Abstract
Slime Mould Algorithm (SMA) is a newly designed meat-heuristic search that mimics the nature of slime mould during the oscillation phase. This is demonstrated in a unique mathematical formulation that utilizes adjustable weights to influence the sequence of both negative and positive propagation waves to develop a method to link food supply with intensive exploration capacity and exploitation affinity. The study shows the usage of the SM algorithm to solve a non-convex and cost-effective Load Dispatch Problem (ELD) in an electric power system. The effectiveness of SMA is investigated for single area economic load dispatch on large-, medium-, and small-scale power systems, with 3-, 5-, 6-, 10-, 13-, 15-, 20-, 38-, and 40-unit test systems, and the results are substantiated by finding the difference between other well-known meta-heuristic algorithms. The SMA is more efficient than other standard, heuristic, and meta-heuristic search strategies in granting extremely ambitious outputs according to the comparison records.
Highlights
Introduction published maps and institutional affilIn the actual functioning of power systems, Economic Load Dispatch (ELD) is a crucial problem to solve
The economic load dispatch problem is a major concern for the cost-effective operation of electric power systems, as it concentrates on basically assembling the power outputs of the units by establishing time intervals in order to decrease generating costs while still meeting other system requirements
Of the paper, the IEEE bus systems in small, medium, and large-size test systems are considered, and comparisons are done with other methods to see how well the slime mould optimization algorithm performed on the economic load dispatch issue
Summary
Vikram Kumar Kamboj 1,2 , Challa Leela Kumari 1 , Sarbjeet Kaur Bath 3 , Deepak Prashar 4 , Mamoon Rashid 5, * , Sultan S. Alshamrani 6 and Ahmed Saeed AlGhamdi 7.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.