The Innovative Optimally Combined Solar Forecasts project recognises that power output of a solar farm fluctuates due to cloud motion over the site. These fluctuations impact the power system, so improved forecasts will help to integrate solar generation into the grid and reduce the cost of solar generation. This forecasting project will forecast the generation of three large scale solar farms using a new solar forecasting system developed by Australian company Proa Analytics. Every five minutes, the Proa Forecasting System (PFS) will produce an updated generation forecast for the next 5-minute period for each solar farm, as well as longer forecasts up to several days ahead. Proa’s forecasts use an innovative combination of four different technologies: skycams, satellites, live data and numerical simulations.
How the project works
The Innovative Optimally Combined Solar Forecasts project consists of the Proa Forecasting System (PFS) used for short-term solar forecasting to track and predict the motion of clouds and the impact on solar generation in Australian conditions. It consists of four individual solar forecasting techniques that are combined to produce an optimal forecast. These include three advanced and proprietary forecasting techniques developed by Proa Analytics – our methods of geostationary satellite cloud motion vectoring (CMV) algorithms, skycam CMV, and live data techniques. While each technology performs best at different time scales and weather conditions, this project aims to demonstrate the benefits of optimally combining them to maximise forecast accuracy.
Report: Proa Analytics Solar Farm Short Term Forecasting Project: Lessons Learnt 2
This Lessons Learnt Report outlines the key from the period between October 2019 – April 2020.Read the report
Report: Proa Analytics Solar Farm Short Term Forecasting Project: Lessons Learnt 1
This Lessons Learnt Report outlines the key from the period between April 2019 – October 2019.Read the report
Report: Short-Term Forecasting Trial on the NEM Progress Report
This report presents a summary of the insights and progress from initial reports submitted by the 11 participants of the Short-Term Forecasting (STF) trial that is taking place between March 2019 to mid 2021.Read the report
Area of innovation
The aims to demonstrate the improved techniques of combining the different forecast methods at short time scales. The project will also demonstrate new methods of identifying clouds at night using infrared satellite images to make accurate solar forecasts in the hours before dawn, and use an infrared skycam to provide additional information on cloud structure during the day.
The improved solar forecasts demonstrated by the project may help to integrate solar generation into the grid and to reduce the costs of existing and new solar generation. Improved solar forecasts are required to help AEMO operate the NEM with greater amounts of solar generation and help additional solar generation to enter the grid.
The project will also analyse the costs and benefits of different forecasting technologies and combinations of technologies and publish this information to the market, to help solar farms to determine the best choice of forecasting technologies that suit their technology type, size, and location.
A trial of forecasting technology has been launched to help predict the future output from wind and solar farms, which varies depending on the weather and time of day.Read more