The operations of the power grid, the components that make up the power grid, and the entities that connect to the power grid must evolve to support a more sustainable, resilient, and carbon-aware future while at the same time, meeting the growing electrical power demands of our society. In order to achieve these goals, IEE’s research programs in Smart Societal Infrastructure are exploring a variety of approaches to improving the grid, the components of the grid, and the interplay of the grid with the wide variety of societal systems that attach to the grid (e.g., commercial and industrial buildings, homes, transportation systems, lighting, electric vehicle charging systems, data centers, etc.)
Grand Challenge
To develop an economically viable building system with zero net energy.
Buildings consume 72% of U.S. electricity and 40% of all U.S. energy. Getting buildings to zero net energy will dramatically reduce U.S. energy use – but getting there will take more than upgrading windows and insulation.
Institute researchers are developing smart building energy management systems to accelerate the transition to zero net energy buildings. Our overarching goal is to develop optimized control systems that will operate buildings at peak comfort and efficiency levels by automatically controlling HVAC, lighting and shading in smart and robust ways. IEE has a long history of innovation in this arena including inventing and licensing learning technologies and software that have already dramatically improved the energy efficiency of over 50 Million square feet of commercial and industrial buildings worldwide.
Grand Challenge
Enable 50% renewable energy integration by 2030 and 100% by 2050.
An often overlooked, but equally important, advantage of quantum computing technologies is their energy footprint compared to classical machines. With their exponential improvement in computational power, quantum computers are already capable of performing specialized tasks in a fraction of the time required for a supercomputer with a fraction of the energy usage. As quantum systems begin to expand beyond the noisy intermediate-scale quantum (NISQ) era, increasing the complexity and scale while maintaining a low energy footprint will require reducing large, table-top experiments to chip-scale technologies.
IEE’s researchers are building photonic and microelectronic integrated hardware and full-stack software to solve some of the most difficult quantum engineering problems. These efforts include developing integrated photonic quantum computers using ultra-efficient photonic materials, heterogeneous integration of lasers and single-photon detectors with silicon photonics, interfacing atomic quantum systems onto photonic chips, and creating energy-efficient programming frameworks for emerging quantum computing technologies.
SUCCESS STORY
Unite to Light
Purpose-Built Solar Reading Light Designed at UC Santa Barbara.
Research Highlights
Towards Grid-Scale Energy Storage for Renewable Energy Professors Rapahaele Clement and Gabriel Menard - A novel energy storage solution for the smart grid, a photoactive redox flow battery. Improving the performance declines in rechargeable Lithium batteries. Towards safer rechargeable batteries and fuel cells. Improved battery materials for life-cycle/recycling. Professor Phillip Christopher Efficient, environmentally friendly chemical processes via novel catalytic materials. Professor Philip Lubin Alternative energy storage technologies.
Demand Response and Renewable Energy Integration Professor Mahnoosh Alizadeh - Electricity demand has historically been left completely out of power system operations, which could prove unsustainable under high levels of renewable energy integration. Demand response programs aim to make demand more elastic and shift it to times and locations where supply is abundant. To achieve this goal, we need to re-imagine the end-use experience of electricity delivery services and how we operate electricity markets.
Electric Transportation Systems Professor Mahnoosh Alizadeh - The design and testing of real-time optimization and network control algorithms for mobility-aware smart charging that allow power and transportation networks to cooperatively minimize the carbon footprint of EVs.
Learning Algorithms to Improve Energy Efficiency in Existing Buildings Professor Igor Mezic - Learning algorithms invented by Professor Mezic and instantiated in his startup EcoRithm’s software manage energy usage in over 50 Million square feet of commercial buildings worldwide.
Smart Lighting – Solid State Lighting & Energy Electronics Center (SSLEEC) Professors Steve DenBaars and Shuji Nakamura - New electronics for energy efficient lighting – best known for making bright and white light LEDs practical via the co-invention of the Blue Laser (2014 Nobel Prize for Professor Nakamura). The shift to LED lighting is projected to save ~200 of millions of tons of CO2 footprint by 2030.
