期刊
RENEWABLE ENERGY
卷 170, 期 -, 页码 1308-1323出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.renene.2021.02.032
关键词
Tidal-stream energy; Power curve; Resource; Optimisation; Renewable energy
资金
- SEEC (Smart Efficient Energy Centre) at Bangor University - European Regional Development Fund (ERDF)
- EPSRC METRIC fellowship [EP/R034664/1]
- Swedish Energy Agency
- Bangor University, as part of the PRIMARE SRV
- EPSRC [EP/R034664/1] Funding Source: UKRI
The study utilized a standardized power curve and global tidal data for the prediction and assessment of tidal-stream energy resources. It was found that there is an optimal match between turbine rated speed and maximum current speed, but this varies in different scenarios. Optimization design for firm power can increase the capacity factor, impacted by tidal form and maximum current speed.
Tidal-stream energy resource 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 h), 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. (C) 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.
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