lable at ScienceDirect

Renewable Energy 64 (2014) 61e70

Contents lists avai

Renewable Energy

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

Technical note

Experimental study on flicker emissions by photovoltaic systems onhighly cloudy region: A case study in Malaysia

Yun Seng Lim*, Jun Huat Tang 1

Universiti Tunku Abdul Rahman, Faculty of Engineering and Science, Jalan Genting Klang, 53300 Kuala Lumpur, Malaysia

a r t i c l e i n f o

Article history:Received 6 July 2013Accepted 28 October 2013Available online 20 November 2013

Keywords:Photovoltaic systemCloudFlickerLoad controller

* Corresponding author. Tel.: þ60 126399520.E-mail addresses: yslim@utar.edu.my (Y.S. Lim), ta

1 Tel.: þ60 126399520.

0960-1481/$ e see front matter � 2013 Elsevier Ltd.http://dx.doi.org/10.1016/j.renene.2013.10.043

a b s t r a c t

Photovoltaic (PV) systems are the most promising renewable energy sources in Malaysia because of itslocation being around the equatorial region where sunlight is available throughout the year. However,the country is warm and surrounded by the South China Sea and Malacca Straits. A large amount ofclouds is created and passed over the region. The impacts of the passing clouds on the PV power outputsand voltage magnitude have to be studied thoroughly. Therefore, an experimental low-voltage networkintegrated with a PV system is set up. The experimental results show that the passing clouds result in thefrequent and rapid fluctuations of PV power outputs, hence producing a large amount of flickers to thedistribution networks. Some of the flickers are actually greater than the statutory limits. To mitigate thispower quality issue, a dynamic load controller is proposed to be the solution because its components arecheap. The load controller is made of a number of 200 W power resistors and solid-state relays. A centralcontroller switches the resistors on and off very rapidly based on the fluctuations of the network voltage.The experimental results show that the dynamic load controller is able to reduce the flickers effectivelyon the distribution networks. The studies and solution presented in this paper are very valuable todifferent parties, such as the government, policy makers, utility companies and owners of the PV sys-tems, in order to ensure an effective growth of the PV systems without compromising the quality ofelectricity supply to the customers.

� 2013 Elsevier Ltd. All rights reserved.

1. Introduction

Malaysia is one of the tropical countries in Southeast Asia. It isdivided into West and East Malaysia by the South China Sea asshown in Fig. 1. Malaysia depends highly on fossil fuels for elec-tricity generation. Electricity generation from renewable energysources was about 1% or less [1]. However, extreme reliance onfossil fuels has created much controversy because of its excessiveGHG emissions [2,3]. Also the reserves of oil and gas are depletingvery rapidly [4]. Therefore, the government has promoted the usageof renewable energy sources by launching renewable energy pro-grammes, such as Main Building Integrated Photovoltaic Project in2005, new feed-in-tariffs for RE in 2012 and the new forwardlooking RE policy in 2012 [5,6].

Photovoltaic (PV) systems are the most promising renewableenergy sources in Malaysia because of its location being around theequatorial region where sunlight is available over the year.

ngjh8@1utar.com (J.H. Tang).

All rights reserved.

However, the country is warm and surrounded by the South ChinaSea and Malacca Straits. Therefore, a large amount of clouds iscreated and passed over the country. Fig. 2 shows the frequency ofcompletely clear sky occurrences at various regions around theworld [7]. Malaysia does not have a single day with a completelyclear sky. As tabulated in Table 1, the average amount of clouds inMalaysia is about 77% which is the highest in the world [8,9].

With a large amount of clouds passing over Malaysia, theincident solar irradiance is therefore highly scattered and fluctu-ating, hence making the power output of the photovoltaic systemsto be very intermittent. Highly intermittent power output from PVsystems causes the voltage at the point of connection to be fluc-tuating sharply and frequently, hence generating a large number ofvoltage fluctuations and flickers to the low-voltage distributionnetworks.

At present, little attention is placed on the flicker emissions bythe PV systems because the majority of the countries is free fromcloudy skies at the most of the time. Flickers introduced by windturbines have been studied by the authors in [10e13]. There are anumber of methods used to reduce flickers generated from thewind turbines. The most common solution is to use a powerelectronic-based device, namely static synchronous compensator

Fig. 1. Malaysia map.

Fig. 2. World map showing the frequency of completely clear sky occurrence (%).

Y.S. Lim, J.H. Tang / Renewable Energy 64 (2014) 61e7062

(STATCOM), integrated with capacitors. STATCOM is installed on apoint of concern to supply reactive power actively to the trans-mission network to reduce the flickers [14]. However, this solutionis effective if the wind turbines are placed on the transmission

Table 1Average amount of cloud and frequency of clear sky occurrence in several regions.

