Research Article
Optimal Power Flow Using Gbest-Guided Cuckoo Search Algorithm with Feedback Control Strategy and Constraint Domination Rule
Table 2
Best solution of different cases for IEEE 30-bus system.
| Control variables | Case 1.1 | Case 1.2 | Case 1.3 | Case 1.4 | Case 1.5 |
| P1 (MW) | 177.3280 | 51.5146 | 160.1819 | 125.8849 | 199.1818 | P2 (MW) | 48.5873 | 80.0000 | 44.1461 | 28.6517 | 52.0165 | P5 (MW) | 21.4006 | 49.9772 | 49.9624 | 46.6602 | 15.0015 | P8 (MW) | 21.1434 | 34.9992 | 10.4269 | 21.9637 | 10.0007 | P11 (MW) | 11.9468 | 29.9993 | 12.1669 | 26.7956 | 10.0005 | P13 (MW) | 12.0065 | 39.9958 | 15.0303 | 38.8220 | 12.0003 | V1 (p.u.) | 1.0834 | 1.0611 | 1.0179 | 1.0616 | 0.9860 | V2 (p.u.) | 1.0642 | 1.0571 | 1.0061 | 1.0522 | 0.9664 | V5 (p.u.) | 1.0337 | 1.0377 | 1.0173 | 1.0555 | 0.9901 | V8 (p.u.) | 1.0384 | 1.0440 | 1.0083 | 1.0545 | 0.9583 | (p.u.) | 1.0851 | 1.0840 | 1.0592 | 1.0990 | 1.0990 | (p.u.) | 1.0408 | 1.0552 | 0.9973 | 1.0505 | 0.9765 | (p.u.) | 1.0800 | 1.0600 | 1.0800 | 1.0400 | 0.9000 | (p.u.) | 0.9100 | 0.9100 | 0.9000 | 0.9000 | 0.9000 | (p.u.) | 0.9600 | 0.9900 | 0.9500 | 0.9700 | 1.0900 | (p.u.) | 0.9700 | 0.9800 | 0.9700 | 0.9600 | 0.9000 | (p.u.) | 0.0460 | 0.0010 | 0.0500 | 0.0090 | 0.0340 | (p.u.) | 0.0140 | 0.0000 | 0.0010 | 0.0040 | 0.0500 | (p.u.) | 0.0410 | 0.0440 | 0.0500 | 0.0200 | 0.0000 | (p.u.) | 0.0490 | 0.0500 | 0.0000 | 0.0080 | 0.0430 | (p.u.) | 0.0390 | 0.0370 | 0.0500 | 0.0040 | 0.0480 | (p.u.) | 0.0500 | 0.0500 | 0.0480 | 0.0250 | 0.0030 | (p.u.) | 0.0290 | 0.0300 | 0.0500 | 0.0030 | 0.0010 | (p.u.) | 0.0500 | 0.0500 | 0.0500 | 0.0140 | 0.0440 | (p.u.) | 0.0200 | 0.0240 | 0.0270 | 0.0000 | 0.0440 | Fuel cost | 800.4173 | 947.5052 | 859.6552 | 886.3236 | 916.9167 | Power loss (MW) | 9.0127 | 3.0862 | 8.5145 | 5.3782 | 14.8014 | Voltage deviations | 0.9131 | 0.9037 | 0.0901 | 0.8834 | 0.6185 | L-index | 0.1376 | 0.1386 | 0.1488 | 0.1365 | 0.1469 |
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