Comprehensive Energy Efficiency Analysis of Buildings Based on FP-Growth Association Rules

Abstract

Energy efficiency analysis is an important basis for the establishment of a sound scientific energy saving mode and optimization operation scheme. Data mining technology is suitable to be applied in the comprehensive energy efficiency analysis because of its capability of processing large volume of data, eliminating redundant information, looking for hidden information and other unique advantages. This paper presents a comprehensive energy efficiency analysis technique based on frequent pattern growth (FP-Growth) association rules for buildings. The technique can effectively analyze the association relationship among the sub-metering data and provide support for the further development of energy saving programs. The proposed method was used in the energy efficiency analysis program of to a commercial building in Shanghai. The results prove the effectiveness and practicality of the proposed technique. 