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The course ELDI1001 H22 has been successfully completed as physical lecturing format, and the students who took the course have achieved the following learning outcomes:Comprehension, analysis, assessment, and application of the basics of renewable energy systems, electrification and digitalization technologies.Knowledge and skills in designing, modeling and analyzing renewable energy systems such as wind and solar energy systems.Understanding of methods used in digitalization technologies such as blockchain technology, artificial intelligence, big data.Understanding of innovative renewable energy management and electrification concepts. The reference group report summarizes the feedback given in a reference group meeting for the course ELDI1001 H22. The meeting attendees included the course coordinator, a teaching assistant, and a reference student. The discussions in the meeting covered lectures, lab sessions, assignments, exams, and communication. The feedback included several recurring themes, such as the need for clearer communication of expectations, a reduction in lecture time, more time for lab sessions, and the addition of numerical examples on the telecommunication part. Some students also suggested adding a point of reflection on lab reports and including a reflection lecture after practical assignments. Concerns were raised about the lab report format and faulty RPIs that prevented some students from learning much in the lab sessions. Additionally, the students asked for more clarity on the curriculum, the amount of time expected for presentations, and the use of discussion tasks. The students were generally satisfied with the exam weighting and suggested that 60/40 was a good measure for next year as well. However, some students with dyslexia requested the use of bold, capital letters and space between letters for the exam. The report highlights the need for better communication of expectations, clearer instructions, more lab time, and the addition of more practical examples to help students better understand the course material.Most of the reported responses satisfied after the meeting, Some of them are not constructive or clear to be considered. Such issues are discussed in the classroom (especially during the bonus exam preparation session. Other points had been noted to be improved next year. According to the results of the assessment results, sentiments of the students and reference group response  that the course has provided students with a broad understanding of renewable energy systems, digitalization technologies, and innovative concepts related to renewable energy management and electrification.

NTNU:TIA:REST

Institutt for elektrisk energi

Department of electric energy

Ingen trykte eller håndskrevne hjelpemidler tillatt. Bestemt, enkel kalkulator tillatt.

Engelsk

Mer om vurdering

50% eksamen og 50% Prosjekt, samt obligatoriske øvinger (4 øvinger). Prosjekt 50 % består av 2 praktiske økter og 1 presentasjon.Oppgave 1: RESOppgave 2: RESOppgave 3: ElektrifiseringPraktisk økt 1: IIot og kommunikasjon med Raspberry PiOppgave 4: AI/ML med RapidminerPraktisk økt 2: Kombiner Rapidminer og AEMSPresentasjoner: Minilitteraturomtale om valgt temaHvert prosjektelement består av 10 % poeng tilsvarende.Hvert vurderingselement består av en ekvivalent på 5 %.Skriftlig eksamen og oppgave skal besvares på engelsk. Ved utsatt eksamen (kontinuasjonseksamen) kan eksamen bli endret til muntlig. Utsatt eksamen blir avholdt i august.

Faglig innhold

Fornybar energiinformatikk involverer dekarbonisering, desentralisering og digitaliseringskomponenter av neste generasjons kraftsystemer. Kurset tar sikte på å spille en veiledende rolle ved å utarbeide de grunnleggende definisjonene og prinsippene for digitalisering (digitalt skifte) og dekarbonisering (grønt skifte) under tre hoveddeler:Seksjon 1: Grunnlaget for fornybar energiteknologi (vind, sol og vannkraft) og elektrifisering (elektriske skip, elektrisk luftfart, energilagringsenheter, elektriske kjøretøyer),Del 2: Grunnleggende informasjons- og kommunikasjonsteknologi brukt for smarte nett, (Smart Grids, SCADA, Energy Management Systems, Internet of Energy og Computational Platforms for Energy Informatics)Del 3: Introduksjon til energianalyse og informatikk ved bruk av kunstig optimalisering, intelligens og blokkjedeteknologi. (Energiprognoser, bruk av kunstig intelligens i energisystemer, energiblokkjede, delingsøkonomi og fremtidige energisystemer)Studentene forventes å få kjerneferdighetene som vil være nødvendige for å tenke grunnleggende om digitale og grønne skift relaterte emner, utvikle innledende design, implementering og drifte ferdigheter ved å bruke informasjonssystemkompetansen og tverrfaglig kunnskap.

