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Hydrogen is playing an important role in many sectors of modern economy (green vehicles, energy conversion and storage in electrical grids, processing industry). Solid oxide electrolysis cell (SOEC) is an emerging technology for the production of hydrogen from steam and electrical energy as well as for renewable energies storage. Unfortunately, operating at high current and electrical transients cause degradation that leads to premature end of life. A remedy is to implement a hardware module capable to perform online condition monitoring and optimization of SOEC systems resulting in improved overall performance and extended lifetime. That is expected to significantly expand their deployment on the market. However, very little has been done so far. The H2020 project REACTT seems to be one of the first attempts to build an embedded system for monitoring, diagnosis, prognostics, and control (MDPC) for SOEC system. The underlying master's thesis contributes to the REACTT project in the segment related to the supervision of different modules of the MDPC system. The supervisor module is aimed to orchestrate the operation of various functional modules (agents) such as data acquisition, system optimization, diagnosis, prognostics, and mitigation. The thesis focuses on the design of the supervisor module and its implementation on a control platform based on Raspberry Pi 4. The main contributions of the thesis are twofold. First, the dynamic operation of the supervisor modelled by using the state transition diagram (STD). Second, the code for implementation of the supervisor on the target platform done in Python in a way that complies with the requirements imposed in the project. Vodik ima pomembno vlogo v številnih panogah sodobnega gospodarstva (zelena vozila, pretvorba in shranjevanje energije v električnih omrežjih, procesna industrija itn.). Trdno-oksidne elektrolizne celice (Solid Oxide Electrolysis Cell – SOEC) predstavljajo novo tehnologijo za proizvodnjo vodika iz pare in električne energije. Žal, delovanje pri visokih tokovih in električnih prehodnih pojavih povzroča degradacijo materiala, ki ima za posledico prehitro uničenje celice. En način kako rešiti problem je vgraditev naprave, ki je sposobna sproti spremljati notranje stanje sistema in optimizirati njegovo delovanje. S tem naj bi se povečala zanesljivost sistema in podaljšala življenjska doba, kar bi znatno prispevalo k njihovi komercialni uporabi. Žal je na tem področju doslej narejeno zelo malo. H2020 projekt REACTT je najbrž eden prvih poskusov izdelave vgrajenega sistema za spremljanje, diagnostiko, prognostiko in optimizacijo delovanja (kratica MDPC) za sistem SOEC. Magistrsko delo prispeva k projektu REACTT v delu, ki se nanaša na nadzor različnih modulov sistema MDPC. Za to skrbi enota, ki se imenuje Supervisor. Supervisor je namenjen orkestriranju delovanja različnih funkcionalnih modulov (agentov), kot so npr. agent za zbiranje podatkov, agent za sprotno optimizacijo, razni agenti za diagnostiko, prognostiko in svetovanje korektivnih posegov. Delo se osredotoča na načrtovanje Supervisor-ja in njegovo implementacijo na platformo, ki temelji na Raspberry Pi 4. Dva poglavitna prispevka dela sta: model dinamičnega delovanja Supervisor-ja z uporabo diagrama prehoda stanja (STD), ter koda za njegovo implementacijo na ciljni platformi v jeziku Python skladno z zahtevami projekta. |
