RTI's Distributed Databus Shows How Grids Can Communicate in the Future
I recently wrote a couple of blogs on the changing requirements of data management in the energy industry. The first discussed how the growth of devices has come in waves, with each wave dealing with an order of magnitude increase in the number of devices. In the not too distant future, billions of distributed energy resources (DER) could be connected to a single (albeit large on a European scale) distribution network. Rigid, predefined data flows are the traditional approach to data management for the energy industry. A highly distributed future could easily break the model of centralized communication. The second blog discussed decentralized communications approaches and how the industry needs to maintain a razor-sharp focus on security.
After these blogs were published, I caught up with Erik Felt, market development director for industrial Internet of Things (IIoT)/distributed communications specialist RTI. RTI is a data distribution service (DDS) vendor, which is an open standard technology managed by the Object Management Group). DDS technology is a potential solution for companies keen to move away from traditional hub and spoke communications models for mass deployments of IIoT technologies.
A Distributed Databus Reduces the Need for Headend Systems
RTI’s genesis was in robotics, where it developed a communications system that was indifferent to the multiple operating systems in use in the 1990s. However, the business expanded into IIoT through its work with the US military to enable disparate devices to communicate without the need for a central server.
Erik Felt shares Navigant Research’s opinion that a new model is required if distribution network communications systems are to scale up to widespread DER. His pitch is that while a network operator will need visibility into DER behavior and availability, using headend systems feeding a central server is not the answer. Centralized systems can be scaled-up to incorporate DER, but this requires some heavy lifting in terms of communications networks, headend systems, and data storage. But the strategy is questionable: Is this desirable? Is it the cheapest and most secure option?
RTI’s approach is to provide integration in the field, rather than using an application programming interface (API) between different central systems, such as advanced metering infrastructure and DER management systems. In-field integration is a difficult nut to crack. A utility’s fleet of connected assets can be extremely heterogeneous ranging in age, communication protocol, multiple vendors, feeding separate systems, and data stored in siloes. DER adds additional complexity because the resources are owned by many different stakeholders. If DER is to bring benefits to the grid, a system operator must know where these assets are, their current behavior, and availability to provide services.
Distributed Databus Enables Device-To-Device Communication
RTI’s in-field integration approach is the RTI Connext Databus. It was specifically designed for IIoT, which provides access for any device to communicate with others regardless or any existing communications standard. The databus is already used at the US’s largest power generation plant, the Grand Coulee Dam, and was also selected by Duke Energy as a way for DER to communicate within some microgrids.
This databus approach—whether RTI’s or another vendor’s—appears to be a logical step to manage a highly distributed grid. Devices can communicate with other devices, distributed central processing units that process data in the field, or send specific messages back to a central data center or the cloud. However, it is a big leap for utilities to move from legacy communications infrastructure and API-based data integration. Utilities will likely progress slowly, and with good reason. Billions of devices actively communicating with each other may be a step too far for many utilities. The market may well evolve in a similar manner to RTI’s, with the databuses deployed in small, isolated projects like microgrids before they are used on the whole grid.