scholarly journals A Modified ANT Colony Algorithm for Solving the Unit Commitment Problem

2016 ◽  
Vol 3 (2/3) ◽  
pp. 15-27
Author(s):  
Ahmad Zand ◽  
Mehdi Bigdeli ◽  
Davood Azizian
Keyword(s):  
Ant Colony Algorithm ◽  
Unit Commitment ◽  
Ant Colony ◽  
Unit Commitment Problem ◽  
Commitment Problem

Nodal ant colony optimization for solving profit based unit commitment problem for GENCOs

2012 ◽  
Vol 12 (1) ◽  
pp. 145-160 ◽  
Author(s):  
C. Christopher Columbus ◽  
K. Chandrasekaran ◽  
Sishaj P. Simon
Keyword(s):  
Ant Colony Optimization ◽  
Unit Commitment ◽  
Ant Colony ◽  
Unit Commitment Problem ◽  
Commitment Problem

scholarly journals EADPSODV Technique for Solving UC Problem

2019 ◽  
Vol 8 (6) ◽  
pp. 2191-2195
Keyword(s):  
Energy Demand ◽  
Unit Commitment ◽  
Optimization Problems ◽  
Large Family ◽  
Minimum Cost ◽  
Ant Colony ◽  
Unit Commitment Problem ◽  
Robust Solution ◽  
Unit System ◽  
Commitment Problem

Unit Commitment problem (UC) is a large family of mathematical optimization problems usually either match the energy demand at minimum cost or maximize revenues from energy production. This paper proposes a new approach for solving Unit Commitment problem using the EADPSODV technique. In PSODV, the appropriate mutation factor is selected by applying Ant Colony search procedure in which internally a Genetic Algorithm (GA) is employed in order to develop the necessary Ant Colony parameters. In EADPSODV method the advantageous part is that, for determining the most feasible configuration of the control variables in the Unit Commitment. An initial observation and verification of the suggested process is carried on a 10-unit system which is extended to 40-unit system over a stipulated time horizon (24hr). The outcomes attained from the proposed EADPSODV approach indicate that EADPSODV provides effective and robust solution of Unit Commitment.

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