Chance-constrained optimal location of damping control actuators under wind power variability
For power system operators, this method provides a computationally efficient way to place damping controllers under high wind penetration, improving dynamic stability.
This paper proposes a probabilistic energy-based method to optimally locate damping control actuators (EIRs) under wind variability, reducing computational time from hours to minutes via linear approximation. On an IEEE-39 bus system with 30% wind power, the method outperforms traditional dominant mode analysis and arbitrary benchmarks in damping performance.
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.