Stochastic Evolutionary Multiobjective Environmental/Economic Dispatch

Power system operation is subject to many uncertainties since acquired data are subject to inaccuracies due to inaccuracies in the process of measuring and forecasting of input data and changes of unit performance during the period between measuring and operation. In the environmental/economic dispatch problem, both fuel cost and emission are to be simultaneously minimized. In this paper, in order to obtain a solution closer to real-world situations, a constrained Monte Carlo sampling scheme is considered with stochastic decision variables, power system loads and objective functions whereby NSGA-II is used for solving the resulting stochastic environmental/economic dispatch problem. Simulation results presented for the standard IEEE 30-bus system show that the optimized system is reliable if stochastic variables are correlated.