Effect of partial shading patterns and degrees of shading on Total Cross-Tied (TCT) photovoltaic array configuration

Available online at www.sciencedirect.com Available online at www.sciencedirect.com

ScienceDirect ScienceDirect

Energy Procedia 00 (2018) 000–000 Available online www.sciencedirect.com Available online atatwww.sciencedirect.com Energy Procedia 00 (2018) 000–000

ScienceDirect ScienceDirect

www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia

Energy Procedia Procedia 00 153(2017) (2018)000–000 35–41 Energy www.elsevier.com/locate/procedia

5th International Conference on Energy and Environment Research, ICEER 2018 5th International Conference on Energy and Environment Research, ICEER 2018

Effect of partial shading patterns and degrees of shading on Total Effect of partial shading patterns and degrees of shading on Total Cross-Tied (TCT) photovoltaic arrayHeating configuration The 15th International Symposium on District and Cooling Cross-Tied (TCT) photovoltaic array configuration a b Chayut Tubniyom ,Watcharin Jaideaw , Rongrit Chatthaworncc, Amnart Suksricc, Assessing the feasibility of a busing the heat demand-outdoor c,d, Chayut Tubniyom ,Watcharin Jaideaw , Rongrit Chatthaworn , Amnart Suksri , Tanakorn Wongwuttanasatian * c,d, heat demand forecast temperature function for a long-term district Tanakorn Wongwuttanasatian * a Postgraduate Student, Department of Electrical Engineering, Faculty of Engineering Khon Kaen University, Khonkaen, Thailand. Postgraduate Department Engineering, FacultyofofEngineering Engineering KhonKaen KaenUniversity, University, Khonkaen,Thailand. Thailand. PostgraduateStudent, Student, DepartmentofofMechanical Electrical Engineering, Khon a,b,c a a Faculty b c Khonkaen, c b Centre for AlternativeofEnergy Research and Development, Kaen University, Khonkaen, Thailand. PostgraduatecStudent, Department Mechanical Engineering, Faculty ofKhon Engineering Khon Kaen University, Khonkaen, Thailand. d c Associate Professor, Department of Mechanical Engineering, Faculty of Khon Engineering, Khon Kaen University, Khonkaen, Thailand. Centre for Alternative Energy Research and Development, Kaen University, Khonkaen, Thailand. a IN+ CenterProfessor, for Innovation, Technology and PolicyEngineering, Research - Instituto Superior Técnico, Av. Kaen Rovisco Pais 1, 1049-001 Lisbon, Portugal d Associate Department of Mechanical Faculty of Engineering, Khon University, Khonkaen, Thailand. b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France ba

I. Andrić

*, A. Pina , P. Ferrão , J. Fournier ., B. Lacarrière , O. Le Corre

Abstract Abstract Effect of partial shading on PV modules is simulated. Three standard configurations of PV array consisting of series-parallel (SP), Abstract Effect of partial shading on PV modules(TCT) is simulated. ThreeNine standard configurations of PV consisting of series-parallel (SP), bridge-linked (BL), and total cross-tied are studied. PV panels are arranged in array 3x3 array. The suitable solar radiation bridge-linked (BL), and total are studied. Nine PV panels are arranged in 3x3 array.of The solar radiation level to start reconfiguring thecross-tied PV array(TCT) according to shading pattern is investigated. Partial shading 1, 2suitable and 4 panels in 9 are District heating networks are commonly addressed in the literature as one of the most effective solutions for decreasing the level to start reconfiguring the PV arrayitaccording to shading pattern is investigated. Partial shading of 1,the 2 and 4 panels 9 are simulated. From the simulation results, is found that the reconfiguration of PV arrays may not increase power outputinhigher greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat simulated. Fromthere the simulation is found of PV arrays may not increase the power the output than 5% when are shadedresults, greaterit than 50%that of the the reconfiguration total area. Therefore, it is unnecessary to reconfigure PV higher array. sales. Due to the changed climate conditions and building renovation policies, heat demand in the future could decrease, than 5% when there are shaded thanreconfiguring 50% of the total area. Therefore, it is unnecessary to reconfigure the PVpatterns array. Conversely, if shaded area is lessgreater than 50% can improve the power output. Moreover, different shading prolonging the investment return period. Conversely, if shaded is less than 50%shaded reconfiguring improve power Moreover, different patterns provide different powerarea outputs even if the areas arecan equal and thethepoints to output. start reconfiguring the array shading are different for The main scope of this paper is to assess the feasibility of using the heat demand – outdoor temperature function for heat demand provide shading differentpatterns. power outputs even if the shaded areas are equal and the points to start reconfiguring the array are different for various forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 various shading patterns. buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district © 2018 The Authors. Published by Elsevier Ltd. renovation scenariosPublished were developed (shallow, © 2018 The The Authors. Authors. by Elsevier Elsevier Ltd. intermediate, deep). To estimate the error, obtained heat demand values were © 2018 by Ltd. This is an open accessPublished article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) This is an open the heat CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) compared with access results article from aunder dynamic demand model, previously developed and validated by the authors. This is an and openpeer-review access article underresponsibility the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection under of the scientific committee of 5th Conference on and Selection andshowed peer-review underonly responsibility of theis scientific committee of the theerror 5th International International Conference on Energy Energy and The results that when weather change considered, the margin of could be acceptable for some applications Selection and peer-review under responsibility of the scientific committee of the 5th International Conference on Energy and Environment Research, ICEER 2018. Environment ICEERwas 2018. (the error in Research, annual demand lower than 20% for all weather scenarios considered). However, after introducing renovation Environment Research, ICEER 2018. scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). Keywords: Solar reconfiguration; total cross-tied; bridge-linked; partial shading. The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the Keywords: Solar reconfiguration; total cross-tied; bridge-linked; partial shading. decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations. © 2017 The Authors. Published by Elsevier Ltd.

