Welcome to the 4th installment in our 5-part series on Smart Grid Technology. In the 2 previous articles, we looked at the growing use of autonomous microgrids and distributed energy resource management systems (DERMS’s) to make electricity delivery more reliable – both locally and across the entire utility network.
This article explores the importance of grid resilience, which involves the full suite of tools used to minimize the impact of natural or man-made disturbances to America’s energy infrastructure, economy, and national security.
Table of Contents
What Is Grid Resilience (a Modern Definition)?
The US Federal Energy Regulatory Commission (FERC) defines “grid resilience” as the,
“[A]bility to withstand and reduce the magnitude and/or duration of disruptive events, which includes the capability to anticipate, absorb, adapt to, and/or rapidly recover from such an event.
In lay speak, grid resilience describes the utility network’s ability to resist disturbances and bounce back with minimal downtime or disruptions.
Historically, the term has been reserved for weather-related events like blizzards or hurricanes – with utility workers scrambling to restore power to impacted communities as quickly as possible. The growing use of autonomous microgrids and consumer solar power have helped mitigate disruptions like these due to redundancies built into localized sections of the electricity grid. As climate change worsens, however, the impact of inclement weather will only become more severe. We’re already seeing the early warning signs now, with Texas going days without power during subfreezing temperatures and Puerto Rico still reeling from the nation’s longest sustained power outage following Hurricane Maria.
Grid resilience is also being used to protect communities from oversupplies and shortages stemming from renewables like solar and wind energy – both of which are intermittent power sources that are difficult to manage and predict. For example, utilities often use behind-the-meter batteries and DERMS technology to streamline network management and smooth out peaks and valleys in energy supply.
In recent years, however, the ever-present threat of cyberattack has brought renewed attention to grid resilience. With malicious actors now capable of downing entire power stations with just a few lines of code, there is a renewed push to shore up the country’s electricity infrastructure to resist and recover from these types of disruptions.
And this highlights the key difference between grid reliability vs. resilience.
Whereas the other components of smart grid design are focused on making the energy network more reliable, resilience focuses on the tools used to reduce the impact of disturbances and recover quickly. In effect, the goal is to make the network more adaptive so that it can withstand the most catastrophic consequences of grid outages. And this involves planning for the full range of potential threats, complete with adequate recovery and backup plans in place to minimize downtime.
Why Is Grid Resilience Important?
It’s impossible to overstate the economic benefits of increasing electric grid resilience to weather outages, with the US Department of Energy’s Berkeley Laboratory reporting that:
- Weather-related outages cost utility customers $2 billion to $3 billion annually.
- For the economy as a whole, these outages represent $20 billion to $55 billion in lost business.
Note that this analysis only factors in weather-related events, where most of the damage is physical and can be repaired by field technicians. The economic impact of cyberattacks is much harder to determine since this is relatively new territory. But according to a 2015 analysis by Lloyd’s and the University of Cambridge’s Centre for Risk Studies, a large-scale cyberattack on 15+ states could leave nearly 100 million Americans without power and result in up to $1 trillion in direct economic losses.
Against this backdrop, building a resilient electric grid is no longer strictly an economic issue. It is a matter of national security, which is why US policymakers, military personnel, and security professionals are increasingly making grid resilience a top priority.
What Does a Resilient Electric Grid Look Like?
Grid resilience is not a new concept. Utilities have always recruited and trained field technicians to help restore power quickly in the wake of major storms. For these repairs to happen, however:
- Impacted customers must first alert their utility providers – which takes time
- Utilities must then dispatch field teams to pinpoint the exact cause and location of the problem (using trial and error)
- Once the issue is isolated, field teams can finally fix the underlying problem
In this scenario, resilience is measured by the time required for these back-to-back steps to unfold. Utilities and independent power producers are constantly looking for ways to shorten notification, response, and repair times.
One mitigating factor is the growing diversity of distributed energy resources. Sudden dips in rooftop solar production, for example, can be offset by stored solar power or increased wind energy from elsewhere in the electricity network. However, the growing complexity of America’s greening grid and increased reliance on the Internet of Things (IoT) have created new demand for tools to help manage this complexity, even amidst emerging threats – like worsening storms or cyberattacks.
