By: Benjamin Kroposki, Andrey Bernstein, Jennifer King and Fei Ding
Read full article on IEEE Spectrum
Autonomous energy grids use AI, renewable energy, and energy storage to optimize the grid
It’s great to have neighbors you can depend on, whether you’re borrowing a cup of sugar or you need someone to walk your dog while you’re out of town. In the western Colorado neighborhood of Basalt Vista, the residents are even closer than most: They share their electricity. But unlike your neighbor with the sugar, the residents of Basalt Vista may not even know when they’re being generous. The energy exchanges happen automatically, behind the scenes. What residents do know is how inexpensive, reliable, and renewable their electricity is.
The 27 smart homes in Basalt Vista, located about 290 kilometers west of Denver, are part of a pilot for an altogether new approach to the power grid. The entire neighborhood is interconnected through a microgrid that in turn connects to the main grid. Within each home, every smart appliance and energy resource—such as a storage battery, water heater, or solar photovoltaic (PV) system—is controlled to maximize energy efficiency.
On a larger scale, houses within the neighborhood can rapidly share power, creating reliable electricity for everyone—solar energy generated at one house can be used to charge the electric car next door. If a wildfire were to knock out power lines in the area, residents would still have electricity generated and stored within the neighborhood. From the spring through the fall, the PV systems can provide enough electricity and recharge the batteries for days at a time. In the dead of winter, with the heat running and snow on the solar panels, the backup power will last for about 2 hours.
In theory, power systems of any size could be covered in a patchwork of Basalt Vistas, layering regions and even an entire country in smart grids to automatically manage energy production and use across millions of controllable distributed energy resources. That concept underlies the autonomous energy grid (AEG), a vision for how the future of energy can be defined by resilience and efficiency.
The concept and core technology for the autonomous energy grid are being developed by our team at the National Renewable Energy Laboratory, in Golden, Colo. Since 2018, NREL and local utility Holy Cross Energy have been putting the concept into practice, starting with the construction of the first four houses in Basalt Vista. Each home has an 8-kilowatt rooftop PV system with lithium iron phosphate storage batteries, as well as energy-efficient, all-electric heating, cooling, water heaters, and appliances. All of those assets are monitored and can be controlled by the AEG. So far, average utility bills have been about 85 percent lower than typical electric bills for Colorado.
AEGs will create at least as many benefits for utilities as they do for customers. With AEGs monitoring distributed energy resources like rooftop solar and household storage batteries, a utility’s control room will become more like a highly automated air traffic control center. The result is that energy generated within an AEG is used more efficiently—it’s either consumed immediately or stored. Over time, the operator will have to invest less in building, operating, and maintaining larger generators—including costly “peaker” plants that are used only when demand is unusually high.
But can a network as large and complicated as a national power grid really operate in a decentralized, automated way? Our research says definitely yes. Projects like the one at Basalt Vista are helping us figure out our ideas about AEGs and demonstrate them in real-world settings, and thus are playing a crucial role in defining the future of the power grid. Here’s how.
Today, grid operators must overcome two big problems. First, an ever-growing number of distributed energy resources are being connected to the grid. In the United States, for instance, residential solar installations are expected to grow approximately 8 percent per year through 2050, while household battery systems are estimated to hit almost 1.8 gigawatts by 2025, and around 18.7 million EVs could be on U.S. roads by 2030. With such anticipated growth, it’s possible that a decade from now, most U.S. electricity customers could have a handful of controllable distributed energy resources in their homes. By that math, Pacific Gas & Electric Co.’s 4 million customers in the San Francisco Bay Area could have a total of some 20 million grid-tied systems that the utility would need to manage in order to reliably and economically operate its grid. That’s in addition to maintaining the poles, wires, transformers, switches, and centralized power plants in its network.
Because of the soaring number of grid-tied devices, operators will no longer be able to use centralized control in the not-so-distant future. Over a geographically dispersed network, the communication latencies alone make a centralized system impractical. Instead, operators will have to move to a system of distributed optimization and control.
The other problem operators face is that the grid is functioning under increasingly uncertain conditions, including fluctuating wind speeds, cloud cover, and unpredictable supply and demand. Therefore, the grid’s optimal state varies every second and must be robustly determined in real time.
A centrally controlled grid can’t handle this amount of coordination. That’s where AEGs come in. The idea of an autonomous energy grid grew out of NREL’s participation in a program called NODES (Network Optimized Distributed Energy Systems) sponsored by the U.S. Department of Energy’s vanguard energy agency, ARPA-E. Our lab’s contribution to NODES was to create algorithms for a model power grid made up entirely of distributed energy resources. Our algorithms had to factor in the limited computational capabilities of many customer devices (including rooftop solar, electric vehicles, batteries, smart-home appliances, and other loads) and yet still allow those devices to communicate and self-optimize. NODES, which wrapped up last year, was successful, but only as a framework for one “cell”—that is, one community controlled by one AEG.
Our group decided to carry the NODES idea further: to extend the model to an entire grid and its many component cells, allowing the cells to communicate with one another in a hierarchical system. The generation, storage, and loads are controlled using cellular building blocks in a distributed hierarchy that optimizes both local operation and operation of the cell when it’s interconnected to a larger grid.
In our model, each AEG consists of a network of energy generation, storage, and end-use technologies. In that sense, AEGs are very similar to microgrids, which are increasingly being deployed in the United States and elsewhere in the world. But an AEG is computationally more advanced, which allows its assets to cooperate in real time to match supply to demand on second-by-second timescales. Similar to an autonomous vehicle, in which the vehicle makes local decisions about how to move around, an AEG acts as a self-driving power system, one that decides how and when to move energy. The result is that an AEG runs at high efficiency and can quickly bounce back from outages, or even avoid an outage altogether. A power grid that consists entirely of AEGs could deftly address challenges at every level, from individual customers up to the transmission system.
To develop the idea, we had to start somewhere. Basalt Vista presented an excellent opportunity to bring the AEG concept out of the lab and onto the grid. The neighborhood is designed to be net-zero energy, and it’s relatively close to NREL’s Energy Systems Integration Facility, where our group is based.
What’s more, Holy Cross Energy had been searching for a solution to manage the customer-owned energy resources and bulk generation in its system. In recent years, grid-connected, customer-owned resources have become much more affordable; Holy Cross’s grid has been seeing 10 to 15 new rooftop solar installations per week. By 2030, the utility plans to install a 150-megawatt solar-powered summer peaking system. Meanwhile, though, the utility had to deal with nonstandardized devices causing instabilities on its grid, occasional outages from severe weather and wildfires, variable generation from solar and wind energy, and an uncertain market for rooftop solar and other energy generated by its customers.
In short, what Holy Cross was facing looked very much like what other grid operators are confronting throughout the country and much of the world.
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