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This paper proposes a new probabilistic energy-based method to determine theoptimal installation location of electronically-interfaced resources (EIRs)considering dynamic reinforcement under wind variability in systems with highpenetration of wind power. The oscillation energy and total action are used tocompare the dynamic performance for different EIR locations. A linearapproximation of the total action critically reduces the computational timefrom hours to minutes. Simulating an IEEE-39 bus system with 30% of powergeneration sourced from wind, a chance-constrained optimization is carried outto decide the location of an energy storage system (ESS) adding damping to thesystem oscillations. The results show that the proposed method, selecting thebus location that guarantees the best dynamic performance with highestprobability, is superior to both traditional dominant mode analysis andarbitrary benchmarks for damping ratios.

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