Metering, Outage Management, Smart Grid

How Distributed Intelligence is Changing Smart Grid Thinking

Issue 7 and Volume 20.

by Tim Wolf, Itron

This was a watershed year in how people used distributed intelligence in their everyday lives. For the first time, consumers more often used apps on their mobile or tablet devices than personal computers and mobile browser-based programs to access the Internet and get things done. Apps’ running at the edge of the network using the intelligence and computing power of a lower-cost and unified mobile computing platform are dominating our increasingly connected world.

The utility industry can gain insights from these trends as the next iteration of the smart grid becomes real. Just as distributed applications offer specific value to consumers, these capabilities are even more important for the interconnected power grid of tomorrow-particularly when it comes to interactivity of devices, multiple communications media, complex calculations and reporting, native functionality and robust data processing. The move to leverage distributed intelligence to improve the reliability, efficiency and flexibility of the grid is well underway.

Defining the Smart Grid of the Future

As a result of advancements in software-defined networks and communications and the affordability of increased computing power, it is possible to deploy a much more robust smart grid technology platform on the lower-voltage network. More important, for the first time, this technology enables coordinated analysis and action among diverse grid devices that wasn’t previously practical or cost-effective to solve key operational challenges. To make this vision a reality, four key technology attributes are required.

Computing power at the edge. Thanks to Moore’s law, which holds that computing power doubles every 18 months while costs drop precipitously, it it is now possible to embed the computing equivalent of a smart phone into smart meters and grid devices at a comparable price point 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.

New communications capabilities. Robust processing power in the endpoint combined with advancements in software-defined communications also have paved the way to solve critical connectivity and communication performance challenges that have frustrated utilities that are deploying single-communications networks. Communication modules combine radio frequency (RF) mesh, power line carrier (PLC) 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 so edge devices can communicate individually or with select groups of devices simultaneously to support new distributed analytics use cases.

Location awareness. 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.

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 grid devices within the network. This continuous self-awareness opens an entirely new approach to smart grid applications that simply were beyond reach before without a reliable, continually updated connectivity model.

Device interoperability at the edge. 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 distribution automation (Distributed Network Protocol or International Electrotechnical Commission (IEC) 61850), load control/demand response (Open Automated Demand Response) and home-area network (Smart Energy Profile 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.

Putting Distributed Intelligence to Use

When combined, these attributes open up an array of new possibilities that provide more efficient, practical and cost-effective solutions to grid operation challenges.

Real-time diversion detection. With current-generation smart metering technology, detecting energy theft can be a laborious exercise of analyzing historical data from disparate systems and drawing inferences about where diversion may be taking place. Diversion detection now can be based on real-time, continuous and localized analysis of changes in electricity current flows and voltage levels in the distribution network to distinguish legitimate metered loads from theft.

When current is drawn through a conductor, voltage drops in a measureable way on the network. With the meter’s ability to communicate directly with other meters and know exactly where it is located, it can identify when current is drawn on the secondary of a transformer that did not go through a meter, indicating theft. This can be done without requiring a dedicated meter at the distribution transformer.

Detection of high-impedance connections. High-impedance connections (HIC) or “hot spots” on the low-voltage distribution system represent a serious and ongoing safety risk and can cause customer voltage problems and utility energy losses. As heating continues, the connection is further degraded, and this causes the HIC to worsen. Symptoms start as voltage problems and can deteriorate to power outage, downed conductors and even fire.

Until now, there has been no practical way to identify and resolve these issues before they led to severe voltage problems or fire. By continuously calculating and monitoring impedance throughout the lower-voltage system, distributed intelligence changes the game for HIC detection. It provides a practical and cost-effective solution for utilities to identify these losses, voltage anomalies and potential safety issues before they become safety hazards or costly liabilities.

Outage detection and analysis. Like energy theft detection, the current state of outage detection 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 reach the utility where they are filtered and analyzed.

By combining locational awareness on the grid with peer-to-peer communications at the edge of the network, the 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.

Transformer load management. Overloading of distribution transformers is an increasingly common problem caused by growing loads and the emergence of distributed generation, which can overload transformers in the reverse direction.

Distributed intelligence allows the load on individual distribution transformers to be analyzed continuously and managed locally in real time.

Once meters determine that they are on the same transformer, they can communicate with each other locally and continually calculate the total load on the transformer in either direction. They also can identify locally when the transformer is approaching overload conditions, whether from the line side or customer side.

When this occurs, a distributed analytic 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 depending upon which direction power is flowing through the transformer to automatically reduce demand below allowed levels.

Conclusion

These are just a few examples of what becomes possible when intelligence extends throughout the network. As tomorrow’s smart grid becomes a reality, these distributed applications offer specific value to utilities and consumers.

By paying attention to the trends, utilities and smart metering companies might find themselves on the forefront of these new developments.


Tim Wolf is director of marketing communications at Itron. Reach him at [email protected].