DC-side fault detection for photovoltaic energy conversion system using fractional-order dynamic-error-based fuzzy Petri net integrated with intelligent meters

作者：Chen Jian Liung; Kuo Chao Lin; Chen Shi Jaw; Kao Chih Cheng; Zhan Tung Sheng; Lin Chia Hung^*; Chen Ying Shin

来源：IET Renewable Power Generation, 2016, 10(9): 1318-1327.

DOI：10.1049/iet-rpg.2015.0517

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.

• 出版日期2016-10