Recent optimization methods for a photovoltaic solar system. Implementation of efficient PV cooling, an additional solar panel can be proposed to increase the temperature of the water outlet, thereby increasing the overall output. It is seen that an increase of almost 7.3% can be obtained by the PCM.
The performance and efficiency of solar PV vary according to types of cells. The mono-crystalline solar cells feature high energy efficiency, but it has a complex manufacturing process. The multi-crystalline solar cells are cost-effective but suffer from low efficiency in comparison to mono-crystalline solar cells.
Different optimization approaches are used for different types of solar cells. For instance, the flower pollination optimization algorithm (FPOA) was employed to extract the features for different cell types and then compared with the evolution strategy and PSO in (Chellaswamy et al., 2019).
Sizing and optimization of solar PV are complex. This method allows for a precise estimation of the amount of energy supplied over a given period. Study of uncertainty parameters under various charging scenarios. The introduced approach was employed in a real network with 20 kV. Solar PV panels improve the supply of electrical energy.
The optimization algorithms have demonstrated excellent outcomes in solar PV applications with regard to sizing, load demand and power generation. Besides, the optimizations help to reduce the operational cost, power losses, as well as achieve better integration and controllability of peak power.
In this vein, several approaches are used to optimize the controlling factor of performance by improving the efficiency of the PV cell via: Improving the quality of the core material to collect more radiation. Integrating other renewable resources and optimizing the size to increase economic feasibility.