IoT for energy and water: Utilities’ role in the internet of things
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. 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. Utilities know how to connect devices and collect field and sensor data reliably and securely with standards-based networks. In the age of IoT, utilities have an opportunity to drive a real shift in how they engage with consumers to enable smarter communities, propel local economic development and better manage energy and water.
But, simply moving data around will not address all of the challenges they face or capitalize on new opportunities. With increasing demands on the electricity grid — including electric vehicles, renewable energy and distributed generation — utilities are moving away from a centralized generation and delivery model to a dynamic, distributed collection of “micro-grids” that will need to be synchronized, monitored and maintained in real time.
Enter the “active grid.” With the active grid, devices not only measure and communicate, but also make decisions and take action in real time. Yesterday, field devices like meters collected reams of data and made sense of it in the utility’s back office. Today, the active grid leverages distributed intelligence by analyzing data in the field to make real-time command and control decisions. It harnesses the power of IoT to improve efficiencies and create value for both energy and water management and smart cities. Imagine using devices that dynamically manage the electric grid — 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 robust IoT technology platform. More importantly, for the first time, technology enables coordinated analysis and action among diverse field devices that wasn’t previously practical or cost-effective to solve key operational challenges.
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 field devices like utility meters, pushing intelligence to the edge. This enables advanced communications, high-resolution data processing and analysis in the edge device.
Assured connectivity capabilities
To ensure network reliability, today’s utilities need adaptive communication technologies, which combine RF mesh, power line carrier and Wi-Fi communications on the same chip set. This unique innovation 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.
Locational awareness
Now, for the first time, smart field devices are intuitively and continuously aware of where they are in relation to other field assets (e.g., electricity feeders, circuits, phases, transformers, distributed generation and meters). This awareness is enabled by continuous monitoring and algorithmic interpretation of electrical characteristics relative to various grid devices within the network.
Multilingual abilities
Robust processing power and memory allow field sensors and smart meters to provide a unified software and computing platform that simultaneously supports multiple communication and application protocols. Field devices can “speak the language” of not only smart meters, distribution automation devices , load control/ demand response (OpenADR) and home area network (SEP 1.X and 2.0, Homeplug).
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. Here are examples how distributed intelligence is revolutionizing electricity management:
Real-time diversion detection
Diversion detection or theft is determined by 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, smart 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.
Identification of high-impedance connections
High-impedance connections (HIC) or “hot spots” on the low-voltage distribution system are a safety risk and can cause customer voltage problems and utility energy losses. Continuously calculating and monitoring impedance throughout the lower voltage system 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.
