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MODELING, SIMULATION AND OPTIMIZATION OF A SUBMERGED RENEWABLE STORAGE SYSTEM INTEGRATED TO A FLOATING WIND FARM: A feasibility case study on the Swedish side of the Baltic sea, based on the geographical and wind conditions
Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
2019 (engelsk)Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
Abstract [en]

Mathematical modeling and simulations of a submerged renewable storage system integrated to a wind farm, chosen based on the geographical and wind conditions at the Baltic Sea, gives insight on the feasibility of the submerged renewable storage and an approximation of the payback period and profits that could be generated. Genetic Algorithms were used to obtain the optimal number of spheres for a certain depth, based on 2 objective functions I.e. Minimum Life Cycle Cost (LCC) and maximum reduction in wind curtailment. The new arrangement concept shows that the Initial Capital Cost (ICC) could be decreased by 25% to 60% depending upon the number of sphere employed. Based on the inputs considered in the study, the results prove that the submerged renewable storage system would be feasible, and the profits ranging from 15 Million Euro to 29 Million Euro can be achieved at the chosen location, towards the Swedish side of the Baltic sea. Although, in a real life scenario it is assumed that only up to half of the profits obtained in the results would be achievable. The results also show that, the Pump/Turbine with a high turbine efficiency and lower pump efficiency, generated better profits, compared to a Pump/Turbine running with a higher pump efficiency and lower turbine efficiency. An attempt to increase the round-trip efficiency by adding a multi stage submersible pump, resulted in additional ICC and LCC, which saw a decrease in profits. 

sted, utgiver, år, opplag, sider
2019. , s. 73
Emneord [en]
Renewable ocean storage, storage spheres, Baltic Sea, Pumped Hydro, Modeling, Simulation, Optimization, Offshore wind farm, Storage sphere Integration, feasibility study, Genetic Algorithm, Multiple objective function, Life cycle cost, Payback period, Profit
HSV kategori
Identifikatorer
URN: urn:nbn:se:mdh:diva-42321OAI: oai:DiVA.org:mdh-42321DiVA, id: diva2:1279493
Fag / kurs
Energy Engineering
Presentation
2018-12-19, Naxos, Högskoleplan 1, Västerås, 722 20, 09:15 (engelsk)
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Examiner
Tilgjengelig fra: 2019-01-20 Laget: 2019-01-16 Sist oppdatert: 2019-01-20bibliografisk kontrollert

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