DocumentCode :
3339872
Title :
A unified scheme for testing alternative techniques for distribution system minimum loss reconfiguration
Author :
Batrinu, Florentin ; Carpaneto, Enrico ; Chicco, Gianfranco
Author_Institution :
Dipartimento di Ingegneria Elettrica, Politecnico di Torino
fYear :
2005
fDate :
18-18 Nov. 2005
Lastpage :
6
Abstract :
The optimal reconfiguration of a large distribution system is a global optimisation problem typically solved by using deterministic or heuristic methods. Comparing the effectiveness of the various methods can be assisted by formulating a unified framework able to identify the common characteristics and the conceptual differences among the methods. This paper illustrates the development of such a framework, interpreting the solution process of a number of methods (iterative improvement, tabu search, simulated annealing, ant colony search and particle swarm optimisation) on the basis of a set of underlying principles, and applies this framework to the reconfiguration of a large real urban distribution system. The paper also shows how the proposed framework allows for developing additional solution algorithms, and presents effective results obtained by using a specific formulation of the evolutionary particle swarm optimisation derived from suitably mixing the underlying principles
Keywords :
deterministic algorithms; distribution networks; evolutionary computation; particle swarm optimisation; search problems; simulated annealing; ant colony search; distribution system minimum loss reconfiguration; evolutionary particle swarm optimisation; global optimisation problem; heuristic methods; iterative improvement; simulated annealing; tabu search; urban distribution system; Ant colony optimization; Indexing; Iterative algorithms; Iterative methods; Optimization methods; Particle swarm optimization; Power system economics; Protection; Simulated annealing; System testing; deterministic and heuristic methods; distribution systems; iterative improvement; minimum losses; optimal reconfiguration; particle swarm optimization; simulated annealing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Future Power Systems, 2005 International Conference on
Conference_Location :
Amsterdam
Print_ISBN :
90-78205-02-4
Type :
conf
DOI :
10.1109/FPS.2005.204275
Filename :
1600548
Link To Document :
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