Utilities traditionally focused on engineering the electric grid for reliability, and have well established metrics and benchmarks to gauge their performance to reliability objectives.  But today’s grid also has serious vulnerabilities highlighted in recent widespread and lengthy power outages caused by downed power lines.  Smart Grid technologies offer the opportunity to significantly re-engineer the supply of electricity to the grid to reduce inherent vulnerabilities cause by reliance on centralized generation and existing fragilities in transmission and distribution.  These technologies include distributed generation, energy storage, microgrids, and fuel cells – aka distributed energy resources or DER.  These resources can be managed as Virtual Power Plants by utilities, other energy service companies, or by the asset owners – residential, commercial, or industrial end users.

Locating electricity supplies in the distribution grid can create grid resiliency – the fast recovery of an acceptable level of electric services on a continuing basis despite disruptions to normal operations.  Grid resiliency implies that the grid has sufficient intelligence to be adaptable to different problem scenarios and offer what could be considered variable qualities of service (QoS) based on those scenarios.  This recent study on consumer attitudes about outages offers interesting data about what people would pay for improved service – meaning a cessation of outages or definitions of acceptable levels of service.   Grid resiliency should become as important as grid reliability and should be reflected in regulatory policies.

But that brings us to a very important question – just how do you measure grid resiliency?  It’s one thing to set an objective to build resiliency into your grid’s electricity supply, it is another thing to measure your success at achieving it.

Business sectors like telecommunications frame resiliency expectations and performance with metrics that include Quality of Service (QoS) and uptime statistics written into Service Level Agreements (SLAs).  SLAs are negotiated and managed to deliver minimum acceptable performance levels that cover network quality and availability.  Traditional utility reliability metrics like SAIDI (System Average Interruption Duration Index) and SAIFI (System Average Interruption Frequency Index) benchmark the number and length of service disruptions across all customers.  Electric utilities and regulators use these measurements to gauge grid performance.  But what if utilities were asked to deliver 99.99%* uptime to all customers in a year instead of performance to a defined amount of downtime?  That would translate into less than an hour of outage in a year.  How differently would utilities design and configure power grids to meet a performance expectation that measures uptime rather than downtime?

Before the advent of Smart Grid technologies that offer DER and intelligent management and analytical insights, measuring downtime was the best we could expect from the power grid.  These new technologies offer the fascinating possibilities to rethink the metrics we use to measure grid performance.  Quality of Service and uptime measures are two possibilities.  There are many more out there that should be given serious consideration.  As we upgrade, enhance, and modernize the electrical grid, we need to ensure that we give equal investment of thought to redefining our expectations of its performance.

*mission-critical telecom equipment is usually engineered for the five nines – 99.999% uptime, or 6 minutes of downtime a year.