Investigation of Evolutionary Computation Techniques Cuckoo Search and Gray Wolf Optimization for Enhancing Solar PV Technology

Abstract

Solar energy is a critical renewable energy technology, but improving efficiency and output is crucial. This study explores Gray Wolf Optimization (GWO) and Cuckoo Search Optimization (CSO) for fine-tuning solar cell parameters. These techniques are used to find the best combination of cell material properties, structural configurations, and operating conditions to maximize energy yield, minimize costs, and enhance system reliability. CSO's unique Lévy flight mechanism helps avoid getting stuck on suboptimal solutions. By comparing these optimization techniques, this research aims to provide valuable insights for designing and operating solar energy systems. The findings can inform stakeholders across the energy spectrum to make informed decisions that drive the development of solar PV technology. This research represents a significant step towards realizing the full potential of solar energy as a sustainable energy source.