corpe ieee peac 2018 no reprint without...

CORPE

Design for Reliability in Power Electronic Systems

Frede Blaabjerg Villum Investigator

Email: [email protected] of Reliable Power Electronics (CORPE)

Department of Energy TechnologyAalborg University, Denmark

IEEE PEAC 2018 No Reprint Without Authorization

http://www.corpe.et.aau.dk/

FREDE BLAABJERG, CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY SL IDE19-NOV-18

1 Towards Reliable Power ElectronicsBeyond Efficiency and Power Density

2IEEE PEAC 2018 No Reprint Without Authorization


► Power ElectronicsReinvent the way electrical energy processed

Electricity generation…

Electricity consumption…

InterfacesIntegration to electric gridPower transmissionPower distributionPower conversionPower control

Power Electronics enable efficient conversion and flexible control of electrical energy



► 100+ Years of Power Electronics

4

Reliability becomes one of the key application-oriented challengesIEEE PEAC 2018 No Reprint Without Authorization


► Performance Factors of Power Electronics

CheaperLighterSmallerCoolermore Reliablemore Versatile…

CostPower densityEfficiencyReliabilityControl Input & output…

5

25% size, 17% weight


FREDE BLAABJERG, CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY SL IDE19-NOV-18 6

► Increasing Use of Power ElectronicsExample 1 – Towards Power Electronics Based Energy System



► Increasing Use of Power Electronics

7

Important issuesReliability/security of supply Efficiency, cost, volume, protectionControl active and reactive powerRide-through operation and monitoringPower electronics enabling technology

Example 2 – Electrical Energy Generation from Renewable Sources (1000 GW in 2018 !)

An Example of Full-Scale Power Converter



► Field Experience Examples 1/25 Years of Field Experience of a 3.5 MW PV Plant

Data source: Moore, L. M. and H. N. Post, "Five years of operating experience at a large, utility-scale photovoltaic generating plant," Progress in Photovoltaics: Research and Applications 16(3): 249-259, 2008

Unscheduled maintenance events by subsystem. Unscheduled maintenance costs by subsystem.(ACD: AC Disconnects, DAS: Data Acquisition Systems)



► Field Experience Examples 2/2350 onshore wind turbines in varying length of time (35,000 downtime events)

Contribution of subsystems and assemblies to the overall failure rate of wind turbines.

Contribution of subsystems and assemblies to the overall downtime of wind turbines.

Data source: Reliawind, Report on Wind Turbine Reliability Profiles – Field Data Reliability Analysis, 2011.



► The Reliability Challenges in Industry

10

Customer expectations

Replacement if failure Years of warranty

Low risk of failure Request for

maintenance

Peace of mind Predictive

maintenance

Reliability target Affordable returns (%) Low return rates ppm return rates

R&D approach Reliability test Avoid catastrophes

Robustness tests Improve weakest

components

Design for reliability Balance with field load

R&D key tools Product operating tests Testing at the limits

Understanding failure mechanisms, field load, root cause, …

Multi-domain simulation …

Past Present Future

Product + Service (new business)Data + Physics of Failure



Lifetime Targets in Power Electronics Applications

Applications Typical design target of Lifetime

Aircraft 20-25 years (100,000 hours flight operation)Automotive 15 years (10,000 operating hours, 300, 000 km)Industry motor drives 5-20 years (40,000 hours in at full load)Railway 20-30 years (73,000 – 110,000 hours)Wind turbines 20-25 years (120,000 hours)Photovoltaic plants 30 years (90,000 to 130,000 hours)



► Changing Mindset and Reliability Culture

12

Reduce costs by improving reliability upfront

Source: DfR Solutions, Designing reliability in electronics, CORPE Workshop, 2012.



