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Energy Conversion and Management

journal homepage: www.elsevier.com/locate/enconman

Review

Overview of technical specifications for grid-connected photovoltaicsystems☆

Arash Anzalchi⁎, Arif SarwatDepartment of Electrical and Computer Engineering, Florida International University, Miami, FL 33174, USA

A R T I C L E I N F O

Keywords:Photovoltaic (PV)PV integration challengesGrid codesGrid-connected inverterStandardsControl strategies

A B S T R A C T

Numerous countries are trying to reach 100% renewable penetration. Variable renewable energy (VRE), forinstance wind and PV, will be the main provider of the future grid. Cost reduction of accelerates the large scaleVRE deployment around the world. The efforts to decrease the greenhouse gases are promising on the currentremarkable growth of grid-connected photovoltaic (PV) capacity. This paper provides an overview of the pre-sented techniques, standards and grid interface of the PV systems in distribution and transmission level. Thispaper compares the different review studies which has been published recently and provides an extensive surveyon technical specifications of grid connected PV systems. Moreover, the adopted topologies of the converters, athorough control strategies for grid connected inverters, as well as their applications in PV farms has beenstudied. This study will help researchers and industry users to establish their research based on connectionrequirements and compare between different existing technologies.

1. Introduction

It has been very clear from recent studies and documentations thefossil fuels would last only a few more decades. The cost of fossil fuelhas become a major challenge for all of human kind. Not only theeconomic value but the environmental impacts of fossil fuels haveclearly made us move toward alternatives [1–3]. The greatest alter-natives that can really make a difference for sustainability, such asreducing green-house gases and long term economics, are the renew-able energy sources (RES) like wind and solar power. Solar photovoltaic(PV) industry is the dominant type of RES technology integrated topower grid systems as its cost reduces over the next ten years, whiledeployment of PV systems continues to increase quickly. As penetrationof PV on the grid grows, finally reaching hundreds of gigawatt (GW)interconnected capacity, a diversity of methods require to be taken intoaccount and also implemented at various scale, for reliable and cost-effective connection into the power grid [4].

Since many PV interconnection applications involve high penetra-tion scenarios, the process needs to allow for a sufficiently rigoroustechnical evaluation to identify and address possible system impacts.Thus, except of reducing the PV cost installation, others issues such asstandardization, simple improvements in design, better power electro-nics, and simplified procedures for grid integration are already im-proving the economics of PV systems.

They are many review studies on grid connected PV systems in theliterature. The comparison of the most recent review papers in the lit-erature is present in this part. In [5] authors studied the current trend ofPV power plants development in the world, comparison of grid codesfor fault ride through (FRT), voltage, frequency, active power, and re-active power was analyzed. After that, voltage stability, frequencystability, active power regulation, and reactive power regulation wasstudied. At last, the compliance technologies were investigated. Authorsof [6] reviewed the technical requirements of PV systems with micro-inverters by analyzing the U.S. National Electrical Codes, standards andutility grid-interconnection application, Michigan state requirements,barriers and solutions for plug-and-play Photovoltaic systems, and ad-vantages of microinverters. Ref. [7] studied the ratio between load andPV power, possible complications associated with high penetration PVinto the grid, grid-connected inverters, and islanding detectionmethods. In [8] standards and specifications of grid-connected PV in-verter, grid-connected PV inverter topologies, Transformers and typesof interconnections, multilevel inverters, soft-switching inverters, andrelative cost analysis have been presented. [9] did a review on pro-spects and challenges of grid connected PV systems in Brazil. [10]mostly focused on the techno- economic analysis of the grid connectedPV system for building application. [11] reviewed the technical barriersof PV system development. The authors did a survey on categorizing thegrid-connected and stand-alone PV systems, energy policy, a number of

http://dx.doi.org/10.1016/j.enconman.2017.09.049Received 21 June 2017; Received in revised form 24 August 2017; Accepted 17 September 2017

☆ This work has been supported by National Science Foundation (NSF) Grant CAREER-1553494.⁎ Corresponding author.E-mail address: aanza005@fiu.edu (A. Anzalchi).

Energy Conversion and Management 152 (2017) 312–327

Available online 04 October 20170196-8904/ © 2017 Elsevier Ltd. All rights reserved.

MARK

technologies implemented in PV cells, maximum power point tracking(MPPT), energy management, energy optimization, issues related tostorage of energy in PV systems, hybrid PV systems, environmental andeconomic concerns, operation and maintenance issues. Ref. [12] pro-vided analysis, explanation, and introduction on typical distributedMPPT and centralized MPPT. In [13] guidelines and standards of thegrid connected PV generation systems, effects of large PV integrationinto the power grid, power quality requirements, protection methods,and control capabilities have been investigated. As it can be seen eachpaper mostly focus on only limited aspects of PV technical specification,and there is no comprehensive review on this topic.

In this paper a handy extensive investigation on grid connectedphotovoltaic system is conducted. The outline of the rest of the paper isas follows. Section 2 analyses the challenges of photovoltaic integrationinto the grid. Some integration solutions are also presented in thissection. In Section 3 the standard requirements and grid codes for PVintegration are studied. Section 4 analyses the power electronic invertertopologies for Photovoltaic interconnection to the grid. Most popularthree phase inverters are investigated in Section 5. Most implementedcontrol algorithms for PV systems are presented at Section 6. Futureapplications of PV are studied in Section 7. Finally, the paper is con-cluded in Section 8.

2. Challenges to integrate solar photovoltaic

In spite of all advantages of PV, it might make some potential ad-verse effect on the present power grid. Solar is known as non-dis-patchable resources. There is no control over the input these kinds ofenergy resources for later use when desirable [14]. The lack of controlover the input has a direct relationship with unpredictability of theoutput power injected to the grid [15]. The incapability of generatingon-demand power triggers stability and reliability concerns to thepower system [14,16,17]. Some of the challenges that come along withusing renewable energies are depicted in Fig. 1 [18].

The information collected from an extensive survey on literatureshows that the PV output power fluctuation due to solar irradianceintermittency is the most important problem of PV grid integration.Thus, large scale integration of photovoltaic system into the distribu-tion grid introduces corresponding problems such as voltage regulationproblem, harmonics, reactive power compensation, synchronization,energy storage, forecasting and scheduling, and load demand man-agement systems. A classification of technical challenges of large-scalePV in the distribution systems are presented in Table 1.

Distributed system protection coordination in a feeder with high PVintegration using widespread distributed feeder measurement and uti-lizing OpenDSS has been studied by [19]. Short circuit detectiontechnique for the PV inverter by valuating the magnitude and slope (d/dt) of the PV inverter current is introduced in [20]. In order to preventany contrary effects of the short circuit current, the proposed systemeither disconnects the inverter or transfers the inverter to a PV dynamicreactive power compensator (STATCOM).

Higher solar integration requires implementation of battery (andsuper-capacitor) energy storage systems to compensate high energy

(and high power) fluctuations caused by stochastic nature of renewableresources [21]. Different methods for calculating the battery energycapacity to accommodate a specific PV penetration level with minimumcost has been studied in the literature [22,23]. Increased use of re-newable energies, especially PV, has resulted in bigger implementationof battery system in LV grid [24,25]. Large scale integration of PVenergy sources has a number of complications that need to be overcomeas PV begins to compete and in time replace more traditional means ofenergy generation, i.e. coal, natural gas, and oil power plants.

There are various types of energy storage systems (ESS) that can beused in conjunction with PV each of which has their uses in the electricgrid. Examples of these ESS are: pumped hydro energy storage (PHES)[26–28], compressed air energy storage (CAES) [29–32,32], flywheelenergy storage (FES) [33–35], battery or electrochemical energy sto-rage (EES) [36–40], flow battery energy storage (FBES) [41], super-conducting magnetic energy storage (SMES) [42–49], and super-capacitors or dual layer capacitors (DLC) [50–55].

The success of alternative energy is dependent upon the engineeringequipment and infrastructure which it is based upon and its ability tocapture and convert this energy [15]. The availability of solar power isdependent upon the position of the sun, angle at which the sun-rays fallupon the surface of the earth, and cloud location [18]. The places atwhich these renewable resources are available are typically far fromtheir intended population areas. This would require extensive invest-ment in transmission infrastructure in order to insure the proper andsecure transfer of energy produced. For the promise of alternative en-ergy to be achieved, the following goals shown in Table 2 must be met[56].

Similarly, for the success of renewable energy, proper technologymust be available for implementation [18]. Most researched technolo-gies take anywhere between twenty to twenty-five years to demonstratethe feasibility and large-scale commercialization before they are im-plemented outside of the laboratory. The reason is that many of theprocesses for these technologies must be perfected and optimized fordifferent operating environments. Apart from the optimization, all ofthe technologies must also be patented, tested, safety evaluations mustbe conducted, land procurement must be acquired, the financial ana-lysis must be conducted, along with several other studies must takeplace before such technologies can be seen to commercial use.

2.1. Present usage of PV generation

Currently, it seems impossible that todays power grid could run onsimple renewable resources unless there is a major advancement inenergy conservation and improved energy efficiency.

One way to overcome this while using the available technology is touse other dispatchable renewable resources which can be kept runningin reserve modes. Examples of some dispatchable renewable resourcesare [15]: Hydroelectric, Biomass, Geothermal.

Some of the other solutions that have been looked at is the solutionof using compressed air storage, batteries, and the use of molten salts inappropriated solar thermal plants [57]. Some of the downsides fromthese approaches include losses in the process of energy storage,transfer and usage along with the limited density of energy that thesesystems are capable of storing with todays available technologies [58].

The inability to produce on-demand real and reactive power, in away that generators have spinning reserve can be compensated by usingenergy storage systems. Therefore, the power generated by renewableenergy resources like solar and the wind could be stored and then laterused in order to abide by the load balancing act and available energy[59]. In todays society, pumped hydro devices almost dominated large-scale energy storage system in the USA [60]. However, some batteryenergy storage System also known as (BESS) are installed [61].

Application of energy storage has been known for their ability toprovide many of the auxiliary functions such as load leveling, peakshaving, voltage regulation, VAR support, frequency control, spinning

Challenges

Grid Performance

Reliability

Power Quality

Communica on

Dispatchability

Power Electronics

Fig. 1. Challenges that arise when integrating renewable resources into the smart grid.

A. Anzalchi, A. Sarwat Energy Conversion and Management 152 (2017) 312–327

313

reserve and power quality mitigation that the power system so despe-rately need [14]. Renewable resources on the grid can be used in orderto fix problems with fluctuations of power by introducing storage of theproduced energy and secondly with the concept of distributed genera-tion [62].

3. Grid code requirements

PV capacity reached a global total of 100 GW as of 2012, estab-lishing itself as just one of the expeditiously growing renewable re-sources. With the massive injection of power from renewable resources,into the energy grid; there is a definite need to keep power require-ments uniform to ensure reliability and stability. The use of universaland detailed standards, that lay out specific guidelines for integratingrenewable resources into the energy grid. These standards and so-calledGrid codes have responsibilities such as: voltage and frequency stabi-lity, power regulation, response to atypical energy system conditions,and system restoration. Presented below are these topics from various

national requirements.