* Corresponding author. Tel.: +66-80-317-3170; fax: +66-43-202-849. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and E-mail address:author. [email protected] * Corresponding Tel.: +66-80-317-3170; fax: +66-43-202-849. Cooling. E-mail address: [email protected] 1876-6102 © 2018 The Authors. Published by Elsevier Ltd. Keywords: Heat demand; Forecast; Climate change This is an open access under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) 1876-6102 © 2018 Thearticle Authors. Published by Elsevier Ltd. Selection under responsibility of the scientific of the 5th International Conference on Energy and Environment This is an and openpeer-review access article under the CC BY-NC-ND licensecommittee (https://creativecommons.org/licenses/by-nc-nd/4.0/) Research, and ICEER 2018. under responsibility of the scientific committee of the 5th International Conference on Energy and Environment Selection peer-review Research, ICEER 2018. 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. 1876-6102 © 2018 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific committee of the 5th International Conference on Energy and Environment Research, ICEER 2018. 10.1016/j.egypro.2018.10.028

36 2

Chayut Tubniyom et al. / Energy Procedia 153 (2018) 35–41 Chayut Tubniyom et al. / Energy Procedia 00 (2018) 000–000

1. Introduction At present, electrical energy is vital for various human activities. The consumption of electrical energy is rapidly increasing while fossil fuel used for electricity generation is limited. Moreover, the emission from fossil fuel strongly causes the environmental problem. Therefore, renewable energy such as hydro energy, solar energy, and wind energy which are clean and no cost of resource are widely promoted for electricity generation, especially, solar energy. According to the statistical data of the Ministry of Energy, Thailand found that the potential of solar energy in Thailand is in a high level (4-5 kWh/m² per day) [1]. The solar energy can be utilized for electrical generation and thermal applications [2]. Nowadays, to generate electricity, the solar PV transforms solar energy into direct current of electricity. The PV material is composed of semiconductor which uses solar energy to stimulate electron transfer reaction in order to generate electricity [3]. Therefore, there is no emission during electricity generation process. However, there are many factors that affect to the solar PV power output such as solar radiation, temperature, solar incidence angle, dust, shade, etc. For the dust or shade, these cause the reduction of current and voltage of the affected panel. The panel that provides the minimum value of power will behave itself as an electrical load which consumes electricity from other panels. This will cause the reduction of total power output. Consequently, many studies aimed to solve this problem by using the method of reconfiguration on solar PV array. The solar PV array reconfiguration is well known and popular method to increase the power output and efficiency of electricity generation. The conventional configuration type of solar PV array can be classified into three types consisting of series-parallel (SP), bridge-linked (BL), and total cross-tied (TCT). For SP, the configuration of this type is the combination between series and parallel connection of each panel. For BL, the connection of each panel is nearly the same as SP configuration but the connections of some rows between each string will be added. Lastly, for TCT, the connection of each panel is nearly the same as BL but there are connections for all rows between each string. TCT is the most suitable for reducing operation loss when PV module is shaded [4]. In 2011, the configuration of PV module was studied by using 52 solar PV panels which were arranged in a thirteen by four. The efficiencies of three conventional configurations were tested. The results found that when some parts of solar PV module are shaded, the generated power will change depending on the number of shaded panels. From the results, SP can provide the highest efficiency when shaded area is low. However, TCT can provide the highest efficiency which is higher than SP by 5% when shaded area is high [5]. Moreover, the mathematical simulation of solar PV has been studied. It was created by the basic equations of solar PV to study the effect of the solar radiation, temperature, diode variables, series-parallel resistor on the power generation. The simulation is applied to the real commercial solar PV and the simulated results are compared with tested data. It was found that series- parallel resistance affects fill factor, variable diodes and temperature of the PV cells then disturbing the output voltage of the solar PV. The solar radiation also affects the output current of the solar PV [6]. In 2012, dynamic efficiency of solar PV was studied by using a four by four array with TCT configuration. In