Power systems with solar panels and wind turbines are like a chess game: cloud cover and load changes are the opponent's moves, impossible to foresee. To maintain balance, operators used to run through dozens of scenarios (uncertainty) — that took too much time and computing power.
The new algorithm acts like a grandmaster: it doesn't just calculate options, but splits the board into independent sections and analyzes them simultaneously. The ADMM helper divides the task so each 'player' solves their piece, then the moves are coordinated. Moreover, the algorithm remembers successful strategies from past games (entropy), avoiding hopeless branches.
In tests, it managed a microgrid with solar panels and wind turbines five times faster than standard industrial solvers — and without a single outage. The first systems of this kind in the 1970s filled entire machine halls; today they fit in an inverter chip. Thanks to this speed and memory, microgrids become truly autonomous: they don't need support from cloud servers.
The ADMM method used in the algorithm was originally developed for distributed big data analysis, and now it manages real energy flows.