Short Term Hydrothermal Scheduling Using Evolutionary Programming

Abstract

Operation of a system having both hydro and thermal plants is far more complex as hydro plants have negligible operating cost, but are required to operate under constraints of water available for hydro generation in a given period of time. The problem of minimizing the operating cost of a hydrothermal system can be viewed as one of minimizing the fuel cost of thermal plants under the constraints of water availability (storage and inflow) for hydro generation over a given period of operation. Earlier, a wide variety of optimization techniques have been applied to solving the Hydrothermal scheduling problems such as dynamic programming (DP), gradient search method etc. But, because of certain drawbacks, such as drastic growth of computational and dimensional requirement, insecure convergence properties, algorithmic complexity, and convergence characteristics these local optimization techniques are not suitable for such a problem. Thus, evolutionary programming has been proposed for solving the Hydrothermal scheduling problems. The work done in this thesis presents solution to short-term hydrothermal scheduling problem. The solution approach is based on Evolutionary programming. Evolutionary programming technique is implemented and demonstrated to solve the hydrothermal scheduling problem with quadratic thermal cost function. The advantage of the EP technique is that it is capable of determining the global or near global optimal solutions to such an optimisation problem with multiple local minima. Evolutionary programming technique provides accurate result as close to the conventional methods. EP algorithms are also capable of finding very nearly global solutions within a reasonable time.