Optimization of photovoltaic solar panel grids coated with ZnO using optimal line flow as well as Euclidean Affine Flower Pollination Algorithms
摘要
In this paper, an attempt has been made to explore ways of improving the output of photovoltaic solar panels by applying an antireflective coating made of zinc oxide that is deposited on the panel by spray pyrolysis, and system-level balancing to the Euclidean Affine Flower Pollination Algorithm. A thin coating of zinc oxide solution was applied on the external surface of commercial photo-voltaic panels. Optical transmittance and surface reflectance were much higher, which made the photon absorption higher and minimized the surface losses. Consequently, the panel coated showed an output voltage growth of 3.6% (between 34.5 volts and 35.7 volts), an increase in power output of 3.5% and a power loss decrease of 1.9% (between 690 and 677 watts). In order to increase energy harvesting and efficiency further, an improved Optimal Line Flow model that was combined with the Euclidean Affine Flower Pollination Algorithm was introduced. The algorithm was useful in streamlining the dispatch of generation and the voltage stability indices and the power flow paths whilst considering the enhanced input of the coated panels. Under algorithm-based optimization, the system was able to increase output voltage by 6.9% and decrease power loss by 8.6% over the coated panel. All in all, the system-level optimization and integrated material-level modification strategy enhanced energy yield, voltage profile, cost-effectiveness and system stability significantly.