3.1. IEEE 1547 [63]

Standard IEEE 1547 establishes foundational criteria for all types ofinterconnected distributed energy resources (DER) connected to AreaElectric Power Systems (EPS). Generally this standard is applicable upto 10 MW of distributed generation, and sets mandatory requirements.The standards main objectives are: technical requirements for inter-connection and testing the interconnection, to EPS. The following sec-tions will outline certain aspects of IEEE 1547.

IEEE Std 1547-2014 presents obligatory prerequisites for the inter-connection of DER with the electric power networks. The focus of thisstandard is mostly on radial distributed feeder interconnections. ForDER interconnected on the distribution grid, all parts of IEEE Std 1547-2014 needs to be fulfilled.

Normally distribution voltage regulation occurs at substation level.However, According to IEEE 1547, photovoltaic and wind turbine

Table 1Technical challenges in regards to implementation of renewable energy to the smart grid.

Technical Challenge Description of challenge and how it effects the smart grid when renewable energy is integrated

Voltage Fluctuation/Intermittency Major issue due to the intermittency of these renewable resources. This is seen to occur because of the variance of available solar energy atany given point throughout the day. Fluctuating voltage can disturb sensitive equipment and possibly reduce the life of power electronicdevices

Harmonic Distortion Voltage distortion and fluctuation issues can be produced by injected harmonics onto the grid. Power electronic devices and operative non-linear appliances are the main sources of high percentage of total harmonic distortion (THD)

Reactive Power Compensation Because of variations in the active and reactive power, a fixed capacitor or switched capacitor or static compensator can be implemented asa power regulator

Synchronization In order to ensure power quality in the grid, synchronization of grid frequency, voltage, and phase is a crucial aspectEnergy Storage This is another aspect that is imperative with the purpose of ensuring the reliability of power delivery. Energy storage systems are being

used to bring the instability and uncertainty under control in the production of varying types of renewable energies. Some existing energystorage methods are listed in Section 2 of this paper

Forecasting and Scheduling Knowing future weather patterns will play a crucial role in the variability of renewable energy as it is introduced into the smart grid. Inorder to reduce the intermittency on the network, accurate forecasts must be produced to produce satisfactory power quality and toperform viable load management systems

Load Demand Management Systems Planning and management of the load demand is crucial for power quality improvement of the smart grid with renewable energyintegration. With proper planning and management adequate power quality can be supplied in a safe and efficient manner uniformlyacross the entire power grid at varying loads and demands

Table 2Required Fundamentals for Grid Integration of Renewable Energies.

Area of interest Target Goals

Standards Must abide and comply with ANSI, UL, NEC, and OSHA standards for operational usageImplementation planning and future forecasting • Must be able to perform for approximately 25–30 years

• Modern energy management systems to incorporate variability of renewable resources

• Computational intelligent forecasting tools

• Integrate storage elements

• Fleet management

• Closed loop control mechanism to reduce disturbances

Performance of the components Over a 25–30 year projected lifetime performance the device should be able to:

• Have less than 5% internal loss while in a fully charged

• Have an efficiency of over 90%

• Be able to perform over 50,000 cycles of charging and discharging with no less than 40% of PV capacity within 1 min

• Must be supplied at a reasonable time frame and generate power on demand regardless of the time of day

Financials/Cost of overall project • Must have feasible cost in regards to performance and return

• Should cost less than 14 cents/kW h after the system is fully installed

• Cost analysis studies should include cost for proposed solutions including the cost of the PV plant, inverters, storagedevices, hardwares, software, interconnection, and other devices which will ensure proper and optimal operations of thesystem

Communication to and from components on thesmart grid

• Must allow monitoring and communication to and from the components within each sub system

• Safe to maintain and preventative against external attack

• Must be able to be controlled and provide feedback to the supplying utility company

• Communication protocols must be compatible with current power electronic devices on the smart grid for having ahomogeneously operating smart grid

• Protocols used in communication cannot be replicated by other industries

• Must be able to respond to electrical market prices and have capability to respond to load forecasting in order todetermine the optimal methods to provide the best power quality within the smart grid

A. Anzalchi, A. Sarwat Energy Conversion and Management 152 (2017) 312–327

314

systems should not cause area electric power systems (EPS) to set thevoltage at the point of common coupling (PCC) actively. In addition, theDER should not force the service voltage of Area Electric Power systemsoutside of operating ranges specified by ANSI C84.1-1995 (Range A).ANSI C84.1-1995 voltage ranges are shown in Table 3.

Area EPS are designed to have radial one-way power flow, which isfrom the substation to the load. This brings a unique challenge becauseDER possibly will cause two-way power flow, which could affect theEPS voltage. For example, if generated power by a DER source is in-jected into the power system, the load current will be offset and reducethe voltage drop at the Area EPS; because of DER, Local EPS loads canbe offset and possibly affect the voltage. In addition, DER sources ab-sorb (Inductive) and supply (Capacitive) reactive power into thesystem. These situations accentuate the need for the IEEE 1547 re-quirement that DER should not actively regulate voltage.

3.1.1. VoltageThere are system response requirements for typical voltages. When

a voltage within the specified range given in Table 4 is detected, theDER should discontinue energizing the Area EPS, in the period of theindicated clearing time. The time between the start of the abnormalcondition and the discontinuing the DER energization of the Area EPS iscalled clearing time.

3.1.2. FrequencyWhen the power system frequency is detected within the ranges

listed in Table 5, the DER should discontinue energizing the Area EPSbefore clearing time limit. The Clearing time is the period of time be-tween the beginning of the condition and the DER discontinuing toenergize the Area EPS. If there is an Area EPS disturbance, the DER isnot allowed to connect back to the power system until Area EPS voltageis restored to the specifications listed in ANSI C84.1-1995 (Range B)and frequency within: 59.3 Hz to 60.5 Hz. Furthermore, the systemshould include a fixed or adjustable delay, up to a maximum time offive minutes, which ensures no reconnect until Area EPS steady-statefrequency and voltage are returned to the aforementioned ranges inTable 5.

3.1.3. Power qualityThe dc current is not allowed to be bigger than 0.5% of the nominal

output current at the PCC. Moreover, there are limitations for injectedharmonic currents into the Area EPS at the point of DER connection;given in Table 6. The concern about dc current injection and dc voltagebias into the grid by PV system is studied in [64]. In this paper a single-phase inverter for PV application with low-frequency transformer (LFT)

investigated. Total harmonic distortion (THD) is another measure ofpower quality in OV systems. Current THD has bigger values in cloudydays, even there is no resonant in the network.

3.1.4. IslandingOne of the most important concerns in utilizing PV in power system

is islanding. Islanding happens when a line is disconnected and is en-ergized by one (or multiple) DERs, whilst that section of the EPS iselectrically cut off from the remainder of the EPS. If this situation is notdiscovered quickly, it may introduce dangerous safety condition [65].During unintentional islanding, the DER shall have the means to re-cognize the accidental island and discontinue to energize the EPS in lessthan two seconds of the island’s creation.

Other General requirements are as follows. IEEE 1547-4.1.3: TheDER shall be in parallel with Area EPS and does not cause any voltagedeviations at PCC larger than ± 5% of the nominal voltage of the AreaEPS. Furthermore, unacceptable flicker shall not be produced by theDER for other customers on the Area EPS. IEEE 1547-4.1.5: the AreaEPS shall not be energized by the DER while the Area EPS is not en-ergized. IEEE 1547-4.1.7: An accessible, lockable, and clearly distin-guishable disconnection device shall be provided to disconnect AreaEPS from DER. IEEE 1547-4.1.8.2: The system of interconnectionshould be able to tolerate current and voltage swells in agreement to theconditions provided in IEEE standard C37.90.1-2012 or IEEE standardcard C62.41.2-2002 as applicable. IEEE 1547-4.1.8.3: The connectedparallel DER to the system should be able to tolerate 220% of the in-terconnection system nominal voltage. IEEE 1547-4.2.1: The DER unitshould stop energizing the Area EPS for faults on the Area EPS circuit towhich it is connected. IEEE 1547-4.2.2: The DER should halt en-ergizing the Area EPS, earlier than reclosure by the Area EPS. IEEE1547-4.2.2: The DER and its linked system should not inject dc currentbigger than 0.5% of the nominal current at the PCC.

3.2. German grid codes

This section will take a look at German Grid code. This researchpicks Germany since this country retained its world rank in 2012 as thethird largest investing country in renewable resources. 7.6 GW of solarcapacity was installed, making it the largest for any country.

The Grid Codes objectives are keeping safety and reliability ofnetwork operation in accordance with the requirements of EnergyEconomy Law (ENergiewirtschaftsgesetz EnWG). The grid code allowsfor on-site calculation of minimum and maximum power at which theplant is connected to the medium voltage network. The grid code

Table 3ANSI C84.1 Voltage Ranges for 120 V Base.[63]

Service Voltage Utilization Voltage

Minimum Maximum Minimum Maximum

Range A 114 (−5%) 126 (+5%) 110 (−8.3%) 125 (+4.2%)Range B 110 (−8.3%) 127 (+5.8%) 106 (−11.7%) 127 (+5.8%)

Table 4Interconnection system response to abnormal Voltages [63]

Voltage range (% of base voltage)a Clearing time (sec)b

V < 50 0.1650 V < 88 2.00

110 < V < 120 1.00V 120 0.16

a Base voltages are stated in ANSI C84.1-1995 as the nominal system voltages.b Maximum clearing times for DER ⩽30 kW default clearing times for DER > 30 kW.

Table 5Interconnection system response to abnormal Frequencies [63]

DER size Frequency, range (Hz) Clearing, time (sec)

⩽30 kW >60.5 0.16< 59.3 0.16> 60.5 0.16

< {59.8 57.0} (adjustable set point) Adjustable 0.16–300

>30 kW <57.0 0.16

Table 6Maximum Harmonic Current Distortion in Percent of Current (I) [63].

Individual harmonic order h (odd harmonics) Percent (%)

h < 11 4.011 < h < 17 2.017 h < 23 1.523 h < 35 0.635 h 0.3Total demand distortion (TDD) up to the h = 50 harmonic 5.0

A. Anzalchi, A. Sarwat Energy Conversion and Management 152 (2017) 312–327

315

specifies that DER shall be dynamically grid supported. More expresslyDER (PV system) must have the capability to remain connected during afault, support or provide system with reactive power for the time offault, and absorb similar or smaller reactive power after the cessation ofa fault.

With respect to PV systems (specified as type 2 plants) in Germangrid code; they must not disconnect from the network when a voltagedrop to 0% Uc and time duration of ⩽150 ms occurs. Fig. 2 indicatesranges for disconnection, and ranges where DER must stay grid con-nected. If there is a voltage drop above borderline 1, the DER mustremain stable and connected. Voltage drops above borderline 2, butbelow borderline 1, shall also be ridden through. Based upon networkoperation agreements certain options are available for this range:

In addition there shall be a set point given by the network operatorthat must be attainable from any operation point. The generation plantmust be able to reduce power in levels of 10% or smaller of the agreedupon rated output power.

As shown in the below Fig. 3, when system frequency rises above50.2 Hz, there must be a reduction in output power. The power re-duction shall be reduced with a gradient of 40%/Hz of instantaneouslyavailable power, and shall not be increased until frequency is below50.05 Hz. For frequencies greater than 51.5 Hz and less than 47.5 Hz,the generation plant shall be disconnected from the grid.

3.2.1. Static grid supportGenerating plants must have the capability to deliver reactive power

at all operational points in line with the following displacement factorin the grid’s connection point: =cos φ( ) 0.95underexcited to 0.95overexcited.

