Research challenges in real-time classification of power quality disturbances applicable to microgrids: A systematic review. (October 2020)

• Record Type: Journal Article
• Authors: Igual, R.; Medrano, C.
• Is Part Of: Renewable & sustainable energy reviews. Volume 132(2020)
• Publication Date: 2020-10
• Subjects: Real-time -- Power quality -- Classification -- Power systems -- Smart infrastructure -- Microgrids; Acc Accuracy -- ADALINE Adaptative linear element -- ADC Analog-to-digital converter -- ALU Arithmetic logic unit -- AMD Advanced micro devices -- ATP Alternative transients program -- BP Bagging predictor -- Combd Combined -- CPU Central processing unit -- CT Clarke transform -- CWT Continuous wavelet transform -- CVC Common vector classifier -- DR Decision rule -- DT Decision tree -- DSP Digital signal processor -- DAG-SVM Directed acyclic graph support vector machine -- DHT Discrete Hilbert transform -- DWT Discrete wavelet transform -- DG Distributed generation -- DDWT Discreet dyadic wavelet transform -- DRST Double-resolution Stockwell transform -- DTW Dynamic time warpping -- EMTDC Electromagnetic transients including direct current -- EMTP Electromagnetic transients program -- EMD Empirical mode decomposition -- EEMD Ensemble empirical mode decomposition -- E Euclidean norm -- ELM Extreme learning machine -- Feat Feature -- FM-DWT Fast match-dynamic time warping -- FDST Fast discrete Stockwell transform -- FF-NN Feed forward neural network -- FPGA Field-programmable gate array -- FT Fourier transform -- FRFT Fractional Fourier transform -- FmA Frequency maximum amplitude -- FF Fundamental frequency -- FCM Fuzzy C-mean -- GB Gigabyte -- GHz Gigahertz -- GPRS General packet radio service -- GPU Graphical processing unit -- GT Gabor transform -- GWT Gabor-Wigner transform -- HDL Hardware description language -- HMM Hidden Markov model -- HHT Hilbert-Huang transform -- HT Hilbert transform -- HST Hyperbolic Stockwell transform -- IA Instantaneous amplitude -- IF Instantaneous frequency -- IMF Intrinsic mode function -- I/O Input / Output -- k-NN k-Nearest neighbor -- Lab Laboratory setup -- LVQ Learning vector quantization -- LS-SVM Least square support vector machine -- LHD Lower harmonic distortion -- LUT Look up table -- MB Megabyte -- MHz Megahertz -- MO-DWT Maximal overlap discrete wavelet transform -- MED Minimum euclidean distance -- MFMM Modified fuzzy min-max clustering -- MST Modified Stockwell transform -- MTD-NN Modified time-delay neural network -- MLP Multilayer perceptron -- MRA Multiresolution analysis -- MG-ST Multiresolution generalized Stockwell transform -- MSVM Multi support vector machine -- NN Neural network -- OPA Orthogonal polynomial approximation -- OpenCL Open computing language -- PSO Particle swarm optimization -- PC Personal computer -- PLC Power line communications -- PQ Power quality -- PSCAD Power systems computer-aided design -- PCA Principal component analysis -- PNN Probabilistic neural network -- RBF Radial basis function network -- RAM Random access memory -- RT Real-time -- RTDS Real-time digital simulator -- RMS Root mean squared -- RMSE Root mean squared error -- SOLAR Self-organizing learning array -- STFT Short time Fourier transform -- SNR Signal-to-noise ratio -- Simul Simulated -- SPWVD Smoothed pseudo Wigner-Ville distribution -- SSD Sparse signal decomposition -- SD Standard deviation -- S-matrix Stockwell-matrix -- ST Stockwell transform -- BNT Supervised balanced neural tree -- SVM Support vector machine -- Synth Synthetic -- TLBN Three-level multiply connected Bayesian network -- TBM Threshold-based method -- TF Time frequency -- TFST Time–frequency-scale transform -- THD Total harmonic distortion -- TmA Time maximum amplitude -- TTT Time-time transform -- Tx Transmission -- μC Microcontroller -- VMD Variational mode decomposition -- VHDL VHSIC hardware description language -- WT Wavelet transform -- WP Wavelet packet -- WBELM Weighted bidirectional extreme learning machine -- WD Wigner distribution -- WD-FT Windowed discrete Fourier transform; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2020.110050
• Languages: English
• ISSNs: 1364-0321

Abstract

Abstract: Microgrids with distributed renewable energy sources are especially sensitive to power quality disturbances. To mitigate the effects of distortions, they must first be detected and classified. Automatic classification of power quality disturbances has been extensively studied. However, real-time classification is yet to be investigated. Real-time classification is especially important in microgrids as they include a large number of subsystems. This paper presents a critical systematic review focused specifically on real-time applications. For this review, 809 papers were identified and the most cited papers of each year were analyzed in detail, i.e., a total of 134 papers were analyzed. Studies on all types of power systems were considered as their distortions can be observed in microgrids. These studies were categorized into three groups depending on their real-time abilities, and a comprehensive analysis to examine key items was performed. Subsequently, the research challenges in real-time operation were identified, i.e., extracting a reduced number of discriminant features with minimal processing, achieving a balance between classification accuracy and computational complexity, using datasets with more types of disturbances, including more types of combined disturbances, using real data to validate the classifiers, distributing public comprehensive datasets, embedding classifiers in dedicated hardware, improving the performance of real-time classification systems, conducting objective real-time analyses in physical devices, and setting a common evaluation framework to objectively compare real-time operations. These research challenges must be tackled to obtain a viable, accurate, fast, low-cost, and embeddable power quality classification system that facilitates the inclusion of distributed renewable energy sources in microgrids. Graphical abstract: Image 1 Highlights: First review on real-time classification of power quality disturbances (PQD). After several systematic searches, a growing trend in research was identified. Few studies embed the classifiers in dedicated hardware, with low performance. Requirement for a common framework to evaluate real-time operation. Challenges: real PQD, public datasets, balancing real-time operation with accuracy.