Multi-objective economic operation of modern power system considering weather variability using adaptive cuckoo search algorithm

Journal of Electrical Systems and Information Technology

Table 1 Simulation results of IEEE 14-bus test system

Item	Scenario 1		Scenario 2		Scenario 3		Scenario 4		Scenario 5
Item	Case (a)	Case (b)	Case (a)	Case (b)	Case (a)	Case (b)	Case (a)	Case (b)	Case (a)	Case (b)
P_d (MW)	259		269.5		282.8		298.9		317.8
Q_d (MVAr)	73.5		84		97.3		113.4		132.3
P_g,CE (MW)	267.82	192.08	278.5	226.96	292	244.31	308.35	263.71	327.62	285.47
Q_g,CE (MVAr)	62.01	23.46	73.16	43.68	87.2	56.29	104.3	72.08	125.55	89.15
P_g,RE (MW)	0	75.2	0	51.65	0	47.45	0	44.17	0	41.54
Q_g,RE (MVAr)	0	27.8	0	21.57	0	22.11	0	23.34	0	25.2
CE_Cost($/h)	8054.41	5197.37	8482.53	6448.67	9024.33	7128.36	9682.55	7895.83	10,460.34	8766.25
P_loss (MW)	8.8190	8.2745	8.9987	9.1107	9.1974	8.9649	9.4504	8.9808	9.8233	9.2046
VCPI_avg	0.006	0.0088	0.0067	0.0082	0.0076	0.0073	0.009	0.0071	0.0112	0.0079
AVDI_avg	0.0006	0.0027	0.0007	0.0011	0.0008	0.0007	0.0011	0.0007	0.0019	0.0008
Optimal schedule at CE sources
P_g1 (MW)	196.52	161.64	197.25	187.16	198.04	191.21	198.61	194.86	199.37	196.78
P_g2 (MW)	36.9	30.43	37.09	35.18	37.27	36.01	37.42	36.72	37.61	37.11
P_g3 (MW)	27.07	0	30.86	4.62	34.49	17.09	37.84	28.19	41.73	34.76
P_g4 (MW)	0	0	0	0	2.69	0	8.61	0	15.36	0
P_g5 (MW)	7.32	0	13.31	0	19.51	0	25.87	3.94	33.56	16.82