“…A detailed literature consisting of 30 valuable papers, including meta‐heuristic algorithms, is given in Table 1 . Based on the literature review, namely, the INFO algorithm, [ 14 ] atomic orbital search algorithm, [ 15 ] improved electromagnetism‐like mechanism algorithm, [ 16 ] northern goshawk optimization algorithm, [ 17 ] improved queuing search optimization algorithm based on differential evaluation, [ 18 ] fractional Henon chaotic Harris Hawks optimization, [ 19 ] hunter‐prey algorithm, [ 20 ] robust niching optimization, [ 21 ] wild horse optimizer, [ 20 ] heap‐based optimizer, [ 22 ] modified stochastic fractal search algorithm, [ 23 ] circle search algorithm, [ 24 ] orthogonal learning gradient‐based optimization, [ 25 ] improved rao‐1 algorithm, [ 26 ] improved political optimization algorithm, [ 27 ] memory‐based improved gorilla troops optimizer, [ 28 ] adaptive fractional‐order Archimedes optimization algorithm, [ 29 ] multistrategy cuckoo search algorithm, [ 30 ] whale optimizer with Nelder‐Mead simplex, [ 31 ] Runge‐Kutta optimizer, [ 32 ] turbulent flow of water‐based optimization, [ 33 ] supply demand optimization, [ 34 ] enhanced chaotic JAYA algorithm, [ 35 ] modified teaching–learning based optimization, [ 36 ] enhanced marine predators algorithm, [ 37 ] hybrid African vultures–grey wolf optimizer, [ 38 ] niche particle swarm optimization in parallel computing, [ 39 ] simulated annealing optimization, [ 40 ] enhanced ant lion optimizer, [ 41 ] enhanced Lévy flight bat algorithm, [ 42 ] and teaching–learning‐based artificial bee colony [ 43 ] algorithms have been used for PV parameter extraction. The results of the parameter extraction problem solved with these meta‐heuristic algorithms are presented under two categories: the simulation and the sensitivity analysis.…”