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    <ns1:title language="sr">Rekonfiguracija distributivne mreže i kompenzacija reaktivne snage korišćenjem kombinacije simuliranog kaljenja i Kruskalovog algoritma</ns1:title>
    <ns2:subtitle language="sr">doktorska disertacija</ns2:subtitle>
    <ns2:alt_title language="en">Distribution network reconfiguration and reactive power compensation using a combination of simulated annealing and Kruskal algorithm : doctoral dissertation</ns2:alt_title>
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    <ns1:description language="sr">Poboljšanje snabdevanja električnom energijom se može postići različitim mešovitim strategijama,kao što su koordinisano upravljanje izvorima električne energije i smanjenje u gubicima aktivnesnage. Zajednička koordinacija ovih strategija može dati optimalne rezultate u cilju minimiziranjagubitaka, popravke naponskog profila i korekcije ulaznog faktora snage distributivne mreže.Povoljni rezultati se mogu ostvariti promenom konfiguracije distributivne mreže –rekonfiguracijom. Cilj doktorske disertacije je da se za relativno dug operativni period od preko1000 sati rada mreže, nađu optimalne konfiguracije na satnom nivou uz fiksno postavljenedistribuirane izvore (vetrogeneratore i solarne panele) i kondenzatorske baterije. U tezi se određujescenario kojim se postižu minimalni troškovi i cene ugrađenih kondenzatorskih baterija, gubitakaaktivne snage, vrednosti neisporučene i isporučene električne energije i ograničenja brojakomutacija. Ovo je urađeno u skladu sa svim tehničkim zahtevima koji se postižu i prisustvomregulatora napona pod opterećenjem, u napojnom čvoru mreže.U analizu je uključena i ugradnja akumulacionih baterija za skladištenje električne energije. Udisertaciji je realizovan algoritam koji je građen na osnovu dva optimizaciona algoritma. Jedan jealgoritam simuliranog kaljenja, a drugi je Kruskalov algoritam. Kruskalov algoritam se primenjujeza problem rekonfiguracije, a simulirano kaljenje naknadno za problem kompenzacije. Kruskalovalgoritam je primenljiv za problem rekonfiguracije mreža sa velikim brojem čvorova i grana. Zaodređivanje pozicije obnovljivih izvora energije, koriste se dva pristupa iz literature. Zavetroagregate primenjena je Monte Carlo metoda sa grafičkim prikazom, dok se solarni panelipostavljaju na osnovu druge heurističke metode.Inženjeri za distributivne mreže su svedoci mnogih promena u današnje vreme. Kada je potrebno danaponi čvorova mreže budu unutar dozvoljenih tolerancija, a da ulazni faktor snage bude veći od0,85 sve tri moderne strategije pametne mreže: rekonfiguracija, otočna kompenzacija i prisustvodistribuirane proizvodnje, moraju biti angažovane. Čak i u tom slučaju, prisustvo regulatora naponapod opterećenjem u napojnom čvoru je, neophodno. Pametne mreže zahtevaju integrisana rešenjaza jasno formulisane probleme, koji odražavaju činjenicu da svi ovi uređaji moraju zajednički daegzistiraju da bi se postigli efikasniji ciljevi kroz minimizaciju gubitaka aktivne snage i visokkvalitet isporučene energije krajnjim potrošačima. U analizu su uključena Gauss-ova i Weibull-ovaraspodela za promenu potrošnje i izlazne snage vetrogeneratora, kao i dnevni dijagrami potrošnje zaradni i neradni dan i insolacija solarnih jedinica.Rekonfiguracija distributivnih mreža vezana je za postupak otvaranja i zatvaranja komutacioneopreme, da bi se izmenila topologija mreže sa određenim ciljem. Status komutacione opreme jediskretan i binaran. Kompenzacija reaktivne snage zahteva od operatera distributivne mreže daodredi mesto i veličinu kondenzatorskih baterija, koja je diskretna veličina tako da obaoptimizaciona problema (rekonfiguracija i otočna kompenzacija) spadaju u klasu mešovitocelobrojnog nelinearnog programiranja. Značaj istraživanja su koristi od optimalne lokacije otočnihkondenzatora, optimalne rekonfiguracije i lokacije distribuiranih generatora i sistema zaskladištenje električne energije. Poboljšanja se sagledaju u: smanjenju gubitaka u vodovima,popravci naponskog profila, regulisanju vršnog opterećenja, smanjenju preopterećenjadistributivnih vodova, smanjenju zagađenja okoline, povećanju ukupne energetske efikasnosti iproduženju rada postojećeg sistema.Doktorska disertacija – Branko StojanovićDisertacija je izložena kroz deset poglavlja. Posebna pažnja je posvećena: jednokriterijumskoj ivišekriterijumskoj optimizaciji rekonfiguracije distributivne mreže, otočnoj kompenzaciji reaktivnesnage, simultanim problemima i obnovljivim izvorima u distributivnim mrežama. Modeli potrošnjei proizvodnje od klasičnih do savremenih prikazani su u posebnom poglavlju. Na primeru dve testmreže (IEEE sa 69 čvorova i 118 čvorova), implementirane su razvijene metode proračuna idobijeni rezultati su prikazani grafički, numerički i tabelarno. Detaljno je urađena komparativnaanaliza rezultata proračuna, kada se primenjuje samo simulirano kaljenje i kada se primenjujekombinacija Kruskalovog algoritma i simuliranog kaljenja, razvijenog u ovoj disertaciji. Tabelarnopoređenje po usvojenim kriterijumima komparacije za opsežan deo dosad urađenih članaka imetoda, dat je na kraju disertacije</ns1:description>
