Quasi-Monte Carlo Simulation Based Economic Dispatch with Wind Power Integrated

This paper proposes a Quasi-Monte Carlo (QMC) simulation based multi-objective economic dispatch, which aims to reduce the fuel cost and emission of the grid simultaneously. During the simulation, QMC models the stochastic behaviours of wind speed and distributed loads with low-discrepancy sequences. In comparison with conventional Monte Carlo (MC) simulation, the computational complexity of QMC is greatly reduced as it only uses a small number of scenarios to simulate the environmental uncertainties. Meanwhile, a multi-objective optimization algorithm, Group Search Optimizer with Multiple Producers (GSOMP), is adopted to solve the economic dispatch. In order to evaluate the proposed dispatch scheme, simulation studies have been taken on a modified IEEE 30-bus system, which attaches three extra wind farms to the grid. A comprehensive comparison is performed among the results achieved using the proposed method and those obtained by the MC and the deterministic dispatch. Moreover, the trade-off relationship between the fuel cost and emission is also discussed in the experimental studies.