La gestion optimale des réseaux électriques par l’intelligence collective
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Date
2017-06-28
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Abstract
Résumé (Français et/ou Anglais) :
To achieve optimal management of electrical energy networks and for demonstrate the performance and effectiveness of collective intelligence algorithms and their capabilities in finding optimal solutions (better global research, convergence, minimal time Compared to conventional optimization algorithms), For this purpose the approach had used the algorithms: Firefly FFA, ants algorithm ACO, modified frog leaping MSFLA, monkey algorithm (Monkey) MA, algorithm of the swarms PSO and Biogeography-based optimization (BBO). Thus the work and in its quest for more reliable and accurate solutions the use of hybridization technique
(the combination of methods):
1) -Hybridization FFA-MPSO, 2) -Hybridization ACO-MSFLA ,
3) - HybridizationPSO-MA,4) - HybridizationBBO-MA .
The problem EPD (economic dispatching) has been solved using the previously mentioned methods by integrating single-objective or multi-objective functions applied on the IEEE-6, IEEE-14, IEEE-30 networks and Networks with 10 and 20 generators.
Description
Doctorat en Sciences
