Optimizing power contribution of distributed energy resources for real time power demand scheduling

1. A method of controlling power at a point of interconnection of a power grid, the method being implemented by one or more data processors forming one or more computing devices and comprising:

receiving, by at least one data processor, power data that characterizes power flow at a point of interconnection of the power grid, the power data comprising power contribution levels of at least one distributed energy resource and at least one analysis profile for a time period;

determining, by at least one data processor, an objective energy function based on the power contribution levels and the at least one analysis profile, the objective energy function characterizing capabilities of the power grid, wherein determining the objective energy function comprises a non-linear criterion summing together (i) an energy loss scaled by energy storage states of the at least one distributed energy resource and (ii) a matrix representation of states of the at least one distributed energy resource multiplied by a penalty factor of the at least one distributed energy resource;

determining, by at least one data processor, a power contribution set-point based on a minimum value of the objective energy function, the power contribution set-point reflecting an optimized power contribution level of the at least one distributed energy resource; and

providing, by at least one data processor, the power contribution set-point to the at least one distributed energy resource to achieve the optimized power contribution level by modifying the power contribution of the at least one distributed energy resource.

2. The method of claim 1 , wherein the penalty factor accounts for at least one operational constraint of the at least one distributed energy resource.

3. The method of claim 1 , wherein determining the power contribution set-point comprises:

receiving, by at least one data processor, an interval of the objective energy function;

iteratively determining, by at least one data processor, a midpoint of the interval and a corresponding power contribution value of the objective energy function at the midpoint; and

iteratively determining, by at least one data processor, convergence of the power contribution value, wherein the power contribution set-point is the lowest power contribution value having convergence.

4. The method of claim 3 , wherein the interval comprises at least one of: a pre-determined interval or a variable interval having a pre-defined end-time.

5. The method of claim 1 , wherein the at least one analysis profile comprises a net power demand profile of the at least one distributed resource and the objective energy function comprises a combinatorial constrained least squares function of the power contribution levels.

6. The method of claim 1 , further comprising performing one or more of:

increasing power generation of the at least one distributed energy resource based on the power contribution set-point;

decreasing power generation of the at least one distributed energy resource based on the power contribution set-point;

maintaining power generation of the at least one distributed energy resource based on the power contribution set-point;

increasing energy storage of the at least one distributed energy resource based on the power contribution set-point;

decreasing energy storage of the at least one distributed energy resource based on the power contribution set-point; or

maintaining energy storage of the at least one distributed energy resource based on the power contribution set-point.

7. The method of claim 1 , wherein the at least one distributed energy resource comprises at least one of: a photovoltaic cell, a battery, a fuel cell, a wind turbine, a combined cycle gas turbine, a sterling engine, an energy storage system, or a generator.

8. The method of claim 1 , wherein the time period comprises at least one of: twenty-four hours, thirty-days, a pre-determined billing cycle, or a variable planning period.

9. The method of claim 1 , wherein the at least one analysis profile comprises at least one of: historical net-load data of the power grid, forecasted weather data, or forecasted energy resource data.

10. A system for controlling power at a point of interconnection of a power grid, the system comprising:

one or more data processors;

memory storing instructions which when executed by at least one data processor result in operations comprising:

receiving, by at least one data processor, power data that characterizes power flow at a point of interconnection of the power grid, the power data comprising power contribution levels of at least one distributed energy resource and at least one analysis profile for a time period;

determining, by at least one data processor, an objective energy function based on the power contribution levels and the at least one analysis profile, the objective energy function characterizing capabilities of the power grid, wherein determining the objective energy function comprises a non-linear criterion summing together (i) an energy loss scaled by energy storage states of the at least one distributed energy resource and (ii) a matrix representation of states of the at least one distributed energy resource multiplied by a penalty factor of the at least one distributed energy resource;

determining, by at least one data processor, a power contribution set-point based on a minimum value of the objective energy function, the power contribution set-point reflecting an optimized power contribution level of the at least one distributed energy resource; and

providing, by at least one data processor, the power contribution set-point to the at least one distributed energy resource to achieve the optimized power contribution level by modifying the power contribution of the at least one distributed energy resource.

11. The system of claim 10 , wherein the penalty factor accounts for at least one operational constraint of the at least one distributed energy resource.

12. The system of claim 10 , wherein determining the power contribution set-point comprises:

receiving, by at least one data processor, an interval of the objective energy function;

iteratively determining, by at least one data processor, a midpoint of the interval and a corresponding power contribution value of the objective energy function at the midpoint; and

iteratively determining, by at least one data processor, convergence of the power contribution value, wherein the power contribution set-point is the lowest power contribution value having convergence.

13. The system of claim 12 , wherein the interval comprises at least one of: a pre-determined interval or a variable interval having a pre-defined end-time.

14. The system of claim 10 , wherein the at least one analysis profile comprises a net power demand profile of the at least one distributed resource and the objective energy function comprises a combinatorial constrained least squares function of the power contribution levels.

15. The system of claim 10 , further comprising performing one or more of:

increasing power generation of the at least one distributed energy resource based on the power contribution set-point;

decreasing power generation of the at least one distributed energy resource based on the power contribution set-point;

maintaining power generation of the at least one distributed energy resource based on the power contribution set-point;

increasing energy storage of the at least one distributed energy resource based on the power contribution set-point;

decreasing energy storage of the at least one distributed energy resource based on the power contribution set-point; or

maintaining energy storage of the at least one distributed energy resource based on the power contribution set-point.

16. The system of claim 10 , wherein the at least one distributed energy resource comprises at least one of: a photovoltaic cell, a battery, a fuel cell, a wind turbine, a combined cycle gas turbine, a sterling engine, an energy storage system, or a generator.

17. The system of claim 10 , wherein the time period comprises at least one of: twenty-four hours, thirty-days, a pre-determined billing cycle, or a variable planning period.

18. The system of claim 10 , wherein the at least one analysis profile comprises at least one of: historical net-load data of the power grid, forecasted weather data, or forecasted energy resource data.

19. A non-transitory computer program product comprising a computer-readable storage medium having computer-readable program instructions, which when executed result in operations comprising:

receiving, by at least one data processor, power data that characterizes power flow at a point of interconnection of the power grid, the power data comprising power contribution levels of at least one distributed energy resource and at least one analysis profile for a time period;

determining, by at least one data processor, an objective energy function based on the power contribution levels and the at least one analysis profile, the objective energy function characterizing capabilities of the power grid, wherein determining the objective energy function comprises a non-linear criterion summing together (i) an energy loss scaled by energy storage states of the at least one distributed energy resource and (ii) a matrix representation of states of the at least one distributed energy resource multiplied by a penalty factor of the at least one distributed energy resource;

determining, by at least one data processor, a power contribution set-point based on a minimum value of the objective energy function, the power contribution set-point reflecting an optimized power contribution level of the at least one distributed energy resource; and

providing, by at least one data processor, the power contribution set-point to the at least one distributed energy resource to achieve the optimized power contribution level by modifying the power contribution of the at least one distributed energy resource.

20. The non-transitory computer program product of claim 19 , wherein the penalty factor accounts for at least one operational constraint of the at least one distributed energy resource.

21. The non-transitory computer program product of claim 19 , wherein determining the power contribution set-point comprises:

receiving, by at least one data processor, an interval of the objective energy function;

iteratively determining, by at least one data processor, a midpoint of the interval and a corresponding power contribution value of the objective energy function at the midpoint; and

iteratively determining, by at least one data processor, convergence of the power contribution value, wherein the power contribution set-point is the lowest power contribution value having convergence.