News Updates Monday 25th Nov 2024 :
  • Welcome to INPRESSCO, world's leading publishers, We have served more than 10000+ authors
  • Articles are invited in engineering, science, technology, management, industrial engg, biotechnology etc.
  • Paper submission is open. Submit online or at editor.ijcet@inpressco.com
  • Our journals are indexed in NAAS, University of Regensburg Germany, Google Scholar, Cross Ref etc.
  • DOI is given to all articles

A Solution to Unit Commitment Problem via Dynamic Programming and Particle Swarm Optimization


Author : S.Usha Rani and C. H. Padmanabha Raju

Pages : 1495-1503
Download PDF
Abstract

The optimization problem while committing the units is minimizing the entire production cost, at the same time meeting the demand and fulfilling the equality and inequality limits. In order to supply adequate power to the consumers in a cost-effective and secured way the commitment of thermal units is the best option available. The commitment of generating units is done depending upon the prediction of upcoming demand. For getting a way out to the unit commitment problem there are numerous conventional and advanced programming practices used. For solving the deterministic problem the conventional dynamic programming algorithm is employed. In this paper DP is used to solve the unit commitment problem. In this paper Particle swarm optimization technique is used which is population based global searching optimization technique to solve the unit commitment problem, for committing the units optimally. It is arrived from the exploration on the bird and fish flocking movement behavior. For the straightforward implementation of the algorithm it is extensively used and rapidly developed and few particles are needed to be attuned. An algorithm was developed to attain a way out to the unit commitment problem using Particle Swarm Optimization technique. The effectiveness of the algorithm was tested on two test systems. The first system comprising of three units and the second system is an IEEE 30-bus system and the attained results using the two methods are compared for total operating cost.

Keywords: Unit Commitment, Dynamic Programming, Particle Swarm Optimization Algorithm

Article published in International Journal of Current  Engineering  and Technology, Vol.3,No.4(Oct- 2013)

 

 

 

Call for Papers
  1. IJCET- Current Issue
  2. Issues are published in Feb, April, June, Aug, Oct and Dec
  3. DOI is given to all articles
  • Inpressco Google Scholar
  • Inpressco Science Central
  • Inpressco Global impact factor
  • Inpressco aap

International Press corporation is licensed under a Creative Commons Attribution-Non Commercial NoDerivs 3.0 Unported License
©2010-2023 INPRESSCO® All Rights Reserved