Optimum sizing of offshore wind farm export cables. (December 2019)

• Record Type: Journal Article
• Authors: Pérez-Rúa, Juan-Andrés; Das, Kaushik; Cutululis, Nicolaos A.
• Is Part Of: International journal of electrical power & energy systems. Volume 113(2019)
• Page Start: 982
• Page End: 990
• Publication Date: 2019-12
• Subjects: Offshore wind energy -- AC transmission cables -- Optimization -- Dynamic temperature estimation -- Electro-thermal stress -- Probabilistic lifetime estimation; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2019.06.026
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Cable optimization is a fundamental driver for offshore wind energy cost reduction. Thermodynamic modelling is essential for cable optimization in offshore wind farms. Electro-thermal stress analysis in cables brings deeper insights on performance and reliability assessment. The effect of power, length, and temperature on cables lifetime must be quantified. Cable optimization must be carried out combining investment and reliability analysis. Abstract: A methodology for optimum sizing of offshore wind farms high voltage AC export cables is presented. The method uses as main input site-dependent time series of wind power generation and seabed temperature, in order to apply Dynamic Temperature Estimation (DTE) analysis using a Thermo-Electrical Equivalent model (TEE), followed by an estimation of loss-of-life fractions in the insulation materials through a probabilistic lifetime model, known as Arrhenius-IPM. The lifetime estimation takes into consideration the effects of cable total length: the high capacitive currents and the statistical volume enlargement law. Furthermore, the cable lifetime is inferred based on the accumulated ageing effects previously quantified. The methodology is embedded in an optimization framework which provides a transparent, flexible, and scalable formulation. Finally, the applicability of the method is illustrated through a case study, complemented with a sensitivity analysis targeting the main parameters. Results show that a reduction of the objective function of around 5 % is achieved when using the proposed methodology.