Neural Based Tabu Search method for solving unit commitment problem with cooling-banking constraints

摘要

This paper presents a new approach to solve short-term unit commitment problem (UCP) using Neural Based Tabu Search (NBTS) with cooling and banking constraints. 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 next H hours. A 7-unit utility power system in India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different IEEE test systems consist of 10, 26 and 34 units. Numerical results are shown to compare the superiority of the cost solutions obtained using the Tabu Search (TS) method, Dynamic Programming (DP) and Lagrangian Relaxation (LR) methods in reaching proper unit commitment.