► Changing Mindset and Reliability Culture

13

Example of Galaxy Note 7

96% of about 3 million Note 7 returned globally;Investigation involved 200,000 handsets, 30,000 standalone batteries, and 700 engineers; Estimated 5 billon loss

Source: http://www.consumerreports.org/smartphones/samsung-investigation-new-details-note7-battery-failures/

Bent negative electrodes caused one set of fires; Incorrect welding allowed for problems in a second batch of batteries

A negative example cost of poor reliability -Galaxy Note 7 Incident



2 Scientific ChallengesPower Electronics Reliability



► Key Reliability Metrics

15

Reliability The probability that an item can perform a required function under given conditions for a given time interval.

Lifetime (for an individual item) The time span between initial operation and failure

(Percentile) Lifetime (for a population of items)The expected life by which a certain percentage might have failed e.g., B10 lifetime – the time when 10% of the items fail.



► Scientific Challenges

16

Stress or strength

Freq

uenc

y of

occ

uran

ce

Load distribution L Strength distribution S

Time i

n serv

ice

Ideal case without degradation

Ideal case without degradation

Strength degradation

with time

Failure

End-of-life(with certain failure rate criterion)Failure

Extreme load

Nominal load

Understanding of load (mission profile), strength, and strength degradation

Stress-strength analysis to describe the cause of failure

■ Uncertainty in load and strength■ Time-consuming to understand degradation by testing




17

Understanding of load (mission profile), strength, and strength degradation

50403020100-10

9000

8000

7000

6000

5000

4000

3000

2000

1000

0

Temp (°C)

Freq

uenc

y

62

2793

5780

8588

8000

66766766

5515

3321

520630

Temperature, Phoenix, AZ - 2007

100806040200

14000

12000

10000

8000

6000

4000

2000

0

%RH

Freq

uenc

y

2831022

14781844

2579

4412

7241

11649

12737

4840

Relative humidity, Phoenix, AZ - 2007

Severe users!

Severe environment!IEEE PEAC 2018 No Reprint Without Authorization



18

Multi-components/multi-failure sources

System Level Application

Hardware Software Human Error

Power Semiconductos

PassiveComponents

OtherComponents

Transistors Diodes Magnetics Capacitors PCB Gate Drivers Fuses

f1 f2 f7 f3 f4 f5 f6

Wear-out Catastrophic

AssemblyLevel

ComponentLevel




19

Multi-time scale modeling/multi-stressor modeling

System Level► Wind turbine► Photovoltaics► Motor drives► Pump drives

► Power devices► Capacitors► PCB

• System–level mission profile.• Electrical/mechanical.

Models:• Component–level mission profile.• Losses, temperature, humidity, etc.

Models:

Mission profiles / Environmental Conditions:

System Specifications:• Machine type• Converter topology• Power device• Etc.

Vdc

I

fsw

Multi – time scale modelling

T

V

RH

Component LevelReliability

Multi – stressor modelling

Component Level System - LevelReliability

RBDAnalysis

Component Reliability

System Reliabilityfn(αn,η n,t)

f2(α2,η 2,t)

f1(α1,η 1,t)

Ta

Vibration

User InputLevel 1

User InputLevel 2

Component 1

Component 2

Component n



► The Research Scope of Power Electronics Reliability

20

Paradigm Shift■ From components to failure mechanisms■ From constant failure rate to failure level with time■ From reliability prediction to robustness validation■ From microelectronics to also power electronics

Sour

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3 State-of-the-ArtSelected examples of power electronics reliability research



Example 1 – Understanding of Component-level Degradation Through Multi-physics Simulation, Accelerated Testing, and Condition Monitoring



► Multiphysics Simulation

23

Simulation results are consistent with micro-sectioning analysis and four-point probing results of degraded modules

Source: Kristian Bonderup Pedersen, IGBT Module Reliability. Physics-of-Failure based Characterization and Modelling, PhDDissertation, CORPE, Aalborg University, 2015

Example – Degradation of IGBT modules based on physics-of-failure simulations



► Better Understanding in Component Degradation

24

Examples of Power Cycling Testing on IGBT Modules

Diagram of an advanced power cycling testing system

A low-power power cycling testing setup

1700 V/1000 A

600 V/30 A




25

Example of Degradation Testing of DC Film Capacitors under Humidity Conditions

A humidity-dependent lifetime model Optical microscopy investigation of one of the degraded samples