With distributed energy resource management systems, for example, grid operators and asset managers can rely on edge device sensor data to quickly detect both the when and where of network disruptions. A downed utility pole will remain down until field teams go on-site to repair it. But under a grid resilience framework, utilities can relay emergency power to impacted communities from microgrids or other sections of the network – until the original transmission lines have been restored.
This agility is a crucial component of self-healing smart grid technology. But it alone isn’t enough if human actors are still involved in the decision-making process. You still need a living-breathing person to:
- Receive real-time sensor data from edge devices like solar panels or batteries
- Realize there is a disturbance in the grid network that needs intervention
- Determine the most appropriate course of action (and take that action)
Although DERMS technology can help shorten response times considerably, there are limits to how much data grid operators and asset managers can analyze. Fortunately, a new generation of machine learning tools is helping to automate the entire process and make the grid leaner, faster, and more resilient.
The Growing Role of Artificial Intelligence in Grid Resilience
Grid resilience describes the ability to bounce back after network disruptions. And a self-healing smart grid is one that has the ability to bounce back quickly without human intervention.
Artificial intelligence (AI) is the key technology responsible for bridging this gap.
At Veritone Energy, our predictive AI software uses both historic and real-time weather, supply, and demand data to determine the optimal balance of power generation and energy storage to ensure uninterrupted electricity delivery. This analysis is already a critical component in Veritone Energy’s DERMS solutions in which our AI technology uses:
- Sensor data on edge devices to receive and interpret energy storage and production levels from the field
- Machine learning algorithms to determine the ideal mix of energy supply and demand
- Edge device receivers to execute instructions – like topping up batteries or scaling back wind production
However, Veritone Energy’s AI software can also be deployed to identify network vulnerabilities, isolate potential disruptions, and take corrective action to minimize downtime. During a cyberattack or weather emergency, for example, microgrids can be islanded and operated autonomously. Grid resilience is assured since Veritone Energy’s technology fuses together data from real-time weather conditions, load forecasting, energy pricing, microgrid generation levels, and even FERC compliance rules to deliver optimal energy dispatch and predictive control – whether between microgrids or autonomously in an islanding configuration.
With the legacy grid, utilities were responsible for relaying power to impacted communities during outages – until the underlying problem could be fixed. With a truly resilient smart grid, the same process is at work. However, power restoration is instantaneous and automated using artificial intelligence. The end result is a self-healing electricity network that can reduce (if not eliminate) blackouts by correcting course on its own.
A useful analogy is the GPS system in your car.
When you miss a turn or run into a roadblock, there’s no need to pull out a physical map and reorient yourself. The GPS instantly finds the fastest route to your destination based on your new location. Our AI technology does the same thing – but for energy. It instantly finds the cheapest and fastest route to dispatch electricity despite outages, congestion, or other grid-related roadblocks.
Natural disasters and cyberattacks are very real threats that directly impact energy delivery, the US economy, and national security. Worse still, these challenges will only become more pronounced due to climate change and our growing reliance on Internet-connected devices.
While it’s not possible to protect against all potential threats, grid resilience allows us to minimize their impact so that we can recover more quickly. Energy diversity, grid redundancies, and DERMS technology are all crucial tools in this fight. But as long as human actors are pulling the levers, grid resilience will continue facing inherent limitations.
In the 5th and final installment of this 5-part series, we’ll take a closer look at artificial intelligence’s growing role in automating smart grid management and bringing us closer to the goal of a fully autonomous power grid.
To learn about the other pillars of smart grid technology, check out the chapeters below.
- The Ultimate Guide to Smart Grid Technology and Benefits
- Distributed Energy Resource Management Systems
- AI-Powered Electricity Grids (coming soon)
You may also enjoy this brief 30-minute podcast that introduces the challenges of smart grids and highlights some of the benefits of AI to improve energy and utility operations.