本文關(guān)鍵詞：電力系統(tǒng)分布式動(dòng)態(tài)狀態(tài)估計(jì)研究　出處：《華北電力大學(xué)》2014年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 機(jī)電暫態(tài) 狀態(tài)估計(jì) 卡爾曼濾波 零阻抗特性 機(jī)網(wǎng)接口

【摘要】：同步相量測(cè)量單元(phasor measurement unit, PMU)能夠?qū)﹄娏ο到y(tǒng)機(jī)電暫態(tài)過程中相量信息進(jìn)行直接測(cè)量,為電力系統(tǒng)動(dòng)態(tài)安全監(jiān)控提供了新的技術(shù)手段。然而,由于傳感器誤差以及干擾的影響,PMU量測(cè)不可避免地存在隨機(jī)誤差和不良數(shù)據(jù)。如果不對(duì)PMU量測(cè)量進(jìn)行處理而直接應(yīng)用,則有可能無法準(zhǔn)確監(jiān)測(cè)電力系統(tǒng)動(dòng)態(tài)過程,甚至導(dǎo)致控制系統(tǒng)做出錯(cuò)誤的控制策略。針對(duì)PMU量測(cè)信息,本文系統(tǒng)地研究了機(jī)電暫態(tài)過程中分布式動(dòng)態(tài)狀態(tài)估計(jì)方法。論文主要研究成果如下： (1)提出分布式動(dòng)態(tài)狀態(tài)估計(jì)框架。在發(fā)電廠和變電站分別進(jìn)行發(fā)電機(jī)動(dòng)態(tài)狀態(tài)估計(jì)和變電站零阻抗特性狀態(tài)估計(jì),將估計(jì)結(jié)果上送至調(diào)度中心進(jìn)行數(shù)據(jù)整合并實(shí)施全系統(tǒng)狀態(tài)估計(jì)。提出了一種系統(tǒng)機(jī)電暫態(tài)過程中基于PMU的發(fā)電機(jī)動(dòng)態(tài)狀態(tài)估計(jì)新方法。該方法充分考慮系統(tǒng)機(jī)電暫態(tài)過程中調(diào)速器對(duì)發(fā)電機(jī)機(jī)械轉(zhuǎn)矩的調(diào)節(jié)作用。建立了系統(tǒng)機(jī)電暫態(tài)過程中發(fā)電機(jī)動(dòng)態(tài)狀態(tài)估計(jì)模型；給出了系統(tǒng)噪聲誤差方差的具體計(jì)算方法；進(jìn)一步提出基于比例對(duì)稱采樣無跡卡爾曼濾波的發(fā)電機(jī)動(dòng)態(tài)狀態(tài)估計(jì)算法。仿真結(jié)果表明提出的方法精度高于機(jī)械轉(zhuǎn)矩恒定的方法。 (2)針對(duì)PMU量測(cè)中存在不良數(shù)據(jù)的問題,提出一種魯棒性發(fā)電機(jī)動(dòng)態(tài)狀態(tài)估計(jì)算法。將時(shí)變多維觀測(cè)噪聲尺度因子引入到容積卡爾曼濾波中,根據(jù)量測(cè)新息對(duì)量測(cè)誤差進(jìn)行在線調(diào)整,使其更加逼近真實(shí)噪聲。再利用調(diào)整后的誤差計(jì)算濾波增益,使其能夠在PMU量測(cè)存在不良數(shù)據(jù)的情況下對(duì)狀態(tài)量預(yù)報(bào)值進(jìn)行準(zhǔn)確修正從而得到精確的發(fā)電機(jī)狀態(tài)量估計(jì)值。針對(duì)時(shí)變多維觀測(cè)噪聲尺度因子為非對(duì)角陣而造成濾波增益求逆發(fā)生奇異的問題,提出解決方案。仿真結(jié)果表明,當(dāng)PMU出現(xiàn)連續(xù)多點(diǎn)壞數(shù)據(jù)時(shí),魯棒動(dòng)態(tài)狀態(tài)估計(jì)仍然能夠得到準(zhǔn)確的估計(jì)結(jié)果。 (3)提出了一種系統(tǒng)機(jī)電暫態(tài)過程中,基于PMU的變電站狀態(tài)估計(jì)新方法。該方法將變電站內(nèi)斷路器的零阻抗特性作為虛擬量測(cè),進(jìn)一步提升冗余度。同時(shí),在系統(tǒng)故障后斷路器狀態(tài)未知的情況下建立狀態(tài)估計(jì)模型,能夠有效辨識(shí)斷路器的實(shí)際狀態(tài)。針對(duì)PMU量測(cè)存在不良數(shù)據(jù)的問題,給出了基于非二次準(zhǔn)則狀態(tài)估計(jì)的不良數(shù)據(jù)辨識(shí)方法,并對(duì)門檻值的選取方案進(jìn)行了改進(jìn),能夠有效辨識(shí)不良數(shù)據(jù)。 (4)提出了一種機(jī)電暫態(tài)過程中全系統(tǒng)狀態(tài)估計(jì)方法。基于機(jī)網(wǎng)接口的直接解法,給出了發(fā)電機(jī)動(dòng)態(tài)狀態(tài)估計(jì)結(jié)果轉(zhuǎn)化為網(wǎng)絡(luò)節(jié)點(diǎn)電壓相量偽量測(cè)的誤差方差計(jì)算方法；提出了考慮發(fā)電機(jī)動(dòng)態(tài)狀態(tài)估計(jì)約束的全系統(tǒng)狀態(tài)估計(jì)方法,通過發(fā)電機(jī)動(dòng)態(tài)狀態(tài)估計(jì)約束進(jìn)一步提升機(jī)電暫態(tài)過程中系統(tǒng)狀態(tài)量的估計(jì)精度。
[Abstract]:The synchronous phasor measurement unit (PMU) can directly measure the phasor information in the electromechanical transient process of power system. It provides a new technique for power system dynamic security monitoring. However, due to sensor error and interference. PMU measurement inevitably has random errors and bad data. If the PMU measurement is not processed directly, it may not be able to accurately monitor the dynamic process of power system. This paper studies the distributed dynamic state estimation method in electromechanical transient process systematically. The main research results are as follows: 1) A distributed dynamic state estimation framework is proposed. Generator dynamic state estimation and substation zero-impedance characteristic