【摘要】：在光聚熱發(fā)電中,云層作為影響輻照量的根本原因之一,其生消與移動都會對電力輸出穩(wěn)定性造成影響。因此,對鏡場范圍內(nèi)云層運動趨勢的預(yù)測是實現(xiàn)輻照功率預(yù)測的關(guān)鍵。對于中長期的輻照量變化,已可通過蓄能裝置進行相應(yīng)調(diào)節(jié)。而輻照量的突變卻會給系統(tǒng)帶來較大干擾,為消除這一影響,光聚熱發(fā)電系統(tǒng)由吸熱器溫度調(diào)控系統(tǒng)通過調(diào)節(jié)入口低溫流體流速對吸熱器溫度損失進行補償。但是此調(diào)控系統(tǒng)存在分鐘級純滯后,當(dāng)云層發(fā)生對太陽遮擋行為時,需要一定的反應(yīng)時間,而這段時間內(nèi)吸熱器出口高溫流體溫度穩(wěn)定性無法得到保證。因此,本次研究的預(yù)測系統(tǒng)可為吸熱器溫度調(diào)控系統(tǒng)提供一個前饋信號,由超短期預(yù)測結(jié)果克服調(diào)控系統(tǒng)存在的純滯后(分鐘級),當(dāng)遮擋發(fā)生時經(jīng)過一個小的波動后,吸熱器出口流體溫度可快速恢復(fù)穩(wěn)定。不同于基于歷史氣象數(shù)據(jù)與衛(wèi)星云圖的中長期預(yù)測,本次研究是基于地基云圖。通過跟蹤拍攝系統(tǒng)完成以太陽為中心的目標(biāo)圖像的獲取,在此基礎(chǔ)上結(jié)合計算機視覺技術(shù)對云層進行觀測與分析。具有實時性好、準(zhǔn)確率高的特點,能夠滿足分鐘級超短期輻照功率預(yù)測的要求。本文分別對系統(tǒng)初始化、鏡頭畸變校正、云層檢測、云層匹配、云層預(yù)測五個方面進行了系統(tǒng)的研究與驗證。本文具體的研究工作包括:(1)利用跟蹤支架、CCD相機、廣角鏡頭構(gòu)成跟蹤拍攝系統(tǒng),獲取以太陽為中心的云圖,由鏡頭中心遮光片對太陽進行遮擋。由RS485通訊協(xié)議實現(xiàn)了跟蹤支架與PC端的數(shù)據(jù)交互,通過調(diào)節(jié)相機曝光時間與信號增益實現(xiàn)曝光自動調(diào)節(jié);(2)確定了一種桶形畸變的校正模型,由多項式地址修正結(jié)合同心圓模板的校正方法,完成了廣角鏡頭桶形失真校正,取得了明顯效果;(3)提出一種先聚類再分類的云檢測思想,以此思想提出顏色特征結(jié)合K-Means聚類的云層檢測算法,并對檢測結(jié)果進行了指標(biāo)評價。相比于灰度閾值分割方法,其在檢測效果上有極大的提升;(4)利用SIFT算法與誤匹配消除方法獲得了準(zhǔn)確的匹配結(jié)果,在此基礎(chǔ)上提出一種針對于間隔1分鐘以上的大時間跨度匹配方法,可獲得數(shù)量更多的匹配點。由云層分片跟蹤方法對所有面積有效云層分別統(tǒng)計匹配點與輪廓點信息,充分體現(xiàn)云層運動狀態(tài)的獨特性;(5)根據(jù)分片跟蹤結(jié)果提出一種分級式預(yù)測模型結(jié)合粒子濾波的云預(yù)測方法,可對4分鐘以內(nèi)的云層移動進行準(zhǔn)確預(yù)測。通過所預(yù)測到的云量信息,來對應(yīng)太陽輻照量以及輻照功率的變化。
[Abstract]:In optical thermal power generation, cloud layer is one of the fundamental reasons that affect the irradiance, and its generation, elimination and movement will have an impact on the stability of power output. Therefore, the prediction of cloud motion trend in the range of mirror field is the key to realize the prediction of irradiation power. For medium and long term irradiance variation, it can be adjusted by energy storage device. However, the sudden change of irradiance will bring great interference to the system. In order to eliminate this influence, the temperature loss of the endothermic power generation system is compensated by adjusting the inlet low temperature fluid flow rate by the endothermic temperature control system. However, there is a minute stage pure lag in this control system, and a certain reaction time is needed when the clouds block the sun, and the temperature stability of the high temperature fluid at the outlet of the absorber can not be guaranteed during this period. Therefore, the prediction system can provide a feedforward signal for the temperature control system of the absorber, and overcome the pure lag (minute stage) of the control system from the ultra-short term prediction results. After a small fluctuation when the occlusion occurs, the fluid temperature at the outlet of the absorber can be quickly restored to stability. Different from the medium and long term prediction based on historical meteorological data and satellite cloud images, this study is based on foundation cloud images. The sun-centered target image is obtained by tracking and shooting system, and the cloud layer is observed and analyzed by computer vision technology. It has the characteristics of good real-time and high accuracy, and can meet the requirements of minute level ultra-short-term irradiation power prediction. In this paper, five aspects of system initialization, lens distortion correction, cloud layer detection, cloud layer matching and cloud layer prediction are systematically studied and verified. The specific research work of this paper includes: (1) using tracking bracket, CCD camera and wide-angle lens to form a tracking shooting system, the sun-centered cloud image is obtained, and the sun is obscured by the lens center shade. The data interaction between the tracking bracket and the PC end is realized by RS485 communication protocol, and the exposure automatic adjustment is realized by adjusting the exposure time and signal gain of the camera. (2) A correction model of barrel distortion is determined, and the correction method of bucket distortion of wide angle lens is completed by the correction method of multinomial address correction combined with concentric circle template, and obvious results are obtained. (3) an idea of cloud detection based on clustering and then classification is proposed, and a cloud layer detection algorithm based on color feature and K-Means clustering is proposed, and the detection results are evaluated. Compared with the gray threshold segmentation method, its detection effect is greatly improved. (4) the accurate matching results are obtained by using SIFT algorithm and error matching elimination method. On this basis, a large number of matching points can be obtained for the long time span matching method with an interval of more than one minute. According to the cloud slice tracking method, the matching point and outline point information of all areas of effective cloud layer are counted respectively, which fully reflects the uniqueness of cloud motion state. (5) according to the piecewise tracking results, a hierarchical prediction model combined with particle filter cloud prediction method is proposed, which can accurately predict the cloud movement within 4 minutes. The predicted cloud amount information is used to correspond to the variation of solar irradiance and irradiation power.
【學(xué)位授予單位】：西安理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM615

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