Reactive power will be delivered only for the duration of the feed-inoperation. Therefore, there is no necessity to deliver reactive power atnight time when no irradiance can be collected from the sun. Reactivepowers set point can be fixed or variable signal by the network op-erator. Criteria for the value of the set point are:

• Fixed displacement factor of cos φ( )• Or a variable displacement factor depending on active power cos φ( )• Variable reactive power depending on voltage Q(U)

To have a better overview of the grid codes in the world, Table 7provides a comparison of national standards and grid codes for selectcountries.

4. Inverter topologies in photovoltaic application

This part of the paper begins with an indication of some currentpower inverter topologies for combining PV modules to the electricpower grid.

Central inverter (20–100 kW): In centralized inverter topology, thePV modules are divided into series connections (called string), eachgenerating a sufficiently high voltage to avoid further amplification.These series connections are then connected in parallel, by using stringdiodes, to reach high power around 10 kW and 250 kW. Central in-verter configuration is shown in Fig. 4(a).

Disadvantages of centralized inverters are as follows.1-High voltagedc cables between the PV modules and the inverter. 2- More power lossdue to a centralized MPPT, mismatch losses between the PV modules,losses in the string diodes. 3- Non flexible design in large production PVplants.

String Inverters (1–8 kW): The string inverters are reduced versionof the centralized inverter, where a single string of PV modules isconnected to the inverter. The input voltage may be high enough toavoid voltage amplification. There are no losses associated with stringdiodes and separate MPPTs which results in the increase of the overallefficiency compared to the centralized inverter, and the reduction in theprice, due to mass production. String inverter configuration is shown inFig. 4(b).

Multi-String Inverters (8–20 kW): In multi string configuration,several strings are interfaced with their own dc-dc converter to acommon dc-ac inverter. The benefit of this configuration is that eachstring can be controlled individually. [69]. Multi-string inverter con-figuration is shown in Fig. 4(c).

AC Modules (150–600 W): The ac modules integrates each PV paneland the inverter into one electrical device [70]. It removes the mis-match loss between PV modules, since there is only one PV module.This configuration increase the possibility of large integration. ACmodules are best for installations where one or more panels may beshaded, or where panels are facing different directions. A system thatuses ac modules will produce slightly more power than a similar systemwith a string inverter, however, they are more expensive than stringinverters [4].AC module configuration is shown in Fig. 4(d).

By performing a comparison between these four configurations it isclear that the efficiency of these inverters have this relationship:

Centralized inverter < Multi-string Inverters ⩽ String Inverter < ACModules.

4.1. Topology classification of inverters

A classification of diverse inverter designs is presented in this sec-tion. The topologies are classified based on the number of power pro-cessing steps, position of capacitors for decoupling the power, if theyutilize transformers or not, and kinds of grid interface.

4.1.1. Stages of power processingFig. 5 displays three circumstances of multiple and single stage

Fig. 2. Fault Ride Through Germany [66].

Fig. 3. Dynamic response of German power grid [67].

A. Anzalchi, A. Sarwat Energy Conversion and Management 152 (2017) 312–327

316

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A. Anzalchi, A. Sarwat Energy Conversion and Management 152 (2017) 312–327

317

inverters.Fig. 5(a) represents a single-stage inverter. This inverter must take

over all the responsibilities by itself, for example, grid current control,MPPT, and voltage increase. This configuration is the typical arrange-ment designed for a central inverter. [70] suggests that the invertershould design in a way that could be able to tolerate a peak power ofdouble of the rated power.

A dual-stage inverter is illustrated in Fig. 5(b). The MPPT andpossibly the voltage increase is are the dc - dc converter responsibility.The dcdc converters output is either a pure dc voltage or modulatedcurrent to follow a rectified sine wave. When the converter is designedto control the rated power, the output is dc. When the dcac inverter isused for handling the grid current using bang-bang operation or pulsewidth modulation (PWM), the output is modulated current. In the latercase, the dcac inverter switching frequency is equal to the grid fre-quency, and the rectified current is transforming to a full sine-wave.Then the current control is managed by the dc dc converter. In this case,a high efficiency can be reached if the nominal power is low. Further-more, PWM mode should be implemented for the grid-connected in-verter if the rated power is high.

The multi-string inverter is illustrated in Fig. 5(c). The dcdc con-verters are solely used for voltage increase and MPPT. The dc-link,which is responsible for controlling the grid current, is the point thatdcac inverter and the dc-dc converter are connected. Using this methodgives a better control of each PV string and the shared dcac inverter

may be based on standard variable speed drive (VSD) technology.

4.1.2. Power decouplingis typically attained by using an electrolytic capacitor, which is the

key factor in limiting the lifetime and should be remained as small aspossible and can be substituted by film capacitors if possible. As shownin Fig. 6, the capacitor can be located either in the dc-link between thestages of inverter or in parallel with the PV modules.

4.1.3. Modes of interconnectionsAs illustrated in Fig. 7, some inverter applications use a line-fre-

quency transformer on the way to the power grid, others use a high-frequency dc-ac inverter or dcdc converter with an implementedtransformer, and finally, some topologies do not utilize transformers atall. Because of the large size of the e-frequency transformer, it is knownas an inadequate component.

Just a small number of high-input-voltage transformerless topolo-gies that can be grounded both at the input and at the output have beenintroduced in the literature [72]. One configuration is illustrated inFig. 8

5. Three phase grid connected inverters

In [73] a Multi-Functional Grid-Connected Inverter (MFGCI) hasexamined as shown in Fig. 9. three-level PWM achieved by employingan asymmetrical leg, similar to the single-phase H-bridge converter,that produces less voltage harmonic on the ac side compared with atwo-level design. In three phase utility, this MFGI can be employed to asthree autonomous voltage source inverters as shown in Fig. 9(a). It canalso be used as a combined inverter as shown in Fig. 9(b), in which thedc-bus is shared with three cells and is fed by renewable energy sourcesand/or energy storage devices.

A three-phase MFGCI configuration utilizing soft-switching

DCACPV

Grid

CPV

DCDCPV

CPV

DCAC

Grid

CDC

a)

b)

Fig. 4. Summary of PV inverters technologies. (a) centralized (b) string (c) multi-string(d) ac-module and ac cell technologies [71].

DCACPV

DCDCPV

DCAC

Grid

Grid

DCDCPV

DCDCPV

DCAC

Grid

b)

a)

c)

Fig. 5. (a) Single power processing stage (For voltage amplification, grid current control,and MPPT) (b) Dual power processing inverter (dcac inverter controls the grid current,the dcdc converter is in charge of the MPPT, the Voltage amplification can be included inboth stages. (c) Dual-stage inverter [71].

DCACPV

Grid

CPV

DCDCPV

CPV

DCAC

Grid

CDC

a)

b)

Fig. 6. Locations of power decoupling capacitor: (a) Parallel with the PV for single-stageinverter utilization. (b) Parallel with the PV modules and/or the dc-link for multi-stageinverter utilizations [70].

DCAC ~PV

Grid

ACAC

a)

LFT

DCACPV

b)HFT

~ Grid

ACDC

DCACPV

c)

HFTFig. 7. (a) For solving problems with dc currents injection to the grid, Line-frequencytransformer (LFT) may be located between the grid and the inverter. (b) For HF-link grid-connected ac/ac inverter applications, a high-frequency transformer (HFT) may be im-plemented (c) HFT is placed in a dc-link PV-module-connected dcdc converter [70].

A. Anzalchi, A. Sarwat Energy Conversion and Management 152 (2017) 312–327

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technology is shown in Fig. 10 [75,76]. This formation generally con-tains auxiliary active resonant commutated snubber link auxiliary(ARCSL), PV array, and LCL-filter. However, the filter can be newlyproposed filters like LLCL or L LCL( )2 [77–79]. An active power filter forintegrated grid-connected PV applications and related controllers areproposed in [80]. Eliminating the harmonics and providing power fromthe PV are two purposes of the controller.

A cascaded multilevel grid-connected inverter for high voltage im-plementation and high power PV system is presented in [82–84]. lowdevice rating, lesser electromagnetic interference, and improved powerquality, modularity, etc. are the advantages of this topology for in-verters. Considering a cascaded PV system, the output voltage fromeach individual converter module synthesizes the total ac output vol-tage in one phase leg that must satisfy grid codes or necessities. Un-balanced ac output voltage can be the result of active power in-compatibility of these units. The reason is that the same grid currentruns in the ac-side of each converter unit.

The reactive power, harmonic and unbalance current can also becompensated by the MFGCI. In order to ease the procedure of referencecurrent generation, multi-functional grid-connected inverters (MFGCIs)mostly use direct current control. Tables 8 and Table 9 display athorough assessment of different kinds of grid connected inverter’stopologies in three-phase and single-phase applications, respectively.

6. Control of grid connected PV systems

In order to connect the PV system to the grid, controlling the powerconditioning devices are the most important task that should be im-plemented. The controlling systems have two major parts.

6.1. Renewable side controllers

These controllers are mostly implemented for maximum powerpoint tracking systems to extract the most from distributed sources.Moreover, these controllers may be used to protect the converters.

6.1.1. MPPT controlMPPT plays a key role in the performance of a PV system [128,129].

Many MPPT methods have been implemented and developed based ondifferent approaches, like computational models used in machinelearning [130], fuzzy and vary in complexity, popularity, requiredmeasurements, convergence speed, implementation hardware, cost andrange of effectiveness.

A comprehensive review was conducted in [131] for many differentMPPT methods introduced in the literature.

In Table 10 the main features of all the MPPT methods are pre-sented.

6.2. Grid-side controllers

that are being used to perform active power control, reactive powercontrol, DC-link voltage control, power quality control, and grid syn-chronization. These are the basic features for grid-connected inverters.However, some utilities may request the additional service like com-pensation of harmonics, voltage regulation, local frequency, etc.

6.2.1. Active and reactive power controlActive power generation at low demand situations can cause

PV

DC

ACCDM

CDM

CCMCnoiseGsysGequ

LDM

LCM

CDM

CDM

CCM

L1

NG

Fig. 8. High-input-voltage transformerless PV inverter (with common-mode (CM) anddifferential mode (DM) EMI filters) [72].

