Grid Aggregations

Live and Forecast

Thousands of PV systems, one forecast

Estimating the aggregate power for hundreds of thousands of PV sites to improve load forecasting, manage your VPP, or beat the market

Grid Aggregations
CLOUD AND IRRADIANCE TRACKING

Tracking the world's clouds in the finest detail

Designed for Solar, from the ground up. Never rely on generic weather model data again. Solcast's real time and forecast data tracks and forecasts real clouds at a resolution of 1-2km and 5 minutes. Our irradiance data and PV power data is updated every 5 to 15 minutes, downscaled to 90 metre resolution. Aerosol and albedo effects are explicitly treated.

CUSTOMISATION

Simplify your approach with powerful customisations unique to your network

Grid Aggregations are dynamic and tailored specifically to your requirements. We model the power output from all solar PV systems in a given market, geographic or network region, creating real-time and forecast power data for each.

VISIBILITY

Achieve visibility over your network with a hardware-free solution

Actionable insights delivered with updates up to every 5 minutes, delivered in real-time. We include probabilistic forecasting outputs, to enable your team to achieve BtM visibility and model network risk.

DATA ACCESS

Improve load forecasting, reduce network risk and enable modern solutions

Build gross demand profile which capture the impacts of cloud cover on behind-the-meter solar. Identify periods of minimum demand or reverse power flows, with confidence. Transform DER from unknown to predictable and improve your load model absolute error by 5-10%.

Grid Aggregation Data Specifications

Geographic coverage

Global, except for ocean and polar regions.

Temporal coverage

Historic data: January 2007 to 7 days ago Operational data: -7 days ago to + 7 days ahead

Temporal resolution

5, 10, 15, 30 & 60 minutes (period-mean values)

Spatial resolution

90 metres (irradiance, PV power, snow soiling, cloud parameters, and other parameters across all regions)

Data parameters

  • PV Power (MW) (10th, 50th, & 90th percentile)
  • PV Power (%) (10th, 50th, & 90th percentile)

Data Access

Via the Solcast API & Solcast Web Toolkit

File Formats

JSON and CSV (CSV not recommended for automation)

Commonly Asked Questions about Grid Aggregations

The total amount of solar generation capacity and actual production in a grid is calculated by aggregating real-time power output data from all connected PV systems. Solcast Grid Aggregations applies the same method in estimating the aggregate power by combining the power output data from multiple distributed PV systems into one unified dataset. The aggregated data is beneficial for forecasting power availability, optimizing energy distribution, and ensuring grid stability.

The curve, said to resemble a duck, is a graphical representation of the gap and imbalance between solar production and peak demand over the course of a day. It shows a dip in net demand during midday when solar generation is typically highest, followed by a rise in the late afternoon and evening as solar generation decreases and demand increases. Managing the curve, especially during weather changes or solar events, is crucial for grid stability and requires efficient energy storage and demand response strategies.

Behind the meter (BTM solar) refers to energy generation or storage systems installed on the customer side of the utility meter, such as residential rooftop solar panels. These systems directly supply power to the consumer, reducing the amount of electricity drawn from the grid. To model BTM solar generation, Solcast uses its Rooftop PV model to cluster installations based on geographic locations and use satellite irradiance measurements to estimate power output.

To help ensure grid stability, having accurate aggregated solar data is crucial. To achieve this, Solcast combines high quality input data from real-time satellite imagery, multiple weather models, and advanced PV modeling algorithms for both utility-scale solar and rooftop solar. Grid aggregation data is often updated every 5 to 15 minutes to ensure that the data shows the most accurate, timely information necessary for efficient grid management. Inaccurate forecasts can lead to grid instability or price hikes in the energy market.