A Refined Teaching-Learning Based Optimization Algorithm for Dynamic Economic Dispatch of Integrated Multiple Fuel and Wind Power Plants

Table 8

Data for the 7-unit practical system with multiple fuel cost coefficient.

Unit	Generation	Fuel type
	Min P1 P2 max		Cost coefficient
	F1  F2  F3		𝑎𝑖	𝑏𝑖	𝑐𝑖	𝑒𝑖	𝑓𝑖
1	50 114 157 230; 1  2  3	1	0.1184𝑒3	−0.1269𝑒1	0.4194𝑒−2	0.1184𝑒0	−0.1269𝑒2
		2	0.1865𝑒1	−0.3988𝑒−1	0.1138𝑒−2	0.1865𝑒−2	−0.3988𝑒0
		3	0.1365𝑒2	−0.1980𝑒0	0.1620𝑒−2	0.1365𝑒−1	−0.1980𝑒1
2	200 332 388 500; 1  2  3	1	0.3979𝑒2	−0.3116𝑒0	0.1457𝑒−2	0.3979𝑒−1	−0.3116𝑒1
		2	−0.5914𝑒2	0.4864𝑒0	0.1176𝑒−4	−0.5914𝑒−1	0.4864𝑒1
		3	−0.2875𝑒1	0.3389𝑒−1	0.8035𝑒−3	−0.2876𝑒−2	0.3389𝑒0
3	99 138 200 265; 1  2  3	1	0.1983𝑒1	−0.3114𝑒−1	0.1049𝑒−2	0.1983𝑒−2	−0.3114𝑒0
		2	0.5285𝑒2	−0.6348𝑒0	0.2785𝑒−2	0.5285𝑒−1	−0.6348𝑒1
		3	0.2668𝑒3	−0.2338𝑒1	0.5935𝑒−2	0.2668𝑒0	−0.2338𝑒2
4	190 338 407 490; 1  2  3	1	0.1392𝑒2	−0.8733𝑒−1	0.1066𝑒−2	0.1392𝑒−1	−0.8733𝑒0
		2	0.9976𝑒2	−0.5206𝑒0	0.1597𝑒−3	0.9976𝑒−1	−0.5206𝑒1
		3	−0.5399𝑒2	0.4462𝑒0	0.1498𝑒−3	0.5399𝑒−1	0.4462𝑒1
5	85 138 200 265; 1  2  3	1	0.5285𝑒2	−0.6348𝑒0	0.2758𝑒−2	0.5285𝑒−1	−0.6348𝑒1
		2	0.1983𝑒1	−0.3114𝑒−1	0.1049𝑒−2	0.1983𝑒−2	−0.3114𝑒0
		3	0.2668𝑒3	−0.2338𝑒1	0.5935𝑒−2	0.2668𝑒0	−0.2338𝑒2
6	200 331 391 500; 1  2  3	1	0.1893𝑒2	−0.1325𝑒0	0.1107𝑒−2	0.1893𝑒−1	−0.1325𝑒1
		2	0.4377𝑒2	−0.2267𝑒0	0.1165𝑒−2	0.4377𝑒−1−	−0.2267𝑒1
		3	−0.4335𝑒2	0.3559𝑒0	0.2454𝑒−3	0.4335𝑒−1	0.3559𝑒1
7	130 213 370 400; 1  2  3	1	0.8853𝑒2	−0.5675𝑒0	0.1554𝑒−2	0.8853𝑒−1	−0.5675𝑒1
		2	0.1530𝑒2	−0.4514𝑒−1	0.7033𝑒−3	0.1423𝑒−1	−0.1817𝑒0
		3	0.1423𝑒2	−0.1817𝑒−1	0.6121𝑒−3	0.1423𝑒−1	−0.1817𝑒0