Electric Grid Vulnerabilities to Rising Air Temperatures in Arizona

Abstract

Ambient air temperatures are expected to increase in the US desert southwest by 1-5 °C mid-century which will strain the electric power grid through increased loads, reduced power capacities, efficiencies, and material lifespans. To better understand and quantify this risk, a power infrastructure failure model is created to estimate changes in outage rates of components for increases in air temperatures in Arizona. Components analyzed include generation, transmission lines, and substations, because their outages can lead to cascading failures and interruptions of other critical infrastructure systems such as water, transportation, and information/communication technology. Preliminary results indicate that components could require maintenance or replacement up to 3 times more often due to mechanical failures, outages could occur up to 30 times more often due to overcurrent tripping, and the probability of cascading failures could increase 30 times as well for a 1 °C increase in ambient air temperature. Preventative measures can include infrastructure upgrades to more thermal resistant parts, installation of cooling systems, smart grid power flow controls, and expanding programs for demand side management and customer energy efficiency.

Full text

Procedia Engineering 145 ( 2016 ) 1346 – 1353
1877-7058
© 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of the organizing committee of ICSDEC 2016
doi: 10.1016/j.proeng.2016.04.173
ScienceDirect
Available online at www.sciencedirect.com
International Conference on Sustainable Design, Engineering and Construction
Electric grid vulnerabilities to rising air temperatures in Arizona
Daniel Burillo
a
*
, Mikhail Chester
a
, Benjamin Ruddell
b
a
Department of Civil Environmental and Sustainable Engineering, Arizona State Univesrsity
660 S College Ave, Tempe 85281, USA
b
Department of Engineering and Computing Systems, Arizona State University
Abstract
Ambient air temperatures are expected to increase in the US desert southwest by 1-5°C mid-century which will strain the electric
power grid through increased loads, reduced power capacities, eff
iciencies, and material lifespans. To better understand and
quantify this risk, a power infrastructure failure model is created to estimate changes in outag
e rates of components for increases
in air temperatures in A
rizona. Components analyzed include generation, transmission lines, and substations, because their
outages can lead to cascading failures and interruptions of other critical in
frastructure systems such as water, transportation, and
information/communication technology. Preliminary results indicate that components could require maintenance or replacement
u
p to 3 times more often due to mechanical failures, outages could occur up to 30 times more often due to overcurrent tripping,
and the probability of cascading failures could increase 30 times as well for a 1°C increase in ambient air temperature.
P
reventative measures can include infrastructure upgrades to more thermal resistant parts, installation of cooling systems, smart
grid power flow controls, and expanding programs for demand side management and customer energy efficiency.
© 2016 The Authors. Published by Elsevier Ltd.
Peer-review under responsibility of organizing committee of the
International Conference on Sustainable Design, Engineering
and Construction 2016.
Keywords: electric power; energy; infrastructure; reliability; resiliency; failure analysis; climate change; extreme heat
*
Corresponding author. Tel.: +1-623-229-3166.
E-mail address: daniel.burillo@asu.edu
© 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of the organizing committee of ICSDEC 2016

