Building energy system with predictive control of battery and green energy resources

1. A predictive controller for a building energy system the building energy system comprising HVAC equipment comprising airside equipment and waterside equipment, the predictive controller comprising one or more processing circuits configured to:

obtain a constraint that defines an amount of energy consumed by both the waterside equipment and the airside equipment at each time step of a time period as a summation of multiple equipment-specific energy components comprising:

a waterside energy component indicating an amount of energy consumed by the waterside equipment during the time step; and

one or more airside energy components indicating one or more amounts of energy consumed by the airside equipment during the time step:

perform a predictive control process subject to the constraint to determine values of the equipment-specific energy components at each time step of the time period, wherein the predictive control process comprises predicting the amount of energy consumed or a cost of the energy consumed by both the waterside equipment and the airside equipment during the time period based on the values of the equipment-specific energy components; and

operate equipment of the building energy system using the values of the equipment-specific energy components.

2. The predictive controller of claim 1 , wherein the one or more processing circuits are further configured to determine temperature setpoints for one or more building zones based on the values of the equipment-specific energy components.

3. The predictive controller of claim 1 , wherein the predictive control process accounts for:

an amount of grid energy or cost of the grid energy obtained from an energy grid; and

an amount of energy savings or cost savings resulting from discharging stored electric energy during the time period.

4. The predictive controller of claim 1 , wherein the predictive control process accounts for a demand charge based on a maximum power consumption of the building energy system during a demand charge period that overlaps at least partially with the time period.

5. The predictive controller of claim 1 , wherein the one or more airside energy components comprise at least one of:

an air handler unit (AHU) energy component indicating an amount of energy consumed by one or more AHUs of the airside equipment during the time step; or

a rooftop unit (RTU) energy component indicating an amount of energy consumed by one or more RTUs of the airside equipment during the time step.

6. The predictive controller of claim 1 , wherein the one or more processing circuits are configured to:

obtain a second constraint that defines a total electric load to be served by the building energy system at each time step as a summation of multiple source-specific energy components comprising:

a first energy component indicating a first amount of energy to obtain from a first energy source during the time step; and

a second energy component indicating a second amount of energy to obtain from a second energy source during the time step; and

perform the predictive control process subject to the second constraint to determine values for each of the source-specific energy components at each time step of the time period.

7. The predictive controller of claim 6 , wherein the source-specific energy components comprise at least two of:

a grid energy component indicating an amount of grid energy to obtain from an energy grid during the time step;

a green energy component indicating an amount of green energy to obtain from green energy generation during the time step; and

a battery energy component indicating an amount of electric energy to store in a battery or discharge from the battery during the time step.

8. The predictive controller of claim 6 , wherein the one or more processing circuits are configured to:

obtain energy pricing data defining a cost per unit of the first amount of energy obtained from the first energy source at each time step of the time period; and

use the energy pricing data as inputs to the predictive control process.

9. A method of operating a building energy system, the building energy system comprising HVAC equipment comprising airside equipment and waterside equipment, the method comprising:

obtaining a constraint that defines an amount of energy consumed by both the waterside equipment and the airside equipment at each time step of a time period as a summation of multiple equipment-specific energy components comprising:

a waterside energy component indicating an amount of energy consumed by the waterside equipment during the time step; and

one or more airside energy components indicating one or more amounts of energy consumed by the airside equipment during the time step:

performing a predictive control process subject to the constraint to determine values of the equipment-specific energy components for the time period, wherein the predictive control process comprises predicting the amount of energy consumed or a cost of the energy consumed by both the waterside equipment and the airside equipment during the time period based on the values of the equipment-specific energy components; and

operating equipment of the building energy system using the values of the equipment-specific energy components.

10. The method of claim 9 , wherein the predictive control process accounts for:

an amount of grid energy or cost of the grid energy obtained from an energy grid; and

an amount of energy savings or cost savings resulting from using green energy.

11. The method of claim 9 , wherein the predictive control process accounts for a cost savings resulting from discharging stored energy from a battery during the time period.

12. The method of claim 9 , wherein operating the equipment of the building energy system using the values of the equipment-specific energy components comprises:

determining temperature setpoints for one or more building zones based on the values of the equipment-specific energy components; and

controlling the equipment using the temperature setpoints.

13. The method of claim 9 , further comprising:

obtaining a second constraint that defines a total electric load to be served by the building energy system at each time step as a summation of multiple source-specific energy components comprising:

a first energy component indicating a first amount of energy to obtain from a first energy source during the time step; and

a second energy component indicating a second amount of energy to obtain from a second energy source during the time step;

performing the predictive control process subject to the second constraint to determine values for each of the source-specific energy components at each time step of the time period.

14. The method of claim 13 , wherein the source-specific energy components comprise at least two of:

a grid energy component indicating an amount of grid energy to obtain from an energy grid;

a green energy component indicating an amount of green energy to obtain from green energy generation; and

a battery energy component indicating an amount of electric energy to store in a battery or discharge from the battery.

15. The method of claim 14 , wherein the battery energy component:

adds to the grid energy component or the green energy component when the amount of electric energy is discharged from the battery; and

subtracts from the grid energy component or the green energy component when the amount of electric energy is stored in the battery.

16. A method of operating a building energy system, the building energy system comprising HVAC equipment comprising airside equipment and waterside equipment, the method comprising:

performing a predictive control process subject to a constraint that defines an amount of energy consumed by both the waterside equipment and the airside equipment at each time step of the future time period as a summation of multiple equipment-specific energy components to determine values of the equipment-specific energy components for the future time period, wherein the predictive control process comprises predicting the amount of energy consumed or a cost of the energy consumed by both the waterside equipment and the airside equipment during the time period based on the values of the equipment-specific energy components, the equipment-specific energy components comprising:

a waterside energy component indicating an amount of energy consumed by the waterside equipment during the time step; and

one or more airside energy components indicating one or more amounts of energy consumed by the airside equipment during the time step; and

operating equipment of the building energy system using the values of the equipment-specific energy components.

17. The method of claim 16 , further comprising:

generating a visualization of a total electric load to be served by the building energy system, the visualization comprising multiple source-specific energy components comprising:

a first energy component indicating a first amount of energy to obtain from a first energy source; and

a second energy component indicating a second amount of energy to obtain from a second energy source; and

causing the visualization to show values of the source-specific energy components for the future time period.

18. The method of claim 17 , wherein the source-specific energy components comprise at least two of:

a grid energy component indicating an amount of grid energy to obtain from an energy grid;

a green energy component indicating an amount of green energy to obtain from green energy generation; and

a battery energy component indicating an amount of electric energy to store in a battery or discharge from the battery.

19. The method of claim 17 , wherein the visualization comprises a plot of the values of the source-specific energy components at a plurality of time steps in the future time period.

20. The method of claim 17 , wherein the visualization comprises at least one of:

a charge level of energy storage equipment; or

an indication of a heating or cooling load served by the building energy system over the future time period.