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Smart Inverters and Controls for Grid-Connected Renewable Energy Sources

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Advances in Control Techniques for Smart Grid Applications

Abstract

This chapter describes the concept of smart inverters and their control strategies for the integration of renewable energy sources (RES) such as solar photovoltaic (PV), wind turbine generators, and fuel cell (FC) systems into the power grid. The necessity of an inverter in RES systems and the types of inverters according to their operational roles in grid-connected mode are described. Mathematical modeling of RES systems is described. The selection parameters criteria of the inverter, its control technique, and switching techniques are discussed. The role of smart inverters in renewable applications with the grid-support functions is reviewed. Three types of grid-interacting inverters are compared, and their control schemes are discussed. Various inner-loop controllers used at the primary control level are classified, and their operating methods are discussed. The advantages and disadvantages of the described inner-loop control techniques are summarized. The simulation diagram and results of a three-phase grid-connected solar PV system are shown in the chapter.

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Abbreviations

V :

Voltage (V)

f :

Frequency (Hz)

P :

Active power

Q :

Reactive power

V g :

Grid voltage

I g :

Grid current

t :

Time period (s)

p.u :

Per unit

P rated :

Rated active power (KW)

P max :

Maximum power

V max :

Maximum voltage

P min :

Minimum active power (W)

I rms :

Root-mean-square of the DER current

I rated :

DER unit rated current capacity

I 1 :

Fundamental current measured at the reference point

h :

Individual harmonic order

E mg :

Microgrid voltage measured at PCC

ω mg :

Microgrid frequency measured at PCC

E:

Error voltage

E* :

Reference voltage of the microgrid

ω:

Error frequency

ω* :

Reference frequency of the microgrid

upi(t):

Output response of the PI controller

upid(t):

Output response of the PID controller

upR(t):

Output response of the PR controller

K p :

Gain of the proportional controller

K i :

Gain of the integral controller

K d :

Gain of the derivative controller

PEpv:

Power error of the PV system

PEw:

Power error of the wind system

CPEpv:

Change in power error of the PV system

CPEw:

Change in power error of the wind system

P array :

Total power of the PV array

P m :

Power of each PV module

N p :

PV cells connected in parallel in an PV module

N s :

PV cells connected in series in an PV module

I ph :

Each PV module photo current

I scr :

Short circuit current of the cell

T :

Temperature in Kelvins (K)

S irrd :

Solar irradiation on the cell (mW/cm2)

K i :

Temperature coefficient of cell’s short circuit current

I rs :

PV module reverse saturation current

q :

Charge of an electron

E g :

Bandgap energy

A :

Diode ideality factor

K :

Boltzmann’s constant [J/K]

T r :

Cell referred temperature

I o :

Module saturation current

I pv :

Output current of a PV cell

V pv :

Output voltage of a PV cell

P pv :

Power of a PV cell

T pv :

Temperature of a PV cell

R se :

Series resistance of a cell

R sh :

Shunt resistance of a cell

P w :

Mechanical power of a wind turbine

A w :

Rotor blades intercepting area (m2)

V w :

Average wind speed (m/s)

ρ :

Air density (kg/m3)

λ :

Tip speed ratio

C p :

Power coefficient (or) Betz’s coefficient

ω r :

Angular speed (rad/s)

Q w :

Wind energy (KWh)

R w :

Radius of the wind turbine (m)

h ref :

Reference height of wind turbine (m)

h :

Height of the turbine to be measured

h o :

Measure of surface roughness

v(h):

Wind speed at height h (m/s)

v(href):

Wind speed at reference height h (m/s)

V Cin :

Cut-in wind speed

V Cout :

Rated wind speed

V RCout :

Rated cut-out speed

k :

Weibull form factor

ω opt :

Optimum rotor angular speed (rad/s)

λ opt :

Ideal tip speed ratio

V FC :

Output voltage of single fuel cell

E Nerst :

Standard reversible voltage

V Act :

Voltage drop due to anode and cathode activation

V Ohm :

Ohmic voltage drop

V Con :

Voltage drop due to concentration

V Cell :

Voltage of the fuel cell

n :

Number of cells in series in a fuel cell stack

∆G :

Standard Gibbs energy change (J/mol)

F :

Faraday constant

S :

