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A Comparative Analysis on Economic Load Dispatch Problem Using Soft Computing Techniques

A Comparative Analysis on Economic Load Dispatch Problem Using Soft Computing Techniques
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Author(s): O.V. Singh (Gautam Buddha University, Greater Noida, India) and M. Singh (Gautam Buddha University, Greater Noida, India)
Copyright: 2020
Volume: 12
Issue: 2
Pages: 24
Source title: International Journal of Software Science and Computational Intelligence (IJSSCI)
Editor(s)-in-Chief: Brij Gupta (National Institute of Technology, Kurukshetra, India) and Andrew W.H. Ip (University of Saskatchewan, Canada)
DOI: 10.4018/IJSSCI.2020040104

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Abstract

This article aims at solving economic load dispatch (ELD) problem using two algorithms. Here in this article, an implementation of Flower Pollination (FP) and the BAT Algorithm (BA) based optimization search algorithm method is applied. More than one objective is hoped to be achieve in this article. The combined economic emission dispatch (CEED) problem which considers environmental impacts as well as the cost is also solved using the two algorithms. Practical problems in economic dispatch (ED) include both nonsmooth cost functions having equality and inequality constraints which make it difficult to find the global optimal solution using any mathematical optimization. In this article, the ELD problem is expressed as a nonlinear constrained optimization problem which includes equality and inequality constraints. The attainability of the discussed methods is shown for four different systems with emission and without emission and the results achieved with FP and BAT algorithms are matched with other optimization techniques. The experimental results show that conferred Flower Pollination Algorithm (FPA) outlasts other techniques in finding better solutions proficiently in ELD problems.

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