Browsing by Author "Barbosa, Fernando Pires Maciel"
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- Sensing Cloud Optimization applied to a non-convex constrained economical dispatchPublication . Fonte, Pedro M; Monteiro, Cláudio; Barbosa, Fernando Pires MacielIn this paper it is intended to solve an Economical Dispatch (ED) problem with a new tool, named Sensing Cloud Optimization (SCO). It is a technique based on clouds of particles which allow a dynamic change in search space. It has appropriate heuristic characteristic to solve not convex, not differentiable and highly constrained optimisation problems. It is provided with a statistical analysis which determines the cloud's dimension with dynamic adjustments in search space in order to accelerate the convergence and to avoid to get trapped in local minima. Two case studies are presented in which SCO demonstrated good performances reaching lower cost values where compared with other techniques.
- Sensing cloud optimization to solve ED of units with valve-point effects and multi-fuelsPublication . Fonte, Pedro M; Monteiro, Cláudio; Barbosa, Fernando Pires MacielIn this paper a solution to an highly constrained and non-convex economical dispatch (ED) problem with a meta-heuristic technique named Sensing Cloud Optimization (SCO) is presented. The proposed meta-heuristic is based on a cloud of particles whose central point represents the objective function value and the remaining particles act as sensors "to fill" the search space and "guide" the central particle so it moves into the best direction. To demonstrate its performance, a case study with multi-fuel units and valve- point effects is presented.