Abstract

In electric power systems, integration of more Distributed Generators (DGs) in the network increase the short circuit level due to the short circuit current contribution of the DGs during faults. As compared to the synchronous and induction machine based generators, the inverter based generators, such as Photovoltaic (PV) solar systems, contributes lower fault current to the network due to the characteristics of PV panels and inverter operation. Although, each PV solar farm may contribute short currents as above, the total amount of fault current contribution may become unacceptably large for a feeder which has several PV systems connected. It is apprehended that short circuit current contributions from multiple solar systems in the distribution feeders may add up to levels that could be damaging to the circuit breakers. As a first step, adequate modeling of PV solar plants for predicting their short circuit contributions during network faults is essential. So far, the above fast faults detection techniques have been used for protection of network and DGs; and for unsymmetrical fault detection in fault current limiters (FCL). However these techniques have not been used to prevent any short circuit current contribution in excess of the rated or utility-acceptable current output of PV solar inverters. In this paper, a new fast detection module for short-circuit current detection has been discussed based on the rate of rise of current together with the current magnitude in a PV solar system based DG. There can be two control operations, as per the applicable grid code in that region, one of which is the disconnection of the PV inverter before the current exceeds the rated output current of the inverter. The second one discusses about transforming the PV inverter into a dynamic reactive power compensator STATCOM and provide grid support functions. A new concept of utilizing PV solar farms as STATCOM (PV-STATCOM) both during nighttime and daytime for different grid support functions was introduced in this paper.

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