Capacitor degradation testing setup Degradation curve of one group of testing

85°C, 55%RH3,850 hours

Sour

ce: H

. Wan

g, D

. A. N

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26

Condition Monitoring of IGBT Modules and Capacitors

Gate Peak Current based IGBT Junction Temperature Monitoring

25°C

125°C3mV/°C

Peak detector output voltages

Gate voltage

1.0 µs/div

150 mV/div

3.3 V/div

Outcome■ Experimentally verified and

calibrated■ Gate voltage compensation

Condition Monitoring and Remaining Lifetime Prediction of Capacitors

Outcome■ An Artificial Neural Network (ANN) based method is applied for estimation of capacitance

■ Based on existing available information, pure software solution

Sour

ce: N

. Bak

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n El

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ical

Met

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for

Junc

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Tem

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Mea

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Example 2 – Impact of Mission Profile Resolution on the Predicted Lifetime of IGBT Modules in an Modular Multi-level Converter (MMC)



► Modular Multi-level Converter (MMC)

28

Background

MMC-based HVDC – Basic Scheme (Source: Siemens)



► Modular Multi-level Converter (MMC)

29

Down-scale sub-module



► Impact of the Mission Profile Resolution

30

Lifetime prediction

Lifetime distribution

Input

Output

Wind Speed

Power Conversion Model

Loss Model

Thermal Model

Counting

Emulate instantaneous losses

Thermal Model

vw

Pw

PT1, PD1, PT2, PD2

Average losses

Lifetime Model

Monte Carlo

Tj

Modules/IGBT/DiodeElectrical behaviorThermal parameters

m ϕ f0

Temperature swings at fundamental frequency

Junc

tion

tem

pera

ture

Design iterations to select proper IGBT modules

Mission profiles



1 hour/data

10 minutes/data

1 second/data

Different studies adopt different resolution of the wind speed, what is the impact on the predicted lifetime?

Source: ABB





(STO1s is stochastic model and 1s wind speed, IEC1s means IEC power curve and 1s wind speed, IEC10minmeans IEC power curve and 10min-average wind speed, IEC1h means IEC power curve and 1h-avergewind speed, STO1sREG means stochastic model and regenerated 1s wind speed based on 10min-averagewind speed. T1, D1, T2, D2 are IGBT1, Diode1, IGBT2, Diode2 respectively. CS, BS, BW mean chip solder,baseplate solder and bond wire respectively).

>7 times difference in degradation prediction for the power modules

Long-term high resolution data (e.g., 1s/data) and dynamicmodels are necessary for degradation performance and reliabilityassessment of electrical components.

Power modules



Example 3 – Two-Terminal Active Capacitors



Concept of a Two-terminal Active Capacitor

Active Capacitor§ Two-terminals only§ Impedance characteristics equivalent to

passive capacitorsA B

Active switches

Passive elements

Sampling and conditioningMicro-controller

Gate driversABi

ABv

Self-power Supply

Feature No signal connection to main circuit No auxiliary power supply Only two-terminal ”A” and ”B” connected to external main circuit

Retain the same level of convenience as a conventional passive capacitor Application independent Lowest apparent power processed by the auxiliary circuit Long life-time a goal

Source: H. Wang, H. Wang and F. Blaabjerg, ¨A two-terminal active capacitor device¨IEEE PEAC 2018 No Reprint Without Authorization


Proof-of-Concept of a Two-terminal Active Capacitor

An implementation of the two-terminal active capacitor concept

Internal auxiliary power from MOSFET

Source: Haoran Wang and Huai Wang, “A two-terminal active capacitor,” IEEE Transactions on Power Electronics, 2017

-50

0

50

100

Mag

nitu

de (d

B)

10-1 100 101 102 103 104-180

-135

-90

Phas

e (d

eg)

Frequency (Hz)

110 µF passive capacitor (3.4 J)

