Adverse weather such as hurricanes can significantly affect the reliability of composite power systems. Predicting the impact of hurricanes can help utilities for better preparedness and make appropriate restoration arrangements. In this dissertation, the impact of hurricanes on the reliability of composite power systems is investigated. Firstly, the impact of adverse weather on the long-term reliability of composite power systems is investigated by using Markov cut-set method. The Algorithms for the implementation is developed. Here, two-state weather model is used. An algorithm for sequential simulation is also developed to achieve the same goal. The results obtained by using the two methods are compared. The comparison shows that the analytical method can obtain comparable results and meantime it can be faster than the simulation method. Secondly, the impact of hurricanes on the short-term reliability of composite power systems is investigated. A fuzzy inference system is used to assess the failure rate increment of system components. Here, different methods are used to build two types of fuzzy inference systems. Considering the fact that hurricanes usually last only a few days, short-term minimal cut-set method is proposed to compute the time-specific system and nodal reliability indices of composite power systems. The implementation demonstrates that the proposed methodology is effective and efficient and is flexible in its applications. Thirdly, the impact of hurricanes on the short-term reliability of composite power systems including common-cause failures is investigated. Here, two methods are proposed to archive this goal. One of them uses a Bayesian network to alleviate the dimensionality problem of conditional probability method. Another method extends minimal cut-set method to accommodate common-cause failures. The implementation results obtained by using the two methods are compared and their discrepancy is analyzed. Finally, the proposed methods in this dissertation are also applicable to other applications in power systems.

Sistemų gedimo modeliavimas paprastai vykdomas taikant taip vadinamus gedimų medžius. Sistemos gedimo tikimybės ir gedimo atsiradimo priežasčių vertinimas dažniausiai atliekamas sudarant minimalių kirtimų aibę (MCS) ir pagal ją įvertinant gedimo tikimybę. Pastaruosius dvidešimt metų tiksliam gedimo tikimybės vertinimui yra taikoma dvejetainė sprendimų diagrama (BDD). Tačiau BDD sudarymo ir taikymo metodika vis dar yra tobulinama. Iki šiol Lietuvoje sistemos gedimo tikimybės vertinimui BDD dar nebuvo taikyta. Pristatant atliktą darbą aprašomi pagrindiniai MCS ir BDD sudarymo metodai bei jų taikymo ypatybės. Taip pat pateikiamas Kauno hidroelektrinės užtvankos vartų valdymo sistemos gedimo modelis ir gedimo tikimybės vertinimas. Šiuo tikslu buvo taikomi skirtingi MCS ir BDD sudarymo metodai bei atitinkamos programinės priemonės. Atlikus bandomuosius skaičiavimus taip pat pateikiamas gautų rezultatų palyginimas. Darbe apibūdinami pagrindiniai MCS ir BDD taikymo privalumai ir trūkumai bei pristatoma naujai sukurta programinė priemonė „DemoITE“. Taikant išanalizuotus algoritmus bei sukurtą programinę priemonę „DemoITE“ buvo ištirtos ir nustatytos sistemos gedimo priežastys bei tiksliai įvertinta sistemos gedimo tikimybė. Be to, pasiūlyta bazinių įvykių rangavimo principas, įgalinantis gauti mažiausią BDD struktūrą. / Modelling of system failure usually is performed applying so-called fault trees. Assessment of system failure probability and failure occurrence causes usually is performed developing a minimal cut-set (MCS) and according to it evaluating probability of system failure. The last twenty years a binary decision diagram (BDD) has been applied for the exact evaluation of system failure. However, a methodology of creation and application of BDD is still under development. Till now in Lithuania for the assessment of system failure probability BDD has not been applied yet. Presenting a performed work the main methods of development of MCS and BDD as well as features of their application is described. Also, the model and assessment of failure of Kaunas hydropower dam gates’ control system is presented. For this task the different methods of development of MCS and BDD as well as corresponding software was applied. Having performed the testing calculations a comparison of results is presented too. In the work the main advantages and disadvantages of MCS and BDD application are described and newly created software “DemoITE” is introduced. The developed algorithms and universal software “DemoITE” is used for visualization of failure causes and for exact estimation of the investigated system failure probability. Also, it is proposed the order of basic events on purpose to design the least BDD.