The Utility’s Role in IoT: Leveraging the Power of the Active Grid

By Tim Wolf, Itron

Energy and water utilities have been connecting millions of networked devices for decades. One could say that the utility industry is a pioneer and first mover in the Internet of Things (IoT). This industry knows how to connect devices and collect field and sensor data reliably and securely with standards-based networks.

But, simply moving data around will not address the challenges before us or capitalize on new opportunities. Utilities must do more than just collect reams of data for billing and back office analysis. They must be able to make decisions and take action at every level of their distribution system; optimizing analytics where it makes sense and enabling multiple applications to run edge devices to solve problems in new ways. Moving from just connecting devices to leveraging their processing power to analyze data and take action at the edge of the network, the utility industry can realize the IoT’s potential and transform the smart grid into the active grid.

Creating the Active Grid

The active grid introduces intelligent, connected devices that not only measure and communicate, but make decisions and take action in real time. Four capabilities make this possible: computing power at the edge, adaptive communications, support for multiple communication and application protocols, and locational awareness of devices.

No. 1: Computing Power at the Edge

According to Moore’s Law, computing power doubles every 18 months while the price drops by half. Thanks to computing power’s greater affordability, utilities now can embed the computing equivalent of a smart phone or desktop computer into smart meters and grid devices at a price point competitive to current single-use smart meter technologies. This enables advanced communications, high-resolution data processing and analysis in the edge device-at several hundred times the data resolution compared with five-minute interval data.

No 2: Adaptive Communications Capabilities

Robust processing power in the endpoint combined with advancements in software-defined communications also are helping solve critical connectivity and communication performance challenges that have long frustrated utilities deploying single-communications networks. Communication modules now combine radio frequency, powerline carrier and Wi-Fi communications on the same chip set. This enables dynamic and continuous selection of the optimal communications path and the most appropriate frequency modulation based on network operating conditions, data attributes and application requirements. This new platform also provides peer-to-peer and local broadcast communications capabilities, allowing grid edge devices to talk to each other individually or communicate with select groups of devices simultaneously to support new distributed analytics use cases.

No. 3: Multilingual Abilities

Robust processing power and memory also allow smart meters and grid sensors to provide a unified software and computing platform that simultaneously supports multiple communication and application protocols. Smart meters or grid devices can “speak the language” of not only smart metering, but also, for example, distribution automation (DNP3 or IEC 61850), load control/demand response (OpenADR) and home area network (SEP 1.X and 2.0, Homeplug). This communication fluency enables localized communication and coordinated action among diverse grid devices to respond to changing conditions at the edge of the network.

No. 4: Locational Awareness of Devices

Historically, the inability of smart meters to know exactly where they are on the distribution network has been the greatest obstacle to leveraging smart meter data and communication capabilities for real-time grid operations. Now, for the first time, smart meters are intuitively and continuously aware of where they are in relation to other grid assets (e.g. feeders, circuits, phases, transformers, distributed generation, other meters). This awareness is enabled by continuous monitoring and algorithmic interpretation of electrical characteristics relative to various grid devices within the network. This continuous self-awareness opens up an entirely new approach to smart grid applications that were simply beyond reach before without a reliable, continually-updated connectivity model.

Putting the Active Grid to Work

With these capabilities in place, utilities can use this distributed intelligence to solve specific business challenges that, until now, were neither practical nor affordable to solve. Core applications, including real-time diversion detection, detection of unsafe grid conditions, outage detection and analysis and transform load management, have the potential to significantly improve the return-on-investment for smart metering technology.

Diversion Detection in Real-Time

Electricity theft has a material financial impact on utilities and their customers throughout the world. While worldwide electricity theft is estimated to be in the range of 8 percent of revenues, in some regions, non-technical loss resulting from diversion (theft) represents 20 to 30 percent of revenue. That’s a huge number, but it also represents a significant opportunity to improve a utility’s financial performance.

