-
公开(公告)号：US11859846B2
公开(公告)日：2024-01-02
申请号：US17318877
申请日：2021-05-12
IPC分类号： F24F11/63 , G05B19/042 , G06Q50/06 , G06N20/10
CPC分类号： F24F11/63 , G05B19/042 , G06N20/10 , G06Q50/06
摘要： A heating, ventilation, and air conditioning (HVAC) fault prediction system for a building including a processing circuit including a processor and memory, the memory having instructions stored thereon that, when executed by the processor, cause the processing circuit to receive HVAC data relating to a plurality of HVAC components, the HVAC data indicating performance of the plurality of HVAC components, generate, based on the received HVAC data, a univariate prediction model and a multivariate prediction model, generate, using the received HVAC data, one or more predicted operational parameters for the plurality of HVAC components corresponding to a future time period, and execute at least one of the univariate prediction model or the multivariate prediction model on the one or more predicted operational parameters to predict a HVAC fault associated with at least one of the plurality of HVAC components to occur during the future time period.
-
2.发明授权公开(公告)号：US11163271B2
公开(公告)日：2021-11-02
申请号：US16115282
申请日：2018-08-28
发明人： Young M. Lee , William N. Schroeder
摘要： A building energy system includes an energy storage system (ESS) configured to store energy received from an energy source and provide the stored energy to one or more pieces of building equipment. The system includes a local building system configured to collect building data and communicate the building data to a cloud platform and the cloud platform configured to receive the building data from the local building system via the network, determine whether to retrain a trained load prediction model based on at least some of the building data, retrain the trained load prediction model based on at least some of the building data in response to a determination to retrain the trained load prediction model, determine a load prediction for the building based on the retrained load prediction model, and cause the local building system to operate.
-
公开(公告)号：US20210190364A1
公开(公告)日：2021-06-24
申请号：US16725961
申请日：2019-12-23
发明人： Young M. Lee , Zhanhong Jiang , Viswanath Ramamurti , Sugumar Murugesan , Kirk H. Drees , Michael James Risbeck
摘要： Systems and methods for training a reinforcement learning (RL) model for HVAC control are disclosed herein. Simulated experience data for the HVAC system is generated or received. The simulated experience data is used to initially train the RL model for HVAC control. The HVAC system operates within a building using the RL model and generates real experience data. A determination may be made to retrain the RL model. The real experience data is used to retrain the RL model. In some embodiments, both the simulated and real experience data are used to retrain the RL model. Experience data may be sampled according to various sampling functions. The RL model may be retrained multiple times over time. The RL model may be retrained less frequently over time as more real experience data is used to train the RL model.
-
公开(公告)号：US20190302157A1
公开(公告)日：2019-10-03
申请号：US16366862
申请日：2019-03-27
发明人： Steven R. Vitullo , Youngchoon Park , Sudhi R. Sinha , Karl Reichenberger , Young M. Lee , Ada L. Ma
摘要： The present disclosure is directed to a method for performing energy analytics in a building management system. The method can include collecting respective data samples of one or more variables from building equipment during a first period of time and a second period of time. The method can include calculating a first plurality of values for one or more energy audit metrics based on the data samples collected during the first period of time and the second period of time. The method can include comparing the first plurality of values and second plurality of values. The method can include displaying, based on the comparison, at least one of the first plurality of values and/or at least one of the second plurality of values on a dashboard to facilitate adjustment of the one or move variables.
-
公开(公告)号：US11268996B2
公开(公告)日：2022-03-08
申请号：US16366862
申请日：2019-03-27
发明人： Steven R. Vitullo , Youngchoon Park , Sudhi R. Sinha , Karl Reichenberger , Young M. Lee , Ada L. Ma
摘要： The present disclosure is directed to a method for performing energy analytics in a building management system. The method can include collecting respective data samples of one or more variables from building equipment during a first period of time and a second period of time. The method can include calculating a first plurality of values for one or more energy audit metrics based on the data samples collected during the first period of time and the second period of time. The method can include comparing the first plurality of values and second plurality of values. The method can include displaying, based on the comparison, at least one of the first plurality of values and/or at least one of the second plurality of values on a dashboard to facilitate adjustment of the one or move variables.
