Enhanced particle swarm optimization for short-term non-convex economic scheduling of hydrothermal energy systems

Vinay Kumar Jadoun, Nikhil Gupta, K. R. Niazi, Anil Swarnkar

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

This paper presents an Enhanced Particle Swarm Optimization (EPSO) to solve short-term hydrothermal scheduling (STHS) problem with non-convex fuel cost function and a variety of operational constraints related to hydro and thermal units. The operators of the conventional PSO are dynamically controlled using exponential functions for better exploration and exploitation of the search space. The overall methodology efficiently regulates the velocity of particles during their flight and results in substantial improvement in the conventional PSO. The effectiveness of the proposed method has been tested for STHS of two standard test generating systems while considering several operational constraints like system power balance constraints, power generation limit constraints, reservoir storage volume limit constraints, water discharge rate limit constraints, water dynamic balance constraints, initial and end reservoir storage volume limit constraints, valve-point loading effect, etc. The application results show that the proposed EPSO method is capable to solve the hard combinatorial constraint optimization problems very efficiently.

Original languageEnglish
Pages (from-to)1940-1949
Number of pages10
JournalJournal of Electrical Engineering and Technology
Volume10
Issue number5
DOIs
Publication statusPublished - 01-09-2015

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Particle swarm optimization (PSO)
Scheduling
Economics
Exponential functions
Cost functions
Power generation
Mathematical operators
Water

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

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abstract = "This paper presents an Enhanced Particle Swarm Optimization (EPSO) to solve short-term hydrothermal scheduling (STHS) problem with non-convex fuel cost function and a variety of operational constraints related to hydro and thermal units. The operators of the conventional PSO are dynamically controlled using exponential functions for better exploration and exploitation of the search space. The overall methodology efficiently regulates the velocity of particles during their flight and results in substantial improvement in the conventional PSO. The effectiveness of the proposed method has been tested for STHS of two standard test generating systems while considering several operational constraints like system power balance constraints, power generation limit constraints, reservoir storage volume limit constraints, water discharge rate limit constraints, water dynamic balance constraints, initial and end reservoir storage volume limit constraints, valve-point loading effect, etc. The application results show that the proposed EPSO method is capable to solve the hard combinatorial constraint optimization problems very efficiently.",
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Enhanced particle swarm optimization for short-term non-convex economic scheduling of hydrothermal energy systems. / Jadoun, Vinay Kumar; Gupta, Nikhil; Niazi, K. R.; Swarnkar, Anil.

In: Journal of Electrical Engineering and Technology, Vol. 10, No. 5, 01.09.2015, p. 1940-1949.

Research output: Contribution to journalArticle

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