本文關(guān)鍵詞：基于混合模型的中央空調(diào)能源優(yōu)化控制系統(tǒng)設(shè)計　出處：《北京交通大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

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【摘要】：在夏季隨著人們生活水平的提高,中央空調(diào)耗電量也不斷提高,中央空調(diào)耗電量占建筑物總耗電量的比例也在不斷提高。為了降低能耗,許多單位對中央空調(diào)進(jìn)行了節(jié)能改造,但仍然存在能效低下和冷量浪費(fèi)嚴(yán)重的問題。針對這些問題本文研究了基于混合模型的中央空調(diào)能源優(yōu)化控制系統(tǒng),利用混合模型能夠預(yù)測能耗和輸出冷量關(guān)系的特點(diǎn),規(guī)劃了在消耗相同能量下最合理的目標(biāo)溫度曲線解決了冷量浪費(fèi)的問題。同樣利用混合模型在實(shí)時控制中協(xié)調(diào)優(yōu)化了對空調(diào)系統(tǒng)各部分的控制,提高了空調(diào)系統(tǒng)的能效。 本文的主要工作有： 針對空調(diào)系統(tǒng)結(jié)構(gòu)復(fù)雜,控制量、能耗和輸出冷量之間關(guān)系難以預(yù)測的問題本文首先建立了帶有待定系數(shù)的中央空調(diào)系統(tǒng)灰箱模型,然后利用空調(diào)系統(tǒng)實(shí)際運(yùn)行數(shù)據(jù)對待定系數(shù)進(jìn)行辨識建立了空調(diào)系統(tǒng)物理模型。 針對物理模型精度比較差的問題,本文借助人工神經(jīng)網(wǎng)絡(luò)建立了中央空調(diào)系統(tǒng)混合模型,并對混合模型的預(yù)測效果進(jìn)行了分析。 針對基于混合模型的實(shí)時控制計算量大,系統(tǒng)快速性無法保障的問題,本文建立了基于混合模型預(yù)測的專家表,通過查表就可以實(shí)現(xiàn)對系統(tǒng)的控制。 針對傳統(tǒng)自動控制系統(tǒng)沒有對能耗的預(yù)測,無法自動優(yōu)化控制目標(biāo)值,造成能源浪費(fèi)的問題,本文設(shè)計了指定能耗下目標(biāo)溫度規(guī)劃功能,既保證了空調(diào)環(huán)境下人體的舒適度又實(shí)現(xiàn)了節(jié)能。 另外本文還對控制系統(tǒng)軟件和硬件的核心部分進(jìn)行了設(shè)計,經(jīng)過模擬分析系統(tǒng)的節(jié)能效果在20%以上。
[Abstract]:In the summer, with the improvement of living standards, the central air-conditioning power consumption is also rising, the central air-conditioning power consumption accounted for the proportion of the total power consumption of buildings is also increasing. In order to reduce the energy consumption, many units of energy-saving of central air-conditioning, but there are still low energy efficiency and cooling capacity of serious waste problem. To solve these problems this paper studies the central air-conditioning energy optimization control system based on hybrid model, using the hybrid model is able to predict the relationship between the characteristics of energy consumption and output of the cold, the temperature curve of the most reasonable planning target in consumption under the same energy to solve the cold waste problem. Using the same hybrid model coordinated optimization control of all the parts in the air conditioning system in control system, improve the energy efficiency of air conditioning system.
The main work of this article is as follows:
In the air-conditioning system with complicated structure, control volume, the relationship between energy consumption and cold output is difficult to predict the problem this paper established a grey box central air conditioning system with undetermined coefficient model, and then use the air conditioning system in actual operation data to coefficient of air conditioning system, the physical model was established for identification.
Aiming at the poor accuracy of the physical model, a hybrid model of the central air-conditioning system is built by artificial neural network, and the prediction effect of the mixed model is analyzed.
In view of the fact that the real-time control based on the hybrid model is too large for computation and the speed of the system is not guaranteed, the expert table based on the mixed model prediction is established, and the control of the system can be realized by look-up table.
Aiming at the problem that the traditional automatic control system does not predict the energy consumption, it can not automatically control the target value and cause the waste of energy. In this paper, we designed the target temperature planning function under the specified energy consumption, which not only ensured the comfort of the human body in the air conditioning environment, but also realized the energy saving.
In addition, the core part of the software and hardware of the control system is designed, and the energy saving effect of the simulation analysis system is more than 20%.

【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TB657.2;TP273

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本文編號：1421627