The modern heuristic techniques mainly include the application of the artificial intelligence approaches such as genetic algorithm, particle swarmoptimization algorithm, ant colony optimization, stochastic diffusion search, differential evolution, etc. The main aspect of these techniques is theirflexibility for solving the optimization problems that have different mathematical constraints. In a power system area, the competition between theelectric utilities is gradually increased due to the deregulation of the electrical markets. For this reason, the generation expansion problem presentsitself as an important issue that needs to be considered in order to achieve reasonable economic decisions.Keywords: Genetic algorithm, Particle swarm opti...
This document describes the application of multi-objective genetic algorithms as techniques and tool...
This document describes the application of multi-objective genetic algorithms as techniques and tool...
This document describes the application of multi-objective genetic algorithms as techniques and tool...
Many areas in power systems require solving one or more nonlinear optimization problems. While analy...
Power system planning, control and operation require an adequate use of existing resources as to inc...
The generation planning and investment problem in restructured industry is to determine what, when, ...
Particle Swarm Optimization (PSO) is one of the concepts of swarm intelligence inspired by studies i...
Planning of microgrids has been a difficult problem, due to the fact that this planning requires con...
Abstract—Many areas in power systems require solving one or more nonlinear optimization problems. Wh...
Electric power systems around the world are changing in terms of structure, operation, management an...
Microgrids have drawn substantial consideration due to high quality and reliable mix sources of elec...
To meet increasing electricity demand and reduce tremendous greenhouse gas emission at the same time...
To meet increasing electricity demand and reduce tremendous greenhouse gas emission at the same time...
This paper presents a comparison of swarm intelligence and evolutionary techniques based approaches ...
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University Lo...
This document describes the application of multi-objective genetic algorithms as techniques and tool...
This document describes the application of multi-objective genetic algorithms as techniques and tool...
This document describes the application of multi-objective genetic algorithms as techniques and tool...
Many areas in power systems require solving one or more nonlinear optimization problems. While analy...
Power system planning, control and operation require an adequate use of existing resources as to inc...
The generation planning and investment problem in restructured industry is to determine what, when, ...
Particle Swarm Optimization (PSO) is one of the concepts of swarm intelligence inspired by studies i...
Planning of microgrids has been a difficult problem, due to the fact that this planning requires con...
Abstract—Many areas in power systems require solving one or more nonlinear optimization problems. Wh...
Electric power systems around the world are changing in terms of structure, operation, management an...
Microgrids have drawn substantial consideration due to high quality and reliable mix sources of elec...
To meet increasing electricity demand and reduce tremendous greenhouse gas emission at the same time...
To meet increasing electricity demand and reduce tremendous greenhouse gas emission at the same time...
This paper presents a comparison of swarm intelligence and evolutionary techniques based approaches ...
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University Lo...
This document describes the application of multi-objective genetic algorithms as techniques and tool...
This document describes the application of multi-objective genetic algorithms as techniques and tool...
This document describes the application of multi-objective genetic algorithms as techniques and tool...