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Journal ArticleDOI

A Hybrid Interior Point Assisted Differential Evolution Algorithm for Economic Dispatch

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TLDR
In this paper, a hybrid algorithm connecting interior point method (IPM) and differential evolution (DE) for solving economic load dispatch problem with valve point effect is proposed, which involves two stages.
Abstract
The paper proposes a novel hybrid algorithm connecting interior point method (IPM) and differential evolution (DE) for solving economic load dispatch problem with valve point effect. The algorithm involves two stages. The first stage employs IPM to minimize the cost function without considering the valve point effect. The second stage considers valve point effect and minimizes the cost function using DE. The initial population for DE is generated in a narrow range of 2π/f around the solution obtained in the first stage. The effectiveness of the algorithm is validated by carrying out extensive tests on three different systems involving 13 and 40 thermal generating units. The proposed method outperforms other existing techniques for economic load dispatch considering valve-point effects.

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Journal ArticleDOI

Quantum-Inspired Particle Swarm Optimization for Power System Operations Considering Wind Power Uncertainty and Carbon Tax in Australia

TL;DR: A computational framework for integrating wind power uncertainty and carbon tax in economic dispatch (ED) model is developed and the probability of stochastic wind power based on nonlinear wind power curve and Weibull distribution is included in the model.
Journal ArticleDOI

Flexible Robust Optimization Dispatch for Hybrid Wind/Photovoltaic/Hydro/Thermal Power System

TL;DR: Robust optimization theory is introduced into optimization dispatch for hybrid wind/photovoltaic/hydro/thermal power systems and concept of uncertainty is introduced to cover shortcoming of conventional robust optimization which is conservative.
Journal ArticleDOI

Neural network methods to solve the Lane–Emden type equations arising in thermodynamic studies of the spherical gas cloud model

TL;DR: Stochastic numerical computing approach is developed by applying artificial neural networks (ANNs) to compute the solution of Lane–Emden type boundary value problems arising in thermodynamic studies of the spherical gas cloud model.
Journal ArticleDOI

Design of unsupervised fractional neural network model optimized with interior point algorithm for solving BagleyTorvik equation

TL;DR: An efficient computing technique has been developed for the solution of fractional order systems governed with initial value problems (IVPs) of the BagleyTorvik equations using fractional neural networks (FNNs) optimized with interior point algorithms (IPAs).
Journal ArticleDOI

Colonial competitive differential evolution

TL;DR: Comparisons show that the CCDE algorithms have good performance and are reliable tools in solving ELD problem and the constraints and operational limitations are considered.
References
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Book

Convex Optimization

TL;DR: In this article, the focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them, and a comprehensive introduction to the subject is given. But the focus of this book is not on the optimization problem itself, but on the problem of finding the appropriate technique to solve it.
Book

Primal-Dual Interior-Point Methods

TL;DR: This chapter discusses Primal Method Primal-Dual Methods, Path-Following Algorithm, and Infeasible-Interior-Point Algorithms, and their applications to Linear Programming and Interior-Point Methods.
Journal ArticleDOI

Genetic algorithm solution of economic dispatch with valve point loading

TL;DR: In this article, a genetic-based algorithm was proposed to solve an economic dispatch problem for valve point discontinuities, which utilizes payoff information of candidate solutions to evaluate their optimality.
Journal ArticleDOI

Evolutionary programming techniques for economic load dispatch

TL;DR: The performance of evolutionary programs on ELD problems is examined and modifications to the basic technique are proposed, where adaptation is based on scaled cost and adaptation based on an empirical learning rate are developed.
Proceedings ArticleDOI

On the usage of differential evolution for function optimization

TL;DR: This paper describes several variants of DE and elaborates on the choice of DE's control parameters, which corresponds to the application of fuzzy rules, and the design of a howling removal unit with DE.
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