
es
pla
ce o
n li
nks
(ro
ads,
ele
ctri
c p
ow
er
tran
smis
sio
n li
nes
, wat
er m
ain
s,
etc.
) (H
) (N
adea
u, 2
007
; Vu
gri
n a
nd
Tu
rnq
uis
t, 2
012;
Elli
son
, Co
rbet
, an
d
Bro
oks
, 201
3)
No
des
—el
emen
t o
f th
e n
etw
ork
th
at c
an r
ecei
ve g
as f
rom
sto
rag
e fa
cilit
ies,
pip
elin
e in
terc
on
nec
tio
ns,
o
r p
rod
uct
ion
are
as (
H)
(An
der
son
20
01; N
adea
u, 2
007
; Elli
son
, Co
rbet
, an
d B
roo
ks, 2
013)
Prim
ary
ener
gy
sup
ply
—in
clu
des
th
e sy
stem
s an
d p
roce
sses
use
d t
o
sup
ply
a p
rim
ary
ener
gy
reso
urc
e to
its
po
int
of
con
vers
ion
into
th
e fi
nal
en
erg
y p
rod
uct
of
inte
rest
(H
) (M
cCar
thy,
Og
den
, an
d S
per
ling
, 20
07)
Sto
rag
e fa
cilit
ies/
no
des
, in
term
edia
te s
tora
ge
(#)
(H)
(Vu
gri
n
and
Tu
rnq
uis
t, 2
012;
Elli
son
, Co
rbet
, an
d B
roo
ks, 2
013)
Emer
gen
cy p
roce
du
res/
emer
gen
cy s
hu
tdo
wn
sys
tem
(M
) (H
su, S
hu
, an
d T
sao
, 201
0)
Max
imu
m/m
inim
um
flo
w (
H)
(Elli
son
, Co
rbet
, an
d B
roo
ks, 2
013)
Co
st p
er u
nit
of
flo
w (
H)
(Elli
son
, Co
rbet
, an
d B
roo
ks, 2
013)
Effi
cien
cy o
f fl
ow
—o
ne
min
us
the
frac
tio
n
of
gas
bu
rned
as
com
pre
sso
r fu
el (
H)
(Nad
eau
, 20
07; E
lliso
n, C
orb
et, a
nd
Bro
oks
, 20
13)
Res
po
nse
to
eq
uip
men
t o
uta
ges
—d
egre
e to
wh
ich
th
e sy
stem
is a
ble
to
co
nti
nu
e to
re
liab
ly o
per
ate
in t
he
even
t o
f eq
uip
men
t d
ow
nti
me
(L)
(McC
arth
y, O
gd
en, a
nd
Sp
erlin
g, 2
007
)
NO
TE: M
etri
c ap
pea
rs in
bo
ld. M
atu
rity
leve
l ap
pea
rs in
par
enth
eses
: H =
hig
h; M
= m
ediu
m; a
nd
L =
low
. Th
e ci
tati
on
s in
clu
ded
in t
his
tab
le a
re in
stan
ces
wh
ere
the
met
ric
can
be
fou
nd
in t
he
liter
atu
re, b
ut
they
are
no
t n
eces
sari
ly e
xhau
stiv
e.