the shade condition, the solar PV with and without automatic array connecting system were compared. The result found that the efficiency of solar PV with automatic array connecting system is higher than 10% compared to the case without automatic array connecting system [7]. Furthermore, mathematical simulation of solar PV configuration was studied via PSIM®. Eight PV panels arranged in an array of four by two were tested. From the calculation of current in the PV simulation model, the result found that the calculation speed was high enough to accomplish for reconfiguration [8]. In 2013, the generation power of solar PV was studied by considering the maximum power points (MPP) of each solar PV panel. The three groups of configuration for testing were classified by using MPP of each solar PV panel as the criteria. For the group 1, all of the panels were configured by considering the real MPP values obtained from the test. For group 2, all of the panels were configured without considering the MPP values. Lastly, in the group 3, all of the panels were configured by considering the simulated MPP values using the parameters shown in the nameplate. From the test, it was found that the generated power obtained from the configured arrays according to the real MPP values of each solar PV panel was around 15% higher than that obtained from the configured arrays without MPP consideration [9]. In 2014, the shading effect of solar PV configuration was studied via Matlab/Simulink. 36 PV panels arranged in a six by six array were tested. The SP, BL, and TCT configurations were compared under some parts of solar PV module were shaded. The results found that TCT had the highest efficiency which was higher than other configurations approximately 5.84% [10]. In addition, the suitable reconfiguration of solar PV array in order to reduce the power loss caused by shade was studied. The four solar PV panels arranged in a 2 by 2 array and connected in SP were tested. The result from this study concluded that when



Chayut Tubniyom et al. / Energy Procedia 153 (2018) 35–41 Chayut Tubniyom et al. / Energy Procedia 00 (2018) 000–000

37 3

shaded panels were cut out from the circuit by using fuzzy logic controller, the power losses were decreased [11]. In 2015, array reconfiguration of 81 solar PV panels arranged in a 9 by 9 array and connected in TCT were studied using Matlab/Simulink. The solar radiations were varied from 200-900 W/m². Genetic algorithm (GA) was used to find the optimal reconfiguration for each shade to obtain the maximum power output. The study concluded that GA gave 34.96% higher power compared to fixed TCT configuration [12]. In 2016, the effect of shade on SP and TCT solar PV configuration was studied. 16 solar PV panels arranged in a 4 by 4 array were tested. The solar radiation was varied from 10-360 W/m2. This study found that efficiency of TCT was better than other configurations when partial shading was occurred [13]. Similarly, in 2017, partial shading on solar PV was studied. 16 solar PV panels arranged in a 4 by 4 array with solar radiation 400-1,000 W/m2 were simulated. The results found that efficiency of TCT was better than other configurations when partial shading was occurred [14]. Moreover, the SP, BL and TCT configurations of 3 by 3 solar PV panels when partial shaded were studied. The results found that BL delivered better power output at around 0.1-14% compared with SP. Also, TCT gave better power output around 2-20% compared with SP. Consequently, the efficiency of TCT was found to be better than other configurations when PV panels were partial shaded [15]. However, suitable solar radiation level to start reconfiguring the solar PV array has never been mentioned. Therefore, a point to start reconfiguring the solar PV array in order to obtain the maximum output power is investigated for each shading pattern in this work. The various shading patterns of 1 in 9 PV panels (11% shaded), 2 in 9 PV panels (22% shaded), 4 in 9 PV panels (44% shaded), and 6 in 9 PV panels (66% shaded) are utilized in the simulation. Total powers obtained from SP, BL and TCT configurations under different clouding conditions were compared to reach a highest power. 2. Research methodology 2.1 Configurations of PV module Reconfiguration of PV module can be classified into three standard configurations consisting of series-parallel (SP), bridge-linked (BL), and total cross-tied (TCT). For SP, it is the integration of series and parallel connections in one circuit. For BL, it is the circuit that includes the bridge connection into the circuit. Finally, TCT is the array connection similar to BL but each row of TCT are connected in order to distribute current when they are shaded. The examples of each configuration are shown in Fig. 1. This PV module consists of nine PV cells with rated total capacity of 180 W. The output power of SP type is used as a base line power for comparisons.

