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This paper presents a new approach for developing a hybrid algorithm for solving the Unit Commitment Problem (UCP) in a Hydro-thermal power system. Unit Commitment is a nonlinear optimization problem to determine the minimum cost turn on/off schedule of the generating units in a power system by satisfying both the forecasted load demand and various operating constraints of the generating units. Tabu search (TS) is a powerful optimization procedure that has been successfully applied to a number of combinatorial optimization problems. It avoids entrapment at local optimum by maintaining a short term memory of recently obtained solutions. The memory structure assists in forbidding certain moves that deteriorates the quality of the solution by assigning Tabu status to the forbidden solutions. The Tabu status of a solution can be overruled if certain conditions are satisfied expressed in the form of Aspiration Level. Aspiration Level (AL) adds flexibility in Tabu Search by directing the search towards attractive moves. The effectiveness of the proposed hybrid algorithm is proved by the numerical results shown comparing the generation cost solutions and computation time obtained by using Tabu Search Algorithm with other methods like Evolutionary Programming and Dynamic Programming in reaching proper unit commitment.

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