FUZZY LOGIC BASED INTEGRATED POWER COORDINATION SYSTEM FOR HYBRID ENERGY STORAGE SYSTEM

• US 20150148973A1
• Filed: 11/26/2014
• Published: 05/28/2015
• Est. Priority Date: 11/26/2013
• Status: Active Grant

• Current Assignee: NEC Corporation
• Original Assignee: NEC Laboratories America Inc (NEC Corporation)
• Inventors: YE, YANZHU, SHARMA, RATNESH
• Granted Patent: US 9,753,511 B2
• Time in Patent Office: Days
• US Class Current: 700/286
• CPC Class Codes: G05B 13/0275 using fuzzy logic only
• CPC Class Codes: G06F 1/263 Arrangements for using multiple switchable power supplies, e.g. battery and AC G06F1/30 takes precedence
• CPC Class Codes: G06F 1/3212 Monitoring battery levels, e.g. power saving mode being initiated when battery voltage goes below a certain level
• CPC Class Codes: G06N 7/02 using fuzzy logic computing arrangements based on biological models G06N3/00; computing arrangements using knowledge-based models G06N5/00
• CPC Class Codes: H02J 1/10 Parallel operation of dc sources
• CPC Class Codes: H02J 7/345 using capacitors as storage or buffering devices
• CPC Class Codes: H02J 7/35 with light sensitive cells

Abstract

A method of managing power between the multiple components of a hybrid electrical energy storage system (HESS) that includes providing at least two power storage elements, and at least one renewable power source. The method further includes managing the power flow among the at least two power storage elements with a fuzzy logic controller. The fuzzy logic controller uses a hardware processor that is configured to increase or decrease current to each of the at least two power storage elements using a fuzzy rule base that is dependent upon at least one of a state of charge for each of the at least two power storage elements, and a requested power demand of the hybrid electrical storage system.

Claims

1. A method of managing power between the multiple components of a hybrid electrical energy storage system (HESS) comprising:

providing at least two power storage elements, and at least one renewable power source; and

managing at least one of a power and energy distribution among the at least two power storage elements with a fuzzy logic controller using a hardware processor that is configured to increase or decrease current to each of the at least two power storage elements using a fuzzy rule base that is dependent upon at least one of a state of charge for each of the at least two power storage elements, and a requested power demand of the hybrid electrical storage system.

2. The method of claim 1, wherein the at least two power storage elements comprise an ultracapacitor and a battery.

3. The method of claim 1, wherein the at least one renewable power source is a photovoltaic system.

4. The method of claim 3, wherein outputs from the fuzzy logic controller include a battery reference current (I_bat) and a deviation from target power (Δ

P).

5. The method of claim 4, wherein a battery reference current (I_bat) provides a control current reference to the battery from the fuzzy logic controller.

6. The method of claim 4, wherein an ultracapacitor current (I_UC) provides a control current reference to the ultracapacitor from the fuzzy logic controller, the ultracapacitor current (I_UC) being calculated from:

7. The method of claim 2, wherein the fuzzy logic controller employs membership functions to assign values to input variables of positive big, positive small, zero, negative small and negative big for the requested HESS power (P_HESS), state of charge for the battery, and the state of charge for the capacitor, wherein the input variables correspond to output variables for the battery reference current (I_bat) and the deviation from target power (Δ

P) from the fuzzy logic controller as set by the fuzzy rule base.

8. The method of claim 7, wherein the output variables for the battery reference current (I_bat) and the deviation from target power (Δ

P) from the fuzzy logic controller are defuzzified through centroid defuzzification, where the assigned value based on the fuzzy rule bases and the membership functions are converted to numerical value for at least one of battery reference current (I_bat) and deviation from target power (Δ

P).

9. A hybrid energy storage system comprising:

an energy source;

at least a first and second power storage element; and

a power management system for controlling at least one of an energy and power distribution among the at least the first and second power storage elements, wherein the power management system comprises a signal conditioning module for suppressing noise in signals from at least the first and second power storage element, a fuzzy logic mutual assistance module for determining from a rule set with a hardware processor a distribution of current to be distributed to each of the at least one first power storage element and the second power storage element, and a rate conditioning module for controlling the operation rate of at least one of the first power storage element and the second power storage element.

10. The system of claim 9, wherein the at least the first and the second power storage elements comprise an ultracapacitor and a battery.

11. The system of claim 9, wherein the energy source is a photovoltaic system.

12. The system of claim 9, wherein the inputs to the fuzzy logic mutual assistance module include at least one of a state of charge for each of the at least two power storage elements, and a requested power demand of the hybrid electrical storage system.

13. The system of claim 9, wherein outputs from the fuzzy logic mutual assistance module include a battery reference current (I_bat) and a deviation from target power (Δ

P).

14. The system of claim 9, wherein the battery reference current (I_bat) provides a current control reference to the battery from the power management system.

15. The system of claim 9, wherein an ultracapacitor current (I_UC) provides a current control reference to the ultracapacitor from the power management system, the ultracapacitor current (I_UC) being calculated from:

16. A computer program product comprising a non-transistory computer readable storage medium having computer readable program code embodied therein for performing a method for managing power between the multiple components of a hybrid electrical energy storage system, the method comprising:

managing power flow among the at least two power storage elements with a fuzzy logic controller, wherein the fuzzy logic controller employs a hardware processor that is configured to increase or decrease current to each of the at least two power storage elements using a fuzzy rule base that is dependent upon at least one of the state of charge for each of the at least two power storage elements, and the requested power demand of the hybrid electrical storage system.

17. The computer program product of claim 16, wherein the at least two power storage elements comprise an ultracapacitor and a battery.

18. The computer program product of claim 16, wherein outputs from the fuzzy logic controller include a battery reference current (I_bat) and a deviation from target power (Δ

P), wherein a battery reference current (I_bat) provides a current control reference to the battery from the fuzzy logic controller.

19. The computer program product of claim 18, wherein an ultracapacitor current (I_UC) provides a current control reference to the ultracapacitor from the fuzzy logic controller, the ultracapacitor current (I_UC) being calculated from:

20. The computer program product of claim 19, wherein the fuzzy logic controller employs membership functions to assign linguistic values to input variables of positive big, positive small, zero, negative small and negative big for the requested HESS power (P_HESS), state of charge for the battery, and the state of charge for the capacitor, wherein the input variables correspond to output variables for the battery reference current (I_bat) and the deviation from target power (Δ

P) from the fuzzy logic controller as set by the fuzzy rule base.