grid connected phatovoltaic plant

5/20/2018 Grid Connected phatovoltaic Plant

1/156 IEEE INDUSTRIAL ELECTRONICS MAGAZINE SEPTEMBER 2013 1932-4529/13/$31.002013IEEE

Digital Ob ject Iden tifier 10.1109/MIE.2 013.2264540

Date of publication : 19 September 2013

Components and Operation

ENRIQUE ROMERO-CADAVAL,GIOVANNI SPAGNUOLO,LEOPOLDO G. FRANQUELO,CARLOS-ANDRS RAMOS-PAJA,

TEUVO SUNTIO, andWEIDONG-MICHAEL XIAO

The main design objective of photovoltaic (PV) systems has been,

for a long time, to extract the maximum power from the PV ar-ray and inject it into the ac grid. Therefore, the maximum power

point tracking (MPPT) of a uniformly irradiated PV array and the

maximization of the conversion efficiency have been the main de-

sign issues. However, when the PV plant is connected to the grid,

special attention has to be paid to the reliability of the system,

the power quality, and the implementation of protection and grid synchroni-

zation functions. Modern power plants are required to maximize their energy

production, requiring suitable control strategies to solve the problems related

to the partial shading phenomena and different orientation of the PV modules

toward the sun. Moreover, the new policy concerning the injection of reactive

power into the grid makes the development of suitable topologies and control

algorithms mandatory. A general view of actual solutions for applications of the

PV energy systems is presented. This article covers several important issues,

including the most reliable models used for simulation, which are useful in the

IMAGE LICENSED BY INGRAM PUBLISHING


2/15SEPTEMBER 2013 IEEE INDUSTRIAL ELECTRONICS MAGAZINE 7

design of control systems, and the

MPPT function, particularly in distrib-

uted applications. The main topolo-

gies used in the PV power processing

system and, finally, grid connection

aspects are discussed, with emphasis

on synchronization, protections, and

integration.

Governments and public organiza-tions are currently concerned about

producing energy using clean tech-

nologies. As a result, the guidelines

for future energy production are being

established according to the Kyoto

Protocol [1], which for European coun-

tries inspires the 20-20-20 target [2].

Energy production technologies based

on hydro, wind, PV, and geothermal

energies are considered clean and

renewable alternatives to unclean con-

ventional technologies dependent onfossil fuels and nuclear fission. Among

the clean technologies, PV has experi-

enced the most growth in the last few

years, close to 60% in Europe.

PV installations are no longer iso-

lated from the grid but connected to

it, aiming to become part of the elec-

tricity generation mix. In this context,

the cost (in US$) per watt of these

plants has decreased from US$1.5/W

in 2009 to US$0.6/W in 2013 (Figure 1,

[3]), and this decreasing tendency will

continue. These plants are economi-

cally viable even without government

subsidies, and the PV plant capacity

is increasing significantly (Figure 1).

Therefore, the power generation of

grid-connected PV plants is increas-

ing continuously all over the world,

reaching values of hundreds of mega-

watts (Figure 2, [4]), thus making these

plants a crucial part of the future elec-

tric energy system and smart grids.This article gives a general descrip-

tion for new researchers and indus-

trial electronics professionals of the

electronics devices needed to connect

these plants to the grid in an efficient

and safe way, describing their compo-

nents (mainly dc/dc converters and

dc/ac converters), structures, control

algorithms, and functions.

In the PV Cells and Associations

section, the more reliable PV mod-

els for simulating mismatched arrays

are recalled and compared in terms

of accuracy and computational bur-

den. These models aim to develop

simulation models that can be used for

testing and evaluating the performance

of the electronic converter control

algorithms. This section also introduces

the main problem related to associ-

ated PV cells that electronic converters

have to solve (the mismatching effect

mainly due to shadowing).

The Structure and Topologies ofGrid-Connected PV Systems section

presents the main topologies used in the

PV power processing system and dis-

cusses their advantages and drawbacks.

The MPPT system described in the

Maximum Power Point Tracking Sys-

tem section is a basic and main part of

the control algorithm. This section also

describes the distributed MPPT, which

tries to improve the energy generation

coping with the mismatching effect pre-

sented in the Structure and Topologies

of Grid-Connected PV Systems section.

Finally, in the Grid Connection sec-

tion, the article exposes issues related

When the PV plant is connected to the grid, special

attention has to be paid to the reliability of the

system, the power quality and the implementationof protection and grid synchronization functions.


3/158 IEEE INDUSTRIAL ELECTRONICS MAGAZINE SEPTEMBER 2013

to the operation of these plants from

the point of view of their smart integra-

tion into the grid, especially synchroni-zation, protection, and integration.

PV Cells and AssociationsThe main components of a PV plant are

the PV cells, which are associated and

complemented by auxiliary elements to

guarantee the power and energy the PV

plant will produce. The design of the

PV field could be done by commercial

solutions such as the software PVsyst

[5], which allows the prediction of so-

lar energy production under variousirradiance and temperature conditions,

taking into account different PV tech-

nologies or sun tracker systems.

A reliable and accurate math-

ematical model that can be used in

standard simulation packages (such

as MATLAB/SIMULINK, PSPICE, or

PSIM) is desired to design and test the

control algorithms of the electronicdevices.

The equivalent circuits of PV gen-

erators proposed in prior studies can

be categorized into two main types:

double diode models (DDMs) [6][8]

and single diode models (SDMs) [9]

[13], which are illustrated in Figure 3.

The I-V characteristic for SDMs can be

expressed by (1). For DDMs, an addi-

tional current term shall be added to

represent the second diode.

