Skip to main content

Absolutely Stochastic Simulated Annealing Approach to Large Scale Unit Commitment Problem

Buy Article:

$55.00 plus tax (Refund Policy)

This paper presents a new approach to the unit commitment problem using the absolutely stochastic simulated annealing method. In each iteration, a solution is taken with a certain probability. Typically, in the simulated annealing minimization method, a higher cost feasible solution is accepted with temperature-dependent probability, but other solutions are accepted deterministically. That may lead to the near optimization slowly. However in this paper, all the solutions, both higher and lower cost, are associated with acceptance probabilities. Besides, the number of bits flipping is decided by an appropriate distribution. Excess units with system-dependent probability distribution handle constraints efficiently. To reduce the economic load dispatch (ELD) overhead recalculations, a sign bit vector is introduced as well. The proposed method is tested using the reported problem data sets. Simulation results for the systems up to 100 units are compared to the previous reported results. Numerical results show an improvement in solution cost and time over to the results obtained from recent powerful algorithms.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: genetic algorithm; probability distribution; simulated annealing; unit commitment

Document Type: Research Article

Affiliations: 1: University of the Ryukyus, Okinawa, Japan 2: Meidensha Corporation, Tokyo, Japan

Publication date: 2006-06-01

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more