Optimization algorithms for loading military diesel generators

Economic Load Dispatch;ELD;Particle Swarm Optimization;PSO;Cuckoo Search;CS;CSO;Bat algorithm;BA;First Fit Decreasing;FFD;generator;optimization algorithm;swarm;metaheuristic

Peterson, Nathan ; Sauer ; Peter W. ; Johnson ; Melanie

关键词: Economic Load Dispatch;    ELD;    Particle Swarm Optimization;    PSO;    Cuckoo Search;    CS;    CSO;    Bat algorithm;    BA;    First Fit Decreasing;    FFD;    generator;    optimization algorithm;    swarm;    metaheuristic;   

Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/102499/PETERSON-THESIS-2018.pdf?sequence=1&isAllowed=y

美国|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

The economic load dispatch (ELD) problem challenges the designer to adequately provide for electrical load demand while minimizing operational costs. The military has a unique set of constraints for meeting the ELD problem to provide power to soldiers in forward operating bases. The constraints include the use of military diesel gensets that remain disconnected from each other and are loaded below a user-defined real power threshold (for a reliability safety cushion). In addition, the system must be simple enough to be constructed with minimal training and require no reconfiguration once established. As a result, a simple tool to quickly assign loads to isolated military diesel generators is required. To meet this need, this study compares the use of several optimization algorithms including particle swarm optimization (PSO), bat algorithm (BA), cuckoo search (CS), first fit decreasing (FFD) bin packing, and an exhaustive search (ES) method. It is found that at large enough search spaces, the optimization algorithms can discover reasonably optimal solutions while substantially decreasing search time. For this application, FFD has more optimal average solutions as well as faster run time compared to the other algorithms.