1100 µF passive capacitor (34.4 J)

Active capacitor1100 µF@100Hz (5.8 J)

High pass filter with cut off frequency of 10 Hz

Impedance characteristics of active capacitor



Key waveforms of the system with 110uF active capacitor

Key waveforms of the system with 1100uF passive capacitor

: [100V/ div]DC linkV −

: [100V/ div]ACv: [10A/ div]ACi

: [20ms/ div]t

Ripple ratio 4.1 %

: [100V/ div]DC linkV −

: [100V/ div]ACv: [10A/ div]ACi

: [20ms/ div]t

Ripple ratio 4.8 %

Single-phase system with active capacitor

ACv

gLActive

Capacitor

A

Resistive load

ACi+ -

DC linkV −

+

-B

Experimental Results of Active Capacitor

Top side

Bottom sideC1 Self-power supply

Micro-controller

GaN based full-bridge

Low voltage DC-link capacitor in full-bridge

High frequency filter inductor

High frequency filter capacitor



Example 4 – Design for Reliability and Robustness (DfR2) Tool Platform



► DfR2 Tool Platform Developed at CORPE, Aalborg University

38

DfR2 Tool

Circuit Simulation Software

FEM/CFD Simulation Software

Reliability Software

Environmental / Operational

Mission Profiles

System-Level Mission Profile

Modeling

System Circuit Simulation

Component Mission Profile

Modeling

Component-Level Reliability

Modeling

System-Level Reliability Modeling

Level 1 Level 2 Level 3 Level 4

Electro-Mechanical System

Power Electronics System

Application dependent Independent Independent Component dependent

Electro-Thermal Ta

RHTa_sys

RHsys

Vsys

Isys

Ta_comp

RHcomp

Vcomp

Icomp

Vcomp f1

f2

f3

f4

Design for Reliability and Robustness (DfR2) HelpSave Load

ExportBack Reset

Wind Power System

Environmental / Operating mission profiles

I.

Mission Profiles Component Reliability System Reliability

Component: Transistor – T1g

Level: IV

Display

Component: Transistor – T1g

Display

Sub-system: Power Module

DisplaySystem-level mission profile modeling

Power electronics circuit modeling

Component-level mission profile modeling

Component-level reliability modeling

System-level reliability modeling

Step I.

Step II.

Step III.

Step IV.

Step V.

Step VI.

Display: Voltage

Display: Temperature

Display: Static lifetime

Lifetime information(e.g. cycles to failure, confidence level, etc.)

Lifetime information(e.g. cycles to failure, confidence level, etc.)

Display: Unreliability curve

Interfaces to other softwareMain GUI panel

Modeling Framework

Design for Reliability and Robustness (DfR2)



► DfR2 Tool Platform Developed at CORPE, Aalborg University

39

Design for Reliability and Robustness (DfR2)



► Summary


CORPE

Design for Reliabiity in Power Electronics Systems

Frede Blaabjerg

eMail: [email protected]

Presentation at PEAC’2018 – Shenzhen, November 5, 2018

Thanks to Prof. Huai Wang, Aalborg University


http://www.corpe.et.aau.dk/

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2. REN21 - Renewables 2014 Global Status Report, June, 2014. (Available: http://www.ren21.net)3. Z. Chen, J.M. Guerrero, F. Blaabjerg, "A Review of the State of the Art of Power Electronics for Wind Turbines," IEEE Trans. on Power

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Power Electronics, Vol. 19, no. 4, pp. 1184-1194, 2004.5. A.D. Hansen, F. Iov, F. Blaabjerg, L.H. Hansen, “Review of contemporary wind turbine concepts and their market penetration,” Journal of

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Electronics, vol. 1, no. 3, pp. 139-152, 2013.9. H. Wang, M. Liserre, F. Blaabjerg, P. P. Rimmen, J. B. Jacobsen, T. Kvisgaard, J. Landkildehus, "Transitioning to physics-of-failure as a

