【摘要】：隨著城市建設與現(xiàn)代化的快速發(fā)展,辦公建筑越來越多,其帶來的建筑能耗也與日俱增。在辦公建筑能耗中,據(jù)統(tǒng)計中央空調(diào)系統(tǒng)的能耗占40%以上,因此,降低中央空調(diào)系統(tǒng)的運行能耗是辦公建筑節(jié)能的一個關(guān)鍵因素。文中針對西安地區(qū)某辦公建筑中央空調(diào)系統(tǒng)的負荷預測與優(yōu)化控制進行了研究,為取得更好地節(jié)能效果打下基礎。首先,分析了辦公建筑的能耗特點以及節(jié)能的重要性,突出了中央空調(diào)系統(tǒng)節(jié)能的必要性;其次,針對影響中央空調(diào)系統(tǒng)負荷的各因素進行了分析,以西安地區(qū)夏季某辦公建筑的中央空調(diào)系統(tǒng)為研究對象,利用回歸分析、最小二乘法建立該中央空調(diào)系統(tǒng)負荷預測模型,利用自適應權(quán)重粒子群算法對模型的參數(shù)進行優(yōu)化,根據(jù)該建筑內(nèi)某個空調(diào)房間一周的空調(diào)負荷數(shù)據(jù)進行模型驗證;最后,針對該辦公建筑中央空調(diào)系統(tǒng)當前PID控制方法存在調(diào)節(jié)時間長和超調(diào)量大的問題,建立變流量中央空調(diào)冷凍水系統(tǒng)數(shù)學模型,根據(jù)預測得到所需負荷來調(diào)節(jié)冷凍水的流量,采用自適應模糊PID控制的方法對冷凍水系統(tǒng)進行優(yōu)化控制。通過Simulink軟件針對PID、模糊PID和自適應模糊PID三種控制算法對冷凍水系統(tǒng)的控制效果進行仿真,對比不同算法控制效果的適用性及有效性。結(jié)果表明:文中提出的空調(diào)負荷預測方法有良好的預測精度,誤差在5%以內(nèi),能夠有效的預測該辦公建筑的中央空調(diào)系統(tǒng)負荷。對中央空調(diào)冷凍水系統(tǒng)采用自適應模糊PID控制算法,經(jīng)過仿真,超調(diào)量為4.7%,調(diào)節(jié)時間為87s,系統(tǒng)具有快速性和穩(wěn)定性,為辦公建筑中央空調(diào)系統(tǒng)的優(yōu)化控制提供了依據(jù)。
[Abstract]:With the rapid development of urban construction and modernization, more and more office buildings, the building energy consumption is also increasing. According to statistics, the energy consumption of central air conditioning system accounts for more than 40% of the energy consumption of office buildings. Therefore, reducing the energy consumption of central air conditioning system is a key factor for office buildings to save energy. In this paper, the load forecasting and optimization control of central air conditioning system in a certain office building in Xi'an area is studied, which lays a foundation for achieving better energy saving effect. Firstly, the characteristics of energy consumption and the importance of energy saving in office buildings are analyzed, and the necessity of energy saving in central air conditioning system is highlighted. Secondly, the factors affecting the load of central air conditioning system are analyzed. Taking the central air conditioning system of a certain office building in Xi'an area in summer as the research object, the load forecasting model of the central air conditioning system is established by regression analysis and least square method, and the parameters of the model are optimized by using adaptive weight particle swarm optimization algorithm. According to the air conditioning load data of one air conditioning room in the building, the model is verified. Finally, the PID control method of the central air conditioning system in the office building has the problems of long adjustment time and large overshoot. A mathematical model of variable flow central air conditioning refrigeration water system is established. According to the prediction of the required load, the flow rate of frozen water is adjusted, and an adaptive fuzzy PID control method is adopted to optimize the control of the system. The control effect of frozen water system is simulated by three control algorithms of Simulink, fuzzy PID and adaptive fuzzy PID, and the applicability and effectiveness of different algorithms are compared. The results show that the method proposed in this paper has good forecasting accuracy and the error is less than 5%, which can effectively predict the central air conditioning system load of the office building. An adaptive fuzzy PID control algorithm is applied to the central air conditioning chilled water system. The simulation results show that the overshoot is 4.7 and the adjustment time is 87 s. The system is fast and stable, which provides the basis for the optimization control of the central air conditioning system in office buildings.
【學位授予單位】：西安建筑科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TU831.2;TP273

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