发明名称 |
Systems and Methods for Optimizing Energy Usage Using Energy Disaggregation Data and Time of Use Information |
摘要 |
The present invention is generally directed to systems and methods for optimizing energy usage in a household. For example, methods for optimizing energy usage in a household may include steps of: receiving, using an energy optimization device, entire energy profile data associated with the household; obtaining, using the energy optimization device, time of use (TOU) energy pricing structure; processing, the entire energy profile data to generate disaggregated appliance level data related to one or more appliances used in the household; retrieving historical patterns of energy usage of the household during both peak and non-peak time periods; applying a behavior shift analysis on the disaggregated data based at least in part on the TOU energy pricing structure, disaggregated data, and historical patterns of the energy usage; and predicting potential energy savings based at least in part on the behavior shift analysis. |
申请公布号 |
US2016070286(A1) |
申请公布日期 |
2016.03.10 |
申请号 |
US201514845189 |
申请日期 |
2015.09.03 |
申请人 |
Gupta Abhay;Garud Vivek |
发明人 |
Gupta Abhay;Garud Vivek |
分类号 |
G05F1/66;G05B13/02 |
主分类号 |
G05F1/66 |
代理机构 |
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代理人 |
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主权项 |
1. A method for optimizing energy usage in a household, the method comprising:
receiving, using an energy optimization device, entire energy profile data associated with the household; obtaining, using the energy optimization device, time of use (TOU) energy pricing structure; processing, using the energy optimization device, the entire energy profile data to generate disaggregated appliance level data related to one or more appliances used in the household; retrieving, using the energy optimization device, historical patterns of energy usage of the household during both peak and non-peak time periods; applying a behavior shift analysis on the disaggregated data based at least in part on the TOU energy pricing structure, disaggregated data, and historical patterns of the energy usage; and predicting potential energy savings based at least in part on the behavior shift analysis. |
地址 |
Cupertino CA US |