Machine Learning Techniques Applied to On-Line Voltage Stability Assessment: A Review

Artificial Intelligence Techniques in Smart Grid: A Survey

“…Liu et al [121] built a feature selection model using partial mutual information (PMI) on an iterated random forest (IRF) model. An in-depth review is also found in Amroune [122]. Table 2 summarizes the AI techniques for the power system stability assessment.…”

“…To improve the accuracy of line trip fault prediction, Wang et al [131] proposed a stacked sparse autoencoder-based network with SVM and PCA to demonstrate its application to real-world data. [106] 2017 TSA ELM, TF Tan et al [108] 2017 TSA CNN, SAEs Liu et al [109] 2017 TSA Ensemble, NN, ELM Ashraf et al [115] 2017 VSA ANN Amroune et al [118] 2017 VSA SVR, FL Baltas et al [99] 2018 TSA Decision tree, SVM, ANN Mosavi et al [105] 2018 TSA ANN Yu et al [107] 2018 TSA RNN, LSTM Amroune et al [119] 2018 VSA SVR Mohammadi et al [116] 2018 VSA SVM Hu et al [104] 2019 TSA SVM Wang et al [14] 2019 FSA ELM Kamari et al [114] 2019 OSA PSO Amroune et al [122] 2019 VSA Survey Wang et al [110] 2020 TSA DBN Shi et al [111] 2020 TSA CNN Shi et al [111] 2020 OSA CNN Xiao et al [113] 2020 OSA MRFR Yang et al [120] 2020 VSA Spectrum estimation method Meng et al [117] 2020 VSA Decision tree Liu et al [121] 2021 VSA Random Forest…”

Techniques of power system static security assessment and improvement: A literature survey

“…Among several operational concerns, power system security is critical due to the substantial social, economic, and political impact it can have when it is threatened [ 7 ]. One blackout incident brought on by human error or component outage due to line overloading may cause multi-billion economic loss and other difficult-to-measure catastrophes [ 3 , 8 ].…”

“…The purpose of dynamic security assessment (DSA) is to identify and evaluate contingencies that may cause transient (angle), frequency or voltage instabilities by evaluating the time dependent transition from the pre-contingent to post contingent steady state [ 28 , 29 ]. Methods such as continuous power flow solutions of P –V or Q-V curves, modal analysis, or computation of voltage stability margin for voltage stability [ 8 ], time-domain simulation for transient stability, and analysis of eigenvalues for small signal stability are used to carry out DSA [ 30 , 31 ]. To prepare appropriate preventive and corrective measures that can maintain system security, simulations covering several operating conditions (obtained from different combinations of load demand and generated power) and contingencies must be performed [ 32 ].…”

“…Data-driven artificial intelligence (AI) techniques such as fuzzy inference systems [ 29 , 33 ], Artificial Neural Network ( ), support vector machine (SVM) [ 14 ], decision tree (DT), graph convolutional neural network [ 34 ], cascaded convolutional network [ 35 ] and long short-term memory network ( ) [ 30 ] have been widely employed to overcome the limitations of classical model-driven simulation approaches in DSA [ 3 ]. Due to their capacity to tackle nonlinear problems with remarkable speed and accuracy, these and other AI approaches have attracted the researchers’ attention [ 8 ].…”