A Modified ANT Colony Algorithm for Solving the Unit Commitment Problem

Abstract

Solving the unit commitment (UC) problem is one of the most complicated issues in power systems that its exact solving can be calculated by perfect counting of entire possible compounds of generative units. UC is equated as a nonlinear optimization with huge size. Purpose of solving this problem is to programming the optimization of the generative units to minimize the full action cost regarding problem constraints. In this article, a modified version of ant colony optimization (MACO) is introduced for solving the UC problem in a power system. ACO algorithm is a powerful optimization method which has the capability of fleeing from local minimums by performing flexible memory system. The efficiency of proposed method in two power system containing 4 and 10 generative units is indicated. Comparison of obtained results from the proposed method with results of the past well-known methods is a proof for suitability of performing the introduced algorithm in economic input and output of generative units. KEYWORDS Unit Commitment (UC), Nonlinear Optimization, Modified Ant Colony Optimization (MACO) Algorithm, Economic Dispatch (ED), Load Demand.