# Performance Enhancement of a Partially Shaded Photovoltaic Array by Optimal Reconfiguration and Current Injection Schemes

^{1}

^{2}

^{3}

^{4}

^{*}

## Abstract

**:**

## 1. Introduction

## 2. PV Model and Impact of Partial Shading

#### 2.1. PV Model

_{ph}), a diode in anti-parallel, series resistance (R

_{s}), and parallel resistance (R

_{sh}).

_{PV}) is obtained through Kirchhoff’s current law, which is given below

_{ph}, the nonlinearity of the diode is given by I

_{D}, and the current flowing through the shunt resistor is given by I

_{sh.}

_{D}and I

_{sh}in Equation (1), I

_{PV}is given in Equation (2)

_{O}is the saturation current of the diode, $\mathsf{\eta}$ is the ideality constant, q is the electron charge (1.602 × 10

^{−19}C), k is the Boltzmann constant (1.3806503 × 10

^{−23}J/K), T is the cell temperature, and V

_{PV}is the voltage generated by the PV cell for the irradiation.

_{S}) and parallel-connected modules (N

_{P}) as shown in Figure 3.

_{PV}is shown in terms of the PV array in Equation (3).

^{2}and 25

^{o}C.

#### 2.2. Partial Shading and Its Effects

## 3. Optimal Reconfiguration and Proposed Half-Bridge Current Injection Scheme

#### 3.1. Optimal Reconfiguration

#### 3.2. Implementation of the HBCI Scheme

- Step 1: Measure the current and voltage from the 4 × 4 SP array and calculate the power of the PV array as shown in Figure 7a. If power is reduced, then
- Step 2: Calculate the column current of each PV string.
- Step 3: Identify the columns that have the highest and lowest currents.
- Step 4: Each of the strings is subdivided into two parts and the whole array is divided into eight parts as shown in Figure 7b.
- Step 5: Swap the panels with lower current with the panels with higher current in any of the columns shown in Figure 7c. Repeat the second and third steps.

_{k}refers to the no of converters.

#### 3.3. Performance Evaluation Parameters

#### 3.3.1. Mismatching Power Loss (ΔP_{L})

_{mp}denotes the maximum power under homogeneous irradiation conditions and P

_{sc}denotes the maximum power under partial shading conditions.

#### 3.3.2. Fill Factor (FF)

_{oc}is the open circuit voltage, I

_{sc}is the short circuit current, V

_{mp}is the voltage during the peak output power, and I

_{mp}is the current during the peak output power.

#### 3.3.3. Efficiency (η)

_{si}is the solar intensity per square meter (watt/m

^{2}) and A

_{pv}is the area of the PV system (m

^{2}).

## 4. Results and Discussions

#### 4.1. Case 1: Single-Panel Shading

^{2}, and the remaining 0.4 kW/m

^{2}is lost due to shading. This case is clearly presented in Figure 9a. Here, the optimal reconfiguration scheme would not hold, so a current injection through the HBCI technique was performed as shown in Figure 9c. It is worth noting that, due to the single-panel shading, the PV array was able to feed only 2807 W and, after the current injection, the power output increased to 3199 W. Therefore, nearly 392 W of power had been yielded at the cost of injecting 28 W of power from the half-bridge circuit. Figure 9d shows that the HBCI technique has a clear edge over all other techniques by presenting a P-V curve with more power and, more importantly, a single power peak. Under similar shading conditions, the other array configurations (SP, BL, HC, and TCT) possess more bumps in the power curve with a lower global power peak. Furthermore, a detailed analysis of the parameters of the PV array was performed and is presented in Table 2. The inference from the table is that the proposed scheme outperforms all its counterparts by having less power loss, higher efficiency, and a higher fill factor. It is evident that the HBCI reconfiguration scheme improves the power output and reduces the power losses by 12.22%, 10.30%, 11.86%, and 9.32% with respect to the four conventional configurations SP, BL, HC, and TCT, respectively. Similarly, the fill factor was improved by 9.03%, 7.60%, 8.76%, and 6.87%, respectively, compared with the conventional configurations. Again, the efficiency of the proposed scheme is higher than that of the four configurations by 1.73%, 1.46%, 1.68%, and 1.32%, respectively.

