Preprints
https://doi.org/10.5194/wes-2025-55
https://doi.org/10.5194/wes-2025-55
03 Apr 2025
 | 03 Apr 2025
Status: this preprint is currently under review for the journal WES.

Locating the Optimal Wind Resource within two Californian Offshore Wind Energy Areas

Arka Mitra, Virendra Ghate, and Raghavendra Krishnamurthy

Abstract. The spatiotemporal variability of wind resource at two Californian offshore wind-energy areas (Humboldt and Morro Bay) is characterized using 23 years (2000–2022) of 2-km-resolution, hourly NOW-23 reanalysis data. Idealized power is estimated for the International Energy Agency 15 MW reference wind turbine. Wind speed and energy output are higher at Humboldt than Morro Bay and for summer months than winter months at both sites. Idealized daily energy output per turbine with one turbine within each model grid cell, peaks at 330 MWh in June for Humboldt and 300 MWh in May for Morro Bay. Energy output per turbine decreases from the oceanward to the coastward perimeter by ~20 %, dropping ~22 MWh across Humboldt and ~46 MWh across Morro Bay. Rotor-layer wind shear and veer exhibit strong seasonal variability, with summertime shear twice of wintertime shear at both sites. Daily wind resource variability is quantified through Fractional Variability (FV), defined as the ratio of the interquartile range of wind speeds/energy to the overall median value for that day of year. Locations and times with higher FV coincide with low wind-speeds (i.e., low output) for both sites. A linear optimization identifies the optimal wind resource locations (that maximizes energy output but minimizes output FV, wind shear, wind veer, and distance to shore) at the oceanward and coastward flanks of Humboldt and Morro Bay, respectively. The gradients in optimization scores are aligned parallel to the coast and are independent of the choice of power curves for rated powers of 8–16 MW.

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Arka Mitra, Virendra Ghate, and Raghavendra Krishnamurthy

Status: open (until 01 May 2025)

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Arka Mitra, Virendra Ghate, and Raghavendra Krishnamurthy

Data sets

NOW-23 National Renewable Energy Laboratory (NREL), USA https://data.openei.org/submissions/4500

15 MW Reference Wind Turbine (RWT) Power Curve National Renewable Energy Laboratory (NREL), USA https://nrel.github.io/turbine-models/IEA_15MW_240_RWT.html

Arka Mitra, Virendra Ghate, and Raghavendra Krishnamurthy

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Short summary
This study introduces a new metric to quantify the spatiotemporal variability of wind resources and a novel numerical technique to locate the optimal wind resource within a large wind farm. The new metric and the novel optimization technique are applied to assist in the pre-construction wind resource assessments of two Californian offshore wind energy areas. This optimization is stable for a diverse choice of wind turbines and is easily scalable and adaptable to any other offshore location.
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