本文選題：分布式光伏發(fā)電系統(tǒng) + LabVIEW�。� 參考：《山東建筑大學(xué)》2017年碩士論文

【摘要】：在全球科技與經(jīng)濟(jì)發(fā)展的推動(dòng)下能源消費(fèi)需求也隨之急劇增長(zhǎng),并且伴隨著極端天氣和霧霾的頻繁出現(xiàn),傳統(tǒng)能源的弊端越來(lái)越突出,人們對(duì)低碳的追求和新能源開發(fā)利用的渴望也愈來(lái)愈強(qiáng)烈。在物質(zhì)利益與能源節(jié)約的權(quán)衡與取舍中,太陽(yáng)能憑借免輸送,零污染,無(wú)噪聲以及取之無(wú)盡、用之無(wú)絕的優(yōu)勢(shì),使其在新興能源領(lǐng)域中的地位尤為凸顯。靈活高效的分布式光伏發(fā)電系統(tǒng)是太陽(yáng)能應(yīng)用領(lǐng)域中普及面最廣的一個(gè)重要分支,但是當(dāng)其并入電網(wǎng)運(yùn)行后,光伏系統(tǒng)出力易受光能波動(dòng)性、間歇性、隨機(jī)性等影響使其成為一個(gè)不可控源,對(duì)電網(wǎng)的高效、安全、穩(wěn)定運(yùn)行帶來(lái)嚴(yán)峻挑戰(zhàn)。通過將提前預(yù)測(cè)出的光伏發(fā)電功率作為基準(zhǔn),來(lái)制定發(fā)電計(jì)劃、及時(shí)判斷系統(tǒng)運(yùn)行情況并作出相應(yīng)解決措施,是最終保障電力系統(tǒng)可靠、持久、穩(wěn)定運(yùn)行的有效舉措。本文以提高光伏發(fā)電輸出功率預(yù)測(cè)模型的精度和運(yùn)算速率為目的,在濰坊某電力科技公司的分布式光伏發(fā)電系統(tǒng)及其數(shù)據(jù)采集平臺(tái)的基礎(chǔ)上,利用LabVIEW編寫數(shù)據(jù)監(jiān)測(cè)平臺(tái)來(lái)實(shí)時(shí)顯示并保存光伏數(shù)據(jù)與氣象數(shù)據(jù)。對(duì)采集到的實(shí)驗(yàn)數(shù)據(jù)進(jìn)行分析與處理后,用改進(jìn)的IHCMAC算法搭建光伏發(fā)電輸出功率預(yù)測(cè)模型。主要研究工作如下:1.探索分析光伏發(fā)電系統(tǒng)組成結(jié)構(gòu)及特性。利用Matlab軟件搭建太陽(yáng)能光伏電池?cái)?shù)學(xué)模型,并得到其輸出特性。借助本地微型氣象站采集的氣象數(shù)據(jù)和光伏系統(tǒng)的功率數(shù)據(jù),從理論上分析光伏系統(tǒng)輸出功率與各要素的相關(guān)性關(guān)系,排除不必要因素對(duì)預(yù)測(cè)結(jié)果的干擾。2.利用LabVIEW軟件搭建分布式光伏發(fā)電系統(tǒng)監(jiān)測(cè)平臺(tái)。開發(fā)具有數(shù)據(jù)采集、顯示、預(yù)測(cè)與保存功能的監(jiān)測(cè)平臺(tái)來(lái)實(shí)時(shí)觀測(cè)光伏系統(tǒng)運(yùn)行狀態(tài)和氣象條件的變化。為便于后續(xù)預(yù)測(cè)工作直接調(diào)用,將數(shù)據(jù)保存為Excel格式。該監(jiān)測(cè)平臺(tái)預(yù)測(cè)功能模塊輸入?yún)?shù)的獲取也是通過調(diào)用已保存為Excel格式的歷史實(shí)測(cè)數(shù)據(jù)實(shí)現(xiàn)的。3.構(gòu)建實(shí)時(shí)監(jiān)測(cè)數(shù)據(jù)的分析與處理模型。借助歷史數(shù)據(jù)對(duì)光伏系統(tǒng)輸入輸出因素進(jìn)行關(guān)聯(lián)性分析,獲取預(yù)測(cè)模型的主要影響因素,并使用均值填充法、GESD算法、Z-score算法對(duì)實(shí)驗(yàn)數(shù)據(jù)進(jìn)行預(yù)處理,使得實(shí)驗(yàn)數(shù)據(jù)更加完備、準(zhǔn)確,為預(yù)測(cè)工作提供合理、可靠的數(shù)據(jù)基礎(chǔ)。4.建立分布式光伏發(fā)電功率預(yù)測(cè)模型。針對(duì)短期光伏預(yù)測(cè)中存在的計(jì)算量大預(yù)測(cè)精確度低等難題,在對(duì)現(xiàn)場(chǎng)數(shù)據(jù)進(jìn)行采集、處理與定量分析的基礎(chǔ)上,基于改進(jìn)的IHCMAC算法,提出了短期智能預(yù)測(cè)算法并對(duì)其加以改進(jìn),利用采集的氣象參數(shù)、光伏發(fā)電數(shù)據(jù),構(gòu)建了光伏發(fā)電功率預(yù)測(cè)模型,并通過性能評(píng)價(jià)驗(yàn)證了該算法的有效性。
[Abstract]:Driven by the development of global science and technology and economic development, the demand for energy consumption has also increased sharply, and with the frequent emergence of extreme weather and smog, the disadvantages of traditional energy have become more and more prominent. The pursuit of low-carbon and the desire for the development and utilization of new energy are becoming more and more intense. In the trade-off between material benefits and energy conservation, solar energy is especially prominent in the emerging energy field because of its advantages of no transportation, zero pollution, no noise and endless use. The flexible and efficient distributed photovoltaic power generation system is one of the most popular and important branches in the solar energy application field. However, when it is incorporated into the power grid, the photovoltaic system is vulnerable to the fluctuation and intermittence of light energy. The influence of randomness makes it an uncontrollable source, which brings severe challenges to the efficient, safe and stable operation of power grid. It is an