發(fā)布時(shí)間：2018-03-11 09:15

  本文選題：高校校園建筑能耗　切入點(diǎn)：能耗數(shù)據(jù)處理　出處：《福建師范大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著國家經(jīng)濟(jì)的迅猛發(fā)展,不斷增加的國家大型公共建筑數(shù)量及其高耗能現(xiàn)象與日益嚴(yán)重的能源短缺問題逐漸被人們所關(guān)注。高校作為社會(huì)的重要組成成員之一,擁有的大型建筑數(shù)量之多、面積之廣,使其能耗不斷攀升,遠(yuǎn)超我國的國民人均能耗消費(fèi)水平。建設(shè)節(jié)約型校園是近年來國內(nèi)眾多高校積極響應(yīng)國家建設(shè)環(huán)境友好與資源節(jié)約社會(huì)的號(hào)召而開展的工作。目前,眾多的高校都開始著手甚至已建設(shè)完成能耗管理系統(tǒng),實(shí)現(xiàn)能源實(shí)施監(jiān)管。本文的主要研究工作也將在此方面進(jìn)行展開。本文第一章首先介紹節(jié)約型校園建設(shè)的背景與意義,分析總結(jié)國內(nèi)外節(jié)約型校園建設(shè)的近況,從而引出本文的研究意義與內(nèi)容,并說明本文的組織結(jié)構(gòu)。然后第二章中,在借鑒浙江大學(xué)、北京理工大學(xué)等國內(nèi)高校節(jié)能監(jiān)管系統(tǒng)建設(shè)的經(jīng)驗(yàn)基礎(chǔ)上,提出一套適合于某大學(xué)的校園建筑能耗智控平臺(tái)解決方案,并利用物聯(lián)網(wǎng)技術(shù)、云計(jì)算技術(shù)等相關(guān)成熟技術(shù)進(jìn)行平臺(tái)構(gòu)建。文中第三章闡述校園建筑能耗統(tǒng)計(jì)分析的指標(biāo),說明校園建筑總能耗的評(píng)價(jià)指標(biāo)組成,重點(diǎn)介紹校園建筑電耗與水耗方面的統(tǒng)計(jì)指標(biāo)計(jì)算方法,并根據(jù)實(shí)際應(yīng)用提出校園建筑節(jié)能指標(biāo)。第四章將研究如何對(duì)傳感設(shè)備實(shí)時(shí)采集上傳的校園能耗數(shù)據(jù)進(jìn)行分析處理與轉(zhuǎn)存,并利用統(tǒng)計(jì)方法進(jìn)行建筑能耗統(tǒng)計(jì)、比較、排名等應(yīng)用。為了讓平臺(tái)更加的智能化,本文第五章將充分利用平臺(tái)的用能統(tǒng)計(jì)數(shù)據(jù),討論分析建筑能耗的影響因子,建立高校建筑能耗預(yù)測模型,利用智能算法預(yù)測其建筑能耗,并詳細(xì)說明該模型。第六章主要完成上述章節(jié)的測試與應(yīng)用。首先總結(jié)應(yīng)用第三、四章內(nèi)容實(shí)現(xiàn)用能統(tǒng)計(jì)。接著對(duì)第五章的模型進(jìn)行預(yù)測的實(shí)驗(yàn)測試,對(duì)比基于遺傳算法改進(jìn)的BP神經(jīng)網(wǎng)絡(luò)與普通的BP神經(jīng)網(wǎng)絡(luò)的預(yù)測結(jié)果。由分析結(jié)果可知,基于遺傳算法改進(jìn)的BP神經(jīng)網(wǎng)絡(luò)預(yù)測效果優(yōu)于未優(yōu)化的BP神經(jīng)網(wǎng)絡(luò)。實(shí)驗(yàn)測試成功后,選取某一座校園建筑對(duì)模型進(jìn)行實(shí)際應(yīng)用,用于采集該座建筑的報(bào)警數(shù)據(jù),實(shí)際應(yīng)用結(jié)果表明,該模型預(yù)測數(shù)據(jù)可相對(duì)準(zhǔn)確地應(yīng)用于平臺(tái)中。綜上,本文提出的預(yù)測模型可以正確地輔助相關(guān)規(guī)則、措施的制訂,從而為節(jié)約型校園的建設(shè)提供技術(shù)手段。
[Abstract]:With the rapid development of national economy, the increasing number of large national public buildings, the phenomenon of high energy consumption and the increasingly serious problem of energy shortage have been paid more and more attention. As one of the important members of the society, colleges and universities are becoming one of the most important members of the society. The number of large buildings and the size of their buildings have increased their energy consumption. The construction of energy-saving campus is the work of many colleges and universities in China in recent years in response to the call of the country to build an environmentally friendly and resource-conserving society. At present, Many colleges and universities have begun to build and even completed energy management systems to implement energy management. The main research work of this paper will also be carried out in this respect. Chapter one of this paper first introduces the background and significance of energy-saving campus construction. This paper analyzes and summarizes the recent situation of energy-saving campus construction at home and abroad, which leads to the significance and content of this paper, and explains the organizational structure of this paper. Then, in the second chapter, we draw lessons from Zhejiang University. Based on the experience of energy conservation supervision system construction in universities such as Beijing University of Technology, this paper puts forward a solution to the intelligent control platform of energy consumption in campus buildings suitable for a university, and utilizes the technology of the Internet of things. Cloud computing technology and other relevant mature technologies to build the platform. The third chapter describes the statistical analysis of campus building energy consumption indicators, explains the overall energy consumption of campus buildings evaluation index composition, This paper mainly introduces the calculation methods of the statistical indexes of power consumption and water consumption of campus buildings. According to the practical application, the paper puts forward the energy saving index of campus building. Chapter 4th will study how to analyze and store the campus energy consumption data collected and uploaded in real time by sensor equipment, and make use of the statistical method to calculate and compare the building energy consumption. In order to make the platform more intelligent, the 5th chapter of this paper will make full use of the platform's energy use statistics data, discuss and analyze the influence factors of building energy consumption, and establish the model of building energy consumption prediction in colleges and universities. The intelligent algorithm is used to predict the building energy consumption, and the model is described in detail. Chapter 6th mainly completes the testing and application of the above chapters. Four chapters implement energy use statistics. Then the model of chapter 5th is tested and compared with the results of the improved BP neural network based on genetic algorithm and the common BP neural network. The prediction effect of improved BP neural network based on genetic algorithm is better than that of unoptimized BP neural network. After the experiment is successful, a campus building is selected for practical application, which is used to collect the alarm data of the building. The practical application results show that the prediction data of the model can be applied to the platform relatively accurately. In summary, the prediction model presented in this paper can correctly assist the formulation of relevant rules and measures, thus providing a technical means for the construction of a conservation-oriented campus.
【學(xué)位授予單位】：福建師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TU111.195;TP18

