A Fast Market Competition Approach to Power System Unit Commitment Using Expert Systems - Intelligent Computing for Sustainable Energy and Environment - page 449

Fig. 1. 10-runs convergence of market competition algorithm in 10-unit power system

Ta b l e 2 . Comparison of costs and average execution time of different methods for 10-unit system

Costs($)

Method SU C FC Best TFC Mean TFC Mean Time(s)

GA 4090 561735.00 565825.00 565889 220

HQCE 4090 559856.30 563938.00 563952 19

PSO 2095 562899.00 565804.00 565868 24

QPSO 4090 559852.30 563942.30 563950 18

BF 2100 562742.00 564842.00 564866 20

SLFA 4090 559847.70 563937.70 563942 19

THMCA without ER 4090 559847.40 563937.40 563940 18

THMCA with ER 4090 559846.60 563936.60 563938 11

Ta b l e 3 . Comparison of costs and average execution time of different methods for 10 to 100 units

TFC($(Mean Time(s)))
Unit

Method 10 20 50 100

GA 565825(220) 1126243(733) 2680085(4065) 5627437(15733)

HQCE 563938(19) 1123370(53) 2673694(142) 5625937(477)

PSO 565804(24) 1126148(69) 2679703(186) 5627510(624)

QPSO 563942(18) 1125510(51) 2673392(134) 5609085(449)

BF 564842(20) 1124892(34) 2674028(86) 5611514(282)

SLFA 563937(19) 1123261(33) 2673458(87) 5624526(289)

THMCA without ER 563937(18) 1122904(31) 2672610(83) 5622742(282)

THMCA with ER 563936(11) 1122872(17) 2672332(45) 5622457(156)

The best comparison results of total fuel cost and mean execution time for power
system with up to 100 generating units are shown in table 3. The execution time of
THMCA with ES increases almost linearly with the size of the UC scheduling problem.
The overall execution time obtained by THMCA with ES is less than that of other