In pursuit of a more reliable and resilient system

By Massoud Amin

As the world grows more interconnected, we are becoming surrounded by complex interactive networks/systems (CIN/S). These systems consist of numerous components interlinked in complicated webs. As a result of the number of components and their intricate interconnections, CIN/S are extremely difficult to design, analyze, control, and protect. Despite these challenges, understanding and managing CIN/S is becoming critical. Many of our nation’s critical infrastructures are complex interdependent/networked dynamical system of systems, including:

  • electric power grids with overlays of sensor/communications/control systems and markets
  • fuel supply networks and energy/oil/gas pipelines
  • telecommunications and satellite systems
  • the Internet, computer networks, and the ‘cyberinfrastructure’
  • transportation systems
  • energy markets, banking and finance systems
  • environmental, consumer, societal and policy macrosystems
  • state and local water supply, emergency, and other services.

The secure, reliable operation of complex, increasingly interdependent, infrastructure systems such as these is fundamental to our economy, security, and quality of life. Of particular importance is the uninterrupted availability of inexpensive, high-quality electrical power and reliable, high-performance communication networks.

The potential for preventing rare events but high-impact cascading phenomena represent just a few of many new science and technology concepts that are under development. Analysis and modeling of interdependent infrastructures (e.g., the electric power grid, together with protection systems, telecommunications, oil/gas pipelines, and energy markets) is especially pertinent.

What’s Needed to Speed Up Restoration?

Since Hurricane Sandy struck the East Coast with unprecedented fury, much discussion has focused on questions about power restoration: Did the smart grid help? Or, would a smart grid have helped?

The questions are valid but the short answer is unsatisfying: it depends. A longer answer is more helpful because it allows us to consider the drivers of grid modernization, the concepts governing a ìself-healingî grid, and how we can maximize the benefits of future investments.

Detailed, post-event analysis will be needed to ascertain whether smart grid technology softened Sandy’s impact or sped up power restoration. Meanwhile, let’s place the storm and its impacts in context.

  • It should be understood that a massive, physical assault on the scale of last October’s superstorm is bound to overwhelm the power infrastructure, at least temporarily. No amount of money or technology can guarantee uninterrupted electric service under such circumstances.
  • The power industry in the United States is just beginning to adapt to a wider spectrum of risk. Both the number and frequency of annual, weather-caused, major outages have increased since the 1950s. Between the 1950s and 1980s, there were two to five such outages per year. In the period 2008–2012, those outages increased to between 70 and 130 per year. In that five-year period, weather-related outages accounted for 66% of power disruptions, which affected up to 178 million customers (meters).
  • This adaptation process continues as we implement strategies, technologies, and practices that will harden the grid and improve restoration performance after a physical disturbance. The investments so far in advanced metering infrastructure and the coming wave of investment in distribution automation are but the beginning of a multidecade, multibillion-dollar effort to achieve an end-to-end, intelligent, secure, resilient and self-healing system.
  • Cost-effective investments to harden the grid and support resilience will vary by region, by utility, by the legacy equipment involved, and even by the function and location of equipment within a utility’s service territory.

In Sandy’s case, coastal areas were subject to storm surges and flooding, while inland, high winds and lashing rain produced the most damage. Improved hardening and resilience for distribution systems in those different environments would take different forms. Underground substations along the coasts may have to be rebuilt on the surface, while it might be cost effective to perform ìselective undergroundingî for some overhead lines further inland.

The one generalization we can make, however, is that the pursuit of an intelligent, self-healing grid has some common characteristics that will make the grid highly reliable in most ≠circumstances—certainly in cases where disruptions are less catastrophic than Hurricane Sandy. Additional, location-specific steps based on rational risk assessment also can be taken by utilities and customers.

What’s the Problem?

It’s fair to ask: why should we make significant investments in upgrading the electric grid?

Currently, outages from all sources cost the U.S. economy US$80–$188 billion annually. A 2011 competitiveness report by the World Economic Forum ranked the U.S. infrastructure below 20 among the world’s nations in most of nine categories and below 30 for the quality of our air transport and electric power sectors.

Clearly, the United States needs to invest in grid modernization simply to catch up with its global rivals.

The Value Proposition

We have to take a critical approach to the enormous investments needed to improve reliability and resiliency and enable economic competitiveness. One metric is return on investment (ROI).

Having studied this in depth various options and their associated costs, benefits, and ROI, each $1 invested garners a return of $2.80–$6 to the broader economy. The ROI begins immediately with job creation and economic stimulus. To reach these numbers, we used a very narrow definition of the smart grid. If the definition is broadened, the benefits increase.

A smarter, stronger grid would reduce the low-end estimate of current outage costs of US$80 billion annually by US$49 billion, in my estimates. That smarter grid would increase the system’s efficiency by about 4.5%. That’s worth another US$20.4 billion, annually. Together, improving just those two aspects—reducing outages, improving efficiency—brings about US$70 billion in annual benefits. A smarter grid would also reduce CO2 emissions by 12–18%.

To accomplish this, cost estimates for the United States as a whole range somewhere between US$338 billion and US$476 billion for a smarter grid and about US$82 billion in hardening costs for a stronger grid. So when you recast it as a 20-year project, it’s going to cost the United States somewhere between US$25–30 billion a year for 20 years.

Much of the early work has been done in the past few years as federal stimulus funding encouraged advanced metering infrastructure (AMI). AMI has introduced end-of-line sensors (a.k.a. “smart meters”) that can communicate price signals and demand response actions that can serve to balance supply and demand and provide ìlast gaspsî that automatically indicate when power has failed at the customer’s premise.