.I I I eR

V IR1

( )

ph s KTA

q V IR

sh

ss

= - - -++ ^c hm8 B

(1)

The electrical characteristics in stan-

dard test conditions (STC) cannot

usually be measured. Therefore, PV

modeling tends to use currentvoltage

data and curves given by cell or

module manufacturers [14]. In this

case, four conditions can be formu-

lated using (1) corresponding to

the known values for short-circuit

current Isc, open-circuit voltage Voc,

operating voltage and current at maxi-mum power point (Vm, Im), and the

implicit information that the peak of P-V

curve at the voltage (Vm). Although the

equations that correspond to the appli-

cation of the four conditions comprise

a complex nonlinear equations system,

they can be solved using various math-

ematical approaches or numerical solv-

ers [12], [15]. As pointed out in [14] and

[16], these four equations do not pro-

vide enough information to solve the

five unknown parameters in an SDM,includingIph, Is, A, Rs,andRsh, which are

the photon current, diode saturation

current, ideality factor, series resis-

tance, and shunt resistance, respec-

tively. One possible solution is to fix

one parameter value, e.g., the ideality

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Silicon Ingot/Wafer Cell Module Plant Capacity

FIGURE 1 All-in-module cost (US$/W) and plant capacity evolution [3].

The high-order model is very sensitive

to the selection of initial conditions.



factor [12] or the shunt resistance [16]

and solve the remaining parameters

accordingly. An ideal SDM (Rs = 0 and

Rsh= ), as shown in [14], can be more

accurate than the standard SDM param-eterization. Moreover, the high-order

model is very sensitive to the selec-

tion of initial conditions, and failing in

it may lead to the reduction of model

accuracy, which supports the use of the

SDM. The DDM generally requires more

preassumed parameters and iterative

tuning cycles than the SDM parameter-

ization, because if the initial condition

is not correctly selected, the accuracy

of the high-order model will be low,

resulting in the opposite effect than

is desired when using this model. Be-

cause of the modeling complexity and

high computational burden, the DDM

approach is not as popular as the SDM.

Simplified SDM is highly recommended

Top Ten by Power

Power Description and Location

250 MWAgua Caliente Solar Project,Yuma County, Arizona

214 MWCharanka Park, Patan DistrictPV Power Plant, Charanka, India

200 MWpGolmud PV Power Plant,Golmud, China

150 MWMesquite Solar I,

Sonora Desert, Arizona

145 MWpSolarpark Neuhardenberg,Neuhardenberg, Germany

128 MW Solarpark Templin, Germany

115 MWCentrale Solaire de Toul-Rosires, France.

106 MW Perovo I-V PV Power Plant, Ukraine

97 MW Sarnia PV Power Plant, Canada

91 MW Solarpark Briest, Germany

Commissioned

2012

2012

2011

2011

2012

2012

2012

2011

2009

2011

300 MW

250 MW

200 MW

150 MW

100 MW

50 MW

0 MW2007 2008 2009 2010 2011 2012

North America Asia Europe

FIGURE 2 Top large-scale PV power plants. The nominal power (in MW) of the PV plants isclassified by the continent where they are installed [4].

Iph Rsh

RsI

V

+

Iph Rsh

R

s

I

V

+

(a)

(b)

FIGURE 3 Equivalent circuits of (a) double-diode and (b) single-diode model.

0 5 10 15 20

0 5 10 15 20

0

2.5

5

7.5

10

Ipv

(A)

0

50

100

Ppv

(W)

Vpv(V)

D3Active D3Not Active

Multiple Maximum Power Points

Inflection Point

Ia

Pa

I2

P2

I1

P1

+

+

+ +

+

+

+

V1

I1 I2

V3

V2

VDS2VDS1

Va

V4

D2

D4

D1

D3

la

(b)(a)

FIGURE 4 Mismatching conditions and bypass diodes activat ion.



in [17] for complex grid-tied systems,

real-time applications, and long-term

simulations.

The measure of normalized root-

mean-square deviation (NRMSD) is

proposed in [17] to quantify the mod-

eling accuracy because different solar

cells can be compared under the same

standard even if their power capaci-ties are widely different. Usually, the

short-circuit current at STC is used as

a normalizing value, for example, to ex-

press the deviation between the mea-

sured data and the data obtained from

the mathematical model [17]. The sin-

gle cell model can be easily aggregated

to any size PV array using the number

of cells connected in series and paral-

lel [17]. However, the approach cannot

mimic partial shading or mismatching

conditions, which are unavoidable in

real-world applications.

Different PV array topologies have

been proposed [18][20], such as

series-parallel, total cross-tied, andbridge-linked, but the series-parallel

topology, depicted in Figure 4(a), is the

one most commonly used. It is based

on series-connected PV modules,

known as strings, which are connected

in parallel to form the array [21]. The

number of PV modules required in the

string is determined to meet the volt-

age requirements of a grid-connected

inverter, and the number of strings in

the array determines the PV power

level. Moreover, the series-parallel

configuration must have blocking di-

odes in series with each PV string to

avoid current flows from one string to

another [22].As an example, consider the case

illustrated in Figure 4, where an ar-

ray composed of two strings of two

modules each are shown, where each

string has its corresponding blocking

diode [Figure 4(a)]. Because of shad-

ing, construction tolerances, or even

different orientations, some of the

PV modules in an array could experi-

ence different operating conditions,

generating the mismatching phenom-

enon [21][23]. In such a condition,the string current is limited by the

lowest PV module current, degrading

the power output of the PV modules

with higher current. Bypass diodes are

placed in antiparallel with the mod-

ules, as described in Figure 4(a), to

protect them by providing a path for

the exceeding current to flow through

[23][25]. In mismatching conditions,

a bypass diode becomes active when

the string current is higher than the

current of the shaded PV module. For

example, Figure 4(a) represents a situ-

ation where the bottom PV module of

the first string receives half the irradi-

ance that the first module receives.

