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Optimum design of transmissions systems for offshore wind farms including decision making under risk

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  • Serrano González, J.
  • Burgos Payán, M.
  • Riquelme Santos, J.

Abstract

The power transmission system of an offshore wind farm constitutes the infrastructure that allows the electricity produced by the power plant to be injected into the onshore power transmission network. The design of this transmission system depends on numerous factors: the rated power of the wind farm, wind conditions at the location, the distance from the shore, the cost of electrical equipment, the price of energy, the maintenance costs, the failure rate of the equipment, and so forth. At the design stage, most of these factors remain defined with a degree of uncertainty that, in many cases, may lead to major deviations (risk) with respect to the planned economic performance of the facility. The objective for the project team of the transmission system is the determination of the most suitable configuration of the evacuation infrastructure by selecting the technology, either HVAC or HVDC, and by sizing the electrical equipment: the cables, substations or converter stations, compensation units, among other pieces. To this end, the approach developed in this work includes the assessment of a broad range of feasible scenarios (probabilistic approach) and then the selection of the optimal configuration based on a method of decision-making, taking into account the main technical and economic aspects of the infrastructure.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:renene:v:59:y:2013:i:c:p:115-127
    DOI: 10.1016/j.renene.2013.03.024
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    References listed on IDEAS

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    1. González, J. Serrano & Rodríguez, Á.G. González & Mora, J. Castro & Burgos Payán, M. & Santos, J. Riquelme, 2011. "Overall design optimization of wind farms," Renewable Energy, Elsevier, vol. 36(7), pages 1973-1982.
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    2. Tshilidzi Marwala, 2013. "Semi-bounded Rationality: A model for decision making," Papers 1305.6037, arXiv.org.
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    4. Serrano González, Javier & Burgos Payán, Manuel & Riquelme Santos, Jesús & González Rodríguez, Ángel Gaspar, 2015. "Maximizing the overall production of wind farms by setting the individual operating point of wind turbines," Renewable Energy, Elsevier, vol. 80(C), pages 219-229.
    5. Sun, Zeyi & Li, Lin & Bego, Andres & Dababneh, Fadwa, 2015. "Customer-side electricity load management for sustainable manufacturing systems utilizing combined heat and power generation system," International Journal of Production Economics, Elsevier, vol. 165(C), pages 112-119.
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    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Chaojun Ding & Tianshou Liu, 2023. "Risk Decision for a Port Shore Power Supply System Based on Cumulative Prospect Theory and an Improved Gray Target," Sustainability, MDPI, vol. 15(19), pages 1-16, September.
    12. Pousinho, H.M.I. & Esteves, J. & Mendes, V.M.F. & Collares-Pereira, M. & Pereira Cabrita, C., 2016. "Bilevel approach to wind-CSP day-ahead scheduling with spinning reserve under controllable degree of trust," Renewable Energy, Elsevier, vol. 85(C), pages 917-927.
    13. Yin, Peng-Yeng & Wu, Tsai-Hung & Hsu, Ping-Yi, 2017. "Simulation based risk management for multi-objective optimal wind turbine placement using MOEA/D," Energy, Elsevier, vol. 141(C), pages 579-597.

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