A DYNAMIC CHARACTERIZATION OF POWER-SYSTEM HARMONICS USING MARKOV-CHAINS

This paper presents a probabilistic approach to the characterization o f dynamic properties of harmonies in power systems. In this framework it is assumed that, in addition to a deterministic component, harmonic s contain a stochastic component that is modeled by a Markov chain. Th is mathematically tractable Approach enables a power system analyst to study dynamics of harmonics, while accommodating the possibility that the underlying stochastic process may have a finite memory. The sugge sted framework thus removes the uncorrelatedness (''whiteness'') assum ption for the temporal evolution of harmonics, which is often not supp orted by actual measurements, Mathematical formulas to compute the fir st and second moments of the resulting random waveforms are presented for the practically relevant ease of finite-dimensional discrete-time Markov chains. The approach is illustrated on computer simulations and on actual data taken from a residential load.