Existing Metrics for Resilience of Electricity, Refined Oil, and Natural Gas Systems 21
Tab
le 4
.6En
erg
y R
esili
ence
Met
rics
fo
r O
il an
d N
atu
ral G
as S
yste
ms
at t
he
Syst
em/R
egio
n L
evel
Inp
uts
Cap
acit
ies
Cap
abili
ties
Perf
orm
ance
Ou
tco
mes
Fun
ctio
nal
zo
nes
—p
rim
ary
ener
gy
sup
ply
, en
erg
y p
roce
ssin
g, a
nd
co
nve
rsio
n a
nd
tra
nsp
ort
(M
) (M
cCar
thy,
Og
den
, an
d
Sper
ling
, 20
07)
Ad
apti
ve c
apac
ity—
deg
ree
to
wh
ich
th
e sy
stem
is c
apab
le o
f se
lf-
org
aniz
atio
n f
or
reco
very
of
syst
em
per
form
ance
leve
ls (
L) (
Vu
gri
n,
War
ren
, an
d E
hle
n, 2
011)
Cap
acit
y—ab
ility
of
the
syst
em
to p
rovi
de
suffi
cien
t th
rou
gh
pu
t to
su
pp
ly fi
nal
dem
and
(M
) (M
cCar
thy,
Og
den
, an
d S
per
ling
, 20
07)
Info
rmat
ion
sec
uri
ty—
the
deg
ree
to w
hic
h in
form
atio
n a
sset
s in
th
e sy
stem
are
sec
ure
ag
ain
st
thre
ats
(L)
(McC
arth
y, O
gd
en, a
nd
Sp
erlin
g, 2
007
)
Inte
rdep
end
enci
es—
the
deg
ree
to w
hic
h t
he
syst
em r
elie
s o
n
oth
er in
fras
tru
ctu
re f
or
its
relia
ble
o
per
atio
n a
nd
is v
uln
erab
le t
o
that
infr
astr
uct
ure
’s d
isru
pti
on
(L)
(M
cCar
thy,
Og
den
, an
d S
per
ling
, 20
07)
Phys
ical
sec
uri
ty—
the
deg
ree
to
wh
ich
ph
ysic
al a
sset
s in
th
e sy
stem
ar
e se
curi
ty a
gai
nst
th
reat
s (L
) (M
cCar
thy,
Og
den
, an
d S
per
ling
, 20
07)
Ab
sorp
tive
cap
acit
y—d
egre
e to
wh
ich
a
syst
em c
an a
uto
mat
ical
ly a
bso
rb t
he
imp
acts
o
f a
syst
em’s
per
turb
atio
ns
and
min
imiz
e co
nse
qu
ence
s w
ith
litt
le e
ffo
rt (
L) (
Vu
gri
n,
War
ren
, an
d E
hle
n, 2
011)
Co
nn
ecti
vity
loss
—th
e av
erag
e re
du
ctio
n in
th
e ab
ility
of
sin
ks t
o r
ecei
ve fl
ow
fro
m s
ou
rces
(M
) (P
olja
nse
k, B
on
o, a
nd
Gu
tier
rez,
201
2)
Ener
gy
pro
cess
ing
an
d c
on
vers
ion
—re
late
s to
pro
du
ctio
n o
f th
e fi
nal
en
erg
y p
rod
uct
(H
) (M
cCar
thy,
Og
den
, an
d S
per
ling
, 20
07)
Flex
ibili
ty—
the
deg
ree
to w
hic
h t
he
syst
em
can
ad
apt
to c
han
gin
g c
on
dit
ion
s (L
) (M
cCar
thy,
Og
den
, an
d S
per
ling
, 20
07)
His
tory
—th
e d
egre
e to
wh
ich
th
e sy
stem
h
as b
een
pro
ne
to d
isru
pti
on
in t
he
pas
t (M
) (M
cCar
thy,
Og
den
, an
d S
per
ling
, 20
07)
Inte
rmit
ten
cy—
the
deg
ree
to w
hic
h t
he
syst
em la
cks
con
stan
t le
vels
of
pro
du
ctiv
ity
(M)
(McC
arth
y, O
gd
en, a
nd
Sp
erlin
g, 2
007
)
Net
wo
rk r
esili
ency
—m
easu
red
by
its
abili
ty t
o
keep
su
pp
lyin
g a
nd
dis
trib
uti
ng
nat
ura
l gas
in
spit
e o
f d
amag
e to
pip
elin
es, l
iqu
efied
nat
ura
l g
as im
po
rt t
erm
inal
s, s
tora
ge,
an
d o
ther
gas
so
urc
es (
M)
(Nad
eau
, 20
07)
Res
po
nse
to
dem
and
flu
ctu
atio
ns—
the
exte
nt
to w
hic
h t
he
syst
em is
ab
le t
o a
dap
t to
ch
ang
