Sizing of hybrid renewable energy systems using a floriculture-motivated optimization technique

Selecting suitable devices for a hybrid renewable energy system is a crucial step in any electrification project. However, the growing number of manufacturers of photovoltaic panels, wind turbines, batteries, and generators has made the sizing process increasingly complex. This paper proposes the use of a recently developed method, the Orchard Algorithm, to address this challenging optimization problem. The effectiveness of this floriculture-motivated algorithm is demonstrated through a hypothetical rural electrification project in Nigeria, yielding a well-performing solution comparable to that obtained using a genetic algorithm—a method widely accepted and employed in various commercial tools. From a cost standpoint, the solution obtained through OA demonstrates a 0.45 % improvement over that produced by the GA implementation. During the optimization process with OA, the search space was extensively explored, resulting in a 10.65 % probability of uncovering an additional local minimum by repeating the optimization process. This outcome provides supporting evidence regarding the optimality of the identified solution.