Predictive Control of Multilevel Converters For

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems

Venkata Narasimha Rao Yaramasu

PhD Final Defense Exam, Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON M5B 2K3 CANADA

January 17, 2014.

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Outline

Outline of Presentation

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Introduction Motivation for Dissertation Research Generalized Predictive Control of Multilevel Diode-Clamped Converters Predictive Current Control of Grid-Tied Inverters Predictive Power Control of Grid-Tied Inverters Predictive Control of 3L-Converters Based PMSG-WECS Predictive Control of 4L-Converters Based PMSG-WECS Low Voltage Ride-Through Enhancement for 3L-Converters Based PMSG-WECS Conclusion

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Introduction Review of Wind Energy

Installed Capacity 300

282.6 Cumulative Annual

Installed Capacity (GW)

250

238.1 198.0

200 158.9 150 120.6 93.9

100 50 0

6.1

39.4 23.9 31.1 7.6 10.2 13.6 17.4

47.6

59.1

73.9

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Year

Excellent growth rate of more than 19% The cumulative wind capacity would reach 760 GW by 2020 In 2012, approximately 45 GWs of new wind power is installed Approximately 83 countries are using wind energy as a commercial basis # 3/30

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Introduction Review of Wind Energy

Evolution of Megawatt WECS

Boeing 747

1980 50kW Φ 15m H 24m

1985 100kW Φ 20m H 43m

1990 1995 Statue 2000 500kW 800kW 2MW of Φ 40m Φ 50m Liberty Φ 80m H 54m H 80m H 92m H 104m

2005 5MW Φ 124m H 114m

2010 7.5MW Φ 126m H 138m

London Gherkin H 180m

2015 10MW Φ 145m H 180m

Turbine size increased from 50 kW in 1980 to 7.5 MW in 2010 10-20 MW turbines will be in market by 2020 Large turbines are efficient and cost effective # 4/30

2020 15-20MW Φ 150-200m H 200-250m

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Introduction Review of Wind Energy

Commercial Configurations of WECS

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Type-1: Type-2: Type-3: Type-4:

SCIG based WECS with ±1% speed-range WRIG based WECS with ±10% speed-range DFIG based WECS with ±30% speed-range PMSG/WRSG/SCIG based WECS with 0–100% speed-range GE (USA) 15.5% Type−3, 4 (3S, DD)

Rest of the world 22.6% Type−1 to 4

Mingyang (China) 2.7% Type−3

Vestas (Denmark) 14% Type−3, 4 (3S)

Sinovel (China) 3.2% Type−3 United Power (China) 4.7% Type−3 Goldwind (China) 6.0% Type−4 (DD)

Siemens (Germany) 9.5% Type−4 (3S, DD)

Enercon (Germany) Suzlon (India)Gamesa (Spain) 6.1% 8.2% 7.4% Type−4 (DD) Type−3 Type−3, 4 (2S) 100% =44,799 MW

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Motivation for Dissertation Research

Dissertation Objectives

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Dissertation Objectives

DD-PMSG Based MV-MW-WECS

Investigation of

Investigation of

Next-Generation

Next-Generation

Power Converters

Control Schemes

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Motivation for Dissertation Research Investigation of Power Converters

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2LVSR

2LVSI

Filter

LVPMSG

LVGrid

activefrontend1 activefrontend2

Existing Full-Scale Power Converters

3LVSR

3LVSI

MVPMSG

Filter

(Topology-2)

(Topology-1) Low Voltage (LV)

Medium Voltage (MV)

(Topology-3) 2L2LBoost PFE VSI Filter LVGrid

Not explored yet passivefrontend1 passivefrontend2

LVPMSG

MVGrid

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Motivation for Dissertation Research Investigation of Power Converters

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(MV)

(MV)

PMSG

WRSG

3L-Boost Converter

3L-VSI

Novel configuration for 3–4 kV class WECS Combines the advantages of low-cost PFE and efficient multilevel converters No boundary conditions for dc-link capacitor voltages Significant improvement in the grid power quality

Proposed Topology

Proposed Configuration–1: Three-Level Converters

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Motivation for Dissertation Research Investigation of Power Converters

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(MV)

(MV)

PMSG

WRSG

4L-Boost Converter

4L-VSI

Novel configuration for 4–10 kV class WECS Higher levels of MV operation without switching devices in series Lower size for grid-side filter Excellent grid power quality compared to 3L converters

Proposed Topology

Proposed Configuration–2: Four-Level Converters

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Motivation for Dissertation Research Investigation of Control Schemes