Nonlinear Load

VSI VSI VSI

~~~

(a)

AC\DC Bidirec onal Rec er

VSI VSI VSI

DVR or Series APF

(b)

Fig. 9. Topology and its of the MFGCI cell (a) application inthree-phase utility (b) application in three-phase utility [74].

A. Anzalchi, A. Sarwat Energy Conversion and Management 152 (2017) 312–327

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overloading of the transformer or serious levels of grid voltage increase.On the other hand, the most important preventive cause to avoid the PVintegration into the grid distribution networks is voltage rise [132].Nominal or maximum power is provided by PV inverters during alimited time and the remaining power capacity of the inverter can beutilized for the voltage control purposes. Active power curtailment andreactive power control are two economical and technically feasiblesolutions [133].

The amount of reactive power that can be provided by a PV systemis limited. The voltage might not maintain in the satisfactory limitswhen active power production is high. This may happen because ofinadequate inverters capacity for a reactive portion. Furthermore, thereactive power effectiveness in low voltage (LV) networks is limited dueto bigger R/X values. In order to prevent the high voltage limit viola-tion, it is essential to curtail the active power. Different techniques forpower curtailment are suggested by [132,134,135]. These techniquesare costly for the PV panel owner because of cutting generated power.Therefore, optimal usage of present reactive power can lead to decreasethe number of power curtailments.

Local control: Among many different proposed methods for re-active power control, three techniques are mostly implemented: 1-localpower generation measurements [132,136,137], 2- local voltage

measurements method [132,136,138], and 3- combination of both. Thereference voltage is defined by local measurement method for con-troller design of reactive voltage, as presented in [139]. If local para-meters are not synced with the grid, the local control techniques maycause an extreme consumption of reactive power or maybe insufficientvoltage support.

Centralized control: The local control parameters were optimizedby using a centralized optimization in [140]. Even though the PVoutput is in direct relationship with the cloud covering situations, op-timum points of operations are achieved by tuning the local controllers.

Cascaded multilevel converters controlA cascaded multi-level PV system for large-scale PV implementation

is proposed in [141]. This system employed cascaded multilevel in-verters and a current-fed dual-active-bridge (CF-DAB) dc - dc convertersand as shown in Fig. 11. Separate control system for active and reactivepower is designed for improving the system performance when it isoperating. Each PV converter controls the reactive power in real-time todecrease the chance of the over-modulation, which may result in theasymmetrical active power output from the PV arrays. The systemlifetime can be enhanced by placing film capacitors instead of electro-lytic capacitors. A large low-frequency dc voltage ripple is allowed bythe proposed PV system. This will not affect the MPPT attained by

Bidirectional Converter with ARCS

Bat

tery

Arr

ay

LCL Filter

Three Phase L

oad

Fig. 10. Utility connected bidirectional soft-switchingMFGCI [81].

Table 8Comparisons of multi-functional three-phase grid-inverter topologies

Utility Author Topology Current mode Modulation/control Capacity Switching frequency(kHz)

Extra functions Application

Three- phase Mohod and Aware [85] H-bridge Direct Hysteresis 50 kVA – APF BatteryMarei et al. [86] H-bridge Direct SPWM/FLC,PI – – APF Micro-sourceCheng et al. [87] H-bridge Direct SPWM/droop control 1 kVA 20 UCa Micro-source

Lv et al. [88] H-bridge Direct SPWM/PI 400 kVA 12.8 APF Micro-sourceHan et al. [89] H-bridge Direct SPWM/PI 30 kVA 10 APF,ISWC WTLi et al. [90] Four-bridge Direct SPWM/PI – 10 ISWCb Micro-sourceWang et al. [91] Four-bridge Direct SPWM/PI,PR – 16 UPQC Micro-sourceYu etal. [92] Four-bridge Direct SPWM/PI – – ISWC,APF Micro-sourceDasgupta et al. [93] H-bridge Direct SPWM/Lyapunov 75 VA – APF Micro-sourceCheng etal. [94] H-bridge Direct – 5 kVA – PFC, UPS PVNaderi etal. [95] H-bridge Direct Hysteresis – – APF,RPI Micro-sourceSawant etal. [96] Four-bridge Direct 3D-SVPWM – 10 APF,UC PMSGWang etal. [97] Four-bridge Direct SPWM/PI 1 kVA 10 APF PVMajumder etal. [98] Full-bridge Direct Hysteresis/LQR – – APF,UC Micro-sourceGajanayake et al. [99] ZVI Direct SVPWM/PI 1 kVA – APF Micro-sourceTsengenes and Adamidis[100]

Three-level NPC Direct SVPWM/PI – – APF PV

Saitou etal. [101] H-bridge Direct SPWM/PI – 15 RPI BatteryChandhaket etal. [76] H-bridge Direct SPWM/PI 20 kVA – PWM BatteryAbolhassani etal. [102] H-bridge Direct SPWM/PI 7.5 kVA – APF DFIGWuetal. [103] H-bridge Direct SPWM/PI 1.1 kVA 20 APF PVHe etal. [104] Full-bridge Direct SPWM/repetitive 5 kVA – APF Micro-sourceYu etal. [105] H-bridge Direct SPWM/PI 10 kVA – APF,RPI Micro-sourceKim etal. [106] H-bridge Direct Hysteresis – 20 APF PV

a Dynamic voltage regulator.b Unified power quality conditioner.

A. Anzalchi, A. Sarwat Energy Conversion and Management 152 (2017) 312–327

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means of CF-DAB dcdc converters.

6.3. Control strategies [142]

Joining the photovoltaic system may cause some major problemslike the instability of the grid and disturbances. By implementingcontrol systems these effects can be mitigated properly. Generally,controllers have six different categories based on their applications,which is summarized in Fig. 12.

(1) Linear controllers have three sub categories

• Classic controllers including: proportional, proportional-integral

(PI), proportional-derivative (PD), and proportional-integral-de-rivative (PID) controllers.

• Proportional - Resonant (PR) controller [143]: the differencebetween classic PI controller and PR controller is how integrationpart perform. The PR controller only integrates frequencies closeto the resonant frequency. Consequently, phase shift or stationaryerror is not included.

• Linear-quadratic Gaussian (LQG) controller is a mixture of thelinear-quadratic regulator (LQR) and a Kalman filter. LQG controlis applicable in both linear time-invariant systems and lineartime-varying systems[144].

(2) Nonlinear controllers: has more complicated design and

Table 9Comparisons of multi-functional single-phase grid-inverter topologies

Utility Author Topology Current mode Modulation/control Capacity Switching frequency (kHz) Extra functions Application

Single-phaseBojoi etal. [107] Full-bridge Direct SPWM/repetitive 4 kVA 10 APF,PFC Micro-sourceCirrincione etal. [108] Full-bridge Direct SPWM/PR – 15 APF PVMacken etal. [109] Full-bridge Direct SPWM/PI 1 kVA – APF PVHosseini etal. [110] Two-boost Indirect SPWM/PI 3 kVA 20 DVRa,PFC PVDasgupta etal. [111] Full-bridge Indirect SPWM/repetitive – 10 DVR,HVC PVLin and Yang [112] Three-leg Direct SPWM/PI 1.5 kVA 20 UPQCb PVPatidar etal. [113] Full-bridge Direct Hysteresis/PI 1.2 kVA 25 APF PVHirachi etal. [114] Full-bridge Direct SPWM/PI 3 kVA – APF PVDasgupta etal. [115] Full-bridge Direct SPWM/Lyapunov – 10 APF Micro-sourceSeo et al. [116] Full-bridge Direct SPWM/PI 3 kVA 20 APF PVWu andShen [117] Full-bridge Direct SPWM/PI 1 kVA 25 APF PVWu etal. [118] Half-bridge Direct SPWM/PI 1.5 kVA 20 APF PVWu et al. [119] Full-bridge Direct SPWM/PI 1 kVA 19.45 APF,PFCc PVSladi etal. [120] Full-bridge Direct Hysteresis – 15 APF PVChiang etal. [121] Full-bridge Direct SPWM/PI 1 kVA – APF,UPSd PVKuo. [122] Three-leg Direct SPWM/PI 1 kVA 18 APF PVSouza et al. [123] HB ZVS Direct SPWM/PI 1 kVA 100/10 APF PVCalleja etal. [124] Full-bridge Direct Hysteresis 1 kVA 14.2 APF,RPIe PVMastromauroetal. [125] Full-bridge Direct SPWM/repetitive 1.2 kVA 2200 DVR,HVCf PVKuo et al. [126] Full-bridge Direct SPWM/PI 1.5 kVA 20 APFg PVWu et al. [127] Full-bridge Direct SPWM/PI 1.5 kVA 20 APF PV

a Power factor correction.b Uninterrupted power source.c Real power injection.d Harmonic voltage compensation.e Active power filter.f Unbalance compensation.g Voltage interruption/sag/swell compensation.

Table 10Examples of different MPPT METHODS.

MPPT Technique PV Array Dependent True MPPT Analog or Digital Periodic Tuning Convergence Speed Complexity Sensed Parameters

Hill-climbing/P &O No Yes Both No Varies Low Voltage, CurrentlncCond No Yes Digital No Varies Medium Voltage, CurrentFractional Voc Yes No Both Yes Medium Low VoltageFractional Isc Yes No Both Yes Medium Medium CurrentFuzzy Logic Control Yes Yes Digital Yes Fast High VariesNeural Network Yes Yes Digital Yes Fast High VariesRCC No Yes Analog No Fast Low Voltage, CurrentCurrent Sweep Yes Yes Digital Yes Slow High Voltage, CurrentDC Link Capacitor Droop Control No No Both No Medium Low VoltageLoad I or V Maximization No No Analog No Fast Low Voltage, CurrentdP/dV or dP/dI Feedback Control No Yes Digital No Fast Medium Voltage, CurrentArray Reconfiguration Yes No Digital Yes Slow High Voltage, CurrentLinear Current Control Yes No Digital Yes Fast Medium IrradianceImpp and Vmpp Computation Yes Yes Digital Yes N/A Medium Irradiance, TemperatureState-based MPPT Yes Yes Both Yes Fast High Voltage, CurrentOCC MPPT Yes No Both Yes Fast Medium CurrentBFV Yes No Both Yes N/A Low NoneLRCM Yes No Digital No N/A High Voltage, CurrentSlide Control No Yes Digital No Fast Medium Voltage, CurrentVoltage Oriented Control Yes Yes Digital No Medium High Voltage, CurrentExtremum Seeking Control Yes Yes Digital Yes Fast Medium Voltage, Current

A. Anzalchi, A. Sarwat Energy Conversion and Management 152 (2017) 312–327

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implementation compared with linear controllers(3) Robust controllers: are designed by considering uncertainties to

reach stability (when there are modeling errors) and robust per-formance, even in multivariable systems.

• Sliding mode controllers (SMC) has been used for output voltageregulation. This kind of controller does not have a sensitivity toparameter variations and load disturbances. The limited samplingrate, chattering phenomenon, and degrading the total systemefficiency are the drawbacks of this control method [144].

• Partial feedback linearization (PFL) controllers transform a non-linear system to a linear system (partially or fully), therefore,design methods for a linear system can be implemented in thistype of controller.

• Hysteresis controllers: in this controller a fixed switching fre-quency must be achieved by an adaptive band of the controller.

(4) Adaptive controllers [144]: automatically regulate the controllerbased on the operational conditions of the system. Due to in-accurate parameters of the high-performance system, the com-plexity of the computation of the system is high.

(5) Robust controllers: are designed by considering uncertainties toreach stability (when there are modeling errors) and robust

performance, even in multivariable systems.

• H-infinity controllers: are used in multivariable systems.However, these controllers are highly complex in terms of com-putational analysis and they need a precise model of the systemthat is going to be controlled.

