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3 min read

Getting Real Results with the IIC Microgrid Testbed

Getting Real Results with the IIC Microgrid Testbed

The Industrial Internet Consortium (IIC) is getting real results from its testbed program. The Microgrid Testbed project, co-led by RTI, is demonstrating the ability to power a grid with 100% renewable energy sources whereas the current grid can’t go above 40%. It’s also showing integration with cloud-based management applications that help a utility manage multiple microgrids. 

The Reason for Microgrids

Interest in solar and wind power generation continues to increase today to reduce pollution, to ensure resilience to disasters, and to save money. But existing electric power transmission and distribution systems were not designed to manage large numbers of distributed energy resources (DERs) that produce variable power like solar and wind. A solar array can lose or regain power in milliseconds with a fast-moving cloud, or the wind can suddenly drop so an alternate source has to be available and ready to pick up the load immediately. It can take up to fifteen minutes to spin up (or down) a centralized generation plant as necessary, and even longer for large-scale thermal plants. Since the supply always has to match demand for proper operation, the voltage or frequency on the grid can drop and lead to grid failure.

Microgrids cover a contained area, usually with a combination of DERs, energy storage systems, such as batteries, and some local control capability that allows the microgrid to isolate itself from the main power grid and run autonomously. They can therefore respond rapidly and locally to a loss of power. This can provide an additional 15 to 30 minutes of time for a utility to ramp up an additional generator and maintain the power.

Figure1

Figure 1. Example of microgrid that uses data communication and edge intelligence to automate local power generation and balance against the power load. Microgrids help to integrate intermittent energy sources like solar and wind.

In addition, these renewable resources generate DC power that needs to be converted to AC via an inverter. Conventional control algorithms assume there are strong voltage and frequency signals for them to follow on the main AC power line. Converting from DC to AC works just fine when most of the power is coming from traditional, spinning generators like a coal plant. But when the majority of the power is coming from DERs, the inverters’ AC-following control algorithms fail as they chase the power signals from each other. As a result, DERs cause grid instability when they constitute more than 20-40%, of the generation. This is also a particular challenge for isolated (“islanded”) microgrids – without something like a diesel generator to generate the main power signal in the microgrid, it isn’t stable.

100% Renewable Energy

Utilities are moving their proprietary communications infrastructure toward Ethernet transport and Internet Protocol (IP) or packet-based networks. This allows us to add time-sensitive networking (TSN), the latest real-time Ethernet network technology, between the inverter nodes to provide sub-millisecond synchronized measurement of phase, frequency and voltage. Instead of the traditional AC signal-following method, we used network communication to share real-time measurements of phase, frequency and voltage values. This lets us create a virtual synchronization master and address the synchronization issue. With this we could demonstrate 100% renewable energy sources in a stable microgrid.

Cloud Integration and Multiple Microgrid Management

The three key capabilities for our proposed microgrid and DERs architecture are intelligent control at the edge of the grid; peer-to-peer, high-performance communications for local autonomy; and cloud-based management integrating third-party data and analytics. We used a tiered architecture to integrate the edge, microgrid control and its real-time databus with cloud-based management, analytics and visualization.

Figure2

Figure 2: Deployed communication and control tiered architecture for microgrid and distribution grid management.

 With the backend management applications, we gather data about the operating conditions of the grid, DERs and loads. We then enhance it with third-party data, such as weather conditions, and perform intelligent analytics to estimate power generation. We also integrate with the local balancing authority for grid stability and integrate with utility back-end system to ensure full visibility and control of the operation of the grid. An integrated dashboard provides the front-end visualization for the distribution operator, micro-grid operator, and in some cases, the end-users themselves.

Figure3

Figure 3. Distribution System Operator interface provides full visibility and control of a distribution grid with DERs, controllable loads and multiple microgrids.

Now that we’ve demonstrated 100% renewables and multi-microgrid control in the lab, the next step is to work with a utility in the field. Stayed tuned for more updates.

To learn more, check out the IIC white paper, “Synchronized and Business-Ready Microgrid.”