NDLI: Comparison of Intelligent Techniques to Solve Economic Load Dispatch Problem with Line Flow Constraints

Content Provider	IEEE Xplore Digital Library
Author	Karthikeyan, S.P. Palanisamy, K. Varghese, L.J. Raglend, I.J. Kothari, D.P.
Copyright Year	2009
Description	Author affiliation: Christian College of Engineering and Technology, Oddanchatram, Dindigul District, Tamil Nadu, INDIA. (Varghese, L.J.) \|\| School of Electrical Sciences, VIT University, Vellore, Tamil Nadu. 632014, INDIA. e-mail: kpalanisamy79@yahoo.co.in (Palanisamy, K.) \|\| School of Electrical Sciences, VIT University, Vellore, Tamil Nadu. 632014, INDIA. e-mail: spk25in@yahoo.co.in (Karthikeyan, S.P.) \|\| Christian College of Engineering and Technology, Oddanchatram, Dindigul District, Tamil Nadu, INDIA. e-mail: jacobraglend@rediffmail.com (Raglend, I.J.) \|\| Vice Chancellor, VIT University, Vellore, Tamil Nadu. 632014. INDIA. e-mail: dpk0710@yahoo.com, vc@vit.ac.in (Kothari, D.P.)
Abstract	A comparative analysis using different intelligent techniques has been carried out for the Economic Load Dispatch (ELD) problem considering line flow constraints for the regulated power system to ensure a practical, economical and secure generation schedule. The objective of this paper is to minimize the total production cost of the thermal power generation. Economic Load Dispatch (ELD) has been applied to obtain optimal fuel cost. Optimal Power Flow has been carried out to obtain ELD solutions with minimum operating cost satisfying both unit and network constraints. In this paper, various intelligent techniques such as Genetic Algorithm (GA), Evolutionary Programming (EP), Particle Swarm Optimization (PSO), and Differential Evolution (DE) have been applied to obtain ELD solutions. The proposed algorithm has been tested on two sample systems viz IEEE 30 bus system and a 15 unit system. The results obtained by the various intelligent techniques are compared. The solutions obtained are quite encouraging and useful in the economic environment. The algorithm and simulation are carried out using Matlab software.
Starting Page	446
Ending Page	452
File Size	4948332
Page Count	7
File Format	PDF
ISBN	9781424429271
DOI	10.1109/IADCC.2009.4809052
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-06
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Power generation economics Power system economics Genetic Algorithm Power generation dispatch Environmental economics Load flow analysis Power system analysis computing Differential Evolution Production Fuel economy Cost function Evolutionary Programming Power generation Particle Swarm Optimization Economic Load Dispatch
Content Type	Text
Resource Type	Article

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