The coming wave of distribution automation is enhancing the overlay of sensing, secure communications and control by adding distributed intelligence, intelligent electronic devices and enabling improved fault detection, isolation and restoration as distribution management systems and outage management systems are integrated. But we need to follow this initial effort with serious levels of annual investment for decades to meet 21st century economic and environmental challenges.

The ‘Self-Healing’ Power Grid

For the purposes of our projects since January 1998, we define a smart grid to be an end-to-end cyber-enabled electric power system, from fuel source to generation, transmission, distribution, and end use, that will:

  • enable integration of intermittent renewable energy sources and help decarbonize power systems
  • allow reliable and secure two-way power and information flows
  • enable energy efficiency, effective demand management, and customer choice
  • provide self-healing from power disturbance events
  • operate resiliently against physical and cyber attacks.

The path for realizing the smart grid is fraught with several formidable challenges. Increased penetration of renewables implies that the transmission systems have to be expanded by a significant amount, by about 42,000 mi, which is 9% of the current 450,000 mi in North America, to support these renewables in dispersed areas. It also introduces operational challenges in terms of requiring significantly higher levels of regulation and ramping capacity. New flow patterns enter the picture at the distribution level and necessitate drastic changes to the protection, distribution automation, and voltage and VAR management. Increased renewable generation also implies limited dispatchability and increased intermittencies, which are concomitant with increased ancillary services. Increased demand the world over, including the anticipated rapid increase in electrification of transportation, will lead to significant new loads on distribution networks, many of which are woefully inadequate when it comes to monitoring and automation.

Without these capabilities and upgrades, just using the word “smart grid” isn’t a very precise term. I prefer smart ìself-healingî grid, because it better describes the desired outcome of the investments I advocate for in grid modernization. The pursuit of a self-healing grid brings a number of benefits through stability and adaptation.

Three elements come into play here.

  • Real-time monitoring can alert grid operators to the precursors or signatures of impending faults, based on probabilistic analysis. Real-time monitoring has been enabled by a leap from traditional supervisory control and data acquisition (scada) systems to phasor measurement units (PMUs), a.k.a. synchrophasors. This technology improves the resolution of data polled from field devices from two to four times/s with SCADA to 20–50 times/s with PMUs. PMUs also provide precise, GPS-based time stamping so that events on the system can be analyzed accurately and chronologically in a wide-area management system, (WAMS). This allows operators to see ìhow the dominoes fell in the dark.
  • Real-time monitoring enables operators to react swiftly to restore balance to the system or to program field devices to respond automatically. This allows constant tuning of the grid’s many components to achieve an optimal, highly efficient state.
  • Rapid isolation allows the system to automatically isolate its parts that are failing or about to fail to avoid the spread of disruption and to enable more rapid restoration.

As a result, the self-healing smart grid is able to reduce the number of outages and their duration. Because all three functions are self-healing in nature, they add an end-to-end resilience to the grid that can detect and override human errors resulting in power outages.

End-to-End Technologies

An end-to-end system that anticipates problems, supports operator decisions or reacts automatically has a few elements worthy of emphasis.

At the customer end are the interval meters that provide usage data, serve as end-of-line sensors for voltage conservation, and emit “last gasps” as they lose power. Upstream of the meters, but downstream of the operators, we’ll see a proliferation of advanced sensors (intelligent electronic devices, or IEDs) that facilitate real-time monitoring and control of critical assets. Advanced protective relays, for instance, provide improved isolation of faults. All of the technologies discussed here are supported by two-way communication networks that bring the real-time monitoring data back to operators and allow the latter to send commands back to assets in the field. Finally, visualization tools such as dashboards convert data into color-coded graphics and automated alerts that provide decision support.

Three-Tiered Intelligence

The self-healing grid can be thought of as having three tiers of intelligence.

The bottom layer, closest to devices in the field, is distributed intelligence. It is akin to the reptilian brain, with simple responses to environmental stimuli. At a substation, for instance, an intelligent device monitors the health of the asset and communicates that to the middle layer, where the validation of incoming data and coordination of various functions takes place in milliseconds. This is similar to a mammalian neocortex that can strategize, act, and be upgraded through experience to higher functionality. The top layer contains the centralized command-and-control functions directed by human operators.

Risk Assessment

The initial step, before implementation, is risk assessment. Risk is dynamic, local, and specific. National policies will help, but achieving hardening and resiliency on the ground will be specific to a utility’s customers’ needs, its legacy systems, location, and technology roadmap.

A dynamic risk landscape requires annual updating to ensure protection of the right assets. How has the risk portfolio or the spectrum of risk changed? With climate change, the variability of weather events has increased. We are going to see more extreme events that have never happened before with greater frequency. Hurricane Sandy appears to be an example of this challenge.

So a clear sense of dynamic risk should guide our investments in hardening and resilience, based on evidence and data. We need a new set of tools and a fresh set of approaches to system upgrades to be more dynamic and more adaptive to achieve resiliency and security.

Back to the ‘Big Picture’

Our immediate and critical goal is to avoid widespread network failure, but the longer-term vision is to enable adaptive, resilient infrastructure. Achieving this vision and sustaining infrastructure reliability, robustness, and efficiency are critical long-term issues that require strategic investments in research and development.

When the United States has made such strategic commitments in the past, the payoffs have been huge. Think of the interstate highway system, the lunar landing project, the Internet. Meeting each of those challenges has produced world-leading economic growth by enabling commerce and technology development. In the process, we developed a highly trained, adaptive workforce.

Similarly, given the economic, societal, and quality-of-life challenges and the ever-increasing interdependencies among infrastructures we have today, we must decide whether to build electric power and energy infrastructures that support a 21st century digital society, or be left behind as a 20th century industrial relic.