Stochastic Power System Simulation Using the Adomian Decomposition Method
For power system engineers, it offers a faster analytical method for stability analysis under uncertainty, though it is incremental.
The paper proposes a stochastic simulation approach using the Adomian decomposition method for power system stability analysis with stochastic loads, achieving better time performance and comparable accuracy compared to the Euler-Maruyama method on the New England 10-machine 39-bus system.
Considering increasing distributed energy resources and responsive loads in smart grid, this paper proposes a stochastic simulation approach for stability analysis of a power system having stochastic loads. The proposed approach solves a stochastic, nonlinear differential equation model of the system in an analytical way by the Adomian decomposition method and generates semi-analytical solutions that express both deterministic and stochastic state variables explicitly as symbolic variables so as to embed stochastic processes directly into the solutions for efficient stability analysis with uncertainties. The proposed approach is tested on the New England 10-machine 39-bus system with different penetration levels of stochastic loads. The approach is also benchmarked with a traditional stochastic simulation approach based on the Euler-Maruyama method. The results show that the new approach has better time performance and a comparable accuracy.