#### 4.2. Case 2: Corner Shading

^{2}, PV5 and PV6 receive 0.5 kW/m

^{2}, and PV9 and PV10 receive only 0.3 kW/m

^{2}. All the other panels receive uniform irradiation of 1kW/m

^{2}as illustrated in Figure 10a. Since the panels in an array receive different irradiation levels, the existence of multiple peaks on the P-V output curves is unavoidable. In addition, the power at the output reduces substantially due to shading; suppose that column 1 and column 2 exert the lowest current of 4.088 amps and column 3 and column 4 receive 7.61 amps of current. Therefore, optimal reconfiguration was performed by bifurcating the columns and swapping the panels between the fourth column and the first column. Additionally, the panels in the second and third strings are exchanged as shown in Figure 10b. At the end of this swapping procedure, it was observed that two columns (columns 1 and 3) had the highest current value (6.138 amps) and the other two columns (columns 2 and 4) had the lowest current value (4.857 amps). There exists a current difference even after reconfiguration was completed. Therefore, the intervention of HBCI was required and a deficit current of 2.562 A was injected into column 2 and column 4 as shown in Figure 10c. As a result, the power output was increased from 1970 W to 2536 W. The estimated global maximum power point was also validated by plotting the simulated PV characteristics and is shown in Figure 10d. Under similar shading conditions, the other array configurations (SP, BL, HC, and TCT) are also plotted. Furthermore, the parameters V

_{oc}, V

_{mp}, I

_{sc}, I

_{mp}, and P

_{mp}were analyzed and are presented in Table 3. It is understood that the HBCI reconfiguration scheme improves the power output by 22.3%, 24.4%, 23.3%, and 25.9% over the conventional schemes, respectively. The power losses by SP, BL, HC, and TCT account for nearly 17.69%, 19.38%, 18.51%, and 20.60% more than that by HBCI. Again, the HBCI scheme improves the fill factor by 25.77%, 27.04%, 26.38%, and 27.99% and improves the efficiency by 2.51%, 2.75%, 2.62%, and 2.92% compared with the SP, BL, HC, and TCT array configurations, respectively. The table also reveals the edge that HBCI has compared with other reconfiguration schemes in terms of fill factor and efficiency.

#### 4.3. Case 3: Long and Wide Shading

^{2}, PV3 and PV7 received 0.4 kW/m

^{2}, PV9 and PV10 received 0.5 kW/m

^{2}, PV13 and PV14 received 0.6 kW/m

^{2}, and PV11 and PV15 received 0.7 kW/m

^{2}. All the other panels received 1000 W/m

^{2}. Due to the various levels of insolation, multiple peaks occurred in the PV curve and the power output was reduced. Column 1 and column 2 received the lowest current value (3.788 amps), column 3 received 4.055 amps, and column 4 received 7.61 amps. Therefore, the optimal reconfiguration procedure was adopted by bifurcation of the columns and some of the panels were swapped between column 2 and column 4. The second column had a higher current (4.857 amps) and the other three columns had lower currents (3.788 amps, 4.055 amps, and 4.139 amps) as shown in Figure 11b. The affected columns were injected with current by using the HBCI converters to inject a sufficient amount of current (2.539 amps) as shown in Figure 11c. This helped to achieve the maximum output power in the array from 973 W to 2282 W as shown in Figure 11d. It is evident that the HBCI reconfiguration scheme improves the power output by 57.3%, 57.9%, 57.3%, and 59.2%, reduces the power losses by 40.93%, 41.37%, 40.94%, and 42.30%, improves the fill factor by 37.16%, 37.63%, 37.17%, and 38.61%, and improves the efficiency by 5.81%, 5.87%, 5.81%, and 6.00% compared with the SP, BL, HC, and TCT array configurations, respectively. Again, a comparative analysis shows that HBCI performs better than the other conventional reconfiguration schemes (Table 4).

#### 4.4. Case 4: Random Shading

^{2}, PV9 and PV10 received 0.8 kW/m

^{2}, PV5, PV11, and PV12 received 0.7 kW/m

^{2}, PV4 received 0.7 kW/m

^{2}, and all other panels received 1 kW/m

^{2}as shown in Figure 12a. The existence of multiple power peaks and power losses are inevitable. The shading pattern was arranged in such a way that column 2 had the highest current (6.787 amps) and column 1, column 3, and column 4 had low current values (5.832 amps, 6.044 amps, and 5.102 amps, respectively). The reconfiguration and current injection schemes were systematically applied and the results are duly presented in Figure 12b,c. With the help of the half-bridge-driven buck converter circuit, the required amount of current (1.761 amps) was injected and the output power after the injection of current increased from 2028 W to 2810 W. Excluding the converter losses of 36 W, the net array output power amounts to 2774 W. The estimated global maximum power point was validated by plotting the simulated PV characteristics and is shown in Figure 12d. Under similar shading conditions, the other array configurations (SP, BL, HC, and TCT) are also plotted. Furthermore, the parameters V

