本文關(guān)鍵詞：分布式發(fā)電多逆變器并網(wǎng)孤島檢測技術(shù)研究　出處：《合肥工業(yè)大學》2014年博士論文　論文類型：學位論文

  更多相關(guān)文章： 分布式發(fā)電 并網(wǎng)逆變器 孤島檢測 主動移頻 小波變換 神經(jīng)網(wǎng)絡(luò)

【摘要】：由于燃料能源的不斷減少及其對環(huán)境危害的日益嚴重,人類把目光投向了太陽能、風能等清潔且儲量巨大的可再生能源,基于可再生能源的分布式發(fā)電(distributed generation, DG)技術(shù)是電力行業(yè)今后發(fā)展的一個重要方向。孤島現(xiàn)象是分布式發(fā)電系統(tǒng)的一個基本問題。所謂孤島,是指主電網(wǎng)因故障或進行檢修而處于失電狀況時,分布式發(fā)電系統(tǒng)仍可能持續(xù)工作,并與本地負載連接處于獨立運行狀態(tài)。孤島產(chǎn)生后,會威脅到電網(wǎng)維修人員的安全,影響配電系統(tǒng)的保護開關(guān)動作程序,在重合閘時可能對用電設(shè)備造成損害。因此,孤島檢測是分布式發(fā)電裝置必須具備的一種保護功能。 目前,并網(wǎng)逆變器型分布式發(fā)電系統(tǒng)的孤島檢測技術(shù)包括被動式和主動式孤島檢測兩大類,但主要是針對這兩大類檢測方法在單臺逆變器并網(wǎng)時的檢測算法與參數(shù)優(yōu)化的研究。隨著大規(guī)模分布式發(fā)電系統(tǒng)的應(yīng)用,實際上常常出現(xiàn)系統(tǒng)連接有多臺并網(wǎng)逆變器的情形,多逆變器并網(wǎng)系統(tǒng)孤島檢測技術(shù)的研究越來越受到關(guān)注。為此,本文針對分布式發(fā)電系統(tǒng)在多逆變器并網(wǎng)條件下的孤島檢測技術(shù)展開了研究,具體研究內(nèi)容如下： 首先,對基于并網(wǎng)逆變器的孤島檢測技術(shù)中與本論文課題相關(guān)的一些基本內(nèi)容展開了研究,主要包括： (1)對基于并網(wǎng)逆變器的孤島檢測方法進行了闡述,分析了被動式及主動式兩類本地孤島檢測法,重點分析了目前應(yīng)用非常廣泛的幾種主動移頻式孤島檢測法的原理及其優(yōu)缺點。 (2)分析了基于Qf×f0坐標系的孤島檢測性能評估方法,給出了主動頻率偏移法、Sandia頻率偏移法以及滑模頻率偏移法等孤島檢測方法的檢測盲區(qū)(Non-Detection Zone, NDZ)邊界曲線的求取方法。 (3)建立了分布式發(fā)電系統(tǒng)的小信號模型,采用恒電流控制策略以及APS孤島檢測法分析了帶正反饋式孤島檢測的逆變器控制策略對系統(tǒng)穩(wěn)定性的影響,從而給出了解決維護系統(tǒng)穩(wěn)定性與提高孤島檢測性能間矛盾的方法。 其次,對現(xiàn)有多逆變器并網(wǎng)條件下分布式發(fā)電系統(tǒng)的孤島檢測方法及其檢測性能進行了研究。對主動頻率偏移法、Sandia頻率偏移法以及滑模頻率偏移法這幾種主動移頻式多逆變器并網(wǎng)孤島檢測法的性能進行了理論分析與仿真驗證；對主動移頻式多逆變器并網(wǎng)孤島檢測法的檢測盲區(qū)問題與稀釋效應(yīng)問題展開了研究；對阻抗測量法、相關(guān)技術(shù)法及負序電流擾動法等多逆變器并網(wǎng)孤島檢測技術(shù)的原理及其性能進行了闡述。 針對主動移頻式多逆變器并網(wǎng)孤島檢測法的檢測盲區(qū)問題與稀釋效應(yīng)問題,提出了解決策略,即利用數(shù)字相關(guān)原理檢測公共耦合點電壓與逆變器輸出電流間的相位差角,根據(jù)檢測到的相位差角對主動移頻式孤島檢測算法中的有關(guān)參數(shù)進行自適應(yīng)調(diào)整,最后對所提策略進行了仿真與實驗驗證。為進一步降低逆變器輸出電流的畸變率,在上述孤島檢測算法改進措施的基礎(chǔ)上,提出了基于鎖相環(huán)的低電流畸變率改進SFS孤島檢測法。對于該種方法,首先分析了采用SFS法時電流畸變率的大小,詳細推算了電壓頻率有偏差及頻率無偏差兩種情況下該法所對應(yīng)的電流THD值；然后介紹了該改進SFS孤島檢測法中所使用的基于二階廣義積分器的虛擬兩相鎖相環(huán)的結(jié)構(gòu)與工作原理；最后,分析了基于鎖相環(huán)的低電流畸變率改進SFS孤島檢測法的原理、參數(shù)設(shè)置及改進方法,并給出了仿真與實驗驗證結(jié)果。 最后,研究開發(fā)了基于小波變換與神經(jīng)網(wǎng)絡(luò)的多逆變器并網(wǎng)孤島檢測法。針對該種方法,首先簡單介紹了小波變換與神經(jīng)網(wǎng)絡(luò)的基本理論；然后詳細分析了該孤島檢測方法MATLAB仿真設(shè)計的原理,給出了6種不同狀態(tài)下該孤島檢測方法在單逆變器及多逆變器并網(wǎng)條件下孤島檢測的仿真效果;最后,分析了該孤島檢測方法中小波變換Mallat算法及BP神經(jīng)網(wǎng)絡(luò)算法的DSP實現(xiàn)過程,給出了該孤島檢測法在孤島與非孤島狀態(tài)的實驗驗證結(jié)果。
[Abstract]:Because the fuel energy decreasing and its harm to the environment is becoming increasingly serious, people set their sights on solar energy, wind energy and other clean and huge reserves of renewable energy, distributed generation based on renewable energy (distributed generation DG) technology is an important direction for future development of electric power industry. The islanding phenomenon is a basic problem in distributed generation the so-called Island, refers to the main power grid due to failure or loss of power in the maintenance of the situation, the distributed power generation system is still likely to continue working, and load connections run independently and locally. The island generated, would threaten the grid maintenance personnel safety, impact protection switch action program of distribution system, in coincidence the gate may cause damage to the electrical equipment. Therefore, islanding detection is a kind of protection function of distributed generation units must have.
At present, the islanding detection technology of grid connected inverter type distributed power generation systems including passive and active islanding detection of two categories, but mainly for the detection methods of the two categories in the single inverter connected to the detection algorithm and parameter optimization research. With the application of large-scale distributed power generation systems, in fact often have more than one connection system the research of grid connected inverter, grid connected inverter system islanding detection technology has attracted more and more attention. Therefore, the islanding detection technology in multi inverter grid under the condition of the distributed power generation system is studied, the main research contents are as follows:
First of all, some basic contents related to this topic in the islanding detection technology based on grid connected inverters are studied, including:
(1) the islanding detection method based on grid connected inverter is described. The passive and active two kinds of local islanding detection methods are analyzed. The principles, advantages and disadvantages of several active frequency shift islanding detection methods are analyzed.
(2) the performance evaluation method of islanding detection based on Qf * F0 coordinate system is analyzed. The method of detecting the Non-Detection Zone (NDZ) boundary curve is given, such as the active frequency offset method, Sandia frequency shift method and sliding mode frequency shift method.
(3) establish a small signal model of the distributed generation system, the constant current control strategy and the APS analysis method for islanding detection with positive feedback inverter islanding detection effect of control strategies on the stability of the system, and gives the resolve to maintain the stability of the system and the method to improve the contradiction of the island detection performance.
Secondly, the distributed generation system under the conditions of the existing multi inverter islanding detection method and its detection performance is studied. The active frequency drift method, the performance of Sandia frequency shift method and slip mode frequency shift method the active frequency drift type multi inverter islanding detection method of theoretical analysis and simulation verification; blind detection and the problem of the dilution effect of active frequency multi inverter islanding detection method is studied; the impedance measurement method, principle and performance of related technology and method of negative sequence current perturbation method and other techniques for islanding detection of grid connected inverter are described.
According to the active frequency drift type multi inverter islanding detection method of blind spot detection problem and the dilution effect, puts forward the strategies, namely the use of digital correlation detection principle of phase voltage of the common coupling point and the output current of the inverter according to the phase difference between the angle of the detected difference angle of shift frequency parameters of active islanding detection algorithm. The adaptive adjustment, finally the strategy was proposed. The simulation and experiments to further reduce the distortion rate of the output current of the inverter, based on the improvement of islanding detection algorithm, this paper proposes an improved SFS method for islanding detection of low current distortion rate based on phase locked loop. For this method, first analyzed by SFS when the size of the current distortion rate, with the projections of the voltage and frequency deviation and frequency corresponding to the current THD method in two cases without deviation value; then introduced the improvement of S The use of FS method in islanding detection structure and two phase locked loop virtual integrator based on the principle of Nikai Hiroyoshi; finally, analyzed the principle of improved SFS islanding detection method for low current distortion rate based on PLL, setting and improvement of method parameters, and gives the simulation and experimental results.
Finally, the research and development of the multi inverter islanding detection method based on wavelet transform and neural network. According to this method, firstly introduces the basic theory of wavelet transform and neural network; then a detailed analysis of the principle of the islanding detection method of MATLAB simulation, simulation results are given for the islanding detection method under 6 different states the island in the single and multi inverter grid connected inverter under the condition of detection; finally, analysis of the islanding detection method of wavelet transform Mallat algorithm and BP neural network algorithm DSP implementation process, gives the islanding detection method in islanding and non islanding state of the experimental results.

【學位授予單位】：合肥工業(yè)大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：TM464

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