Overview of Control Schemes

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Converter Control Techniques

Hysteresis Control

Linear Control

Sliding Mode Control

Intelligent Control

Predictive Control

Current Control

Current Control

Current Control

Fuzzy Logic Control

Deadbeat Control

Model Predictive Control (MPC)

Direct Torque Control (DTC)

Field Oriented Control (FOC)

Voltage Control

Artificial Neural Network Based Control (ANN)

Hysteresis Based Control

MPC With Continuous Control Set (CCS)

Direct Power Control (DPC)

Voltage Oriented Control (VOC)

Trajectory Based Control

MPC With Finite Control Set (FCS)

Classical Control Techniques

Fuzzy-ANN Control

Advanced Control Techniques

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Motivation for Dissertation Research Investigation of Control Schemes

Linear Control Technique i ∗ (k)

v ∗ (k)

e + −

PI

i (k) Carrier Signal

vcr (k)

Pulse Width/ Space Vector Modulation (PWM/SVM)

Sa

Inverter

Sb Sc

Most popular linear control method Uses cascaded linear regulators and a modulation stage SVM involves several design steps and complex modeling Several challenges related to fast dynamic response and good power quality # 11/30

3−φ L/M/G

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Motivation for Dissertation Research Investigation of Control Schemes

Finite Control-Set Model Predictive Control Technique

i ∗ (k)

i (k)

Extrapolation

Predictive Model

i ∗ (k + 1)

i p (k + 1)

Cost Function Minimization gk

Sa

Inverter

Sb Sc

Established control strategy in slow process systems Uses simple concepts and easy to understand Optimizations are greatly simplified Can handle multivariable control programs in a decoupled manner # 12/30

3−φ L/M/G

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Motivation for Dissertation Research Investigation of Control Schemes

Cost Function Flexibility

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Secondary Objectives

Capacitor Voltages Balancing  p p  λdc ∗ vc1 − vc2 vcp = (Sk+1 ) Filter Resonance Mitigation λr ∗ |W1 i p | i p = (Sk+1 )

λdc

λr

Peak Current Limitation λlim ∗ |i p | < imax i p = (Sk+1 )

Switching Frequency Reduction λswc ∗ nswc nswc = (Sk+1 )

Weighting Factors

λswc   Objectives     ∗ Primary i − iap  + i ∗ − i p  + ic∗ − icp  b     ∗a p   b∗ va − va  + v − v p  + vc∗ − vcp  b b |P ∗ − P p |

λlim

λcmv

|Q ∗ − Q p |   T ∗ − Tep    e∗ ψ − ψsp 

Common-Mode Voltage Minimization λcmv ∗ cmv cmv = (Sk+1 )

s

λss

λvdc

Net dc-bus Voltage Control  ∗ p  λvdc ∗ vdc − vdc p vdc = (Sk+1 )

λswl

Switching Losses Reduction λswl ∗ Eswl Eswl = (Sk+1 )

Spectrum Shaping λss ∗ |F (i ∗ − i p )| λss ∗ |DFT (i ∗ − i p )| i p = (Sk+1 )

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Generalized Approach for Predictive Control in High-Performance Multilevel Diode-Clamped Converters Introduction

Control Requirements and Challenges for MLDCCs HighPerformance MLDCCs

Control Requirement

Possible Solutions

Recommended Solution

Existing Solution Proposed Solution

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Load/Grid Current Control

dc-link Cap. Voltage Control

Switching Frequency Minimization

Common-Mode

Voltage Minimization

Software

Software

Hardware

Software

Software

Hardware

Reconfiguration

Reconfiguration

Reconfiguration

Reconfiguration

Reconfiguration

Reconfiguration

Generalized Approach

Classical PWM/SVM Generalized FCS-MPC

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Generalized Approach for Predictive Control in High-Performance Multilevel Diode-Clamped Converters Control Scheme

Generalized Control Scheme

# 15/30

MLDCC

vdc

vc(m−1)

ia (k)

Rfa , Lfa Ra

ea

ib (k)

Rfb , Lfb Rb

eb

P

vc(m−2)

n vc(m−3) vc1

ic (k) Rfc , Lfc Rc

N 6 × (m − 1)

ec Back emf/ Grid

S(k)

Cost function

iα∗ (k iβ∗ (k

+ 2) + 2)

Extrapolation

Minimization vc1 (k. + 2) .. vc(m−1) (k + 2)

iα (k + 2) iβ (k + 2) Controller

S(k) iα (k) iβ (k)

iα∗ (k) iβ∗ (k)