_{oc}, V

_{mp}, I

_{sc}, I

_{mp}, and P

_{mp}were calculated and are displayed in Table 5. It is evident that the HBCI reconfiguration scheme improves the power output by 27.8%, 29.1%, 27.9%, and 25.8%, reduces the power losses by 24.45%, 25.57%, 24.56%, and 22.73%, improves the fill factor by 25.34%, 25.01%, 25.42%, and 21.37%, and improves the efficiency by 3.46%, 3.63%, 3.48%, and 3.22% compared with the SP, BL, HC, and TCT array configurations, respectively.

#### 4.5. Comparison of the Cases

#### 4.6. Cost–Benefit Analysis

## 5. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

- Bastidas-Rodriguez, J.D.; Cruz-Duarte, J.M.; Correa, R. Mismatched Series–Parallel Photovoltaic Generator Modeling: An Implicit Current–Voltage Approach. IEEE J. Photovolta.
**2019**, 9, 768–774. [Google Scholar] [CrossRef] - Maki, A.; Valkealahti, S. Effect of Photovoltaic Generator Components on the Number of MPPs under Partial Shading Conditions. IEEE Trans. Energy Convers.
**2013**, 28, 1008–1017. [Google Scholar] [CrossRef] - Ali, A.; Almutairi, K.; Padmanaban, S.; Tirth, V.; Algarni, S.; Irshad, K.; Islam, S.; Zahir, M.H.; Shafiullah, M.; Malik, M.Z. Investigation of MPPT Techniques Under Uniform and Non-Uniform Solar Irradiation Condition—A Retrospection. IEEE Acces
**2020**, 8, 127368–127392. [Google Scholar] [CrossRef] - Wang, S.-C.; Pai, H.-Y.; Chen, G.-J.; Liu, Y.-H. A Fast and Efficient Maximum Power Tracking Combining Simplified State Estimation with Adaptive Perturb and Observe. IEEE Access
**2020**, 8, 155319–155328. [Google Scholar] [CrossRef] - Li, S.; Li, F.; Zheng, J.; Chen, W.; Zhang, D. An improved MPPT control strategy based on incremental conductance method. Soft Comput.
**2020**, 24, 6039–6046. [Google Scholar] [CrossRef] - Deshmukh, N.R. Comparision of Perturb and Observer and Incremental Conductance MPPT Based Solar Tracking System. Int. J. Eng. Res.
**2015**, 4, 222–223. [Google Scholar] [CrossRef] - Li, H.; Yang, D.; Su, W.; Lu, J.; Yu, X. An Overall Distribution Particle Swarm Optimization MPPT Algorithm for Photovoltaic System under Partial Shading. IEEE Trans. Ind. Electron.
**2019**, 66, 265–275. [Google Scholar] [CrossRef] - Manickam, C.; Raman, G.; Ganesan, S.I.; Nagamani, C. A Hybrid Algorithm for Tracking of GMPP Based on P&O and PSO with Reduced Power Oscillation in String Inverters. IEEE Trans. Ind. Electron.
**2016**, 63, 6097–6106. [Google Scholar] [CrossRef] - Tey, K.S.; Mekhilef, S.; Seyedmahmoudian, M.; Horan, B.; Oo, A.T.; Stojcevski, A. Improved Differential Evolution-Based MPPT Algorithm Using SEPIC for PV Systems Under Partial Shading Conditions and Load Variation. IEEE Trans. Ind. Inform.
**2018**, 14, 4322–4333. [Google Scholar] [CrossRef] - Ramasamy, S.; Dash, S.S.; Selvan, T. An Intelligent Differential Evolution based Maximum Power Point Tracking (MPPT) Technique for Partially Shaded Photo Voltaic (PV) Array. Int. J. Adv. Soft Comput. Appl.
**2014**, 6, 1–16. [Google Scholar] - Titri, S.; Larbes, C.; Toumi, K.Y.; Benatchba, K. A new MPPT controller based on the Ant colony optimization algorithm for Photovoltaic systems under partial shading conditions. Appl. Soft Comput.
**2017**, 58, 465–479. [Google Scholar] [CrossRef] - Sridhar, R.; Jeevananthan, S.; Dash, S.S.; Vishnuram, P. A new maximum power tracking in PV system during partially shaded conditions based on shuffled frog leap algorithm. J. Exp. Theor. Artif. Intell.
**2016**, 29, 481–493. [Google Scholar] [CrossRef] - Arulmurugan, R. Optimization of Perturb and Observe Based Fuzzy Logic MPPT Controller for Independent PV Solar System. WSEAS Trans. Power Syst.
