Stochastic Power System Simulation Using the Adomian Decomposition Method

TL;DR

This paper introduces a semi-analytical stochastic simulation method for power system stability analysis using the Adomian decomposition, offering improved efficiency over traditional methods.

Contribution

It presents a novel analytical approach for stochastic power system simulation that explicitly incorporates uncertainties and outperforms traditional numerical methods in speed.

Findings

Better computational efficiency than Euler-Maruyama method

Comparable accuracy in stability analysis

Effective handling of stochastic loads in power systems

Abstract

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.