Table 8 Comparison of 10-unit wind–thermal system with other algorithms
From: Optimum generation scheduling incorporating wind energy using HHO–IGWO algorithm
Method | Best cost | Worst cost | Mean | CPU time (in seconds) |
|---|---|---|---|---|
Operational cycle-based algorithm [19] | 563,937.70 | – | 564,227 | 19.4 |
GA [27] | 563,977 | 565,606 | 564,275 | 221 |
EACO [19] | 563,938 | 565,869 | 564,831 | – |
DBDE [28] | 563,977 | 564,241 | 564,028 | 3.6 |
PSO [27] | 564,212 | 565,783 | 565,103 | 120 |
Clustering method [19] | 563,938 | 563,976 | 563,945 | 39.6 |
QBGSA [19] | 515,339.6 | 517,156.8 | 516,425.4 | 49 |
BPSO [19] | 516,778.5 | 519,963.0 | 518,304.5 | 61 |
BGSA [19] | 517,736.6 | 520,577.2 | 519,254.8 | 61 |
EP [29] | 564,551 | 566,231 | 565,352 | 100 |
HPSO [19] | 563,942 | 565,785 | 564,772 | – |
BF [30] | 564,842 | 565,872 | NA | 110 |
SGA [27] | 565,943 | 570,121 | 569,042 | – |
hGWO-RES [19] | 511,680 | 511,687 | 511,683 | 80.3 |
hHHO–IGWO[Proposed Method] | 492,856.29 | 492,862.73 | 492,888.48 | 3.48 |