Firefly-inspired algorithm for optimal sizing of renewable hybrid system considering reliability criteria

Abstract

Abstract Renewable energy sources are usually seen as a response to actual environmental, social and economic issues. However, the random nature of these sources requires the development of sizing rules and the use of these systems for their exploitation. This article presents the results of a developed hybrid PV/wind optimization sizing method, taking into account the strong combination between the intermittent energy resource (solar and wind), the storage capacity and a given load profile. This optimization method is based on the use of metaheuristic techniques. These algorithms, often inspired by nature, are designed to solve complex optimization problems. Among the most recent metaheuristics, we used the Firefly Algorithm (FA), considering the Load Dissatisfaction Rate (LDR) criteria and the Electricity Cost (EC) indicator for power reliability and system cost. The suggested method determines the system optimum configuration, which can achieve the desired LDR with minimum EC. To achieve this aim, an objective function is formulated for the EC. It must be kept to a minimum while respecting the reliability constraints (LDRdesired). The effectiveness of the FA in solving a hybrid system optimization problem is scrutinized and its performance is compared to other renamed optimization algorithms. To highlight the propounded method performance a real case study has been conducted and the results are discussed.