1347
Daniel Burillo et al. / Procedia Engineering 145 ( 2016 ) 1346 – 1353
1. Introduction
The electric power grid in the USA, and desert southwest
specifically, is of the most reliable in the world [1-2],
but like all electrical power systems it is sensitive to heat in terms of its power capacity and component materials’
lif
e-span [3]. Arizona’s power authorities typically plan 10-15 years in advance to manage risk considering increased
s
ystem burdens due to social, economic, and technological, environmental, and policy factors [4-5]. These plans do
n
ot explicitly consider potential effects of rising ambient air temperatures. Significant increases in ambient air
te
mperatures (1-5°C) are predicted by mid-century [4-5], and grid construction projects require as much as 10 years
and m
any millions of dollars each to complete. Therefore, developing a better un
derstanding of the risks of rising air
temperatures to the power grid is both timely and necessary to maintain reliable critical infrastructure systems.
Predicting the change in probability of electric power failing is obtained using fault-tree logic in this study [8]. A
failure analysis framework is develo
ped inclusive of generation, transmission, and substation component
performance using thermophysical equations for power flow and material degradation rate with stochastic inputs for
air temperature. The model estimates the probability of failure when supply is insufficient or component outages
occu
r. The effects of increases in air temperature are q
uantified as changes in power flow capacity (MW) and
efficiency (% MWh), as well as the mechanical mean time to failure (MTTF) of component parts. The potential
chan
ge in multiple simultaneous outages occurring and triggering cascading failures is also quantified. This research
estimates the magnitude of the risk of rising air temperatures to critical civ
il infrastructure systems, and identifies
corresponding vulnerabilities within the power grid.
Nomenclature
θ
µ
°C mean of the maximum ambient air temperature during June, July, and August
θ
σ
°C standard deviation of θ
µ
θ
+
°C increase in θ
µ
, input control variable
θ
PRM
°C average temperature at which the PRM is engaged on a day
θ
PRMcrit
°C average temperature at which the PRM reaches its critical value on a day
β
GC
% loss of generation capacity per θ
+
β
TDE
% loss of T&D network efficiency per θ
+
β
PKload
% increase in peak load per θ
+
β
TC
% loss of transmission line current capacity per θ
+
β
SC
% loss of substation transformer current capacity per θ
+
β
PK
% net peak load adjustment factor per θ
+
α % probability that two simultaneous component outages lead to a cascading failure in the system
λ #/day failure rate
a
b
Pf'
% change in probability of failure, or λ, of a system component, where a = P or M, b = G or T or S
a
bk
Pf
% probability of failure, or λ, of a system component, where a = P or M, b = G or T or S, k = i or f
A
b
years
age of component, where b = G or T or S
IP
%
current in a system component as a percentage of the component’s rated ampacity
MTTF years mean time to failure
PRM % planning reserve margin
PRM
crit
%
PRM critical value for potential service interruption and the possibility of cascading failures
S % strength loss per year
S
Teol
%
strength loss for a transmission line to reach expected lifespan
Commonly used subscripts and superscripts
P, M power- or mechanical-based component failure
G, T, S generation, transmission, substation
i, f initial (current air temperature scenario with θ
µ
and θ
σ
), final (higher ambient air temperature scenario θ
+
)
μ, σ mean, standard deviation

1348 Daniel Burillo et al. / Procedia Engineering 145 ( 2016 ) 1346 – 1353
2. Methods
This analysis focuses on the thermal performance of the three major current carrying components in the electric
po
wer grid: generation, transmission, and substation transformers. This approach is consistent with other recent
studies of the impact of rising air temperatures on power infrastructure such as [9]. To estimate how much
in
creasing ambient air temperatures can increase component outages, cascading failures, and ultimately service
in
terruptions, it is necessary to first understand the flow of electric power in the system, as well as the sequence of
event
s that can lead to interruptions and potentially cascading outages. See Fig. 1. System operators maintain an n-1
red
undancy standard in design at the high-voltage transmission level meaning that the single largest generator,
trans
mission line branch, or substation (of which there are at least hundreds in every region) can fail at any time
without any interruption to service [10]. These n-1 redundancies are represented in Fig. 1b using octagon boxes and
log
ical AND gates. Service interruptions due to major component failures only occur when more than one individual
component fails at the same time. Such events can lead to cascading failures including blackouts as in [11].
Service interruption occurs when power does not reach the load, such as a building or street light, and this
anal
ysis estimates specifically how much the frequency of service interruptions can increase. Fig. 1b shows the two
w
ays that a service interruption can occur that are analyzed in this paper: either there is not enough total generation
to
meet total demand, or particular power pathways (transmission lines and substations) do not have sufficient
capacity to deliver power to the load
. The following list explains how increases in ambient air temperatures can
trigger failures leading to service interruptions consistent with the lettering in Fig. 1b.
A. High air temperatures can result in reduced peak energy g
eneration capacity and or efficiency losses in the
transmission and distribution (T&D) network [8, 11]. If the system is also in high demand, (B), then load can
exceed
generation and put the system in a state of over demand. If there are insufficient generation reserves, then
th
ere will be a service interruption.
B. High air temperatures can result in higher demand, especially during the already hot summer months due to
in
creased burden on building air conditioning systems [12].
C. High air temperatures result in less T&D power flow capacity in
lines and transformers [8, 11]. If a circuit is in
high demand, then power flow can exceed safe operating capacit
y and lines and transformers can exceed their
rated ampacities and become in a state of overcurrent [11].
i. If protection devices function correctly, then overcurrent will cause tripping
of the line or transformer
within the T&D network [11]. If there is insufficient capacity in parallel branches to provide power to the
load, then there will be a service interruption [11].
ii. If a protection device fails to trip and a circuit is ov
ercurrent, then a component can exceed its thermal
rating. Excess heat accelerates the chemical degradation rate of sensitive materials and can result in
mechanical failure (E) [12-13]. Protection devices can fail because they are not accurately designed or
calibrated
for local climate conditions or other reasons [1]. Depending on the type and location of
overcurrent failure, a generator, transmission line, substation, qu
ality device, or other protection device can
fail. If a generator fails, then the system state goes to (A) as the system now has less generation. If a
trans
former fails, then it goes to (A) and or (C) as the T&D network operates at lower efficiency and or has
less power flow capacity. If a power quality device fails, then it goes to (C) again or directly to overcurrent
dep
ending on the circumstances. If another redundant protection device fails, then the cycle of potential
failures repeats for additional components on connected circuits.
D. High air temperatures can result in a protectio
n device failing to trip [1]. The device could be calibrated to a
certain power rating that should be lower for the actual air temperature. If that occurs during high loading, then a
component can go overcurrent and fail as in (ii).
E. High air temperatures can result in an accelerated
physical material degradation rate, which can result in
accelerated failures for any electrical devices [3]. The same failure scenarios can
occur as described above, with
the addition of an undesired trip of a protection device. If a protection device fails with an undesired trip, and
there is no redundant power flow, then a service interruption occurs.

