Data-Driven Optimal Dispatch of Integrated Energy in Zero-Carbon Building System Considering Occupant Comfort and Uncertainty

Zero-carbon emissions in building systems play a critical role in promoting energy transition and mitigating climate change, while optimal energy dispatch in highly electrified building systems is essential to achieve this goal. To address this issue, we develop an integrated energy system model for zero-carbon buildings. The carbon capture and carbon processing devices are incorporated in the system, while the uncertainty of renewable energy sources is handled by a robust optimization approach. Occupant comfort is also expressed using chance constraints to minimize energy costs. Furthermore, we propose a data-driven approach to solve the optimization problem, where uncertain parameters are clustered into subsets to construct uncertainty sets. Numerical results demonstrate that the total energy cost can be reduced by 18.87% in summer and 27.22% in winter when relaxing the occupant comfort constraints, and comparative analysis shows that the proposed approach can achieve a balance between conservativeness and computational complexity.