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Advances, Systems and Applications

Table 3 Sub-problems of Load Forecasting

From: A Review of Intelligent Verification System for Distribution Automation Terminal based on Artificial Intelligence Algorithms

Sub-Problem

Description

Type of method

Status

Load Forecasting

Predicts power demand for a period of time in the future by analyzing past power consumption data and other factors.

SVM

SVRM

WT

ANN + PSO

PSO + SVM

DBN

DRNN-GRU

Empirical Mode Decomposition

CNN

SDA

LSTM

LSTM-RNN

PDRNN

[73]

[22]

[74]

[28]

[75]

[76]

[77]

[78, 79]

[80]

[81]

[82, 83]

[84]

[85]

STLF

Ultra short-term load forecasting generally outputs load changes in the next few minutes to several hours.

DFN

FFDNN + RDNN

CNN + K-Means

DNN

DBN

COSMOS

[86]

[87]

[88]

[89]

[90]

[91]

MTLF

Medium term load forecasting predicts the load values for the coming weeks and months.

SVM

[21]