IEEE Technology and Society Magazine - June 2018 - 67
Peerenboom distinguishes between cascading, esca-
lating, and common cause failures between infrastruc-
tures. In his representation, cascading failures are those
in which a disruption in one infrastructure causes fail-
ures in another, while escalating failures are those for
which a disruption in one infrastructure exacerbates an
independent disruption in another [22]. This differs from
the more narrow definition of a cascading failure within
the electric power system research community: "a
sequence of dependent failures of individual compo-
nents that successively weakens the power system" [23].
Common cause failures occur when two or more infra-
structures are disrupted simultaneously, by a severe
storm for example [22]. Peerenboom, like Perrow, called
for cross-disciplinary collaboration, a call continued in
[24], which apparently includes those who study normal
accidents or HROs through the generic qualifier of
"social scientists."
A 2004 opinion piece argued that the electric power
system has a lot to learn from air traffic control [25];
one of the authors participated in the aforementioned
critical infrastructure workshop [26]. Air traffic control is
a darling of both frameworks. From the normal accident
framework, the authors recognize that operations and
investigations into failure must be located in separate
agencies [25], presumably to reduce political and social
pressures. They also propose that national coordination
is needed, although local and regional actions dominate
[25]. Consistent with the HRO framework, the authors
suggest transforming panicked responses when things
go wrong into incident investigations and research and
development for new tools [25]. The authors also note
the need for comprehensive data monitoring and real-
time interpretation [25], helping to create a big-picture
view of the system. Although the authors do not men-
tion either framework, it is clear that their suggestions
for changes in the electric power system were inspired
by case studies and findings from both frameworks.
In a 2006 conference paper, Hines et al. examined
large blackouts in the United States to test the assump-
tion that blackout frequency (adjusted for demand
growth) should decrease due to engineering and policy
changes made after each large blackout since the late
1960s [27]. The authors argue that "[t]he U.S. air traffic
control system provides precedent for a large, complex
system undergoing a significant decrease in risk follow-
ing appropriate engineering and policy actions" [27].
Using data from 1984 to 2000, the authors note that
"human error" accounts for 11% of all reported distur-
bances [27]. (Recall Perrow's warning about this label).
Excluding outages caused by weather, the authors found
that the frequency of large blackouts is not decreasing,
speculating that the possible increase is caused by
under-investment in transmission and a lack of mandatory,
JUNE 2018
∕
enforceable rules for reliability [27]. They also note that
the protection system, which isolates stressed equip-
ment to avoid damage to the individual component, tends
to cause cascading failures at the system level rather
than control them [27].
When systems have self-organizing
criticality, actions designed to mitigate
problems may actually increase the
likelihood of large disruptions.
In a 2009 journal article, the same group of authors
found that blackout frequency: 1) has not decreased with
time, 2) changes seasonally, and 3) increases during
times of peak use [28]. Furthermore, the size of the
blackout follows a power law probability distribution (as
shown by other researchers) and is not correlated with
restoration time [28]. They recommend doubling the
operators during peak use times and focusing mitigation
on both large and small outages [28]. Although Hines et
al. do not acknowledge either normal accidents or HROs,
their findings and policy recommendations could have
benefited from such attention. Whether organizational
redundancy (adding more operators during peak use
times) will actually help is an open question. HRO re-
searchers believe that such redundancy is important,
while normal accident researchers are unconvinced. A
footnote seems to acknowledge this, noting that "most
electric utilities, and other system operators, increase
operations staff during peak periods and daytime hours"
[28]. Why has the blackout risk during peak hours per-
sisted even though utilities use increased organizational
redundancy? The normal accident framework would sug-
gest that it is because the electric grid is more tightly
coupled as load increases. The HRO framework might
suggest ways in which organizational redundancy is not
actually fulfilling its desired function through "mindless-
ness" or limited cooperation [29].
In 2011, a group of power system researchers investi-
gated the "complex systems aspects of blackout risk
and mitigation" [30]. By focusing on the frequency distri-
bution of different sized blackouts, the authors argue
that components cannot be assumed to be independent
[30]. If independence was a valid assumption, the prob-
ability of large blackouts would show an exponential
decay; instead, it follows a power law distribution [30],
[31]. The authors claim that this property of the blackout
frequency distribution supports Perrow's description of
IEEE Technology and Society Magazine
67
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