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中央空調風系統(tǒng)節(jié)能優(yōu)化控制算法的研究

發(fā)布時間:2018-12-13 17:45
【摘要】:近年來,隨著中國對節(jié)能減排以及環(huán)保的重視,加深了人們對能源危機的認識,低碳已經(jīng)逐漸成為國家生產和人民日常生活的關鍵詞,建筑節(jié)能的主要要求是讓中央空調降低消耗,這主要是因為能源在世界范圍已經(jīng)非常短缺,且空調的使用量與日俱增。所以,,在“低碳化”的進程中,中央空調的降耗成為一個關鍵性的課題。 首先,通過閱讀大量的國內外參考文獻,本文綜述了中央空調的發(fā)展和研究現(xiàn)狀。其次,本文介紹了暖通空調系統(tǒng)尤其是空氣處理系統(tǒng)的結構與工藝原理。中央空調系統(tǒng)是先通過制冷機組產生冷(熱)源,之后通過管道將冷(熱)源送到每個空調末端以便達到制冷(熱)的目的。本文將能量守恒定律和熱傳導作為依據(jù),針對中央空調空氣處理系統(tǒng)各工作環(huán)節(jié)的能耗特點的主要工藝流程,建立了相應的空氣處理單元的數(shù)學模型,同時通過現(xiàn)有的研華控制模擬實驗平臺工控機采集到了空調房間的溫、濕度、送風量及送風風閥閥門開度的電信號等數(shù)據(jù),并運用最小二乘法建立了關于空氣處理系統(tǒng)中能耗設備(送風風機風扇、冷凍水水泵)的靜態(tài)模型。 然后根據(jù)實際中央空調空氣處理系統(tǒng)的運行特點,本文提出了空氣處理系統(tǒng)的優(yōu)化目標和約束條件。針對中央空調空氣處理單元的非線性、大滯后、多擾動的系統(tǒng)特性,本文提出一種改進的蟻群算法對其進行優(yōu)化。利用改進的蟻群算法求解中央空調空氣處理系統(tǒng)的最小功率。 本文通過改變算法中的概率選擇公式以及信息素揮發(fā)因子的表達式,克服了基本蟻群算法的容易出現(xiàn)停滯現(xiàn)象,出現(xiàn)局部最優(yōu),以及迭代次數(shù)過多的現(xiàn)象,提高了優(yōu)化算法的搜索速度和精度,為中央空調空氣處理系統(tǒng)的節(jié)能優(yōu)化提供了一種新的有效方法。 最后,本文通過實驗室中的小型中央空調系統(tǒng),對空氣處理單元的不同工況驗證改進蟻群算法的有效性,得到了令人滿意的優(yōu)化結果,充分驗證了此算法的可行性。
[Abstract]:In recent years, with the importance of energy conservation and emission reduction and environmental protection in China, people have deepened their understanding of the energy crisis. Low carbon has gradually become the key word of national production and people's daily life. The main requirement for building energy efficiency is to allow central air conditioners to reduce consumption, mainly because of the worldwide shortage of energy and the increasing use of air conditioners. Therefore, in the process of low-carbonization, the consumption reduction of central air-conditioning has become a key issue. Firstly, through reading a lot of references at home and abroad, this paper summarizes the development and research status of central air conditioning. Secondly, this paper introduces the structure and process principle of HVAC system, especially air treatment system. The central air conditioning system first produces the cold (heat) source through the refrigeration unit, then sends the cold (heat) source through the pipeline to each air conditioning end to achieve the purpose of refrigeration (heat). Based on the law of conservation of energy and heat conduction, the mathematical model of air treatment unit is established according to the main process flow of energy consumption characteristics of each working link of central air conditioning system. At the same time, the temperature, humidity, air supply volume and electrical signal of the valve opening of the air supply valve are collected by the industrial control computer, which is the simulation experiment platform of the existing Yanhua control system. The static model of energy consumption equipment (air fan, chilled water pump) in the air treatment system is established by using the least square method. Then, according to the operation characteristics of the air treatment system of central air conditioning system, the optimization goal and constraint conditions of the air processing system are put forward in this paper. An improved ant colony algorithm (ACA) is proposed to optimize the central air-conditioning air processing unit for its nonlinear, large delay and multi-disturbance characteristics. The improved ant colony algorithm is used to solve the minimum power of central air conditioning system. By changing the formula of probability selection and the expression of pheromone volatilization factor in the algorithm, this paper overcomes the phenomenon that the basic ant colony algorithm is prone to stagnation, appears local optimum, and has too many iterations. The search speed and precision of the optimization algorithm are improved, which provides a new and effective method for energy saving optimization of central air conditioning system. Finally, the effectiveness of the improved ant colony algorithm is verified by the small central air conditioning system in the laboratory, and the validity of the improved ant colony algorithm is verified by the different working conditions of the air treatment unit, and the feasibility of the algorithm is fully verified.
【學位授予單位】:沈陽工業(yè)大學
【學位級別】:碩士
【學位授予年份】:2014
【分類號】:TB657.2;TP13

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