IEEE Power & Energy Magazine - March/April 2018 - 29

Resiliency Quantification:
Risk-Based Maps
as the notion of resiliency gets further defined, it is necessary to introduce quantitative ways of measuring resiliency.
One possible approach is to define risk as a measure of resiliency. a well-established risk definition commonly used in
the engineering fields defines risk as
Risk = Hazard # Vulnerability # Impacts,
where
✔ intensity t is the threat intensity
✔ hazard is the probability of threat with intensity t
✔ vulnerability is the probability of a consequence c if a

Temperature

Wind

Resiliency in Control Strategies:
Hierarchically Coordinated Protection
When the electricity grid is in the in extremis state, fast control
actions are needed; in most cases, these cause protective relaying systems to "trip" circuit breakers and disconnect faulted
parts of the system from service. the protective relaying
function is decentralized to substations for faster action and
operates in the millisecond time frame. control center personnel do not get involved in initiating the relaying actions
because of the subsecond time-frame response required,
but they are greatly concerned with the outcomes of such
actions to enable mitigation of impacts and bring the power
grid back to its normal operating state. to improve resiliency going forward, fast control actions will also have to be
redesigned to allow for hierarchically coordinated protection (HcP). such a concept was introduced following the

Weather
Precipitation Clouds

Lightning

Humidity
Forward Market

Real-Time Market

Power Generation
Renewables:
Hydro
Solar
Wind
Fossils:
Gas
Coal

Power Transmission
Substations
Lines
Cables

Power Distribution
Substations
Lines
Cables

Probabilistic Spatiotemporal
State of Risk
Probabilistic Regression

Customers
Residential
Commercial
Industrial

Vulnerability

Mitigation
Monitoring
Control and Protection
Flexible Load

Risk

Risk Assessment

Elements at Risk

Risk Mitigation Risk Threats

threat with intensity t occurs
✔ impacts are the stimulated economic and/or social impacts if consequence c has occurred.
this approach not only allows the resiliency to be quantified
but also defines a framework to assess and mitigate threats
for the elements of the grid at risk. most importantly, the risk
can be expressed in monetary values, which further mea-

sures the economic impact of the loss of resiliency. such a
framework is shown in Figure 3.
this framework is illustrated in several applications discussed later in this article, when asset and outage impacts on
resiliency are introduced. By selecting proper data analytics, the risk can be predicted, and associated risk prediction
maps can be generated that provide guidelines to operators
for mitigating risk and, hence, improving resiliency. (the
resiliency definition and quantification require further studies beyond the scope of this article.)

Hazard

used in presentations by d.J. sobajic and J. douglas of the
electric Power research institute (ePri) in early 2003, shows
an example how the wholesale markets may go into different
market states depending the ways in which the physical system
states unfold.

Causal Probabilistic Risk Assessment

figure 3. A risk assessment and mitigation framework for resiliency quantification.
march/april 2018

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Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - March/April 2018