Nature

Probabilistic day-ahead forecasting of system-level renewable energy and electricity demand

Addressing these challenges introduced by the uncertainty in the electricity demand and the VRE generation requires characterizing the relation between weather and energy accurately 20, identifying ...
Nature

Probabilistic sunspot predictions with a gated recurrent units-based combined model guided by pinball loss

Predicting the amplitude of the solar cycle, along with its maximum and minimum times, is a fundamental endeavor in solar physics. Governed by the sun’s magnetic field, the solar cycle wields ...
pv magazine International

Ultra-short-term PV forecasting based on convolutional neural network, long short-term memory

Scientists have created a novel probabilistic model for 5-minutes ahead PV power forecasting. The method combines a convolutional neural network with bidirectional long short-term memory, attention ...
Grist

Traditional weather forecasting is slow and expensive. AI could help.

Every day, meteorologist Hannah Wangari takes the free graphs and maps produced by the five forecasting models she subscribes to and interprets what she sees. “What’s the likelihood of rain in ...
The New York Times

Google Introduces A.I. Agent That Aces 15-Day Weather Forecasts

GenCast, from the company’s DeepMind division, outperformed the world’s best predictions of deadly storms as well as everyday weather. By William J. Broad William J. Broad reported earlier this year ...
Insider Monkey

Implied Probability Is the Only Forecast You Can Audit

Markets are full of predictions that cannot be checked until after the fact. Implied probability is different. It is already priced, already quantified, and therefore testable. When you translate a ...