Regions Europe US SouthAfrica nearequator

South Americanear equator

Malaysia

Average amount ofcloud (%)

53.29 56.44 60.44 62.81 76.86

Frequency ofclear skyoccurrence (%)

22.95 16.87 11.37 13.10 0.71

networks because the line reactance is larger than the resistance.Another method is to control actively the supply of real power fromthe converter of the wind turbines so that the flickers can beminimised [10,16]. This approach is effective if the wind turbinesare installed on the distribution networks because the line resis-tance is larger than the reactance.

The general technical issues caused by the distributed genera-tion have also been studied by the researchers in [17e19]. Althoughsome researchers have investigated the impacts of photovoltaicsystems on the voltage levels [20e23], they use simulation ap-proaches to carry out the studies. Experimental studies on thepower quality issues caused by the PV systems are not verycommon.

The objective of this paper is to present the findings on theflicker emissions by the photovoltaic systems on Malaysia. An

Fig. 3. Experimental set up.

Y.S. Lim, J.H. Tang / Renewable Energy 64 (2014) 61e70 63

experimental system is set up to carry out the experiments. Thissystem consists of a low-voltage distribution network integratedwith a PV system and a load bank. Characterisation of the PV poweroutput is carried out to show the frequency and the duration of thepeak PV power outputs. Standard formulas are used to calculate thevoltage fluctuation index, short-term flickers and long-term flickersfrom a collection of the measurement. Dynamic load controller isproposed to mitigate the flickers because it is a cheap and effectiveapproach.

This paper begins with a brief description of the impacts ofvoltage fluctuation and flickers, followed by the set-up of theexperimental network and the characterisation of the PV poweroutput. The severities of voltage fluctuation and flickers are thenpresented based on the measurement data. The reduction inflickers using the load controllers is shown before the conclusion ispresented.

2. Impacts of voltage fluctuation and flickers

Usually, the main sources of voltage fluctuations and flickers onHV and MV networks are arcing furnaces, welding machines, roll-ing mills, mine winders, large capacitor bank for reactive powercompensation and electric boilers. The main sources of voltagefluctuations and flickers on the low voltage networks are starting oflarge electrical motors, X-ray, pumps, refrigerators and electriccookers [24].

The flickers cause electrical motors to change in their startingtorques and power consumption, hence causing the increase in thetemperature and the deterioration of the efficiencies of the ma-chines. The lifespan of the motors are then shortened. Air condi-tioners are very common appliances in Malaysia. The motors beingused in the air conditioners can fail prematurely. Therefore, the costassociated with the repair and maintenance of the air conditionersmay increase substantially. Also rapid changes in voltage supply canmake the motors to run at the varying speeds with vibration, henceleading to the poor quality of products in any manufacturing fac-tories [25].

The voltage fluctuations and flickers can cause the light sources,such as incandescent lamps, to vary their luminous of light flux.Anyone who is affected by light flickering can suffer headaches,migraines and eye discomfort. In addition, unstable voltage supplycauses electronic equipment malfunction, unwanted triggering ofuninterruptible power supply (UPS) units to switch to batterymodeand reduce the operational efficiency [26].

3. Set up of the experimental low-voltage distributionnetwork with a photovoltaic system

To study the characteristics of PV power output and voltagemagnitude at the point of the PV connection, a low-voltage three-phase distribution network is set up as shown in Fig. 3. A photo-voltaic (PV) system and a controllable load bank are connected tothe distribution network. Either the utility grid or a 15 kW gener-ator can be used as the supply source to the distribution network.The 15 kW generator is used to study the flickers purely generatedby the photovoltaic system. The technical details of the 15 kWgenerator are given in Appendix A.

The type of solar cells in the modules is polycrystalline. Thetechnical specifications of the PV modules are shown in AppendixA. The PV modules are commercial products that comply with allthe technical standards. Therefore, the quality of the PV modulesand their power outputs are well trusted.

Each PVmodule has a maximum capacity of 230W. There are 32modules being mounted on the car park area to produce themaximum capacity of 7.36 kW as shown in Fig. 4. These 32 PV

modules are divided into four strings. Each string has the capacityof 1.84 kW and is detachable from the solar inverter such that thecapacity of the PV system can be fixed at 1.84, 3.68, 5.52 and7.36 kW.

