Facilitating revenue generation from wholesale electricity markets based on a self-tuning energy asset model
First Claim
1. An apparatus for generating operation parameters and/or operating schedules for at least one building asset, the apparatus comprising:
- at least one communication interface;
at least one memory to store processor-executable instructions and a day-ahead building asset model; and
at least one processing unit communicatively coupled to the at least one communication interface and the at least one memory, wherein, upon execution of the processor-executable instructions, the at least one processing unit;
A) determines the day-ahead building asset model;
wherein the day-ahead building asset model is a dynamic self-tuning energy asset model that comprises a computation of thermodynamics properties of the at least one building asset;
wherein the dynamic self-tuning energy asset model adapts itself to the conditions, including physical characteristics, of the at least one building asset; and
wherein the dynamic self-tuning energy asset model is predictive of energy consumption of the at least one building asset as a function of time; and
B) computes the operation parameters and/or operating schedules for at least one building asset using the day-ahead building asset model and variations in the forecast wholesale electricity price of electric energy usage in the wholesale market during a defined time period; and
C) controls the at least one communication interface to transmit to the energy customer the determined operation parameters and/or operating schedules;
wherein the day-ahead building asset model is used to generate operation parameters and operating schedules for at least one building asset based at least in part on at least one operation characteristic of the building asset; and
wherein input to the day-ahead building asset model includes at least one operation characteristic of the at least one building asset.
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Accused Products
Abstract
The apparatus, systems and methods herein facilitate generation of energy-related revenue for an energy customer of an electricity supplier. The apparatuses and methods herein can be used to generate suggested operating schedules for the energy assets that including a controllable energy asset, using an objective function. The objective function is determined based on a dynamic simulation model of the energy profile of the energy assets. The dynamic simulation model is adaptive to physical changes in the energy assets based on a parametric estimation using at least one model parameter. The model parameter is at least one of an operation characteristic of the controllable energy asset, a thermodynamic property of the energy assets, and a projected environmental condition. Energy-related revenue available to the energy customer is based at least in part on a wholesale electricity market or on a regulation market.
187 Citations
19 Claims
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1. An apparatus for generating operation parameters and/or operating schedules for at least one building asset, the apparatus comprising:
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at least one communication interface; at least one memory to store processor-executable instructions and a day-ahead building asset model; and at least one processing unit communicatively coupled to the at least one communication interface and the at least one memory, wherein, upon execution of the processor-executable instructions, the at least one processing unit; A) determines the day-ahead building asset model; wherein the day-ahead building asset model is a dynamic self-tuning energy asset model that comprises a computation of thermodynamics properties of the at least one building asset; wherein the dynamic self-tuning energy asset model adapts itself to the conditions, including physical characteristics, of the at least one building asset; and wherein the dynamic self-tuning energy asset model is predictive of energy consumption of the at least one building asset as a function of time; and B) computes the operation parameters and/or operating schedules for at least one building asset using the day-ahead building asset model and variations in the forecast wholesale electricity price of electric energy usage in the wholesale market during a defined time period; and C) controls the at least one communication interface to transmit to the energy customer the determined operation parameters and/or operating schedules; wherein the day-ahead building asset model is used to generate operation parameters and operating schedules for at least one building asset based at least in part on at least one operation characteristic of the building asset; and wherein input to the day-ahead building asset model includes at least one operation characteristic of the at least one building asset. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method for generating operation parameters and/or operating schedules for at least one building asset, the method comprising:
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A) determining, using at least one processing unit, the day-ahead building asset model; wherein the day-ahead building asset model is a dynamic self-tuning energy asset model that comprises a computation of thermodynamics properties of the at least one building asset; wherein the dynamic self-tuning energy asset model adapts itself to the conditions, including physical characteristics, of the at least one building asset; and wherein the dynamic self-tuning energy asset model is predictive of energy consumption of the at least one building asset as a function of time; and B) computing, using the at least one processing unit, the operation parameters and/or operating schedules for at least one building asset using the day-ahead building asset model and variations in the forecast wholesale electricity price of electric energy usage in the wholesale market during a defined time period; and C) controlling at least one communication interface to transmit to the energy customer the determined operation parameters and/or operating schedules; wherein the day-ahead building asset model is used to generate operation parameters and operating schedules for at least one building asset based at least in part on at least one operation characteristic of the building asset; and wherein input to the day-ahead building asset model includes at least one operation characteristic of the at least one building asset. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. A non-transitory machine readable memory medium having at least one program embodied thereon, the at least one program including processor-executable instructions which when executed cause at least one processing unit to execute a method comprising:
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A) determining, using at least one processing unit, the day-ahead building asset model; wherein the day-ahead building asset model is a dynamic self-tuning energy asset model that comprises a computation of thermodynamics properties of the at least one building asset; wherein the dynamic self-tuning energy asset model adapts itself to the conditions, including physical characteristics, of the at least one building asset; and wherein the dynamic self-tuning energy asset model is predictive of energy consumption of the at least one building asset as a function of time; and B) computing, using the at least one processing unit, the operation parameters and/or operating schedules for at least one building asset using the day-ahead building asset model and variations in the forecast wholesale electricity price of electric energy usage in the wholesale market during a defined time period; and C) controlling at least one communication interface to transmit to the energy customer the determined operation parameters and/or operating schedules; wherein the day-ahead building asset model is used to generate operation parameters and operating schedules for at least one building asset based at least in part on at least one operation characteristic of the building asset; and wherein input to the day-ahead building asset model includes at least one operation characteristic of the at least one building asset.
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Specification