Power Plant Operation Optimisation: Unit commitment of gas turbines using Machine Learning and MILP programming 2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 30 credits / 45 HE creditsStudent thesis

Sustainable development

The essay/thesis is partially on sustainable development according to the University's criteriaAlternative title

Optimización de la operación de centrales eléctricas : Asignación de unidades de turbinas de gas utilizando aprendizaje automático y programación MILP (Spanish)

Place, publisher, year, edition, pages

2018. , p. 133

Keywords [en]

Gas Turbine, CCGT, Economic Dispatch, Load Forecasting, MILP, Machine Learning, Boosted Regression Trees, Energy Systems Optimisation.

National Category

Energy Systems

Identifiers

URN: urn:nbn:se:hig:diva-27660OAI: oai:DiVA.org:hig-27660DiVA, id: diva2:1239495

External cooperation

Siemens Industrial Turbomachinery (SIT)

Subject / course

Energy systems

Educational program

Energy systems – master’s programme (two years)

Presentation

2018-08-14, 11320, Kungsbäcksvägen 47, 801 76, Gävle, 09:30 (English)

Supervisors

Examiners

Available from: 2018-08-24 Created: 2018-08-16 Last updated: 2018-08-24Bibliographically approved

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Energy system

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Energy Systems

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