建筑用户行为节能潜力评估新方法
A new energy-saving potential evaluation method for building occupant behavior improvement

现有建筑用户行为节能潜力评估方法未能充分考虑不同用户之间的差异性，从而显著降低了评估结果的准确性。针对此种不足，提出一种行为节能潜力评估的新方法。通过主成分分析对用户行为影响因素进行降维处理，在此基础上，采用数据挖掘方法中的聚类分析技术对样本用户进行合理分类，并针对不同类用户特征分别进行节能潜力评估。由于该方法既全面考虑了同一用户不同因素的影响，又充分体现了不同用户之间的差异性，可显著提高评估结果的准确性。通过将其应用于湖南省3所高校100名研究生用户电脑待机行为的节能潜力评估表明，该方法有效可行。
Existing energy-saving potential evaluation methods for building occupant behavior improvement do not take occupants' diversity into consideration. This significantly decreases the accuracy of evaluation results. To address this issue, a new energy-saving potential evaluation method has been established. First, principal component analysis is used to reduce the number of influencing factors of occupant behavior. Then, a data mining technique, clustering analysis is used to classify sample occupants into different groups. At last, energy-saving potentials are evaluated in terms of different groups characteristics. This method takes both the impact of various influencing factors and the diversity of occupants into account, and thus could improve the evaluation accuracy significantly. The method was applied to evaluate the energy-saving potential of 100 graduate students' computer standby usage behavior in 3 universities in Hunan province. The results demonstrate its effectiveness and feasibility.