【摘要】：作為最大的發(fā)展中國(guó)家,我國(guó)對(duì)電力的需求量巨大,并不斷增長(zhǎng)。面對(duì)日益凸顯的能源危機(jī)和環(huán)境問題,我國(guó)政府提出了一系列發(fā)展清潔低碳能源的計(jì)劃。風(fēng)能和太陽能被認(rèn)為是當(dāng)前能夠大規(guī)模開發(fā)和具有商業(yè)化發(fā)展前景的清潔能源之一,風(fēng)力發(fā)電與太陽能互補(bǔ)發(fā)電系統(tǒng)是科學(xué)利用自然資源的最新成果,研究風(fēng)電及光伏裝機(jī)容量的空間分布情況對(duì)于有效地大規(guī)模風(fēng)光電并網(wǎng)、消納,具有十分重要而緊迫的意義。從氣候角度出發(fā)評(píng)估我國(guó)的風(fēng)能及太陽能分布情況及其開發(fā)前景需要長(zhǎng)達(dá)幾十年甚至上百年的觀測(cè)數(shù)據(jù),若要進(jìn)行大規(guī)模長(zhǎng)期觀測(cè),并得到同步數(shù)據(jù)資料較為困難。因此,本文以評(píng)估我國(guó)的風(fēng)能及太陽能分布的現(xiàn)狀為研究目標(biāo),利用美國(guó)海軍耦合海洋/大氣中尺度預(yù)報(bào)系統(tǒng)COAMPS(Coupled Ocean-Atmosphere Mesoscale Prediction Sysytem)模擬我國(guó)全境一年的風(fēng)資源潛力與太陽能輻射分布, 并基于概率論原理及COAMPS輸出結(jié)果,利用計(jì)算得到的風(fēng)能及光伏輸出功率分析我國(guó)風(fēng)電及光伏輸出功率在不同時(shí)間及區(qū)域尺度下的變化規(guī)律,最后根據(jù)預(yù)估,在假設(shè)的理想情況下,分析了六大分電網(wǎng)互相并網(wǎng)下棄風(fēng)率的改善情況。主要研究成果如下：1.根據(jù)COAMPS中尺度數(shù)值模擬結(jié)果,得到了我國(guó)的風(fēng)能及太陽能資源分布區(qū)域,模擬結(jié)果顯示,我國(guó)的東南沿海、山東、遼東沿海地區(qū)屬于風(fēng)資源豐富區(qū)域,青藏高原屬于風(fēng)能資源較豐富區(qū)域,川云貴高原以及塔里木盆地西北部屬于風(fēng)資源欠佳區(qū)域。對(duì)于我國(guó)太陽能資源資源分布情況,模擬結(jié)果顯示我國(guó)寧夏北部、甘肅北部、新疆東南部、青海西部以及西藏西部太陽年輻射總量較大,屬于太陽能資源豐富區(qū)域。江蘇、安徽、湖北、浙江、四川、貴州等地區(qū)太陽年輻射總量較低,屬于太陽能資源欠佳區(qū)域。2.通過對(duì)COAMPS模擬輸出結(jié)果進(jìn)行再分析,進(jìn)一步探究風(fēng)電及光電輸出功率,結(jié)果顯示當(dāng)任意兩個(gè)選點(diǎn)之間的距離為2000km時(shí),太陽輻射能的相關(guān)系數(shù)高于0.7,當(dāng)選點(diǎn)間的距離范圍擴(kuò)大到5000kmn時(shí),太陽輻射能相關(guān)系數(shù)降低到0.4,而此時(shí)選點(diǎn)間風(fēng)速已失去相關(guān)性。當(dāng)區(qū)域尺度從200krn擴(kuò)大到800km時(shí),風(fēng)電輸出功率波動(dòng)性呈現(xiàn)出輸出平滑、波動(dòng)性下降的趨勢(shì),而光伏輸出功率每小時(shí)變化率的歷時(shí)曲線呈現(xiàn)出的平滑效應(yīng)十分有限。3.根據(jù)現(xiàn)階段我國(guó)用電水平以及國(guó)家規(guī)劃,對(duì)我國(guó)未來各分電網(wǎng)電力需求趨勢(shì)做出預(yù)測(cè)。預(yù)測(cè)結(jié)果顯示,西北電網(wǎng)的風(fēng)電容量利用率最高,為34.7%,東北電網(wǎng)與華北電網(wǎng)次之,為32%,華中地區(qū)風(fēng)電容量系數(shù)最低,為22.3%,而各個(gè)分電網(wǎng)的光伏容量利用率差異較小,在14%---17%范圍內(nèi)。同時(shí),預(yù)測(cè)結(jié)果顯示,如果將我國(guó)各大分電網(wǎng)進(jìn)行并網(wǎng),到2050年我國(guó)可以新增5%的風(fēng)電容量,整個(gè)系統(tǒng)的棄風(fēng)率將從29%下降到3%。
[Abstract]:As the largest developing country, China's demand for electricity is huge and growing. Facing the increasingly prominent energy crisis and environmental problems, our government has put forward a series of plans to develop clean and low carbon energy. Wind energy and solar energy are considered to be one of the clean energy sources which can be developed on a large scale and have the prospect of commercial development. Wind and solar complementary power generation systems are the latest achievements in the scientific utilization of natural resources. It is very important and urgent to study the spatial distribution of wind power and photovoltaic installed capacity for large-scale wind and photovoltaic grid connection and absorption. It is necessary to evaluate the distribution of wind and solar energy in China and its development prospects from the point of view of climate. It is difficult to carry out large-scale long-term observation and to obtain synchronous data. Therefore, the purpose of this paper is to evaluate the distribution of wind and solar energy in China. A coupled oceanic / atmospheric mesoscale prediction system (COAMPS (Coupled Ocean-Atmosphere Mesoscale Prediction Sysytem) is used to simulate the wind resource potential and solar radiation distribution in China for one