Continued lessons learned from Superstorm Sandy
Reflecting on the anniversary of Superstorm Sandy, it is tempting to dwell only on the immediate impact of the storm on the hardest hit areas. The effected communities have shown tremendous strength in rebuilding the devastated infrastructure, and will continue to heal emotionally. However, it would be short-sighted to remember Sandy only for the pain and suffering it inflicted. Indeed, metaphorically the winds that drove Sandy’s destruction have reached far into many North American utilities’ emergency preparation psyche and have caused significant changes to the way in which assets and systems are built, protected and repaired.
Nowhere is this more visible than in the coastal utilities in the Northeast, who have clearly heard the message of preparation. However, as we reflect upon the potential lessons learned, we continue to be concerned that the response is not as broad-based as the industry really needs. Indeed, many utilities continue to have two dangerous biases that could severely impact their resilience in the face of future events and their ability to maintain and/or restore reliable service proactively.
The first of these biases is a view that these types of disastrous events will only happen in coastal communities. Indeed, risk managers should be modeling a variety of risks and the unique implications of each on reliable service. For example, the extent of the destruction related to Sandy could also be partially recreated by a wide-spread fire, a tornado, or other event. Each would require very different protection schemes to be in place, and a very different response profile.
The second concern is with those utilities that continue to model their responses on the basis of an “n-1 or n-2” scenario. Most significantly, damaging natural phenomenon demand a view of planning that creates more of an “n-m” scenario, necessitating a completely different statistical modeling approach to the problem. DNV GL has been collaborating with entities globally to more effectively models both the risks and the likely system impacts associated with such risks on the basis of a statistical predictive modeling tool called “ADAPT.”
As a framework, ADAPT is an adjunct to modern planning tools and provides operational insights uniquely linked to an emerging view on risk management. As the industry looks forward, let’s make sure we collectively use the opportunity to learn from the broader lessons Sandy should have taught us, and prepare our systems accordingly.
SlideShare presentation: ADAPT Framework for Grid Resiliency
Probabilistic risk-based modelling tool for the power industry
Enhancing resilience to severe weather and climate change
DNV GL: Adaptation To A Changing Climate (Video)
Adaptation to a Changing Climate Report
One year later: Superstorm Sandy underscores need for a resilient grid
When the Bough Breaks: Managing Extreme Weather Events Affecting Electrical Power Grids, IEEE P&E, Sept/Oct 2014
Assessing Climate Change Hazards to Electric Power Infrastructure – A Sandy Case Study, IEEE P&E, Sept/Oct 2014