Change in entropy (J/mol)

\(P_{{\text{H}}_2 }\) :

Partial pressure of hydrogen (atm)

\(P_{{\text{O}}_2 }\) :

Partial pressure of oxygen (atm)

R :

Universal gas constant (8.314 J/K mol)

T ref :

Reference temperature (K)

ξ i :

Parametric coefficients

I stack :

Cell operating current (A)

\(C_{{\text{O}}_2 }\) :

Oxygen concentration (mol/cm)

R c :

Resistance to protons passing through membrane

R m :

Resistance to the passage of electrons through membrane

ρ m :

Membrane specific resistivity for electron flow (cm)

C o :

Initial SOC point of the battery

C bat :

Battery capacity

I bat :

Battery current

η bat :

Battery efficiency of charging or discharging

σ :

Self-discharge rate of a battery

T bat :

Battery Temperature

\(C_{{\text{bat}}}^{\prime}\) :

Nominal battery capacity

P s :

PV array’s power

P w :

Wind turbine’s power

P load :

Load power

η rect :

Rectifier efficiency

η inv :

Inverter efficiency

V o :

Output voltage

V s :

Input source voltage

C p-opt :

Optimal-wind turbine power coefficient

inc:

Increment

I mppt ( k ) :

Current at MPPT at sample time k

Epv(k):

Error output of PV system at sample time k

CEpv(k):

Change in error of a PV system at sample time k

Ew(k):

Error output of wind system at sample time k

CEw(k):

Change in error of a wind system at sample time k

µ(D)i:

Duty cycle’s aggregated membership function

T m-opt :

Optimum mechanical torque

K opt :

Constant

P dc :

Inverter DC input power

η MPPT :

Efficiency of the MPPT

f r :

Filter resonant frequency

f c :

Carrier frequency

L fg :

Filter inductor on the grid side

L fi :

Filter inductor on the inverter side

C fg :

Filter capacitance

V n :

Rated line-to-neutral grid voltage

I c , max :

Maximum AC current ripple

M amp :

Amplitude modulation

M freq :

Frequency modulation

Ar:

Amplitude of the sinewave signal

Ac:

Amplitude of carrier wave

fr:

Frequency of the sinewave signal

abc:

Natural reference frame

dq :

Synchronous rotating reference

αβ :

Stationary reference frame

Vd* (or) Vtq1:

Reference voltage signal in d-coordinate

Vq* (or) Vtq1:

Reference voltage signal in q-coordinate

id*(or) idref:

Reference current signal in d-coordinate

iq*(or) iqref:

Reference current signal in q-coordinate

iq (or) iq1:

Measured current signal in q-coordinate

id (or) id1:

Measured current signal in d-coordinate

V d :

Measured voltage signal in d-coordinate

V q :

Measured voltage signal in q-coordinate

P* :

Active power reference

Q* :

Reactive power reference

V* :

Reference voltage

ω* :

Reference frequency

P gm :

Measured active power of the grid

Q gm :

Measured reactive power of the grid

P g * :

Grid active power reference

Q g * :

Grid reactive power reference

RES:

Renewable energy sources

PV:

Photovoltaic

FC:

Fuel cell

DER:

Distributed energy resources

BSS:

Battery storage systems

EPS:

Electrical power system

PCC:

Point of common coupling

Hz:

Hertz

f :

Frequency

V :

Voltage

p.u.:

Per unit

RMS:

Root mean square

THDs:

Total harmonic distortions

KW:

Kilo watt

VRT:

Voltage ride through

FRT:

Frequency ride through

UV:

Under voltage

OV:

Over voltage

OF:

Over frequency

UF:

Under frequency

DC:

Direct current

SCC:

Short circuit current

OCV:

Open circuit voltage

PWM:

Pulse width modulation

TRD:

Total rated current distortion

AC:

Alternating current

h :

Individual harmonic order

ESS:

Energy storage systems

MPPT:

Maximum power point tracker

MPP:

Maximum power point

P&O:

Perturbation and Observation

INC:

Incremental conductance

IGBTs:

Insulated gate bipolar transistors

VSI:

Voltage source inverter

CSI:

Current source inverter

VV:

Volt-Var

PQ:

Power-reactive power

Vf:

Voltage-frequency

IV:

