鲍里斯·萨夫科维奇,建筑智商
调节大型建筑(办公楼、医院、购物中心、赌场等)内部温度和湿度的供暖、通风和空调(暖通空调)系统约占全球总能耗的30%。暖通空调系统效率低下,造成不必要的能源浪费。这种效率低下的原因是,大多数暖通空调控制系统是被动的,没有主动地和可预测地考虑到天气模式的变化、天气预报、可变能源成本和电价以及潜在的建筑热特性,以便最佳地控制和调节建筑的内部温度和以减少总能耗。
In collaboration with the Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia’s national science agency, BuildingIQ has developed the first and only cloud-based software, employing sophisticated big data machine learning methods that continuously optimize HVAC performance in real time for minimum energy consumption, while ensuring maximum comfort for building occupants. The key advantage of this industry-leading software is that it seamlessly interfaces with current building control systems, requiring little to no capital investment for deployment within most existing building control systems. In addition to seamless integration, the software also delivers results for clients, generally achieving energy savings of 10–25% on HVAC operations, depending on the underlying building and HVAC dynamics.
本演示文稿概述了在将研发转化为实践中所遇到的问题、实现方法、实现的节能效果、面临的挑战,以及MATLAB如何®用于基本算法开发和与其他基于BuildingIQ云的系统的接口。
记录日期:2015年3月25日
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