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Semantic data modelling with graph databases enabling interoperability in smart grids : master thesis
ID Dervišević, Amila (Author), ID Zajc, Matej (Mentor) More about this mentor... This link opens in a new window, ID Suljanović, Nermin (Comentor)

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Abstract
The process of digitalisation of the electricity supply chain and introduction of the smart grid as a concept that will facilitate inclusion of renewable energy resources and electrical vehicles into the existing power grid, led to a significant increase of data generation and information exchange between stakeholders. Each stakeholder or entity in the electricity domain can use a different approach to model data which poses a challenge for data interoperability between them. Some business use cases and applications require data from different sources at various locations, making this problem even more difficult. This master thesis addresses the described problem by investigating semantic modelling of electricity data and storing this data in graph databases for further fast and reliable information retrieval. The Common Information Model (CIM) enables semantic interoperability of electricity data related to different process and time scales from real-time to long-term planning (e.g. grid models, measurements, market data etc). Originating from the classification of electricity data, CIM ontology for semantic data modelling is overviewed in this thesis. Since Resource Description Framework (RDF) represents the efficient mean of data serialization on Semantic Web and currently big electricity data is commonly serialized in this format, an effort is given to deep understanding of RDF. In the next step, this thesis investigates methodology for storing data serialized as an RDF/XML file into a graph database as well as approaches for data retrieval from databases requested by other business processes. In order to enable combining electricity data with other data available at Semantic Web (e.g. weather data, Google maps etc), the work presented in this thesis will leverage semantic query languages for electricity data retrieval from database. In the scope of the practical work of this thesis, distribution grid models in RDF format will be deployed in two graph databases with different designs (Neo4j and GraphDB) and their performances with standard KPIs (key performance indicators) for databases will be compared. The master thesis contributes to the overall investigation of semantic data modelling and data interoperability in the electricity domain, as a crucial component for wider deployment of smart grid technologies in the future.

Language:English
Keywords:CIM, smart grid, big data, Internet of Things (IoT), ICT, interoperability, graph database, RDF
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FE - Faculty of Electrical Engineering
Place of publishing:Ljubljana
Publisher:[A. Dervišević]
Year:2021
Number of pages:XXVI, 95 str.
PID:20.500.12556/RUL-124822 This link opens in a new window
UDC:621.31(043.3)
COBISS.SI-ID:69298691 This link opens in a new window
Publication date in RUL:20.02.2021
Views:1523
Downloads:196
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Secondary language

Language:Slovenian
Title:Semantično modeliranje podatkov z grafnimi bazami za podporo interoperabilnosti v pametnih omrežjih : 2nd cycle postgraduate study programme in Electrical engineering
Abstract:
Postopek digitalizacije dobavne verige z električno energijo in uvedba pametnega omrežja kot koncepta, ki bo olajšal vključitev obnovljivih virov energije in električnih vozil v obstoječe elektroenergetsko omrežje, je privedla do znatnega povečanja podatkov in izmenjave informacij med deležniki. Vsaka zainteresirana stran ali subjekt na področju električne energije lahko z različnim pristopom oblikuje podatke, kar predstavlja izziv za njihovo interoperabilnost. Nekateri primeri poslovne uporabe in aplikacije zahtevajo podatke iz različnih virov na različnih lokacijah, kar dodatno povzroča težave. Magistrsko delo obravnava ta problem s preučevanjem semantičnega modeliranja podatkov o električni energiji in shranjevanjem teh podatkov v grafne podatkovne baze za nadaljnje hitro in zanesljivo iskanje informacij. Skupni informacijski model (CIM) omogoča semantično interoperabilnost podatkov o električni energiji, ki se nanašajo na različne procesne in časovne lestvice od realnega časa do dolgoročnega načrtovanja (npr. Mrežni modeli, meritve, tržni podatki itd.). Izhajajoči iz klasifikacije podatkov o električni energiji, CIM ontologija za semantično modeliranje podatkov je obravnana v tej nalogi. Ker okvir za opis virov (RDF) predstavlja učinkovito sredstvo za serializacijo podatkov na semantičnem spletu in so trenutno veliki podatki o električni energiji pogosto serializirani v tej obliki, si prizadevamo za globlje razumevanje RDF. V naslednjem koraku bomo preučili metodologijo za shranjevanje podatkov, serializiranih kot datoteka RDF/XML, v grafno podatkovno bazo ter pristope za iskanje podatkov iz baz podatkov, ki jih zahtevajo drugi poslovni procesi. Da bi omogočili kombiniranje podatkov o električni energiji z drugimi podatki, ki so na voljo v semantičnem spletu (npr. Vremenski podatki, Google Maps itd.), bo delo, predstavljeno v tej nalogi, uporabilo semantične poizvedbene jezike za pridobivanje podatkov o električni energiji iz baze podatkov. V okviru praktičnega dela te naloge bodo modeli distribucijskih mrež v formatu RDF postavljeni v dve grafne baze podatkov z različno zasnovo (Neo4j in GraphDB) in primerjane bodo njihove zmogljivosti s standardnimi KPI (ključni kazalniki uspešnosti) za baze podatkov. Magistrsko delo prispeva k celoviti raziskavi semantičnega modeliranja podatkov in interoperabilnosti podatkov na področju električne energije kot ključne komponente za širšo uvajanje tehnologij pametnih omrežij v prihodnosti.

Keywords:CIM, pametna omrežja, veliki podatki, Internet stvari, IKT, interoperabilnost, grafne baze podatkov, RDF

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