Optimal charging and discharging control for hybrid energy storage system based on reinforcement learning
US10985572B2 · kind B2 · utility
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20Claims
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Key dates
| Filing date | Jul 22, 2019 |
| Grant date | Apr 20, 2021 |
| Priority date | — |
| Expiry date | Jul 22, 2039 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02E40/40
- WIPO fieldElectrical machinery, apparatus, energy
- WIPO sectorElectrical engineering
Abstract
Systems and methods are disclosed to manage a microgrid with a hybrid energy storage system (HESS) includes deriving a dynamic model of a bidirectional-power-converter (BPC)-interfaced HESS; applying a first neural network (NN) to estimate a system dynamic; and applying a second NN to calculate an optimal control input for the HESS through online learning based on the estimated system dynamics.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.