Optimal photovoltaic array reconfiguration for alleviating the partial shading influence based on a modified harris hawks optimizer

Large-scale solar photovoltaic (PV) plants play an essential role in providing the increasing demand for energy in recent time. Therefore, in the purpose of achieving the highest harvested power under the partial shading conditions as well as protecting the PV array from the hot-spot calamity, the PV reconfiguration strategy is established as an efficient procedure. This is performed by redistribution of PV modules according to their levels of shading. Motivated by this, the authors in this article have introduced a novel population-based algorithm that is known as marine predators algorithm (MPA) to restructure the PV array dynamically. Moreover, a novel objective function is introduced to enhance the algorithm performance rather than utilizing the regular weighted objective function in the literature. The effectiveness of the proposed algorithms based on the novel objective function is evaluated using several metrics such as fill factor, mismatch losses, percentage of power loss, and percentage of power enhancement. Besides, the obtained results are compared with a regular total-cross-tied (TCT) connection, manta ray foraging optimization (MRFO), harris hawk optimizer (HHO) and particle swarm optimizer (PSO) based reconfiguration techniques. Furthermore, to demonstrate the suitability of the proposed methods, large scale PV arrays of $16\times16$ and $25\times25$ are considered and evaluated. The results reveal that MPA enhanced the PV array power by percentage of 28.6 %, 2.7 % and 5.7 % in cases of $9\times9$ , $16\times16$ and $25\times25$ PV arrays, respectively. The comprehensive comparisons endorse that MPA shows a successful shade dispersion; hence the number of multiple peaks in the PV characteristics has reduced, and high values of power have been harvested with least mean execution time in comparison with PSO, HHO and MRFO. Moreover, the Wilcoxon signed-rank test has been accomplished to confirm the reliability and applicability of the proposed approach for the PV large scale arrays as well.

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A Robust Strategy Based on Marine Predators Algorithm for Large Scale Photovoltaic Array Reconfiguration to Mitigate the Partial Shading Effect on the Performance of PV System

Power enhancement of PV system via physical array reconfiguration based Lo Shu technique

A novel objective function with artificial ecosystem-based optimization for relieving the mismatching power loss of large-scale photovoltaic array

Massive infiltration of photovoltaic (PV) systems into electric supply networks creates numerous challenges in the present era, as the PV systems become an alternative to non-renewable energy resources. Partial shading, nevertheless, is an essential problem which affects the productivity and life of PV plants. PV reconfiguration is known as a powerful technique to resolve this effect. It is achieved by rearranging the PV modules according to their temperature and levels of shade. Therefore, in this paper, we have utilized three simple population-based optimization algorithms that are known as the flow regime algorithm (FRA), the social mimic optimization algorithm (SMO), and the Rao optimization algorithm to dynamically restructure the PV array. The effectiveness of the proposed algorithms is evaluated using several metrics such as fill factor, mismatch losses, percentage of power loss, and percentage of power enhancement. Besides, the results obtained are compared with a regular total-cross-tied (TCT) connection and recently published techniques such as the competence square (CS) and genetic algorithm (GA). Furthermore, to demonstrate the suitability of proposed approaches in real-time implementation, real-time irradiation data of a particular location are considered and fed into the proposed algorithms for effective shade dispersion. After successful shade dispersion, the total energy generated using the three proposed algorithms is calculated and compared with the TCT reconfigured system for one year. The presented energy calculations and revenue generation confirm that the power produced by the proposed FRA technique is 13% higher than that generated by the TCT configuration. Furthermore, the presented PV characteristics show a reduced number of multiple peaks in the system. Thus, the proposed FRA technique can be endorsed as a technique that is superior to other existing methods.

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Photovoltaic Array Reconfiguration System for Maximizing the Harvested Power Using Population-Based Algorithms

Partial shading condition drastically reduces the maximum power output of photovoltaic array. Partial shading occurs due to several factors, such as flying birds, trees, and passing clouds. Many ways can be mitigated partial shading problems in photovoltaic (PV) array. One among the way is reconfiguration techniques, namely reconfigure the location of PV modules in PV array based on irradiance levels in order to distribute shading effects and increasing maximum power. This paper proposed an optimal SuDoKu reconfiguration pattern for $9\times 9$ total-cross-tied (TCT) PV array to improve maximum power under partial shading conditions. In this approach, the physical location of PV modules in TCT array are rearranged based on optimal SuDoKu style without altering the electrical connections, so that the shading effects can distribute over the array. Further, the performance of proposed pattern investigated with existing SuDoKu pattern under different shading conditions by comparing the global maximum power point, mismatch losses, fill-factor, and efficiency using MATLAB-Simulink. Based on the results of this paper, it concluded that the proposed optimal SuDoKu reconfiguration arrangement is reducing the wiring arrangement and increasing the shading distribution over the array as compared to SuDoKu arrangement.

Optimal SuDoKu Reconfiguration Technique for Total-Cross-Tied PV Array to Increase Power Output Under Non-Uniform Irradiance

The mismatch effect creates a difference between the sum of maximum power generated by individual Photovoltaic (PV) modules and the overall PV array power output. Mismatch effects can be classified into internal and external mismatch effects. Internal mismatch effect occurs because of factors such as manufacturing defects and ageing. The external effect occurs because of variations in solar irradiance and temperature. This paper presents the investigation of internal and external mismatch effects on various 5×4 Photovoltaic (PV) array interconnections such as series-parallel, total-cross-tied, bridge-link, honey-comb, hybrid SP-TCT, hybrid BL-TCT, along with proposed hybrid HC-TCT and hybrid HC-BL. Six mismatch case studies are considered in this paper to investigate the performance of PV array connections. Among the six cases, three cases are due to internal mismatch effects, and the remaining three cases belong to the external effects. In addition, the global maximum power point (GMPP), the voltage at GMPP, thermal voltage, power loss, fill-factor, efficiency (η), and possible local peaks (PLP) parameters are calculated and compared for each PV array connection under all case studies using Matlab-Simulink. Also, for each PV array connection, the revenue generation is calculated from energy savings under mismatch effects. The paper summary shows that TCT, HC-TCT, and HC-BL array connections delivered beneficial results under external effects, and TCT, HC, HC-TCT, and HC-BL provided superior results under internal effects.

/pdf/investigation-of-power-losses-on-solar-photovoltaic-array-2wa7t1ucp5.pdf

Sai Krishna G

Papers

Optimal SuDoKu Reconfiguration Technique for Total-Cross-Tied PV Array to Increase Power Output Under Non-Uniform Irradiance

Investigation of Power losses on Solar Photovoltaic Array Interconnections Under Mismatch Conditions