Prescriptive Analytics to Optimize Power Grid Operations and Planning Based On Energy Storages and Human Energy Behaviour in Northern Norway

Dette industrielle PhD-prosjektet er et samarbeid mellom Arva AS og UiT, Norges arktiske universitet. I dette prosjektet vil vi forske på hvordan man kan optimalisere bruket av batterier tilknyttet strømnettet når disse leverer flere nettjenester. Prosjektet søker å vurdere hvordan batteriapplikasjoner kan støtte nettet i å møte økt energibehov på en mer kostnadsoptimal måte (sammenlignet med tradisjonelle metoder). På grunn av det grønne skiftet og generell vekst i kraftetterspørselen, er investeringer i ny kapasitet i strømnettet, som kraftlinjer og transformasjonsstasjoner, nesten uunngåelige. Det er både svært kostbart, tar tid å bygge, og har visse miljø- og samfunnsutfordringer. Gjennom dette arbeidet tar vi sikte på å gi netteiere billigere og potensielt raskere alternativer for å legge til rette for økt energietterspørsel som erstatning eller supplement til ny infrastruktur, ved hjelp av optimaliseringsmodeller for batterisystemer.

This industrial PhD project is a collaboration between Arva AS and UiT The Arctic University of Norway. We will research how large batteries, as well as other energy storage technologies and the nudging of human energy behavior can be utilized to benefit the power grid in the most optimal way. Due to the green shift and general growth in power demand, investments in new grid infrastructure capacity, such as power lines and transformation stations, are necessary. This is very costly, takes time to build, and induces certain environmental problems. Through this work, we aim at providing the regional power system operators with alternatives to facilitate an increased electricity consumption. We will do so by building a knowledge foundation for all parts involved, construct methodologies and develop new applied tools within prescriptive analytics. Focus will be on two locations in Northern Norway with different grid problems, Northern-Senja and Tromsøya. At Northern-Senja, Arva has newly installed two battery energy storage systems (BESS) and the PhD project will use data and experience for operating those. Using methods in energy modelling and multi-objective optimization with elements of machine learning, we will develop decision support tools that optimally allocate the battery capacity for different grid applications, as to maximize profit and grid system support. Such trade-off task is also referred to as value stacking. At Tromsøya our methods will be adapted and further developed with long-term decision support for new BESS investments. The tool will incorporate the results of optimal BESS operation, in addition to new research results. Those results include optimization of sector-coupling effects between the electricity grid, hydrogen, and district heating as well as the use of strategic nudging tools for the human energy behavior. In summary, the objective is to improve short-term grid operations and reduce long-term infrastructure investments.