Current-Voltage

PV:

Power- Voltage

PI:

Proportional-integral

PR:

Proportional resonant

PID:

Proportional-integral derivative

FLC:

Fuzzy logic controller

ANFIS:

Adaptive neuro-fuzzy inference system

NN (or) ANN:

Artificial neural networks

MF:

Membership functions

PLL:

Phase locked loop

VBD:

Voltage based droop

LQR:

Linear quadratic regulator

LQI:

Linear quadratic integrator

DB:

Deadbeat controller

VSC:

Voltage source converter

THD:

Total harmonic distortion

RC:

Repetitive controller

FL:

Fuzzy logic

PE:

Power error

CPE:

Change in power error

PSF:

Power signal feedback

OTC:

Optimal torque control

PMSG:

Permanent magnet synchronous generator

HSC:

Hill climbing search

TSR:

Tip speed ratio

SOC:

State of charge

PEM:

Proton exchange membrane

PEMFC:

Proton exchange membrane fuel cell

SPWM:

Sinusoidal Pulse width modulation

PMSG:

Permanent pole magnet synchronous generator

D:

Duty cycle

OTC:

Optimum torque control

PSF:

Power signal feedback

LF:

Low frequency

HF:

High frequency

MPC:

Model predictive controller

H∞:

H-infinity controller

FL:

Fuzzy logic

SMC:

Slider mode control

References

  1. R.J. Campbell, Increasing the efficiency of existing coal-fired power plants, in Coal-Fired Power Plants: Efficiency Improvement Options (2015), pp. 77–111

    Google Scholar 

  2. R.C. Dugan, T.E. Mcdermott, Distributed generation. IEEE Ind. Appl. Mag. 8(2), 19–25 (2002). https://doi.org/10.1109/2943.985677

    Article  Google Scholar 

  3. IEEE Standard Association, IEEE Std. 1547–2018. Standard for Interconnection and Interoperability of Distributed Energy Resources with Associated Electric Power Systems Interfaces, IEEE Std 1547–2018 (Revision of IEEE Std 1547–2003) (2018)

    Google Scholar 

  4. A.Q. Al-Shetwi et al., Grid-connected renewable energy sources: review of the recent integration requirements and control methods. J. Clean. Prod. 253, 119831 (2020). https://doi.org/10.1016/j.jclepro.2019.119831

    Article  Google Scholar 

  5. J. Rocabert et al., Control of energy storage system integrating electrochemical batteries and supercapacitors for grid-connected applications. IEEE Trans. Ind. Appl. 55(2), 1853–1862 (2019). https://doi.org/10.1109/TIA.2018.2873534

    Article  Google Scholar 

  6. B. Arbab-Zavar et al., Smart inverters for microgrid applications: a review. Energies 12(5) (2019). https://doi.org/10.3390/en12050840

  7. H. Patel, M. Gupta, A.K. Bohre, Mathematical modeling and performance analysis of MPPT based solar PV system. Int. Conf. Electr. Power Energy Syst. ICEPES 2016, 157–162 (2017). https://doi.org/10.1109/ICEPES.2016.7915923

    Article  Google Scholar 

  8. M. Hlaili, H. Mechergui, Comparison of different MPPT algorithms with a proposed one using a power estimator for grid connected PV systems. Int. J. Photoenergy(2016). https://doi.org/10.1155/2016/1728398

  9. B. Bhandari et al., Mathematical modeling of hybrid renewable energy system: a review on small hydro-solar-wind power generation. Int. J. Precis. Eng. Manuf.- Green Tech. 1(2), 157–173 (2014). https://doi.org/10.1007/s40684-014-0021-4

    Article  Google Scholar 

  10. O. Zebraoui, M. Bouzi, Comparative study of different MPPT methods for wind energy conversion system. IOP Conf. Ser.: Earth Environ. Sci. 161(1) (2018). https://doi.org/10.1088/1755-1315/161/1/012023

  11. R. Seyezhai, B.L. Mathur, Mathematical modeling of proton exchange membrane fuel cell. Int. J. Comput. Appl. 20(5), 1–6 (2011). https://doi.org/10.5120/2433-3272

    Article  Google Scholar 

  12. A.O. Althobaiti, Proportional resonant control of three-phase grid-connected inverter during abnormal grid conditions (2017)

