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    Electrical Equipment Fault Diagnosis And Control
    1.
    发明申请
    Electrical Equipment Fault Diagnosis And Control 有权

    公开(公告)号：US20210191341A1

    公开(公告)日：2021-06-24

    申请号：US17129270

    申请日：2020-12-21

    Applicant: Budderfly, Inc.

    Inventor： Albert Subbloie ,  Christopher J. DeBenedictis ,  Jacob Marchinus Boerma ,  William Butler ,  Jaan Leemet ,  Kenneth Scott Fassman ,  Kenneth Buda

    IPC: G05B13/02 ,  G01R19/165 ,  H02H1/00 ,  H02H7/20

    Abstract: A system for automatically learning and adapting to the energy usage of an equipment installed at a facility or many pieces of equipment at a plurality of facilities, where the system is provided with an initial baseline energy usage signature for the equipment, which is modified by measured energy usage and by at least one peripheral sensor measurement data to create a modified energy usage signature. The system uses artificial intelligence to learn and adapt the baseline energy usage signature to learn the business operation and account for external variables such as temperature variance and increased business flow or an interaction between devices. The smart system can identify when a piece of equipment falls outside of “normal” operation and determines what automatic action is to be taken for that piece of equipment.

    Facilities grid micro demand response system
    2.
    发明授权
    Facilities grid micro demand response system 有权

    公开(公告)号：US12206245B2

    公开(公告)日：2025-01-21

    申请号：US18484945

    申请日：2023-10-11

    Applicant: Budderfly, Inc.

    Inventor： Albert Subbloie ,  Christopher J. DeBenedictis ,  Kenneth Buda ,  Jaan Leemet

    IPC: H02J3/14 ,  G05B13/02 ,  G05F1/66 ,  G06Q50/06 ,  H02J3/00

    Abstract: A system and method for dynamically and automatically adjusting the load on a power grid through micro adjustments of equipment coupled to the consumer side of the power grid. The system allowing for the automatic adjustment of equipment to either decrease or increase instantaneous power demand on the grid in response to peak demands and demand valleys to smooth the demand curve on the power grid. The system able to balance demand within the grid to adjust demand within various different portions of the power grid and allowing for reducing the power buffer supplied by electric utilities to reduce waste and carbon emissions.

    Machine Learning Application To Predictive Energy Management
    3.
    发明申请
    Machine Learning Application To Predictive Energy Management 有权

    公开(公告)号：US20220121160A1

    公开(公告)日：2022-04-21

    申请号：US17563973

    申请日：2021-12-28

    Applicant: Budderfly, Inc.

    Inventor： Albert Subbloie ,  Christopher J. DeBenedictis ,  Jaan Leemet ,  Kenneth Buda

    IPC: G05B13/02 ,  G01R19/165 ,  H02H1/00 ,  H02H7/20

    Abstract: A system for automatically learning and adapting to the energy usage of an equipment operating according to a control input including at least one sensor for measuring an energy usage of the equipment an generating a baseline energy usage over time signature that is used to compare active energy usage measurements to so as to determine operational deviations. The system includes software that matches and compares equipment operation to established norms and can modify the functioning of the equipment when threshold deviations are detected. The system includes the ability to learn the functioning of the equipment and can adjust for dynamically changing conditions to avoid generation of false alerts or alarms while at the same time detecting longer term deviations that if left unchecked, could shorten the lifespan of the equipment and increase the costs associated with running the equipment.

    Machine Learning Application To Predictive Energy Management
    4.
    发明申请
    Machine Learning Application To Predictive Energy Management 有权

    公开(公告)号：US20210173358A1

    公开(公告)日：2021-06-10

    申请号：US17110961

    申请日：2020-12-03

    Applicant: Budderfly, Inc.

    Inventor： Albert Subbloie ,  Christopher J. DeBenedictis ,  Jaan Leemet ,  Kenneth Buda

    IPC: G05B13/02

    Abstract: A system for automatically learning and adapting to the energy usage of an equipment operating according to a control input including at least one sensor for measuring an energy usage of the equipment an generating a baseline energy usage over time signature that is used to compare active energy usage measurements to so as to determine operational deviations. The system includes software that matches and compares equipment operation to established norms and can modify the functioning of the equipment when threshold deviations are detected. The system includes the ability to learn the functioning of the equipment and can adjust for dynamically changing conditions to avoid generation of false alerts or alarms while at the same time detecting longer term deviations that if left unchecked, could shorten the lifespan of the equipment and increase the costs associated with running the equipment.

    Thermo Efficiency Measurement System
    5.
    发明申请
    Thermo Efficiency Measurement System 审中-公开

    公开(公告)号：US20200088433A1

    公开(公告)日：2020-03-19

    申请号：US16574944

    申请日：2019-09-18

    Applicant: Budderfly, Inc.

    Inventor： Albert Subbloie ,  Kenneth Buda ,  Jaan Leemet ,  Mark Alphonse Veikos

    IPC: F24F11/46 ,  F24F11/63

    Abstract: Systems and methods are provided for determining an energy transfer rate of a room via one or more sensors to determine a baseline efficiency measurement of a room as well as delta efficiency gains obtained by making changes to internal or external factors affecting thermal efficiency. The system further include the automatic control for various equipment associated with the room and automatic measurement based on the status of the room.

    Electrical equipment fault diagnosis and control
    10.
    发明授权
    Electrical equipment fault diagnosis and control 有权

    公开(公告)号：US11625012B2

    公开(公告)日：2023-04-11

    申请号：US17129270

    申请日：2020-12-21

    Applicant: Budderfly, Inc.

    Inventor： Albert Subbloie ,  Christopher J. DeBenedictis ,  Jacob Marchinus Boerma ,  William Butler ,  Jaan Leemet ,  Kenneth Scott Fassman ,  Kenneth Buda

    IPC: G05B15/02 ,  G05B13/02 ,  H02H1/00 ,  H02H7/20

    Abstract: A system for automatically learning and adapting to the energy usage of an equipment installed at a facility or many pieces of equipment at a plurality of facilities, where the system is provided with an initial baseline energy usage signature for the equipment, which is modified by measured energy usage and by at least one peripheral sensor measurement data to create a modified energy usage signature. The system uses artificial intelligence to learn and adapt the baseline energy usage signature to learn the business operation and account for external variables such as temperature variance and increased business flow or an interaction between devices. The smart system can identify when a piece of equipment falls outside of “normal” operation and determines what automatic action is to be taken for that piece of equipment.

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