Distributed Energy Resources

Northrop Grumman Aerospace Systems is developing a dish-shaped sunlight-concentrating hybrid solar converter that integrates high-efficiency solar cells and a thermo-acoustic engine that generates electricity directly from heat. Current solar cells lose significant amounts of energy as heat, because they do not have heat storage capability. By integrating a high-temperature solar cell and thermo-acoustic engine into a single system, thermal energy losses are minimized.

Gas Technology Institute (GTI) is developing a hybrid solar converter that focuses sunlight onto solar cells with a reflective backside mirror. These solar cells convert most visible wavelengths of sunlight to electricity while reflecting the unused wavelengths to heat a stream of flowing particles. The particles are used to store the heat for use immediately or at a later time to drive a turbine and produce electricity.

The University of Tulsa is developing a hybrid solar converter that captures ultraviolet and infrared wavelengths of light in a thermal fluid while directing visible wavelengths of light to a photovoltaic (PV) cell to produce electricity. The PV cells can be kept at moderate temperatures while high-quality heat is captured in the thermal fluid for storage and conversion into electricity when needed.

MicroLink Devices is developing a high-efficiency solar cell that can maintain efficient operation at high temperatures and leverage reusable cell templates to reduce overall cell cost. MicroLink’s cell will be able to operate at temperatures above 400°C, unlike today’s solar cells, which lose efficiency rapidly above 100°C and are likely to fail at high temperatures over time.

Over the past 50 years, progress in optical metamaterial device design has led to the manipulation of light over a wide range of wavelengths spanning the ultraviolet to the far infrared, resulting in technological advancements such as selective radiative absorbers for solar energy and daytime passive cooling using deep space. Further advances in optical metamaterial devices could enable increased energy efficiency, reduced national primary energy consumption, inexpensive long duration energy storage, and next generation solid-state heat engines.

Stanford University will develop a machine-learning enhanced framework for the design of optical communications components that will enable them to operate at their physical performance limits. Information processing and communications systems use a significant fraction of total global energy. Data centers alone consume more than 70 billion kilowatt-hours per year. Much of this energy usage is intrinsic to electronic wiring. However, optical-based technologies offer a promising option to reduce energy consumption.

Iowa State University will develop novel machine learning tools to accelerate the inverse design of new microstructures in photovoltaics. The team will create a new deep generative model called bi-directional inverse design networks to combat challenges in real-world inverse design problems. The proposed inverse design tools, if successful, will produce novel, manufacturable material microstructures with improved electromagnetic properties relative to existing technology for better, more efficient solar energy.