1349
Daniel Burillo et al. / Procedia Engineering 145 ( 2016 ) 1346 – 1353
System Boundary
Power Failure
Mechanical Failure
Overcurrent
Over demand
Energy /
Efficiency Loss
(Gen, T&D)
High Demand
T&D Capacity
Reduced /
High Loading
Higher Material
Degradation
Rate
Transmission
Line
Protection
Device
Generator
Protection
Device Failure
(Heat: Calibr)
Undesired Trip
Fail to Trip
Insufficient capacity
or pow er flow in
parallel components
Insufficient
generation reserves
No redundant
prot ection device
Quality
Device
Event trigger
(potentially
due to heat)
Logical
AND
Component
State or
System State
Insufficient
Redundancies
(N-1 condition fail)
2
1
Service
Interrupt
Tripping
1
3
2
3
Logical OR is implicit a s
multiple input arrows
or multiple output arrows
Substation
Transformer
(b)
A
B
C
D
E
i
ii
Generation
High-Voltage
Transformer
High-Voltage
Power Line
(69-500 kV)
High-Voltage
Transformer
Low-Voltage
Power Line
(8-69KV)
Low-Voltage
Transformer
Residential &
Commercial
Load
Industrial &
Large
Commercial
Load
High-Voltage
Substation
High-Voltage
Substation
PROTECTION
& QUALTIY
Devices
PROTECTION
Relays
Switches
Fuses
Circuit Breakers
Reclosers
QUALITY
Capacitors
Conditioners
Regulators
Surge arrestors
Main
Power Flow
Components
Legend
Protection and
Quality Devices
Power Flow
Electric power grid infrastructure
(a)
Legend
Fig. 1. (a) Power grid infrastructure analysis system boundary; (b) Fault tree to service interruption. (a) Shows the flow of power from
generation to load through system components and identifies the analysis system boundary inclusive of major power-flow components including:
generation, transmission, substation transformers, and load. Changes in performance of protection and power quality devices are not analysed.
(b) Shows the terminal event of a service interruption on the right, and the power- and mechanical-failures that can lead to a service interruption
logically preceding from the left. On the far left are the events that can be caused by higher ambient air temperatures and ultimately lead to
service interruption in conjunction with other failures as indicated. Mechanical failures feedback into the event triggers as their loss of
functionality results in a loss of power-flow that could cause an interruption.
A model is developed to estimate the change in probabilities of component failures (or failure rates) and service
interruptions due to increases in ambient air temperatures, shown in equation (1). This is done by quantifying the
fault processes in Fig. 1 for the primary current-carrying components. The structure of this model is shown in Fig. 2
where climate and infrastructure inputs are used to estimate changes in power-based and mechanical-based failures.
These values are used to estimate the change in probability of a cascading event that can be triggered by two or
more component failures occurring at the same time.