Predictive

vc1.(k) .. vc(m−1) (k)

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Generalized Approach for Predictive Control in High-Performance Multilevel Diode-Clamped Converters Control Scheme

Cost Function Definition g (k) = gtrack (k) + gbal (k) + gswc (k) + gcmv (k)  2 2 gtrack (k) = [iα∗ (k + h) − iα (k + h)] + iβ∗ (k + h) − iβ (k + h)  2 gbal (k) = λdc · [vcj (k + h) − vcj+1 (k + h)] j=1,··· ,m−1

gswc (k) = λswc ·



swcx

x=a,b,c

gcmv (k) = λcmv · |vcm | All the control goals are modeled in terms of converter switching states. The control requirements are achieved simultaneously. A detailed empirical analysis is provided for weighting factors selection. Two-step predictive control is introduced. # 16/30

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Generalized Approach for Predictive Control in High-Performance Multilevel Diode-Clamped Converters Simulation Results

Simulation Results: DC Capacitor Voltage Control

# 17/30

λdc = 0

λdc = 0.1 300

λdc = 0.1

vc1

150 vc2

0

(a) 3L-DCC

200

vc1

100 vc2

vc3

0

(b) 4L-DCC 150

vc3

vc1

75 vc4

0 120

vc1

vc2 (c) 5L-DCC vc4

vc2

60 vc3

0 0

0.1

vc5 0.2 0.3 Time (sec) (d) 6L-DCC

0.4

0.5

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Predictive Current Control of Grid-Tied Diode-Clamped Inverters Control Scheme

Overall Control Scheme Four-level Inverter

idc

via + − +

Rdc

− +

E

−

∗ (k + 1) iqg

vc1 (k)

# 18/30

λswc

Sjx (k − 1) θg (k) vc1 (k) vc2 (k) vc3 (k)

vib

vc2 (k)

λdc

Look-Up Table

Lag

Rbg

Lbg

Rcg

Lcg

vag

iag

vc3 (k)

Power flow

∗ (k + 1) idg

Rag

vic 18 Sjx (k) Cost Function Minimization

ibg

vbg

icg

vcg

Power flow SRF-PLL

∗ (k + 1) idg ∗ (k + 1) iqg

vc1 (k + 1) idg (k + 1) iqg (k + 1) vc2 (k + 1) vc3 (k + 1) Predictive Model

iag (k) ibg (k) vag (k)vbg (k)

Lagrange Extrapolation ∗ (k) idg

∗ (k) iqg

abc/dq Transformation

÷ PI −1.5vdg (k) Qg∗ (k)

− + ∗ (k)pu vdc

vdg (k) vqg (k) idg (k) iqg (k)

θg (k)

+ + +

vc1 (k)pu vc2 (k)pu vc3 (k)pu

idg (k) iqg (k) vdg (k) vqg (k)

n

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Predictive Current Control of Grid-Tied Diode-Clamped Inverters Control Scheme

Cost Function Definition ∗ g (k) = (idg (k + 1) − idg (k + 1))2 ∗ + (iqg (k + 1) − iqg (k + 1))2

+ λdc ∗ {

2  ([vcj (k + 1) − vcj+1 (k + 1)]2 ) j=1

+ λswc

+ [vc1 (k + 1) − vc3 (k + 1)]2 }  ∗ swcx x=a,b,c

System Analysis: Steady-state analysis Transient-state analysis DC-link dynamics Switching frequency regulation # 19/30

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Model Predictive Decoupled Active and Reactive Power Control for Grid-Tied Diode-Clamped Inverters Control Scheme

Overall Control Scheme

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Front-end Converter with Net dc-bus Voltage Control

MV Grid

Lg

a, b, c

vc1 (k) D

ig (k)

vc2 (k)

vg (k)

idg (k)

E

SRF

abc/dq

vc3 (k)

θg (k)

iqg (k)

PLL

18 vdg (k)

S(k) Cost Function

Pg∗ (k

vqg (k)

+ 1) Extrapolation

Minimization vc1 (k + 1)

Pg (k + 1)

vc2 (k + 1)

Qg (k + 1)

vc3 (k + 1) S(k) θg (k)

Qg∗ (k + 1)

Discrete-time Predictive Controller

Qg∗ (k)

Grid Operator

MPPT

vc1 (k) vc2 (k)

vw (k)

vc3 (k) vdg (k + 1)

vdg (k)

Pg∗ (k)

idg (k)

Anemometer

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Model Predictive Decoupled Active and Reactive Power Control for Grid-Tied Diode-Clamped Inverters Control Scheme

