At current growth rates of wind and solar power, fossil fuels could be pushed out of the world’s electricity markets by the mid-2030s and replaced entirely by 2050, according to a report from the London-based non-profit Carbon Tracker. While rapid increases in renewable power generation are necessary to meet US climate goals, it raises critical concerns about power grid reliability.
The electric grid is a complex system in which grid operators must ensure power supply and demand are always balanced to avoid blackouts or other system failures. Due to environmental, seasonal and daily cycles, renewables cannot consistently produce energy throughout the day and may generate more than is needed during peak cycles. Additionally, the grid offers limited storage capacity and adjustments must be made in real-time to meet electric demand consistently and reliably. A power plant may turn off during the middle of the day, for example, to use the energy produced from solar panels in place of fossil electricity.
Ramping traditional power plants up and down to offset renewable energy is costly and inefficient, and grid operators will increasingly have to manage oversupply as renewable generation increases. Now more than ever, a highly scalable, resilient power system that can minimize the operational challenges of renewable generation is needed to meet the nation’s grid decarbonization goals.
Electrical and computer engineering assistant professor Mingxi Liu will address these challenges and improve energy security by developing a distributed framework for managing grid-edge resources to increase power system flexibility. Existing distributed frameworks have yet to address scalability issues resulting from the growing number and diversity of distributed renewable resources like rooftop and community solar panels, electric vehicles, smart thermostats. They also lack sufficient measures for protecting owners’ private information and the understanding necessary to prevent stealthy cyber-attacks that can cause long-term damage.
Liu’s project, CAREER: Scalable and Secure Control of Distributed Grid-Edge Resources for Enhanced Grid Reliability, will play a transformative role in the management of grid-edge resources by overcoming three critical challenges, scalability, privacy and cybersecurity. His Energy, Control, and Optimization (ECO) Lab will develop new optimization, machine learning, and statistical tools to maintain the balance of power supply and demand across a vast number of grid-edge users.
To ensure the highest level of privacy while still allowing central operators to manage the generation of distributed resources to improve grid reliability, Liu’s team will develop and implement cryptology-based and non-cryptology-based privacy-preserving methods. They will also leverage decentralized and distributed optimization algorithms to determine the detectability of stealthy for-purpose cyber-attacks and develop corresponding detection and mitigation strategies based on their findings. Liu’s project will make it possible to integrate an increasing amount of renewable generation into the grid in a cost-effective, secure and reliable way, and has the potential to improve other grid services.
As part of the project’s educational efforts, Liu will work with the STEM Community Alliance Program to educate Utah youth in custody about his findings and introduce them to engineering concepts. He will support the program endeavor to help students identify as science-capable learners and encourage them to pursue STEM careers.
Find out more about this project and research opportunities by visiting ECO Lab.