Power factor

• US 9,343,904 B2
• Filed: 08/02/2012
• Issued: 05/17/2016
• Est. Priority Date: 03/29/2012
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation, Universiti Brunei Darussalam
• Original Assignee: International Business Machines Corporation, Universiti Brunei Darussalam
• Inventors: Seetharamakrishnan, Devasenapathi P, Hazra, Jagabondhu, Narayanaswamy, Balakrishnan, De Silva, Liyanage Chandratilak
• Primary Examiner(s): Bahta, Kidest
• Application Number:
  US13/565,130
• Publication Number:
  US 20130261824A1
• Time in Patent Office: 1,384 Days
• Field of Search: 700/296, 700/295, 700/293, 700/286, 700/287, 702/61, 702/62, 705/30, 307/84, 307/207, 323/205
• US Class Current: 1/1
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: H02J 3/18 Arrangements for adjusting, eliminating or compensating reactive power in networks for adjustment of voltage H02J3/16
• CPC Class Codes: Y02E 40/30 Reactive power compensation
• CPC Class Codes: Y02P 80/10 Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier

Abstract

A method for improving power factor includes collecting consumption data of at least one appliance, building a consumption profile for each of the at least one appliance based on the consumption data collected, reconstructing reactive power consumption of each of the at least one appliance based on the consumption profile for each of the at least one appliance, and computing a schedule for each of the at least one appliance in accordance the reactive power consumption of each of the at least one appliance to improve power factor while respecting at least one constraint.

Claims

1. A computer-implemented method for improving power factor, wherein the computer-implemented method comprises:

collecting consumption data of at least one inductive appliance and at least one capacitive appliance;

building a consumption profile for each of the at least one inductive appliance and the at least one capacitive appliance based on the consumption data collected;

reconstructing reactive power consumption of each of the at least one inductive appliance and the at least one capacitive appliance based on the consumption profile for each of the at least one inductive appliance and the at least one capacitive appliance, wherein said reactive power is distinct from active power, said reactive power being stored in an appliance and said active power being consumed by the appliance; and

computing a single operating schedule encompassing the at least one inductive appliance and the at least one capacitive appliance, in accordance with the reconstructed reactive power consumption, to reduce reactive power flow within the at least one inductive appliance and the at least one capacitive appliance to improve power factor while respecting at least one constraint;

wherein the steps are carried out by instructions that are (i) embodied on at least one non-transitory computer readable storage medium and (ii) executable by at least one computer device.

2. The computer-implemented method of claim 1, further comprising:

storing the consumption profile for each of the at least one inductive appliance and the at least one capacitive appliance in a database.

3. The computer-implemented method of claim 1, further comprising:

displaying the operating schedule via an output device.

4. The computer-implemented method of claim 1, further comprising:

editing the operating schedule based on user input.

5. The computer-implemented method of claim 1, wherein collecting consumption data of the at least one inductive appliance and the at least one capacitive appliance comprises collecting consumption data from a smart meter.

6. The computer-implemented method of claim 1, further comprising:

updating the consumption profile of at least one of the at least one inductive appliance and the at least one capacitive appliance.

7. The non-transitory computer-implemented method of claim 1, wherein the at least one constraint comprises at least one of user availability, comfort, user preference for device usage time and duration and delay, user preference for device usage intensity and change in intensity, user preference for device co-scheduling and re-scheduling, cost related to reactive power, and available source of power.

8. The computer-implemented method of claim 1, wherein the at least one inductive appliance is a component of a residence, a group of residences or a commercial location.

9. The computer-implemented method of claim 1, wherein said computing the operating schedule comprises co-scheduling multiple appliances to improve a net power factor.

10. The computer-implemented method of claim 1, wherein said computing the operating schedule comprises re-scheduling an appliance based on real-time pricing of reactive power.

11. The computer-implemented method of claim 1, further comprising:

implementing a circuit so as to reduce electrical distance between inductive and capacitive loads so that power loss is reduced.

12. A computer-implemented method comprising:

classifying, from a collection of multiple appliances, one or more inductive appliances and one or more capacitive appliances;

computing one or more reactive power parameters pertaining to the one or more inductive appliances and the one or more capacitive appliances; and

scheduling the one or more inductive appliances and the one or more capacitive appliances together via a single operating schedule to shorten flow of the reactive power within the one or more inductive appliances and the one or more capacitive appliances by minimizing a cost function, wherein said cost function is based on at least (i) a cost for consuming reactive power, (ii) a level of reactive power consumption by the one or more inductive appliances and the one or more capacitive appliances, (iii) a rate for reactive power, and (iv) the number of appliances among the one or more inductive appliances and the one or more capacitive appliances;

wherein the steps are carried out by instructions that are (i) embodied on at least one non-transitory computer readable storage medium and (ii) executable by at least one computer device.

13. The computer-implemented method of claim 12, wherein the cost function is further based on source power capacity.

14. The computer-implemented method of claim 12, wherein the cost function is further based on measures of user inconvenience when an operating level and an operating time, respectively, of a given appliance are modified.

15. The non-transitory computer-implemented method of claim 12, wherein the cost function is further based on power consumed by a load associated with the one or more inductive appliances and the one or more capacitive appliances.