doktorska disertacija
Mitja Antončič (Author), Boštjan Blažič (Mentor)

Abstract

V doktorskem delu obravnavamo zvišanje spoznavnosti v elektroenergetskem omrežju, in sicer se osredotočamo na spoznavnost v srednjenapetostnih in nizkonapetostnih distribucijskih omrežjih. Omenjeno postaja aktualno s potrebo po zvišanju vodljivosti sodobnega distribucijskega sistema z vse višjim deležem obnovljivih virov, toplotnih črpalk, električnih vozil in električnih shranjevalnikov. Po drugi strani zvišanje spoznavnosti predstavlja izziv v današnjih distribucijskih omrežjih, za katere je značilna nizka količina razpoložljivih omrežnih meritev. V začetnih poglavjih naloge so predstavljene ključne značilnosti današnjih elektroenergetskih omrežij. Pri opisu se osredotočamo na lastnosti obeh nivojev distribucije. Vključevanje sodobnih tipov bremen v distribucijska omrežja zahteva vpeljavo vodljivosti v distribucijski sistem. Predpogoj zanjo pa je vzpostavitev spoznavnosti, ki je že dalj časa stalnica v prenosnih omrežjih. Parametri distribucijskih omrežij se bistveno razlikujejo od tistih, ki veljajo za prenosna omrežja, zato neposredna uporaba različnih rešitev, razvitih za prenosno omrežje, ni možna. Je pa omenjeno mogoče nasloviti z namenskim algoritmom za oceno stanja distribucijskega sistema. Dosedanje aktivnosti na področju ocene stanja v distribuciji so predstavljene ob koncu prvega poglavja. Ločeno poglavje obravnava matematično ozadje ključnih gradnikov ocenjevalnika stanja. Ker predstavljajo osnovo metode, je njihovo poznavanje pomembno za razumevanje delovanja samega algoritma. Predstavljeno je ozadje matematičnega modeliranja, ki se zaradi lastnosti distribucijskih omrežij nekoliko razlikuje od modeliranja prenosnega omrežja. Razloženo je tudi ozadje ključnih matematičnih funkcij, s pomočjo katerih ocenjevalni algoritem sistemske meritve prek poznavanja topologije povezuje s spremenljivkami stanja. Uvodni del se zaključuje s predstavitvijo metode uteženih najmanjših kvadratov, ki je najpogosteje uporabljena v ocenjevalniku stanja in tako predstavlja referenco za razviti novi algoritem. Temu sledi opis metode Kalmanovega filtra, ki predstavlja osnovo novega algoritma ocenjevalnika stanja. V sklopu doktorskega dela je bil razvit in praktično preizkušen nov algoritem ocenjevalnika stanja za distribucijska omrežja, ki je predstavljen v nadaljevanju. Ločeno je v podpoglavju podrobno predstavljen zajem in obdelava meritev algoritma. Neposredna uporaba omrežnih meritev namreč ne zadošča, saj je njihovo število v distribucijskem omrežju prenizko za ustrezen nivo redundance. Sledi opis načina priprave matematičnega modela, potrebnega za izvedbo procesa ocene stanja. Med izračunom algoritem ocene stanja pridobljene meritve