The rating of the solar inverter is 3.0 kW. Two inverters are usedto accommodate the 7.36 kW PV modules. The technical specifi-cations of the solar inverter are given in Appendix A. The inverter isa well-recognised solar device that complies with all the technicalstandards. Therefore, the quality of the device and AC outputvoltage are well within the permissible tolerance.

The PV modules are mounted on the car park area surroundedby trees and buildings. The nearest building is more than 30 maway from the PVmodules. The building is too far away from the PVpanel and should not shade the PV panel. The trees are the onlypossible object to shade the PV panel. The shortest distance fromthe PV modules to the nearest tree is about 15.8 m. The PV panel isalighted with the tree in a straight line pointing towards the East.The trees may shade the PV panel early in the morning. The heightsof the PV mounting structure and the tree are 3.3 and 6.6 mrespectively. The angle made between the PV plane and the solarradiation just before the PV panel receives the direct sunlight in themorning is calculated to be 12.4�. This inclination angle can happenapproximately at 8 am as determined by using PSA algorithm [27].After 8 am, the PV panel receives direct sunlight throughout the daywithout being shaded by any surrounding objects. Therefore, themeasurement of the voltage and current from the PV is set to takeplace after 8 am.

4. Characterisation of the PV power output

A case study is carried out to characterise the power output ofthe PV system in the experimental network. The two PV systemsare connected to phase A of the distribution network. The terminalvoltage and the current output of the PV systems are measured byusing two national instrument modules, namely NI 9225 voltagemodule and NI 9227 current module. Labview is used as a pro-gramming platform to read the readings from the NI modules andstore them in a Microsoft excel file. The PV systems are monitoredover a period of 9 months. The result of a particular day is shown inFig. 5. The PV power output fluctuates very rapidly, causing thevoltage magnitude to change frequently throughout the day. Threeunique characteristics of the PV power outputs are observed aslisted below.

1. Many high PV power outputs happen within short durations.

Fig. 4. Mounting of the PV array on the site.

Y.S. Lim, J.H. Tang / Renewable Energy 64 (2014) 61e7064

2. Some of the high power outputs drop down suddenly instead ofgradually. For example, the high power output of 2.7 kW thathappens between 12.00 and 12.22 pm drops immediately to1.2 kW after 12.22 pm.

3. The magnitude of reduction in the PV power output is signifi-cant, about 63% of reduction in the PV power output.

Many high PV power outputs happen within short durationsbecause of the high frequency of the passing clouds over the PVpanels. The sudden reductions in the PV power outputs are causedby the thick clouds that reduce the total solar irradiation arriving atthe solar panels. Some of the thick clouds can reduce the solarirradiation substantially, hence making a significant reduction inthe PV power output.

A collection of PV power outputs over a period of 9 months ischaracterised to derive a chart as shown in Fig. 6. This chart showsthe frequency of various PV power outputs and the correspondingduration. It is noticed that the majority of the high PV power out-puts happen for less than 5 min.

A comprehensive PV monitoring data from Thailand, China,Hong Kong and the UK are collected from the sources of [28e31].Fig. 7 shows the characteristics of PV power outputs in Thailand,China Hong Kong and the UK. It is shown that themajority of the PVpower outputs in China, Hong Kong and the UK happen for morethan 30 min which is much longer than that in Malaysia. Further-more, the PV power outputs reduce gradually. Therefore, themagnitudes of flickers produced by the photovoltaic systems aresignificantly less than that in Malaysia. It is noticed that the lifespanof some high PV power outputs in Thailand are short, less than

Fig. 5. Fluctuation in PV output and voltage magnitude.

5 min. This is because Thailand is close to Malaysia, making thisregion to be vulnerable to much passing clouds.

5. Quantification of voltage fluctuations and flickersproduced by the photovoltaic system

To quantify the voltage fluctuation and flickers produced by thephotovoltaic systems, standard formulas are adopted from [11,32].The method described in this paper to calculate the short-termflickers is an estimation approach as described in IEC 61000-3-3[33] as well as the handbook of power quality [34]. It is a simplifiedassessment technique for estimating the short-term flicker severitycaused by equipment at the low voltage networks. It is also knownas the unity flicker severity curve approach. This methodmakes useof the fact that the short-term flicker severity is a linear parameterto the magnitude of the voltage changes that causes it. It providesgood indication of the flicker severity and has been used in the pastas described in [11,32,35]

This method is chosen and incorporated into the control algo-rithm of the load controller because it is a quick and simpleassessment approach which creates a very little delay in theexecution of the load controller. The approach defined in IEC61000-4-15 [6] calculates the short-term flicker accurately. How-ever, this approach needs more computation effort than the flickercurve method. If it is used in the control algorithm, the execution ofthe programme can slow down the response of the load controllertowards voltage fluctuations substantially.

