{
  "$type": "site.standard.document",
  "description": "A system, method, and solar photovoltaic (PV) network for solar PV variability reduction with reduced time delays and battery storage optimization are described. The system includes a Moving Regression (MR) filter; a State of Charge (SoC) feedback control; and a Battery Energy Storage System…",
  "path": "/patents/1366815",
  "publishedAt": "2024-07-11T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "H02S40/38",
    "KING FAHD UNIVERSITY OF PETROLEUM AND MINERALS"
  ],
  "textContent": "A system, method, and solar photovoltaic (PV) network for solar PV variability reduction with reduced time delays and battery storage optimization are described. The system includes a Moving Regression (MR) filter; a State of Charge (SoC) feedback control; and a Battery Energy Storage System (BESS). The MR filter, SoC feedback control and BESS are configured to provide smoothing of solar PV variabilities. The MR filter is a non-parametric smoother that utilizes a machine learning concept of linear regression to smooth out solar PV variations at every time step.",
  "title": "SOLAR AND WIND ENERGY NETWORK"
}