es in
th
e q
uan
tity
of
ener
gy
dem
and
ed
or
loca
tio
n o
f d
eman
d (
L) (
McC
arth
y, O
gd
en,
and
Sp
erlin
g, 2
007
)
Syst
emic
imp
act—
imp
act
that
a d
isru
pti
on
h
as o
n s
yste
m p
rod
uct
ivit
y; m
easu
red
by
eval
uat
ing
th
e d
iffe
ren
ce b
etw
een
a t
arg
etin
g
syst
em p
erfo
rman
ce le
vel a
nd
th
e ac
tual
sy
stem
per
form
ance
(L)
(V
ug
rin
, War
ren
, an
d
Ehle
n, 2
011;
Vu
gri
n a
nd
Tu
rnq
uis
t, 2
012)
Dem
and
sat
isfi
ed (%
) (H
) (N
adea
u, 2
007
)
Imp
acts
on
inte
rdep
end
ent
syst
ems—
the
deg
ree
to w
hic
h
a d
isru
pti
on
in t
he
syst
em
mig
ht
feas
ibly
cau
se d
amag
e to
inte
rdep
end
ent
syst
ems
(L)
(McC
arth
y, O
gd
en, a
nd
Sp
erlin
g, 2
007
)
Op
tim
al r
esili
ence
co
sts—
resi
lien
ce c
ost
s fo
r a
syst
em
wh
en t
he
op
tim
al r
eco
very
st
rate
gy—
min
imiz
ing
th
e co
mb
ined
sys
tem
imp
act
and
to
tal r
eco
very
eff
ort
co
sts—
is
emp
loye
d (
L) (
Vu
gri
n, W
arre
n,
and
Eh
len
, 201
1)
Rec
ove
ry-d
epen
den
t re
silie
nce
co
sts—
resi
lien
ce
cost
s o
f a
syst
em u
nd
er a
p
arti
cula
r re
cove
ry s
trat
egy
(L)
(Vu
gri
n, W
arre
n, a
nd
Eh
len
, 20
11)
NO
TE: M
etri
c ap
pea
rs in
bo
ld. M
atu
rity
leve
l ap
pea
rs in
par
enth
eses
: H =
hig
h; M
= m
ediu
m; a
nd
L =
low
. Th
e ci
tati
on
s in
clu
ded
in t
his
tab
le a
re in
stan
ces
wh
ere
the
met
ric
can
be
fou
nd
in t
he
liter
atu
re, b
ut
they
are
no
t n
eces
sari
ly e
xhau
stiv
e.
22 Measuring the Resilience of Energy Distribution Systems
Tab
le 4
.7En
erg
y R
esili
ence
Met
rics
fo
r O
il an
d N
atu
ral G
as S
yste
ms
at t
he
Reg
ion
/Nat
ion
Lev
el
Inp
uts
Cap
acit
ies
Cap
abili
ties
Perf
orm
ance
Ou
tco
mes
Div
ersi
ty o
f im
po
rt f
uel
s (H
) (G
nan
sou
no
u, 2
009
)
Nat
ura
l gas
str
ateg
ic
rese
rve
(M)
(Elli
son
, Kel
ic,
and
Co
rbet
, 20
06)
Her
fin
dah
l-H
ersc
hm
ann
in
dex
—u
sed
to
mea
sure
mar
ket
con
cen
trat
ion
ris
k; s
qu
are
of
each
par
tici
pan
t’s
mar
ket
shar
e ad
ded
to
get
her
acr
oss
all
par
tici
pan
ts w
ith
th
e la
rges
t sh
ares
(M
) (B
lyth
an
d L
efev
re,
200
4; R
eym
on
d, 2
007
)
Imp
ort
leve
ls—
the
deg
ree
to
wh
ich
pri
mar
y en
erg
y su
pp
ly
relie
s o
n r
eso
urc
es o
rig
inat
ing
o
uts
ide
of
the
cou
ntr
y (H
) (M
cCar
thy,
Og
den
, an
d S
per
ling
, 20
07)
Imp
ort
co
nce
ntr
atio
n—
the
deg
ree
to w
hic
h im
po
rts
are
con
cen
trat
ed a
mo
ng
a s
mal
l g
rou
p o
f su
pp
lyin
g c
ou
ntr
ies
(H)
(McC
arth
y, O
gd
en, a
nd
Sp
erlin
g,
2007
)
Imp
ort
dep
end
ency
—d
ivid
ed
into
so
urc
e d
epen
den
ce, t
ran
sit
dep
end
ence
, an
d f
acili
ty
dep
end
ence
(M
) (R
eym
on
d,
2007
)
Ind
ust
rial
asp
ects
—vu
lner
abili
ty
ind
icat
or
(M)
(Rey
mo
nd
, 20
07)
Rat
e o
f d
epen
den
cy—
mea
sure
d
by
the
net
en
erg
y im
po
rts/
tota
l p
rim
ary