The steps of the flicker curve method are described as follows:-

Fig. 6. Characteristic of PV output in Kuala Lumpur.

Fig. 7. Characteristic of PV output in other countries.

Fig. 8. Unity flicker curve at PST0 ¼ 1.

Y.S. Lim, J.H. Tang / Renewable Energy 64 (2014) 61e70 65

Step 1: Determine the magnitude of every voltage changes overthe specified minute using the following equation.

DV ¼ Vmax � VminVnom

*100 (1)

where Vmax is the maximum voltage, Vmin refers to minimumvoltage and Vnom is the nominal voltage, which is 230 V inMalaysia.

Step 2: Determine the number of voltage changes within thespecified minute, r.Step 3: Calculate the average value, d, of the all the voltagechanges DV happening within the specified minute.Step 4: Substituting, r, expressed as the number of voltagechanges per minute, into the severity curve as shown in Fig. 8 tofind the corresponding relative voltage change, d0, that pro-duces PST0 ¼ 1.0.Step 5: The short-time flicker severity can therefore be calcu-lated using the following correlation.

PST ¼ PST0 �dd0

¼ dd0

(2)

The long-term flicker index, PLT, is the average of PST evaluatedover 2 h using the cubic law as defined below.

PLT ¼

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiXNi¼1

�PiST

�3N

3

vuuut (3)

where N is the total number of short-term flickers within the 2 hand PiST is the short-term flicker at the number of i.

Fig. 10. A number of short-term flickers being calculated from the collection of voltagemagnitude.

Y.S. Lim, J.H. Tang / Renewable Energy 64 (2014) 61e7066

5.1. Case study 1: study flicker emission on the network with the15 kW generator

A case study is carried to investigate the severity of flickersintroduced by the photovoltaic system. A 1.84 kW photovoltaicsystem is connected to phase A of the distribution network. A15 kW generator is used to be the supply source to the networkbecause the generator does not generate any severe flickers to thenetwork. As a result, any flickers experienced at the point of thecommon coupling are generated from the photovoltaic system.

The voltage magnitude at the point of the common coupling ismeasured and used to calculate the short-term and long-termflickers. Fig. 9 shows the voltage fluctuation index (VFI), short-term flickers (PST) and long-term flickers (PLT). There are 47 short-term flicker indices that are calculated from the collection of dataas shown in Fig. 10. The average of the 47 short-term flickers is thelong-term flicker. Table 2 shows the values of the voltage fluctua-tion, short and long-term flicker indices. It is noticed that themaximum value of the short-term flicker exceeds the statutorylimit. The long-term flicker index is also greater than the statutorylimit. These results show that the flickers produced by the photo-voltaic systems can exceed the allowed limits.

5.2. Case study 2: study on flicker emission on the network with theutility grid

A second case study is carried out to investigate the severity offlicker caused by various PV capacities on phase A when the utilitygrid is used as the supply source to the network. For each PV ca-pacity, the voltage magnitudes on phase A, B and C at the point ofcommon coupling are measured and used to calculate all the short-term flicker indices as well as the long-term flicker index over theperiod of measurement. Figs. 11e13 show the worst flickers expe-rienced on phase A, B and C at the point of common coupling.

Fig. 11 shows that the short and long-term flicker indices are0.231 and 0.1247 respectively when the PV system is not connectedto the network. These values represent the background flickerindices. These background indices can vary depending on the ac-tivities on the university premise. These values can increase if thereare a number of air conditioners or machineries operating at thesame time. When a 1.84 kW PV system is connected to the network,the background flicker is combined with the flickers introduced bythe PV system to give rise to the total short and long-term flickers of0.922 and 0.365 as shown in Fig. 11.

Fig. 9. Variation in voltage magnitude caused by the fluctuation in the power output ofthe 1.84 kW photovoltaic system.

As the PV capacity increases from 1.84 to 7.37 kW on phase A,the short and long-term flickers grow from 0.922 to 1.158 and 0.365to 0.509 respectively. The results prove that the capacity of PVsystem contributes to the growth of the short and long-termflickers. It is also noticed that the short-term flicker index be-comes greater than the statutory limit of 1.0 when the PV capacityis 7.37 kW. The index is projected to be much higher if the PV ca-pacity is higher than 7.37 kW.