Even with current generation smart metering technology, detecting energy theft can be an inefficient and laborious exercise of analyzing historical data from disparate systems and drawing inferences about where diversion might be taking place. With the active grid’s distributed intelligence, diversion detection can be based on real-time, continuous and localized analysis of changes in electricity current flows and voltage levels in the distribution network. This can quickly distinguish legitimate metered loads vs. those from theft.

The meter’s ability to communicate directly with other meters at different network levels, and knowing the exact location of these meters on the distribution system allows systems to identify when current did not go through a meter and is drawn on a transformer’s secondary. This ability greatly increases the accuracy and timeliness of diversion detection.

Detection of Unsafe Grid Conditions

High impedance connections (HIC) or “hot spots” on the low-voltage distribution system represent a safety risk, while also causing customer voltage problems and utility energy losses. A high impedance connection is simply a poor electrical connection that can be created when splicing, tapping or connecting wires, when foliage touches a line, or when a cable or connection fails.

When current is drawn through the high impedance connection, heating occurs and voltage drop across the connection occurs. As heating continues, the connection is further degraded, causing the HIC to worsen over time. Symptoms begin as voltage problems and can ultimately deteriorate to power outages or fires or both.

Until now, there has been no practical way to identify and resolve these issues until they lead to significant voltage problems, failure or fire.

The active grid’s distributed intelligence changes the game in HIC detection and provides a practical and cost-effective solution for utilities to identify these losses, voltage anomalies and potential safety issues before they become a safety hazard or a costly liability. This enables continuous impedance monitoring at each meter and notification of the presence and location of impedance outside of programmed thresholds or parameters.

In the event of a sudden change in impedance, as caused by failing connections or cables, this solution can send a priority message over the network to utility personnel informing them of the event and providing them with relevant data and the location of the suspected fault. Field services resources can then be dispatched quickly and precisely to correct the problem.

Outage Detection and Analysis

While current-generation smart metering technology has added a valuable data stream to the outage management equation, it is not a panacea for improving outage detection, analysis and restoration efforts. Like energy theft detection, the current state of outage detection and analysis via the smart metering network is still an inferential exercise based on how many affected meters can successfully transmit “last gasp” outage messages over the network and how many of those messages reach the utility. The filtering and analysis continues from there. This process often is still hampered by lack of an accurate connectivity model that associates meters and distribution system assets.

With the active grid, by combining locational awareness on the grid with peer-to-peer communications at the edge of the network, meters systematically and continuously evaluate the status of nearby meters and devices to quickly model and localize outage events and report reliable and actionable information back to the utility in near real time. The utility receives accurate and actionable information, including the scale and location of the outage and affected meters and transformers, in a compressed timeframe.

Transformer Load Management

Distribution transformer overloading is an increasingly common problem caused by growing loads and the emergence of distributed generation on the customer side of the meter, which can overload transformers in the reverse direction. Putting intelligence at the grid’s edge allows the load on individual distribution transformers to be analyzed continuously and managed locally in real time.

Distributed intelligence allows the load on individual distribution transformers to be analyzed continuously and managed locally in real time. Meters communicate with each other locally and continually calculate the total load on the transformer. They know when the transformer is approaching overload conditions and whether the overload is coming from the line side or customer side. When this occurs, distributed analytics running on the meters determines whether to shut off controlled loads behind the transformer, turn on or increase local distributed generation behind the transformer or take other actions to reduce loading below allowed levels.

Looking Ahead

Globally, many utilities are in a position to leverage these recent and significant advancements in distributed intelligence and analytics as they implement their grid modernization strategies. The convergence of smart grid with emerging smart cities and IoT markets is accelerating the trend toward a more distributed model and creation of the active grid. The result will be both a stronger business case for smart metering and new, highly-innovative solutions to longstanding grid operations challenges. Utilities can and will play an integral role in enabling IoT and addressing the challenges facing the utility industry and beyond.

Author Tim Wolf is the director for marketing at Itron, where he is responsible for marketing and communications for Itron’s global electricity and smart grid businesses. He is a regular presenter at industry conferences and writer in the industry trade press. He can be contacted at

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