Adaptive control of hybrid ultracapacitor-battery storage system for photovoltaic output smoothing

Patent metadata

Field	Value
Publication number	US-9536205-B2
Application number	US-201414162732-A
Country	US
Kind code	B2
Filing date	Jan 23, 2014
Priority date	Jan 24, 2013
Publication date	Jan 3, 2017
Grant date	Jan 3, 2017

Abstract

A hybrid ultracapacitor-battery energy storage system is integrated with a photovoltaic system to help solve fluctuations. A fuzzy-logic-based adaptive power management system enables optimization of the power/energy distributions and a filter-based power coordination layer serving as a rudimentary step for power coordination among the hybrid storage system and a fuzzy-logic-based control adjustment layer that keeps monitoring the operation status of all the energy storage devices, taking into account their dynamic characteristics, and fine-tuning the control settings adaptively.

First claim

The invention claimed is:

1. A method comprising;
employing a fuzzy logic-based adaptive power management system in a an electrical energy system;
coupling a photovoltaic system to the power management system;
coupling a first capacitor based energy storage system to the power management system;
coupling a second battery energy based storage system to the power management system; and
coupling a storage of knowledge of system operation and operation of energy storage related devices within an electric energy system to the power management system, and a management storage system communicating with the photovoltaic system, first capacitor and battery based energy system and storage of knowledge for influencing energy fluctuations ahead of detailed control loops in power electronic devices, the fuzzy logic based adaptive system including a filter based power coordination layer for power conditioning among the energy based storage system and a fuzzy logic based control adjustment for monitoring operational status of all energy storage devices taking into account their dynamic characteristics for tuning control settings with the system adaptively and influencing optimal power or energy distributions within the system; and
prioritizing with fuzzy logic to prevent saturation or depletion of energy capacity with a priority to prevent saturation or depletion of energy capacity of the battery energy based storage system;
wherein the fuzzy logic based control adjustment comprises applying rules:
1) If SoC uc is NB or SoC be , is NB, ΔT 1 is NB;
2) If SoC uc is PB or SoC be , is PB, ΔT 1 is NB;
3) If SoC uc is NS or SoC be , is NS, ΔT 1 is NS;
4) If SoC uc is PS or SoC be , is PS, ΔT 1 is NS;
5) If SoC uc is ZO and SoC be , is ZO, ΔT 1 is PB or ZO,
where SoC uc is system operation of ultracapacitor, SoC be , is system operation of the battery system, fuzzy variables of input and output are expressed as “positive big (PB)”, “positive medium (PM)”, “positive small (PS)”, “Zero (ZO)”, “negative big (NB)”, “negative medium (NM)”, “negative small (NS)”, and T 1 is smoothing parameter.

2. The method of claim 1 , wherein the filter based power coordination ensures that a supercapacitor storage device provides for compensating sudden changes in rapidly fluctuating PV output power while the battery covers a smoothing power profile, and during normal operation periods, the references for different energy storage devices work sufficiently with the references being modifiable under certain conditions in order to improve the overall system performance.

3. The method of claim 2 , wherein the fuzzy logic based control adjustment comprises that during the system operation, the energy storage device will provide for keeping switching among different operation modes and present different dynamics, achieving smooth changes over various operation modes and maintaining consistent system performance including tuning the control along with those changes, and also providing advantages in non-linear system control without requiring a precise mathematical modeling or sophisticated computations in certain situations.

4. The method of claim 1 , wherein the fuzzy logic based control adjustment comprises fuzzy logic based smoothing control, fuzzy logic based battery power control and fuzzy logic based ultracapacitor power control.

5. The method of claim 1 , wherein the fuzzy logic based smoothing control comprises low pass filtering that influences a smoothing power profile, a difference between smoothing power and actual power being covered by discharging or charging of a hybrid electrical energy system, a parameter in the smoothing control determining a smoothing performance in that as the parameter becomes larger the more fluctuating power needs to be compensated by hybrid electric storage system which means more energy and power will be requested out of energy storages.

6. The method of claim 1 , wherein the fuzzy logic based smoothing control comprises preventing the saturation or depletion of energy capacity, and ensuring sustainable system operation with states of charge for capacitance of the battery energy and ultracapacitor being updatable when different unit sizes are applied in the PV system, with a power-intensive storage the ultracapacitor may presents a relatively fluctuating state of charge profiles is prone to energy depletion and saturation so positive big and negative big range take up a larger range than a battery in the system.

7. The method of claim 1 , whereinthe fuzzy logic based control adjustment comprises fuzzy logic based ultracapacitor power control adjusting a simulated ultracapacitor reference current by adding a deviating value, output of the ultracapacitor reference current being directly applicable on a converter current control loop, and including fuzzy rules for preventing the ultracapacitor from energy depletion or saturation.

8. The method of claim 1 , wherein the fuzzy logic based control adjustment comprises fuzzy logic based battery power control adjusting a simulated battery reference current by adding a deviating value and an output of the battery reference current can be directly applied on a converter current control loop.

9. The method of claim 1 , wherein fuzzy control in the fuzzy logic-based adaptive power management system comprises configuring from a heuristic knowledge of the system operation in the storage of knowledge, tuning the fuzzy control through system simulation and configuration of the adaptive power management system while keeping the system in a sustainable operation status and preserving energy storage devices acceptable life cycles.

10. The method of claim 1 , wherein the fuzzy logic based control adjustment comprises fuzzy logic based smoothing control, fuzzy logic based battery power control and fuzzy logic based ultracapacitor power control.

Assignees

• Nec Lab America Inc
• Nec Corp

Inventors

• Ye Yanzhu
• Sharma Ratnesh K
• Shi Di

Classifications

• Y02E70/30

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

• Y02E40/10

  Flexible AC transmission systems [FACTS] · CPC title

• Y02E10/50

  Photovoltaic [PV] energy · CPC title

• G06N7/02 Primary

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

• H02J7/35

  with light sensitive cells · CPC title