Figs. 12 and 13 show a significant increase in the short and long-term flicker indices on phase B and C even though the PV system ison phase A. The flickers on phase A cause the flicker indices onphase B and C to increase. This is because there are mutual cou-plings or capacitive linkages between the three phases in an elec-trical cable. These linkages establish an electrical connectionbetween the three phases. Any high magnitude of flickers andharmonic currents on one phase can propagate to the other phasephases through the mutual couplings. The experimental resultsshow that the impacts caused by the intermittency of the PV poweroutput can be widely spread across the distribution network.Therefore, it is very important to mitigate the flickers caused by thefluctuation of the PV power output.

6. Dynamic load controller for mitigating flickers

There are several options available to mitigate voltage fluctua-tion and flicker issues. Installing static capacitors, power electronic-based switching devices or increasing the cable size of the distri-bution network is one of the mitigation techniques [33]. Supercapacitor is claimed to be an effective means for mitigating thevoltage fluctuation from the photovoltaic systems [34]. By incor-porating the mitigation technique as part of the photovoltaic sys-tems, the total cost of the photovoltaic systems can be very high.

Table 2The values of voltage fluctuation index, short- and long-term flickers.

Index Magnitude Statutory limits

Voltage fluctuation index (VFI) 0.254a N/Ab

Short-term flicker (PST) Maximum PST ¼ 2.150c 1.00d

Long-term flicker (PLT) 0.834e 0.65f

a The voltage fluctuation index is based on the voltage data of one day.b The statutory limit for the voltage fluctuation index is not available.c These are the maximum and minimum values of PST among the all values of PST.d The statutory limit of short-term flicker is from [17].e The value of the long-term flicker is based on the data of one day.f The statutory limit of long-term flicker is from [17].

Fig. 11. Short-term and long-term flicker indices on phase A with respect to variouscapacity of PV.

Fig. 13. Short-term and long-term flicker indices on Phase C with respect to variouscapacity of PV.

Y.S. Lim, J.H. Tang / Renewable Energy 64 (2014) 61e70 67

Hence, the photovoltaic systems can be an unattractive renewableenergy source in Malaysia. In order to keep the cost of the photo-voltaic systems as low as possible, the mitigation methods must becheap and yet effective enough to reduce the indices of voltagefluctuation and flickers.

It is proposed to use dynamic load controllers to mitigate thevoltage fluctuations and flickers. Dynamic load controllers are aform of demand side management usually used to control the levelof power consumption on the electrical grid. They can reduce thepeak demand to avoid any power interruptions on the grid ormaintain the frequency of standalone power systems due to thelimited capacity of the power generation as described in Refs. [35e39]. Demand side management is also proved to be an effectiveapproach for reducing the distribution losses and hence cuttingdown the electricity bills for customers [40,41]. It is also used tosolve voltage rise issues on distribution networks integrated with alarge number of distributed generation (DG) [42]. Using the loadcontrollers to mitigate flickers caused by the photovoltaic systemsmay not be studied thoroughly.

Theproposed load controller ismadeof a numberof resistors andsolid-state relays which are cheap components. The load controllermakes use of the real power to correct the network voltage on thedistribution network because the line resistance is bigger than thereactance. Furthermore, the amount of real power required by theloadcontroller is small. Therefore,onlya small amountofPVpower isdissipatedasheat in the resistors. This amount canbeused toheatupwater for washing purposes.

Fig. 12. Short-term and long-term flicker indices on Phase B with respect to variouscapacity of PV.

The load controller is implemented in the experimentalnetwork as shown in Fig. 3. It consists of 6 units of 200 W powerresistors with solid state relays to switch on and off the powerresistors. The resistance of each resistor is 288 U. A simple controlalgorithm is developed using LabVIEWas a programming platformin a computer. Fig.14 shows theflowchart of the control algorithm.The control algorithm uses the voltage magnitude at the point ofthe common coupling to determine whether the voltage is withinthe required tolerance or not. The nominal value of the low-voltagedistribution network is 240 V. The tolerance with the upper andlower limits of 243 and 238 V is established in the control algo-rithm. If the network voltage is detected to be outside the toler-ance, the control algorithm can immediately switch on or off theresistors to reduce the voltage fluctuation or flickers. The algo-rithm is very simple and therefore the resistors can be switched onand off very rapidly.

The cost of a STATCOM with the use of capacitors is at least US$5000.00 [43]. The cost of the dynamic load controller is estimatedto be Ringgit Malaysia (RM) 1000.00 or US$ 314.00 based on theexchange rate of 0.31 USD/RM. It is shown that the cost of the dy-namic load controller is very much lower than that of STATCOM.