1350 Daniel Burillo et al. / Procedia Engineering 145 ( 2016 ) 1346 – 1353
Fig. 2. Failure analysis model. The model is structured in five parts: (i) ambient air temperature, the increase of which is the primary control
variable, θ
+
; (ii) power capacity and energy efficiency factors, β’s, which are proportional to ambient air temperature; (iii) probability of power-
based failures for each component type,
P
b
Pf
, for which there could be insufficient capacity to support power demand; (iv) probability of
mechanical-based failures for each component type,
M
G
Pf
,wherein the wear of thermally sensitive parts over time results in a higher failure rate
or probability of failure on a given day; (v) cascading failures, that can occur if two or more component failures occur at the same time.
,,
aa
bf bi
a
b
a
bi
G generation
Pf Pf
M mechanical based failure
Pf a b T transmission
P power based failure
Pf
S substation





°
'    
®®

 
¯
°

¯
% per day
(1)
2.1. Ambient air temperature
Ambient air temperature is the primary control variable in the model, and is defined as a normal distribution
curv
e with base case mean maximum temperature θ
µ
= 42.22°C and standard deviation θ
σ
= 3.04°C from the average
maximum temperature at the Phoenix airport for the months of June, July, and August 2009 to 2014 [15].
Summertime increases in air temperature, θ
+
, are modeled as increases in the mean of the maximum temperature θ
µ
with no change in standard deviation θ
σ
.
2.2. Electric power capacity and energy efficiency factors
Electronic components are generally subject to at
least two stresses: electrical and thermal [3]. Electrical
resistance increases as conductor temperature increases, which further increases operating temperature and
decreas
es efficiency [16]. The model inputs for capacity and efficiency losses are β
GC
= 0.7%, β
TDE
= 0.5%, β
PKload
=
7.5%, β
TC
= 1.5%, and β
SC
= 0.7% per 1°C increase in ambient air temperature as are the marginal unit linearization
of the results in [5, 11]. The generation factor only considers natural g
as plants. These values are for high operating
temperatures, which are within the range of this analysis, and are combined into the net adjustment factors β
PK =
β
PKload
+ β
TDE
+ β
GC
= 8.7%, β
T =
β
PKload
+ β
TC
= 9%, and β
S =
β
PKload
+ β
SC
= 8.2% per °C.
2.3. Power-based failures
Power-based failures are failures where there is
insufficient capacity in a circuit to meet demand. These can occur
due to insufficient generation, when a transmission line is overcurrent, or a substation is overcurrent.
2.3.1. Gen
eration – PRM deficiency
PRM is the amount of generation capacity available to m
eet expected demand, and is calculated as the difference
in prospective resources and net internal demand, divided by net internal demand [17]. PRM is institutionally
ma
naged to maintain reliable grid operations in the event of unexpected increases in demand and or outages of
exist
ing capacity [17]. System operators historically issue alerts w
hen PRM falls below 5% and ask customers to
curtail their electricity usage [18]. Therefore 5% is used as the critical PRM value, PRM
crit
, where other
simultaneous component failures can cause a service interruption and
trigger cascading failures.
P
G
Pf'
is estimated in equation (1) assuming PRM is marginally engaged for the top 5% of air temperature values
for θ
µ
and θ
σ
, which is ≥ 47.22°C and represents the expected 4.6 hottest days per year from 2009 to 2014 [15]. The
temperature that PRM
crit
occurs at is estimated in equation (2), where PRM
i
= 17% as is WECC’s 2024 projected
summer PRM [19].
P
Gi
Pf
= 1.8% per day is the area under a normal curve of θ
µ
and θ
σ
above θ
PRMcrit
.
P
Gf
Pf
is
estimated by shifting θ
µ
by θ
+
.

icrit
PRM
PK
PRMcrit
PRM PRM
TT
E


°C
(2)
2.3.2. Transmission – Line Overcurrent
P
T
Pf'
is estimated in equation (1) assuming that if a line exceeds its rated amperage it will trip.
P
Ti
Pf
= 0.0032%
per day is the area under a normal distribution for the line load as a percentage of the current carrying capacity
w
here IP
Tµ
= 60%, IP
Tσ
= 10%, and rated amperage is equal to 1.
P
Tf
Pf
is estimated by shifting IP
Tµ
by θ
+
and β
T
.

