發(fā)布時(shí)間：2018-12-13 17:45

【摘要】：近年來(lái)，隨著中國(guó)對(duì)節(jié)能減排以及環(huán)保的重視，加深了人們對(duì)能源危機(jī)的認(rèn)識(shí)，低碳已經(jīng)逐漸成為國(guó)家生產(chǎn)和人民日常生活的關(guān)鍵詞，建筑節(jié)能的主要要求是讓中央空調(diào)降低消耗，這主要是因?yàn)槟茉丛谑澜绶秶�已�?jīng)非常短缺，且空調(diào)的使用量與日俱增。所以，，在“低碳化”的進(jìn)程中，中央空調(diào)的降耗成為一個(gè)關(guān)鍵性的課題。 首先，通過(guò)閱讀大量的國(guó)內(nèi)外參考文獻(xiàn)，本文綜述了中央空調(diào)的發(fā)展和研究現(xiàn)狀。其次，本文介紹了暖通空調(diào)系統(tǒng)尤其是空氣處理系統(tǒng)的結(jié)構(gòu)與工藝原理。中央空調(diào)系統(tǒng)是先通過(guò)制冷機(jī)組產(chǎn)生冷（熱）源，之后通過(guò)管道將冷（熱）源送到每個(gè)空調(diào)末端以便達(dá)到制冷（熱）的目的。本文將能量守恒定律和熱傳導(dǎo)作為依據(jù)，針對(duì)中央空調(diào)空氣處理系統(tǒng)各工作環(huán)節(jié)的能耗特點(diǎn)的主要工藝流程，建立了相應(yīng)的空氣處理單元的數(shù)學(xué)模型，同時(shí)通過(guò)現(xiàn)有的研華控制模擬實(shí)驗(yàn)平臺(tái)工控機(jī)采集到了空調(diào)房間的溫、濕度、送風(fēng)量及送風(fēng)風(fēng)閥閥門(mén)開(kāi)度的電信號(hào)等數(shù)據(jù)，并運(yùn)用最小二乘法建立了關(guān)于空氣處理系統(tǒng)中能耗設(shè)備（送風(fēng)風(fēng)機(jī)風(fēng)扇、冷凍水水泵）的靜態(tài)模型。 然后根據(jù)實(shí)際中央空調(diào)空氣處理系統(tǒng)的運(yùn)行特點(diǎn)，本文提出了空氣處理系統(tǒng)的優(yōu)化目標(biāo)和約束條件。針對(duì)中央空調(diào)空氣處理單元的非線性、大滯后、多擾動(dòng)的系統(tǒng)特性，本文提出一種改進(jìn)的蟻群算法對(duì)其進(jìn)行優(yōu)化。利用改進(jìn)的蟻群算法求解中央空調(diào)空氣處理系統(tǒng)的最小功率。 本文通過(guò)改變算法中的概率選擇公式以及信息素?fù)]發(fā)因子的表達(dá)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(guò)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(diào)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(guò)實(shí)驗(yàn)室中的小型中央空調(diào)系統(tǒng)，對(duì)空氣處理單元的不同工況驗(yàn)證改進(jìn)蟻群算法的有效性，得到了令人滿意的優(yōu)化結(jié)果，充分驗(yàn)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(xué)位授予單位】：沈陽(yáng)工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TB657.2;TP13

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