Renewable Resource Atlas V2: High-Resolution Solar and Wind Measurement Dataset for the Kingdom of Saudi Arabia

This official dataset, curated by the King Abdullah City for Atomic and Renewable Energy (K.A.CARE), provides foundational information for the kingdom's energy transition and smart grid initiatives. It supports stakeholders in solar and wind energy by offering reliable, ground-truthed data critical for investment and research decisions.

Core Components of the Dataset:

• Solar Radiation Monitoring: Ground stations measure the three components of solar irradiance: Direct Normal Irradiance (DNI), Global Horizontal Irradiance (GHI), and Diffuse Horizontal Irradiance (DHI), along with other relevant climatic parameters.
• Wind Resource Assessment: Specialized stations measure wind resources using anemometers at 6 different heights and wind vanes at 3 heights, alongside temperature, relative humidity, and atmospheric pressure sensors.
• Satellite-Derived Solar Estimates (SIENNA Model): A satellite-based solar resource model calibrated with high-precision ground data, providing comprehensive coverage across the country.
• Typical Meteorological Year (TMY) Data: Long-term time series analysis is used to generate TMY datasets representing typical (50th percentile) and low-radiation (90th percentile) conditions, crucial for financial feasibility analyses of energy projects.

This dataset is a prime example of how IoT sensor networks and big data analytics converge to enable smarter energy systems and planning.