1351
Daniel Burillo et al. / Procedia Engineering 145 ( 2016 ) 1346 – 1353
2.3.3. Substation – Transformer Overcurrent
P
S
Pf'
is estimated using the same method as 2.3.2 by using equation (1), and assuming that if a transformer
exceeds its rated amperage it will trip.
P
Si
Pf
=0.0032% per day is the area under a normal distribution for the
transformer load as a percentage of the current carrying capacity where IP
Sµ
= 60%, IP
Sσ
= 10%, and rated amperage
is equal to 1.
P
Sf
Pf
is estimated by shifting IP
Sµ
by θ
+
and β
S
.
2.4. Mechanical-based Failures
Mechanical failures occur due to physical degradation of thermally-sensitive parts within components such as a
co
nductor, insulator, or contact. A failure rate, λ, is defined as the inverse of the MTTF with units of failures per
day. Change in failure rates are estimated as the percent change in th
e initial and expected λ for increased air
temperature conditions as in equation (1).
2.4.1. Gen
eration – Part Wear
A value of 0.001% is assumed for
P
Gi
Pf
, and
P
Gf
Pf
is set to that multiplied by (1+θ
+
/100).
2.4.2. Transmission – Conductor Loss of Strength
There are three primary factors considered in defining the ther
mal limit of a power line: sag, loss of strength, and
the fittings of the conductor [20]. Sag is measured as the vertical distance that the line moves closer towards the
ground due to thermal expansion, and increases the chance of flashover resulting in a ground fault and outage of the
circuit. Such an event typically occurs
when a line comes too close to trees, which may occur because trees have not
been trimmed, or the line sags beyond the safety margin [13]. While sag is a mechanical process, it is not associated
with conductor damage or loss of life [13]. Therefore analyzing the physical conductor sag constraints would be
redundant with the previous power-based failure analysis for transmission line overcurrent. Loss of conductor
strength occurs due to annealing, a gradual process whereby a metal recrystallizes over time, and ACSR conductors
ann
eal at operating temperatures above 100°C [21]. Significant loss of strength may result in breakages during high
m
echanical stress events such as gusts of wind [21]. Properly designed and selected fittings are not a thermal
limiting factor for the conductor [13].
M
T
Pf'
is estimated by equation (1) assuming a MTTF
Ti
= 70 years for ACSR lines based on [22] and that it is
causally proportional to loss of conductor strength due to annealing.
M
Ti
Pf
= λ
Ti
= 0.0039% per day is the inverse of
the MTTF
Ti
.
M
Tf
Pf
is estimated by adjusting MTTF as in equation (3). The strength loss associated with conductor
end of life, S
Teol
, is estimated as the weighted sum of the hours per day over MTTF
Ti
that a transmission line is
expected to exceed nominal current by 10%, 20%, and 30%, and log-linear strength loss factors of 3%, 5%, and
7.5% respectiv
ely that are the approximate results of [23]. This assumes that percentage loss of tensile strength
relates 1:1 to reduced lifespan. The initial strength reduction rate, S
Ti
, is estimated linearly as S
Teol
per MTTF
Ti
.
Transmission line current is assumed to be normally distrib
uted with initial current loading IP
Tµ
= 60% and IP
Tσ
=
10% as in 2.3. Nominal current is assumed to be 85% of rated capacity. The higher ambient air temperature scenario
strength reduction rate S
Tf
is estimated using the same approach, increasing IP
Tµ
by β
T
and θ
+
accordingly.

Teol Ti T
Tf T
Tf
SSA
MTTF A
S


years
(3)
2.4.3. Substation – transformer insulation degradation
Substations consist of several power quality and protection
devices to ensure safe and reliable grid operations,
and this analysis focuses on transformers which are current-carrying devices used to change voltage levels for safe
and ef
ficient T&D of power throughout the network. The major parts of interest within transformers are the
co
nductor windings and their insulation.
M
S
Pf'
is estimated by equation (1) assuming an initial MTTF of insulation life of 48.9 years as are the results of
[24] for an oil-based distribution transformer, and is assumed representative of s
ubstation transformers.
M
Si
Pf
= λ
Si
=
0.0056% per day.
M
Sf
Pf
is estimated scaling MTTF by the marginal unit linear adjustment factor from the same
study where MTTF decreased from 48.9 to 46 years per 1
% increase in ambient air temperature. It is important to