aplicira na matematični model omrežja in s tem na nek način preverja njihovo smiselnost. To je mogoče samo z ustrezno definiranim omrežnim modelom. Sledi predstavitev nadgradenj, ki smo jih razviti in testirali v sklopu doktorskega dela. Prva predstavlja poenostavitev klasične metode uteženih najmanjših kvadratov za hitrejšo izvedbo ocene stanja nizkonapetostnega distribucijskega sistema. Pri poenostavitvi smo izhajali iz razklopljene metode, ki v primeru prenosnega sistema izkorišča njegove specifične lastnosti pri zanemaritvi posameznih delov sistemskih matrik. Ob upoštevanju razlik med obema napetostnima nivojema smo metodo preoblikovali in uspešno testno izvedli v simulacijski analizi ocene stanja nizkonapetostnega omrežja. Uporabljene predpostavke veljajo samo za nizkonapetostni nivo, torej metode ni mogoče neposredno aplicirati v srednji napetosti. Dodatno imajo ocenjevalniki, osnovani na metodi uteženih najmanjših kvadratov, težavo z robustnostjo v primeru izpadlih meritev, kar je pogost pojav pri merilnih sistemih v današnjih distribucijskih omrežjih. Zaradi opaženih težav z zanesljivostjo merilnega sistema smo se v nadaljevanju osredotočili na robustnejše metode. Mednje sodijo metode iz skupine Kalmanovih filtrov. Nov algoritem smo osnovali na metodi razširjenega Kalmanovega filtra, ki smo jo dodatno nadgradili. Med analizo se je namreč izkazalo, da je mogoče izračun stanja v stacionarnem sistemu bistveno pohitriti s poenostavitvijo na nivoju izračuna sistemskih matrik. Pohitritev ima zanemarljiv vpliv na natančnost izračuna. Z dodatno ustrezno izvedeno detekcijo spremembe v sistemu tako pridemo do hitrega, robustnega in hkrati natančnega algoritma za oceno stanja distribucijskega omrežja. Slednji je bil razvit in implementiran tudi v okviru pričujočega doktorskega dela. V zadnjem delu naloge so ločeno predstavljeni rezultati uporabe razvite metode v laboratorijskem okolju in v realnih omrežjih na terenu. Dodatno je predstavljen način modeliranja samega omrežja. Testiranje v laboratoriju je pokazalo, da razviti algoritem ustrezno zaznava in premaguje izzive, ki so pričakovani v procesu ocene stanja distribucijskih omrežij. Omenjeno se je kot resnično izkazalo tudi med praktično izvedbo, kar je prikazano v zaključnem delu poglavja. To prikazuje tudi izzive, ki so se med praktično izvedbo pokazali v procesu analize podatkovnih baz operaterjev in zajema meritev. Te izzive je bilo treba nasloviti pred samo izvedbo algoritma v realnih omrežjih. Sklepni del podaja zaključke in povzema nekaj glavnih ugotovitev doktorskega dela. Izpostavljeni sta tudi bistveni pomanjkljivosti današnjih distribucijskih omrežij v luči spoznavnosti sistema. Ti sta nezanesljiv merilni sistem in pomanjkljive podatkovne baze omrežij.

