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Original scientific paper

https://doi.org/10.17559/TV-20150720093711

Solving convex and non-convex static and dynamic economic dispatch problems using hybrid particle multi-swarm optimization

Aamir Nawaz ; Faculty of Engineering & Technology, Gomal University, Dera Ismail Khan-29050, Pakistan
Ehtasham Mustafa ; Faculty of Engineering & Technology, Gomal University, Dera Ismail Khan-29050, Pakistan
Nasir Saleem ; Faculty of Engineering & Technology, Gomal University, Dera Ismail Khan-29050, Pakistan
Muhammad Irfan Khattak ; Faculty of Engineering & Technology, Gomal University, Dera Ismail Khan-29050, Pakistan
Muhammad Shafi ; Faculty of Engineering, University of Science and Technology, Bannu-28100, Pakistan
Abdul Malik ; Faculty of Engineering & Technology, Gomal University, Dera Ismail Khan-29050, Pakistan


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Abstract

Economic Load Dispatch problem has been previously solved successfully with swarm techniques. However, power systems with complex behaviours still await a robust algorithm to be developed for their optimization more precisely. Economic Dispatch problem with constraints such as generator limits, total power demand, ramp rate limits and prohibited operating zones, makes the problem more complicated to solve even for global techniques. To overcome these complications, a new algorithm is proposed called Hybrid Particle Multi-Swarm Optimization (HPMSO). The proposed algorithm has a property of deep search with quite fast response. Convex and Non-convex cost functions along with equality and inequality constraints have been used to evaluate performance of proposed approach. Moreover, Dynamic Economic Dispatch cases have also been included in statistical studies to test the proposed approach even in real time. Different case studies have been accomplished using standard test systems of Static and Dynamic Economic Dispatch. Comparison of proposed approach and previous techniques show that the proposed algorithm has a better performance.

Keywords

convex and non-convex problems; economic dispatch; Hybrid Multi-Particle Swarm Optimization (HPMSO); valve-point effects

Hrčak ID:

185447

URI

https://hrcak.srce.hr/185447

Publication date:

31.7.2017.

Article data in other languages: croatian

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