Journal ArticleDOI
An enhanced firefly algorithm to multi-objective optimal active/reactive power dispatch with uncertainties consideration
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TLDR
In this article, an enhanced firefly algorithm for solving multi-objective optimal active and reactive power dispatch problems with load and wind generation uncertainties was presented. And the results showed that the proposed method achieved a more favorable solution than the other algorithms.About:
This article is published in International Journal of Electrical Power & Energy Systems.The article was published on 2015-01-01. It has received 79 citations till now. The article focuses on the topics: Economic dispatch & Slack bus.read more
Citations
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Journal ArticleDOI
An improved discrete bat algorithm for symmetric and asymmetric Traveling Salesman Problems
TL;DR: A discrete version of the bat algorithm to solve the well-known symmetric and asymmetric Traveling Salesman Problems and an improvement in the basic structure of the classic bat algorithm are proposed.
Journal ArticleDOI
Gaussian bare-bones water cycle algorithm for optimal reactive power dispatch in electrical power systems
TL;DR: A Gaussian bare-bones WCA (NGBWCA) is proposed and utilized to tackle optimal reactive power dispatch (ORPD) problem in electric power systems and the experimental results and statistical tests vividly demonstrate the efficiency of the NGBW CA algorithm in solving ORPD problem.
Journal ArticleDOI
A discrete firefly algorithm to solve a rich vehicle routing problem modelling a newspaper distribution system with recycling policy
Eneko Osaba,Eneko Osaba,Xin-She Yang,Fernando Diaz,Enrique Onieva,Antonio D. Masegosa,Asier Perallos +6 more
TL;DR: This work has tackled a real-world newspaper distribution problem with recycling policy as an asymmetric and clustered vehicle routing problem with simultaneous pickup and deliveries, variable costs and forbidden paths (AC-VRP-SPDVCFP), which is the first study of such a problem in the literature.
Journal ArticleDOI
Optimal reactive power dispatch with uncertainties in load demand and renewable energy sources adopting scenario-based approach
TL;DR: A formulation and solution procedure for stochastic optimal reactive power dispatch (ORPD) problem with uncertainties in load demand, wind and solar power, and the effectiveness of a proper constraint handling technique is substantiated.
Journal ArticleDOI
Research and application of a hybrid model based on multi-objective optimization for electrical load forecasting
TL;DR: In this paper, a modified generalized regression neural network (GRNN) based on a multi-objective firefly algorithm (MOFA), employed to optimize the initial weights and thresholds of the GRNN, is proposed.
References
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Book
Nature-Inspired Metaheuristic Algorithms
TL;DR: This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms in optimization, including genetic algorithms, bee algorithms, particle swarm optimization, simulated annealing, ant colony optimization, harmony search, and firefly algorithms.
Book ChapterDOI
Firefly algorithms for multimodal optimization
TL;DR: In this article, a new Firefly Algorithm (FA) was proposed for multimodal optimization applications. And the proposed FA was compared with other metaheuristic algorithms such as particle swarm optimization (PSO).
Book
Power System Analysis
TL;DR: This is the first text in this area to fully integrate MATLAB and SIMULINK throughout and provides students with an author-developed POWER TOOLBOX DISK organized to perform analyses and explore power system design issues with ease.
Journal ArticleDOI
Optimal reactive dispatch through interior point methods
TL;DR: An implementation of an interior point method to the optimal reactive dispatch problem is described in this article, which is based on the primal-dual algorithm and the numerical results in large scale networks (1832 and 3467 bus systems) have shown that this technique can be very effective to some optimal power flow applications.
Journal ArticleDOI
Optimal Power Flow By Newton Approach
TL;DR: In this paper, a direct simultaneous solution for all of the unknowns in the Lagrangian function on each iteration is proposed, where each iteration minimizes a quadratic approximation of the Lagrangeian.