Figure 4(b) shows the correspond-

ing I-V and P-V curves (red traces I1

and P1) of such a string. Because the

string current is higher than the short-

circuit current of the second module

(2.5 A), the associated bypass diode

D3becomes active, providing an alter-native path through which the current

exceeding the shaded module current

can flow. Otherwise, if the string cur-

rent is lower than the short-circuit

module current (2.5 A), the bypass

diode D3is not active.

The shading affects the string cur-

rent and power curves via the bypass

diodes, leading to the appearance

of multiple maximum power points

within the string [21], [26][28].

Figure 4(b) shows the inflection pointexhibited by the first string current,

Centralized

Configuration

String

Configuration

Multistring

Configuration

Modular Configuration

PV Array PV String

dc

ac

ac

dc

acdc

acdc

dcdc

dcdc

dcdc

acdc

acdc

Three Phase Single PhaseSingle or

Three Phase

Single or Three PhaseSingle Phase

dc

ac

dc

ac

dc

ac

dcdc

dcdc

Inverter

Modules

dc Bus

dcModulesModule

Configuration

(Each PV Panel IsInterfaced By a Dedicated

dc/ac Converter)

PV Panel

FIGURE 5 PV system configurations.



which also affects the array electri-

cal characteristics. In contrast, the

second string, which operates at the

uniform irradiation conditions, has a

single maximum power point.

To predict solar energy production

under mismatching conditions, the

effect of the bypass diodes was stud-

ied in [19], [20], [23] and [25][27].A mathematical model is proposed in

[21], where each PV module is repre-

sented by an SDM and bypass diodes

by Shockley equations. Such a model

provides an accurate representation of

the PV array by means of (N+1) non-

linear equations with (N+1) unknowns

(N PV voltages and blocking diode

voltage) depending on the Lambert-

W function. A different approach was

proposed in [28], where the bypass di-

odes are modeled by ideal switches tocalculate the inflection-point current

and voltage. This approach allows the

reduction of the computation effort re-

quired to predict the array current and

power because an array voltage lower

than a given number of inflection volt-

ages, e.g.,Kinflection voltages, implies

that (N-K) bypass diodes are active,

where the associated PV modules

have almost zero voltage and negligi-

ble power production. Therefore, the

number of nonlinear equations and

unknown variables is reduced by K,

requiring shorter computation time.

Structure and Topologiesof Grid-Connected PV SystemsAs shown previously, PV panels can

be arranged in different configura-

tions that directly affect the structure

and topology of the electronic device.

Usually, this device includes a dc/

dc converter and, as the PV plant is

connected to the grid, it also needs a

dc/ac converter. The combination of

both types of elements, panels, and

converters determines the cost, op-eration, and efficiency of the whole PV

system. Figure 5 shows the schematic

representation of the most common

PV configurations following the clas-

sification established in [29]:

Centralized configuration is mainly

used in PV plants that have nominal

power higher than 10 kWp, where a

high number of PV panels are con-

nected in series-parallel configuration

(array). Each string has a blocking di-

ode to prevent the energy reversion

produced by the strings operating at

different irradiance conditions and by

the existence of energy storage sys-

tems that operate during the night.

String configuration is a simplified

version of the centralized configu-

ration, where each string is con-

nected to one dc/ac converter. If

the string voltage does not have the

appropriate value, a boost dc/dc

converter or a step-up transformer

(which is usually placed on the ac

side) is needed.

Multistring configuration is anevolution of the string configura-

tion that unites the advantages of

string and centralized configura-

tions. Each dc/dc converter imple-

ments the MPPT for the string. This

configuration has a flexible design

and improves overall PV plant

efficiency.

AC modules configuration is where

each PV module incorporates a dc/

ac converter that implements an

automatic control that performs

the MPPT control at module lev-

el. This topology operates like a

TABLE 1CLASSIFICATION OF TOPOLOGIES FOR GRID-CONNECTED PV SYSTEMS [31].

WITH DC/DC CONVERTER WITHOUT DC/DC CONVERTER

WITH ISOLATION WITHOUT ISOLATION WITH ISOLATION WITHOUT ISOLATION

CHARACTERISTIC DC/DC-DC/AC WITH HFT DC/DC-DC/AC WITH LFT DC/DC-DC/AC DC/AC WITH LFT DC/AC

Example andreferences

Figure 6(a)[35], [36]

Figure 6(b)[37], [38]

Figure 6(c)[39], [40]

Figure 6(d)[41][45]

Figure 6(e)[46][49]

Isolation Yes Yes Leakage currentthrough earth hasto be controlled

Yes Leakage cur rentthrough earth hasto be controlled

DC component inthe injected current

It has to becontrolled

It is zero It has to becontrolled

It is zero It has to becontrolled

Design Complex Medium Medium Simple Simple and compact

MPPT Implemented indc/dc converter

Implemented indc/dc converter

Implemented indc/dc converter

Implemented inac/dc converter

Implemented inac/dc converter

Power range Medium-high High Medium-high High Low

Efficiency Good Medium Good Good Very good

Transformer Non conventionaltransformer. Lowweight and vo lume.

Usual transformer.High weight andvolume.

No Usual transformer.High weight andvolume.

