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定時(shí)限保護(hù)定值優(yōu)化及其在在線整定中的應(yīng)用研究

發(fā)布時(shí)間:2018-11-06 11:40
【摘要】:近年來(lái),隨著電網(wǎng)規(guī)模的快速發(fā)展和運(yùn)行方式的日益復(fù)雜,傳統(tǒng)的逐級(jí)配合的繼電保護(hù)離線整定計(jì)算方法在定值性能方面存在的問(wèn)題日益突出,急需找到解決途徑。如果能夠從整體性能最優(yōu)出發(fā)安排定值,將整定計(jì)算作為優(yōu)化問(wèn)題進(jìn)行考慮,并根據(jù)電網(wǎng)的實(shí)時(shí)運(yùn)行狀態(tài)調(diào)整性能存在問(wèn)題的定值,則可以大大提高繼電保護(hù)定值的性能。針對(duì)以上問(wèn)題,本文對(duì)定時(shí)限保護(hù)定值優(yōu)化及其在在線整定系統(tǒng)中的應(yīng)用進(jìn)行了研究,主要內(nèi)容如下: 對(duì)繼電保護(hù)定值全局優(yōu)化問(wèn)題的研究現(xiàn)狀進(jìn)行了綜述研究。從反時(shí)限保護(hù)定值優(yōu)化、混合保護(hù)定值優(yōu)化、定時(shí)限保護(hù)定值優(yōu)化三個(gè)方面對(duì)現(xiàn)有優(yōu)化模型進(jìn)行歸納總結(jié);對(duì)優(yōu)化算法則分常規(guī)優(yōu)化算法和人工智能優(yōu)化算法兩個(gè)方面進(jìn)行探討。在此基礎(chǔ)上,對(duì)定值優(yōu)化領(lǐng)域有待解決的問(wèn)題進(jìn)行了展望,為本文后續(xù)的研究奠定了理論基礎(chǔ)。 將風(fēng)險(xiǎn)理論引入定值優(yōu)化問(wèn)題研究,提出了基于風(fēng)險(xiǎn)指標(biāo)的定時(shí)限保護(hù)定值全局優(yōu)化方法。綜合考慮電網(wǎng)的不確定因素以及線路故障造成的嚴(yán)重性后果,定義“繼電保護(hù)廣義動(dòng)作時(shí)間”作為風(fēng)險(xiǎn)指標(biāo),以運(yùn)行風(fēng)險(xiǎn)最小為目標(biāo)進(jìn)行優(yōu)化建模。采用遺傳算法對(duì)所建模型進(jìn)行仿真,結(jié)果表明該模型得到的定值優(yōu)化結(jié)果可以有效地降低運(yùn)行風(fēng)險(xiǎn),提高繼電保護(hù)的定值性能,有利于電網(wǎng)的安全可靠運(yùn)行。 最后討論了定時(shí)限保護(hù)定值優(yōu)化在在線整定中的應(yīng)用問(wèn)題。對(duì)繼電保護(hù)在線校核/整定一體化系統(tǒng)的基本結(jié)構(gòu)進(jìn)行了概述,在此基礎(chǔ)上,提出了計(jì)及上級(jí)限定值的定值在線優(yōu)化方法。該方法采用同心松弛搜索算法快速確定定值優(yōu)化范圍,計(jì)及上級(jí)限定值建立定值在線優(yōu)化模型,并采用遺傳算法進(jìn)行定值局部尋優(yōu),實(shí)現(xiàn)了定值的快速在線優(yōu)化。
[Abstract]:In recent years, with the rapid development of power network scale and the increasing complexity of operation mode, the traditional off-line setting calculation method of relay protection with step by step cooperation has become more and more serious in setting performance, so it is urgent to find a way to solve it. If the setting value can be arranged according to the overall optimal performance, the setting calculation can be considered as an optimization problem, and the fixed value of the performance problem can be adjusted according to the real-time operation state of the power network, the performance of the relay protection setting can be greatly improved. Aiming at the above problems, this paper studies the timing and limit protection setting optimization and its application in the on-line setting system. The main contents are as follows: the research status of the relay protection setting global optimization problem is summarized and studied. The existing optimization models are summarized from three aspects: the optimization of setting value of inverse time-limited protection, the optimization of setting value of mixed protection and the optimization of setting value of time-limited protection. The optimization algorithm is divided into two aspects: conventional optimization algorithm and artificial intelligence optimization algorithm. On this basis, the problems to be solved in the field of fixed value optimization are prospected, which lays a theoretical foundation for further research in this paper. In this paper, the risk theory is introduced into the problem of fixed value optimization, and a global optimization method of fixed value with time-limited protection based on risk index is proposed. Considering the uncertain factors of power network and the serious consequences caused by line faults, the generalized operation time of relay protection is defined as the risk index, and the optimal modeling is carried out with the aim of minimum operational risk. The genetic algorithm is used to simulate the model. The results show that the optimization result can effectively reduce the operational risk, improve the performance of relay protection, and is conducive to the safe and reliable operation of the power network. Finally, the application of timing protection optimization in online setting is discussed. In this paper, the basic structure of the integrated system of on-line checking and setting of relay protection is summarized. On the basis of this, a method of on-line optimization of fixed value with the limit value of superior is put forward. In this method, concentric relaxation search algorithm is used to quickly determine the optimal range of fixed values, and the on-line optimization model of fixed values is established by taking into account the upper limit values, and the local optimization of fixed values is carried out by genetic algorithm, and the fast online optimization of fixed values is realized.
【學(xué)位授予單位】:華中科技大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2014
【分類號(hào)】:TM771

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1 張盛;徐寧;余t,

本文編號(hào):2314160


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