Control of the Power Flows of a Stochastic Power System

TL;DR

This paper develops a control method for stochastic power systems to ensure phase-angle differences stay within safe limits with high probability, using Brownian motion models and numerical simulations.

Contribution

It introduces a novel control approach for stochastic power systems modeled with Brownian motion, ensuring safety constraints are met with probabilistic guarantees.

Findings

Control method successfully maintains phase-angle differences within safe bounds.

Numerical results demonstrate improved system performance under the proposed control.

Applicable to various network topologies like ring and grid networks.

Abstract

How to determine the vector of power supplies of a stochastic power system for the next short horizon, such that the probability is less than a prespecified value that any phase-angle difference of a power line of the power network exits from a safe set? The power system is modelled such that the differential equation of each frequency is affected by a Brownian motion process. A safe set can be selected to be any subset of the interval $(-\pi/2, ~ +\pi/2)$, which is a sufficient condition for not losing synchronization. That the controlled system has an improved performance is shown by numerical results of three academic examples including a particular eight-node academic network, a twelve-node ring network, and a Manhattan-grid network.