-
公开(公告)号：US20210373509A1
公开(公告)日：2021-12-02
申请号：US16885959
申请日：2020-05-28
发明人： Surajit Borah , Santle Camilus , ZhongYi Jin , Vish Ramamurti , Young M. Lee , Jason B. Koh
摘要： A building system including one or more memory devices configured to store instructions thereon that, when executed by one or more processors, cause the one or more processors to receive training data including acronym strings and tag strings, train a statistical model based on the training data, receive an acronym string for labeling, the acronym string comprising a particular plurality of acronyms, and generate a tag string for the acronym string with the statistical model, wherein the statistical model outputs a tag of the tag string for one acronym of the particular plurality of acronyms based on the one acronym and contextual information of the acronym string, wherein the contextual information includes other acronyms of the particular plurality of acronyms, wherein the statistical model implements a many to many mapping between the particular plurality of acronyms and a plurality of target tags.
-
公开(公告)号：US20210056452A1
公开(公告)日：2021-02-25
申请号：US16549037
申请日：2019-08-23
发明人： Sugumar Murugesan , Young M. Lee
摘要： A building system for building data point prediction, the building system comprising one or more memory devices configured to store instructions, that, when executed by one or more processors, cause the one or more processors to receive first building data for a building data point of a building and generate training data, the training data comprising a probability distribution sequence comprising a first probability distribution for the building data point. The instructions cause the one or more processors to train a prediction model based on the training data, receive second building data for the building data point, and predict, for one or more time-steps into the future, one or more second probability distributions with the second building data based on the prediction model, each of the one or more second probability distributions being a probability distribution for the building data point at one of the one or more time-steps.
-
公开(公告)号：US20210056386A1
公开(公告)日：2021-02-25
申请号：US16549656
申请日：2019-08-23
发明人： Sugumar Murugesan , Young M. Lee
摘要： A building system for generating input forecast data. The building system comprising one or more memory devices configured to store instructions thereon that, when executed by one or more processors, cause the one or more processors to retrieve a current prediction set of measurements comprising current values associated with a plurality of time-steps; identify time-steps of the plurality of time-steps for which historical prediction values of a historical prediction set of measurements are outside of a tolerance of corresponding historical actual values of a historical actual set of measurements; replace each current value of the current prediction set of measurements that is associated with the identified time-steps with a predetermined value to generate an updated prediction set of measurements; and provide the updated prediction set of measurements to a prediction model.
-
9.发明申请公开(公告)号：US20200073342A1
公开(公告)日：2020-03-05
申请号：US16115282
申请日：2018-08-28
发明人： Young M. Lee , William N. Schroeder
摘要： A building energy system includes an energy storage system (ESS) configured to store energy received from an energy source and provide the stored energy to one or more pieces of building equipment. The system includes a local building system configured to collect building data and communicate the building data to a cloud platform and the cloud platform configured to receive the building data from the local building system via the network, determine whether to retrain a trained load prediction model based on at least some of the building data, retrain the trained load prediction model based on at least some of the building data in response to a determination to retrain the trained load prediction model, determine a load prediction for the building based on the retrained load prediction model, and cause the local building system to operate.
-
公开(公告)号：US11669794B2
公开(公告)日：2023-06-06
申请号：US16841328
申请日：2020-04-06
IPC分类号： G06F16/245 , G06F16/29 , G06F17/15 , G06F17/18 , G06Q10/0635
CPC分类号： G06Q10/0635 , G06F16/245 , G06F16/29 , G06F17/15 , G06F17/18
摘要： A building risk analysis system including one or more memory devices storing instructions thereon, that, when executed by one or more processors, cause the one or more processors to receive threats, each of the threats including a location, wherein each of the threats are threats of a particular threat category, determine a number of threats for each of geographic areas based on the location of each of the threats, and generate a distribution based on the number of threats for each of the geographic areas. The instructions further cause the one or more processors to determine a risk score for each of the geographic areas based on one or more characteristics of the distribution and the number of threats for each of the geographic areas.
-
-
-
-
-
-
-
-
-
搜索结果
33 条记录 (耗时 0.02 秒)