SP

BL

TCT

Fig. 1. Solar PV module configurations.

2.2 Shading patterns The shading patterns studied in this work are 1 in 9 PV panels (11% shaded), 2 in 9 PV panels (22% shaded), 4 in 9 PV panels (44% shaded), and 6 in 9 PV panels (66% shaded) as shown in Fig. 2. For the conditions of simulation, in normal case, the solar radiation is set to 1,000 W/m2 and the temperature is constantly set at 40 °C. In the case of partial shading on solar PV, the solar radiation drops from 900 W/m2 to 100 W/m2 respectively with the temperature of 40 °C as shown in Fig. 3. The solar radiation value that meets a 5% difference of output power for each shading condition will be considered as a point to start reconfiguring the solar PV array.

Tubniyom et al. / Procedia Energy Procedia 153 (2018) 35–41 Chayut Chayut Tubniyom et al. / Energy 00 (2018) 000–000

38 4

Case 1

Case 2

Case 3

Case 4

Case 5

Case 6

Case 7

Case 8

Fig. 2. Shading patterns on solar PV [15].

Fig. 3. Solar radiations drops when shading occurred on solar PV.

2.3 Model of 3x3 PV modules The model of PV modules using SP configuration is shown in Fig . 4. Matlab/Simulink© is used for simulation for different shading patterns. The BL and TCT configurations are similarly simulated. Each PV panel has characteristics listed in Table 1. Table 1. The characteristic of 20 W solar PV poly-crystalline type. Characteristics

Spec.

Maximum power (Pmax)

20W

Maximum power voltage (Vmax)

17.6V

Maximum power current (Imax)

1.14A

Open circuit voltage (Voc)

21.4V

Shot circuit current (Isc)

1.57A

Output tolerance (%)

±3%

Chayut Tubniyom et al. /etEnergy Procedia 00 (2018) 000–000 Chayut Tubniyom al. / Energy Procedia 153 (2018) 35–41



395

Fig. 4. SP configuration model of 3x3 solar PV array.

3. Results and discussions Simulation of solar PV array configurations were performed by Matlab/Simulink. The tests were classified into three configurations (SP, BL, and TCT) and each configuration was tested on eight shading patterns as shown in Fig. 2. In Case1, the solar radiation was initially set as 1,000 W/m2 for all panels with the temperature of 40 °C. In the case of shading on solar PV, the solar radiation dropped from 900 to 100 W/m2 with the temperature of 40 °C. For Case 2 where 1 of 9 panel was shaded, the obtained results revealed that at 900 W/m2, the output power delivered from SP configuration was decreased from 177.90 W to 174.60 W. Moreover, when solar radiation was decreased, the output power decreased accordingly. However, when the configuration changed from SP to BL, the output power was nevertheless decreased to 175.4 (0.46%) but less than that of SP. Also, when changing from SP to TCT, the output power was decreased less than that of SP at 175.6 (0.57%) as shown in Table 2. Table 2. Output powers from solar PV configurations when shaded in Case 2. Total Power (% difference) Solar Radiation (W/m 2)

SP (W)

BL (W)

TCT (W)

1000

177.90

177.9(0%)

177.9(0%)

900

174.60

175.4(0.46%)

175.6(0.57%)

800

168.80

171.2(1.42%)

171.8(1.78%)

700

162.50

165.9(2.09%)

167.1(2.83%)

600

155.00

160.0(3.23%)

161.8(4.39%)

500

146.80

153.6(4.63%)

156.1(6.34%)

400

137.90

146.8(6.45%)

150.2(8.92%)

300

128.60

139.8(8.71%)

144(11.98%)

200

118.80

132.4(11.45%)

137.5(15.74%)

