IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i16p3191-d259255.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/16/3191/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/16/3191/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Satir, Mert & Murphy, Fionnuala & McDonnell, Kevin, 2018. "Feasibility study of an offshore wind farm in the Aegean Sea, Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2552-2562.
    2. Tiago A. Antunes & Rui Castro & Paulo J. Santos & Armando J. Pires, 2023. "Standardization of Power-from-Shore Grid Connections for Offshore Oil & Gas Production," Sustainability, MDPI, vol. 15(6), pages 1-21, March.
    3. Bains, Henna & Madariaga, Ander & Troffaes, Matthias C.M. & Kazemtabrizi, Behzad, 2020. "An economic model for offshore transmission asset planning under severe uncertainty," Renewable Energy, Elsevier, vol. 160(C), pages 1174-1184.
    4. Sajid Ali & Sang-Moon Lee & Choon-Man Jang, 2017. "Techno-Economic Assessment of Wind Energy Potential at Three Locations in South Korea Using Long-Term Measured Wind Data," Energies, MDPI, vol. 10(9), pages 1-24, September.
    5. 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).
    6. Wiegner, J.F. & Andreasson, L.M. & Kusters, J.E.H. & Nienhuis, R.M., 2024. "Interdisciplinary perspectives on offshore energy system integration in the North Sea: A systematic literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    7. Meng, Yongqing & Yan, Shuhao & Wu, Kang & Ning, Lianhui & Li, Xuan & Wang, Xiuli & Wang, Xifan, 2021. "Comparative economic analysis of low frequency AC transmission system for the integration of large offshore wind farms," Renewable Energy, Elsevier, vol. 179(C), pages 1955-1968.
    8. 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.
    9. Ioannou, Anastasia & Angus, Andrew & Brennan, Feargal, 2018. "A lifecycle techno-economic model of offshore wind energy for different entry and exit instances," Applied Energy, Elsevier, vol. 221(C), pages 406-424.
    10. Silvio Rodrigues & Carlos Restrepo & George Katsouris & Rodrigo Teixeira Pinto & Maryam Soleimanzadeh & Peter Bosman & Pavol Bauer, 2016. "A Multi-Objective Optimization Framework for Offshore Wind Farm Layouts and Electric Infrastructures," Energies, MDPI, vol. 9(3), pages 1-42, March.
    11. Chiang, Amy C. & Keoleian, Gregory A. & Moore, Michael R. & Kelly, Jarod C., 2016. "Investment cost and view damage cost of siting an offshore wind farm: A spatial analysis of Lake Michigan," Renewable Energy, Elsevier, vol. 96(PA), pages 966-976.
    12. Meere, Ronan & Ruddy, Jonathan & McNamara, Paul & O'Donnell, Terence, 2017. "Variable AC transmission frequencies for offshore wind farm interconnection," Renewable Energy, Elsevier, vol. 103(C), pages 321-332.
    13. Lüth, Alexandra & Werner, Yannick & Egging-Bratseth, Ruud & Kazempour, Jalal, 2024. "Electrolysis as a flexibility resource on energy islands: The case of the North Sea," Energy Policy, Elsevier, vol. 185(C).
    14. de Prada Gil, Mikel & Gomis-Bellmunt, Oriol & Sumper, Andreas, 2014. "Technical and economic assessment of offshore wind power plants based on variable frequency operation of clusters with a single power converter," Applied Energy, Elsevier, vol. 125(C), pages 218-229.
    15. McKenna, Russell & Pfenninger, Stefan & Heinrichs, Heidi & Schmidt, Johannes & Staffell, Iain & Bauer, Christian & Gruber, Katharina & Hahmann, Andrea N. & Jansen, Malte & Klingler, Michael & Landwehr, 2022. "High-resolution large-scale onshore wind energy assessments: A review of potential definitions, methodologies and future research needs," Renewable Energy, Elsevier, vol. 182(C), pages 659-684.
    16. Woochul Nam & Ki-Yong Oh, 2020. "Mutually Complementary Measure-Correlate-Predict Method for Enhanced Long-Term Wind-Resource Assessment," Mathematics, MDPI, vol. 8(10), pages 1-20, October.
    17. de Guibert, Paul & Shirizadeh, Behrang & Quirion, Philippe, 2020. "Variable time-step: A method for improving computational tractability for energy system models with long-term storage," Energy, Elsevier, vol. 213(C).
    18. Marko Hočevar & Lovrenc Novak & Primož Drešar & Gašper Rak, 2022. "The Status Quo and Future of Hydropower in Slovenia," Energies, MDPI, vol. 15(19), pages 1-13, September.
    19. Mollik, Sazib & Rashid, M.M. & Hasanuzzaman, M. & Karim, M.E. & Hosenuzzaman, M., 2016. "Prospects, progress, policies, and effects of rural electrification in Bangladesh," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 553-567.
    20. Lukas Kriechbaum & Philipp Gradl & Romeo Reichenhauser & Thomas Kienberger, 2020. "Modelling Grid Constraints in a Multi-Energy Municipal Energy System Using Cumulative Exergy Consumption Minimisation," Energies, MDPI, vol. 13(15), pages 1-23, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:16:p:3191-:d:259255. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.