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 汪晶;譚清巖;葉君玲;;電力網(wǎng)理論線損在線計(jì)算系統(tǒng)的研究[J];電子技術(shù)與軟件工程;2016年01期

2 劉剛;葉倩;魏慶們;周敏;;公共建筑能耗指標(biāo)值確定方法研究[J];建設(shè)科技;2015年14期

3 路闊;鐘伯成;;基于LMBP神經(jīng)網(wǎng)絡(luò)的建筑能耗預(yù)測[J];計(jì)算機(jī)技術(shù)與發(fā)展;2015年06期

4 黃世澤;郭其一;許慧;屠旭慰;;能耗管理系統(tǒng)不同數(shù)據(jù)預(yù)測模型的比較研究[J];電器與能效管理技術(shù);2014年21期

5 李瑩瑩;廖勝明;饒政華;;高層辦公建筑能耗影響因素的研究[J];建筑熱能通風(fēng)空調(diào);2013年03期

6 張碩鵬;李銳;;辦公類建筑能耗影響因素與節(jié)能潛力[J];北京建筑工程學(xué)院學(xué)報(bào);2013年01期

7 張國琦;張小潔;張興忠;;基于回歸模型的某高校能耗數(shù)據(jù)分析研究[J];科技情報(bào)開發(fā)與經(jīng)濟(jì);2012年22期

8 盧宇;吳進(jìn)營;樂仁昌;吳允平;蔡聲鎮(zhèn);鄭俊;朱麗;;基于SOA架構(gòu)的分布式異構(gòu)數(shù)據(jù)同步通信控制策略分析[J];計(jì)算機(jī)應(yīng)用;2012年05期

9 劉莉莉;段中興;;基于LonWorks技術(shù)的校園電力能耗監(jiān)控系統(tǒng)的研究與實(shí)現(xiàn)[J];現(xiàn)代電子技術(shù);2012年05期

10 韓雪;;基于物聯(lián)網(wǎng)技術(shù)的智慧校園系統(tǒng)設(shè)計(jì)研究[J];電子設(shè)計(jì)工程;2011年24期

，

本文編號(hào)：1597525