Staying on course
On August 9, 2019, during rush hour, London and large parts of England and Wales faced a massive power outage that crippled the entire country.
In February 2021, as Texas battled record-low temperatures and snow and ice rendered the highways impassable, its electric grid operator lost control of the power supply. In the wake of a blackout that lasted for days, senior state legislators requested probes, and citizens demanded accountability from the government.
Closer home, February 2022 saw Mumbai dealing with a significant power outage that affected the city’s central, western, and southern portions, leaving the financial capital without its primary lifeline—the local rail services.
In this context of burgeoning cities and increased demands, the utility sector must develop metrics that can monitor, evaluate, and execute corrective actions during disruptive events and fallouts.
Standard metrics to measure utilities’ performance
The utility sector has evolved globally.
Technological upgrades and new user requirements have led to major developments in the utility sector (transmission and distribution). Even as the industry strives to maximize customer satisfaction, regulators are introducing stringent measures to enhance efficiency.
Key metrics that are used to evaluate performance include:
Availability – The demand vs. supply gap
Quality – Adherence to regulatory voltage levels and frequency, harmonics, system stability, and so on
Reliability – SAIDI, SAIFI, and CAIDI, with the intent to determine the number of interruptions and their duration, as well as the total number of end users affected
Flexibility – Time to respond and cater to sudden changes in power requirements
Affordability – Price per unit for end users
While these metrics are critical, they fail to identify the inherent capability of the grid to effectively cater to consumers in the context of a disruptive event.
Resilience: The new power metric
Resilience encompasses both quantitative and qualitative metrics.
The Electric Power Research Institute (EPRI) defines resilience as the ability to reduce the magnitude and duration of disruptive events through three aspects—prevention, recovery, and survivability. Thus, resilience encompasses both quantitative and qualitative metrics.
Quantitative metrics include availability, reliability, and power quality, while qualitative ones could include factors like the utility’s ability to withstand or prevent the effect of disruptive events. Grid resilience or resiliency goes hand in hand with the grid modernization drive that utilities had to undertake against the backdrop of aging infrastructure, lack of real-time centralized control, and the exponential increase of connecting renewables to the system.
A utility is resilient if it continues to serve its consumers despite an untoward event.
This depends on the utility’s ability to withstand disruption and not merely its ability to recover quickly from failure. We can aim to measure the system or asset performance under multiple heads, including:
Headroom and condition of the assets while sustaining or resisting failure
Ability to thwart a physical or cyber attack
Time to restore 100% supply after an event
Responsiveness while catering to sudden supply or demand changes
Ability to resolve congestions without interruption
Ease of absorption of distributed energy resources (DERs) in the system
Thus, quite distinctively, we see three stages of grid resilience:
We can observe and experience the concession and retrieval phases since they are most obviously manifested. By monitoring the time of the outage as well as the time taken for restoration, we will get a discrete idea of the grid’s resilience (illustrated in the resilience trapezoid in Figure 1).
Figure 1: The resilience trapezoid
Going beyond grid performance
It is feasible to monitor the confrontation phase.
In addition, operations can also be automated by programming them against certain event thresholds with advanced distribution management. However determining the degree of resistance provided by remedial measures entails many dependent and independent elements, including manual decision-making.
What remains a mystery is the evasion phase and its scope in terms of time and capacity. That is because field assets often suffer uneven non-linear deteriorations, further compounded by external influences. Consequently, the amount of withstanding or evasion will be a real-time conflation of performance metrics, asset conditions, and operational permutations.
Combining phases A, B, and C, gives us a valid measure for gauging grid resilience. As we advance, thinking beyond grid performance and leveraging stakeholder collaboration will be essential to minimize an event's severity and safeguard our world.