Differential evolution - based system design optimization for net zero energy buildings under climate change

A proper system design is crucial for a net-zero energy building (NZEB) to achieve the desired performance during its lifecycle. Most conventional design methods utilize TMY (typical meteorological year) data or multi-year historical data for NZEB system sizing. Due to the climate change, future weather data may differ considerably from these utilized data. Consequently, these designs may not guarantee NZEBs to achieve the expected performance during their lifecycle. Therefore, this study proposes a differential evolution - based system design for NZEBs under climate change. Using the predicted weather data of Hong Kong (including temperature and solar radiation), the proposed system design can optimize building system sizes for minimizing its lifecycle cost with user-defined performance constraints satisfied. Three performance constraints were considered and they were thermal comfort, energy balance and grid interaction. Using the actual weather data, the proposed design has been validated by comparing with two conventional designs (i.e., TMY data-based design and multi-year historical data-based design) in an office building. The results indicated that the proposed design can achieve better performance in terms of lifecycle cost and constraints satisfaction. With improved performance, the proposed design can be used in practice for NZEB system sizing especially as climate change considered.