Design of an electrical power system for a 1U nanosatellite using modified G3PCX

The increasing demand for nanosatellite deployment has necessitated the development of efficient and reliable Electrical Power System (EPS) specifically designed to address their unique challenges. The EPS is critical for their optimal functionality, which necessitates accurate component selection. The traditional design is a time-consuming process that involves manually selecting components and susceptible to errors, especially for a complex EPS. Optimization methods offer a promising approach to designing such EPS, enabling the selection of optimal component configurations and operating parameters that satisfy the mission requirements. To address this challenge, a new optimization-based approach is proposed that uses the optimization algorithms to automate the component selection process. This study presents a novel contribution by applying Modified Generalized Generation Gap 3-Parent Crossover (MG3PCX) applied to Mohammed V University 1U CubeSat’s EPS design. To evaluate its efficiency, a comparative study was conducted against Interior Point OPTimizer (IPOPT), Particle Swarm Optimization (PSO), and Genetic Algorithms (GA). These algorithms are evaluated based on their performance in optimizing component selection concerning predefined parameters such as the input/output voltage, the efficiency of the MPPT converters, and the load-side converters, significantly reducing the design time and effort. MG3PCX demonstrated its effectiveness compared to other algorithms.