ener
gy
con
sum
pti
on
ra
tio
(M
) (R
eym
on
d, 2
007
)
Vu
lner
abili
ty—
pro
po
rtio
nal
to
th
e re
lian
ce o
n im
po
rted
gas
fr
om
co
un
trie
s in
geo
po
litic
al
con
flic
t (M
) (R
eym
on
d, 2
007
)
Ab
ility
to
exp
and
fac
iliti
es—
the
deg
ree
to w
hic
h t
he
syst
em c
an
be
easi
ly a
nd
co
st-e
ffec
tive
ly
exp
and
ed (
L) (
McC
arth
y, O
gd
en,
and
Sp
erlin
g, 2
007
)
Imp
ort
cap
acit
y (M
) (E
lliso
n,
Co
rbet
, an
d B
roo
ks, 2
013)
Pip
elin
e ca
pac
ity
use
d (%
) (H
) (N
adea
u, 2
007
)
Res
ilien
cy—
abili
ty t
o s
up
ply
gas
to
cu
sto
mer
s w
illin
g t
o p
ay t
he
clea
rin
g p
rice
, eve
n in
th
e fa
ce
of
sup
ply
co
nst
rain
ts (
L) (
Ellis
on
, K
elic
, an
d C
orb
et,2
006
)
Res
tora
tive
cap
acit
y—ab
ility
of
a sy
stem
to
be
rep
aire
d e
asily
; th
ese
rep
airs
are
co
nsi
der
ed t
o b
e d
ynam
ic (
L) (
Vu
gri
n, W
arre
n, a
nd
Eh
len
, 201
1)
Tota
l rec
ove
ry e
ffo
rt—
effi
cien
cy
wit
h w
hic
h t
he
syst
em r
eco
vers
fr
om
a d
isru
pti
on
, mea
sure
d b
y an
alyz
ing
th
e am
ou
nt
of
reso
urc
es
exp
end
ed d
uri
ng
th
e re
cove
ry
pro
cess
(L)
(V
ug
rin
, War
ren
, an
d
Ehle
n, 2
011)
Sect
or
coo
rdin
atio
n—
the
deg
ree
to w
hic
h c
oo
rdin
atio
n
bet
wee
n s
take
ho
lder
s w
ith
in
the
sect
or
resu
lts
in a
n e
ffec
tive
ex
chan
ge
of
info
rmat
ion
ale
rtin
g
stak
eho
lder
s o
f em
erg
ing
th
reat
s an
d m
itig
atio
n s
trat
egie
s (L
) (M
cCar
thy,
Og
den
, an
d S
per
ling
, 20
07)
Tran
spo
rtat
ion
—en
com
pas
ses
the
tran
smis
sio
n a
nd
dis
trib
uti
on
of
the
fin
al e
ner
gy
pro
du
ct t
o it
s p
oin
t o
f en
d u
se (
H)
(McC
arth
y, O
gd
en, a
nd
Sp
erlin
g, 2
007
)
Eco
no
mic
imp
act—
the
deg
ree
to w
hic
h a
dis
rup
tio
n in
th
e sy
stem
mig
ht
feas
ibly
cau
se
eco
no
mic
dam
age
to in
du
stry
st
akeh
old
ers,
th
e g
ove
rnm
ent,
o
r th
e p
ub
lic (
L) (
McC
arth
y,
Og
den
, an
d S
per
ling
, 20
07)
Envi
ron
men
tal i
mp
act—
the
deg
ree
to w
hic
h a
dis
rup
tio
n
in t
he
syst
em m
igh
t fe
asib
ly
cau
se e
nvi
ron
men
tal d
amag
e (M
) (M
cCar
thy,
Og
den
, an
d
Sper
ling
, 20
07)
Hu
man
hea
lth
imp
act—
the
deg
ree
to w
hic
h a
dis
rup
tio
n in
th
e sy
stem
mig
ht
feas
ibly
har
m
the
hea
lth
of
emp
loye
es o
r th
e p
ub
lic (
M)
(McC
arth
y, O
gd
en,
and
Sp
erlin
g, 2
007
)
Phys
ical
sh
ort
age
(M)
(Elli
son
, K
elic
, an
d C
orb
et, 2
006
)
Pric
e/p
rice
vo
lati
lity
(H)
(Elli
son
, Kel
ic, a
nd
Co
rbet
, 20
06; M
cCar
thy,
Og
den
, an
d
Sper
ling
, 20
07)
NO
TE: M
etri
c ap
pea
rs in
bo
ld. M
atu
rity
leve
l ap
pea
rs in
par
enth
eses
: H =
hig
h; M
= m
ediu
m; a
nd
L =
low
. Th
e ci
tati
on
s in
clu
ded
in t
his
tab
le a
re in
stan
ces
wh
ere
the
met
ric
can
be
fou
nd
in t
he
liter
atu
re, b
ut
they
are
no
t n
eces
sari
ly e
xhau
stiv
e.
