Solar energy is predicted to be the largest form of power generation globally by 2040 and having accurate forecasts is critical to balancing the grid. Unlike fossil fuels, renewable energy resources are unpredictable in terms of power generation from one hour to the next. In order to balance the grid, operators need a close estimate of when and how much solar and wind power will be generated on a given day.

Open Climate Fix (an open source AI company) developed and deployed PVNet, a large ML model which forecasts solar generation for the next 36 hours. The forecasts are used by the UK electricity grid operator for real-time decision making and for reserve planning. These forecasts can save 300,000 tonnes of CO₂ and £30 million per year.

But how do we have a global impact? We decided to build a lightweight solar forecast that works anywhere in the world, which we showcased last year at FOSDEM. Combining this with every country's solar capacity, we are able to produce a solar forecast for every country in the world. In this talk, we'll demo our Global Forecast and discuss how this forecast can support grid transition as well as open-source renewable energy projects all over the globe.

Open Climate Fix is an open-source not for profit company using machine learning (ML) to respond to the need for accurate renewable energy forecasts. Connecting energy industry practitioners with ML researchers doing cutting-edge energy modelling is our aim, and one way we seek to do this is by making much of our code open-source.