• Mu-synthesis controllers: can be implemented in order to takeinto account the influence of unstructured and structured un-certainties on the execution of the system.

(6) Predictive controllers: forecast the upcoming performance of thecontrolled parameters. Predefined optimization criterion is used toreach the ideal performance. The execution of this type of controlleris easy, however, it has a rapid dynamic response and multivariablecases can be implemented.

• Deadbeat controllers: In this type of controller, the dynamic be-havior of the system is defined by the differential equations.Then, the control signals are estimated for the state variables toachieve the references at for each sampling period.

• Model predictive control (MPC): uses a cost function criteriawhich needs to be minimized in order to choose the ideal actions.The structure of this controller is illustrated in Fig. 13. Systemconstraints and nonlinearities can be easily included in the design

Fig. 11. Grid connected PV system with cascaded multilevelconverter.

Controllers

Linear controllers Nonlinear controllers

Classic controllers

PR Controllers

LQG controllers

Sliding mode controllers

PFL controllers

Hysteresis controllers

Robust controllers

H-infinity controllers

Mu-synthesis controllers

Adaptive controllers

Predictive controllers

Deadbeat controllers

MPC controllers

Intelligent controllers

Repetitive controllers (RC)

NN controllers

Fuzzy logic controllers

Autonomous controllers

Fig. 12. Summary of control strategies for Photovoltaic applications.

A. Anzalchi, A. Sarwat Energy Conversion and Management 152 (2017) 312–327

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of the controller [144,145].(7) Intelligent controller: is a class of controller that implements a kind

of computing artificial intelligence methods which mostly wereemulated the biological intelligence. A number of these methodsare as follows.

• Repetitive controllers (RC): use the internal model basics totrack/reject any reference/disturbance which is injected in theclosed-loop. The general structure of this controller is shown inFig. 14 [146].

• Neural network (NN) Controller: is a predictive and estimatorcontroller that use a couple of artificial neurons that mimic brainsystem. This type of controller can be trained online or offline toprovide the suitable inputs of the plant with the intention ofobtaining desired outputs.

• Fuzzy logic controllers (FLC): is a decision making mathematical

logic which has inputs with continuous values among 0 and 1.This is in contrast to digital logic with discrete values of true orfalse (1 or 0). FLC has the following components: 1- rule basewhich is a group of rules that defines how to control the system.2- Fuzzification which is the procedure of translating the alge-braic inputs to a kind that can be implemented by the inferencemechanism. 3- Information of the fuzzification are used by theinference mechanism. This mechanism chooses which rules areemployed on the current status. 4- the decisions that are attainedby the inference mechanism are transformed to a numerical inputfor the plant by defuzzification.

• Autonomous controllers: are able to accomplish complex tasksindividually. High levels of computerization can be achieved bythe addition of human knowledge and intelligence.

Fig. 13. The general layout of a Model Predictive Control[144].

Fig. 14. The general layout of a Repetitive Controller [147].

Fig. 15. Typical configuration of synchronous rotating (dq)reference frame control method [148].

Fig. 16. Typical configuration of synchronous rotating (dq)reference frame control method [148].

A. Anzalchi, A. Sarwat Energy Conversion and Management 152 (2017) 312–327

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6.3.1. Reference framesIn order to control inverters that are connected to the three-phase

grid, designers are mostly using dq reference frame or αβ referenceframe.

• dq reference frame: Zero-direct-quadrature or simply dq0 transformuses Park transformation to convert the abc frame to the dq frame.By using this method the grid voltage and current waveforms will beconverted to a rotational reference frame that has the same fre-quency of the grid. In this way, variables of the control system willbe transformed into DC variables, which makes the controller designand filtering much easier. The general configuration of dq referenceframe controller is shown in Fig. 15.

• αβ reference frame: Alpha-beta transform uses Clarke transforma-tion to transform the abc frame or the single-phase frame toαβ-frame. A stationary reference frame is made by this transforma-tion by using grid current. By using this method, the variables of thecontrol system will be changed to sinusoidal variables. The generalconfiguration of the Alpha-beta reference frame is illustrated inFig. 16.

7. Future applications of PV renewable energy

Distributed generation will lead to diverse sources which willaverage out the variation in the production of energy across the grid.Due to the lack of or the over development of renewable energythroughout the day, this source of power can be used in order to powerbattery electric vehicles. These battery electrical vehicles will requirereaching longer distances and thus requiring more charging locationsalong the road.

Increasing the power conversion efficiency is one of the cutting edgeresearches worldwide. This goal can by reducing the amount of mate-rial that is needed for each cell. Another approach can be implementingwider spectrum to produce electricity out of the sun. Silicon PV panelshave efficiency rates of around 20%. Researchers succeeded in produ-cing power in both visible and near infrared regions of the solar arrayspectrum [149]. The utilization of the infrared segment of the spectrumof the sun can improve the efficiencies of solar by 30% or more. Har-vesting the solar energy need space to install ground mounted PV pa-nels in a large scale. A French company Ciel & Terre International, de-veloped floating solar in large scale on big bodies of water. Besideproducing energy and saving land space, this method can reserve waterby reducing the vaporization of water. Energy harvesting trees areanother technology that will be used to save more space on the ground.Researchers are thinking of generating solar power in the space, wherethe sunshine is always available and the definition of the weather iscompletely different. Japanese Space Agency (JAXA) and Mitsubishiwere able to transmit 10 kW power from a distance of 500 meters bylarge antennas. The only effective way to send wireless power over longdistances is using either laser or Microwave. In cloudy weather condi-tions, Microwave works properly but lasers have the same problem thatsolar power does on earth [150]. One way to harvest more energy fromthe sun is solar clothing. The produced energy can be used to cool downand warm up the person who wears it, charge the smart phones, smartwatches, and other personal devices. The transparent panel is one ideathat can be implemented in both clothes and buildings. Transparentpanels are thin film technology, which can be installed on high-rises,transparent bus shelters, etc.

8. Conclusion

In this paper a comprehensive review on challenges and develop-ments in grid connected photovoltaic systems is provided. Many in-ternational and North American organizations such as 1547.8 groupand IEEE 1547.7 are defining modeling recommendations and meth-odologies for renewable energy interconnection. Photovoltaic inverter

manufacturers, utilities, and other involved area experts are focused ondesigning improved smart control strategies for PV inverters. However,there are still numerous gaps in the dynamic analysis of grid-connectedPV performance. The increase of large scale PV-penetration circum-stances needs a more thorough investigation of these gaps and sys-tematic interconnection studies. Several technical challenges and re-quired fundamentals for implementation of renewable energies in thegrid was provided in this study. Secure, safe, and economic properoperation of the power network at voltage and frequency violations fordifferent countries are specified by the grid codes. Inverters can beconsidered as the brain of a PV system. The inverter topologies areclassified based on the number of power processing steps, the positionof capacitors for decoupling the power, if they utilize transformers ornot, and kinds of grid interface. Moreover, many control methods havebeen suggested by researchers to control the MPPT, current, voltage,active and reactive power. An overview of these controllers was dis-cussed in this paper. Finally, higher solar integration requires im-plementation of battery (and super-capacitor) energy storage systems tocompensate high energy (and high power) fluctuations caused by sto-chastic nature of renewable resources. A brief description of energystorage systems as a whole, problems that are presented with the largescale integration of PV renewable energy, and the uses of energy sto-rage systems to provide a means to resolve those problems were simi-larly discussed in this paper.

References

[1] Anzalchi A, Sarwat A. Analysis of carbon tax as an incentive toward buildingsustainable grid with renewable energy utilization. In: 2015 seventh annual IEEEgreen technologies conference; April 2015. p. 103–9.

[2] Rahman M, Oo A. Distributed multi-agent based coordinated power managementand control strategy for microgrids with distributed energy resources. EnergyConvers Manage 2017;139:20–32 Available: <http://www.sciencedirect.com/science/article/pii/S0196890417301255> .

[3] Ifaei P, Karbassi A, Jacome G, Yoo C. A systematic approach of bottom-up as-sessment methodology for an optimal design of hybrid solar/wind energy re-sources case study at middle east region. Energy Convers Manage2017;145:138–57 Available: <http://www.sciencedirect.com/science/article/pii/S019689041730417X> .

[4] Ye B, Zhang K, Jiang J, Miao L, Li J. Towards a 90% renewable energy future: acase study of an island in the South China Sea. Energy Convers Manage2017;142:28–41 Available: <http://www.sciencedirect.com/science/article/pii/S0196890417302522> .

[5] Cabrera-Tobar A, Bullich-Massagu E, Arags–Pealba M, Gomis-Bellmunt O. Reviewof advanced grid requirements for the integration of large scale photovoltaic powerplants in the transmission system. Renew Sustain Energy Rev 2016;62:971–87Available: <http://www.sciencedirect.com/science/article/pii/S136403211630154X> .

[6] Mundada AS, Nilsiam Y, Pearce JM. A review of technical requirements for plug-and-play solar photovoltaic microinverter systems in the united states. Sol Energy2016;135:455–70 Available: <http://www.sciencedirect.com/science/article/pii/S0038092X16301815> .

[7] Eltawil MA, Zhao Z. Grid-connected photovoltaic power systems: technical andpotential problems—a review. Renew Sustain Energy Rev 2010;14(1):112–29Available: <http://www.sciencedirect.com/science/article/pii/S1364032109001749> .

[8] Jana J, Saha H, Bhattacharya KD. A review of inverter topologies for single-phasegrid-connected photovoltaic systems. Renew Sustain Energy Rev 2017;72:1256–70Available: <http://www.sciencedirect.com/science/article/pii/S1364032116306943> .

