STTR Phase I: Distributed and Scalable Coordination of Solar Photovoltaic and Battery Storage Systems

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The broader impact/commercial potential of this project is the development and validation of technologies that enable electric energy systems to operate reliably and affordably with very large amounts of renewable energy. Clean, reliable and affordable electricity is vital to modern society. However the variability of wind and solar generation can lead to catastrophic grid reliability problems if real-time demand does not match the supply. This project will develop and demonstrate a system to manage distributed (e.g., rooftop) solar photovoltaic systems operating with and without local electrical energy storage (i.e., batteries) in a way that extracts the most value for the customer, while simultaneously improving the reliability of the electricity infrastructure. The project will leverage algorithms inspired by those used by millions of devices to send data over the Internet. Like Internet data, energy will be delivered in discrete energy packets. These packets are coordinated independently, anonymously, and fairly to simultaneously solve real-world grid problems and provide value to end-users. The result of this project will be an integrated software-as-a-service and hardware solution in which customers gain incentives for participating and electricity industry members realize savings by reducing infrastructure needs, such as additional fossil fuel generation.This Small Business Technology Transfer (STTR) Phase I project will enable the decentralized, randomized, and bottom-up coordination of two- and four-quadrant power-electronic inverters attached to solar photovoltaic and electric battery storage systems. In contrast to competing, centralized, top-down scheduling approaches, the proposed technology enables inverters to regulate both active and reactive power output according to an automaton that undergoes probabilistic state-transitions based on both real-time local measurements and communication with an aggregator. By incorporating local measurements, the method ensures that the energy needs of the end-use consumer are met while providing flexibility to a load aggregator or electric utility. This flexibility will enable distribution utilities to manage feeder power flows, losses, and voltage constraints. The probabilistic nature of the coordination prevents harmful synchronization effects, such as oscillations, while maintaining privacy of end-consumers through anonymous interactions akin to how data packets are routed on the Internet. Upon completion of the project, a commercially viable, human-friendly software-as-a-service (SaaS) technology will be demonstrated that implements this decentralized approach to coordinate distributed inverters in a manner that is compatible with modern grid operations.