The converter is a crucial part of the doubly fed induction generator (DFIG) wind energy conversion system (WECS). Breakdown of the converter will lead to huge economic loss; this is relating to the downtime of the converter that will shut down the whole turbine-generator system and curtail the energy production. Fault diagnosis is considered a preliminary tool that is used to tackle the possibilities of converter downtime. There are varieties of fault diagnosis techniques and algorithms for different faults types and location. This paper is presenting an enhanced technique based on the possibility of combining the DFIG currentmeasurements and torque to develop a robust FD technique for DFIG converter systems. The results obtained from the simulation phase is encouraging to merge fault indicators from current and torque to identify the fault location and nature at either side of the DFIG converters.

Power electronic systems such as inverters play a vital role in today's life serving various applications. It has a great impact on renewable power integration and energy savings techniques. Condition monitoring of these devices is challenging due to several factors like accessibility of physical components. There are various faults which affects the inverter performance and cause shutdown if not diagnosed and rectified early enough. Fault diagnosis is a critical reliability tool to minimize the inverter's operation downtime. There are several approaches of inverter fault diagnosis. However, this paper presents a new fault diagnosis technique for multi-switch open circuit faults using the load current average and rms, the method centred around using fuzzy logic based identifications technique to identify the faulty switch. The results show the capability of the developed technique in accurately identifying the faults in a single switch as well as multiple switches in different phases.

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