No

Energy production technologies based on hydro,

wind, photovoltaic and geothermal energies can be

considered to be clean and renewable alternatives. PV

has experienced the most growth in the last few years.



plug-and-play system, having a PV-

module-integrated converter. Thisconfiguration is more expensive

and difficult to maintain than other

configurations when the power of

the plant increases. Modular configuration [30] is

based on a modular design, with

conventional dc/dc and dc/ac con-

verters sharing a common dc bus.

Each dc/dc converter is connect-

ed to a string and implements the

MPPT algorithm. As many dc/ac

converters are connected to the

dc bus and grid as are necessary

to achieve the desired power lev-

el. The system reliability is high,and it is easy to maintain because

only the damaged converter has

to be replaced.

The typical structure can be de-

duced from the PV architecture pre-

sented earlier. In any of them, PV

systems connected to the grid have

to be provided with a dc/ac converter

adapting the PV panels dc magnitudes

to the grids ac ones. In addition to the

dc/ac converter, a dc/dc converter can

be used to adjust the dc voltage andto implement the MPPT algorithm (as

will be discussed in the Maximum

Power Point Tracking System sec-

tion). It is also important to determine

if the galvanic isolation is needed and

where to place the corresponding

transformer: either in the part of the

system that operates at high frequency

[having a high-frequency transformer

(HFT)], or in the part that operates at

low frequency [having a low-frequency

transformer (LFT) designed for 50 or

60 Hz]. Based on these criteria, the con-

version topologies can be classified

into the categories used in Table 1 [31],

which also summarizes their char-

acteristics and cites references that

address their design and analysis.

Nowadays, multilevel topologies

[Figure 6(d)] are of interest because

of their lower harmonic waveform

content and the use of semiconduc-

tors in less stressful conditions. Thenumber of commercial inverters that

use this topology is increasing ev-

ery day. The use of high-bandgap

devices, mainly SiC and GaN [32],

in inverters is also an area of active

research to improve inverter efficien-

cy, but the cost of these devices is

still high compared to conventional

semiconductors.

Finally, a filter is needed between

the dc/ac converter and the grid. L,

LC, or LCL are the most commonlyused filter topologies [33], [34].

(a)

(b)

(c)

(d)

(e)

FIGURE 6 Examples of topologies following the classification of Table 1 [31]. (a) DC/DC-DC/ACwith HFT. (b) DC/DC-DC/AC with LFT. (c) DC/DC-DC/AC. (d) DC /AC with LFT. (e) DC /AC.

Nowadays, multilevel topologies are of interest due

to their lower harmonic waveform content and to the

use of semiconductors in less stressing conditions.



Maximum Power Point

Tracking SystemThis efficiency maximization of the PV

power processing system is useless

if the MPPT control does not ensure

that the maximum power is extracted

from the PV array, both at a steady

state and under varying climatic con-

ditions. In fact, the total efficiency of

the power processing system is al-

most the product of the conversion

efficiencies, which must be maxi-

mized by taking into account the ex-

tremely variable operating conditions

throughout the day [50] as well as the

MPPT efficiency.

There are multiple MPPT tech-

niques [51] that could be comparedusing different criteria (Table 2). The

main techniques are dP/dV or dP/dI

feedback control, incremental conduc-

tance (IncCond), and hill climbing [or

perturbationobservation (P&O)].

MPPT Operation and Efficiency

Commercial products typically use

perturbative approaches for tracking

the MPP, determining, instant by in-

stant, the voltage value at which the

PV generator delivers its maximum

power. Perturb and observe and incre-

mental conductance methods require

an accurate parametric design [21]

and usually control the reference sig-nal of a feedback-controlled switching

converter, generally a dc/dc regula-

tor that matches the PV array voltage

with the dc bus one or works as a bat-

tery charger.

Figure 7 shows some examples of

MPPT operation by employing a dc/

dc converter: the outermost feed-

back cannot be taken either from the

output-side signals without compro-

mising the stability of the interfac-

ing [52], [53]. The MPPT operation

usually acts on the PV voltage be-

cause of its logarithmic dependence

TABLE 2MAJOR CHARACTERISTICS OF MPPT TECHNIQUES.

MPPT TECHNIQUE PV ARRAYDEPENDENT?

TRUEMPPT?

ANALOG ORDIGITAL

CONVERGENCESPEED

IMPLEMENTATIONCOMPLEXITY

SENSEDPARAMETERS

Hill-climbing/P&O No Yes Both Varies Low Voltage, current

IncCond No Yes Digital Varies Medium Voltage, current

Fractional Voc Yes No Both Medium Low Voltage

Fractional Isc Yes No Both Medium Medium CurrentFuzzy logic Yes Yes Digital Fast High Varies

Neural network Yes Yes Digital Fast High Varies

RCC No Yes Analog Fast Low Voltage, current

Current sweep Yes Yes Digital Slow High Voltage, current

DC link capacitor droop control No No Both Medium Low Voltage

Load Ior Vmaximization No No Analog Fast Low Voltage, current

dP/dVor dP/dIfeedback control No Yes Digital Fast Medium Voltage, current

ipv ipv ipv

vpv

vpvvpv

ipv

u(t) u(t) u(t)

x = d(t) x = d(t)

x = vref(t)ipv

vpv vpvvo

io

vo vo

vo

io io

io

MPPT MPPT

Duty-CycleMPPT Algorithm

MPPT Algorithmat the Converter Output

PWMModulator

PWMModulator

PWMModulator

VoltageController

Voltage BasedMPPT Algorithm

MPPT

dc/dc Load dc/dc dc/dcLoad

Load

(a) (b) (c)

FIGURE 7 Dif ferent ways of implementing the MPPT operation by means of a dc/dc converter: (a) by acting on the duty cycle value or (b) on areference signal. (c) The output power can be observed instead of the input power.



on the irradiance level. Instead,

an action based on the PV current

would allow having a more prompt

reaction to the irradiation variation.

