Genetic Algorithm Applications to Stochastic Thermal Power Dispatch

This paper presents a genetic algorithm (GA) based effective method for the optimal scheduling of thermal generation incorporating the uncertainties in the system production cost data. A stochastic model of system production cost equation is formulated, with production cost coefficients and generator outputs as random variables. Minimization of total operating cost for thermal units in the system subjected to recognized constrains is solved using simple genetic algorithm (SGA). The advantages of this method lies in its faster convergence towards the global solution. The algorithm gives fairly accurate results. The effectiveness of the method has been demonstrated by analyzing sample systems and the results are presented.