Table 1.
Solar power by country– 2021 (Courtesy:MNRE).
Fig 1.
Installed solar power capacity in India– 2022 (www.mnre.gov.in).
Fig 2.
Twin support vector machine predictor model.
Fig 3.
Proposed VMD-ALO-DLFTSVM predictor framework.
Fig 4.
Fuzzy based TSVM hyperplane formation.
Fig 5.
Architecture of proposed DLFTSVM solar PV power predictor.
Table 2.
Kernel functions adopted in the new DLFTSVM predictor.
Table 3.
Sample of solar PV power generation dataset.
Fig 6.
VMD output for the considered solar PV farm.
Table 4.
Simulation parameters of the proposed predictor model.
Fig 7.
Plot of actual and predicted solar PV output power (Plant 1 solar PV farm).
Fig 8.
Plot of actual and predicted solar PV output power (Plant 2 solar PV farm).
Table 5.
Evaluated performance metrics using VMD-ALO-DLFTSVM predictor.
Fig 9.
Convergence plot for the proposed predictor model during DL training.
Table 6.
MSE evaluated over iterations for DLFTSVM predictor.
Table 7.
Sample predicted output samples with VMD-ALO-DLFTSVM predictor.
Table 8.
Comparisons of proposed technique with other techniques.
Fig 10.
Plot for comparisons MSE value and accuracy of proposed technique with other techniques (Solar PV plant 1).
Fig 11.
Plot for comparisons of MSE value and accuracy of proposed technique with other techniques (Solar PV plant 2).