{
  "$type": "site.standard.document",
  "description": "A method for probabilistic forecast of day-ahead power generation sequences of a plurality of renewable power plants. The method includes the steps of: a) for each one of a plurality of client devices, mapping its raw data input to latent features; b) transmitting a locally hosted forecasting model…",
  "path": "/patents/1389926",
  "publishedAt": "2026-06-11T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "H02J3/004",
    "City University of Hong Kong"
  ],
  "textContent": "A method for probabilistic forecast of day-ahead power generation sequences of a plurality of renewable power plants. The method includes the steps of: a) for each one of a plurality of client devices, mapping its raw data input to latent features; b) transmitting a locally hosted forecasting model in the form of the latent features and model parameters of each client device to a server; c) aggregating the locally hosted forecasting models of the plurality of client devices at the server; d) dispatching the aggregated models to the client devices; e) updating the locally hosted forecasting model on each client device based on the aggregated models; and f) generating, at each client device, power output sequence probabilistic forecasts based on the updated locally hosted forecasting model. The plurality of client devices each corresponds to a respective one of the plurality of renewable power plants. The plurality of client devices is connected to the server.",
  "title": "DATA PRIVACY PRESERVING METHOD AND SYSTEM FOR PROBABILISTIC RENEWABLE POWER GENERATION SEQUENCE FORECASTING"
}