Optimization of the design and operation strategies of sustainable buildings

申请人研究计划的长期目标是优化可持续建筑的设计和运营策略，最大限度地利用可再生能源，最大限度地减少生命周期对自然环境的影响，同时提供高质量的室内环境。这是一个高度原创和创新的研究项目，旨在为未来建筑的设计和运营开发知识和技术，并具有HVAC行业的应用潜力。未来五年研究活动的短期目标集中在：（1）商业和机构建筑中现有供暖，通风和空调（HVAC）系统的运行正在进行的调试，以及（2）作为HVAC系统的特殊情况，太阳能组合（SCS）的设计和运行优化。 任务1的拟议研究方法包括分析和使用现有HVAC系统的楼宇自动化系统（BAS）趋势数据，以开发新的数学模型和分析方法，并开发一个正在进行的调试原型工具，该工具集成了拟议的新开发。将开发基准模型、预测模型和虚拟传感器模型，并使用一些现有建筑物的测量结果进行测试，但目标是开发可大规模应用于其他建筑物的通用模型。对于每栋建筑物，新的训练数据集将用于确定模型参数。任务2包括SCS优化方法的改进，以及新的优化方法与详细的能量分析程序的耦合，以评估系统的性能，最后在加拿大不同地点选择最佳的SCS配置。 在第一个目标下，将进行以下任务：（1.a）HVAC系统性能基准的开发，（1.b）需求响应控制策略的电力需求预测，（1.c）HVAC系统虚拟传感器库的开发，以及（1.d）正在进行的调试和校准自动化助理的开发。在第二个目标下，将开展以下任务：（2.a）优化SCS的配置，（2.b）开发改进的优化方法。

The long-term objective of the applicant’s research program is the optimization of the design and operation strategies of sustainable buildings, which maximize the use of renewable energy sources and minimize the life cycle impacts on the natural environment, while offering high quality indoor environment. This is a highly original and innovative research program leading to the development of knowledge and technologies for the design and operation of buildings of the future, with high potential of application by the HVAC industry. The short-term objectives of research activities over the next five years focus on: (1) the ongoing commissioning for the operation of existing heating, ventilation and air conditioning (HVAC) systems in commercial and institutional buildings, and (2) the optimization of the design and operation of solar combisystem (SCS), as a particular case of HVAC systems. The proposed research approach for task 1 comprises the analysis and use of Building Auto,ation System (BAS) trend data from existing HVAC systems for the development of new mathematical models and analysis methods, and the development of an ongoing commissioning prototype tool that integrates the proposed new developments. The benchmark models, forecasting models and virtual sensor models will be developed and tested with measurements from some existing buildings, however, the goal is the development of generic models that could be applied on a large scale to other buildings. For each building, the new training data set will be used for the identification of model parameters. Task 2 covers the improvement of SCS optimization methods, and the coupling of new optimization methods with a detailed energy analysis program for assessing the systems’ performance, and finally the selection of optimum SCS configuration at different locations in Canada. Under the first objective the following tasks will be undertaken: (1.a) the development of benchmarks of the performance of HVAC systems, (1.b) the forecasting of electric demand for the demand response control strategy, (1.c) the development of a library of virtual sensors for the HVAC system, and (1.d) the development of the Automated Assistant for Ongoing Commissioning and Calibration. Under the second objective the following tasks will be undertaken: (2.a) the optimization of the configuration of SCS, and (2.b) the development of improved optimization methods.