Open AccessSolution of economic load dispatch problem via hybrid particle swarm optimization with time‐varying acceleration coefficients and bacteria foraging algorithm techniques
Author(s) -
Abedinia Oveis,
Amjady Nima,
Ghasemi Ali,
Hejrati Zakariya
Publication year - 2013
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/etep.1674
Subject(s) - particle swarm optimization , economic dispatch , mathematical optimization , acceleration , computer science , genetic algorithm , nonlinear system , multi swarm optimization , power (physics) , swarm behaviour , control theory (sociology) , electric power system , mathematics , artificial intelligence , physics , control (management) , classical mechanics , quantum mechanics
SUMMARY In this research, a hybrid particle swarm optimization with time‐varying acceleration coefficients (HPSOTVAC) and bacteria foraging algorithm (BFA) are presented for solving a complex economic load dispatch problem. Basically, there are many realistic constraints that affect feasible operation such as generation limitation, ramp rate limits, prohibited operating zone, nonlinear cost functions, and transmission loss that are considered in this research. The effectiveness of the proposed HPSOTVAC/BFA is tested in 6‐, 15‐, and 40‐unit generating systems. Also, for 6‐unit case study, the valve‐point effect is considered too. The numerical results demonstrate that the proposed hybrid technique gives less total generation costs than genetic algorithm (GA), particle swarm optimization (PSO), hybrid GA/PSO, active power optimization, iteration PSO, and self‐organizing hierarchical PSO methods. Copyright © 2012 John Wiley & Sons, Ltd.