Oceans contain rich tidal current energy, which can provide sufficient power for offshore microgrids. However, the uncertainty of tidal flow may endanger the operational reliability of an offshore microgrid. In this paper, a probabilistic prediction model of tidal current is established based on support vector quantile regression to reduce the infl...
Tidal-stream energy can be predicted deterministically, provided tidal harmonics and turbine-device characteristics are known. Many turbine designs exist, all having different characteristics (e.g. rated speed), which creates uncertainty in resource assessment or renewable energy system-design decision-making. A standardised normalised tidal-stream power-density curve was parameterised with data from 14 operational horizontal-axis turbines (e.g. mean cut-in speed was ∼30% of rated speed). Applying FES2014 global tidal data (1/16° gridded resolution) up to 25 km from the coast, allowed optimal turbine rated speed assessment. Maximum yield was found for turbine rated speed ∼97% of maximum current speed (maxU) using the 4 largest tidal constituents (M2, S2, K1 and O1) and ∼87% maxU for a “high yield” scenario (highest Capacity Factor in top 5% of yield cases); with little spatial variability found for either. Optimisation for firm power (highest Capacity Factor with power gaps less than 2 hours), which is important for problematic or expensive energy-storage cases (e.g. off-grid), turbine rated speed of ∼56% maxU was found – but with spatial variability due to tidal form and maximum current speed. We find optimisation and convergent design is possible, and our standardised power curve should help future research in resource and environmental impact assessment.