23
CHAPTER FIVE
Developing Metrics for Energy Resilience
Resilience is a topic of interest for policymakers as they consider the complex risks from natu-ral disasters, terrorism, aging infrastructure, and climate change faced by the transmission, storage, and distribution systems for U.S. energy. If energy infrastructure is to become more resilient, better use of metrics will be crucial to guiding planning and evaluating progress. The literature review presented in this report suggests three recommendations that could improve the metrics available to support energy policy.
Improve Collection and Management of Data on Inputs and Capacities at the Facility and System Levels
The literature on energy resilience includes many metrics that describe the state of inputs and capacities for energy facilities or localized energy systems. Because these metrics are col-lected by different organizations and entities for specific purposes, they are frequently not standardized and are rarely collected and managed in a manner that facilitates analysis to support policy. Doing so could provide an evidence base upon which cost-effective strate-gies to improve energy resilience could be developed. Examples of alternative standardization approaches vary, from mandatory regulatory reporting requirements to voluntary adoption of consensus-based management best practices. However, these types of knowledge management alternatives could also be costly. Thus, it is prudent to consider alternative approaches to imple-menting data collection and management, how much they might cost, and how they might serve the interests of different stakeholder groups.
Develop Better Measures of Capabilities at the System and Regional Levels
Improvements in capability are the principal levers through which energy system owners and operators can improve performance to achieve desired societal outcomes. However, this litera-ture review suggests that at the system and regional levels, metrics have not been well defined and performance data on capabilities are not regularly collected.
Measuring capabilities to respond to and recover from extreme events is difficult. For complex energy systems, there is not yet a consensus about what the core required capabili-ties for a system or region should be. Without opportunities to observe performance of capa-bilities regularly, because extreme events are rare, it is difficult to demonstrate proficiency in capabilities. Approaches used to measure and improve quality of services in other contexts—
24 Measuring the Resilience of Energy Distribution Systems
such as health care quality, community resilience, and public health preparedness—illustrate approaches that may be useful. Examples from these fields include extracting insights from exercises and after-action reviews, developing drills that test components of a system, and developing community recommendations through consensus processes that collect experience across communities or sectors.
Defining and measuring capabilities are useful steps in developing a framework for improving the resilience of energy systems. Developing a stronger understanding of what are key capabilities and how to measure a system or region’s proficiency requires public- and private-sector cooperation to identify which capabilities to measure, practical and valid exer-cises or tests of proficiency in those capabilities, and efficient means of collecting and manag-ing data on capability metrics.
Improve Understanding of How Capabilities and Performance Translate to Outcomes at the Regional and National Levels
The goal of improving energy system resilience is to make communities safer and more pro-ductive. The literature on outcomes of energy system resilience reflects these goals and includes many potential outcome metrics. The literature does not, however, provide clarity about how to adjust capabilities and system performance to most effectively achieve desired outcomes. Building this understanding requires a coordinated effort to establish an evidence base in terms of metrics for inputs, capacities, capabilities, and performance described earlier in this chapter. This empirical foundation can then serve as a basis for modeling and understanding the complex technical and social interactions through which energy systems support societal goals for safety and prosperity.
25
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