**2020**, 19, 159–167. [Google Scholar] [CrossRef] - Rahman, M.M.; Islam, M.S. PSO and ANN Based Hybrid MPPT Algorithm for Photovoltaic Array under Partial Shading Condition. Eng. Int.
**2020**, 8, 9–24. [Google Scholar] [CrossRef] - Ulaganathan, M.; Devaraj, D. A novel MPPT controller using Neural Network and Gain-Scheduled PI for Solar PV system under rapidly varying environmental condition. J. Intell. Fuzzy Syst.
**2019**, 37, 1085–1098. [Google Scholar] [CrossRef] - Manjunath Suresh, H.N.; Rajanna, S. Performance Enhancement of Hybrid Interconnected Solar Photovoltaic Array Using Shade Dispersion Magic Square Puzzle Pattern Technique under Partial Shading Conditions. Sol. Energy
**2019**, 194, 602–617. [Google Scholar] [CrossRef] - Deng, S.; Zhang, Z.; Ju, C.; Dong, J.; Xia, Z.; Yan, X.; Xu, T.; Xing, G. Research on hot spot risk for high-efficiency solar module. Energy Procedia
**2017**, 130, 77–86. [Google Scholar] [CrossRef] - Venkateswari, R.; Sreejith, S. Factors influencing the efficiency of photovoltaic system. Renew. Sustain. Energy Rev.
**2019**, 101, 376–394. [Google Scholar] [CrossRef] - Bingöl, O.; Özkaya, B. Analysis and comparison of different PV array configurations under partial shading conditions. Sol. Energy
**2018**, 160, 336–343. [Google Scholar] [CrossRef] - Sai Krishna, G.; Moger, T. Improved SuDoKu Reconfiguration Technique for Total-Cross-Tied PV Array to Enhance Maximum Power Under Partial Shading Conditions. Renew. Sustain. Energy Rev.
**2019**, 109, 333–348. [Google Scholar] [CrossRef] - Bonthagorla, P.K.; Mikkili, S. Performance investigation of hybrid and conventional PV array configurations for grid-connected/standalone PV systems. CSEE J. Power Energy Syst.
**2020**. [Google Scholar] [CrossRef] - Karmakar, B.K.; Karmakar, G. A Current Supported PV Array Reconfiguration Technique to Mitigate Partial Shading. IEEE Trans. Sustain. Energy
**2021**, 12, 1449–1460. [Google Scholar] [CrossRef] - Alkahtani, M.; Wu, Z.; Kuka, C.S.; Alahammad, M.S.; Ni, K. A Novel PV Array Reconfiguration Algorithm Approach to Optimising Power Generation Across Non-Uniformly Aged PV Arrays by Merely Repositioning. Multidiscip. Sci. J.
**2020**, 3, 5. [Google Scholar] [CrossRef] [Green Version] - Bendary, A.; Abdelaziz, A.; Ismail, M.; Mahmoud, K.; Lehtonen, M.; Darwish, M. Proposed ANFIS Based Approach for Fault Tracking, Detection, Clearing and Rearrangement for Photovoltaic System. Sensors
**2021**, 21, 2269. [Google Scholar] [CrossRef] - Prince Winston, D.; Kumaravel, S.; Praveen Kumar, B.; Devakirubakaran, S. Performance Improvement of Solar PV Array Topologies during Various Partial Shading Conditions. Sol. Energy
**2020**, 196, 228–242. [Google Scholar] [CrossRef] - Keerti, Y.; Anuprita, M. Analysis and Modeling of Photo-Voltaic (PV) Cell Power Generation System Using Simulink. Int. J. Recent Trends Eng. Res.
**2018**, 4, 128–135. [Google Scholar] - Sharma, H.; Kumar, P.; Patra, J. Performance Analysis of Different PV Topologies with MPPT. Int. J. Trend Sci. Res. Dev.
**2017**, 1, 656–664. [Google Scholar] [CrossRef] - Said, M.; Shaheen, A.M.; Ginidi, A.R.; Sehiemy, R.A.E.; Mahmoud, K.; Lehtonen, M.; Darwish, M.M.F. Estimating Parameters of Photovoltaic Models Using Accurate Turbulent Flow of Water Optimizer. Processes
**2021**, 9, 627. [Google Scholar] [CrossRef] - Naeijian, M.; Rahimnejad, A.; Ebrahimi, S.M.; Pourmousa, N.; Gadsden, S.A. Parameter estimation of PV solar cells and modules using Whippy Harris Hawks Optimization Algorithm. Energy Rep.
**2021**, 7, 4047–4063. [Google Scholar] [CrossRef]

