Table 3.

Summary of techniques used for sizing of renewable energy based hybrid systems

S. No.	Optimization techniques	Description
1	Traditional methods Trade off method [46], Iterative approach [47], Probabilistic approach [48], Linear programming [49], Graphical construction technique [50], Direct algorithm [51] and Analytic method [52], Numerical method [53], Mixed integer linear programming [54]	Traditional methods are relatively simple to implement “by hand” or with spreadsheets. For this reason, a majority of PV system installers use them. However, compared to simulating the system with a software tool, such methods can take more time. Secondly, these methods do not take into account weather changes and the variation in the shape of the consumption profiles, which are based on daily average values and not instantaneous. Furthermore, these methods focus on minimizing economic cost and satisfying user demand. They do not integrate environmental concerns
2	Meta-heuristic algorithms Genetic Algorithm (GA) [55], Particle Swarm Optimization (PSO) [56], Simulated Annealing (SA) [57], Ant Colony Algorithms (ACA) [58], Artificial Bee Colony Algorithm (ABC) [59], Cuckoo Search (CS) [60], Bacterial Foraging Algorithm (BFA) [61].	Known for many years for their efficiency, meta-heuristics are a family of stochastic methods that consist of solving optimization problems. They generally exploit random processes in the exploration of the research space to cope with the combinatorial explosion generated by the use of exact methods. On the other hand, they often prove to be efficient in very large problems and, moreover, can benefit from convergence theorems while providing good quality solutions in a reasonable time. The disadvantage of this type of method is the existence of parameters to be adjusted in order to obtain a satisfactory convergence
3	Software tools [62] HOMER, iHOGA, HYBRID2, TRNSYS, HYDROGEMS, INSEL, ARES, SOLSIM, SOMES, H2RES	Most of these tools are used to simulate a given system predefined by the user and are rather dedicated to evaluate a certain system configuration and manually visualize the effect of a change in its parameters. The degree of precision of the models that use these tools varies from one to another and do not integrate the primary energy contained in the system as an evaluation indicator, so that only the economic aspect is considered