Stochastic Small-Signal Stability Analysis of Grid-Connected Photovoltaic Systems

As the penetration level of photovoltaic (PV) generators into the grid is rapidly increasing, the effect of a variable PV power output on the stability of power systems cannot be ignored. Due to the stochastic characteristics of PV power generation, deterministic analysis approaches are not able to fully reveal the impact of high-level PV integration. This paper investigates the impact of the stochastic PV generation on the dynamic stability of grid-connected PV systems by using a probabilistic small-signal analysis approach. The sensitivity of the critical eigenvalue to the variation of solar irradiance is obtained. With the knowledge of the sensitivity relationship and the statistics of solar irradiance data, the probability density function (pdf) of the real part of the critical eigenvalue is approximated by Gram-Charlier expansion. This pdf is then used to calculate the probability of the stochastic small-signal stability of a power system. The impacts of important system parameters on the stochastic stability of the system are also analyzed. It has been found that these system parameters can significantly affect the stochastic stability of the system. Results of Monte Carlo and time-domain simulations of the grid-connected system verify the effectiveness of the proposed stochastic stability analysis method.