Engineering problems | Scientific problems | Difficulty description | Key SML techniques | Role in planning |
---|---|---|---|---|
Large-scale renewable energy grid-connection | (a) High dimensional correlation modeling | (1) A large amount of renewable energy bring dimension disaster to uncertain modeling. | Singular value decomposition && principal component analysis [157] | Uncertainty modeling of decision variables, which includes capacity or location. |
 |  | (2) The high dimension reduces the accuracy of probability modeling. |  |  |
 |  |  | Convolutional neural network[158] |  |
 |  | (3) The correlation coefficient can only grasp the overall characteristics, and the correlation simulation is not accurate. |  |  |
Extreme operation scenarios | (b) Small probability estimation | Small probability event is difficult to estimate accurately, but it affects the electric network reliability. | Response surface methodology [153] | Uncertainty constraint modeling, which includes voltage amplitude and static voltage index. |
 |  |  | First-order reliability method [159] |  |
 |  |  | Second-order reliability method [160] |  |
 |  |  | Analytical method [161] |  |
 |  |  | Central moment method [162] |  |
Typical operation scenarios | (c) Classification | Typical scenario extraction is usually based on clustering algorithm, but the correctness of unsupervised learning is difficult to verify. | The nearest neighbor approach && nonnegative matrix factorization [96] | Uncertainty objective modeling, which includes network loss and return on investment. |
 |  |  | Wasserstein distance metric [155] |  |
 |  |  | k-means clustering algorithm [163] |  |