PREDICTIVE PHASE BALANCING FOR DEMAND RESPONSE

• US 20140031998A1
• Filed: 07/30/2012
• Published: 01/30/2014
• Est. Priority Date: 07/24/2012
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Mukherjee, Maharaj
• Granted Patent: US 9,350,172 B2
• Time in Patent Office: Days
• US Class Current: 700/291
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: H02J 3/26 Arrangements for eliminating or reducing asymmetry in polyphase networks
• CPC Class Codes: H02J 3/28 Arrangements for balancing of the load in a network by storage of energy
• CPC Class Codes: Y04S 10/50 Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

Predictive phase balancing is implemented by receiving customer demand profiles from each customer serviced by a poly-phase grid network and creating a demand forecast from anticipated power demands collected from the customer demand profiles. Creating the customer demand profiles includes breaking down loads for each customer by corresponding phases in the poly-phase power grid network. The loads correspond to the anticipated power demands. The predictive phase balancing is further implemented by balancing the loads among each of the phases based on any load imbalances determined from the demand forecast.

Claims

1. A method for implementing predictive phase balancing, comprising:

receiving, at a computer processor, customer demand profiles from each customer serviced by a poly-phase grid network;

creating, by the computer processor, a demand forecast from anticipated power demands collected from the customer demand profiles, the creating comprising breaking down loads for each customer by corresponding phases in the poly-phase power grid network, the loads corresponding to the anticipated power demands; and

balancing the loads among each of the phases based on any load imbalances determined from the demand forecast.

2. The method of claim 1, wherein the creating further includes breaking down the loads for each customer into time intervals, wherein balancing the loads among each of the phases includes balancing the loads among the phases within one of the time intervals.

3. The method of claim 2, further comprising:

determining the load imbalances in the demand forecast, comprising;

summing a quantified value of the loads in each of the phases and for each of the time intervals resulting in a total summation value for each of the phases and for each of the time intervals;

storing the loads and corresponding total summation values for each of the phases and at each of the time intervals; and

for each of the time intervals;

determining a difference between the summation value of a first phase of the phases and a second phase of the phases, a difference between the second phase of the phases and a third phase of the phases, and a difference between the first phase and the third phase; and

upon determining that the difference between any of the summation values exceeds a threshold value, incrementally removing smallest loads from the phase having the highest summation value and iteratively re-allocating the smallest loads to other phases until the loads in all of the phases are balanced, the loads determined to be balanced when each of the summation values is substantially equal to one another.

4. The method of claim 2, wherein the time intervals are represented in hours.

5. The method of claim 2, wherein the time intervals are represented in days.

6. The method of claim 1, wherein balancing the loads among each of the phases is implemented by a phase switch in the poly-phase grid network.

7. The method of claim 1, wherein the anticipated power demands for at least one of the customer demand profiles are calculated as a function of an occupancy rate for a facility of the corresponding customer.

8. The method of claim 1, further comprising:

re-balancing the loads among each of the phases based on load imbalances determined from data collected from a smart meter.

9. A computer program product for implementing predictive phase balancing, the computer program product comprising a storage medium having computer instructions embodied thereon, which when executed by a computer, causes the computer to implement a method, the method comprising:

receiving customer demand profiles from each customer serviced by a poly-phase grid network;

creating a demand forecast from anticipated power demands collected from the customer demand profiles, the creating comprising breaking down loads for each customer by corresponding phases in the poly-phase power grid network, the loads corresponding to the anticipated power demands; and

balancing the loads among each of the phases based on any load imbalances determined from the demand forecast.

10. The computer program product of claim 9, wherein the creating further includes breaking down the loads for each customer into time intervals, wherein balancing the loads among each of the phases includes balancing the loads among the phases within one of the time intervals.

11. The computer program product of claim 10, wherein the method further comprises:

determining the load imbalances in the demand forecast, comprising;

summing a quantified value of the loads in each of the phases and for each of the time intervals resulting in a total summation value for each of the phases and for each of the time intervals;

storing the loads and corresponding total summation values for each of the phases and at each of the time intervals; and

for each of the time intervals;

determining a difference between the summation value of a first phase of the phases and a second phase of the phases, a difference between the second phase of the phases and a third phase of the phases, and a difference between the first phase and the third phase; and

upon determining that the difference between any of the summation values exceeds a threshold value, incrementally removing smallest loads from the phase having the highest summation value and iteratively re-allocating the smallest loads to other phases until the loads in all of the phases are balanced, the loads determined to be balanced when each of the summation values is substantially equal to one another.

12. The computer program product of claim 10, wherein the time intervals are represented in hours.

13. The computer program product of claim 10, wherein the time intervals are represented in days.

14. The computer program product of claim 9, wherein balancing the loads among each of the phases is implemented by a phase switch in the poly-phase grid network.

15. The computer program product of claim 9, wherein the anticipated power demands for at least one of the customer demand profiles are calculated as a function of an occupancy rate for a facility of the corresponding customer.

16. The computer program product of claim 9, wherein the method further comprises:

re-balancing the loads among each of the phases based on load imbalances determined from data collected from a smart meter.