基于SCADA數(shù)據(jù)的風(fēng)電機(jī)組發(fā)電量計(jì)算方法研究
[Abstract]:With the global attention to the problem of environmental pollution, the development of clean energy has become the focus of attention all over the world. Now all countries in the world are vigorously developing the wind power industry. The construction of wind farm tends to be stable day by day, and the economic benefit and operation evaluation of wind turbine after wind farm operation have been paid more and more attention by all walks of life. The power generation of wind turbine is an important index to evaluate the economic benefit after the operation of wind farm, so it is of great significance to improve the accuracy of power generation calculation of wind turbine. The calculation method of power generation is studied, and it is found that few people at home and abroad consider the influence of temperature on power generation. On this basis, a power generation calculation model based on temperature normalization is proposed in this paper. The most commonly used power generation calculation model is to integrate the wind speed probability density function with the power function of the wind turbine, so this paper focuses on the wind frequency function and the power curve characteristics of the wind turbine. According to the influence of temperature change on air density, it is found that the fluctuation of air density will further affect the output power of wind turbine in actual operation. In order to eliminate the reduction of temperature to the calculation of power generation, the model is proposed. In order to verify the accuracy of the calculation model based on temperature normalization, the annual power generation of four typhoon units in Dabancheng wind farm in Xinjiang is calculated by taking the historical operation SCADA data of a wind farm in Dabancheng, Xinjiang as an example. By comparing the traditional calculation method of power generation with the calculation method of temperature normalization proposed in this paper, it is found that the calculation result of power generation considering temperature is smaller than that of the traditional algorithm. The calculation results of the model are closer to the actual network power monitored by SCADA system, which verifies the accuracy of the model. Because of the influence of temperature on the power of wind turbine, the manufacturer of wind turbine should also design the control strategy combined with the characteristics of temperature fluctuation, so as to improve the economic benefit of wind farm.
【學(xué)位授予單位】:新疆大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2017
【分類號】:TM614
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 秦海巖;;依托“十三五”規(guī)劃加快新能源發(fā)展步伐[J];中國電力企業(yè)管理;2017年01期
2 戴巨川;袁賢松;劉德順;龍辛;劉旋;;基于SCADA系統(tǒng)的大型直驅(qū)式風(fēng)電機(jī)組機(jī)艙振動分析[J];太陽能學(xué)報(bào);2015年12期
3 劉麗麗;;風(fēng)電場空氣密度對風(fēng)電機(jī)組發(fā)電量影響的研究[J];風(fēng)能;2015年12期
4 韓建輝;;研究影響風(fēng)電機(jī)組實(shí)際運(yùn)行功率曲線的相關(guān)因素分析[J];科技創(chuàng)新導(dǎo)報(bào);2015年29期
5 劉景龍;袁本雄;齊偉;;環(huán)境溫度對燃機(jī)發(fā)電能力的影響分析[J];山東化工;2015年14期
6 王海云;張革榮;;風(fēng)電場選址軟件WindPRO在本科教學(xué)中的應(yīng)用[J];機(jī)電信息;2015年15期
7 姜廣緒;潘晶雯;田景奎;;雙參數(shù)威布爾分布風(fēng)況中基于k值分析的能量分布研究[J];電力建設(shè);2015年03期
8 LI Jing Hua;LI Jia Ming;WEN Jin Yu;CHENG Shi Jie;XIE Hai Lian;YUE Cheng Yan;;Generating wind power time series based on its persistence and variation characteristics[J];Science China(Technological Sciences);2014年12期
9 李慧;孫宏斌;張芳;;風(fēng)電場風(fēng)速分布模型研究綜述[J];電工電能新技術(shù);2014年08期
10 孫振軍;李紅梅;趙延軍;劉成;;低溫型風(fēng)力發(fā)電機(jī)組的研發(fā)[J];上海電氣技術(shù);2014年01期
相關(guān)會議論文 前3條
1 ;風(fēng)電機(jī)組實(shí)際運(yùn)行功率特性復(fù)雜性[A];中國農(nóng)機(jī)工業(yè)協(xié)會風(fēng)能設(shè)備分會《中小型風(fēng)能設(shè)備與應(yīng)用》(2015年第4期)[C];2015年
2 尹詩;李闖;申?duì)T;孟凱峰;包大恩;;風(fēng)電機(jī)組應(yīng)發(fā)電量的計(jì)算方法及分析比較[A];2013電力行業(yè)信息化年會論文集[C];2013年
3 游達(dá)章;;最小二乘法在威布爾分布的可靠性評估[A];武漢機(jī)械設(shè)計(jì)與傳動學(xué)會第17屆學(xué)術(shù)年會論文集[C];2009年
相關(guān)重要報(bào)紙文章 前2條
1 于歡;鐘銀燕;;2016國際能源變革論壇再結(jié)碩果[N];中國能源報(bào);2016年
2 胡佳逸;錢怡;;推動能源變革 共享綠色發(fā)展[N];蘇州日報(bào);2016年
相關(guān)碩士學(xué)位論文 前9條
1 潘險(xiǎn)險(xiǎn);基于實(shí)測運(yùn)行數(shù)據(jù)的風(fēng)電場仿真模型的研究[D];華北電力大學(xué);2015年
2 萬杰;基于SCADA數(shù)據(jù)的風(fēng)電機(jī)組運(yùn)行狀態(tài)評估方法研究[D];華北電力大學(xué);2014年
3 梁穎;基于SCADA系統(tǒng)的大型風(fēng)電機(jī)組在線狀態(tài)評估及故障定位研究[D];華僑大學(xué);2013年
4 劉峰;基于主成分—神經(jīng)網(wǎng)絡(luò)的風(fēng)電場輸出功率短期預(yù)測研究[D];華北電力大學(xué);2013年
5 楊江平;基于神經(jīng)網(wǎng)絡(luò)組合預(yù)測的風(fēng)電場風(fēng)速及發(fā)電功率短期預(yù)測[D];重慶大學(xué);2012年
6 蔡禎祺;基于數(shù)值天氣預(yù)報(bào)NWP修正的BP神經(jīng)網(wǎng)絡(luò)風(fēng)電功率短期預(yù)測研究[D];浙江大學(xué);2012年
7 劉剛;風(fēng)電場風(fēng)速及功率預(yù)測系統(tǒng)研究[D];華東交通大學(xué);2012年
8 李若昭;風(fēng)電機(jī)組綜合性能評估與運(yùn)行特性分析[D];華北電力大學(xué)(北京);2009年
9 姜廣緒;風(fēng)電場風(fēng)能資源與發(fā)電量設(shè)計(jì)后評估研究[D];華北電力大學(xué)(北京);2009年
,本文編號:2496160
本文鏈接:http://sikaile.net/kejilunwen/dianlidianqilunwen/2496160.html