Controlling the Smart Grid
Electricity doesn’t flow like water, and the U.S. grid is leaking reliability as many more renewable resources are being added. Grid modernization is needed to continue to allow continued anticipated growth in renewable and other energy sources, according to Mark Buckner, Oak Ridge National Laboratory (ORNL), power and energy systems group leader.
Smart Grid advances
Buckner, with a doctorate in applied artificial intelligence, previously worked in the machine learning area of ORNL. He discussed opportunities and challenges of Smart Grid implementation at NIWeek 2016. Eight summarized points follow.
1. Regulations: Smart Grid advancements are occurring more slowly than some might have expected, in a regulated industry that can have different owners for distribution, transmission, and generation assets.
2. Advancements in distribution systems may happen more quickly than transmission or large generation, because as the number of control points increases, there’s a greater need for very precise control and more orchestration. As advancements become available, there’s a need to equip engineers and educate customers how to use the next killer app for energy.
3. Big Data: There’s more data than is needed to solve the problems in creating and maintaining a Smart Grid. Intelligence on edge, near where data is measured, will help. These initiatives are needed; several states have been looking at halting grid-connected renewables until grid capabilities catch up.
4. Grid modernization: Many smart people associated with the Department of Energy (DOE) Grid Modernization Initiative (GMI) have been working to upgrade our electrical infrastructure, which has served us well, but needs updates to deal with emerging threats, rapid addition of renewable generation (often in much smaller increments and in many more locations than traditional generation), extreme events, and new services.
5. Modern methods to accelerate grid research: Scrum methodologies (doing twice the work in half the time) are among the initiatives being applied to create an open framework for accelerated grid research. Prototyping platforms are looking at microgrid and nanogrid designs and connections to utilities, demo sites are being created, and accelerated testing is underway.
6. Higher visibility and management of small systems: Efforts include an additive manufacturing site with integrated energy services; a powerline conductor accelerated testing facility; nanogrid sites where electric vehicle (EV) car batteries help balance grid load with smart inverters; home generators and battery management systems; and secondary use electrical storage using collections of de-rated EV batteries.
7. Simulation to advance research: Grid simulation software provides an open framework for advanced grid research. High-speed models help with grid tuning in real time, as it now exists in the field. Capability exists to monitor small (or large) renewable (or other) generating or storage resources offline and synchronize with the grid instantaneously for smarter load balancing. IEEE Time Sensitive Networking (TSN), a variant of Ethernet under development, is being used (see photos).
8. Grid resiliency and cybersecurity: exercises are underway using machine learning, artificial intelligence, and Big Data to detect, isolate, and recover from threats.
Intelligent automation, control, and monitoring advances can help owners and users of electrical energy to think again about Smart Grid capabilities.
Mark T. Hoske, content manager, CFE Media, Control Engineering, firstname.lastname@example.org.
Learn more about IEEE Time Sensitive Networking (TSN) in this Control Engineering article.
Learn more about the Department of Energy Grid Modernization Initiative from ORNL.