Lead WRA for upcoming wind projects across the countryOpportunity to progress your career in a collaborative work environmentAbout Our Client
Our client is a well known company for its robust engineering and manufacturing capabilities and is committed to delivering innovative solutions to its clients.
Job Description
- Installation, maintenance, management, and performance of met masts and LiDAR / SODAR systems.
- Conduct QA / QC and validation of wind measurement data
- Analyze wind speed, direction, turbulence, shear, and seasonal variation using industry-standard tools (, WindPRO, WAsP, OpenWind, WindFarmer).
- Perform long-term wind data correlation using satellite datasets, data corelation and onsite measurements.
- Conduct energy production assessments (P50, P75, P90) and uncertainty analysis.
- Generate comprehensive pre-construction energy yield reports for internal approvals and external investors / lenders.
- Microsite & Optimize turbine layout based on terrain, wind flow modeling, wake loss, and micro siting studies.
- Collaborate with OEMs and site teams for turbine selection and placement.
- Carry out turbine suitability study
- Support project development teams in assessing technical feasibility and bankability of potential sites.
- Conduct third-party technical due diligence and review of external energy yield reports.
- Carry our operational re-forecast for operational projects
- Prepare Independent Energy Yield Assessment report
- Work closely with permitting, grid, construction, and commercial teams to align technical studies with overall project timelines
The Successful Applicant
- in Mechanical, Electrical, Renewable Energy, or related field. in Wind Energy or Atmospheric Science is preferred.
- Technical Proficiency : Advanced user of wind modelling tools (WindPRO, WAsP, CFD tools, WindFarmer, etc.)
- 12-15 years in wind resource assessment, preferably with an IPP, OEM, renewable energy developer, or technical consultant.
- Experience with offshore wind resource assessment (if applicable).
- Familiarity with hybrid (wind-solar-storage) modeling and co-location analysis.