Journal ArticleDOI
An efficient hybrid evolutionary algorithm based on PSO and HBMO algorithms for multi-objective Distribution Feeder Reconfiguration
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TLDR
A robust searching hybrid evolutionary algorithm based on the combination of the Honey Bee Mating Optimization and the Discrete Particle Swarm Optimization, called DPSO–HBMO, is implied to solve the multi-objective Distribution Feeder Reconfiguration problem.About:
This article is published in Energy Conversion and Management.The article was published on 2009-08-01. It has received 126 citations till now. The article focuses on the topics: Evolutionary algorithm & Optimization problem.read more
Citations
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New inspirations in swarm intelligence: a survey
TL;DR: This tutorial highlights the most recent nature-based inspirations as metaphors for swarm intelligence meta-heuristics and describes the biological behaviours from which a number of computational algorithms were developed.
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Improved particle swarm optimisation for multi-objective optimal power flow considering the cost, loss, emission and voltage stability index
TL;DR: In this paper, an improved particle swarm optimisation (IPSO) method for the multi-objective optimal power flow (OPF) problem is presented, which considers the cost, loss, voltage stability and emission impacts as the objective functions.
Journal ArticleDOI
A new hybrid algorithm for optimal power flow considering prohibited zones and valve point effect
TL;DR: In this article, an effective and reliable algorithm based on Shuffle Frog Leaping Algorithm (SFLA) and Simulated Annealing (SA) is proposed for solving the optimal power flow (OPF) problem with non-smooth and non-convex generator fuel cost characteristics.
Journal ArticleDOI
DSTATCOM allocation in distribution networks considering reconfiguration using differential evolution algorithm
TL;DR: In this paper, a combinatorial process based on reconfiguration and DSTATCOM allocation is implemented to mitigate losses and improve voltage profile in power distribution networks, where differential evolution algorithm (DEA) has been used to solve and overcome the complicity of this combinatorsial nonlinear optimization problem.
Journal ArticleDOI
Enhanced gravitational search algorithm for multi-objective distribution feeder reconfiguration considering reliability, loss and operational cost
TL;DR: In this article, an efficient method for solving the multi-objective reconfiguration of radial distribution systems with regard to distributed generators is presented, which considers reliability, operation cost and loss simultaneously.
References
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Journal ArticleDOI
Particle swarm optimization
TL;DR: A snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems, is included.
Journal ArticleDOI
Network reconfiguration in distribution systems for loss reduction and load balancing
Mesut E. Baran,Felix F. Wu +1 more
TL;DR: Accuracy analysis and the test results show that estimation methods can be used in searches to reconfigure a given system even if the system is not well compensated and reconfiguring involves load transfer between different substations.
Journal ArticleDOI
Particle swarm optimization to solving the economic dispatch considering the generator constraints
TL;DR: In this paper, a particle swarm optimization (PSO) method for solving the economic dispatch (ED) problem in power systems is proposed, and the experimental results show that the proposed PSO method was indeed capable of obtaining higher quality solutions efficiently in ED problems.
Journal ArticleDOI
Distribution feeder reconfiguration for loss reduction
TL;DR: In this paper, a scheme that utilizes feeder reconfiguration as a planning and/or real-time control tool to restructure the primary feeder for loss reduction is presented.
Journal ArticleDOI
Reconfiguration of electric distribution networks for resistive line losses reduction
D. Shirmohammadi,H.W. Hong +1 more
TL;DR: In this paper, the authors describe a heuristic method for the reconfiguration of distribution networks in order to reduce their resistive line losses under normal operating conditions, characterized by convergence to the optimum or a near-optimum solution and the independence of the final solution from the initial status of the network switches.
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