1352 Daniel Burillo et al. / Procedia Engineering 145 ( 2016 ) 1346 – 1353
note that this method does not explicitly consider the current loading at the substation IP, and that an oil-based
distribution transformer may not be representative of transmission-level transformers.
2.5. Cascading failures
The change in probability of a cascading failure, ∆Pc
, is calculated in the same manner as equation (1).
i
Pc
=
0.0013% per day and
f
Pc
are estimated in equation (4) as one minus the probability that no failure occurs on a
random day minus the probability of exactly one failure occurring on a day, times the cascade trigger coefficient
α=10%. The probability that two simultaneous outages trigg
er a cascade are the results of [25] wherein a dynamic
power flow simulation of a 2,383-bus system was used to assess the probability of cascading failures occurring in
th
e event of two simultaneous outages within 2,896 component branches for n-1 contingency.
,
,
,
1(1) (1), ,,{ ,}
aaa
kbkbkbk
ab
ab
ab
i initial
Pc Pf Pf Pf where k a b other a b
f final
D
§·
ªº
§·
ªº

¨¸
       
«»
¨¸
®
«»
¨¸

¯
«»
¬¼
©¹
¬¼
©¹
¦

% per day
(4)
3. Results
A 1-5°C increase in ambient air te
mperatures can significantly increase the rate of mechanical- and power-based
failures as well as the cascading outages in the electric grid in Arizona. As listed in Table 1, mechanical failures in
tran
smission lines could increase almost 200% for a 1°C increase. This means that the same strength loss that occurs
in an overhead ACSR line over 70 years due to annealing could occur in 25 years, and lines could need to be
recon
ductored or replaced that much more often. Mechanical failures in substations could increase by 16% with the
fi
rst 1°C
θ₊, and then approximately double for each 1°C thereafter if conductor insulation oil is not changed with
that additional frequency. Power failures due to insufficient generation
could be more than twice as likely with a 1°C
increase in air temperatures. In that case reserve margins would fall below 5% on very hot days more often with
ad
ditional load, reduced generation capacity, and reduced distribution efficiency proportional to the distribution of
dail
y max temperatures. Power failure frequency in substations and transformers can increase 22x to 30x
respectiv
ely for a 1°C
θ₊. Increases in system peak load and decreases in current capacity in those components
during peak hours could result in exceedance of rated current and tripping with much higher frequency. The
proba
bility of two or more failures triggering a cascading outage can increase by 26x with the first
θ₊=1°C. The
change in probability of cascading failures grows exponentially with
θ₊ and increases in power-based failures. If the
probability of a cascading failure event is currently once every 20-30 years, then that probability could increase to
on
ce every 1-2 years with hotter summers if preventative measures are not taken.
Table 1. Increased probability of failures per degree increase in ambient air temperature.
θΕ (°C)
P
G
Pf'
P
T
Pf'
P
S
Pf'
M
G
Pf'
M
T
Pf'
M
S
Pf'
Pc'
0
-
-
-
-
-
-
-
1
135
2,955
2,225
1
183
16
2,587
2
400
43,799
28,751
2
409
39
77,788
3
871
305,542
194,967
3
576
73
1,287,827
4
1,620
1,087,885
744,306
4
685
128
10,275,393
5
2,691
2,183,150
1,704,373
5
711
236
35,679,472
4. Conclusion
Specific vulnerabilities in the electric power grid are identified where proactiv
e governance may be able to
prevent future outages otherwise resultant from rising ambient air temperatures in Arizona. Preventative measures in
operation
s and maintenance could include more frequent reconductoring and changing of insulators, component
d
erating, upgrades to more thermal resistant parts, forced-air cooling systems, dynamic power-flow routing, and or
dem
and side management programs including energy efficiency, demand response, and peak load shifting [4, 11, 19,
24]. Increased inspections and flexible maintenance schedules around weather patterns could be useful in the
in
terim. Failure to do so may result in outages in other critical interdep
endent infrastructure systems including water,
transportation, telecommunications, and information technology [27].

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Daniel Burillo et al. / Procedia Engineering 145 ( 2016 ) 1346 – 1353
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