[9] de Faria H, Trigoso FB, Cavalcanti JA. Review of distributed generation withphotovoltaic grid connected systems in brazil: challenges and prospects. RenewSustain Energy Rev 2017;75:469–75 Available: <http://www.sciencedirect.com/science/article/pii/S1364032116307407> .

[10] Sommerfeldt N, Madani H. Revisiting the techno-economic analysis process forbuilding-mounted, grid-connected solar photovoltaic systems: part one review.Renew Sustain Energy Rev 2017;74:1379–93 Available: <http://www.sciencedirect.com/science/article/pii/S1364032116310048> .

[11] Lupangu C, Bansal R. A review of technical issues on the development of solarphotovoltaic systems. Renew Sustain Energy Rev 2017;73:950–65 Available:<http://www.sciencedirect.com/science/article/pii/S1364032117302022> .

[12] Xiao W, Moursi MSE, Khan O, Infield D. Review of grid-tied converter topologiesused in photovoltaic systems. IET Renew Power Gener 2016;10(10):1543–51.

[13] Wu YK, Lin JH, Lin HJ. Standards and guidelines for grid-connected photovoltaicgeneration systems: a review and comparison. IEEE Trans Indus Appl2017;53(4):3205–16.

[14] Smith SC, Sen PK, Kroposki B, Malmedal K. Renewable energy and energy storage

A. Anzalchi, A. Sarwat Energy Conversion and Management 152 (2017) 312–327

324

systems in rural electrical power systems: issues, challenges and applicationguidelines. In: 2010 IEEE rural electric power conference (REPC); May 2010. p.B4–B4-7.

[15] Jayasinghe SDG, Vilathgamuwa DM, Madawala UK. Dual inverter based batteryenergy storage system for grid connected photovoltaic systems. In: IECON 2010 –36th annual conference on IEEE industrial electronics society; Nov 2010. p.3275–80.

[16] Fthenakis V. Sustainability of photovoltaics: the case for thin-film solar cells.Renew Sustain Energy Rev 2009;13(9):2746–50 Available: <http://www.sciencedirect.com/science/article/pii/S1364032109000896> .

[17] Agalgaonkar YP, Hammerstrom DJ. Evaluation of smart grid technologies em-ployed for system reliability improvement: pacific northwest smart grid demon-stration experience. IEEE Power Energy Technol Syst J 2017;PP(99):1.

[18] Lakshminarayana S, Quek TQS, Poor HV. Combining cooperation and storage forthe integration of renewable energy in smart grids. In: 2014 IEEE conference oncomputer communications workshops (INFOCOM WKSHPS); April 2014. p. 622–7.

[19] Tang Y, Ayyanar R. Methodology of automated protection analysis for large dis-tribution feeders with high penetration of photovoltaic systems. IEEE PowerEnergy Technol Syst J 2017;4(1):1–9.

[20] Varma RK, Rahman SA, Atodaria V, Mohan S, Vanderheide T. Technique for fastdetection of short circuit current in PV distributed generator. IEEE Power EnergyTechnol Syst J 2016;3(4):155–65.

[21] Anzalchi A, Pour MM, Sarwat A. A combinatorial approach for addressing inter-mittency and providing inertial response in a grid-connected photovoltaic system.In: 2016 IEEE power and energy society general meeting (PESGM); 2016. p. 1–5.

[22] Al-falahi MD, Jayasinghe S, Enshaei H. A review on recent size optimizationmethodologies for standalone solar and wind hybrid renewable energy system.Energy Convers Manage 2017;143:252–74 Available: <http://www.sciencedirect.com/science/article/pii/S0196890417303230> .

[23] Derrouazin A, Aillerie M, Mekkakia-Maaza N, Charles J-P. Multi input-outputfuzzy logic smart controller for a residential hybrid solar-wind-storage energysystem. Energy Convers Manage 2017;148:238–50 Available: <http://www.sciencedirect.com/science/article/pii/S0196890417304958> .

[24] Wu Z, Zhang XP, Brandt J, Zhou SY, LI JN. Three control approaches for optimizedenergy flow with home energy management system. IEEE Power Energy TechnolSyst J 2015;2(1):21–31.

[25] Castillo A, Gayme DF. Grid-scale energy storage applications in renewable energyintegration: a survey. Energy Convers Manage 2014;87:885–94 Available:<http://www.sciencedirect.com/science/article/pii/S0196890414007018> .

[26] Iwafune Y, Ikegami T, da Silva Fonseca JG, Oozeki T, Ogimoto K. Cooperativehome energy management using batteries for a photovoltaic system consideringthe diversity of households. Energy Convers Manage 2015;96:322–9 Available:<http://www.sciencedirect.com/science/article/pii/S0196890415002046> .

[27] Vandewalle J, Bruninx K, Dhaeseleer W. Effects of large-scale power to gas con-version on the power, gas and carbon sectors and their interactions. EnergyConvers Manage 2015;94:28–39 Available: <http://www.sciencedirect.com/science/article/pii/S0196890415000424> .

[28] Dufo-Lpez R, Bernal-Agustn JL. Techno-economic analysis of grid-connected bat-tery storage. Energy Convers Manage 2015;91:394–404 Available: <http://www.sciencedirect.com/science/article/pii/S0196890414010772> .

[29] Amirante R, Cassone E, Distaso E, Tamburrano P. Overview on recent develop-ments in energy storage: mechanical, electrochemical and hydrogen technologies.Energy Convers Manage 2017;132:372–87 Available: <http://www.sciencedirect.com/science/article/pii/S019689041631055X> .

[30] Oliveira L, Messagie M, Mertens J, Laget H, Coosemans T, Mierlo JV, et al.Environmental performance of electricity storage systems for grid applications, alife cycle approach. Energy Convers Manage 2015;101:326–35 Available:<http://www.sciencedirect.com/science/article/pii/S0196890415005282> .

[31] Ji W, Zhou Y, Sun Y, Zhang W, An B, Wang J. Thermodynamic analysis of a novelhybrid wind-solar-compressed air energy storage system. Energy Convers Manage2017;142:176–87 Available: <http://www.sciencedirect.com/science/article/pii/S019689041730153X> .

[32] Ghalelou AN, Fakhri AP, Nojavan S, Majidi M, Hatami H. A stochastic self-sche-duling program for compressed air energy storage (CAES) of renewable energysources (RESs) based on a demand response mechanism. Energy Convers Manage2016;120:388–96 Available: <http://www.sciencedirect.com/science/article/pii/S0196890416303399> .

[33] Amodeo S, Chiacchiarini H, Solsona J, Busada C. High-performance sensorlessnonlinear power control of a flywheel energy storage system. Energy ConversManage 2009;50(7):1722–9 Available: <http://www.sciencedirect.com/science/article/pii/S0196890409000983> .

[34] Tripathy S. Simulation of flywheel energy storage system for city buses. EnergyConvers Manage 1992;33(4):243–50 Available: <http://www.sciencedirect.com/science/article/pii/019689049290114C> .

[35] Itani K, Bernardinis AD, Khatir Z, Jammal A. Comparative analysis of two hybridenergy storage systems used in a two front wheel driven electric vehicle duringextreme start-up and regenerative braking operations. Energy Convers Manage2017;144:69–87 Available: <http://www.sciencedirect.com/science/article/pii/S0196890417303461> .

[36] Koohi-Kamali S, Rahim NA. Coordinated control of smart microgrid during andafter islanding operation to prevent under frequency load shedding using energystorage system. Energy Convers Manage 2016;127:623–46 Available: <http://www.sciencedirect.com/science/article/pii/S0196890416308512> .

[37] Singh S, Singh M, Kaushik SC. Feasibility study of an islanded microgrid in ruralarea consisting of PV, wind, biomass and battery energy storage system. EnergyConvers Manage 2016;128:178–90 Available: <http://www.sciencedirect.com/

science/article/pii/S0196890416308366> .[38] Chua KH, Lim YS, Morris S. Cost-benefit assessment of energy storage for utility

and customers: a case study in Malaysia. Energy Convers Manage2015;106:1071–81 Available: <http://www.sciencedirect.com/science/article/pii/S0196890415009632> .

[39] Colmenar-Santos A, Linares-Mena A-R, Velzquez JF, Borge-Diez D. Energy-efficientthree-phase bidirectional converter for grid-connected storage applications.Energy Convers Manage 2016;127:599–611 Available: <http://www.sciencedirect.com/science/article/pii/S0196890416308378> .

[40] Wu K, Zhou H, An S, Huang T. Optimal coordinate operation control for wind-photovoltaic-battery storage power-generation units. Energy Convers Manage2015;90:466–75 Available <http://www.sciencedirect.com/science/article/pii/S0196890414009959> .

[41] Kusakana K. Feasibility analysis of river off-grid hydrokinetic systems withpumped hydro storage in rural applications. Energy Convers Manage2015;96:352–62 Available: <http://www.sciencedirect.com/science/article/pii/S0196890415002125> .

[42] Devotta J, Rabbani M. Application of superconducting magnetic energy storageunit in multi-machine power systems. Energy Convers Manage2000;41(5):493–504 Available: <http://www.sciencedirect.com/science/article/pii/S0196890499001004> .

[43] Kondoh J, Ishii I, Yamaguchi H, Murata A, Otani K, Sakuta K, et al. Electricalenergy storage systems for energy networks. Energy Convers Manage2000;41(17):1863–74 Available: <http://www.sciencedirect.com/science/article/pii/S0196890400000285> .

[44] Shayeghi H, Shayanfar H, Jalili A. Load frequency control strategies: a state-of-the-art survey for the researcher. Energy Convers Manage 2009;50(2):344–53Available: <http://www.sciencedirect.com/science/article/pii/S0196890408003567> .

[45] Pothiya S, Ngamroo I. Optimal fuzzy logic-based PID controller for load–frequencycontrol including superconducting magnetic energy storage units. Energy ConversManage 2008;49(10):2833–8 Available: <http://www.sciencedirect.com/science/article/pii/S0196890408000952> .

[46] Molina MG, Mercado PE, Watanabe EH. Static synchronous compensator withsuperconducting magnetic energy storage for high power utility applications.Energy Convers Manage 2007;48(8):2316–31 Available: <http://www.sciencedirect.com/science/article/pii/S0196890407000714> .

[47] Ansari MT, Velusami S. Dual mode linguistic hedge fuzzy logic controller for anisolated wind–diesel hybrid power system with superconducting magnetic energystorage unit. Energy Convers Manage 2010;51(1):169–81 Available: <http://www.sciencedirect.com/science/article/pii/S0196890409003501> .

[48] Ngamroo I. An optimization technique of robust load frequency stabilizer for su-perconducting magnetic energy storage. Energy Convers Manage2005;46(18):3060–90 Available <http://www.sciencedirect.com/science/article/pii/S0196890405000531> .

[49] Tripathy S. Dynamic simulation of hybrid wind-diesel power generation systemwith superconducting magnetic energy storage. Energy Convers Manage1997;38(9):919–30 Available: <http://www.sciencedirect.com/science/article/pii/S0196890496000933> .

[50] Wen H, Su B. Operating modes and practical power flow analysis of bidirectionalisolated power interface for distributed power systems. Energy Convers Manage2016;111:229–38 Available: <http://www.sciencedirect.com/science/article/pii/S0196890415011802> .

[51] Yin C, Wu H, Locment F, Sechilariu M. Energy management of {DC} microgridbased on photovoltaic combined with diesel generator and supercapacitor. EnergyConvers Manage 2017;132:14–27 Available: <http://www.sciencedirect.com/science/article/pii/S0196890416310135> .

[52] Torreglosa JP, Garca-Trivio P, Fernndez-Ramirez LM, Jurado F. Decentralizedenergy management strategy based on predictive controllers for a medium voltagedirect current photovoltaic electric vehicle charging station. Energy ConversManage 2016;108:1–13 Available: <http://www.sciencedirect.com/science/article/pii/S0196890415009966> .

