In the quest for carbon-neutral buildings, a team of researchers from Cornell University has made a significant stride, leveraging the power of quantum computing to optimize energy management. Akshay Ajagekar, a systems engineering expert from Cornell University, has spearheaded a study that promises to revolutionize the way we control energy consumption in buildings, potentially reshaping the energy sector’s approach to decarbonization.
The research, published in the journal *Engineering* (translated to English as “Engineering”), introduces an adaptive quantum approximate optimization-based model predictive control (MPC) strategy. This innovative approach is designed to manage energy in buildings equipped with battery energy storage and renewable energy generation systems. “Our goal was to minimize net energy consumption and promote decarbonization while reducing the computational efforts required for quantum approximate optimization algorithms,” Ajagekar explained.
The study demonstrates a remarkable 6.8% improvement in energy efficiency over deterministic MPC methods. This is no small feat, considering the complexity of managing building energy systems. The proposed strategy efficiently manages battery energy storage and renewable generation sources, leading to a substantial reduction in carbon emissions—41.2% to be precise. This is a significant step towards achieving carbon-neutral building operations, a goal that has been increasingly urgent in the face of climate change.
The implications for the energy sector are profound. As buildings account for a significant portion of global energy consumption and carbon emissions, optimizing their energy management can have a ripple effect across the entire sector. The adaptive quantum optimization-based MPC strategy could pave the way for more energy-efficient and low-carbon building operations, setting a new standard for the industry.
Moreover, the research presents opportunities for scaling to larger control problems with a significant reduction in utilized quantum computing resources. This scalability is crucial for the widespread adoption of quantum computing technologies in the energy sector. “Our approach not only improves energy efficiency and reduces carbon emissions but also makes quantum computing more accessible and practical for real-world applications,” Ajagekar noted.
The study’s findings are a testament to the potential of quantum computing in addressing complex energy management challenges. As the technology continues to evolve, we can expect to see more innovative solutions that drive the energy sector towards a sustainable future. The research by Ajagekar and his team is a significant milestone in this journey, offering a glimpse into the transformative power of quantum computing in the quest for carbon neutrality.