Abstract
Abstract Co-location of wind and tidal stream turbines provides opportunity for improved economic viability of electricity generation from these resources relative to projects exploiting each resource separately. Here co-deployment is assessed in terms of energy generation and loading of support structures. Energy yield is modelled using an eddy viscosity wake model for wind turbines and superposition of self-similar wakes for tidal turbines. A case-study of the Inner Sound of the Pentland Firth is considered. For 3.5 years of coincident resource data, 12 MW wind capacity co-located with a 20 MW tidal array results in a 70% increase in energy yield, compared to operating the tidal turbines alone. Environmental loads are modelled for a braced monopile structure supporting both a wind and tidal turbine, as well as for each system in isolation. Peak loading of the combined system is found to be driven by wind loads with greatest overturning moment occurring with the wind turbine operating at close to rated-speed and the tidal turbine close to its shutdown speed. Mean loads vary across the tidal array by 6% indicating no significant shielding effects are gained by co-locating in more sheltered regions of the array.
Highlights
In-line with the commitments signed by the 175 countries of the 2015 Paris Agreement recognising the need to significantly cut global greenhouse gas emissions [1], further expansion of large offshore wind farm deployments are expected
This study addresses co-location of wind turbines at sites being developed for tidal stream arrays, since a strong tidal stream resource will be required for tidal generation
The approach used can be applied to longer time-series, as more data becomes available. This analysis provides an indication of the relative magnitude of wind to tidal energy yield, the power variability, and when used for analysing loads, the operational conditions of the turbines during peak load events. Since this dataset is at relatively coarse spatial and temporal resolution, a linear measurecorrelate-predict (MCP) approach has been applied to the UKV data, using wind data from an hourly, 400 m resolution mesoscale Weather Research and Forecasting (WRF) model [14,15] employed over the Pentland Firth region
Summary
In-line with the commitments signed by the 175 countries of the 2015 Paris Agreement recognising the need to significantly cut global greenhouse gas emissions [1], further expansion of large offshore wind farm deployments are expected. Many planned wind farm locations require deployment in water depths greater than 30 m where traditional support structures may no longer be feasible and the required systems may have higher capital cost. D. Lande-Sudall et al / Renewable Energy 118 (2018) 627e643 including dimensions, complexity and number of support structures, as well as site-specific installation costs. Lande-Sudall et al / Renewable Energy 118 (2018) 627e643 including dimensions, complexity and number of support structures, as well as site-specific installation costs To this end, a model of the energy yield from co-located wind and tidal turbines is first presented, along with evaluation of time varying power for a casestudy farm comprising 12 MW offshore wind power capacity colocated with 20 MW tidal capacity, situated in the Inner Sound of the Pentland Firth, Scotland. The loads are compared against those acting on support structures for wind and tidal turbines in isolation
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