[53] Pavkovi D, Lobrovi M, Hrgeti M, Komljenovi A. A design of cascade control systemand adaptive load compensator for battery/ultracapacitor hybrid energy storage-based direct current microgrid. Energy Convers Manage 2016;114:154–67Available: <http://www.sciencedirect.com/science/article/pii/S0196890416300280> .

[54] Ray PK, Mohanty SR, Kishor N. Proportional–integral controller based small-signalanalysis of hybrid distributed generation systems. Energy Convers Manage2011;52(4):1943–54 Available: <http://www.sciencedirect.com/science/article/pii/S019689041000511X> .

[55] Choudar A, Boukhetala D, Barkat S, Brucker J-M. A local energy management of ahybrid PV-storage based distributed generation for microgrids. Energy ConversManage 2015;90:21–33 Available: <http://www.sciencedirect.com/science/article/pii/S0196890414009625> .

[56] Bu S, Yu FR, Liu PX, Zhang P. Distributed scheduling in smart grid communicationswith dynamic power demands and intermittent renewable energy resources. In:2011 IEEE international conference on communications workshops (ICC); June2011. p. 1–5.

[57] Toledo OM, Filho DO, Diniz ASAC. Distributed photovoltaic generation and energystorage systems: a review. Renew Sustain Energy Rev 2010;14(1):506–11Available: <http://www.sciencedirect.com/science/article/pii/S136403210900207X> .

[58] Ibrahim H, Ilinca A, Perron J. Energy storage systems–characteristics and com-parisons. Renew Sustain Energy Rev 2008;12(5):1221–50 Available: <http://www.sciencedirect.com/science/article/pii/S1364032107000238> .

A. Anzalchi, A. Sarwat Energy Conversion and Management 152 (2017) 312–327

325

[59] Nikolakakis T, Fthenakis V. The optimum mix of electricity from wind- and solar-sources in conventional power systems: evaluating the case for New York state.Energy Policy 2011;39(11):6972–80 Asian Energy Security. Available: <http://www.sciencedirect.com/science/article/pii/S0301421511004526> .

[60] Afgan NH, Gobaisi DA, Carvalho MG, Cumo M. Sustainable energy development.Renew Sustain Energy Rev 1998;2(3):235–86 Available: <http://www.sciencedirect.com/science/article/pii/S1364032198000021> .

[61] Gohla-Neudecker B, Wagner U, Hamacher T. Analysis of renewable energy gridintegration by range extension technologies of BEVs. In: 2013 International con-ference on clean electrical power (ICCEP); June 2013. p. 155–62.

[62] Denholm P, Margolis RM. Evaluating the limits of solar photovoltaics (PV) inelectric power systems utilizing energy storage and other enabling technologies.Energy Policy 2007;35(9):4424–33 Available: <http://www.sciencedirect.com/science/article/pii/S030142150700095X> .

[63] IEEE approved draft standard conformance test procedures for equipment inter-connecting distributed resources with electric power systems amendment 1. IEEEP1547.1a/D5, December. 2014 1–19; May 2015.

[64] Papanikolaou N, Kyritsis A, Loupis M, Tzotzos C, Zoga E. Design considerations forsingle-phase line frequency transformers applied at photovoltaic systems. IEEEPower Energy Technol Syst J 2015;2(3):82–93.

[65] Guha B, Haddad RJ, Kalaani Y. Voltage ripple-based passive islanding detectiontechnique for grid-connected photovoltaic inverters. IEEE Power Energy TechnolSyst J 2016;3(4):143–54.

[66] Banham-Hall DD, Taylor GA, Smith CA, Irving MR. Towards large-scale directdrive wind turbines with permanent magnet generators and full converters. In:IEEE PES general meeting; July 2010. p. 1–8.

[67] Bae Y, Vu TK, Kim RY. Implemental control strategy for grid stabilization of grid-connected PV system based on german grid code in symmetrical low-to-mediumvoltage network. IEEE Trans Energy Convers 2013;28(3):619–31.

[68] Abraham Ellis BZDJRP, Walling Reigh. Interconnection requirements for variablegeneration. Nor Am Electr Reliab Corp (NERC) 2012.

[69] Meinhardt M, Cramer G. Past, present and future of grid connected photovoltaic-and hybrid-power-systems. In: 2000 power engineering society summer meeting(Cat. No.00CH37134), vol. 2; 2000. p. 1283–8.

[70] Kjaer SB, Pedersen JK, Blaabjerg F. A review of single-phase grid-connected in-verters for photovoltaic modules. IEEE Trans Indus Appl 2005;41(5):1292–306.

[71] Vilathgamuwa M, Nayanasiri D, Gamini S. Power electronics for photovoltaicpower systems. Synth Lect Power Electron 2015;5(2):1–131. http://dx.doi.org/10.2200/S00638ED1V01Y201504PEL008.

[72] Huang J, Shi H. A hybrid filter for the suppression of common-mode voltage anddifferential-mode harmonics in three-phase inverters with CPPM. IEEE Trans IndusElectron 2015;62(7):3991–4000.

[73] Lin B-R, Yang T-Y. Implementation of active power filter with asymmetrical in-verter legs for harmonic and reactive power compensation. Electr Power Syst Res2005;73(2):227–37 Available: <http://www.sciencedirect.com/science/article/pii/S0378779604001828> .

[74] Latran MB, Teke A. Investigation of multilevel multifunctional grid connectedinverter topologies and control strategies used in photovoltaic systems. RenewSustain Energy Rev 2015;42:361–76 Available: <http://www.sciencedirect.com/science/article/pii/S1364032114008478> .

[75] Yamamoto H, Inaba CY, Hiraki E, Nakaoka M. Multifunctional digitally-controlledbidirectional three-phase soft-switching PWM converter. In: 2000 eighth interna-tional conference on power electronics and variable speed drives (IEE Conf. Publ.No. 475); 2000. p. 86–90.

[76] Chandhaket S, Yoshida A, Eiji H, Nakamura M, Konishi Y, Nakaoka M. Multi-functional digitally-controlled bidirectional interactive three-phase soft-switchingPWM converter with resonant snubbers. In: 2001 IEEE 32nd annual power elec-tronics specialists conference (IEEE Cat. No.01CH37230), vol. 2; 2001. p. 589–93.

[77] Anzalchi A, Moghaddami M, Moghaddasi A, Pour MM, Sarwat A. A modifiedhigher order power filter for grid-connected renewable energy systems. In: 2016IEEE/IAS 52nd industrial and commercial power systems technical conference (ICPS); May 2016. p. 1–9.

[78] Anzalchi A, Moghaddami M, Moghadasi A, Pour MM, Sarwat A. Design and ana-lysis of a higher order power filter for grid-connected renewable energy systems.IEEE Trans Indus Appl 2017;PP(99):1.

[79] Anzalchi A, Moghaddami M, Moghaddasi A, Sarwat AI, Rathore AK. A new to-pology of higher order power filter for single-phase grid-tied voltage-source in-verters. IEEE Trans Indus Electron 2016;63(12):7511–22.

[80] Tuyen ND, Fujita G. PV-active power filter combination supplies power to non-linear load and compensates utility current. IEEE Power Energy Technol Syst J2015;2(1):32–42.

[81] Zeng Z, Yang H, Zhao R, Cheng C. Topologies and control strategies of multi-functional grid-connected inverters for power quality enhancement: a compre-hensive review. Renew Sustain Energy Rev 2013;24:223–70 Available: <http://www.sciencedirect.com/science/article/pii/S1364032113001925> .

[82] Liu L, Li H, Xue Y. A coordinated active and reactive power control strategy forgrid-connected cascaded photovoltaic (PV) system in high voltage high powerapplications. In: 2013 twenty-eighth annual IEEE applied power electronics con-ference and exposition (APEC); March 2013. p. 1301–8.

[83] Babaei E, Hosseini SH. New cascaded multilevel inverter topology with minimumnumber of switches. Energy Convers Manage 2009;50(11):2761–7 Available:<http://www.sciencedirect.com/science/article/pii/S0196890409002489> .

[84] Colak I, Kabalci E, Bayindir R. Review of multilevel voltage source invertertopologies and control schemes. Energy Convers Manage 2011;52(2):1114–28Available: <http://www.sciencedirect.com/science/article/pii/S0196890410004085> .

[85] Mohod SW, Aware MV. Micro wind power generator with battery energy storagefor critical load. IEEE Syst J 2012;6(1):118–25.

[86] Marei MI, El-Saadany EF, Salama MMA. A novel control algorithm for the DGinterface to mitigate power quality problems. IEEE Trans Power Deliv2004;19(3):1384–92.

[87] Cheng PT, Chen CA, Lee TL, Kuo SY. A cooperative imbalance compensationmethod for distributed-generation interface converters. IEEE Trans Indus Appl2009;45(2):805–15.

[88] Lv Z, Luo A, Wu C, Shuai Z, Kang Z. A research of microgrid energy supply andfiltering system based on inverter multiplexing. In: 2009 international conferenceon sustainable power generation and supply; April 2009. p. 1–7.

[89] Han B, Bae B, Kim H, Baek S. Combined operation of unified power-quality con-ditioner with distributed generation. IEEE Trans Power Deliv 2006;21(1):330–8.

[90] Li Y, Vilathgamuwa DM, Loh PC. Microgrid power quality enhancement using athree-phase four-wire grid-interfacing compensator. IEEE Trans Indus Appl2005;41(6):1707–19.

[91] Wang F, Duarte JL, Hendrix MAM. Grid-interfacing converter systems with en-hanced voltage quality for microgrid application – concept and implementation.IEEE Trans Power Electron 2011;26(12):3501–13.

[92] Yu X, Khambadkone AM. Multi-functional power converter building block to fa-cilitate the connection of micro-grid. In: 2008 11th workshop on control andmodeling for power electronics; Aug 2008. p. 1–6.

[93] Dasgupta S, Mohan SN, Sahoo SK, Panda SK. A lyapunov function based currentcontroller to control active and reactive power flow in a three phase grid con-nected pv inverter under generalized grid voltage conditions. In: 8th internationalconference on power electronics – ECCE Asia; May 2011. p. 1110–7.

[94] Cheng L, Cheung R, Leung KH. Advanced photovoltaic inverter with additionalactive power line conditioning capability. In: PESC97. Record 28th annual IEEEpower electronics specialists conference. Formerly power conditioning specialistsconference 1970–71. Power processing and electronic specialists conference 1972,vol. 1; Jun 1997. p. 279–83.

[95] Naderi S, Pouresmaeil E, Gao WD. The frequency-independent control method fordistributed generation systems. Appl Energy 2012;96:272–80 smart Grids.Available: <http://www.sciencedirect.com/science/article/pii/S0306261911006374> .

[96] Sawant RR, Chandorkar MC. A multifunctional four-leg grid-connected compen-sator. IEEE Trans Indus Appl 2009;45(1):249–59.

[97] Wang F, Duarte JL, Hendrix MAM. Control of grid-interfacing inverters with in-tegrated voltage unbalance correction. In: 2008 IEEE power electronics specialistsconference; June 2008. p. 310–6.

[98] Majumder R, Ghosh A, Ledwich G, Zare F. Load sharing and power quality en-hanced operation of a distributed microgrid. IET Renew Power Gener2009;3(2):109–19.

[99] Gajanayake CJ, Vilathgamuwa DM, Loh PC, Teodorescu R, Blaabjerg F. Z-source-inverter-based flexible distributed generation system solution for grid powerquality improvement. IEEE Trans Energy Convers 2009;24(3):695–704.

[100] Tsengenes G, Adamidis G. A multi-function grid connected PV system with threelevel NPC inverter and voltage oriented control. Sol Energy2011;85(11):2595–610 Available: <http://www.sciencedirect.com/science/article/pii/S0038092X11002593> .

[101] Saitou M, Shimizu T. Generalized theory of instantaneous active and reactivepowers in single-phase circuits based on hilbert transform. In: 2002 IEEE 33rdannual IEEE power electronics specialists conference. Proceedings (Cat. No.02CH37289), vol. 3; 2002. p. 1419–24.

[102] Abolhassani MT, Enjeti P, Toliyat H. Integrated doubly fed electric alternator/active filter (IDEA), a viable power quality solution, for wind energy conversionsystems. IEEE Trans Energy Convers 2008;23(2):642–50.