Cost Function Definition g (k + 1) = ||Pg∗ (k + 1) − Pgp (k + 1)|| + ||Qg∗ (k + 1) − Qgp (k + 1)|| p p + λdc ∗ ([vc1 (k + 1) − vc2 (k + 1)]2 p p + [vc2 (k + 1) − vc3 (k + 1)]2

+ λswc

p p + [vc3 (k + 1) − vc1 (k + 1)]2 ) ∗ (swca + swcb + swcc )

System Analysis: Transient- and steady-state analysis Comparison to classical VOC Comparison to standard extrapolation Capacitor voltages balancing # 21/30

Robustness analysis

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Predictive Control of Three-Level Converters Based PMSG-WECS Control Scheme

Control Scheme Wind Turbine

# 22/30

Three-Level Boost Converter

Diode Rectifier Direct-Driven MV PMSG

dc-Link

MV Grid

Rg , Lg

vg (k)

a, b, c

vc1 (k)

idc (k) vin (k)

ig (k) iαg (k)

vc2 (k)

ωm (k)

iβg (k) 2

∗ (k) Pdc

Extrapolation

Boost

io1 (k)

Output Currents

Calculator ωm (k)

Minimization

Minimization vc1 (k + 1)

io2 (k)

vc2 (k + 1)

Predictive Control of Boost Converter

12

∗ Cost function, gi (k) iαg (k + 1)

Cost function, gt (k)

idc (k + 1) ×

Si (k)

St (k)

St (k − 1)

÷

∗ (k + 1) idc

ig (k)

Si (k)

vin (k)

idc (k)

PLL

vαg (k) vdg (k) vβg (k)

θg (k)

Extrapolation ∗ (k) iαg ∗ (k) iβg

iβg (k + 1)

θg (k)

dq/αβ

Predictive Control of NPC Inverter

12 MPPT

∗ (k + 1) iβg

abc/αβ abc/dq

iαg (k + 1) Si (k − 1)

∗ (k) idc

vin (k)

Three-Level NPC Converter

∗ (k) iqg

−1.5vdg (k) ÷ ×

vc1 (k)

vαg (k)

iαg (k)

vc2 (k)

vβg (k)

iβg (k)

Qg∗ (k)

∗ (k) idg

PI

+ −

∗ (k) vdc

vdc (k)

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Predictive Control of Three-Level Converters Based PMSG-WECS Control Scheme

Cost Function Definition ∗ gt (k) = [idc (k + 1) − idc (k + 1)]2

+ λdc,b ∗ [vc1 (k + 1) − vc2 (k + 1)]2  + λswc,b ∗ | Sjt (k) − Sjt,op (k) | j=1,2



2  ∗ 2 ∗ (k + 1) − iαg (k + 1) + iβg (k + 1) − iβg (k + 1) gi (k) = iαg   + λswc,i ∗ | Sjx (k) − Sjx,op (k) | j=1, 2 x=a,b,c

System Analysis: Dynamic changes in wind speed and reactive power Comparison to BTB-NPC converters Capacitor voltages balancing # 23/30

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Predictive Control of Four-Level Converters Based PMSG-WECS Control Scheme

Overall Control Scheme Four-Level Boost Converter

Diode Rectifier Direct-Driven MV PMSG

C1

idc (k) + v (k) −in

C2

ωm (k)

Four-Level Inverter

dc-Link

C3

Filter Rg , Lg

+ vc1 (k) − + vc2 (k) − + vc3 (k) −

MV Grid iag (k) vag (k) ibg (k) vbg (k) icg (k) vcg (k)

Wind Turbine MPPT

3

ωm (k) ∗ (k) ωm

vw (k)

− +

Sb (k)

18

Si (k)

Pin∗ (k) PI |vc1 − vc2 | + |vc2 − vc3 | + |vc1 − vc3 | = 0

Control System for

Control System for

Four-Level

Four-Level

Boost Converter

Diode-Clamped Inverter

# 24/30

idc (k)

Si (k)

iag (k) ibg (k) icg (k)

vin (k)

Anemometer vc1 (k) vc2 (k) vc3 (k)

iag (k) ibg (k) icg (k)

vag (k) vbg (k) vcg (k)

vc1 (k) vc2 (k) vc3 (k)

∗ (k) vdc

Qg∗ (k)

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Predictive Control of Four-Level Converters Based PMSG-WECS Control Scheme