An experiment is carried to investigate the effectiveness of usingthe load controllers to mitigate flickers. In this experiment, a1.84 kW PV system is connected to the laboratory network with the15 kWgenerator being the supply source. The short-termflickers arethen calculated and shown in Fig. 15. It is noticed that all the short-term flicker indices are reduced when the load controllers are used.The maximum flicker is lower than the statutory limit. The long-term flicker is also reduced to 0.458. This experiment shows thatthe load controller is an effective means of mitigating voltage fluc-tuation and flickers. The load controller consumes about 10% of thetotal electricity generated by the 1.84 kW PV system. Therefore, theelectricity consumed by the resistors is 0.65 kWh per day. The fre-quency of switching the load controller varies depending on theintermittency of the PV power outputs. It is noticed that theswitching frequency can vary ranging from100 to 150 times per day.

7. Conclusion

Photovoltaic systems are recognised as a potential renewableenergy sources in Malaysia because of the large amount of solarirradiation available throughout the year. However, a large amountof clouds is generated and passed over the country, hence causingthe PV systems to inject severe flickers to the distribution networks.Therefore, a laboratory network has been set up to investigate theseverity of flicker emissions by the photovoltaic systems.

Fig. 14. Flow chart of the control algorithm.

Y.S. Lim, J.H. Tang / Renewable Energy 64 (2014) 61e7068

The PV power output and the voltage magnitude have beenmeasured and characterised to show the frequency and the dura-tion of the high power output. The majority of the high PV poweroutputs happen within short durations. The changes in the poweroutputs happen very rapidly. These are due to the large number ofclouds passing over the PV panel. Some of the clouds are very thick,hence reducing the solar irradiation substantially.

The collection of voltage magnitudes is used to calculate theshort and long-term flickers with respect to various PV capacities.The experimental results show that the severity of the flickersgrows with the PV capacity. Some of the short-term flickers exceedthe statutory limits. In addition, the presence of the mutual

Fig. 15. Values of short-term flickers produced by the 1.84 kW photovoltaic system onthe laboratory network.

coupling enables any severe flickers on one phase to propagate tothe other two phases of the network. Therefore, the effects of theflickers can be widely spread out across the distribution network.

A load controller is proposed to be the mitigation methodbecause its components are cheap. It consists of several resistors andsolid state relays. It can switch the resistors on and off very rapidly toreduce severity of flickers caused by the photovoltaic system. Theload controller is an effective approach on the distribution networkbecause the line resistance is larger than the reactance. Furthermore,the amount of real power required by the load controller is small.Therefore, only a small amount of PV power is dissipated as heat.

Appendix A. Specifications of the laboratory distributionnetwork

Tables A1eA3 show the technical specifications of the photo-voltaic modules, the inverter and the generator.

Table A1Technical specifications of photovoltaic modules.

PV module Specifications

Type of solar cells PolycrystallineModule efficiency 14.1%Maximum power (Pmax) 230 W with tolerance of þ10% and �5%Short circuit current (ISC) 8.42 AOpen circuit voltage (VOC) 37.0 VMaximum power current ðIPmax

Þ 7.83 AMaximum power voltage ðVPmax

Þ 29.4 VMax. system open circuit voltage 1000 VPhysical dimension 1658*986*50 mmPhysical weight 23 kgCompliance with standards IEC61215, IEC61730, IEC61730-2

and CE mark

Table A2Technical specifications of photovoltaic inverter.

Photovoltaic inverter Specifications

Type Single-phase grid-connected solar inverterDC inputMax. input voltage 500 VMPPT voltage range 150e450 VMax. input current 2*12 AAC outputNominal power 3000 WNominal voltage 230 VVoltage range 184e264 VMax. output current 14 ANominal frequency 50/60 HzFrequency range 49e51 HzTemperature range �20� to 50�

Table A3Some of the technical specifications of the generator

15 kW generator Specifications

Type Three phase synchronous generatorVoltage (V) 415Rating power (kVA) 17Efficiency (%) at 0.8 PF 85.4Phase resistance

(ohms) at 20 �C0.94

Voltage regulation accuracy �1% in steady state conditionCompliance with Standards IEC 60034-1; CEI 2-3, BS 4999-5000;

VDE 0530; NF 51-100, 111; OVE M-10,

Y.S. Lim, J.H. Tang / Renewable Energy 64 (2014) 61e70 69

NEMA MG 1.22

Appendix B. Relationship between the change in PV poweroutput and voltage magnitudes

The changes in the PV power output (DP) and the correspondingfluctuations in voltage magnitude (DV) are determined from thecollected measurements and plotted as shown in Fig. B1.