A few examples of this approach have

been recently proposed in the litera-

ture [54], [55] because of the intrin-

sic instability of the current control

when irradiation drops occur.

The MPPT performances are main-ly affected by two types of disturbanc-

es: an endogenous one, that is, the

noise unpredictably moving the PV

operating point away from the MPP,

and an exogenous one, that is, the in-

homogeneous irradiance received by

the modules of the PV array. The ef-

fects of the former source must be

minimized by a proper control action,

e.g., [21], without using any passive

filtering that could affect the conver-

sion efficiency. The mismatched op-

eration of the PV array requires very

sophisticated MPPT techniques. In-

deed, perturbative methods are able

to perform a local, not global, maxi-

mization of the PV power, thus not

ensuring that the absolute MPP of the

multimodal PV characteristic result-

ing from the mismatched operation

[see Figure 4(b)] is tracked. Some

real-time global optimization methods

have been presented in the literature,

e.g., [27], but they are usually very

complicated, so the leading compa-

nies operating in the field prefer to of-

fer the possibility of doing a periodicsweep of the PV curve to discover

where the absolute maximum power

point really is [56]. Needless to say,

a frequent sweep analysis improves

power production in daylight hours

when shadows affect the PV array,

but it reduces the power the system

is able to produce when working in

homogeneous conditions. In the last

five years, many papers have been

dedicated to the so-called distributed

MPPT control and the dynamical re-

configuration of the PV arrays [57];

both solutions allow the increase of

power production in the presence of

mismatching effects, but both also

have drawbacks.

Distributed MPPT Schemes

The long PV strings are very sensitive

to the partial shading effects caused

by nearby obstacles, such as build-

ings, trees, chimneys, flag poles, and

even the passing of clouds, due to

the currentsource nature of the indi-

vidual PV cells [58], [59]. To reduce

the detrimental effect of shading onenergy production, the PV modules

are usually equipped with bypass or

shunt diodes (as shown previously),

but these alone will not give the de-

sired results of maximizing the energy

output of the PV generator. Other ac-

tions are needed, such as providing

each PV module or its submodules

with a dedicated MPP-tracking con-

verter [60][66], so that the detri-

mental effects of mismatching remain

limited to the penalized modules andthe MPPT algorithms almost oper-

ate on single-peak currentvoltage

characteristics. Such arrangements

are known as distributed or granu-

lar MPP-tracking schemes. In [63], it

is estimated that module-integrated

MPP tracking can improve the energy

captured in shaded conditions by 16%

compared to string-based MPP track-

ing. If the granularity is extended to

the cell level, the improvement could

be as high as 30%.

The module level distributed MPP

tracking can be implemented either

by connecting the output terminals

of the dc/dc converters in parallel, as

shown in Figure 8(a) [64], or in series,

M1

Mn

M1

Mn

vPV1

vPV1

vPVn

vPVn

iPVn

vPV1ref

Zdclink

vdclink

vPVnref

iPV1

MPPT1

MPPTn

dc

dc

dc

dc

vPV1

vPV1

vPVn

vPVn

iPVn

vPV1ref

vPVnref

iPV1

MPPT1

MPPTn

dc

dc

dc

dc

1(+)

1(

)

n(+)

n()

+

+

Zdclink

vdclink

1(+)

2(+)

1(

)

n(+)

n()

n1()

(a) (b)

FIGURE 8 A PV module-integrated distributed MPP-tracking arrangement, using (a) parallel-connected and (b) series-connected dc/dc converters.

A frequent sweep analysis improves

the power production in daylight hours when

a shadow affects the PV array, but reduces

the power the system is able to produce when

it works in homogeneous conditions.



as in Figure 8(b) [65]. In grid-connected

applications, the dc-link voltage is in

the order of the peak or twice the

peak of the grid voltage. Therefore,

the parallel-connected scheme requires

the use of dc/dc converters with trans-

former isolation and quadratic conver-

sion ratio as well as high-voltage-rated

components [64]. It is assumed thatthe cascade-connected scheme can

be implemented by using nonisolated

dc/dc converters with low-voltage-

rated components yielding superior

efficiency and reliability performance

over the parallel-connected scheme.

The output-terminal voltage of the

cascade-connected converter is highly

dependent on the power the converter

supplies and the dc-link voltage. As

a consequence, the buck-boost-type

converter has to be utilized for thecascaded system to work properly

[68]. In addition, the conditions for

low voltage may not be valid, requiring

the use of components with a greater

capacity to withstand higher voltage

[68]. The terminal voltages can be

balanced by connecting at the output

terminals of the converters an addition-

al converter known as string-current

diverter, as explained in detail in [69].The same technology is also the basis

for the submodule-integrated dis-

tributed MPP-tracking schemes. The

output-terminal voltages are also prone

to disturbances during the changes

in the irradiation condition [62], [65]

necessitating the use of feedback

control for eliminating them [62]. The

parallel-connected arrangement does

not suffer from such disturbances.

It is well proven that the distrib-

uted MPP-tracking arrangement cansubstantially increase the energy

capture of a PV generator when sub-

jected to severe shading conditions.

The parallel-connected arrangement

may eventually be the best choice

even if the series-connected arrange-

ment is commonly assumed to be

superior in terms of cost, efficiency,

and reliability over the parallel-

connected arrangement. The feasibilityof the submodule-integrated solutions

must be studied case by case.

