Context-aware smart home energy manager

Abstract

A context-aware smart home energy management (CASHEM) system and method is disclosed. CASHEM dynamically schedules household energy use to reduce energy consumption by identifying contextual information within said household, selecting a comfort of service preference, wherein said comfort of service preference is based on different said contextual information, and extracting an appliance use schedule for maximum energy savings based on said contextual information in light of said comfort of service preferences, by executing a program instruction in a data processing apparatus. CASHEM correlates said contextual information with energy consumption levels to dynamically schedule said appliance based on an energy-saving condition and a user's comfort. Comfort of service preferences are gathered by CASHEM by monitoring occupant activity levels and use of said appliance. CASHEM can also recommend potential energy savings for a user to modify comfort of service preferences.

1 . A method for dynamically scheduling household energy use that reduces wasteful energy consumption, reduces peak electricity demand, integrates renewable energy and storage technology, and changes a user's behavior to manage and consume less energy, said method comprising:
 identifying contextual information within said household, by executing a program instruction in a data processing apparatus;   identifying a user preference for comfort and service within said household, by executing a program that allows said user to indicate said user preference;   selecting a comfort of service preference, wherein said comfort of service preference is based on different said contextual information and said user preference, by executing a program instruction in a data processing apparatus; and   extracting an appliance use schedule for maximum energy savings based on said contextual information, said user preference, and said comfort of service preference, by executing a program instruction in a data processing apparatus.   
     
     
         2 . The method of  claim 1  further comprising extracting a schedule for using renewable energy sources and storage batteries within said household, wherein said extracted schedule reflects said contextual information about demand response, by executing a program instruction in a data processing apparatus. 
     
     
         3 . The method of  claim 1  further comprising:
 monitoring ongoing appliance use to infer compliance with said appliance use schedule, by executing a program instruction in a data processing apparatus; and 
 dynamically modifying said appliance use schedule according to monitored contextual information and said user's evolving energy use behavior, by executing a program instruction in a data processing apparatus. 
 
     
     
         4 . The method of  claim 1  further comprising correlating said contextual information with energy consumption levels to dynamically schedule said appliance based on an energy-saving condition and a user's comfort, by executing a program instruction in a data processing apparatus. 
     
     
         5 . The method of  claim 1  further comprising coordinating an energy manager to perform at least one of the following operations:
 gathering contextual information related to environmental conditions; 
 gathering energy supply type conditions; 
 gathering cost conditions; 
 selecting a comfort of service preference; and 
 configuring an appliance use schedule. 
 
     
     
         6 . The method of  claim 5  wherein said energy manager comprises a graphical user interface and data processing apparatus, wherein said graphical user interface is configured for at least one of the following operations:
 gathering said contextual information related to user activity and a daily schedule; 
 gathering information about user comfort and service preferences; 
 displaying energy use feedback to said user; 
 displaying energy saving opportunities in compliance with said user's evolving behavior; 
 recommending use of renewable energy source and stored energy within said household; and 
 displaying incentive or motivational information to said user based on observed energy use behavior and adaptive to said user's energy use pattern. 
 
     
     
         7 . The method of  claim 1  further comprising monitoring said household's occupant activity levels and use of said appliance for configuring said appliance use schedule, by executing a program instruction in a data processing apparatus. 
     
     
         8 . The method of  claim 1  wherein said contextual information either entered by said user or via a networked device includes at least one of the following:
 current weather information; 
 forecast weather information; 
 security system information; 
 utility information; 
 renewable energy-use information; 
 energy storage information; 
 energy supply type; and 
 utility signals including at least one of the following types of signals: demand response (DR), real-time-pricing (RTP) information, time-of-use (TOU) tariff. 
 
     
     
         9 . The method of  claim 1  further comprising operating said appliance according to said appliance use schedule at a recommended level equal to a comfort of service preference for maximum energy savings, by executing a program instruction in a data processing apparatus. 
     
     
         10 . A system for dynamically scheduling household energy use that reduces wasteful energy consumption, reduces peak electricity demand, integrates renewable energy and storage technology, and changes a user's behavior to manage and consume less energy, said system comprising:
 a data-processing apparatus;   a module executed by said data-processing apparatus, said module and said data-processing apparatus being operable in combination with one another to:
 identifying contextual information within said household, by executing a program instruction in a data processing apparatus; 
 identifying a user preference for comfort and service within said household, by executing a program that allows said user to indicate said user preference; 
 selecting a comfort of service preference, wherein said comfort of service preference is based on different said contextual information and said user preference, by executing a program instruction in a data processing apparatus; and 
 extracting an appliance use schedule for maximum energy savings based on said contextual information, said user preference, and said comfort of service preference, by executing a program instruction in a data processing apparatus. 
   
