In 2008, the number of “things” connected to the Internet surpassed the number of people on our planet. By 2020, the number of Internet-connected things is estimated to reach 50 billion. In this age of the Internet of Things (IoT), what role do utilities play? Smart meters and smart grid technology are among these connected devices and are integral to making the IoT possible in the utility sector.
These technologies are already delivering tangible benefits to both utilities and consumers; however, while smart grid networks and devices do a fine job of moving data around today, will simply connecting devices be enough to enable the IoT tomorrow?
With increasing demands on the grid, including electric vehicles, renewable energy and distributed generation, we are moving away from a centralized generation and delivery model to a dynamic, distributed collection of “microgrids” that will need to be synchronized, monitored and maintained in real time.
Enter the active grid.
Beyond being smart, the modernized grid needs to be active, meaning it also needs to have the inherent capability to respond in real time. Today, metering and grid systems collect reams of data and make sense of it in the utility’s back office. The active grid leverages data to make real-time changes in the field. The active grid harnesses the power of the IoT to improve efficiencies and create value for both utilities and communities.
With this approach to the grid, utilities can capitalize on the potential of these connected devices that have the computing power to not only measure and communicate, but solve problems on the grid in real time. Imagine data analysis and decisions taking place where it makes the most sense – at the edge of the network rather than only in the utility back office. Imagine using devices that dynamically detect theft situations or transformer overload before it happens – improving safety, reliability and ultimately, profitability. This is true distributed intelligence.
Key Attributes of Distributed Intelligence
As a result of advancements in software-defined networks and communications, and the affordability of increased computing power, it is now possible to deploy a much more robust smart grid technology platform. More importantly, 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.
In-field Processing Power
Thanks to Moore’s Law, which holds that computing power doubles every 18 months, it is now possible to embed the computing equivalent of a smartphone 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.
Adaptive Communications Capabilities
Robust processing power in the endpoint combined with advancements in software-defined communications have also paved the way to solve critical connectivity and communication performance challenges that have long frustrated utilities deploying single-communications networks. Communication modules now combine 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 that edge devices can talk to each other individually or communicate with select groups of devices simultaneously to support new distributed analytics use cases.
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.
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 (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.
Leveraging Distributed Intelligence the ability for edge devices to know exactly where they are, process and analyze data independently and communicate with other types of devices creates many new possibilities for improving the accuracy, resolution and timeliness of analytic applications. When combined, the aforementioned technology attributes open up an array of new possibilities that provides more efficient, practical and cost-effective solutions to grid operation challenges, including realtime diversion detection, outage detection and analysis, identification of high impedance connections and transformer load management.
Real-time Diversion Detection
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 to distinguish legitimate metered loads from theft.
Outage Detection and Analysis
By combining locational awareness on the grid with peer-to-peer communications at the edge of the network, meters can 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.
Identification of High-impedance Connections
High-impedance connections (HIC) or “hot spots” on the low-voltage distribution system represent a safety risk and can cause customer voltage problems and utility energy losses. 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 a safety hazard or a costly liability.
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.
Globally, many utilities are in a position to leverage these capabilities and the significant advancements in distributed intelligence and analytics as they implement their grid modernization strategies and connect to broader opportunities beyond operational efficiency to smart cities and IoT. In the age of IoT, we must keep up with the latest technology trends and enable new IoT applications that reach beyond connections and truly bring the power of action and intelligence to field-level devices.
The convergence of smart with the emerging smart cities and IoT markets is helping accelerate this trend. Nevertheless, thresholds of innovation are reached that warrant a shift in thinking about how to approach and solve problems. For tomorrow’s grid, that time is now.
ABOUT ROBERTO AIELLO Dr. Roberto Aiello is responsible for new business innovation at Itron, including Internet of Things. His previous experience includes managing wireless research at Interval Research, Paul Allen’s technology incubator and technology transfer at Disney Research. He is an advisor to Google Advanced Technology and Projects (ATAP) and is a Lean Startup expert who serves as a mentor at the Cleantech Open and Startup Weekend. Dr. Aiello also founded two venture-funded, wireless semiconductor companies and one web/ mobile startup. Dr. Aiello worked as a physicist at Stanford Linear Accelerator Center and Superconducting Super Collider.