    Google Scholar 

  13. K. Sarita, R. Devarapalli, P. Rai, Modeling and control of dynamic battery storage system used in hybrid grid. Energy Storage 2(3), 1–14 (2020). https://doi.org/10.1002/est2.146

    Article  Google Scholar 

  14. A. Haddou et al., Comparative study of new MPPT control approaches for a photovoltaic system. Int. J. Power Electron. Drive Syst. 11(1), 251–262 (2020). https://doi.org/10.11591/ijpeds.v11.i1.pp251-262

    Article  Google Scholar 

  15. T. Bogaraj, J. Kanakaraj, J. Chelladurai, Modeling and simulation of stand-alone hybrid power system with fuzzy MPPT for remote load application. Arch. Electr. Eng. 64(3), 487–504 (2015). https://doi.org/10.2478/aee-2015-0037

    Article  Google Scholar 

  16. S. Samal, P.K. Barik, S.K. Sahu, Extraction of maximum power from a solar PV system using fuzzy controller based MPPT technique, in International Conference on Technologies for Smart City Energy Security and Power: Smart Solutions for Smart Cities, ICSESP 2018—Proceedings (2018) pp. 1–6. https://doi.org/10.1109/ICSESP.2018.8376721

  17. K. Amara et al., Improved performance of a PV solar panel with adaptive neuro fuzzy inference system ANFIS based MPPT. in 7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018 (vol. 5, 2018), pp. 1098–1101. https://doi.org/10.1109/ICRERA.2018.8566818

  18. Z.M.S. Elbarbary, M.A. Alranini, Review of maximum power point tracking algorithms of PV system. Front. Eng. Built Environ. 1(1), 68–80 (2021). https://doi.org/10.1108/febe-03-2021-0019

    Article  Google Scholar 

  19. S.A. Mohamed Abdelwahab, A.M. Hamada, W.S.E. Abdellatif, Comparative analysis of the modified perturb and observe with different MPPT techniques for PV grid connected systems. Int. J. Renew. Energy Res. 10(1), 155–164 (2020)

    Google Scholar 

  20. A.M. Noman, K.E. Addoweesh, A.I. Alolah, Simulation and practical implementation of ANFIS-based MPPT method for PV applications using isolated Ćuk converter. Int. J. Photoenergy2017 (2017). https://doi.org/10.1155/2017/3106734

  21. H.B. Massawe, Grid connected photovoltaic systems with smartgrid functionality (2013) pp. 37–39

    Google Scholar 

  22. Utility-scale PV inverters—Yaskawa—Solectria Solar (no date). Available at: https://www.solectria.com/pv-inverters/utility-scale-inverters/ (Accessed: 3 November 2021)

  23. M.A. Abella, (11) (PDF) Choosing the right inverter for grid-connected PV systems. Renew. Energy World 134 (2004)

    Google Scholar 

  24. M.J. Mnati, D.V. Bozalakov, A. den Van Bossche, PID control of a three phase photovoltaic inverter tied to a grid based on a 120-degree bus clamp PWM. IFAC-PapersOnLine 51(4), 388–393 (2018). https://doi.org/10.1016/j.ifacol.2018.06.097

    Article  Google Scholar 

  25. An improved PID and repetitive control for single phase inverters of photovoltaic power system (December 2018)

    Google Scholar 

  26. A.F. Tazay, Smart inverter control and operation for distributed energy resources (2017)

    Google Scholar 

  27. H.R. Karshenas, H. Saghafi, Basic criteria in designing LCL filters for grid connected converters. IEEE Int. Symp. Ind. Electron. 3(1 c), 1996–2000 (2006). https://doi.org/10.1109/ISIE.2006.295879

  28. C. Gurrola-Corral et al., Optimal LCL-filter design method for grid-connected renewable energy sources. Int. J. Electr. Power Energy Syst. 120(8), 105998 (2020). https://doi.org/10.1016/j.ijepes.2020.105998

    Article  Google Scholar 

  29. M. Hojabri, M. Hojabri, Design, application and comparison of passive filters for three-phase grid-connected renewable energy systems. ARPN J. Eng. Appl. Sci. 10(22), 10691–10697 (2015)