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Electronics Magazine, vol.7, no. 2, pp. 17-26, Jun. 2013.11. S. B. Kjaer, J. K. Pedersen, and F. Blaabjerg, “A review of single-phase grid connected inverters for photovoltaic modules,” IEEE Trans.

on Ind. Appl., vol. 41, no. 5, pp. 1292-1306, Sep. 2005.12. K. Ma, F. Blaabjerg, and M. Liserre, “Thermal analysis of multilevel grid side converters for 10 MW wind turbines under low voltage ride

through”, IEEE Trans. Ind. Appl., vol. 49, no. 2, pp. 909-921, Mar./Apr. 2013.13. K. Ma, M. Liserre, and F. Blaabjerg, “Reactive power influence on the thermal cycling of multi-MW wind power inverter”, IEEE Trans. on

Ind. Appl., vol. 49, no. 2, pp. 922-930, Mar./Apr. 2013.14. C. Busca, R. Teodorescu, F. Blaabjerg, S. Munk-Nielsen, L. Helle, T. Abeyasekera, and P. Rodriguez, “An overview of the reliability

prediction related aspects of high power IGBTs in wind power applications,” Journal of Microelectronics Reliability, vol. 51, no. 9-11, pp.1903-1907, 2011.

15. E. Koutroulis and F. Blaabjerg, “Design optimization of transformerless grid-connected PV inverters including reliability,” IEEE Trans. onPower Electronics, vol. 28, no. 1, pp. 325-335, Jan. 2013.

16. K. B. Pedersen and K. Pedersen, “Bond wire lift-off in IGBT modules due to thermo-mechanical induced stress,” in Proc. of PEDG’ 2012,pp. 519 - 526, 2012.


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43. X. Wang, F. Blaabjerg, and P. C. Loh, “Grid-current-feedback active damping for LCL resonance in grid-connected voltage sourceconverters,” IEEE Transactions on Power Electronics (Early Access Article, DOI: 10.1109/TPEL.2015.2411851).

44. Y. Yang, H. Wang, and F. Blaabjerg, "Reduced junction temperature control during low-voltage ride-through for single-phase photovoltaicinverters,“ IET Power Electronics, pp. 1-10, 2014.

45. D. Zhou, F. Blaabjerg, M. Lau, and M. Tonnes, "Thermal cycling overview of multi-megawatt two-level wind power converter at full gridcode operation", IEEJ Journal of Industry Applications, vol.2, no.4 pp.173–182, 2013.

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47. K. Ma, F. Blaabjerg "Thermal optimized modulation method of three-level NPC inverter for 10 MW wind turbines under low voltage ridethrough", IET Journal on Power Electronics, vol. 5, no. 6, pp. 920-927, Jul 2012.

48. R. Wu, F. Blaabjerg, H. Wang, and M. Liserre, "Overview of catastrophic failures of freewheeling diodes in power electronic circuits",Microelectronics Reliability, Vol. 53, no. 9–11, Pages 1788–1792, Sep 2013.


http://dx.doi.org/10.1109/TPEL.2014.2382565



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48. F. Blaabjerg and K. Ma, "Wind Energy Systems," in Proceedings of the IEEE, vol. 105, no. 11, pp. 2116-2131, Nov. 2017.doi: 10.1109/JPROC.2017.2695485Open Access : URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7927779&isnumber=8074545

49. F. Blaabjerg, Y. Yang, D. Yang and X. Wang, "Distributed Power-Generation Systems and Protection," in Proceedings of the IEEE,vol. 105, no. 7, pp. 1311-1331, July 2017. doi: 10.1109/JPROC.2017.2696878

Open Access : URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7926394&isnumber=7951054


http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7927779&isnumber=8074545

http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7926394&isnumber=7951054