**Figure 1.**Different PV array configurations: (

**a**) series parallel; (

**b**) bridge link; (

**c**) honeycomb; (

**d**) total cross tied.

**Figure 4.**(

**a**) Shaded SP PV array; (

**b**) PV curve for uniform irradiation; (

**c**) PV curve for nonuniform irradiation.

**Figure 5.**(

**a**) Optimal reconfiguration scheme for a shaded PV array; (

**b**) Half-Bridge Current Injection (HBCI) scheme.

**Figure 7.**(

**a**) The 4 × 4 SP PV array; (

**b**) the switching matrix-based PV array; (

**c**) rearranging the PV array; (

**d**) after reconfiguration; (

**e**) reconfiguration with Half-Bridge Current Injection (HBCI).

**Figure 9.**Case 1: single-panel shading: (

**a**) the SP array configuration; (

**b**) after reconfiguration with HBCI; (

**c**) reconfiguration with HBCI; (

**d**) PV characteristics.

**Figure 10.**Case 2: corner shading: (

**a**) the SP array configuration; (

**b**) after reconfiguration with HBCI; (

**c**) reconfiguration with HBCI; (

**d**) PV characteristics.

**Figure 11.**Case 3: long and wide shading: (

**a**) the SP array configuration; (

**b**) after reconfiguration with HBCI; (

**c**) reconfiguration with HBCI; (

**d**) PV characteristics.

**Figure 12.**Case 4: random shading: (

**a**) the SP array configuration; (

**b**) after reconfiguration with HBCI; (

**c**) reconfiguration with HBCI; (

**d**) PV characteristics.

**Figure 13.**HBCI power output and power consumption during the injection of current for the shading cases (Note: the different schemes have a 2 s gap).

**Figure 14.**Net power gain by the proposed reconfiguration and the HBCI scheme compared to the traditional schemes (SP, series parallel; BL, bridge link; HC, honeycomb; TCT, total cross tied) for different cases (single panel, corner, long and wide, random) of PV array shading (net power gain = HBCI power output-power output by a traditional scheme-HBCI power consumption).

**Table 1.**Specifications for a KyoceraKC200GT 200 W panel (electrical performance under Standard Test Conditions (STCs)).

Specification Parameters | Values |
---|---|

Maximum Power (P_{max}) | 200.143 W |

Maximum Power Voltage (V_{mp}) | 26.3 V |

Maximum Power Current (I_{mp}) | 7.61 A |

Open Circuit Voltage (V_{oc}) | 32.9 V |

Short Circuit Current (I_{sc}) | 8.21 A |

Temperature Coefficient of V_{oc} | −0.1230 V/K |

Temperature Coefficient of I_{sc} | 0.0032 A/K |

Number of Series-Connected Cells in the Module | 54 |

Configuration | V_{oc} (V) | I_{sc} (A) | V_{mp} (V) | I_{mp} (A) | P_{mp} (W) | ∆P_{L} (%) | FF (%) | η (%) |
---|---|---|---|---|---|---|---|---|

Series Parallel (SP) | 131.3 | 32.8 | 98.49 | 28.51 | 2807.95 | 12.25 | 65.20 | 12.45 |

Bridge link (BL) | 131.3 | 32.8 | 99.57 | 28.82 | 2869.607 | 10.32 | 66.63 | 12.72 |

Honeycomb (HC) | 131.3 | 32.8 | 98.69 | 28.57 | 2819.573 | 11.89 | 65.47 | 12.50 |

Total Cross Tied (TCT) | 131.3 | 32.8 | 100.1 | 28.98 | 2900.898 | 9.35 | 67.36 | 12.86 |

