Optimal System Design for Net Zero Energy Buildings under Climate Change

氣候變化下零能耗建築的系統優化設計

Student thesis: Doctoral Thesis

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Award date6 Sept 2019

Abstract

Net zero energy building (NZEB) is considered as a promising solution to the increasing energy shortage and environmental problems. A proper system design is crucial for a NZEB to achieve the desired lifecycle performance. In conventional designs, the NZEB systems are sized using typical year weather data (e.g., typical meteorological year - TMY) or multi-year historical weather data. However, due to climate change, the future weather data during a NZEB lifecycle may differ considerably from these utilized data at the design stage. Consequently, these conventional designs may not be able to guarantee the NZEB to achieve their desired lifecycle performance.

Up to now, few studies have been systematically conducted to investigate the climate change and its impacts on NZEB’s lifecycle performance, and thus researchers are still unclear about NZEB actual performance under climate change. Meanwhile, with climate change impacts considered, proper measures should be taken to improve the conventionally designed NZEB’s performance. Furthermore, as climate change may have significant adverse impacts, the NZEB systems should be carefully designed for achieving the desired performance with the consideration of climate change. Therefore, this thesis intends to conduct the following works to address these raised issues.

The future weather data is prerequisite for studying the climate change and its impacts on building performance. In the first part, the method for future weather prediction is identified. Using the real future weather data, the accuracy of the identified method is validated. Then, the long-term future weather data are predicted and analyzed.

In the second part, the climate change impacts on conventionally designed NZEB’s performance are investigated in typical climate regions of China. Using the predicted future weather data, the multi-criteria performance (i.e. thermal comfort, energy balance and grid interaction) of a typical NZEB, designed using TMY weather data, is systematically assessed. The assessment results are compared and analyzed in the five typical climate regions.

In the third part, different mitigation measures are adopted to improve the conventionally designed NZEB’s performance under climate change in the diverse regions. A few representative measures are chosen for each considered performance. For instance, the renewable system size variation and free cooling utilization are adopted to improve NZEB energy balance. Then, the effectiveness of these measures is evaluated in improving the NZEB performance during its lifecycle. The evaluation results are also compared and analyzed in the five typical climate regions.

Finally, considering climate change and its impacts, a differential evolution–based NZEB system design optimization is proposed. Using the predicted future weather data, the proposed system design aims at optimizing the building system sizes for minimizing the building’s lifecycle cost with user-defined performance constraints (i.e. thermal comfort, energy balance and grid interaction). Using the real future weather data, the effectiveness of the proposed design is further validated through performance comparison with two commonly used conventional designs (i.e., TMY data-based design and multi-year historical data-based design).

The main contributions of the study can be summarized as below. First, it identifies a method that can generate reliable and accurate long-term future weather data. Then, it proposes a method to systematically evaluate the climate change impacts on NZEB lifecycle performance. Associated evaluation results will help researchers and designers recognize the significance of climate change impacts on NZEB lifecycle performance. Finally, under climate change, the study proposes a novel system design method which can minimize NZEB lifecycle cost with user-defined performance constraints.

    Research areas

  • Net zero energy building, climate change, system design optimization, lifecycle performance, multi-criteria constraints