Abstract
Fault occurrence or voltage disturbance, such as mismatch operations or electrical faults caused by structural changes in photovoltaic (PV) panels, local/remote faults, or heavy load operation, can disturb a PV energy conversion system (PVECS) on both the DC and AC sides. On the AC side, any serious disturbance can be isolated using power fuses, overcurrent protection and ground-fault protection devices. Therefore, the authors propose the use of fractional-order dynamic-error-based fuzzy Petri net (FPN) to detect disturbance events in a microdistribution system. PV energy conversion depends on solar radiation and temperature, and a maximum power point tracking control is used to maintain stable output power and voltage to microdistribution loads. When the desired maximum power is estimated, a bisection approach algorithm is used to regulate the output voltage of the PVECS by adjusting the duty ratios of a buck–boost converter. The maximum power drops, which are compared with meter-reading power from intelligent meters, are used to detect faults on the DC side. Then, fractional-order dynamic errors between the desired and estimated powers and a FPN are employed to detect faults. For a small-scale PVECS, computer simulations are conducted to show the effectiveness of the proposed model.
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