year. Based on the probability theory and COAMPS output results, Using the calculated wind energy and photovoltaic output power to analyze the variation of wind power and photovoltaic output power in China at different time and regional scales. Finally, according to the prediction, under the hypothetical ideal condition, In this paper, the improvement of the abandonment rate of six sub-grids is analyzed. The main research results are as follows: 1. According to the results of COAMPS mesoscale numerical simulation, the distribution regions of wind and solar energy resources in China are obtained. The simulation results show that the coastal areas of southeast China, Shandong and Liaodong are rich in wind resources. The Qinghai-Tibet Plateau is rich in wind energy resources, and the Sichuan Yungui Plateau and the northwestern Tarim Basin are poor wind resources areas. For the distribution of solar energy resources in China, the simulation results show that the annual solar radiation in northern Ningxia, northern Gansu, southeastern Xinjiang, western Qinghai and western Tibet is relatively large, which belongs to the region rich in solar energy resources. Jiangsu, Anhui, Hubei, Zhejiang, Sichuan, Guizhou and other regions with low annual solar radiation, belong to the region of poor solar energy resources. 2. Through reanalysis of the COAMPS simulation output, the wind power and optoelectronic output power are further explored. The results show that when the distance between any two selected points is 2000km, the correlation coefficient of solar radiation energy is higher than 0.7. When the range of distance between the selected points is extended to 5000kmn, the correlation coefficient of solar radiation energy decreases to 0.4, but the correlation of wind speed between the selected points has been lost. When the regional scale is extended from 200krn to 800km, the fluctuation of wind power output is smooth and the fluctuation is decreasing, while the diachronic curve of photovoltaic output power per hour shows a very limited smoothing effect. According to the current level of power consumption and the national planning, the trend of power demand of each sub-grid in China is forecasted in the future. The forecast results show that the northwest power grid has the highest utilization ratio of wind capacity (34.7B), the Northeast Power Grid and North China Power Grid have the highest utilization ratio (32cm), and the central China area has the lowest wind power capacity coefficient (22.33cm). The difference of PV capacity utilization ratio between 14% and 17% is small. At the same time, the forecast results show that, if the major sub-grid of our country are connected to the grid, the wind power capacity can be increased by 5% by 2050, and the abandoned wind rate of the whole system will be reduced from 29% to 3%.
【學(xué)位授予單位】：南京信息工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TM61;P49

【參考文獻(xiàn)】

相關(guān)期刊論文 前4條

1 張宇;郭振海;張文煜;黃鶴;;中尺度模式不同分辨率下大氣多尺度特征模擬能力分析[J];大氣科學(xué);2010年03期

2 劉燕華;田茹;張東英;張旭;周繼惠;;風(fēng)電出力平滑效應(yīng)的分析與應(yīng)用[J];電網(wǎng)技術(shù);2013年04期

3 白永清;陳正洪;王明歡;成馳;;基于WRF模式輸出統(tǒng)計(jì)的逐時(shí)太陽總輻射預(yù)報(bào)初探[J];大氣科學(xué)學(xué)報(bào);2011年03期

4 李澤椿;朱蓉;何曉鳳;張德;;風(fēng)能資源評(píng)估技術(shù)方法研究[J];氣象學(xué)報(bào);2007年05期

，

本文編號(hào)：2363749