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U disertaciji je predstavljen pristup zasnovan na algoritmu mešovitog celobrojnog linearnog programiranja (MILP) za određivanje optimalnog broja, tipa i lokacije uređaja za automatizaciju distributivne mreže. Ugradnja različitih tipova nove opreme (daljinski kontrolisani reklozeri, sekcioneri i indikatori prolaska struje kvara) kao i relokacija postojeće opreme su istovremeno razmatrani. Prilikom određivanja optimalnog scenarija za automatizaciju, predloženi pristup uvažava troškove ispada potrošača/proizvođača usled trenutnih, kratkotrajnih i dugotrajnih ispada, najčešće korišćene pokazatelje pouzdanosti (SAIFI, SAIDI, MAIFI, i ASIDI) kao i troškove distributivnog preduzeća, asocirane uređajima za automatizaciju i ekipama koje su uključene u proces rešavanja prekida napajanja. Dakle, osnovni cilj ove disertacije je, da se napravi model zasnovan na mešovitom celobrojnom linearnom programiranju koji će omogućiti određivanje najboljeg scenarija za automatizaciju distributivne mreže u slučajevima kada se ocena kvaliteta isporuke definiše preko pokazatelja pouzdanosti, preko troškova usled prekida napajanja ili kombinacijom ova dva pokazatelja., The dissertation presents a mixed integer linear programming (MILP) based approach for determining the optimal number, type and location of automation devices to be installed in the network by considering different types of devices simultaneously (remotely controlled circuit breakers/reclosers, sectionalizing switches, remotely supervised fault passage indicators). Simultaneously, it determines the new (optimal) locations of the automation devices that already exist in the network. In determining the most effective network automation scenario, the proposed approach takes into account the outage cost of consumers/producers due to momentary, short-term, and long-term interruptions, the commonly used network reliability indices (SAIFI, SAIDI, MAIFI, and ASIDI) as well as the cost of automation devices and the cost of crews. It provides the best network automation scenario in distribution systems if the network reliability indices are used for measuring the distribution system reliability, if cost of interruptions is defined to all consumers/producers, and if both approaches (criteria) are used.

U disertaciji je predstavljen pristup zasnovan na algoritmu mešovitog celobrojnog linearnog programiranja (MILP) za određivanje optimalnog broja, tipa i lokacije uređaja za automatizaciju distributivne mreže. Ugradnja različitih tipova nove opreme (daljinski kontrolisani reklozeri, sekcioneri i indikatori prolaska struje kvara) kao i relokacija postojeće opreme su istovremeno razmatrani. Prilikom određivanja optimalnog scenarija za automatizaciju, predloženi pristup uvažava troškove ispada potrošača/proizvođača usled trenutnih, kratkotrajnih i dugotrajnih ispada, najčešće korišćene pokazatelje pouzdanosti (SAIFI, SAIDI, MAIFI, i ASIDI) kao i troškove distributivnog preduzeća, asocirane uređajima za automatizaciju i ekipama koje su uključene u proces rešavanja prekida napajanja. Dakle, osnovni cilj ove disertacije je, da se napravi model zasnovan na mešovitom celobrojnom linearnom programiranju koji će omogućiti određivanje najboljeg scenarija za automatizaciju distributivne mreže u slučajevima kada se ocena kvaliteta isporuke definiše preko pokazatelja pouzdanosti, preko troškova usled prekida napajanja ili kombinacijom ova dva pokazatelja., The dissertation presents a mixed integer linear programming (MILP) based approach for determining the optimal number, type and location of automation devices to be installed in the network by considering different types of devices simultaneously (remotely controlled circuit breakers/reclosers, sectionalizing switches, remotely supervised fault passage indicators). Simultaneously, it determines the new (optimal) locations of the automation devices that already exist in the network. In determining the most effective network automation scenario, the proposed approach takes into account the outage cost of consumers/producers due to momentary, short-term, and long-term interruptions, the commonly used network reliability indices (SAIFI, SAIDI, MAIFI, and ASIDI) as well as the cost of automation devices and the cost of crews. It provides the best network automation scenario in distribution systems if the network reliability indices are used for measuring the distribution system reliability, if cost of interruptions is defined to all consumers/producers, and if both approaches (criteria) are used.

In power system planning and operation, accurate assessment of reliability worth is essential for making informed decisions. The accuracy of the reliability worth estimation is directly affected by the interruption cost model used in the analysis. Residential interruption costs vary with season, day of week and time of day, and can be difficult to handle because of their intangible characteristics. This paper develops a cost model for residential customers that includes the timing of the outage by modeling the underlying factors that give rise to the temporal variations in residential interruption costs. By considering the stochastic nature of the underlying factors, as for example outdoor temperature, the proposed model makes it possible to estimate the costs for an event that is extreme in other senses than having a long duration. Time sequential Monte Carlo simulations were applied to a test system in order to assess reliability worth. The results show that the commonly used customer damage function overestimates the reliability worth. By accounting for the timing of the outages a more realistic estimation of the interruption costs can be obtained., QC 20160202

It is very difficult to find pre-emptive scheduling algorithms that consider all the main characteristics of computer vision systems. Moreover, there is no generic algorithm that considers interruption costs for such systems. Taking the interruption of tasks into account scheduling results can be improved. But it is also very important to take the costs that arise from interruptions into account because they not only increase the total execution time, but also because the scheduler can evaluate whether it is adequate to interrupt certain tasks or not. Thus, the result can be more realistic. Therefore, we present an extension to the static algorithm SASEPA for computer vision which considers interruption costs.

It is very difficult to find pre-emptive scheduling algorithms that consider all the main characteristics of computer vision systems. Moreover, there is no generic algorithm that considers interruption costs for such systems. Taking the interruption of tasks into account scheduling results can be improved. But it is also very important to take the costs that arise from interruptions into account because they not only increase the total execution time, but also because the scheduler can evaluate whether it is adequate to interrupt certain tasks or not. Thus, the result can be more realistic. Therefore, we present an extension to the static algorithm SASEPA for computer vision which considers interruption costs.