From: A systematic review of real-time detection and classification of power quality disturbances
Type of technique | Advantages | Disadvantages | Application | |||||
---|---|---|---|---|---|---|---|---|
Multiple PQDs | Sags | Notches | ||||||
Refs | % | Refs | % | Refs | % | |||
Handcrafted | Simple application Physical interpretation Fast operation | Inaccuracy Expert knowledge needed Time-consuming design | [33] | 1 | 9 | – | 0 | |
Probabilistic | Simple application Sound theoretical foundation Physical interpretation | Difficult modeling and implementation | 7 | 7 | – | 0 | ||
Shallow ANN | Flexibility Detailed knowledge of the phenomena is not required Able to solve nonlinear functions | Time-consuming training Extensive data for training Handcrafted feature extraction | [37,38,39, 44, 46,47,48, 52, 53, 56, 57, 62, 64, 65, 71, 79, 81,82,83,84,85, 89, 90, 93,94,95, 100, 102, 106,107,108, 113, 123] | 33 | 13 | – | 0 | |
Deep ANN | Flexibility Detailed knowledge of phenomena is not required Able to solve nonlinear functions Automatic feature extraction | The very high computational burden for training Extensive computations during operation hinder real-time applications | 10 | 20 | – | 0 | ||
Decision tree | Very simple application Efficiency for real-time application Robustness to outliers and noisy data | Complex decision trees can be difficult to understand Complexity increases exponentially with the size of the tree | [42, 49, 66, 70, 72, 75, 77, 79, 80, 85, 87, 89, 91, 96,97,98,99, 101, 102, 104,105,106, 109, 112, 114, 117, 122, 126, 128] | 30 | 7 | [200] | 4 | |
SVM | Sound theoretical foundation Only a dozen examples for training are required | Computational inefficiency Low scalability | [47, 50, 51, 59, 60, 63, 69, 74, 76, 86, 88, 92, 98, 101, 102, 110, 114, 115, 127] | 19 | 11 | [211] | 4 | |
k-NN | Very simple application Ease understanding | Reduced accuracy Sensitive to the choice of k | 4 | 4 | – | 0 | ||
Fuzzy logic | Better representation of expert knowledge Physical interpretation of events Robustness to noisy data | Reduced accuracy No systematic It depends on human knowledge A lot of testing is necessary | 10 | [132] | 2 | [189] | 4 |