Offshore wind power offers a viable solution to the challenge of reducing fossil fuel dependency. However, certain offshore wind projects encounter challenges in meeting expected returns, particularly over the medium to long term. This study addresses the discrepancy between assumed and actual cost behaviors in techno-economic assessments of wind farm projects. The present study evaluates their impact of operational loss trends (eg increased failure rates, aging, potential curtailment) on project viability through a comprehensive techno-economic assessment. To this end, key metrics including Net Present Value and Levelized Cost of Energy, complemented by stochastic analyzes are explored through Monte Carlo Simulation and sensitivity analysis. Results indicate that costs may exceed those of the reference scenario by up to 21.6% in the worst-case scenario, highlighting the critical need for proactive monitoring and management of operational losses.
This paper presents the methods developed and key findings of the IWEC project performed by Ocean Harvesting Technologies AB (OHT). It aimed to reduce the levelized cost of energy (LCoE) of OHT’s wave energy converter InfinityWEC, by analysing how different key parameters impact cost and annual output using a model of a 100-MW array installation. Component-level cost functions were developed and mapped to key parameters and constraints of the system. A large number of system configurations were then evaluated with a numerically efficient 3 degree-of-freedom (DoF) nonlinear radiationdiffraction model in WEC-Sim along with OHT’s sea statetuned polynomial reactive control (PRC). The most promising configurations were identified and investigated in more detail. The configuration with the best LCoE were finally identified and analysed further, including estimation of the effect of changing the PRC to model predictive control, which resulted in 17-34% higher annual output and 12-23% lower LCoE. The final LCoE was found to be 93-162 EUR MWh at 100 MW installed capacity. An important finding from the study is that using simplified metrics such as CAPEX/ton was found to be irrelevant. Numerical wave tank testing, high-fidelity computational fluid dynamics (CFD), were used to tune the viscous drag of the 3 DoF WEC-Sim model. Applying verification and validation (V&V) techniques the CFD simulations showed a relatively large numerical uncertainty, but the average power and the motion responses were found to be sufficiently accurate.
The levelized costs of energy (LCoE) of wave power is still not fully competitive with other sources of renewable energy. However, wave energy is partly in a different phase than other renewable energy types and could thus contribute to a better predictability and smoothed power output. This work focuses on co-location of wave and wind power by investigating the intermittency of wind and waves power based on measured historical data from several hundreds of locations worldwide. Employing wind power curves and wave power matrices, the sites are evaluated based on several different metrics. The results indicate that there are several spots where wave power has a much lower intermittency than wind power providing reliable energy supply. Best sites for co-location in terms of energy yield were found in North-Western Europe. However, both wind and wave production have the same seasonal variability in these sites. Only a handful of sites found in California showed the possibility of seasonal power smoothing using the combination of wind and wave.