|
| ML technique | Reference | Application |
|
| ANN | [217] | In the buildings of industry savings of the energy are verified and measured |
| [218] | Forecast solar radiation and predict wind speed |
| [219] | Electricity cost is forecasted |
| [220] | Power generation plans are created and scheduled and fluctuations in the wind power are controlled |
| [221] | Various capacities of the renewable energy generation are optimized |
|
| MLP | [222] | Plants are ranked |
| [223] | Forecast solar radiation |
| [224] | Predict solar power generation |
| [225] | Predict load |
| [226] | Solar irradiation is forecasted |
|
| SVM | [227] | Forecast price of the electricity in the market |
| [228] | Estimate the power quality |
| [229] | Disturbances in the power quality will be classified |
|
| WNN | [230] | Time series forecast |
| [231] | Predict the speed of the wind |
| [232] | In forecasting the wind power fluctuations can be mitigated |
|
| ANFIS | [233] | A protection system is presented |
| [234] | Demand of power is forecasted |
| [235] | Solar radiation is forecasted |
|
| Decision tree | [236] | Blackout risk is forecasted |
| [237] | Cost minimization in energy systems |
|
| Deep learning | [238] | Estimation of state-of-charge of battery |
| [239] | Predicting the electricity demand in the households |
| [240] | Energy consumption is forecasted |
|
| Ensemble model | [241] | Building electricity demand is forecasted |
| [242] | Predict buildings cooling load |
|