Cost Function Definition 4L-boost converter cost function: gb (k) = gtrack,b (k) + gdc,b (k) + gswc,b (k) Pin (k + 2) = vin (k + 2) · idc (k + 2) gdc,b (k) = λdc,b ∗ [vc1 (k + 2) − vc2 (k + 2)]2 + λdc,b ∗ [vc2 (k + 2) − vc3 (k + 2)]2 + λdc,b ∗ [vc1 (k + 2) − vc3 (k + 2)]2  gswc,b (k) = λswc,b ∗ | Sxf (k) − Sxf ,op (k) | x=1,2,3

4L-inverter cost function:

# 25/30

gi (k) = gtrack,i (k) + gswc,i (k) + gcm,i (k) 2  ∗ 2 ∗ gtrack,i (k) = idg (k + 2) − idg (k + 2) + iqg (k + 2) − iqg (k + 2)   gswc,i (k) = λswc,i ∗ | Sxj (k) − Sxj,op (k) | 

x=1, 2, 3 j=a,b,c

gcm,i (k) = λcmv,i ∗ | vcm (k) |

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Predictive Control for Low Voltage Ride-Through Enhancement of Three-Level Converters Based WECS Overview

Overview

# 26/30

FCS-MPC is proposed for LVRT enhancement of DD-PMSG based MW-WECS The turbine-generator rotor inertia is used to store the active power surplus Three-level converters are used No additional hardware is used Coordination of boost and NPC converters is formulated Simulation and experimental results are presented

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Predictive Control for Low Voltage Ride-Through Enhancement of Three-Level Converters Based WECS Control Scheme

Overall Control Scheme Diode Rectifier

Three-Level dc Link-1 Boost Converter

dc Link-2

R1 , L1

D1

P(1)

idc Pw

ibs

vc1

+ Cin ics

Direct Driven MV PMSG

−

S1b

S1c

S2a

S2b

S2c Rg , Lg

C2 −

ic2

D2

Grid Integration Pg , Q g

iag ibg

+

S2

Wind Turbine

# 27/30

vdc

Z(0)

vin

vc2

Wind

ias

S1a

Filter

+ ic1 C1 −

S1

icg

S 1a

S 1b

S 1c

S 2a

S 2b

S 2c

vag vbg vcg

Ps

Pm

Three-Level NPC Inverter

Pdc

N(-1) 2

TLB Gating Signals, Sb

12

NPC Gating Signals, Si

Wind Turbine

Generator-side

Grid-side

Pitch Controller

Converter Controller

Inverter Controller

∗ idc

∗ idg

Generator Integration Supervisory System ∗ iqg

|vc1 − vc2 | = 0 Generation of Reference Control Variables Control System

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Predictive Control for Low Voltage Ride-Through Enhancement of Three-Level Converters Based WECS Control Scheme

Generation of Reference Control Variables ∗ (k) ωm

λT ,op ×vw (k) rT

+ −

vw (k)

PI

∗ idc,NORM (k)

∗ (k) idc

0 1

∗ (k) idc,LVRT

ωm (k) Anemometer

3.062 × vbg vc1 (k) vc2 (k) ibg ·

√

LVRT Signal

∗ (k) vdc

+ − 

PI vdc (k)

+

∗ iqg ,LVRT (k)

(·)2

−

≤ 0.9 LVRT Signal 0 = NORM 1 = LVRT

Qg∗ (k)

∗ (k) idg

0

∗ idg ,LVRT (k)

2

vdg ,pu (k)

∗ idg ,NORM (k)

1

(·)2

Grid Integration Supervisory System

# 28/30

LVRT Signal

MPPT

×

÷

−1.5 vdg (k)

vdg (k) Look-up Table



(·) LVRT Signal ∗ iqg ,NORM (k) 0 ∗ iqg ,LVRT (k)

∗ (k) iqg

1

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems Conclusions

Conclusions A detailed survey on wind energy industry, power converters and control schemes is presented Two next generation power converters are proposed 3–10 kV WECS Continuous- and discrete-time models are presented A simple and generalized approach is proposed to control the MLDCCs Two advanced techniques are proposed to control the grid-tied converters Complete control systems have been built for the 3L and 4L converters based WECS A simple solution is proposed for the LVRT enhancement Variable switching frequency nature of the FCS-MPC is mitigated Empirical solutions for the weighting factor selection are presented. A novel extrapolation method is proposed Two-step predictive control is introduced A novel delay compensation technique is introduced for the FCS-MPC Robustness of the proposed predictive controller is investigated Several prototype converters are developed 22 Journal and 16 Conference papers are developed # 29/30

Predictive Control of Multilevel Converters For Megawatt Wind Energy Conversion Systems

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