It is shown that DP is linearly proportional to DV with thegradient of 0.171. This result does not agree with the conventionalidea of non-linear relationship between the power flowand voltagemagnitude. To understand exactly how DP is related to DV, thecorrelation between DP and DV has to be determined. It is knownthat the changes in voltage magnitude (DV) and current (DI) arerelated as follows:-

Fig. B1. Correlation between DP and DV.

DV ¼ Z � DI (B1)

where Z is the impedance of the transmission line where the PVsystem is connected to. The change in PV power output (DP) isrelated to DI by the following equation.

DP ¼ ðV þ DVÞ � DI (B2)

DI is related to DV by the following equation.

DI ¼ DVZ

(B3)

Substituting Eq. (B2) into Eq. (B3) gives the following.

DP ¼ ðV þ DVÞ � DVZ

(B4)

V is the nominal voltage and is much greater than DV. Therefore,

DPz�VZ

�� DV (B5)

The change of the voltage magnitude depends on two factorsbased on Eq. (B5). It depends on the change of the PV power outputand the impedance (Z) of the cable where the PV system is con-nected to. If the impedance of the cable (Z) is high, then the changeof the voltage magnitude is reduced.

References

[1] Che Khalib MN. Nuclear energy as an option for Malaysia, Kuala Lumpur;2012.

[2] Choi TW. PM pledges conditional reduction of GHG emission by 2020 [Online].Available from: www.thestar.com.my; 18 March 2012 [accessed 01.05.12].

[3] Douglas UE. Malaysia second national communication to the UNFCCC. Putra-jaya; 2012.

[4] Gan P. An econometric study on long-term energy outlook and the implica-tions of renewable energy utilisation in Malaysia. Energy Policy Feb 2008:890e9.

[5] SEDA. SEDA [Online]. Available from: www.seda.gov.my; 1 Feb 2012 [accessed21.03.12].

[6] Koh SL, Lim YS. Meeting energy demand in a developing economy withoutdamaging the environment e a case study in Sabah Malaysia from technical,environmental and economic perspectives. Energy Policy 2010;38:12e26.

[7] Hahn Carole J, Warren Stephen G. Climatic atlas of clouds over land and ocean.University of Washington; August 2010 [Online]. Available from: http://www.atmos.washington.edu/CloudMap/ [accessed 23.01.13].

[8] Warren Stephen G, Hahn Carole J. UW atmospheric sciences [Online]. Avail-able from: http://www.atmos.washington.edu/CloudMap/; June 2012[accessed 06.06.12].

[9] Kushnir Y. The climate system [Online]. Available from: http://eesc.columbia.edu/courses/ees/climate/lectures/gen_circ/index.html; 2007 [accessed 18.11.12].

[10] Hu W, Chen Z, Wang Y. Flicker mitigation by active power control of variable-speed wind turbines with full-scale back-to-back power converters. IEEETrans Energy Convers Sept 2009:640e9.

[11] Nambiar A, Kiprakis A, Wallace A. Quantification of voltage fluctuationscaused by a wave farm connected to weak, rural electricity networks. In: 14thinternational conference on harmonics and quality of power, 2010 26e29Sept 2010. Bergamo, Italy.

[12] Ammar M. Flicker emission of distributed wind power: a review of impacts,modeling, grid codes and mitigation techniques. In: 2012 IEEE power andenergy society general meeting, San Diego, CA, USA 2012.

[13] Jakus D, Goic R, Krstulovic J. The impact of wind power plants on slow voltagevariations in distribution networks. Electr Power Syst Res 2011;81:589e98.

[14] Ferdous MJ, Arafat Y, Azam MA. Flicker level mitigation of weak grid con-nected wind turbine with DFIG by injecting optimum reactive power usingSTATCOM, 2013 International Conference on Informatics. Electronics andVision 17e18 May 2013:1e5.

[16] Ali H, Alaboudy Kasem, Daoud Ahmed A, Desouky Sobhy S, Salem Ahmed A.Converter controls and flicker study of PMSG-based grid connected windturbines. Ain Shams Eng J March 2013;4(1). ISSN: 2090-4479:75e91. http://dx.doi.org/10.1016/j.asej.2012.06.002.

[17] Ortega MJ, Hernandez J, Garcia OG. Measurement and assessment of powerquality characteristics for photovoltaic systems: harmonics, flicker, unbalanceand slow voltage variations. Electr Power Syst Res 2013:23e35.

[18] Hernandez JC, Ortega MJ, Vidal PG. Procedure for the technical measurementof harmonic, flicker and unbalance emission limits for photovoltaic-

Y.S. Lim, J.H. Tang / Renewable Energy 64 (2014) 61e7070

distributed generation. In: Proceedings of the 2011 international conferenceon power engineering, energy and electrical drives, Malaga, Spain 2011.

