Did you happen to see the New York Times story about TXU Energy’s free-nights-and-weekends rate plan? The Lone Star State generates 10 percent of its power from wind turbines and accounts for some 23 percent of the nation’s total wind capacity. But, since the wind comes up about the same time most people are bedding down for the night, TXU is trying to use rates to shift consumption to leverage all that inexpensive wind power it has whipping around the state.

Imagine the grid consequences of that much generation from an intermittent renewable resource. You still have to provide renewable firming, and you need to manage the power-factor conditions that are created by variable generation. Texas may be largely alone with its grid, but it isn’t alone with this problem. And the problem is likely to become much more common, as Distributed Energy Resources (DER) are being deployed with remarkable speed.

One third of new electric capacity added between 2007 and 2014 came from wind installations, and growth should continue at a fast clip for the next few years, according to research from the Lawrence Berkeley National Lab. Energy storage system deployments will go from 62 megawatts in 2014 to 220 megawatts in 2015, and 90 percent is on the utility side of the meter, says GTM research. Meanwhile, a recent report from Navigant Research predicts worldwide installations of microgrid capacity will grow from 866 megawatts in 2014 to more than 4,100 megawatts by 2020. Most of it will go online in North America.

These statistics demonstrate that DER aren’t just in our future anymore. They’re here, and they’re changing the entire landscape of utility automation systems.

With the proliferation of DER and an ever-increasing number of smart-grid components, it’s crucial that we push for greater interoperability and system awareness for equipment now populating our grid edge and distribution feeders. That’s why the Smart Grid Interoperability Panel (SGIP) has multiple initiatives underway, including one called EnergyIoT™, which takes a holistic view of utility connectivity to behind-the-meter devices, utility enterprise systems and grid operations in light of the Internet of Things (IoT). A subset of SGIP’s work is the OpenFMB™ project, which is a framework for peer-to-peer messaging for fielded devices and interconnected systems.

OpenFMB teammates from multiple utilities, power-sector vendors and research institutions reached a milestone in early November: They created and presented a live demonstration of the OpenFMB framework in operation in a simulated microgrid. The display also will be available to attendees of next year’s DistribuTECH conference slated for Feb. 9-11, 2016 in Orlando, Fla.

OpenFMB team at SGIP 2015 Annual Conference
 

Interoperability matters
Phase one of the OpenFMB working group’s activities has been focused on the interplay between multiple systems, such as those associated with microgrids and the grid as a whole or smart substations serving distribution feeders. Sure, grid automation is nothing new, but the proliferation of DER and intelligent systems is adding a new twist to it.

The exponential growth of smart substations and grid-edge devices is making centralized intelligence less necessary and centralized control unmanageable. Sending sensor and measurement data back to the control center so that some centralized system can decide what a feeder device should do won’t be the most efficient way to run the grid once it’s jam-packed with automation.

That means we need to push both intelligence and control to the distribution-system and grid-edge devices themselves. When you do that, those devices will need knowledge from other power-system devices around them. They’ll need to know about the status and other information related to power lines and equipment nearby.

Here’s an example why: Suppose you have a feeder automation device – a capacitor, a load tap changer or some other piece of equipment – and it’s connected to a bunch of smart meters at people’s houses. Those smart meters can relay voltage information from each endpoint, and the feeder automation device can help you keep voltage steady. But, there’s a problem. The way the distribution system is constructed, when you install the feeder automation device, you don’t actually know which meters you’re connected to because electro-connectivity can change when distribution switching happens.

So how does a feeder automation device make use of measurements from meters if it doesn’t know which meters it’s connected to? In order to attach meter information to feeder information, it has to go all the way back to the control center and wait for a control signal because the distribution management system or GIS has a network model.

Under that approach, if part of your communications network is degraded or overloaded due to something such as a storm, all of a sudden you have compromised the resiliency of the system as a whole. You have essentially a single point of failure – the GIS or distribution management system – if you’re always relying on such software to provide all the intelligence of the grid.

Here’s where OpenFMB comes in: We’re pushing power system information into the field so that the devices can make intelligent decisions, either individually or in cooperation with other devices. Like the DNP3 and IEC 61850 protocols that exchange device information, the OpenFMB methodology leverages common information model (CIM) messaging about the electrical network to give devices insight into the power system as a whole. Unlike previous, point-to-point communication, the OpenFMB approach uses a publish/subscribe paradigm. In this paradigm, data sources publish their information once, and every device that subscribes to that data and has permissions receives that data.

Helping the players play nice
The result of this approach is more highly defined intelligence for the many players out on a smart distribution grid, as well as a unified way of communicating across a system of interconnected sub-systems.

This was apparent in the live demonstration at SGIP’s 2015 annual conference in New Orleans early in November. There, the OpenFMB team showed different microgrid devices publishing information to the bus and all interested devices receiving that data, including the microgrid controller. Elements of the microgrid included simulated load, two generators, a solar installation and a recloser for islanding. In order for such local devices to make intelligent decisions, they need to exchange status information related to the grid and device operations. The field message bus that gives OpenFMB its name facilitates interchange of data and use of CIM-based system information.

At the end of the day, this demonstration showed that multiple vendors with disparate device types can interact and easily communicate. This opens up a number of promising developments for grid modernization efforts.

The OpenFMB approach can enable legacy equipment to be retrofitted for new capabilities and extended life with OpenFMB adapters. This allows grid devices, such as meters, relays, inverters and cap bank controllers, to speak to each other. Because it connects previously siloed domains, it facilities data integration, supports decentralized intelligence and reduces data latency issues while helping utilities manage local grids efficiently based on local resources and conditions. Bottom line: OpenFMB will help utilities put solutions right next to the problems that will hit our distribution lines as DERs proliferate.

If you attend DistribuTECH next February, be sure to see the OpenFMB demonstration for yourself. It will show you how the diverse universe of players in the smart grid can more easily interconnect. And, like TXU Energy’s nighttime electricity, it’s free.
 

About the Author

John Gillerman is a business and integration architect with in depth experience in data governance, information modeling, middleware, and process management systems. His focus is on the integration of real-time and business applications, and he brings world class experience for implementing and integrating OT systems using utility industry standards and protocols.