Fractal Graph Framework for an Evolving Grid Architecture

Enable a new electrical grid control architecture that is decentralized and flexible, allowing increased Distributed Energy Resources (DER) (generation) AND Demand-Side Management (usage) to be managed on the last mile of the grid or the ‘grid edge’. Using autonomous distributed edge intelligence software is a radical new approach to increasing the control of DER in the grid providing real-time grid optimization. The problem to be investigated here is confirming the dynamic stability of a decentralized and autonomous system approach. The method proposed uses market-based economic principals to balance the systems competing demands including energy balance concerns (supply and demand) and engineering performance criteria. It uses a fractal grid architecture with control algorithms that are self- similar (fractal) at multiple levels of the grid. Real-time pricing signals are developed at pricing nodes and broadcast to lower edge devices that make independent, local, and real-time control decisions. In Phase 1, a new grid architecture (Fractal Grid Control) was developed and fully detailed. The design was also tested to determine how these new real-time pricing signals would enhance adoption of the technology and DER. Lastly, the project explored the development of algorithms for the edge devices, proving that edge control was feasible. The proposed project’s objective is to confirm the dynamic stability of an operational microgrid using the fractal grid architecture developed in phase I coupled with real-time pricing signals (transactive energy system) to manage the electrical grid, autonomously balance demand/supply, and keep the system engineering requirements within acceptable tolerances. The project is developed around Brunswick Landing, a former Naval Air Station run by the Midcoast Regional Redevelopment Authority. The current business park will be fully characterized from an engineering standpoint with 45 smart grid sensors as data to be fed into a three level simulation of the Fractal Grid Control architecture. This will confirm that autonomously developed real-time pricing can provide for effective, dynamically stable control of the grid from the edge. Commercialized, the new grid architecture and control algorithms enables distributed intelligence in the electrical grid while being inherently secure, reduces transmission losses, increases efficiency, optimize energy demand distribution, and makes large-scale distributed energy a reality. This project and the innovations developed in the process can also be used in managing transportation for smart cities; helping the US become more efficient.