HBCI | 131.4 | 32.8 | 105.2 | 30.41 | 3199.132 | 0.03 | 74.23 | 14.18 |

Configuration | V_{oc} (V) | I_{sc} (A) | V_{mp} (V) | I_{mp} (A) | P_{mp} (W) | ∆P_{L} (%) | FF (%) | η (%) |
---|---|---|---|---|---|---|---|---|

Series parallel (SP) | 129.9 | 32.7 | 82.5 | 23.88 | 1970.1 | 38.43 | 46.38 | 8.73 |

Bridge link (BL) | 129.9 | 32.7 | 81.36 | 23.55 | 1916.028 | 40.12 | 45.11 | 8.49 |

Honeycomb (HC) | 129.9 | 32.7 | 81.96 | 23.72 | 1944.091 | 39.25 | 45.77 | 8.62 |

Total cross tied (TCT) | 130 | 32.7 | 80.53 | 23.31 | 1877.154 | 41.34 | 44.16 | 8.32 |

HBCI | 130.2 | 27 | 99.86 | 25.4 | 2536.444 | 20.74 | 72.15 | 11.24 |

Configuration | V_{oc} (V) | I_{sc} (A) | V_{mp} (V) | I_{mp} (A) | P_{mp} (W) | ∆P_{L} (%) | FF (%) | η (%) |
---|---|---|---|---|---|---|---|---|

Series parallel (SP) | 128.2 | 23.7 | 57.99 | 16.78 | 973.0722 | 69.59 | 32.03 | 4.31 |

Bridge link (BL) | 128.2 | 23.7 | 57.56 | 16.66 | 958.9496 | 70.03 | 31.56 | 4.25 |

Honeycomb (HC) | 128.2 | 23.7 | 57.98 | 16.78 | 972.9044 | 69.60 | 32.02 | 4.31 |

Total cross tied (TCT) | 128.2 | 23.7 | 56.66 | 16.4 | 929.224 | 70.96 | 30.58 | 4.12 |

HBCI | 129.9 | 25.4 | 92.12 | 24.78 | 2282.734 | 28.66 | 69.19 | 10.12 |

Configuration | V_{oc} (V) | I_{sc} (A) | V_{mp} (V) | I_{mp} (A) | P_{mp} (W) | ∆P_{L} (%) | FF (%) | η (%) |
---|---|---|---|---|---|---|---|---|

Series parallel (SP) | 130.6 | 32.7 | 83.72 | 24.23 | 2028.536 | 36.61 | 47.50 | 9.00 |

Bridge link (BL) | 130.6 | 31.9 | 82.34 | 24.2 | 1992.628 | 37.73 | 47.83 | 8.83 |

Honeycomb (HC) | 130.6 | 32.7 | 83.64 | 24.21 | 2024.924 | 36.72 | 47.42 | 8.98 |

Total cross tied (TCT) | 130.6 | 31 | 84.84 | 24.56 | 2083.67 | 34.89 | 51.47 | 9.24 |

HBCI | 130.8 | 29.5 | 99.04 | 28.38 | 2810.755 | 12.16 | 72.84 | 12.46 |

Cases | MPPT without HBCI | MPPT with HBCI |
---|---|---|

Case 1 | 2807.95 W | 3199.13 W |

Case 2 | 1877.15 W | 2536.44 W |

Case 3 | 929.22 W | 2282.73 W |

Case 4 | 1992.62 W | 2810.75 W |

Total | 7606.94 | 10,829.05 |

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Vadivel, S.; Boopthi, C.S.; Ramasamy, S.; Ahsan, M.; Haider, J.; Rodrigues, E.M.G.
Performance Enhancement of a Partially Shaded Photovoltaic Array by Optimal Reconfiguration and Current Injection Schemes. *Energies* **2021**, *14*, 6332.
https://doi.org/10.3390/en14196332

**AMA Style**

Vadivel S, Boopthi CS, Ramasamy S, Ahsan M, Haider J, Rodrigues EMG.
Performance Enhancement of a Partially Shaded Photovoltaic Array by Optimal Reconfiguration and Current Injection Schemes. *Energies*. 2021; 14(19):6332.
https://doi.org/10.3390/en14196332

**Chicago/Turabian Style**

Vadivel, Srinivasan, C. S. Boopthi, Sridhar Ramasamy, Mominul Ahsan, Julfikar Haider, and Eduardo M. G. Rodrigues.
2021. "Performance Enhancement of a Partially Shaded Photovoltaic Array by Optimal Reconfiguration and Current Injection Schemes" *Energies* 14, no. 19: 6332.
https://doi.org/10.3390/en14196332