100

110.00

124.7(13.36%)

130.8(18.91%)

0

110.00

116.8(6.18%)

123.9(12.64%)

From Table 2, it was found that when 1 in 9 panel was shaded and solar radiation was varied, the output power from SP was decreased. However, when changing SP to BL or TCT, the reductions of output powers were less than those of SP configuration. Thereby, when considering the reconfiguration that can increase the output power at 5%, it was found that the most suitable solar radiation for the purpose of reconfiguring on the solar PV array from SP to TCT must be less than or equal to 500 W/m2. Hence, if the solar radiation value is much higher than 500 W/m2, it is unnecessary to reconfigure the array because it can only provide less incremental on output power.

Chayut Tubniyom et al. / Energy Procedia 153 (2018) 35–41 Chayut Tubniyom et al. / Energy Procedia 00 (2018) 000–000

40 6

From the reconfiguration of solar PV array, it was found that TCT provided less decrease of output power compared with BL. Therefore, for the rest of other cases, the reconfiguration from SP to TCT was only considered. In addition, the degree of shading is also classified into three levels. They are light cloud (solar radiation at 900-700 W/m2), medium dark cloud (solar radiation at 600-400 W/m2) and dark cloud (solar radiation at 300-100 W/m2) as presented in Table 3. Table 3. The difference of output power from reconfiguring SP to TCT when there is shading on solar PV. Difference power ( Case2

Case3

Case4

SP

)

Case5

Case6

Case7

Case8

1000

0%

0%

0%

0%

0%

0%

0%

0%

Medium Light cloud dark cloud

Case1

TCT-SP

900

0%

0.57%

0.35%

0.53%

0.36%

1.63%

0%

0%

800

0%

1.78%

1.14%

1.44%

0.79%

4.62%

0%

0%

700

0%

2.83%

1.70%

2.87%

1.46%

9.13%

0%

0%

600

0%

4.39%

1.99%

5.02%

2.16%

16.13%

0%

0%

500

0%

6.34%

2.67%

7.94%

3.26%

18.00%

0%

0%

400

0%

8.92%

3.52%

11.97%

4.64%

3.38%

0%

0%

Dark cloud

Solar radiation (W/m²)

300

0%

11.98%

4.41%

-2.09%

6.51%

-11.34%

0%

0%

200

0%

15.74%

5.52%

-5.47%

14.33%

-25.23%

0%

0%

100

0%

18.91%

6.82%

-5.70%

12.84%

-40.32%

0%

0%

From Table 3, in the Case 3 and 4 when 2 in 9 panels were shaded, the two shaded panels were on the same string in Case 3 and on the different strings in Case 4. The results showed that the suitable solar radiation for reconfiguring solar PV from SP to TCT in Case 3 was less than 200 W/m2 and in Case 4 was less than 600 W/m2. In the Case 5 and 6, there were four shaded panels for both cases. The four shaded panels were located on two strings, and each string had two shaded panels for Case 5. Whereas, in Case 6, the four shaded panels were located on three strings seen in Fig. 2. The results showed that the suitable solar radiation for reconfiguring solar PV from SP to TCT for the Case 5 was less than 300 W/m2 and less than 700 W/m2 for Case 6. In the Case 7 and 8, there were six shaded panels for both cases. In Case 7, the six shaded panels were located on two strings and each string had three shaded panels. Also, in Case 8, the six shaded panels were located on three strings and each string had two shaded panels. The results show that there was no need to reconfigure for both cases because the differences were zero for all levels. It can be seen from the results that, even if shaded area of solar PV module was equal, the suitable solar radiations for reconfiguring solar PV array varied. It was because the number of shaded panels on the same string affected the greater decrease of output power compared with the shaded panels on many strings. In addition, when shading occurred greater than or equal to 50% of the total area of solar PV module, there was no difference of output power for all levels. Therefore, it is necessary to reconfigure the solar PV array when shading area is less than half of total area. 4. Conclusion The simulation of 3x3 solar PV modules under various shading patterns with degrees of shading are performed based on Matlab/Simulink. The three standard configurations of solar PV array consisting of series-parallel (SP), bridge-linked (BL), and total cross-tied (TCT) are studied .In addition, the suitable solar radiation level to start reconfiguring solar PV array is also determined. The shading patterns 1 in 9 PV panels (11% shaded), 2 in 9 PV panels (22% shaded), 4 in 9 PV panels (44% shaded), and 6 in 9 PV panels (66% shaded) are utilized in the simulations. It is found from the simulation results that when shading has occurred greater than or equal to 50% of the total area of solar PV module, the reconfiguration of solar PV arrays cannot increase the power output higher than 5%. Therefore, it is unnecessary to reconfigure the solar PV array. As for cases of shaded area less than 50% of the total



