How Intelligent Is Your Grid?

Many people in the utility industry see the intelligent grid — an electric transmission and distribution network that uses information technology to predict and adjust to network changes — as a long-term goal that utilities are still far from achieving. Energy Insights research, however, indicates that today’s grid is more intelligent than people think. In fact, utilities can begin having the network of the future today by better leveraging their existing resources and focusing on the intelligent-grid backbone.


Before discussing the intelligent grid backbone, it’s important to understand the drivers directing the intelligent grid’s progress. While many groups — such as government, utilities and technology companies — may be pushing the intelligent grid forward, they are also slowing it down. Here’s how:

  • Government. With the 2005 U.S. Energy Policy Act and the more recent 2007 Energy Independence and Security Act, the federal government has acknowledged the intelligent grid’s importance and is supporting investment in the area. Furthermore, public utility commissions (PUCs) have begun supporting intelligent grid investments like smart metering. At the same time, however, PUCs have a duty to maintain reasonable prices. Since utilities have not extensively tested the benefits of some intelligent grid technologies, such as distribution line sensors, many regulators hesitate to support utilities investing in intelligent grid technologies beyond smart metering.
  • Utilities. Energy Insights research indicates that information technology, in general, enables utilities to increase operational efficiency and reduce costs. For this reason, utilities are open to information technology; however, they’re often looking for quick cost recovery and benefits. Many intelligent grid technologies provide longer-term benefits, making them difficult to cost-justify over the short term. Since utilities are risk-aware, this can make intelligent grid investments look riskier than traditional information technology investments.
  • Technology. Although advanced enough to function on the grid today, many intelligent grid technologies could become quickly outdated thanks to the rapidly developing marketplace. What’s more, the life span of many intelligent grid technologies is not as long as those of traditional grid assets. For example, a smart meter’s typical life span is about 10 to 15 years, compared with 20 to 30 years for an electro-mechanical meter.

With strong drivers and competing pressures like these, it’s not a question of whether the intelligent grid will happen but when utilities will implement new technologies. Given the challenges facing the intelligent grid, the transition will likely be more of an evolution than a revolution. As a result, utilities are making their grids more intelligent today by focusing on the basics, or the intelligent grid backbone.


What comprises this backbone? Answering this question requires a closer look at how intelligence changes the grid. Typically, a utility has good visibility into the operation of its generation and transmission infrastructure but poor visibility into its distribution network. As a result, the utility must respond to a changing distribution network based on very limited information. Furthermore, if a grid event requires attention — such as in the case of a transformer failure — people must review information, decide to act and then manually dispatch field crews. This type of approach translates to slower, less informed reactions to grid events.

The intelligent grid changes these reactions through a backbone of technologies — sensors, communication networks and advanced analytics — especially developed for distribution networks. To better understand these changes, we can imagine a scenario where a utility has an outage on its distribution network. As shown in Figure 1, additional grid sensors collect more information, making it easier to detect problems. Communications networks then allow sensors to convey the problem to the utility. Advanced analytics can efficiently process this information and determine more precisely where the fault is located, as well as automatically respond to the problem and dispatch field crews. These components not only enable faster, better-informed reactions to grid problems, they can also do real-time pricing, improve demand response and better handle distributed and renewable energy sources.


A deeper dive into each of these intelligent grid backbone technologies reveals how utilities are gaining more intelligence about their grid today.

Network sensors are important not only for real-time operations — such as locating faults and connecting distributed energy sources to the grid — but also for providing a rich historical data source to improve asset maintenance and load research and forecasting. Today, more utilities are using sensors to better monitor their distribution networks; however, they’re focused primarily on smart meters. The reason for this is that smart meters have immediate operational benefits that make them attractive for many utilities today, including reducing meter reader costs, offering accurate billing information, providing theft control and satisfying regulatory requirements. Yet this focus on smart meters has created a monitoring gap between the transmission network and the smart meter.

A slew of sensors are available from companies such as General Electric, ABB, PowerSense, GridSense and Serveron to fill this monitoring gap. Tracking everything from load balancing and transformer status to circuit breakers and tap changers, energized downed lines, high-impedance faults and stray voltage, and more, these sensors are able to fill the monitoring gap, yet utilities hesitate to invest in them because they lack the immediate operational benefits of smart meters.

