Abstract: This study presents a modified version of the artificial bee colony (ABC) algorithm by including a local search technique for solving the non-convex economic power dispatch problem. The local search step is incorporated at the end of each iteration. Total system losses, valve-point loading effects and prohibited operating zones have been incorporated in the problem formulation. Thus, the problem becomes highly nonlinear and with discontinuous objective function. The proposed technique is validated using an IEEE benchmark system with ten thermal units. Simulation results demonstrate that the proposed optimization algorithm has better convergence characteristics in comparison with the original ABC algorithm.
Abstract: The objective of the Economic Dispatch(ED) Problems
of electric power generation is to schedule the committed generating
units outputs so as to meet the required load demand at minimum
operating cost while satisfying all units and system equality and
inequality constraints. This paper presents a new method of ED
problems utilizing the Max-Min Ant System Optimization.
Historically, traditional optimizations techniques have been used,
such as linear and non-linear programming, but within the past
decade the focus has shifted on the utilization of Evolutionary
Algorithms, as an example Genetic Algorithms, Simulated Annealing
and recently Ant Colony Optimization (ACO). In this paper we
introduce the Max-Min Ant System based version of the Ant System.
This algorithm encourages local searching around the best solution
found in each iteration. To show its efficiency and effectiveness, the
proposed Max-Min Ant System is applied to sample ED problems
composed of 4 generators. Comparison to conventional genetic
algorithms is presented.
Abstract: In this paper, an Interactive Compromise Approach
with Particle Swarm Optimization(ICA-PSO) is presented to solve the
Economic Emission Dispatch(EED) problem. The cost function and
emission function are modeled as the nonsmooth functions,
respectively. The bi-objective including both the minimization of cost
and emission is formulated in this paper. ICA-PSO is proposed to
solve EED problem for finding a better compromise solution. The
solution methodology can offer a global or near-global solution for
decision-making requirements. The effectiveness and efficiency of
ICA-PSO are demonstrated by a sample test system. Test results can
be shown that the proposed method provide a practical and flexible
framework for power dispatch.