Hybrid Reinforcement Learning (RL) to Control a Water Distribution Network

    公开(公告)号:US20250021060A1

    公开(公告)日:2025-01-16

    申请号:US18760741

    申请日:2024-07-01

    Applicant: Autodesk, Inc.

    Abstract: A method and system control a water distribution network. A database is maintained of prior states based on a residential water demand, a tank level, and an energy tariff. A current state of the water distribution network is determined. Rewards are determined and include a tank level constraint, an energy cost, and a toggle count. A query based model is used to determine a set of control points used to control a first prior state. An RL agent is trained based on the prior states and rewards. The RL agent determines a control setpoint (that changes the pump speed) that maintains the tank level, minimizes the energy cost, and complies with the toggle count. The RL agent determines time slots and selects one of the time slots. Hybrid setpoints are generated to control the water distribution network within the selected time slot.

Patent Agency Ranking