Framework for energy-based decision support system (DSS) for residential construction projects

多年来，加拿大寒冷的气候一直是既定能源设计要求的主要驱动因素。虽然为提供更好的室内生活条件，能源需求一直在稳步增长，但在建筑围护结构和供暖和制冷系统中使用的技术和系统方面却几乎没有相应的创新。因此，为了满足这些需求，建设项目的资本成本增加了。由于缺乏创新的框架来有效地探索建筑围护结构和加热/冷却系统的不同组合，在设计阶段，不充分的能源设计程序进一步阻碍了从业者。本研究通过将能源研究与目标成本计算技术相结合，提出了一种提高能源效率的新方法。能源评价过程基于所建议的建筑系统的直接能源影响-三级分层系统；装配系统、子装配系统和构造组件——以及它们由于系统之间可互换的相互作用而产生的间接影响。因此，将对满足客户要求和目标成本的所有可能的能源模型进行基于内部比较的能源评估，并将生成改进的能源设计以及详细的项目估算分解和项目规范的完整列表。能源因子和能源数学模型的引入，将促进根据具体项目设计探索能源模型的各种可能配置。通过利用数据挖掘技术，所开发的能源函数将自动生成一个项目所有可能的能源消耗模拟结果列表，并基于规则的分析（RBA）将选择产生最高能源效率的替代方案。最后，拟议的能源管理系统将为验证和更新已开发的teng提供所需的基础，这反过来将指导未来住宅项目的能源设计。

Over the years, Canada's cold climate has been the primary driver of the established energy design requirements. While energy demands have been steadily increasing to provide better indoor living conditions, there has been little corresponding innovation with respect to the technology and systems used in the building envelope and heating and cooling system. Thus, the capital costs of construction projects have increased in order to meet these demands. Insufficient energy design procedures have further hindered practitioners during the design stages due to the lack of an innovative framework allowing the efficient exploration of different combinations of building envelope and heating/cooling systems. This research introduces a novel solution for energy efficiency improvement by incorporating energy studies with target costing techniques. The energy evaluation process is based on the direct energy impact of the proposed construction systems-the three level hierarchical systems; assembly systems, sub-assembly systems, and construction components-and their indirect impact due to the interchangeable interactions among the systems. Consequently, an internal comparative-based energy evaluation of all possible energy models that satisfy client's requirements and target cost will be established, and improved energy design along with detailed project estimate breakdown and a full list of project specifications will be generated. The introduction of energy factors and energy mathematical models will promote the exploration of all possible configurations of energy models according to a specific project design. Through the utilization of data mining techniques, the developed energy functions will automatically generate a list of all possible simulated results of the energy consumption of a project, and the rule-based analysis (RBA) will select the alternatives that yield the highest energy efficiency. Finally, the proposed energy management system will provide the basis needed to validate and update the developed TCEng, which, in turn, will guide the energy design for future residential projects.