Kursmateriell

Informasjon om kurstmateriell vil bli gitt i begynnelsen av semesteret.

Læringsutbytte

Kunnskap:Etter å ha fullført dette kurset, vil studentene være i stand til å forstå, analysere, vurdere og anvende følgende:<ul><li>Grunnleggende om fornybare energisystemer, elektrifiserings- og digitaliseringsteknologier</li><li>Metoder for design, modellering og analyse av fornybare energisystemer som vind- og solenergisystemer</li><li>Metoder som brukes i digitaliseringsteknologier som blokkjedeteknologi, kunstig intelligens, big data</li><li>Forståelse av innovative konsepter for fornybar energistyring og elektrifisering.</li></ul>Ferdigheter:Etter å ha fullført dette kurset vil studenten kunne:<ul><li>Forstå viktigheten og driverne til den grønne og digitale energiomstillingen</li><li>Forstå effekten av elektrifisering på kraftsystemer og markeder</li><li>Utføre enkel analyse av hvordan ulike fornybare energisystemer fungerer</li><li>Beregne årlig energiutbytte fra ulike fornybare energiressurser</li><li>Forstå grunnleggende prinsipper for kunstig intelligens, maskinlæring og big data</li><li>Utføre enkel analyse av hvordan ulike digitaliseringsmetoder og teknologier fungerer i energidomenet</li><li>Forstå det grunnleggende om energianalyse og tidsserieprognoseverktøy ved hjelp av statistikk eller maskinlæring</li><li>Forstå hvordan blokkjedeteknologi fungerer</li></ul>

Læringsformer og aktiviteter

Forelesninger, øvingsforelesninger, obligatoriske øvinger og små prosjekter

Øvinger

Laboratorie

Fornybar energi med energiinformatikk

Elkraftteknikk

Bachelor i Elektrifisering og digitalisering

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This course had been developed from scratch. There were no similar courses or any textbooks identified which provided similar content. Therefore I decided to write a textbook that aimed to be primarily used for this course. The title of the book is "Digitalziaiton of Power Markets and Systems using Energy Informatics". We identified some further improvement points for the next years. The content will be slightly reduced to provide a better mental load challenge for the students. We would like to modify some of the assignments as well. <h2>Course Content:</h2>Renewable Energy Informatics involves decarbonization, decentralization, and digitalization components of next-generation power systems. The course aims to play a guidance role by elaborating the basic definitions and principles of digitalization (digital shift) and decarbonization (green shift) under three main sections:·       Section 1: Foundations of renewable energy technologies (wind, solar and hydropower) and electrification (Electric Ships, Electric Aviation, Energy Storage Units, Electric Vehicles),·       Section 2: Basics of information and communication technology used for smart grids, (Smart Grids, SCADA, Energy Management Systems, Internet of Energy and Computational Platforms for Energy Informatics)·       Section 3: Introduction to energy analytics and informatics using artificial optimization, intelligence, and blockchain technology. (Energy Forecasting, Use of AI in Energy Systems, Energy Blockchain, Sharing Economy &amp; Future Energy Systems)