References (Harmonic Stability)1. X. Wang and F. Blaabjerg, “Harmonic stability in power electronic based power systems: concept, modeling, and analysis,” IEEE Trans. Smart Grid, Early Access, 2018. 2. X. Wang, F. Blaabjerg, and W. Wu, “Modeling and analysis of harmonic stability in ac power-electronics-based power system,” IEEE Trans. Power Electron., vol. 29, no. 12, pp. 6421-6432, Dec. 2014.3. X. Wang, L. Harnefors, and F. Blaabjerg, “Unified impedance model of grid-connected voltage-source converters," IEEE Trans. Power Electron., vol. 33, no. 2, pp. 1775-1787, Feb. 2018.4. X. Wang, F. Blaabjerg, and P. C. Loh, “Passivity-based stability analysis and damping injection for multiparalleled VSCs with LCL filters,” IEEE Trans. Power Electron., vol. 32, no. 11, pp. 8922-8935, Nov. 2017. 5. Y. Wang, X. Wang, F. Blaabjerg, and Z. Chen, "Small-signal stability analysis of inverter-fed power systems using component connection method," IEEE Trans. Smart Grid, Early Access, 2018.6. M. Lu, X. Wang, P. C. Loh, and F. Blaabjerg, “Resonance interaction of multi-parallel grid-connected inverters with LCL filter,” IEEE Trans. Power Electron., vol. 32, no. 2, pp. 894-899, Feb. 2017.7. J. Kwon, X. Wang, F. Blaabjerg, C. L. Bak, A. R. Wood and N. R. Watson, “Harmonic instability analysis of single-phase grid connected converter using harmonic state space (HSS) modeling method”, IEEE

Trans. Ind. Appl.,, Vol. 52, No. 5, pp. 4188 – 4200. Sept./Oct. 2016.8. L. Harnefors, X. Wang, A. G. Yepes, and F. Blaabjerg, “Passivity-based stability assessment of grid-connected VSCs – an overview,” IEEE J. Emerg. Sel. Topics Power Electron., vol. 4, no. 1, pp. 116-125, Mar.

2016.9. L. Harnefors, “Modeling of three-phase dynamic systems using complex transfer functions and transfer matrices,” IEEE Trans. Ind. Electron. vol. 54, no. 4, pp. 2239-2248, Aug. 2007.10. L. Harnefors, L. Zhang, and M. Bongiorno, “Frequency-domain passivity-based current controller design,” IET Power Electron., vol. 1, no. 4, pp. 455-465, Dec. 2008.11. J. Kwon, X. Wang, F. Blaabjerg, C. L. Bak, A. R. Wood, and N. Watson, “Linearized modeling methods of ac-dc converters for an accurate frequency response,” IEEE J. Emerg. Sel. Topics Power Electron., vol.

5, no. 4, pp. 1526-1541, Dec. 2017. 12. R. D. Middlebrook, “Predicting modulator phase lag in pwm converter feedback loop,” Powercon 1981, pp. 1-6. 13. R. D. Middlebrook and S. Cuk, “A general unified approach to modeling switching-converter power systems,” in Proc. IEEE PESC 1976, pp. 73-86.14. K. D. Ngo. “Low frequency characterization of PWM converters,” IEEE Trans. Power Electron., vol. PE-1, no. 4, pp. 223-230, Oct. 1986.15. X. Wang, Y. W. Li, F. Blaabjerg, and P. C. Loh, “Virtual-impedance-based control for voltage- and current-source converters,” IEEE Trans. Power Electron. vol. 30, no. 12, pp. 7019-7037,

Dec. 2015.16. X. Wang, F. Blaabjerg, Y. Pang, P. C. Loh, “A series-LC-filtered active damper with grid disturbance rejection for ac power-electronics-based power systems,” IEEE Trans. Power Electron.

vol. 30, no. 8, pp. 4037-4041, Aug. 2015.17. B. Ferreira, "Understanding the Challenges of Converter Networks and Systems: Better opportunities in the future," IEEE Power Electronics Mag., vol. 3, no. 2, pp. 46-49, Jun. 2016.18. B. Kroposki, et al., “Achieving a 100% renewable grid: operating electric power systems with extremely high levels of variable renewable energy,” IEEE Power & Energy Mag. vol. 15, no. 2,

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