Power system with an energy generator and a hybrid energy storage system

Patent metadata

Field	Value
Publication number	US-9733657-B2
Application number	US-201414292851-A
Country	US
Kind code	B2
Filing date	May 31, 2014
Priority date	Jun 19, 2013
Publication date	Aug 15, 2017
Grant date	Aug 15, 2017

Abstract

Systems and methods are disclosed to control a power system with an energy generator and a hybrid energy storage system. The system includes two or more energy storage system, each with different energy storage capacity and energy discharge capacity. The system includes developing data for one or more control variables refined from expert knowledge, trials and tests; providing the control variables to a fuzzy logic controller with a rule base and membership functions; and controlling the energy generator and the hybrid energy storage system using the fuzzy logic controller.

First claim

What is claimed is:

1. A power system, comprising:
an energy generator;
a hybrid energy storage system (HSS) including two or more energy storage system, each with different energy capacity and power capacity; and
a fuzzy logic controller with a rule base and membership functions for control variables refined from expert knowledge, trials and tests;
wherein a exponential smoothing filter comprises
y ( t )=( a )· x ( t )+(1− a )· y ( t− 1)

where x(t) is the input to the filter and y(t−1) is the output at previous time step (t−1).

2. The system of claim 1 , wherein the controller uses an exponential smoothing filter for suppressing noise in voltage and current measurements.

3. The system of claim 1 , comprising the fuzzy logic controller coupled to a hybrid energy storage system with a low energy density source coupled to a high energy density source.

4. The system of claim 3 , wherein the fuzzy logic controller comprises first, second and third layer to control the hybrid energy storage system for photovoltaic output smoothing, wherein the first layer provides data conditioning of input signals, the second layer computes a power command for different energy storage elements using fuzzy logic based on present status inputs from each component of the hybrid energy storage system, and the third layer adapts operation rates based on energy storage element dynamic characteristics.

5. The system of claim 1 , comprising an operation rate conditioning layer to alter an operation rate for different energy storage element based on their dynamic characteristics.

6. The system of claim 1 , comprising a supercapacitor operated on a high rate with fast dynamic characteristics and a battery system operated at a low rate to reduce the number of micro-cycles during system operation.

7. The system of claim 1 , wherein the fuzzy controller is updated along with the changes in energy storage components through rule base and membership function updates.

8. The system of claim 1 , wherein the rule base includes rules to
a) maintain BE in a range of SOC where it has capacity to absorb and deliver energy
b) maintain UC in a range of SOC where it can absorb as well as deliver power quickly
c) minimize the change in battery current
d) aid UC in cases where SOC of UC goes below the recommended lower value by additional discharging of BE
e) aid UC in cases where SOC of UC goes above the recommended higher value by additional charging of BE; and
f) slow down charging/discharging when close to upper/lower SOC limit to permit smooth SOC curves.

9. A method to control a power system with an energy generator and a hybrid energy storage system including two or more energy storage system, each with different energy storage capacity and energy discharge capacity, comprising
developing data for one or more control variables refined from expert knowledge, trials and tests;
providing the control variables to a fuzzy logic controller with a rule base and membership functions; and
controlling the energy generator and the hybrid energy storage system using the fuzzy logic controller;
wherein the exponential smoothing comprises
y ( t )=( a )· x ( t )+(1− a )· y ( t− 1)

where x(t) is the input to the filter and y(t−1) is the output at previous time step (t−1).

10. The method of claim 9 , comprising a supercapacitor operated on a high rate with a fast responding time and a battery system operated at a low rate to reduce the number of micro-cycles during system operation.

11. The method of claim 9 , comprising updating the fuzzy controller and changes in energy storage components through rule base and membership function updates.

12. The method of claim 9 , wherein the rule base includes rules to:
maintain BE in a range of SOC where it has capacity to absorb and deliver energy;
maintain UC in a range of SOC where it can absorb as well as deliver power quickly;
minimize the change in battery current;
aid UC in cases where SOC of UC goes below the recommended lower value by additional discharging of BE;
aid UC in cases where SOC of UC goes above the recommended higher value by additional charging of BE; and
slow down charging/discharging when close to upper/lower SOC limit to permit smooth SOC curves.

13. A power system, comprising:
an energy generator;
a hybrid energy storage system (HSS) including two or more energy storage system, each with different energy capacity and power capacity;
a fuzzy logic controller with a rule base and membership functions for control variables refined from expert knowledge, trials and tests, the fuzzy logic controller coupled to a hybrid energy storage system with a low energy density source coupled to a high energy density source; and
an ultra-capacitor coupled to a battery, wherein the ultracapacitor alleviates high power pressure on the battery and wherein the battery charges the ultracapacitor.

14. The method of claim 9 , comprising an operation rate conditioning layer to alter an operation rate for different energy storage element based on dynamic characteristics.

15. The method of claim 9 , comprising performing exponential smoothing for suppressing noise in voltage and current measurements.

16. The method of claim 9 , wherein the HSS includes a low energy density source coupled to a high energy density source.

17. The method of claim 16 , comprising executing rules in the fuzzy logic controller with first, second and third layer to control the hybrid energy storage system for photovoltaic output smoothing, wherein the first layer provides data conditioning of input signals, the second layer computes a power command for different energy storage elements using fuzzy logic based on present status inputs from each component of the hybrid energy storage system, and the third layer adapts operation rates based on energy storage element characteristics.

18. The method of claim 16 , comprising an ultra-capacitor coupled to a battery, wherein the the ultracapacitor alleviates high power pressure on the battery and wherein the battery charges the ultracapacitor.

Assignees

• Nec Lab America Inc
• Nec Corp

Inventors

• Ye Yanzhu
• Sharma Ratnesh

Classifications

• G06N7/02

  using fuzzy logic (computing arrangements based on biological models G06N3/00; computing arrangements using knowledge-based models G06N5/00) · CPC title

• G05F1/66 Primary

  Regulating electric power · CPC title

• Y02E70/30

  Systems combining energy storage with energy generation of non-fossil origin · CPC title

• G05B15/02

  electric · CPC title

• H02J7/35

  with light sensitive cells · CPC title