effective measure to ensure the reliable, lasting and stable operation of the power system in the end by taking the photovoltaic power generation power predicted in advance as the benchmark to formulate the power generation plan, judge the operation of the system in time and make the corresponding measures to solve the problem. In order to improve the precision and calculation rate of photovoltaic output power prediction model, this paper is based on the distributed photovoltaic power generation system and its data acquisition platform of a power company in Weifang. LabVIEW is used to compile data monitoring platform to display and save photovoltaic data and meteorological data in real time. After analyzing and processing the collected experimental data, an improved IHCMAC algorithm is used to build a photovoltaic output power prediction model. The main research work is as follows: 1. To explore and analyze the structure and characteristics of photovoltaic power generation system. The mathematical model of solar photovoltaic cell is built by Matlab software, and its output characteristics are obtained. With the help of meteorological data collected by local micrometeorological station and the power data of photovoltaic system, the correlation between output power of photovoltaic system and various elements is analyzed theoretically, and the interference of unnecessary factors to forecast results is eliminated. LabVIEW software is used to build a distributed photovoltaic system monitoring platform. A monitoring platform with the functions of data acquisition, display, prediction and storage is developed to observe the changes of the operating state and meteorological conditions of photovoltaic system in real time. The data is saved in Excel format to facilitate the direct call of the subsequent prediction work. The acquisition of input parameters of the function module of the monitoring platform is also realized by calling the historical measured data saved as Excel format. The analysis and processing model of real-time monitoring data is constructed. With the help of historical data, the relationship between input and output factors of photovoltaic system is analyzed, and the main influencing factors of the prediction model are obtained, and the experimental data are preprocessed by using the mean filling GESD algorithm and Z-score algorithm, which makes the experimental data more complete. Accurate, provide reasonable and reliable data base for forecasting work. 4. A distributed photovoltaic power prediction model is established. In view of the difficult problems in short-term photovoltaic prediction, such as large amount of calculation and low precision of prediction, on the basis of collecting, processing and quantitative analysis of field data, based on the improved IHCMAC algorithm, a short-term intelligent prediction algorithm is proposed and improved. Based on the collected meteorological parameters and photovoltaic power generation data, a photovoltaic power prediction model is constructed, and the effectiveness of the algorithm is verified by performance evaluation.
【學(xué)位授予單位】：山東建筑大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM615

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