Faculty Publications

Impact Of Electrical Topology, Capacity Factor And Line Length On Economic Performance Of Offshore Wind Investments

Document Type



Cost-benefit analysis, DC collection, Energy economics, HVAC, HVDC, Levelized cost of electricity (LCOE), Offshore wind

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In this study, an economic performance assessment of offshore wind investments is investigated through electrical topology, capacity factor and line length. First, annual energy yield production and electrical system losses for AC and DC offshore wind configurations are estimated by using Weibull probability distributions of wind speed. A cost model for calculating core energy economic metrics for offshore wind environment is developed by using a discount cash flow analysis. A case study is then conducted for a projected offshore wind farm (OWF) rated 100 MW and 300 MW sizes situated in the Aegean sea. Finally, a sensitivity analysis is performed for AC and DC OWFs with three different capacity factors (e.g., 45%, 55% and 60%) and various transmission line lengths ranging from 20 km to 120 km. The OWF is found to be economically viable for both AC and DC configurations with the estimated levelized cost of electricity (LCOE) ranging from 88.34 $/MWh to 113.76 $/MWh and from 97.61 $/MWh to 126.60 $/MWh, respectively. LCOEs for both options slightly change even though the wind farm size was increased three-fold. The sensitivity analysis reveals that, for further offshore locations with higher capacity factors, the superiority of AC configuration over the DC option in terms of LCOE reduces while the advantage of DC configuration over the AC option in terms of electrical losses is significant. Losses in the AC and DC configurations range from 3.75% to 5.86% and 3.75% to 5.34%, respectively, while LCOEs vary between 59.90 $/MWh and 113.76 $/MWh for the AC configuration and 66.21 $/MWh and 124.15 $/MWh for the DC configuration. Capacity factor was found to be more sensitive in LCOE estimation compared to transmission line length while line length is more sensitive in losses estimation compared to capacity factor.


Department of Technology

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UNI ScholarWorks, Rod Library, University of Northern Iowa