[19] Passey R, Spooner T, MacGill L, Watt M, Syngellakis K. The potential impacts ofgrid-connected distributed generation and how to address them: a review oftechnical and non-technical factors. Energy Policy 2011;39:6280e90.

[20] Woyte A, Thong VV, Belmans R. Voltage fluctuations on distribution levelintroduced by photovoltaic systems. IEEE Trans Energy Convers 2006;21(1):202e9.

[21] Widen J, Wackelgard E, Paatero J, Lund P. Impacts of distributed photovoltaicson network voltages: stochastic simulations of three swedish low-voltagedistribution grids. Electr Power Syst Res 2010;80:1562e71.

[22] Wong J, Lim YS, Taylor P, Morris S. Optimal utilisation of small scaleembedded generators in a developing country - a case study in Malaysia.Renew Energy 2011;36:2562e72.

[23] Trichakis P, Taylor PC, Lyons P, Hair R. Predicting the technical impacts of highlevel of small scale embedded generators on low voltage network. IET RenewPower Gener 2008:249e62.

[24] Hanzelka Z, Bien A. Copper development association [Online]. Available from:http://www.copperinfo.co.uk/power-quality/voltage-disturbances/flicker-measurement.shtml; October 2005 [accessed 19.11.12].

[25] Waghmare SA. Induction motor voltage flicker analysis and its mitigationMeasures using custom power devices: a case study. Int J Eng Sci Technol2010:7626e40.

[26] International Electrotechnical Commssion. Electromagnetic compatibility (EMC)- part 3: limits - section 3: limitation of voltage fluctuations and flicker in low-voltage supply systems for equipment with rated current <¼ 16 A; 1994.

[27] Muriel B. Plataforma Solar de Almerya [Online]. Available from: http://pvcdrom.pveducation.org/SUNLIGHT/sunPSA.HTM; 2012 [accessed 22.01.13].

[28] Chokmaviroja S, Wattanapongb R, Suchartc Y. Performance of a 500 kWP gridconnected photovoltaic system at Mae Hong Son Province, Thailand. RenewEnergy 2006:19e28.

[29] Zou X. Performance of a grid-connected BIPV system at Jiangsu Province,China. In: Power and energy engineering conference (APPEEC), 2012 Asia-Pacific, Shanghai 27e29 March 2012.

[30] Danny HWL, Gary HWC. Analysis of the operation performance and efficiencycharacteristic for photovoltaic system in Hong Kong. Energy Convers Manag2005:1107e18.

[31] More solar PV goodness [Online]. Available from: http://blog.darrenscott.com/2012/05/27/more-solar-pv-goodness/; 2012 [accessed 16.01.13].

[32] Sanjay AD, Waghmare LL. Induction motor voltage flicker analysis and itsmitigation meassures using custom power devices: a case study. Int J Eng SciTechnol 2010:7626e40.

[33] Roger CD, Mark FM, Surya SH, Wayne B. Electrical power system quality. TheMcGraw-Hill; 2002.

[34] Woyte A, Bodach M, Belmans R, Nijs J. Power fluctuations in micro-gridsintroduced by photovoltaics: analysis and solutions. In: 2nd European PV-hybrid and mini-grid conference, Kassel, Germany 2003.

[35] Eto J. The past, present, and future of U.S. utility demand side management pro-grams. California: Ernrst Orlando Lawrence Berkeley National Laboratory; 1996.

[36] Strbac G. Demand side management: benefits and challenges. Energy Policy2008;36:4419e26.

[37] Gellings CW. The smart grid: enabling energy efficiency and demandresponse. The Fairmont Press; 2009.

[38] Sinha A. Role of demand side management for power distribution utility inIndia. In: Power and energy society general meeting 2011.

[39] Han J, Piette M. Solutions for summer electric power shortages: demandresponse and its application in air conditioning and refrigerating system.USA; 2008.

[40] Hedrick K. Demand side management: why utility-directed load managementprogramsmakemore sense than ever before; 2011 [Online]. [accessed 18.11.12].

[41] Zhang N, Ochoa LF, Kirschen DS. Investigating the impact of demand sidemanagement on residential customers. In: 2nd IEEE PES international con-ference and exhibition 2011.

[42] Lim YS, Taylor P. Innovative application of demand side management to po-wer systems. In: First international conference on industrial and informationsystems, Sri Lanka 2006.

[43] Static Synchronous Compensator e STATCOM. Source: http://www.alibaba.com/showroom/statcom.html, [accessed 14.10.13].