Orchestrated energy
A facility providing systems and methods for managing and optimizing energy consumption and/or production is provided. The facility provides techniques for optimizing energy-consuming and energy-producing systems to meet specified demands or goals in accordance with various constraints. The facility relies on models to generate an optimization for an energy system. In order to use generic models to simulate and optimize energy consumption for an energy system, the generic models are calibrated to properly represent or approximate conditions of the energy system during the optimization period. After the appropriate models have been calibrated for a given situation using one or more modeling parameter sets, the facility can simulate inputs and responses for the corresponding system. The facility uses the generated simulations to generate a plan or control schedule to be implemented by the energy system during the optimization period.
1. A method, performed by a computing system, for managing energy consumption within an energy-consuming system during a period, the method comprising:
determining, by the computing system, environmental conditions for the energy-consuming system, wherein determining at least one environmental condition for the energy-consuming system comprises invoking a device abstraction layer or service to communicate with a first device;
calibrating, by the computing system, at least one of a plurality of models;
identifying, by the computing system, one or more constraints for the period;
identifying, by the computing system, one or more objectives for the period;
determining, for the energy-consuming system,
susceptibility of the energy-consuming system to change conditions based on at least a first component and a second component within the energy-consuming system that drives conditions within the energy-consuming system, wherein the first component is a heating, ventilation, and air conditioning (HVAC) component and the second component is not an HVAC component,
drive strength of at least the first component and the second component within the energy-consuming system that drives conditions within the energy-consuming system, and
an entropy rate in the absence of at least the first component and the second component within the energy-consuming system that drives conditions within the energy-consuming system;
modeling the susceptibility, drive strength, and entropy rate;
performing a plurality of simulations, wherein each simulation generates a plurality of simulated input values to the calibrated at least one model and a plurality of simulated responses to the simulated input values;
optimizing, by the computing system, the simulated input values generated for a prediction quantity by the performed simulation;
generating, by the computing system, a control schedule for the energy-consuming system during the period based at least in part on the identified one or more constraints for the period, the identified one or more objectives for the period, the susceptibility, the drive strength, and the entropy rate; and
controlling a heating, ventilation, and air conditioning system in accordance with the generated control schedule.
2. The method of claim 1 , further comprising:
periodically generating a modeling parameter set for the energy-consuming system and storing the generated modeling parameter set.
3. The method of claim 1 , further comprising:
providing the generated control schedule to the energy-consuming system.
4. The method of claim 1 , wherein the models include:
a thermal model, and
an electrical model.
5. The method of claim 1 , wherein the determined environmental conditions comprise:
at least one weather-related value for the energy-consuming system during the period,
at least one occupancy-related value for the energy-consuming system during the period,
at least one size-related value for the energy-consuming system during the period, or
any combination thereof.
6. The method of claim 5 , wherein the at least one weather-related value for the energy-consuming system comprises a forecasted outdoor temperature, a forecasted outdoor humidity, or forecasted solar irradiance for the energy-consuming system for the period, wherein the at least one occupancy-related value for the energy-consuming system comprises a day of the week for the period, and wherein the at least one size-related value for the energy-consuming system comprises an area of the energy-consuming system.
7. The method of claim 1 , wherein the energy-consuming system is one of: a pool pump, an electric vehicle charger, a lighting system, or a water heater.
8. The method of claim 1 , further comprising:
obtaining, by the computing system, a plurality of generic models representative of energy consumption; and
identifying, by the computing system, a modeling parameter set for the period,
wherein the calibrating comprises calibrating at least one of the obtained generic models representative of energy consumption based at least in part on the selected modeling parameter set for the period.
9. The method of claim 1 , wherein at least one of the identified objectives is a user-specified objective.
10. The method of claim 1 , wherein optimizing the simulated input values generated for the prediction quantity comprises linearly optimizing the simulated input values generated for the prediction quantity by the performed simulation.
11. A method, performed by a computing system, for managing energy consumption during a period within an energy-consuming system having a Heating, Ventilating, and Air Conditioning (HVAC) system with HVAC components, and having a plurality of energy consuming, non-HVAC components, the method comprising:
determining, by the computing system, environmental conditions for the energy-consuming system, wherein determining at least one environmental condition for the energy-consuming system comprises invoking a device abstraction layer or service to communicate with a first device;
calibrating, by the computing system, at least one of a plurality of models;
identifying, by the computing system, a modeling parameter set for the period;
identifying, by the computing system, one or more constraints for the period;
identifying, by the computing system, one or more objectives for the period;
determining, for the energy-consuming system,
susceptibility of the energy-consuming system to change conditions based on at least a first component and a second component within the energy-consuming system that drives conditions within the energy-consuming system, wherein the first component is a HVAC component and the second component is a non-HVAC component,
drive strength of at least the first component and the second component within the energy-consuming system that drives conditions within the energy-consuming system, and
an entropy rate in the absence of at least the first component and the second component within the energy-consuming system that drives conditions within the energy-consuming system;
performing a plurality of simulations, wherein each simulation generates a plurality of simulated input values to the calibrated at least one model and a plurality of simulated responses to the simulated input values;
optimizing, by the computing system, the simulated input values generated for a prediction quantity by the performed simulation;
generating, by the computing system, a control schedule for the energy-consuming system during the period based at least in part on the identified one or more constraints for the period, the identified one or more objectives for the period, the susceptibility, drive strength, and entropy rate; and
controlling the HVAC system in accordance with the generated control schedule.
12. The method of claim 11 , further comprising:
periodically generating a modeling parameter set for the energy-consuming system and storing the generated modeling parameter set.
13. The method of claim 11 , wherein the determined environmental conditions comprise:
a weather-related value for the energy-consuming system during the period,
an occupancy-related value for the energy-consuming system during the period,
a size-related value for the energy-consuming system during the period, or
any combination thereof.
14. The method of claim 13 , wherein the weather-related value for the energy-consuming system comprises a forecasted outdoor temperature, a forecasted outdoor humidity, or forecasted solar irradiance for the energy-consuming system for the period, wherein the occupancy-related value for the energy-consuming system comprises a day of the week for the period, and wherein the at least one size-related value for the energy-consuming system comprises an area of the energy-consuming system.
15. The method of claim 11 , wherein the non-HVAC component is one of: a pool pump, an electric vehicle charger, a lighting system, or a water heater.