Keywords

ocenjevalniki stanja;distribucijska omrežja;spoznavnost;Kalmanov filter;demonstracija v omrežju;doktorati;

Data

Language: Slovenian
Year of publishing:
Typology: 2.08 - Doctoral Dissertation
Organization: UL FE - Faculty of Electrical Engineering
Publisher: [M. Antončič]
UDC: 621.311.1(043.3)
COBISS: 68695299 Link will open in a new window
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Other data

Secondary language: English
Secondary title: MEDIUM AND LOW VOLTAGE DISTRIBUTION-NETWORK STATE ESTIMATOR BASED ON KALMAN FILTER
Secondary abstract: With the increased penetration of the advanced modern loads, such as distributed renewable energy resources, heat pumps, electric vehicle chargers and energy storage, there is an urge to implement some extent of controllability in the distribution network. This would allow for the better use of existing resources, postponing the need for equipment upgrade. In order to introduce any kind of control to the system, it must be observable in the first place. Establishing observability is a challenge in today's distribution networks, which are known for their low quantity of available network measurements. In the following doctoral thesis, we consider the increase of observability in the power network, with special interest to the medium-voltage and low-voltage distribution networks. Key features of nowadays power networks are presented in the beginning of the thesis. Due to its context, here we focus mostly to the characteristics of the medium and low voltage distribution networks and their key differences in comparison with the high voltage transmission networks. The latter are long known for a successful implementation of different methods that render them observable. With the increasing penetration of modern loads, similar task is now foreseen also for the distribution networks. Due to the significant discrepancy between the two, direct implementation of methods, used in transmission system observability is not possible in the distribution networks. This challenge can be addressed with a dedicated algorithm to assess the state of the distribution system. Recent efforts in the field of the distribution system state estimation are presented at the end of the first chapter. Next chapter gives the mathematical background of crucial parts of the state estimation algorithm. As these represent the heart of the estimation process, their basic knowledge is of great importance for understanding the operation of the algorithm itself. So, the mathematical modelling of the distribution network is given first. As a result of different topologies an electrical characteristic, obtained model differs significantly, from the transmission network models. Additionally, also the necessary measurement functions are explained in this part of the work. These functions and their derivatives enable the estimation algorithm to relate the system measurements with the appropriate state variables, taking into account the mathematical model of the network. The introductory part concludes with a presentation of the weighted least squares method, which is commonly used in the state estimation algorithms. Consequently, it is chosen as a reference for assessment of the developed new algorithm performance. Description of the Kalman filter method is provided next. Kalman filter represents the basis for the developed new state estimation algorithm. A new state estimation algorithm was developed under the scope of the doctoral thesis. Its performance was demonstrated also through field testing in the autonomous estimation of the real Slovenian distribution networks. New algorithm is described in the dedicated chapter. There, the underlying tasks of measurement acquisition and mathematical model development are explained in detail. The straightforward usage of solely network measurements is not sufficient in the distribution network state estimation, as their number is not adequate for establishing the appropriate level of measurement redundancy. Mathematical model, being the other key input of the state estimator, should also be prepared in order to faithfully mimic the real network in order to calculate accurate estimate of the network state. In the process of state estimation, the algorithm attaches the obtained measurements to the mathematical model of the network and thus, in some way, checks their accuracy. This is only possible with a properly defined network model. The presentation of the upgrades, developed and tested as part of the doctoral thesis, are given in the end of the chapter. Firstly, the simplification of the classical weighted least squares method is presented. It enables a faster calculation of the state estimation in the low-voltage distribution system. Simplification is based on the decoupling, known from the transmission system. It takes advantage of some key characteristics of the grid, which allow neglection of the individual parts of the system matrices. Taking into account the differences between the two voltage levels, we redesigned the method and proved its successful performance in the low-voltage network state estimation. However, the employed assumptions are true only in the low voltage network, so the method cannot be applied directly to the medium voltage level. Additionally, estimators based on the weighted least squares method have a problem with robustness in case of great measurement errors, which tend to happen frequently in today’s distribution networks measurement systems. The initial investigations of the established measurement system revealed frequent measurement drops. Consequently, we had to focus ourselves to more robust methods for state estimator. Extended Kalman filter belongs to such methods and was therefore chosen as a basis for the developed new algorithm. During the initial studies it turned out that the state estimation process can be significantly accelerated with introduction of some simplifications to the calculation of system matrices. These can be kept constant when there is no significant change in the estimated system. With additional successful implementation of the system change detection we get to a fast, robust and at the same time accurate algorithm for distribution network state estimation, which is the main outcome of the presented doctoral thesis. In the end, the results of the developed method implementation are presented. This part includes results of the laboratory testing, followed by the results from the real network field testing. Laboratory testing has proven that the developed algorithm adequately detects and overcomes the challenges, expected to emerge in the actual process of distribution network state estimation. This was further on proven through the developed estimator field test and operation. Its brief outcomes conclude the last chapter, together with the difficulties faced during the development and practical implementation of the estimator in the field. These obstacles had to be properly addressed and mitigated prior the algorithm implementation. The final part gives conclusions and summarizes some of the main outcomes of the work. The significant shortcomings of today's distribution networks in the light of system observability are also highlighted. These can be packed to unreliable measurement system and outdated, scarce network databases.
Secondary keywords: state estimation;distribution networks;observability;Kalman filter;pilot operation;
Type (COBISS): Doctoral dissertation
Study programme: 1000319
Embargo end date (OpenAIRE): 1970-01-01
Thesis comment: Univ. v Ljubljani, Fak. za elektrotehniko
Pages: 165, 18 str.
ID: 13085163