Assessment of hurricane versus sine‐cosine optimization algorithms for economic/ecological emissions load dispatch problem

Summary In the current research, a comparative study of two modern optimization algorithms is carried out for finding the solution of non‐smooth economic/ecological emission load dispatch (EELD) problem. These optimization methods are hurricane optimization algorithm (HOA) and sine‐cosine algorithm (SCA). A multi‐objective optimization module is successively developed for the competitive algorithms. In the competitive algorithms, random initial populations of the search agents are created in the search space with optimizing the conflicted objectives, economic and emission, simultaneously of the EELD problem. The multi‐objective optimal solutions are achieved based on Pareto concepts. The competitive algorithms are tested on six test function and two general standard engineering problems called tension/compression design and welded beam design problem. Then, the optimization algorithms are validated for an important operation issue of power systems by solving the non‐smooth EELD on the standard six generators, IEEE 30‐bus standard test system. Single and multiobjective frameworks are considered to reduce the generation fuel costs as well as minimizing the corresponding ecological emissions. Simulation results are assessed with previous famous optimizers. Also, these results prove the reasonable performances of the proposed two competitive algorithms compared with previous optimization techniques. In addition, HOA has more competitive performance compared with SCA according to convergence rate and statistical analysis of the studied real engineering problems as well as for benchmarking and design engineering problems. Therefore, these algorithms are considered as efficient and capable algorithms for other non‐smooth large‐scale complex problems in real power networks.