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

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

O.V. Singh (Gautam Buddha University, Greater Noida, India) and M. Singh (Gautam Buddha University, Greater Noida, India)
DOI: 10.4018/IJSSCI.2020040104
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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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1. Introduction

Nowadays, cloud computing, Big Data, and the internet of things (IoT) have become inseparable parts of modern communication and information systems. They cover various aspects of society like business, industry, finance, management, and manufacturing along with various other information and communication. Hence, it is highly necessary to remain in touch with the latest advancements, applications, current issues and challenges (Gupta & Agrawal, 2019). Soft computing techniques across the globe are used for research and development, specifically in the advancement of computing technologies and overlapping areas that are essential to take care of various research challenges in this area. In order to do so, collection of high-quality articles of recently reported research advancement in applying soft computing techniques for big data and cloud computing, engaging many topics of interest, is done (Gupta et al., 2018). To minimize the overall cost, response time and load on service provider, simulation-based deployment of the algorithms along with a comparison study with other known algorithms is done which form the field, confirms the ability of the proposed algorithm to perform best (Manasrah et al., 2019).

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