Abstract
In this paper, an improved antlion optimization algorithm (IALO) was proposed to search for promising solutions for optimal economic load dispatch (ELD) problems to minimize electrical generation fuel costs in power systems with thermal units and to ensure all constraints are within operating ranges. IALO can be more effective than the original method, called the antlion optimization algorithm (ALO), because of the high performance of the applied modifications on the new solutions searching process. In order to evaluate the abilities of the IALO method, we completed many tests on thermal generating systems including 10, 15, 20, 30, 60, 80, and 90 units with different constraints and fuel-consuming characteristics. The results suggest that the offered method is superior to the ALO method with more stable search ability, faster convergence velocity, and shorter calculation times. Furthermore, the obtained results of the IALO method are much better than those of almost all the other methods used to solve problems for the same systems. As a result, IALO is suggested to be a highly effective method, and it can be applied to other problems in power systems instead of ALO, which has a lower performance.
Highlights
Economic load dispatch (ELD) is known as a means of lowering fuel costs for electricity generation in thermal power plants
The results showed that the EMFA method provided the highest quality results compared to all other methods including the firefly optimization algorithm (FOA), Particle swarm optimization (PSO), differential evolution (DE), Cuckoo Search Algorithm (CSA), and genetic algorithm (GA)
In order to investigate the real performance of the improved antlion optimization algorithm (IALO) method, another comparison criterion was considered to be the number of fitness evaluations, Nfes, which is shown in the following equation: N f es = ω ∗ Np ∗ Gmax
Summary
Economic load dispatch (ELD) is known as a means of lowering fuel costs for electricity generation in thermal power plants. Traditional methods have to take the partial derivative in the process of finding solutions These methods have some restrictions if they solve the ELD problem for complex systems, for example, those with non-smooth shape objective functions. An improved antlion optimization algorithm (IALO) is suggested for solving the ELD problem Constraints such as transmission losses, POZ, RRL, and SR are considered. The combination of the highly effective proposed modification and the applied modification can support the proposed IALO method in finding optimal solutions effectively and quickly; Consider the different systems that contain complex objective functions and constraints; Compare our proposed IALO with classic ALO.
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