Grid ConnectionThe operation of inverters that are

connected to the grid compared to

inverters that operate in isolated

installations needs the implementa-

tion of additional functions, such

as synchronization and protection

functions. The energy storage func-

tion usually needed in isolated PVinstallations is not so important in

grid-connected systems. However,

energy storage is becoming more

important nowadays for achieving a

smart integration into the grid, as a

consequence of increasing the nomi-

nal power of PV plants.

Electronic

Converter VInv1 OutputFilter

IInv

PCC ZS

VGrid VS

VInv,1

IInv VGrid,1+

Lf

3.96

3.96

53.

97

3.97

53.

98

3.98

53.

99

3.99

5 4

20

15

105

0

5

10

15

20

Reference Current

iInvCurrent Injected intothe GridinvCurrent Injected intothe Grid

Time (s)

(d)

600

400

200

0

200

400

600

3.96

3.96

53.

97

3.97

53.

98

3.98

53.

99

3.99

5 4

VGrid,1+

VInv,1V rid,1+

Vnv,

Time (s)

(c)

VGrid

(a) (b)

IInv

FIGURE 9 Example of waveforms synchronization for achieving a unity power factor operation: (a) scheme of connections for the inverter, (b)phasorial relationship between electrical magnitudes of the scheme, (c) inverter and grid voltage waveforms and fundamental positive componentof grid voltage, and (d) inverter reference and injected current waveforms.

Energy storage is becoming more important nowadays

for achieving a smart integration into the grid.



Synchronization

Most inverters operate as current

sources injecting a current that is si-

nusoidal and in phase with the grid

voltage, with a power factor equal

or very close to unity. It is required

that the inverter synchronizes with

the fundamental component of

the grid voltage, even in the caseswhen the grid voltage is distorted

or unbalanced or when the grid fre-

quency varies.

An example of synchronization in

steady state for a single-phase sys-

tem is shown in Figure 9, where it can

be seen that even when the grid volt-

age, vGrid, is distorted, the synchro-

nization system is able to extract its

fundamental and positive sequencecomponent, vGrid,1+, which is used for

determining the fundamental voltage

component the inverter has to gener-

ate, iInv,1, to ensure that the current

injected into the grid, i Inv, is in phase

with the fundamental grid voltage. In

this way, the active power flowing to

the grid can be controlled; this pow-

er, assuming that the power factor is

equal to unity, is given by the follow-ing expression:

TABLE 3COMPARISON OF MAIN SYNCHRONIZATION METHODS USED IN PV SYSTEMS.

SYNCHRONIZATIONMETHOD

DISTORTIONIMMUNITY

ADAPTATION TOFREQUENCY

UNBALANCEROBUSTNESS

DYNAMICRESPONSE

COMPUTATIONALCOST

COMPLEXITY

SINGLEPHASE

AM ZCD Low, it suffers from

harmonic instabilityMedium Slow, it reacts with

the next zero crossingLow Low

OLDM

DFT High High, with variablefrequency platforms

Slow High High

ANF Medium Medium Very slow High High

KF Medium-high Very high Very high

WLSE Medium-high Medium Medium

ANN Medium-high Medium-Fast Low High

CLDM

PLL Medium, it dependson the bandwidth

Medium, due tothe internalsecond harmonic

Medium, it dependson the bandwidth

Low-medium Low, it can belinearized to a servotransfer function

EPLL High High, it eliminatesthe internalsecond harmonic

Medium-slow Medium Low-medium

APLL Medium Medium-high Medium-fast Medium Medium

SRF-PLL High High, they can be

frequency adaptive

Medium Medium-high Medium-high

THREEPHASE

AM

PLO Medium Medium Medium Variable Medium Very high,synchronization inthe control loop

OLDM

LPF High Low, very sensible Low, Clarketransformationmaintains inversesequence data

Medium Medium-low Medium-low

SVF High, if well tuned Low, sensible Low, Clarketransformationmaintains inversesequence data

Medium-slow High Medium-high

KF High Medium Medium Medium High High

WLSE Medium, it is slow High Fast High, it presentsome problems Medium

CLDM

SRF-PLL Medium Medium, due tothe second harmonicof d-q components

Medium, due to thesecond harmonic ofd-q components

Fast Medium Low, easylinearization

SRF-PLL LPF Medium-high Medium-high Medium-high Medium Medium Medium-low

SRF-PLL MAF High, i t e liminatesthe second harmonic

Medium-high High, it eliminatesthe second harmonic

Slow Medium Medium

SRF-PLL DFT High, it el iminatesthe second harmonic

Medium-high High, it eliminatesthe second harmonic

Medium-slow High High

SRF-PLL SC High, i t ext ract s thepositive sequence

High High Medium Medium-high,except the onesbased on neuralnetworks

Medium-high

AM: analog method, OLDM: open-loop digital method, CLDM: closed-loop digital method.



.P V I,1Grid Grid Inv= + (2)

To obtain the fundamental positive

component of the grid voltage at the

point of common coupling (PCC) volt-

age is not a simple task. This voltage

could contain disturbances due to

harmonics or unbalances present in

the grid or due to the resonance atthe switching frequency between the

passive elements of the inverter and

the grid impedance [e.g., the voltage

shown in Figure 9(c)]. Furthermore, the

synchronization system has to guaran-

tee the required filtering with the de-

sired dynamic and steady responses.

