The energy sector faces a dual challenge of meeting increasing energy demands while the climate crisis is forcing a transition to low-carbon-emitting energy sources. Nuclear power is one such option, but its drawbacks, including high building and maintenance costs, nuclear waste disposal, and safety concerns, have resulted in the sector’s slow growth in recent years.
Renewable energy sources such as wind and solar power are now playing the key role in the energy transition, but their weather-dependent nature poses challenges to grid stability. Accurate yield predictions are crucial to maintaining the power grid system’s balance between production and consumption.
Potsdam-based startup 4cast is developing real-time forecasting platforms that leverage data science and machine-learning models to predict the electricity output of individual photovoltaic or wind plants to entire parks. This allows renewable energy producers to generate higher revenue while facilitating grid stability.
The modern era is marked by an unprecedented thirst for energy, as people have become accustomed to the abundance of electricity with greater availability than ever before. Nearly every step in the daily routine of the modern individual would be impossible without consuming substantial amounts of energy. While the energy consumed by households is significant, it pales compared to industries’ massive appetite for it.