# Smart Inverters for Microgrid Applications: A Review
## 2 Smart Inverters
### Self-Awareness  
In the definition of smart inverter, self-awareness is another key concept to be considered. In simple words, this means that the inverter is aware of its possible faulty parts, can determine their exact location, work out the cause of the fault, and be able to isolate them. In addition, the ability to predict possible future fault occurrences to program preventive maintenance is essential. Self-awareness can be divided into three different, yet closely related concepts [34; 63; 64]:  
* Diagnostics so the inverter finds out the reason and origin of a fault after the occurrence.
* Condition monitoring (CM) which is a real-time evaluation of the component health status.
* Prognosis to estimate if a fault is going to happen in the future and when.  
These three methods rely on fault detection procedures. For diagnostics, it is obvious that in order to work out the reason for a fault, at first, it needs to happen and be detected. For CM and prognosis, a fault or an initiation of a fault needs to be located in order to prevent the complete system to shut down or even worse. However, there are several challenges accompanied by this procedure. One problem is the effect of continuous measurements. The three concepts require measurements and it is a well-known fact that measurements cannot always be taken without interrupting the normal operation of the device. In addition, the process of deriving health indicators from physical measurements and furthermore extract prediction indicators from them can be complex [63; 64].  
Inverter faults are mostly triggered by thermomechanical fatigue in IGBTs [65]. They are commonly classified as, open-circuit faults, short-circuit faults and intermittent gate signal [66; 67]. Detecting short-circuit faults can be easy, since in case of an occurrence, the current will rise to about four or five times the normal value. Therefore, traditional relays can be effective enough to detect and shut down the faulty component. However, the case is very different in open circuit faults, since the increase in current is not that significant, and if the sensitivity of the relays is reduced to the point they can sense these small current fluctuations, false tripping will also occur [68; 69]. The intermittent behavior of RES can also cause false alarms if relays are being used for open-circuit fault detection [68]. Normally, open-circuit faults do not trigger a system shutdown but they cause the system to misbehave or work less efficient. Therefore, they can remain undetected for a long operational time resulting to other faults and further damages to the inverter [67]. As an outcome, it can be stated that open-circuit faults cannot be detected by hardware. However, there are several methods and algorithms available to effectively detect them.  
In general, open circuit fault detection has been categorized into current-based methods and voltage-based methods [70]. One of the pioneering approaches in the first category is [PERSON]'s vector method proposed in [71]. In this method, by applying Park vector transformation on the calculated average 3-phase current, the angle and magnitude of the currents in the complex domain are obtained, and by using pattern algorithms to analyze the trajectory of the space vector deviations, a fault can be identified. The complexity of this method is its main drawback [67; 69]. In addition, this current based method and other similar ones in this category, such as two methods proposed in [72], contain another disadvantageous behavior which is a full one fundamental period delay between the occurrence and the actual detection [73]. Using voltage measurements is another criterion. Here the actual voltages at the key points of the circuit are measured and compared with their reference values derived by analytical models. This method is faster than the current based methods and the fault can be detected in one-fourth of a cycle but since voltage measurement devices are included, it adds to the complexity of the system [69; 70; 73].