本文選題：輸變電設(shè)備　切入點(diǎn)：狀態(tài)檢修　出處：《浙江大學(xué)》2014年碩士論文

【摘要】：信息技術(shù)、微電子技術(shù)、網(wǎng)絡(luò)通信技術(shù)等的發(fā)展為電力設(shè)備在線狀態(tài)監(jiān)測提供了良好的技術(shù)支撐,推動了狀態(tài)檢修技術(shù)的應(yīng)用和發(fā)展。同時(shí)狀態(tài)檢修作為堅(jiān)強(qiáng)智能電網(wǎng)建設(shè)和電網(wǎng)全壽命資產(chǎn)管理的重要組成部分,也成為電力企業(yè)科學(xué)發(fā)展的重點(diǎn)研究內(nèi)容之一。狀態(tài)檢修是一種預(yù)測性維修,能夠在設(shè)備性能下降到一定程度或故障將要發(fā)生之前及時(shí)、有針對性地安排好設(shè)備檢修,能夠有效縮短停電時(shí)間、延長設(shè)備經(jīng)濟(jì)壽命,同時(shí)降低檢修成本、提高電網(wǎng)安全性和可靠性。 狀態(tài)檢修一般包括狀態(tài)監(jiān)測、狀態(tài)評估、檢修決策三個(gè)環(huán)節(jié),三者循序漸進(jìn),順次進(jìn)行。狀態(tài)監(jiān)測和狀態(tài)評估是狀態(tài)檢修的前提和基礎(chǔ),檢修決策是狀態(tài)檢修的核心和目標(biāo)。因此,如何做好科學(xué)的檢修決策是體現(xiàn)狀態(tài)檢修價(jià)值的關(guān)鍵。本文以狀態(tài)檢修決策為中心,開展了輸變電設(shè)備狀態(tài)檢修決策研究,得到設(shè)備個(gè)體層面的最優(yōu)檢修方案；以此為基礎(chǔ),開展了電網(wǎng)狀態(tài)檢修決策研究,得到設(shè)備個(gè)體和電網(wǎng)整體綜合最優(yōu)的檢修方案。 提出一種基于D-S證據(jù)理論的輸變電設(shè)備狀態(tài)檢修多屬性群決策方法。新模型在建立的檢修決策框架引導(dǎo)下,歸納了以效用、成本為一級指標(biāo)的決策指標(biāo)體系并給出量化方法；將這些相互獨(dú)立的決策指標(biāo)作為證據(jù)源,將依據(jù)狀態(tài)檢修導(dǎo)則劃分的檢修方式和基于設(shè)備健康狀態(tài)的剩余預(yù)測壽命劃分的檢修時(shí)段組合形成的檢修方案作為識別框架,通過D-S合成法則,得到綜合指標(biāo)作用下的群體決策意見,實(shí)現(xiàn)了輸變電設(shè)備檢修方式和檢修時(shí)段的同時(shí)決策。算例表明通過對各個(gè)指標(biāo)賦予決策者的主觀權(quán)重并將指標(biāo)綜合權(quán)重分配到BPA值中,實(shí)現(xiàn)了決策者檢修意愿的融合,并且可以根據(jù)決策者檢修意愿調(diào)整相應(yīng)指標(biāo)的權(quán)重系數(shù)來控制和調(diào)整決策結(jié)果,決策結(jié)果使所有指標(biāo)達(dá)到綜合最優(yōu)。 考慮到設(shè)備之間、設(shè)備與電網(wǎng)之間的實(shí)時(shí)關(guān)聯(lián)性,提出了電網(wǎng)狀態(tài)檢修概念和基于D-S證據(jù)理論的電網(wǎng)狀態(tài)檢修決策方法。首先歸納出電網(wǎng)狀態(tài)檢修決策的指導(dǎo)原則,并對所有待修設(shè)備在個(gè)體決策層面得到的可能檢修方案依據(jù)原則進(jìn)行組合與篩選,得到電網(wǎng)狀態(tài)檢修的可能方案集合,然后建立了能夠全面反映電網(wǎng)整體運(yùn)行的安全性、可靠性和經(jīng)濟(jì)性的決策指標(biāo),并給出量化方法。在上述指標(biāo)的指導(dǎo)下,通過基于D-S證據(jù)理論的電網(wǎng)狀態(tài)檢修決策模型對電網(wǎng)狀態(tài)檢修可能方案進(jìn)行決策尋優(yōu),得到設(shè)備個(gè)體與電網(wǎng)整體運(yùn)行綜合最優(yōu)的檢修方案。
[Abstract]:The development of information technology, microelectronics technology and network communication technology provides a good technical support for on-line condition monitoring of power equipment, and promotes the application and development of condition-based maintenance technology.At the same time, as an important part of smart grid construction and lifetime asset management, condition-based maintenance has also become one of the key research contents in the scientific development of electric power enterprises.Condition-based maintenance (CBM) is a kind of predictive maintenance. It can arrange the equipment maintenance timely before the equipment performance drops to a certain extent or the failure will occur. It can effectively shorten the blackout time and prolong the economic life of the equipment.At the same time, reduce the cost of maintenance, improve the security and reliability of the grid.Condition-based maintenance generally includes three links: condition monitoring, condition evaluation and maintenance decision, which are carried out step by step and sequentially.Condition monitoring and condition evaluation are the premise and foundation of condition based maintenance. Maintenance decision is the core and goal of condition based maintenance.Therefore, how to make scientific maintenance decision is the key to reflect the value of condition based maintenance.In this paper, based on the decision of condition-based maintenance (CBM), the research on condition-based maintenance of power transmission and transformation equipment is carried out, and the optimal maintenance scheme on individual level of equipment is obtained, based on which, the research of power network condition-based maintenance decision is carried out.A comprehensive and optimal overhaul scheme is obtained for both the individual equipment and the power grid.A multi-attribute group decision-making method based on D-S evidence theory for condition based maintenance of power transmission and transformer equipment is proposed.Under the guidance of the established maintenance decision framework, the new model induces the decision index system with utility and cost as the primary index and gives the quantitative method, and takes these independent decision indicators as the evidence source.The maintenance scheme, which is based on the maintenance mode divided according to the condition maintenance guidelines and the maintenance period based on the remaining life prediction of the equipment health condition, is taken as the identification framework, and the D-S synthesis rule is adopted.The group decision advice under the action of comprehensive index is obtained, and the maintenance mode and the maintenance period of transmission and transformation equipment are realized at the same time.The numerical examples show that the decision makers' willingness to overhaul can be merged by assigning the subjective weights to the decision-makers and assigning the comprehensive weights to the BPA value.And the weight coefficient of the corresponding index can be adjusted according to the decision maker's willingness to overhaul to control and adjust the decision result. The decision result makes all the indexes achieve the comprehensive optimum.Considering the real-time relationship between equipment and power network, the concept of power network condition-based maintenance and the decision-making method based on D-S evidence theory are proposed.Firstly, the guiding principles of power network condition based maintenance decision are summarized, and the possible maintenance schemes for all the equipment to be repaired are combined and screened according to the principles, and the set of possible network condition maintenance schemes is obtained.Then, a decision index which can reflect the safety, reliability and economy of the whole power network is established, and the quantitative method is given.Under the guidance of the above indexes, through the decision-making model based on D-S evidence theory, the possible scheme of power network condition-based maintenance (CBM) is optimized, and the comprehensive optimal maintenance scheme of the equipment and the whole operation of the power network is obtained.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TM73

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本文編號：1691462