To harvest maximum amount of solar energy and to attain higher efficiency, photovoltaic generation (PVG) systems are to be operated at their maximum power  point (MPP) under both variable climatic and partial shaded condition (PSC). From literature most of conventional MPP tracking (MPPT) methods are able to guarantee MPP successfully under uniform shading condition but fails to get global MPP as they may trap at local MPP under PSC, which adversely deteriorates the efficiency of Photovoltaic Generation (PVG) system. In this paper a novel MPPT based on Whale Optimization Algorithm (WOA) is proposed to analyze analytic modeling of PV system considering both series and shunt resistances for MPP tracking under PSC. The proposed algorithm is tested on 6S, 3S2P and 2S3P Photovoltaic array configurations for different shading patterns and results are presented. To compare the performance, GWO and PSO MPPT algorithms are also simulated and results are also presented.  From the results it is noticed that proposed MPPT method is superior to other MPPT methods with reference to accuracy and tracking speed.Article History: Received July 23rd 2016; Received in revised form September 15th 2016; Accepted October 1st 2016; Available onlineHow to Cite This Article: Kumar, C.H.S and Rao, R.S. (2016) A Novel Global MPP Tracking of Photovoltaic System based on Whale Optimization Algorithm. Int. Journal of Renewable Energy Development, 5(3), 225-232.http://dx.doi.org/10.14710/ijred.5.3.225-232

ABSTRACT:Partial shading condition is one of the adverse phenomena which effects the power output of photovoltaic (PV) systems due to inaccurate tracking of global maximum power point. Conventional Maximum Power Point Tracking (MPPT) techniques like Perturb and Observe, Incremental Conductance and Hill Climbing can track the maximum power point effectively under uniform shaded condition, but fails under partial shaded condition. An attractive solution under partial shaded condition is application of meta-heuristic algorithms to operate at global maximum power point. Hence in this paper, an Enhanced Grey Wolf Optimizer (EGWO) based maximum power point tracking algorithm is proposed to track the global maximum power point of PV system under partial shading condition. A Mathematical model of PV system is developed under partial shaded condition using single diode model and EGWO is applied to track global maximum power point. The proposed method was programmed in MATLAB environment and simulations are carried out on 4S and 2S2P PV configurations for dynamically changing shading patterns. The results of the proposed method were analyzed and compared with GWO and PSO algorithms. It was observed that proposed method is effective in tracking global maximum power point with more accuracy in less computation time compared to other methods.

Partial shading causes mismatch losses in the solar PV system. In the PV array, the power output from the healthy PV modules is gone in vain due to the mismatch losses. The PV array construction with the high resistivity to the mismatch loss generation is the progressing research work in the research field. In this work, a new kind of array configuration scheme is framed for the PV system for overcoming the effect of partial shading. The proposed array configuration has a high resistivity to the mismatch loss generation over the other conventional array configuration methods. The array configuration is framed in a pattern that is similar to the spiral step pattern. Each row of the PV array is constructed with the PV modules from each row of the conventional Total Cross Tied configuration with the optimized distance. This row construction allows the system to uniformly disperses the partial shading over the PV array. The simulation analysis is carried out by applying various shading patterns in MATLAB/Simulink®. The performance of the proposed array configuration is also analyzed in the experimental setup and the results were presented.

Solar Photovoltaic array may often be subjected to partial shading, which may lead to uneven row current and creates local maximum power point on the power-voltage characteristics. One of the effective approaches to dilute the concentration of partial shading is the array reconfiguration technique. This study proposes a ken-ken puzzle-based reconfiguration technique for 4x4 total-cross-tied configuration to rearrange the position of modules within the array and to improve the maximum power under partial shading conditions. Further, the performance of the ken-ken puzzle arrangement is compared with the total-cross-tied configuration and existing reconfiguration techniques namely odd-even, Latin Square, and Sudoku reported in the literature. The performance of all these configurations is evaluated in terms of fill factor, mismatch loss, power loss, execution ratio, and performance enhancement ratio. The proposed ken-ken puzzle-based reconfiguration technique mitigates the occurrence of local maximum power point and eliminates the need for a complex algorithm to track the global maximum power point. The simulation result shows that the KK puzzle-based reconfiguration technique has obtained an improved PE of 10.85 % compared to TCT configuration, followed by LS, Sudoku, and OE. Also, the experimental result shows the effectiveness of the ken-ken in diluting the effects of partial shading when the rows of the photovoltaic array are shaded. The ken-ken puzzle-based reconfiguration technique reduces the complexity, maintenance and increases reliability, scalability of the PV array.INDEX TERMSShade dispersion, ken-ken puzzle pattern, global maximum power point, local maximum power point, and performance enhancement ratio.

The Photovoltaic (PV) cell converts a portion of incident irradiation of visible wavelength into electricity and the remaining into heat, thereby decreasing the electrical efficiency. Hence, it is necessary to transfer the heat generated in the module by a cooling medium, thereby maintaining the operating temperature within the operating limit. This study discusses the feasibility of cooling the monocrystalline and polycrystalline modules by using rehashed edible oil (coconut oil, sesame oil, and peanut oil) with an integrated oil tank attached to the backside of the module. This study has used the environmentally friendly rehashed edible oil as a coolant, which can be used as an alternate to the toxic mineral oil. Hence, this study can prevent the consumption of reused edible oil along with the food, which causes harmful effects on human health. The rehashed edible oil flows from the storage tank through the backside of the module and is collected in another storage tank, which can be reused. Also, the performance of the monocrystalline and polycrystalline modules under different rehashed edible oil shows a significant reduction in module temperature and improvement in the efficiency of the module. The performance of the peanut oil is found to be superior in improving the performance by 14.0 % and 16.8 % on monocrystalline and polycrystalline modules respectively.