By monitoring this gap, however, utilities will sustain longer-term grid benefits such as reduced generation capacity building. Utilities have found they can begin monitoring this gap by:

  • Prioritizing sensor investments. Customer complaints and regulatory pressure have pushed some utilities to take action for particular parts of their service territory. For example, one utility Energy Insights studied received numerous customer complaints about a particular feeder’s reliability, so the utility invested in line sensors for that area. Another utility began considering sensor investments in troubled areas of its distribution network when regulators demanded that the utility raise its System Average Interruption Frequency Index (SAIFI) and System Average Interruption Duration Index (SAIDI) ratings from the bottom 50 percent to the top 25 percent of benchmarked utilities. By focusing on such areas, utilities can achieve “quick wins” with sensors and build utility confidence by using additional sensors on their distribution grid.
  • Realizing it’s all about compromise. Even in high-priority areas, it may not make financial sense for a utility to deploy the full range of sensors for every possible asset. In some situations, utilities may target a particular area of the service territory with a higher density of sensors. For example, a large U.S. investor-owned utility with a medium voltage-sensing program placed a high density of sensors along a specific section of its service territory. On the other hand, utilities might cover a broader area of service territory with fewer sensors, similar to the approach taken by a large investor-owned utility Energy Insights looked at that monitored only transformers across its service territory.
  • Rolling in sensors with other intelligent grid initiatives. Some utilities find ways to combine their smart metering projects with other distribution network sensors or to leverage existing investments that could support additional sensors. One utility that Energy Insights looked at installed transformer sensors along with a smart meter initiative and leveraged the communications networks it used for smart metering.

While sensors provide an important means of capturing information about the grid, communication networks are critical to moving that information throughout the intelligent grid — whether between sensors or field crews. Typically, to enable intelligent grid communications, utilities must either build new communications networks to bring intelligence to the existing grid or incorporate communication networks into new construction. Yet utilities today are also leveraging existing or recently installed communications networks to facilitate more sophisticated intelligent grid initiatives such as the following:

  • Smart metering and automated meter-reading (AMR) initiatives. With the current drive to install smart meters, many utilities are covering their distribution networks with communications infrastructure. Furthermore, existing AMR deployments may include communications networks that can bring data back to the utility. Some utilities are taking advantage of these networks to begin plugging other sensors into their distribution networks.
  • Mobile workforce. The deployment of mobile technologies for field crews is another hot area for utilities right now. Utilities are deploying cellular networks for field crew communications for voice and data. Although utilities have typically been hesitant to work with third-party communications providers, they’ve become more comfortable with outside providers after using them for their mobile technologies. Since most of the cellular networks can provide data coverage as well, some utilities are beginning to use these providers to transmit sensor information across their distribution networks.

Since smart metering and mobile communications networks are already in place, the incremental cost of installing sensors on these networks is relatively low. The key is making sure that different sensors and components can plug into these networks easily (for example, using a standard communications protocol).

The last key piece of the intelligent grid backbone is advanced analytics. Utilities are required to make quick decisions every day if they’re to maintain a safe and reliable grid, and the key to making such decisions is being well informed. Intelligent grid analytics can help utilities quickly process large amounts of data from sensors so that they can make those informed decisions. However, how quickly a decision needs to be made depends on the situation. Intelligent grid analytics assist with two types of decisions: very quick decisions (veQuids) and quick decisions (Quids). veQuids are made in milliseconds by computers and intelligent devices analyzing complex, real-time data – an intelligent grid vision that’s still a future development for most utilities.

Fortunately, many proactive decisions about the grid don’t have to be made in milliseconds. Many utilities today can make Quids — often manual decisions — to predict and adjust to network changes within a time frame of minutes, days or even months.

no matter how quick the decision, however, all predictive efforts are based on access to good-quality data. In putting their Quid capabilities to use today — in particular for predictive maintenance and smart metering — utilities are building not only intelligence about their grids but also a foundation for providing more advanced veQuids analytics in the future through the following:

  • The information foundation. Smart metering and predictive maintenance require utilities to collect not only more data but also more real-time data. Smart metering also helps break down barriers between retail and operational data sources, which in turn creates better visibility across many data sources to provide a better understanding of a complex grid.
  • The automation transition. To make the leap between Quids and veQuids requires more than just better access to more information — it also requires automation. While fully automated decision-making is still a thing of the future, many utilities are taking steps to compile and display data automatically as well as do some basic analysis, using dashboards from providers such as OSIsoft and Obvient Strategies to display high-level information customized for individual users. The user then further analyzes the data, and makes decisions and takes action based on that analysis. Many utilities today use the dashboard model to monitor critical assets based on both real-time and historical data.


As these backbone components show, utilities already have some intelligence on their grids. now, they’re building on that intelligence by leveraging existing infrastructure and resources — whether it’s voice communications providers for data transmission or Quid resources to build a foundation for the veQuids of tomorrow. In particular, utilities need to look at:

  • Scalability. Utilities need to make sure that whatever technologies they put on the grid today can grow to accommodate larger portions of the grid in future.
  • Flexibility. Given rapid technology changes in the marketplace, utilities need to make sure their technology is flexible and adaptable. For example, utilities should consider smart meters that have the ability to change out communications cards to allow for new technologies.
  • Integration. due to the evolutionary nature of the grid, and with so many intelligent grid components that must work together (intelligent sensors at substations, transformers and power lines; smart meters; and distributed and renewable energy sources), utilities need to make sure these disparate components can work with one another. Utilities need to consider how to introduce more flexibility into their intelligent grids to accommodate the increasingly complex network of devices.

As today’s utilities employ targeted efforts to build intelligence about the grid, they must keep in mind that whatever action they take today – no matter how small – must ultimately help them meet the demands of tomorrow.