In order to investigate the performance of SFSA and ISFSA, simulation is carried out to eight test systems with and without integration of renewables. MATLAB 7.8 is the solution platform and the hardware configuration is Intel core i5 processor with 2GHz speed and 4 GB RAM.

Parameter Selection of SFSA

As SFSA is a heuristic method, it also requires optimal tuning parameter to discover global optima solution. In order to investigate best optimal tuning parameter of SFSA, it is applied on the 10-unit test system having non convex fuel cost characteristic due to VPL effect. Twenty-five independent run were conducted with different start point (NP) and maximum diffusion number (MDN). The statistical results are tabulated

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The outcome of simulation result is tabulated in Table 7.2. Here it is observed that results in terms of cost, standard deviation and also the CPU time get improved with respect to SFSA technique. Comparison of results of SFSA and ISFSA is presented in Table 7.3 and convergence characteristics is shown in Fig-7.1.

Table 7.2 Selection of Scale Factor

Scale Factor(F) Min Cost ($/hr.) Ave Cost ($/hr.) Max Cost ($/hr.) S. D CPU (sec)

0.3 111497.6741 111497.7233 111497.8003 0.0517 11.82

0.4 111497.6470 111497.6815 111497.7230 0.0308 11.62

0.5 111497.6225 111497.6324 111497.6350 0.0023 11.42

0.6 111497.6478 111497.6818 111497.7190 0.0252 11.72

0.7 111497.6619 111497.6938 111497.7741 0.0459 11.63

Table 7.3 Comparison of SFSA and

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Second test system is 13-unit with VPL and without losses. It is observed here that results obtained by SFSA are better than any reported results in literature.

Test system I: 10-unit system with VPL

This test system has ten thermal generating units with non-smooth cost function and emission. VPL effects are included in the cost function. Transmission line losses are also considered here. The entire data for this system is adopted from [11] with power demand of 2000 MW. The simulation result obtained by SFSA in terms of minimum cost is 111497.630825 $/h whereas minimum emission is 4572.16811ton/h. Table-7.4 depicts the optimum power generation for each individual case i.e. Best Cost Solution(ELD), Best Emission Solution(EED) and best compromise