The start-up time that the synchroni-

zation system requires for being op-

erative and for the inverter to start to

inject energy must also be taken into

account.Several techniques have been intro-

duced in the literature for implement-

ing the grid synchronization paying

attention to the issues described ear-

lier [70], [71], which can be classi-

fied according to [72] as follows: zero

crossing detector (ZCD), phase locked

oscillator (PLO), based on digital Fou-

rier transformer (DFT), adaptive notch

filter (ANF), based on Kalman filters

(KF), weighted least squares estima-

tion (WLSE), artificial neural network

(ANN), usual phase locked loop (PLL),

enhanced PLL (EPLL), adaptive PLL(APLL), synchronous reference frame

PLL (SRF-PLL), and combining SRF-PLL

with LPF (SRF-PLL LPF), moving aver-

age filter (SRF-PLL MAF), DFT (SRF-PLL

DFT), or using symmetric components

(SRF-PLL SC). A comparison of these

methods is presented in Table 3.

Protections

Most national and international grid

codes, which regulate the PV plants

connected to the grid, require havingmaximum and minimum voltage and

frequency protections. If the grid RMS

voltage and/or frequency are outside

the predefined operating range, the

PV plant must be disconnected from

the grid.

Another protection that is com-

monly implemented in grid-connected

inverters is anti-islanding protection,

which prevents the inverter from

continuing to work when the grid

is not energized (due to a fault or a

maintenance activity in the electrical

system). There are multiple methodsthat try to detect the absence of grid

voltage [24], [73], [74], and these can

be classified in two main groups: local,

implemented at inverter level, which

could be passive, active, or hybrid; or

remote, implemented at grid level or

based on communication systems.

The main characteristics of the

most relevant anti-islanding methods

are summarized in Table 4. These anti-

islanding methods are as follows: re-

active power variation (RPV), activefrequency shift (AFS), slip-mode fre-

quency shift (SMS), active frequency

drift with positive feedback (AFDPF,

Sandia frequency shift), active fre-

quency drift with pulsating chopping

factor (AFDPC), general electric fre-

quency scheme (GEFS), grid imped-

ance estimation by harmonic injection

(GIEHI), grid impedance estimation

using external switched capacitors

(GIEESC), and based on communica-

tion systems (BCS).

TABLE 4CHARACTERISTICS OF THE MOST RELEVANT ANTI-ISLANDING METHODS.

ANTI-ISLANDINGMETHOD

RELIABILITY NDZ1 POWER QUALITY PQ MULTIPLE INVERTERINTEGRATION

STANDARDIZATIONPOSSIBILITIES

RPV High, NDZ couldbe eliminated

High, without harmonicsbut reduces the PF2

Low Low, due to theparallel problems

AFD Medium, does noteliminates NDZ

Low, it introduces low-order harmonics

Low, it cannot manageconcurrent detections

Low

SMS Medium, does not

eliminates NDZ

Medium, it affects the PF Low, it cannot manage

concurrent detections

Low

AFDPF High, NDZ could beeliminated

Medium, PQ could be affectedby continuous shifts

Medium, it can work with parallelinverter, but affects the PQ

Medium

AFDPCF Medium high, withcontrolled stability

High, it introduces harmonicsbut controls the THD

High, but limited High, stability and THDcould be controlled

GEFS Very high. it eliminates NDZand controls stability

Very high, THD changes very few High, but limited High, it does notdegrades the THD

GIEHI High, NDZ could beeliminated

Medium, it depends on thefrequency of injected harmonics

Low Low

GIEESC High, NDZ could be eliminated Low, it introduces low-order harmonics Low Low

BCS Medium high, if communicationquality is good

High, it does not influence on the PQ High, it depends on thecommunication reliability

High, a large termdue to cost

1NDZ: nondetection zone.2PF: power factor.

The synchronization system has to guarantee

the required filtering with the desired dynamic

and steady responses.



Grid Integration

Several regulations (grid codes) have

been established to avoid problems

connecting a large number of PV in-

stallations into the grid. These prob-

lems are mainly due to unmanageable

behavior (the produced energy can-

not be controlled because it depends

on the weather conditions, mainly

irradiation and temperature), the in-

jection of current harmonics, and its

operation under abnormal grid states[75][79] (usually produced in after-

fault or reconnection grid scenarios).

Some of the existing regulations

related to harmonic injection could

equally be applied to PV installations

(for example, IEC 61000 [78] or IEEE

Standard 519-1992 [76]). These norms

mainly define limits for the total and

individual harmonic distortion ratios

the injected current can have, depend-

ing on the nominal power or current of

the inverter.

Another major issue when con-

necting PV installations to the grid is

related to the ability to control reac-

tive power in both transient (under

abnormal situations) and steady

conditions. The inverter has to con-

trol the phase of currents to inject

or demand a pre-established reactive

power, that is imposed by the electric

system operator (to guarantee the

manageable behavior of the plant),or that is determined by the inverter

itself, depending on the magnitudes

measured from the grid.

The association of energy storage

systems (ESS) with PV installations is

also a key factor to be solved in the

future. It has to be determined when

and how to charge and discharge the

energy, taking into account the prices

of produced and consumed energy,

as well as the ESS size optimization.

It is known as smart energy stor-age, and there are some commercial

solutions already available on the

market [80], [81].

ConclusionsPV power processing plants connected

to the grid are increasing both in the

number of installations and also in

the rated power of each plant, and

will cover a significant percentage of

the electric generation mix. In this

article, a comprehensive overview of

grid-connected PV power processingsystems is presented with the aim of

giving clues for future improvements

and research activities in the field.

There are different techniques

and architecture that can reduce the

effects of control problems related

to the nonuniform operation of the

modules the PV array is made of.

Some solutions to these problems are

related to the structure of the array

itself and involve the use of block

and bypass diodes, while others are

related to how to apply the MPPT al-

gorithm, covering distributed control

and its integration in a dedicated dc/

dc converter.

