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住宅建筑空调使用行为的随机性和不确定性对空调能耗预测精度影响很大。如何在准确掌握空调随机使用行为特征的基础上,建立科学合理的住宅建筑空调随机使用行为模拟方法,对其空调负荷及能耗模拟具有重要意义。鉴于此,本研究利用基于主体建模的思想建立了住宅建筑空调随机使用行为的模拟方法。首先建立建筑户型、住户类型、空调数量和安装位置的对应关系,其次将居民划分为青年、中年、老年等3类,建立各类居民的在室规律、空调使用行为规则、以及不同类型居民之间空调使用的交互特征;基于主体建模的思想,利用netlogo软件建立居住建筑空调随机使用行为模拟模型。在此基础上,选取杭州市一栋典型住宅建筑进行案例应用,于2017年1月5日至1月11日,对该栋建筑内所有住户每个成员的在室行为、空调使用行为、以及所有住户的空调运行状态进行问卷调研,同时选取典型住户对室内外温度和空调运行情况进行实时监测。根据上述模拟方法对该栋建筑所有住户的空调随机使用情况进行模拟,并将模拟结果和住户空调运行情况进行校核。结果表明,该模拟方法有较好的精度保证,可用于居住建筑空调随机使用行为的模拟。
The randomness and uncertainty of air conditioning use behavior in residential buildings have a great impact on the prediction accuracy of air conditioning energy consumption. How to establish a scientific and reasonable method of random usage behavior of air conditioning in residential buildings based on the accurate understanding of the characteristics of random use of air conditioners is of great significance to the simulation of air conditioning load and energy consumption. In view of this, this study established a simulation method of stochastic behavior of residential building air conditioners based on the idea of subject modeling. First of all, establish the corresponding relationship between the type of apartment layout, the type of household, the number of air conditioners and the installation location. Secondly, divide the residents into three categories: youth, middle age and old age. Establish rules of occupancy, rules of using air conditioners and different types of residents Based on the idea of subject modeling, the use of netlogo software to establish residential buildings air conditioning random use behavior simulation model. On this basis, we select a typical residential building in Hangzhou for case application. From January 5, 2017 to January 11, 2017, we conducted a survey on the room behavior, air-conditioning use behavior of each member of all tenants in the building, and All households in the state of air conditioners conducted a questionnaire survey, at the same time select a typical household on the indoor and outdoor temperature and air conditioning running real-time monitoring. According to the simulation method above, all occupants of the building were randomly selected to simulate the air conditioners. The simulation results and the operation of the household air conditioners were checked. The results show that the simulation method has better accuracy and can be used to simulate the random behavior of air conditioning in residential buildings.