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Due to the energy transition in Germany and the European Union, the relevance of renewable energy is steadily increasing. Besides hydropower and solar energy, offshore and onshore wind energy already forms a major part of renewables energies and will also be further expanded in the future (COMMISSION, 2020). In addition to the investments in the expansion of renewable energy, further research and development should focus on reducing the levelized cost of energy (LCoE) of wind energy to improve its market position.
The LCoE is the average net cost of electricity generated by a power plant that converts a certain type of energy into electrical power. The LCoE is estimated as the ratio of the discounted lifetime costs (i.e. capital expenditures (CAPEX) plus operational expenditures (OPEX)) to the discounted sum of the annual energy production (AEP) over its lifetime. For an offshore wind farm, the CAPEX contain the investment costs for the structures and remaining parts of the wind farm. The OPEX include the cost related to the structural integrity management (SIM) and the operation and maintenance of the remaining parts. The AEP is a function of the number of turbines, the nominal (turbine) capacity, the nominal capacity availability factor, the turbine availability, and the feed in tariff.
Several options are available to reduce the LCoE of a wind farm. For example, the energy production can be increased by increasing the turbine availability. Another option is to optimize the SIM and thus reduce the OPEX. To study the influence of SIM on the LCoE of a wind farm, we perform a variance-based sensitivity analysis of the LCoE (Saltelli et al., 2008). In this analysis, the importance of a given parameter influencing the LCoE is measured in term of its first-order sensitivity index, which quantifies the contribution the parameter to the variance of the LCoE. The CAPEX and OPEX are decomposed into costs related to the structures and costs associated to the remaining parts of the wind farm. The mean value of the CAPEX and OPEX related to the structures and the remaining parts are determined based on a literature study. The OPEX related to the structures are assumed to be in accordance with the requirements and regulations of German Hydrographic Authority (Hydrographie, 2015). They amount to 1.6% of the total OPEX for an average scenario (Martinez-Luengo and Shafiee, 2019).
The determined sensitivity indices for the parameters influencing the LCoE are shown (Figure 1). The nominal capacity, the nominal capacity availability factor, the turbine availability factor, and the feed in tariff have the highest (first-order) sensitivity indices. The CAPEX and OPEX for the wind turbine support structures have small sensitivity indices. It can be concluded that an optimization of the SIM may have negligible influence on the LCoE. However, an extension of the service life by means of structural health information (Thöns et al., 2017) may have an effect due to its reasonable influence on the LCoE .
One crucial metric of interest to wind farm operators is the remaining useful life (RUL) of single components, wind turbines, or even entire wind farms. Occasionally, questions arise regarding how to operate a turbine, even in the presence of manufacturing or design errors, which from a computational design standpoint reduce the remaining lifetime below the intended service life. A typical measure involves adapting the monitoring and inspection plan. Using such a maintenance plan, the author intends to simulate the lifetime of jacket-type structure in a fatigue test. The objective of the experiment is to demostrate that systems like three-dimensional jackets possess redundancies that enable reliable continued operation, despite the reduced fatigue life of individual components due to technical flaws, if an appropriate maintenance concept is in place. This presentation discusses the steps leading to the procedure of the experiment including the design process and the maintenance planning.