Building consume a large amount of energy and a plenty of methods to mine into energy consumption data to aid intelligent management are proposed. However, the data quality issues are inevitable and the influence is lack of discussion. This paper proposed a data cleaning method combing threshold and cluster method. This paper also proposed an index to evaluate the accuracy improvement on big data prediction. A case study is conducted and it is found that the accuracy of data filling is not sure to agree with the improvement of prediction after filling.
This research was funded by the National Key R&D Program of China (grant No. 2017YFC0704200) and the National Natural Science Foundation of China (grant No. 51778336). This research was also supported by Tsinghua University—Glodon Joint Research Center for Building Information Model (RCBIM).
2018.1-2021.12: Research on information-driven multi-scale performance simulation and analysis technologies for existing buildings