Chayut Tubniyom et al. / Energy Procedia 153 (2018) 35–41 Chayut Tubniyom et al. / Energy Procedia 00 (2018) 000–000

41 7

area, it is much more suitable to reconfigure the solar PV array. Moreover, when shaded area of solar PV module is equal but in different patterns, the suitable solar radiations for reconfiguring solar PV array are not the same values because the number of shaded panels on the same string affect greater decreases of output power when compared with the shaded panels on several strings. Acknowledgements The authors would like to express gratitude to national research council of Thailand (NRCT), grand challenges Thailand funding, an improvement on solar generation efficiency via automatic photovoltaic array reconfiguration. Appreciation also goes to centre of alternative energy research and development (AERD). Lastly, the authors gratefully acknowledge the department of electrical engineering, and the energy engineering, department of mechanical engineering, faculty of engineering, Khon Kaen University, Thailand. References [1] Department of Alternative Energy Development and Efficiency. “Solar Radiation.” 2015. http://www.dede.go.th. [2] Department of Alternative Energy Development and Efficiency. “Technology of solar cell.” 2015. http://www.dede.go.th. [3] Electricity Generating Authority of Thailand. “Solar cell.” 2015. http://www3.egat.co.th/re/solarcell/solarcell_pg5.htm. [4] P. Srinivasa Rao, G. Saravana Ilango, Chilakapati Nagamani. “Maximum Power from PV Arrays Using a Fixed Configuration Under Different Shading Conditions,” IEEE Journal of Photovoltaics, 4(2) (2014) [5] S. T. Buddha, “Topology reconfiguration to improve the photovoltaic (PV) array performance,” Master of Science thesis, Arizona State University, (2011) [6] Datnititorn Impreeda, Wanchai Subsingha, “Real- time Simulation with MATLAB/Simulink Photovoltaic Module,” The 4th Thailand Renewable Energy for Community Conference 4 (2011): 37-44. [7] Jonathan P. Storey, Peter R. Wilson, Darren Bagnall. “Improved Optimization Strategy for Irradiance Equalization in Dynamic Photovoltaic Arrays,” IEEE Trans. Power Electronics, 28(6) (2012): 2946-2956 [8] C.A. Ramos-Paja, J.D. Bastidas, A.J. Saavedra-Montes, F. Guinjoan-Gispert, “Mathematical Model of Total Cross-Tied Photovoltaic Arrays in Mismatching Conditions,” IEEE CWCAS , (2012) [9] Srisin Dantrakul, Harnpon Phungrassami, Phairat Usubharatana, “A Study of the Maximum Power Point of the Photovoltaic Array for Optimization to the Solar Power Plant,” The 6th National Conference on Technical Education, NCTechEd06TEE07 (2013): 38-44. [10] Moein Jazayeri, Sener Uysal, Kian Jazayeri. “Comparative Study on Different Photovoltaic Array Topologies under Partial Shading Conditions,” IEEE PES T&D Conference and Exposition, (2014) [11] A. Tabanjat, M. Becherif, and D. Hissel, “Reconfiguration solution for shaded PV panels using switching control,” Renewable Energy, 82 (2015): 4–13. [12] S. N. Deshkar, S. B. Dhale, J. S. Mukherjee, T. S. Babu, and N. Rajasekar, “Solar PV array reconfiguration under partial shading conditions for maximum power extraction using genetic algorithm,” Renewable and Sustainable Energy Reviews, 43 (2015): 102–110. [13] A. Kumar, R. K. Pachauri, and Y. K. Chauhan, “Experimental Analysis of SP/TCT PV Array Configurations under Partial Shading Conditions,” ICPEICES, 2 (2016) [14] P. Das, A. Mohapatra, and B. Nayak, “Modeling and characteristic study of solar photovoltaic system under partial shading condition,” Mater. Today Proc, 4(14) (2017): 12586–12591. [15] Watcharin Jaideaw, Amnart Suksri, Tanakorn Wongwuttanasatian, “Simulation of photovoltaic module configuration for different shaded patterns,” IOP Conf. Series: Earth and Environmental Science, 113 (2018)