The different single- and multiple-

stage conversion topologies proposed

in recent research can be compared in

terms of their main issues related to

the grid connection, determining their

pros and cons. Most of these compari-

sons have been done in this article.Finally, it must be determined the

synchronization, power (active and

reactive) control, and protection func-

tions that the inverter has to imple-

ment to achieve a smart integration

into the grid, taking into account their

main characteristics.

In the near future, industrial elec-

tronics researchers will have to solve

the emerging problems associated

with smart grids, such as those re-

lated to control of multiple distributedgeneration plants integrated within

houses, and to develop smart energy

storage systems.

BiographiesEnrique Romero-Cadaval(ercadaval@

ieee.org) received the M.Sc. degree in

industrial electronic engineering from

the Escuela Tcnica Superior de Ing-

eniera (ICAI), Universidad Pontificiade Comillas, Madrid, Spain, in 1992,

and the Ph.D. degree from the Univer-

sidad de Extremadura, Badajoz, Spain,

in 2004. In 1995, he joined the Univer-

sity of Extremadura. He is a professor

of power electronics and a researcher

with the Power Electrical and Elec-

tronic Systems (PE&ES) R&D Group in

the School of Industrial Engineering,

Badajoz, Spain. His research interests

include power electronics applied to

power systems, power quality, activepower filters, electric vehicles, smart

grids, and control and integration into

the grid of distributed/renewable en-

ergy resources. He is a Senior Member

of the IEEE.

Giovanni Spagnuolo(gspagnuolo@

unisa.it) received the M.Sc. degree in

electronic engineering from the Uni-

versity of Salerno in 1993 and the Ph.D.

degree in electrical engineering from

the University of Napoli Federico II,

Naples, Italy, in 1997. Since January

2004 he has been an associate pro-

fessor of electrical engineering at

the University of Salerno. He is an

associate editor of IEEE Transact ions

on Industrial Electronicsand editor of

IEEE Journal of Photovoltaics for the

topic PV system control. Since 2002,

he has worked in the field of power

electronics for photovoltaics. He is a

Senior Member of the IEEE.

Leopoldo G. Franquelo ([email protected]) received the M.Sc. and

Ph.D. degrees in electrical engineering

from the Universidad de Sevilla, Se-

ville, Spain in 1977 and 1980, respec-

tively. He is currently a full professor

and head of the Power Electronics

Group of the University of Seville. He

has been vice president of the Indus-

trial Electronics Society (IES) Spanish

Chapter (20022003), member-at-large

of the IES AdCom (20022003), vice

president for conferences (20042007),IES president elect (20082009), IES

New policy concerning the injection

of reactive power into the grid makes the

development of suitable topologies and

control algorithms mandatory.



president (20092011), and past presi-

dent of the IES since 2012. He has been

a Distinguished Lecturer since 2006

and an associate editor forIEEE Trans-

actions on Industrial Electronics since

2007. He was a corecipient of the 2008

Best Paper Award of IEEE Industrial

Electronics Magazine, the 2012 Best Pa-

per Award of IEEETransactions on In-dustrial Electronics,and the recipient of

the 2012 IEEE IES Dr.-Ing. Eugene Mittel-

mann Achievement Award for excel-

lence in research on power converter

topologies, modeling, modulation and

control techniques for high-power ap-

plications and renewable energy sys-

tems. His research interests include

modulation techniques for multilevel

inverters and its application to power

electronic systems for renewable ener-

gy systems. He is a Fellow of the IEEE.Carlos-Andrs Ramos-Paja (cara-

[email protected]) received the en-

gineering degree in electronics from

the Universidad del Valle, Colombia, in

2003, the masters degree in automatic

control from the same university in

2005, and the Ph.D. degree in power

electronics from the Universitat Rovira

i Virgili, Spain, in 2009. In 2009, he be-

came an assistant professor at the Uni-

versidad Nacional de Colombia where

he has been, since 2011, an associate

professor at the same university. His

main research activities are in the de-

sign and control of renewable energy

systems, switching converters, distrib-

uted power systems, and power quality

solutions. In particular, his work has fo-

cused on photovoltaic and fuel cell pow-

er systems. He is a Member of the IEEE.

Teuvo Suntio([email protected])

received the M.Sc. and Ph.D. degrees

in electrical engineering from the Hel-sinki University of Technology, Espoo,

Finland, in 1981 and 1992, respective-

ly. From 1977 to 1998, he worked in

the power-electronics-related indus-

try. Since 1998, he has been a pro-

fessor in power electronics first at

the University of Oulu Electronics

Laboratory, and since August 2004,

at the Tampere University of Tech-

nology Department of Electrical En-

gineering. He holds ten international

patents and has authored more than190 international scientific journal

and conference papers, one book,

and two book chapters. His research

interests include dynamic modeling

and control design of power electron-

ics converters in renewable energy

applications. He is a Senior Member

of the IEEE.

Weidong-Michael Xiao (mwxiao@

masdar.ac.ae) received the M.Sc. andPh.D. degrees from the University of

British Columbia, Vancouver, Canada,

in 2003 and 2007, respectively. He is a

faculty member with the electric pow-

er engineering program at the Masdar

Institute of Science and Technology,

Abu Dhabi, United Arab Emirates.

In 2010, he was a visiting scholar at

the Massachusetts Institute of Tech-

nology (MIT), Cambridge. Prior to

his academic career, he worked with

MSR Innovations, Inc. in Canada asan R&D engineering manager focus-

ing on projects related to integration,

research, optimization, and design of

photovoltaic power systems. His re-

search interests include photovoltaic

power systems, dynamic systems and

control, power electronics, and indus-

try applications. He is a Member of

the IEEE.

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