[103] Wu TF, Shen CL, Chang CH, Chiu JY. A 1 phi;3w grid-connection PV power in-verter with partial active power filter. In: 2002 IEEE 33rd annual IEEE powerelectronics specialists conference. Proceedings (Cat. No.02CH37289), vol. 3; 2002.p. 1512–7.

[104] He J, Munir MS, Li YW. Opportunities for power quality improvement through DG-grid interfacing converters. In: The 2010 international power electronics con-ference – ECCE ASIA; June 2010. p. 1657–64.

[105] Yu H, Pan J, Xiang A. A multi-function grid-connected PV system with reactivepower compensation for the grid. Sol Energy 2005;79(1):101–6 Available:<http://www.sciencedirect.com/science/article/pii/S0038092X04003019> .

[106] Kim S, Yoo G, Song J. A bifunctional utility connected photovoltaic system withpower factor correction and ups facility. In: Conference record of the twenty fifthIEEE photovoltaic specialists conference – 1996; May 1996. p. 1363–8.

[107] Bojoi RI, Limongi LR, Roiu D, Tenconi A. Enhanced power quality control strategyfor single-phase inverters in distributed generation systems. IEEE Trans PowerElectron 2011;26(3):798–806.

[108] Cirrincione M, Pucci M, Vitale G. A single-phase DG generation unit with shuntactive power filter capability by adaptive neural filtering. IEEE Trans IndusElectron 2008;55(5):2093–110.

[109] Macken KJP, Vanthournout K, den Keybus JV, Deconinck G, Belmans RJM.Distributed control of renewable generation units with integrated active filter.IEEE Trans Power Electron 2004;19(5):1353–60.

[110] Hosseini SH, Danyali S, Goharrizi AY. Single stage single phase series-grid con-nected PV system for voltage compensation and power supply. In: 2009 IEEEpower energy society general meeting; July 2009. p. 1–7.

[111] Dasgupta S, Sahoo SK, Panda SK, Amaratunga GAJ. Single-phase inverter-controltechniques for interfacing renewable energy sources with microgrid – part ii:series-connected inverter topology to mitigate voltage-related problems alongwith active power flow control. IEEE Trans Power Electron 2011;26(3):732–46.

A. Anzalchi, A. Sarwat Energy Conversion and Management 152 (2017) 312–327

326

[112] Lin B-R, Yang T-Y. Active power filter with asymmetrical inverter legs for har-monic and reactive power compensation. In: Circuits and systems, 2004. MWSCAS’04. The 2004 47th midwest symposium on, vol. 2; July 2004. p. II-285–II-288.

[113] Patidar RD, Singh SP, Khatod DK. Single-phase single-stage grid-interactive pho-tovoltaic system with active filter functions. In: IEEE PES general meeting; July2010. p. 1–7.

[114] Hirachi K, Mii T, Nakashiba T, Laknath KGD, Nakaoka M. Utility-interactive multi-functional bidirectional converter for solar photovoltaic power conditioner withenergy storage batteries. In: Proceedings of the 1996 IEEE IECON. 22nd interna-tional conference on industrial electronics, control, and instrumentation, vol. 3;Aug 1996. p. 1693–8.

[115] Dasgupta S, Sahoo SK, Panda SK. Single-phase inverter control techniques forinterfacing renewable energy sources with microgrid – part i: parallel-connectedinverter topology with active and reactive power flow control along with gridcurrent shaping. IEEE Trans Power Electron 2011;26(3):717–31.

[116] Seo HR, Jang SJ, Kim GH, Park M, Yu IK. Hardware based performance analysis ofa multi-function single-phase PV-AF system. In: 2009 IEEE energy conversioncongress and exposition; Sept 2009. p. 2213–7.

[117] Wu YE, Shen CL. Implementation of a dc power system with PV grid-connectionand active power filtering. In: The 2nd international symposium on power elec-tronics for distributed generation systems; June 2010. p. 116–21.

[118] Wu TF, Nien HS, Hsieh HM, Shen CL. PV power injection and active power fil-tering with amplitude-clamping and amplitude-scaling algorithms. IEEE TransIndus Appl 2007;43(3):731–41.

[119] Wu TF, Chang CH, Chen YK. A multi-function photovoltaic power supply systemwith grid-connection and power factor correction features. In: 2000 IEEE 31stannual power electronics specialists conference. Conference proceedings (Cat. No.00CH37018), vol. 3; 2000. p. 1185–90.

[120] Sladi S, Barii B, Sokovi M. Cost-effective power converter for thin film solar celltechnology and improved power quality, J Mater Process Technol 2008;201(13):786–90 [10th International Conference on Advances in Materials andProcessing TechnologiesAMPT 2007]. Available: <http://www.sciencedirect.com/science/article/pii/S0924013607013052>.

[121] Chiang SJ, Chang KT, Yen CY. Residential photovoltaic energy storage system.IEEE Trans Indus Electron 1998;45(3):385–94.

[122] Kuo Y-C, Liang T-J, Chen J-F. A high-efficiency single-phase three-wire photo-voltaic energy conversion system. IEEE Trans Indus Electron 2003;50(1):116–22.

[123] Chaitanakulwat A, Kinnares V, Thungsuk N. Single-phase grid-connected photo-voltaic system with active power filter functionality. In: 2012 15th internationalconference on electrical machines and systems (ICEMS); Oct 2012. p. 1–3.

[124] Calleja H, Jimenez H. Performance of a grid connected {PV} system used as activefilter. Energy Convers Manage 2004;45(1516):2417–28 Available: <http://www.sciencedirect.com/science/article/pii/S0196890403003613> .

[125] Mastromauro RA, Liserre M, Dell’Aquila A. PV system power quality enhancementby means of a voltage controlled shunt-converter. In: 2008 IEEE power electronicsspecialists conference; June 2008. p. 2358–63.

[126] Kuo Y-C, Liang T-J, Chen J-F. Novel maximum-power-point-tracking controller forphotovoltaic energy conversion system. IEEE Trans Indus Electron2001;48(3):594–601.

[127] Wu TF, Nei HS, Shen CL, Li GF. A single-phase two-wire grid-connection PV in-verter with active power filtering and nonlinear inductance consideration. In:Applied power electronics conference and exposition, 2004. APEC ’04. Nineteenthannual IEEE, vol. 3; 2004. p. 1566–71.

[128] Altin N, Ozdemir S. Three-phase three-level grid interactive inverter with fuzzylogic based maximum power point tracking controller. Energy Convers Manage2013;69:17–26 Available: <http://www.sciencedirect.com/science/article/pii/S0196890413000320> .

[129] Altin N, Sefa ibrahim. dSPACE based adaptive neuro-fuzzy controller of grid in-teractive inverter. Energy Convers Manage 2012;56:130–9 Available: <http://www.sciencedirect.com/science/article/pii/S0196890411003359> .

[130] Anzalchi A, Sarwat A. Artificial neural network based duty cycle estimation formaximum power point tracking in photovoltaic systems. In: SoutheastCon 2015;April 2015. p. 1–5.

[131] Ram JP, Babu TS, Rajasekar N. A comprehensive review on solar {PV} maximumpower point tracking techniques. Renew Sustain Energy Rev 2017;67:826–47

Available: <http://www.sciencedirect.com/science/article/pii/S1364032116305706> .

[132] Mokhtari G, Ghosh A, Nourbakhsh G, Ledwich G. Smart robust resources control inLV network to deal with voltage rise issue. IEEE Trans Sustain Energy2013;4(4):1043–50.

[133] Turitsyn K, Sulc P, Backhaus S, Chertkov M. Local control of reactive power bydistributed photovoltaic generators. In: 2010 first IEEE international conferenceon smart grid communications; Oct 2010. p. 79–84.

[134] Tonkoski R, Lopes LAC, El-Fouly THM. Coordinated active power curtailment ofgrid connected PV inverters for overvoltage prevention. IEEE Trans Sustain Energy2011;2(2):139–47.

[135] Demirok E, Sera D, Teodorescu R, Rodriguez P, Borup U. Evaluation of the voltagesupport strategies for the low voltage grid connected PV generators. In: 2010 IEEEenergy conversion congress and exposition; Sept 2010. p. 710–7.

[136] Demirok E, Gonzlez PC, Frederiksen KHB, Sera D, Rodriguez P, Teodorescu R.Local reactive power control methods for overvoltage prevention of distributedsolar inverters in low-voltage grids. IEEE J Photovolt 2011;1(2):174–82.

[137] Braun M, Stetz T, Brndlinger R, Mayr C, Ogimoto K, Hatta H, et al. Is the dis-tribution grid ready to accept large-scale photovoltaic deployment? state of theart, progress, and future prospects. Prog Photovolt: Res Appl 2012;20(6):681–97.http://dx.doi.org/10.1002/pip.1204.

[138] Tonkoski R, Lopes LAC, EL-Fouly THM. Droop-based active power curtailment forovervoltage prevention in grid connected PV inverters. In: 2010 IEEE internationalsymposium on industrial electronics; July 2010. p. 2388–93.

[139] Tanaka K, Oshiro M, Toma S, Yona A, Senjyu T, Funabashi T, et al. Decentralisedcontrol of voltage in distribution systems by distributed generators. IET GenerTransmis Distrib 2010;4(11):1251–60.

[140] Weckx S, Gonzalez C, Driesen J. Combined central and local active and reactivepower control of PV inverters. IEEE Trans Sustain Energy 2014;5(3):776–84.

[141] Liu L, Li H, Xue Y, Liu W. Decoupled active and reactive power control for large-scale grid-connected photovoltaic systems using cascaded modular multilevelconverters. IEEE Trans Power Electron 2015;30(1):176–87.

[142] Monica P, Kowsalya M. Control strategies of parallel operated inverters in re-newable energy application: a review. Renew Sustain Energy Rev2016;65:885–901 Available: <http://www.sciencedirect.com/science/article/pii/S1364032116303057> .

[143] Ozdemir S. Z-source t-type inverter for renewable energy systems with propor-tional resonant controller. Int J Hydrogen Energy 2016;41(29):12591–602 [spe-cial Issue on 3rd European conference on renewable energy systems (ECRES2015),710 October 2015, Kemer, Antalya, Turkey]. Available: <http://www.sciencedirect.com/science/article/pii/S0360319915316360>.

[144] Athari H, Niroomand M, Ataei M. Review and classification of control systems ingrid-tied inverters. Renew Sustain Energy Rev 2017;72:1167–76 Available:<http://www.sciencedirect.com/science/article/pii/S1364032116306839> .

[145] Dufo-Lpez R, Fernndez-Jimnez LA, Ramrez-Rosado IJ, Artal-Sevil JS, Domnguez-Navarro JA, Bernal-Agustn JL. Daily operation optimisation of hybrid stand-alonesystem by model predictive control considering ageing model. Energy ConversManage 2017;134:167–77 Available: <http://www.sciencedirect.com/science/article/pii/S0196890416311220> .

[146] Ramos GA, Costa-Castelló R, Olm JM. Repetitive control. Berlin, Heidelberg:Springer; 2013. p. 5–12. http://dx.doi.org/10.1007/978-3-642-37778-5_2.

[147] Tang Z, Akin B. Suppression of dead-time distortion through revised repetitivecontroller in PMSM drives. IEEE Trans Energy Convers 2017;32(3):918–30.

[148] Blaabjerg F, Teodorescu R, Liserre M, Timbus AV. Overview of control and gridsynchronization for distributed power generation systems. IEEE Trans IndustElectron 2006;53(5):1398–409.

[149] Huang Z, Li X, Mahboub M, Hanson KM, Nichols VM, Le H, et al. Hybrid molecule-nanocrystal photon upconversion across the visible and near-infrared. Nano Lett2015;15(8):5552–7. http://dx.doi.org/10.1021/acs.nanolett.5b02130. pMID:26161875.

[150] Ackerman E. Japan Demoes wireless power transmission for space-based solarfarms; 2015. Available: <http://spectrum.ieee.org/energywise/green-tech/solar/japan-demoes-wireless-power-transmission-for-spacebased-solar-farms> [ac-cessed August 21, 2017.

A. Anzalchi, A. Sarwat Energy Conversion and Management 152 (2017) 312–327

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