    <ns1:description language="en">Supply improving of electrical energy can be achieved through various mixed strategies, such ascoordinated management of electricity sources and reduction in active power losses. The jointcoordination of these strategies can yield optimal results in minimizing losses, improving voltageprofiles, and correcting the power factor of the distribution network. Favorable outcomes can beattained by changing the configuration of the distribution network – through reconfiguration. Theaim of the doctoral dissertation is to find optimal configurations on an hourly basis for a relativelylong operating period of over 1000 hours of network operation, with fixed distributed sources (windgenerators and solar panels) and capacitor banks. The thesis determines a scenario that achievesminimal costs and prices of installed capacitor banks, active power losses, the value of undeliveredand delivered electrical energy, and limitations on the number of commutations. This is done inaccordance with all technical requirements along with load tap changer in the network&apos;s supplynode.The analysis includes the installation of battery energy storage systems. An algorithm developed inthe dissertation is based on two optimization algorithms: simulated annealing and Kruskal&apos;salgorithm. Kruskal&apos;s algorithm is applied to the reconfiguration problem, while simulated annealingis subsequently used for the compensation problem. Kruskal&apos;s algorithm is applicable to thereconfiguration problem of networks with a large number of nodes and branches. Two approachesfrom the literature are used to determine the positions of renewable energy sources. For windturbines, the Monte Carlo method with graphical presentation is applied, while solar panels areplaced based on another heuristic method.Distribution network engineers are witnessing many changes in today&apos;s world. When it is necessaryfor node voltages to be within allowed tolerances and for the power factor to be greater than 0,85,all three modern smart grid strategies: reconfiguration, shunt compensation, and the presence ofdistributed generation, must be engaged. Even in this case, the presence of a load voltage regulatorat the supply node is essential. Smart grids require integrated solutions for clearly formulatedproblems, reflecting the fact that all these devices must coexist to achieve more efficient goalsthrough minimizing active power losses and ensuring high-quality energy delivery to endconsumers. Gaussian and Weibull distributions are included in the analysis for changes inconsumption and output power of wind turbines, as well as daily consumption diagrams forworking and non-working days and insolation of solar units.Reconfiguration of distribution networks is related to the process of opening and closing switchingequipment to change the network&apos;s topology with a specific objective. The status of switchingequipment is discrete and binary. Reactive power compensation requires the distribution networkoperator to determine the location and size of capacitor banks, which is a discrete variable, so bothoptimization problems (reconfiguration and shunt compensation) fall into the class of mixed integernonlinear programming. The significance of the research lies in the benefits of optimal shuntcapacitor locations, optimal reconfiguration and location of distributed generators and energystorage systems. Improvements are seen in: reducing losses in conductors, improving voltageprofiles, regulating peak loads, reducing overloads of distribution lines, reducing environmentalpollution, increasing overall energy efficiency, and extending the life of the existing system.The dissertation is presented in ten chapters. Special attention is paid to: single and multi-criteriaoptimization of distribution network reconfiguration, reactive power compensation, simultaneousDoktorska disertacija – Branko Stojanovićproblems, and renewable sources in distribution networks. Models of consumption and productionfrom classical to modern are presented in a separate chapter. Using two test networks (IEEE with 69nodes and 118 nodes) as examples, the developed calculation methods are implemented, and theresults obtained are presented graphically, numerically, and in tables. A detailed comparativeanalysis of calculation results is performed when only simulated annealing is applied and when acombination of Kruskal&apos;s algorithm and simulated annealing, developed in this dissertation, isapplied. A tabular comparison based on adopted comparison criteria for a significant part ofpreviously conducted articles and methods is provided at the end of the dissertation.</ns1:description>
    <ns1:description language="sr">Tehničke nauke – Elektrotehnika- Elektroenergetski sistemi / Technical science – Electrical engineering - Power Systems  Datum odbrane: 30.09.2024. </ns1:description>
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