An evolutionary programming based tabu search method for solving the unit commitment problem in utility system

This paper presents a new approach to solving the short-term unit commitment problem in utility system using an evolutionary programming based tabu search method. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for the next H hours. Evolutionary programming, which happens to be a global optimization technique for solving unit commitment problem, operates on a system, which is designed to encode each unit´s operating schedule with regard to its minimum up/down time. The best population is selected by evolutionary strategy. A 66-bus utility power system with twelve generating units in India demonstrates the effectiveness of the proposed approach. Numerical results are shown comparing the cost solutions and computation time obtained by using the evolutionary programming method and other conventional methods like dynamic programming, Lagrangian relaxation and tabu search in reaching proper unit commitment.