According to some embodiments, a thermostat obtains real-time energy prices from a electricity grid. It may also obtain additional data from external data sources, such as predicted energy prices or weather predictions. The thermostat attempts to find a control strategy for when to switch available aggregates that may include furnaces and air conditioners on and off. In order to solve this integer programming problem, the thermostat uses a random search algorithm. According to some embodiments, various data sources, such as day-ahead prices and real-time prices, are combined into forecasts of electricity prices for the present and future time periods. In some embodiments, a thermostat selects predictively between heating or cooling by letting outside air in or by using heating and cooling aggregates. Additional embodiments are discussed and shown.
Claim CLM-00001. 1. An energy cost optimizer comprising an electronic data interface, a computing device, and a switch for an electric load, said computing device comprising an electronic processor and electronic memory, wherein said computing device is configured
to obtain through an electronic input of said computing device a first time series of forward-looking electricity prices for an electricity market and holding said time series in said electronic memory of said computing device, said time series comprising a plurality of said forward-looking electricity prices, with each member of said plurality corresponding to a specific time interval characterized by a start time and an end time, and each of said prices being a cost per unit of electricity, to obtain through an electronic input of said computing device a second time series of data points, said second time series of data points being a different time series than said first time series, said second time series comprising a plurality of values, with each member of said plurality corresponding to a specific time interval characterized by a start time and an end time, to compute an improved time series of estimated electricity prices, by computing on said computing device at least one price correction value using data from said second time series, and applying said price correction value to said first time series, said improved time series comprising a plurality of improved forward-looking electricity prices, with each member of said plurality corresponding to a specific time interval characterized by a start time and an end time, and each of said prices being a cost per unit of electricity, to hold said improved time series of estimated electricity prices in said electronic memory, to determine an expected benefit from running said load by evaluating a function stored in said electronic memory, and to control said electric load automatically by said computing device through said switch so as to run said load if said expected benefit from running said load at the present time exceeds said price estimate according to said improved time series.
Claim CLM-00017. 17. A method for optimizing the cost of electricity consumed by an electric load, comprising
obtaining, by a first computing device, through an electronic input of said computing device a first time series of forward-looking electricity prices for an electricity market and holding said time series in electronic memory of said computing device, said time series comprising a plurality of said forward-looking electricity prices, with each member of said plurality corresponding to a specific time interval characterized by a start time and an end time, and each of said prices being a cost per unit of electricity, obtaining, by said first computing device, through an electronic input of said computing device a second time series of data points, said second time series of data points being a different time series than said first time series, said second time series comprising a plurality of values, with each member of said plurality corresponding to a specific time interval characterized by a start time and an end time, computing, by said first computing device, an improved time series of estimated electricity prices, by computing at least one price correction value using data from said second time series, and applying said price correction value to said first time series, said improved time series comprising a plurality of improved forward-looking electricity prices, with each member of said plurality corresponding to a specific time interval characterized by a start time and an end time, and each of said prices being a cost per unit of electricity, holding said improved time series of estimated electricity prices in said electronic memory, to determine an expected benefit from running said load by evaluating a function stored in said electronic memory, and controlling said electric load, by said first or by a second computing device, so as to run said load if said expected benefit from running said load at the present time exceeds said price estimate according to said improved time series.
