This study proposed a probabilistic methodology based on a confidence interval with the aim of overcoming the limitations of deterministic methods. A stability evaluation technique was required because the output variability of renewable energy can lead to instability of the distribution system. The proposed method can predict the possibility of violating stability in the future. It can also provide a theoretical basis for securing distribution system stability and improving operational efficiency by assessing the in-stability risk and worst-case scenarios. Because of steady-state analysis in the distribution system to which solar power is connected, the probability of violating the standard voltage during the daytime when PV fluctuations are severe was the highest. Moreover, as a result of a simulation of a three-phase short-circuit in the distribution system that is connected to the PV and WT, it was observed that it could violate the allowable capacity of the CB owing to the effects of the power demand pattern and output variability.
In general, a temporary overvoltage (TOV) on the healthy phases occurs because of the neutral-shift phenomenon during a single line-to-ground (SLG) fault. The TOV can destroy the insulation of electric devices and cause damage to other equipment and customer loads in just a few cycles. In practice, the TOV can be affected by numerous factors: the sequence reactance ratio of the interconnection transformer, the ratio of load to DG, and the distance to the fault. More importantly, inverter-based distributed generations (DGs) have different influences on the TOV from traditional synchronous-machine-based DGs. In this sense, this work performed an efficient and comprehensive investigation on the effect of these various parameter types and their extensive variations, based on steady-state analysis with sequence equivalent circuits and three-dimensional representations. The proposed methodology can facilitate judging the impact of multi-parameter conditions on the TOV readily and comparing the fault characteristics of synchronous-machine-based and inverter-based DGs. Finally, the results can be used for future studies on TOV mitigation techniques.
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