A Study Of Data-Driven Building Energy Analysis And Energy-Efficient Design

Sustainable development has become an important strategy for our society.Improving the energy efficiency of buildings is a critical job to achieve this ambition.In recent years,more and more building energy information datasets are being built,which makes data-driven building energy-efficient design possible.At present,there are no systematic data-driven building energy-efficient design theory and technical methods.To solve this problem,this study carried out thorough research and the main contents include:1)Based on the theory of data mining and the requirements of building energy-efficient design,the theoretical framework of data-driven building energy-efficient design is proposed.2)Used for collecting realistic building data,the building energy information model is designed.This work lays a concrete foundation for building a building energy database.3)Built a customized database with a large amount of building design data.4)Explored the determinant factors of building energy consumption;carried out advanced regression and classification learnings on predicting building energy consumption;and analyzed the impacts of building operation time and climate on the evaluation of building energy efficiency.5)Proposed and fulfilled the theory and technical solutions for data-driven building energyefficient design by applying data-mining methods.6)Implemented two case studies with the proposed data-driven building energy-efficient design methods for passive design,active design,energy-efficiency evaluation and evacuating retrofit opportunities.The proposed data-driven building energy-efficient design extends the spectrum building performance design,and makes it possible to conduct building energy analysis easily and effectively.