state estimation are carried out in power plants and substations respectively. The estimation results are sent to the dispatching center for data integration and the whole system state estimation is implemented. A new method of generator dynamic state estimation based on PMU in the electromechanical transient process of the system is proposed. The method takes full account of the system. The dynamic state estimation model of generator in electromechanical transient process is established. The calculation method of system noise error variance is given. Furthermore, a generator dynamic state estimation algorithm based on proportional symmetric sampling unscented Kalman filter is proposed. The simulation results show that the proposed method is more accurate than the method with constant mechanical torque. 2) aiming at the problem of bad data in PMU measurement, a robust dynamic state estimation algorithm for generator is proposed. The time-varying multidimensional noise scale factor is introduced into the volumetric Kalman filter. The measurement error is adjusted online according to the measurement innovation to make it more approximate to the real noise. Then the filter gain is calculated by using the adjusted error. It can correct the prediction value of state quantity under the condition of bad data in PMU measurement, and get the accurate estimation value of generator state quantity. The scale factor of noise is non-diagonal matrix for time-varying multi-dimensional observation. The singular problem is caused by the inverse of the filter gain. The simulation results show that the robust dynamic state estimation can still get accurate results when the PMU has continuous multi-point bad data. In this paper, a new method of substation state estimation based on PMU is proposed, in which the zero impedance characteristics of circuit breakers in substation are taken as virtual measurements. At the same time, when the state of circuit breaker is unknown after the system fault, the state estimation model can effectively identify the actual state of the circuit breaker. The problem of bad data exists in the PMU measurement. In this paper, an identification method of bad data based on non-quadratic criterion state estimation is presented, and the selection scheme of threshold is improved, which can effectively identify bad data. A state estimation method for the whole system in the electromechanical transient process is proposed, which is based on the direct solution of the machine network interface. An error variance calculation method is presented in which the dynamic state estimation results of the generator are transformed into the pseudo-measurement of voltage phasor of the network node. A full system state estimation method considering the constraints of generator dynamic state estimation is proposed. By using generator dynamic state estimation constraints, the estimation accuracy of system state variables in electromechanical transient process is further improved.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM31

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