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

Abstract

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.

Controller design for gantry crane system using modified sine cosine optimization algorithm

“…The nonlinear dynamics of the gantry crane system is modeled bellow using Lagrangian method, where 1 and 2 are the mass of the trolley and the payload respectively; and ℓ are the speed of the trolley and the payload respectively; is the gravitational acceleration, is the actuating force acted on the trolley, and are viscous friction coefficient with the rail and due to pendulum axis respectively; is the moment of inertia of the payload. Ultimately, as shown in (9) and (11) represent the nonlinear model of the system due to the terms of trigonometric functions and the quadratic terms. In this study, it is assumed that the tension force of the hoisting steel wire that causes the cable elongation has a small effect, which can be neglected, thus the length of the cable is considered to be constant and hence, substitute ℓ̇= ℓ̈= 0 as shown in.…”

“…In this study, it is assumed that the tension force of the hoisting steel wire that causes the cable elongation has a small effect, which can be neglected, thus the length of the cable is considered to be constant and hence, substitute ℓ̇= ℓ̈= 0 as shown in. (9) and (11).…”

“…It was proposed by S. Mirjalili [8], in the year 2016, inspired by the cyclic pattern of the sine and cosine trigonometric function to allow a solution to be re-positioned around another solution. The SSCO algorithm was applied on the several optimization problems appeared in the literature such as automatic generation controller of multi-area thermal system [9], solving of global optimization and structure engineering design problems [10], solution of economic/ecological emissions load problems [11], designing truss structures through discrete sizing and optimization [12].…”

Energy Management of a Power System for Economic Load Dispatch Using the Artificial Intelligent Algorithm

“…Considering that the intelligent algorithm has a strong global search ability and has no high requirements of objective function, various intelligent algorithms have been widely used to get the best scheme of ELD. So far, the Grey Wolf Optimization algorithm (GWO) [17], differential evolution algorithm [18], Cuckoo Search Algorithm (CSA) [19], Immune Algorithm (IA) [20], Artificial Bee Colony (ABC) algorithm [21], Symbiotic Organisms Search (SOS) algorithm [22], Artificial Algae Algorithm (AAA) [23], Sine Cosine Algorithm (SCA) [24], Biogeography-Based Optimization (BBO) algorithm [25], Electronics 2020, 9, 108 3 of 19 and other intelligent algorithms have been applied in economic dispatching successively and achieved great prediction results.…”

Multiverse optimizer for structural damage detection: Numerical study and experimental validation

“…[63,64] SCA is applied to solve a wide variety of engineering problems. [65][66][67][68] Pal et al investigated the performance of SCA on large-scale optimization problems. [69] To enhance exploitation ability of the solutions and to decrease overflow of diversity existing in the search equations of standard SCA, Gupta and Deep developed an improved version of SCA.…”