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Impact of Electrical Topology, Capacity Factor and Line Length on Economic Performance of Offshore Wind Investments

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  • Sadik Kucuksari

    (Department of Technology, University of Northern Iowa, Cedar Falls, IA 50614, USA
    These authors contributed equally to this work.)

  • Nuh Erdogan

    (Marine and Renewable Energy Centre, University College Cork, P43 C573 Cork, Ireland
    These authors contributed equally to this work.)

  • Umit Cali

    (Department of Engineering Technology and Construction Management, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
    These authors contributed equally to this work.)

Abstract

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.

Suggested Citation

  • Sadik Kucuksari & Nuh Erdogan & Umit Cali, 2019. "Impact of Electrical Topology, Capacity Factor and Line Length on Economic Performance of Offshore Wind Investments," Energies, MDPI, vol. 12(16), pages 1-21, August.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:16:p:3191-:d:259255
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    1. Houghton, T. & Bell, K.R.W. & Doquet, M., 2016. "Offshore transmission for wind: Comparing the economic benefits of different offshore network configurations," Renewable Energy, Elsevier, vol. 94(C), pages 268-279.
    2. Ahmed Al Ameri & Aouchenni Ounissa & Cristian Nichita & Aouzellag Djamal, 2017. "Power Loss Analysis for Wind Power Grid Integration Based on Weibull Distribution," Energies, MDPI, vol. 10(4), pages 1-16, April.
    3. Korompili, Asimenia & Wu, Qiuwei & Zhao, Haoran, 2016. "Review of VSC HVDC connection for offshore wind power integration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1405-1414.
    4. Ruddy, Jonathan & Meere, Ronan & O’Donnell, Terence, 2016. "Low Frequency AC transmission for offshore wind power: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 75-86.
    5. Kim, Ji-Young & Oh, Ki-Yong & Kang, Keum-Seok & Lee, Jun-Shin, 2013. "Site selection of offshore wind farms around the Korean Peninsula through economic evaluation," Renewable Energy, Elsevier, vol. 54(C), pages 189-195.
    6. Serrano González, J. & Burgos Payán, M. & Riquelme Santos, J., 2013. "Optimum design of transmissions systems for offshore wind farms including decision making under risk," Renewable Energy, Elsevier, vol. 59(C), pages 115-127.
    7. Salo, Olli & Syri, Sanna, 2014. "What economic support is needed for Arctic offshore wind power?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 343-352.
    8. Nieradzinska, K. & MacIver, C. & Gill, S. & Agnew, G.A. & Anaya-Lara, O. & Bell, K.R.W., 2016. "Optioneering analysis for connecting Dogger Bank offshore wind farms to the GB electricity network," Renewable Energy, Elsevier, vol. 91(C), pages 120-129.
    9. Saidur, R. & Islam, M.R. & Rahim, N.A. & Solangi, K.H., 2010. "A review on global wind energy policy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(7), pages 1744-1762, September.
    10. De Prada Gil, Mikel & Domínguez-García, J.L. & Díaz-González, F. & Aragüés-Peñalba, M. & Gomis-Bellmunt, Oriol, 2015. "Feasibility analysis of offshore wind power plants with DC collection grid," Renewable Energy, Elsevier, vol. 78(C), pages 467-477.
    11. Staffell, Iain & Pfenninger, Stefan, 2016. "Using bias-corrected reanalysis to simulate current and future wind power output," Energy, Elsevier, vol. 114(C), pages 1224-1239.
    12. Dicorato, M. & Forte, G. & Pisani, M. & Trovato, M., 2011. "Guidelines for assessment of investment cost for offshore wind generation," Renewable Energy, Elsevier, vol. 36(8), pages 2043-2051.
    13. Serrano González, Javier & Burgos Payán, Manuel & Santos, Jesús Manuel Riquelme & González-Longatt, Francisco, 2014. "A review and recent developments in the optimal wind-turbine micro-siting problem," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 133-144.
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    Cited by:

    1. Javier Serrano González & Bruno López & Martín Draper, 2021. "Optimal Pitch Angle Strategy for Energy Maximization in Offshore Wind Farms Considering Gaussian Wake Model," Energies, MDPI, vol. 14(4), pages 1-18, February.
    2. Lingling Bin & Haiyang Pan & Li He & Jijian Lian, 2019. "An Importance Analysis–Based Weight Evaluation Framework for Identifying Key Components of Multi-Configuration Off-Grid Wind Power Generation Systems under Stochastic Data Inputs," Energies, MDPI, vol. 12(22), pages 1-22, November.
    3. Deveci, Muhammet & Cali, Umit & Kucuksari, Sadik & Erdogan, Nuh, 2020. "Interval type-2 fuzzy sets based multi-criteria decision-making model for offshore wind farm development in Ireland," Energy, Elsevier, vol. 198(C).
    4. Darya Pyatkina & Tamara Shcherbina & Vadim Samusenkov & Irina Razinkina & Mariusz Sroka, 2021. "Modeling and Management of Power Supply Enterprises’ Cash Flows," Energies, MDPI, vol. 14(4), pages 1-17, February.
    5. Mingyu Li & Dongxiao Niu & Zhengsen Ji & Xiwen Cui & Lijie Sun, 2021. "Forecast Research on Multidimensional Influencing Factors of Global Offshore Wind Power Investment Based on Random Forest and Elastic Net," Sustainability, MDPI, vol. 13(21), pages 1-19, November.
    6. Francisco Haces-Fernandez, 2020. "Wind Energy Implementation to Mitigate Wildfire Risk and Preemptive Blackouts," Energies, MDPI, vol. 13(10), pages 1-19, May.
    7. Shengjin Wang & Hongru Yang & Quoc Bao Pham & Dao Nguyen Khoi & Pham Thi Thao Nhi, 2020. "An Ensemble Framework to Investigate Wind Energy Sustainability Considering Climate Change Impacts," Sustainability, MDPI, vol. 12(3), pages 1-17, January.

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