Chance-constrained optimal location of damping control actuators under wind power variability

TL;DR

This paper introduces a probabilistic energy-based method for optimally placing damping control actuators in power systems with high wind power penetration, improving dynamic stability under wind variability.

Contribution

It presents a novel chance-constrained optimization approach that efficiently determines optimal EIR locations considering wind variability and dynamic performance.

Findings

The method reduces computational time significantly.

Optimal placement improves damping ratios compared to traditional methods.

The approach is validated on an IEEE-39 bus system with high wind penetration.

Abstract

This paper proposes a new probabilistic energy-based method to determine the optimal installation location of electronically-interfaced resources (EIRs) considering dynamic reinforcement under wind variability in systems with high penetration of wind power. The oscillation energy and total action are used to compare the dynamic performance for different EIR locations. A linear approximation of the total action critically reduces the computational time from hours to minutes. Simulating an IEEE-39 bus system with 30% of power generation sourced from wind, a chance-constrained optimization is carried out to decide the location of an energy storage system (ESS) adding damping to the system oscillations. The results show that the proposed method, selecting the bus location that guarantees the best dynamic performance with highest probability, is superior to both traditional dominant mode analysis and arbitrary benchmarks for damping ratios.