【摘要】：科學(xué)技術(shù)的發(fā)展和國民對電力需求的日益增長使得電力系統(tǒng)的規(guī)模逐漸增大,電網(wǎng)的結(jié)構(gòu)也越來越復(fù)雜,電網(wǎng)出現(xiàn)故障的幾率也隨之提高,引發(fā)的后果更加嚴(yán)重,如果不能及時(shí)的檢測出故障并且確定故障位置,將會給國民經(jīng)濟(jì)帶來巨大損失。因此,采取有效的算法對故障進(jìn)行檢測和定位,為調(diào)度中心的決策提供及時(shí)有效的輔助措施,對于保證供電可靠性,避免不必要的損失有著重要意義。廣域測量系統(tǒng)所用的采集裝置是同步相量測量單元,由于其上傳的數(shù)據(jù)為實(shí)時(shí)數(shù)據(jù),速度快并且可精確到微秒級,所以其投入和發(fā)展對于電網(wǎng)的研究起到了至關(guān)重要的作用,但目前PMU測點(diǎn)較少,而SCADA系統(tǒng)覆蓋面廣,上傳信息較全面,所以本文首先運(yùn)用粒子濾波方法通過PMU上傳的信息進(jìn)行故障檢測,若檢測出故障后,則進(jìn)一步運(yùn)用詞計(jì)算理論通過SCADA中的獲得的信息進(jìn)行故障定位。首先,研究粒子濾波的應(yīng)用原理,通過總結(jié)得出其運(yùn)用過程中有兩方面缺陷:重要性函數(shù)選取困難和粒子容易喪失多樣性。從這兩方面對粒子濾波進(jìn)行改進(jìn),通過PMU測得的數(shù)據(jù)運(yùn)用粒子濾波算法對發(fā)電機(jī)的功角進(jìn)行實(shí)時(shí)監(jiān)測,用殘差法進(jìn)行故障的檢測,當(dāng)出現(xiàn)殘差較大時(shí),判斷故障發(fā)生。其次,介紹詞計(jì)算理論的基本原理以及其優(yōu)勢,針對其實(shí)現(xiàn)過程的三個(gè)步驟中的核心步驟,利用三角模糊數(shù)實(shí)現(xiàn)模糊約束的表達(dá),并用格值自動機(jī)理論完成模糊約束的傳播,形成一種模糊的格值自動機(jī)推理方法,并總結(jié)推理步驟,在檢測出電網(wǎng)發(fā)生故障后,利用SCADA中的開關(guān)信息進(jìn)一步對故障位置進(jìn)行確定。最后,在前面研究的基礎(chǔ)上,提出基于粒子濾波和詞計(jì)算理論的電網(wǎng)故障檢測和定位的方法,總結(jié)方法步驟并給出算法流程圖,通過算例分析,驗(yàn)證本文所提出的方法的可行性和有效性。
[Abstract]:With the development of science and technology and the increasing demand for power, the scale of power system is gradually increasing, the structure of power network is becoming more and more complex, the probability of power network failure is also increasing, and the consequences are more serious. If failure can not be detected in time and fault location can be determined, it will bring huge losses to the national economy. Therefore, it is of great significance to adopt effective algorithms to detect and locate faults and to provide timely and effective auxiliary measures for decision making of dispatching center, which can ensure the reliability of power supply and avoid unnecessary losses. The acquisition device used in the wide area measurement system is the synchronous phasor measurement unit. Because the data uploaded by the system is real-time, fast and accurate to the microsecond level, its input and development have played an important role in the research of power grid. But at present, there are few PMU measurement points, and the SCADA system covers a wide area and uploads more comprehensive information. Therefore, this paper firstly uses particle filter method to detect the fault through the information uploaded by PMU, if the fault is detected, Then further use word computing theory to locate fault through the information obtained in SCADA. Firstly, the application principle of particle filter is studied, and two defects in its application are concluded: the difficulty of selecting importance function and the loss of diversity of particles. From these two aspects, the particle filter is improved, the data measured by PMU is used to monitor the power angle of generator in real time, and the residual method is used to detect the fault. When the residual error is large, the fault occurs. Secondly, the basic principle and advantages of word computing theory are introduced. According to the core steps of the three steps in the realization process, the expression of fuzzy constraints is realized by triangular fuzzy numbers, and the propagation of fuzzy constraints is accomplished by lattice valued automata theory. A fuzzy lattice-valued automata reasoning method is formed, and the reasoning steps are summarized. After detecting the fault in the power network, the fault location is further determined by using the switch information in SCADA. Finally, on the basis of the previous research, the paper puts forward the method of fault detection and location based on particle filter and word computing theory, summarizes the method steps and gives the flow chart of the algorithm. The feasibility and effectiveness of the proposed method are verified.
【學(xué)位授予單位】：東北石油大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM711;TM732

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