Optimal Scheduling of Short-Range Fixed Head Hydro-Thermal Systems

Abstract

Abstract Optimum scheduling of power plant generation is of great importance to electric utility systems. The optimal scheduling of an electric power system is the determination of the generation for every plant such that the total system generation cost is minimum while satisfying the system constrains. However due to insignificant marginal cost of hydroelectric power, the problem of minimizing the operational cost of a hydrothermal system essentially reduces to that of minimizing the fuel cost for thermal plants under the constraints of the generating limits and water available. The problem of optimal economic operation of hydrothermal electric power systems with fixed head hydro plants is considered. The implementation is based on a Approximate Newton's iterative procedure, with special initial guess and sparsity-based matrix manipulations to obtain improved convergence properties. Approximate Newton Raphson method is developed and demonstrated to solve the hydrothermal scheduling problem with quadratic thermal cost function together with and without valve point loading effect. ANN (artificial neural network) models are faster as compared to conventional method (Approximate Newton Raphson Method) and provide accurate result as close to the conventional methods. Here error back propagation method is used to solve the hydro thermal scheduling with and without valve point loading.