论文标题
通过基于生理云的受控HVAC系统实现热舒适
Towards Achieving Thermal Comfort through Physiologically Cloud based controlled HVAC System
论文作者
论文摘要
共享空间中的热舒适度对于居住者的福祉至关重要，在能源消耗的管理中必不可少。室内共享空间的现有热控制系统机械地调节温度设定点，因此很难智能地实现所有人的热舒适度。最近的研究表明，由于个体偏好以及乘员无法在温度设定点上达到热折衷，共享空间中的热舒适度很难实现。本文提出了一个热舒适系统，以在共享空间中自动调整温度设定点，同时识别单个偏好。所提出的系统的控制策略基于算法，以使用单个的热偏好和预测乘员的热舒适价值来调整共享空间的温度设定点。首先确定乘员的热偏好，并用作乘员剖面的一部分，该偏好映射为根据乘员测量的生理数据和环境数据预测的热舒适值。该算法达成共识，以找到最佳的温度设定点，该温度设定点考虑了单个的热偏好及其生理反应。
Thermal comfort in shared spaces is essential to occupants well-being and necessary in the management of energy consumption. Existing thermal control systems for indoor shared spaces adjust temperature set points mechanically, making it difficult to intelligently achieve thermal comfort for all. Recent studies have shown that thermal comfort in a shared space is difficult to achieve due to individual preferences and the inability of occupants to reach a thermal compromise on temperature set points. This paper proposes a thermal comfort system to automatically adjust the temperature set-points in a shared space whilst recognising individual preferences. The control strategy of the proposed system is based on an algorithm to adjust the temperature set point of the shared space using the individual thermal preferences and predicted thermal comfort value of the occupants. The thermal preferences of the occupants are determined first and used as part of the occupants profile, which is mapped to thermal comfort values predicted from the occupants measured physiological data and environmental data. A consensus is reached by the algorithm to find the optimal temperature set-point, which takes into account individual thermal preferences and their physiological responses.
