Dynamic load profiling in a power network

1. A method for dynamic load profiling in a power network, the method comprising:

receiving static load data in the power network;

generating a load forecast from the static load data;

receiving distributed load data from distributed assets to generate current and predicted dynamic load data;

predicting and generating dynamic load data from data related to distributed assets in the power network based on predicting locations of the distributed assets in the power network; and

modifying the load forecast based on the dynamic load data for profiling the dynamic load data, wherein generating dynamic load data comprises receiving distributed asset registration data, predicting the locations of the distributed assets from the distributed asset registration data, and predicting load requirements of the distributed assets from the asset registration data.

2. The method as claimed in claim 1 wherein the distributed registration data includes predetermined location data for the distributed assets.

3. The method as claimed in claim 1 wherein the distributed asset registration data includes times of day of predetermined locations and time predictions of connections to the power network.

4. The method as claimed in claim 1 further comprising generating a power dispatch plan.

5. The method as claimed in claim 4 wherein the power dispatch plan includes a state of the power network and load demand locations in the power network in order to determine distribution of power.

6. The method as claimed in claim 4 wherein the power dispatch plan includes a state of the power network and load demand locations in the power network in order to determine modifying an amount of power in the power network.

7. A computer program product for dynamic load profiling in a power network, the computer program product including a non-transitory computer readable medium having instructions for causing a computer to implement a method, the method comprising:

receiving static load data in the power network;

generating a load forecast from the static load data;

receiving distributed load data from distributed assets to generate current and predicted dynamic load data;

predicting and generating dynamic load data from data related to distributed assets in the power network based on predicting locations of the distributed assets in the power network; and

modifying the load forecast based on the dynamic load data for profiling the dynamic load data, wherein generating dynamic load data comprises receiving distributed asset registration data, predicting the locations of the distributed assets from the distributed asset registration data, and predicting load requirements of the distributed assets from the asset registration data.

8. The computer program product as claimed in claim 7 wherein the distributed registration data includes predetermined location data for the distributed assets.

9. The computer program product as claimed in claim 7 wherein the distributed asset registration data includes times of day of predetermined locations and time predictions of connections to the power network.

10. The computer program product as claimed in claim 7 further comprising generating a power dispatch plan.

11. The computer program product as claimed in claim 10 wherein the power dispatch plan includes a state of the power network and load demand locations in the power network in order to determine distribution of power.

12. The computer program product as claimed in claim 10 wherein the power dispatch plan includes a state of the power network and load demand locations in the power network in order to determine modifying an amount of power in the power network.

13. A system for dynamic load profiling, the system comprising:

a processor configured to:

receive static load data in a power network;

generate a load forecast from the static load data;

receive distributed load data from distributed assets to generate current and predicted dynamic load data;

predict and generate dynamic load data from data related to distributed assets in the power network based on predicting locations of the distributed assets in the power network; and

modify the load forecast based on the dynamic load data for profiling the dynamic load, wherein the processor is further configured to receive distributed asset registration data, predict the locations of the distributed assets from the distributed asset registration data, and predict load requirements of the distributed assets from the asset registration data.

14. The system as claimed in claim 13 wherein the distributed registration data includes at least one of predetermined location data for the distributed assets, times of day of predetermined locations and time predictions of connections to the power network.