A new hybrid bacterial foraging and simplified swarm optimization algorithm for practical optimal dynamic load dispatch

This paper presents a novel approach to depict the practical constraints of generator units such as reserve constraints, prohibited operating zones and valve-point effects in the optimal dynamic dispatch problem. Determining the power generation output of units at minimum total fuel cost a dynamic environment with ramp rate limits to satisfy load demand and transmission losses is too complicated and has a lot of local optima in its search space. In addition, the proposed problem has a non-linear, non-convex, non-smooth, multi-modal, non-separable, and non-differentiable nature. In order to overcome above problems a new hybrid technique, based on bacterial foraging and simplified swarm optimization algorithms combined with a new mutation operator and opposition-based initialization is proposed to restraint the premature convergence of the solutions. Therefore, the bacteria in chemo-tactic procedure are moved in short or long steps as well as swimming movements. Furthermore, to increase the diversity of the solution of the search space a novel self-adaptive mutation strategy which profits from four mutation rules is implemented. For more validation the simulation results are applied on four small, medium and large scale systems with 5-unit, 10-unit, 30-unit and 100-unit and compared with those of other methods in the area.

► Formulate reserve constrained dynamic dispatch with valve-point effect, POZ and SRR.
► Consider many practical constraints in the optimal dynamic dispatch problem.
► Propose a new hybrid modified bacterial foraging and simplified swarm optimization.
► Present a new self-adaptive mutation strategy and opposition-based initialization.
► Use Rosenbrock, Rastrigin, Ackley and Griewank functions for performance validation.