     
     
         11 . The system of  claim 10  wherein said module and said data-processing apparatus are further operable in combination with one another to extract a schedule for using renewable energy sources and storage batteries in said household, wherein said extracted schedule reflects said contextual information about demand response, by executing a program instruction in a data processing apparatus. 
     
     
         12 . The system of  claim 10  wherein said module and said data-processing apparatus are further operable in combination with one another to:
 monitor ongoing appliance use to infer compliance with said appliance use schedule, by executing a program instruction in a data processing apparatus; and 
 dynamically modify said appliance use schedule according to monitored contextual information and said user's evolving energy use behavior, by executing a program instruction in a data processing apparatus. 
 
     
     
         13 . The system of  claim 10  wherein said module and said data-processing apparatus are further operable in combination with one another to correlate said contextual information with energy consumption levels to dynamically schedule said appliance based on an energy-saving condition and a user's comfort, by executing a program instruction in a data processing apparatus. 
     
     
         14 . The system of  claim 10  wherein said module and said data-processing apparatus are further operable in combination with one another to coordinate an energy manager to perform at least one of the following operations:
 gather contextual information related to environmental conditions; 
 gather energy supply type conditions; 
 gather cost conditions; 
 select a comfort of service preference; and 
 configure an appliance use schedule. 
 
     
     
         15 . The system of  claim 14  wherein said energy manager comprises a graphical user interface and data processing apparatus, wherein said module, said data-processing apparatus, and said graphical user interface are further operable in combination with one another to:
 collect said contextual information related to user activity and a daily schedule; 
 collect information about user comfort and service preferences; 
 display energy use feedback to said user; 
 display energy saving opportunities in compliance with said user's evolving behavior; 
 recommend use of renewable energy source and stored energy within said household; and 
 display incentive or motivational information to said user based on observed energy use behavior and adaptive to said user's energy use pattern. 
 
     
     
         16 . The system of  claim 12  wherein said module and said data-processing apparatus are further operable in combination with one another to monitor said household's occupant activity levels and use of said appliance to configure said appliance use schedule, by executing a program instruction in a data processing apparatus. 
     
     
         17 . The system of  claim 12  wherein said contextual information either entered by said user or via a networked device includes at least one of the following:
 current weather information; 
 forecast weather information; 
 security system information; 
 utility information; 
 renewable energy-use information; 
 energy storage information; 
 energy supply type; and 
 utility signals including at least one of the following types of signals: demand response (DR), real-time-pricing (RTP) information, time-of-use (TOU) tariff. 
 
     
     
         18 . The system of  claim 12  wherein said module and said data-processing apparatus are further operable in combination with one another to operate said appliance according to said appliance use schedule at a recommended level equal to a comfort of service preference for maximum energy savings, by executing a program instruction in a data processing apparatus. 
     
     
         19 . An apparatus comprising one or more processor readable storage devices having processor readable code on said processor readable storage devices, said processor readable code for programming one or more processor to perform a method for dynamically scheduling household energy use that reduces wasteful energy consumption, reduces peak electricity demand, integrates renewable energy and storage technology, and changes homeowner behavior to manage and consume less energy, comprising:
 identifying contextual information within said household, by executing a program instruction in a data processing apparatus;   identifying a user preference for comfort and service within said household, by executing a program that allows said user to indicate said user preference;   selecting a comfort of service preference, wherein said comfort of service preference is based on different said contextual information and said user preference, by executing a program instruction in a data processing apparatus; and   extracting an appliance use schedule for maximum energy savings based on said contextual information, said user preference, and said comfort of service preference, by executing a program instruction in a data processing apparatus.   
     
     
         20 . The apparatus of  claim 19  further comprising:
 a sensor to detect contextual information; 
 a network; and 
 an energy manager coupled to said network comprising said sensor for detecting context information, a display, said data processing apparatus, and a set of instructions for dynamically scheduling household energy use that reduces wasteful energy consumption, reduces peak electricity demand, integrates renewable energy and storage technology, and changes homeowner behavior to manage and consume less energy.