Students are expected to gain the core skills which will be necessary to conceive the basics of the digital and green shift related topics, develop initial design, implementation and operation skills by using the information systems competencies and multi-disciplinary knowledge. <h2>Learning Outcomes: </h2>  <h3>Knowledge:</h3>After successfully completing this course, the students will be able to comprehend, analyze, assess and apply, as applicable, the following:·       Basics of renewable energy systems, electrification and digitalization technologies,·       Methods of designing, modelling and analysis of renewable energy systems such as wind and solar energy systems,·       Methods used in digitalization technologies such as blockchain technology, artificial intelligence, big data,·       Understanding of innovative renewable energy management and electrification concepts.   <h3>Skills:</h3>After completing this course the student will be able to:·       Understand the importance and drivers of green and digital energy transition,·       Understand the effect of electrification on power systems and markets,·       Perform simple analysis of how various renewable energy systems work, ·       Calculate annual energy yield from various renewable energy resources. ·       Perform basic technology economic calculations including levelized cost of energy/electricity (LCoE) and cost-benefit analysis (this part is excluded due to lack of time)·       Understand basic principles of artificial intelligence, machine learning and big data,·       Perform simple analysis of how various digitalization methods and technologies work in energy domain, ·       Understand fundamentals of energy analytics and timeseries forecasting tools using statistics or machine learning,·       Understand how blockchain technology works  In parallel to the regular course material, we (with TAs) developed the laboratory material and assignments using various elements such as IoT devices, sensors, energy management modules, PV panel, battery, and other supportive elements which are used to develop a hands-on project-based Universal PV based Energy Monitoring System. The intention was to reach the highest level (Create) in Bloom's Taxonomy domain. The developed course is defined as one of the backbone components of the newly developed ELDIG program. The entire course development process took almost 2 years.

Students presented their short projects at the end of the semester.

Anbefalte forkunnskaper

Skriftlig eksamen og mappeinnhold skal besvares på engelsk. Ved utsatt eksamen (kontinuasjonseksamen) kan eksamen bli endret til muntlig .

Renewable Energy Informatics involves decarbonization, decentralization and digitalization components of next generation power systems. The course aims to play a guidance role by elaborating the basic definitions and principles of digitalization (digital shift) and decarbonization (green shift) under three main sections:<ul><li>Section 1: Foundations of renewable energy technologies (wind, solar and hydropower) and electrification (Electric Ships, Electric Aviation, Energy Storage Units, Electric Vehicles),</li><li>Section 2: Basics of information and communication technology used for smart grids, (Smart Grids, SCADA, Energy Management Systems, Internet of Energy and Computational Platforms for Energy Informatics)</li><li>Section 3: Introduction to energy analytics and informatics using artificial optimization, intelligence and blockchain technology. (Energy Forecasting, Use of AI in Energy Systems, Energy Blockchain, Sharing Economy &amp; Future Energy Systems)</li></ul> Students are expected to gain the core skills which will be necessary to conceive the basics of the digital and green shift related topics, develop initial design, implementation and operate skills by using the information systems competencies and multi-disciplinary knowledge.

Lectures, exercise lectures, mandatory exercises and small projects will be prepared using Conceive, Design, Implement and Operate (CDIO) pedagogical convention. 

Knowledge:After successfully completing this course, the students will be able to comprehend, analyze, assess, and apply, as applicable, the following:<ul><li>Basics of renewable energy systems, electrification and digitalization technologies,</li><li>Methods of designing, modeling and analysis of renewable energy systems such as wind and solar energy systems,</li><li>Methods used in digitalization technologies such as blockchain technology, artificial intelligence, big data,</li><li>Understanding of innovative renewable energy management and electrification concepts.</li></ul> Skills:After completing this course the student will be able to:<ul><li>Understand the importance and drivers of the green and digital energy transition,</li><li>Understand the effect of electrification on power systems and markets,</li><li>Perform simple analysis of how various renewable energy systems work,</li><li>Calculate annual energy yield from various renewable energy resources.</li><li>Perform basic technology economic calculations including Levelized Cost of Energy (LCoE) and cost-benefit analysis</li><li>Understand basic principles of artificial intelligence, machine learning and big data,</li><li>Perform simple analysis of how various digitalization methods and technologies work in the energy domain,</li><li>Understand the fundamentals of energy analytics and time series forecasting tools using statistics or machine learning,</li><li>Understand how blockchain technology works</li></ul>

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Fornybar energi med energiinformatikk - ELDI1001