    Google Scholar 

  30. G. Majic, M. Despalatovic, B. Terzic, LCL filter design method for grid-connected PWM-VSC. J. Electr. Eng. Technol. 12(5), 1945–1954 (2017). https://doi.org/10.5370/JEET.2017.12.5.1945

    Article  Google Scholar 

  31. S.-H. Kim, Pulse width modulation inverters, in Electric Motor Control (2017), pp. 265–340. https://doi.org/10.1016/B978-0-12-812138-2.00007-6

  32. Y. Li et al., Grid synchronization technology for distributed power generation system, in IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014—Conference Proceedings (2014), pp. 1–6. https://doi.org/10.1109/ITEC-AP.2014.6941268

  33. Y. Xue et al., On a future for smart inverters with integrated system functions, in 2018 9th IEEE International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2018 (2018), pp. 1–8.https://doi.org/10.1109/PEDG.2018.8447750

  34. B. Mirafzal, A. Adib, On grid-interactive smart inverters: features and advancements. IEEE Access 8, 160526–160536 (2020). https://doi.org/10.1109/ACCESS.2020.3020965

    Article  Google Scholar 

  35. K. Rahimi et al., Voltage regulation performance of smart inverters: power factor versus volt-VAR control, in 2017 North American Power Symposium, NAPS 2017 [Preprint] (2017). https://doi.org/10.1109/NAPS.2017.8107407

  36. A. Vinayagam et al., PV based microgrid with grid-support grid-forming inverter control-(simulation and analysis). Smart Grid Renew. Energy 08(01), 1–30 (2017). https://doi.org/10.4236/sgre.2017.81001

    Article  MathSciNet  Google Scholar 

  37. S. Reichert, G. Griepentrog, B. Stickan, Comparison between grid-feeding and grid-supporting inverters regarding power quality, in 2017 IEEE 8th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2017 (2017), pp. 1–4.https://doi.org/10.1109/PEDG.2017.7972536

  38. P. Unruh et al., Overview on grid-forming inverter control methods. Energies 13(10) (2020). https://doi.org/10.3390/en13102589

  39. A.M. Bouzid et al., A survey on control of electric power distributed generation systems for microgrid applications. Renew. Sustain. Energy Rev. 44, 751–766 (2015). https://doi.org/10.1016/j.rser.2015.01.016

    Article  Google Scholar 

  40. M.A. Hossain et al., Overview of AC microgrid controls with inverter-interfaced generations. Energies 10(9), 1–27 (2017). https://doi.org/10.3390/en10091300

    Article  Google Scholar 

  41. M.A. Hannan et al., Fuzzy logic inverter controller in photovoltaic applications: issues and recommendations. IEEE Access 7, 24934–24955 (2019). https://doi.org/10.1109/ACCESS.2019.2899610

    Article  Google Scholar 

  42. A. Alhejji, M.I. Mosaad, Performance enhancement of grid-connected PV systems using adaptive reference PI controller. Ain Shams Eng. J. 12, 541–554 (2020). https://doi.org/10.1016/j.asej.2020.08.006

    Article  Google Scholar 

  43. P. García et al., ANFIS-based control of a grid-connected hybrid system integrating renewable energies, hydrogen and batteries. IEEE Trans. Industr. Inf. 10(2), 1107–1117 (2014). https://doi.org/10.1109/TII.2013.2290069

    Article  Google Scholar 

  44. J.R. Jang, Neuro-fuzzy modeling. 83(3) (1995)

    Google Scholar 

  45. J.S. Jang, C.T. Sun, E. Mizutani, Neuro-fuzzy and soft computing (no date)

    Google Scholar 

  46. J.S.R. Jang, ANFIS: adaptive-network-based fuzzy inference system. IEEE Trans. Syst. Man Cybern. 23(3), 665–685 (1993). https://doi.org/10.1109/21.256541

    Article  Google Scholar 

  47. A. Taher, Adaptive neuro-fuzzy systems (2010)

    Google Scholar 

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Ali, M., Thotakura, N.L. (2022). Smart Inverters and Controls for Grid-Connected Renewable Energy Sources. In: Das, S.K., Islam, M.R., Xu, W. (eds) Advances in Control Techniques for Smart Grid Applications. Springer, Singapore. https://doi.org/10.1007/978-981-16-9856-9_8

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