## 4 Results and Discussion
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**PSs**} & \multirow{2}{*}{\(\mathbf{\pi_{m}}\)} & \multicolumn{3}{c}{**GA [22]**} & \multicolumn{3}{c}{**PSO [23]**} & \multicolumn{3}{c}{**GSA [16]**} & \multicolumn{3}{c}{**OGSA**} \\ \cline{3-14}  & & \(\mathbf{\phi_{m}}\) & **PG** & **Profit** & \(\mathbf{\phi_{m}}\) & **PG** & **Profit** & \(\mathbf{\phi_{m}}\) & **PG** & **Profit** & \(\mathbf{\phi_{m}}\) & **PG** & **Profit** \\ \hline
1 & 2.0 & 0.044090 & 160 & 1592.4 & 0.042666 & 160 & 1645.73 & 0.049231 & 160 & 1815.32 & 0.049984 & 160 & 1848.47 \\
2 & 1.75 & 0.19429 & 75.05 & 712.19 & 0.211031 & 74.81 & 735.14 & 0.224134 & 77.45 & 839.65 & 0.223528 & 78.68 & 867.49 \\
3 & 1.0 & 0.300167 & 57.94 & 459.54 & 0.436374 & 49.28 & 433.95 & 0.722945 & 40.95 & 425.33 & 0.680819 & 42.5 & 446.15 \\
4 & 3.25 & 0.094465 & 100 & 846.85 & 0.103858 & 100 & 880.18 & 0.097653 & 100 & 966.18 & 0.099466 & 100 & 1006.9 \\
5 & 3.0 & 0.280553 & 53.50 & 439.52 & 0.275273 & 57.95 & 488.96 & 0.289934 & 60.80 & 573.06 & 0.307913 & 59.41 & 574.36 \\
6 & 3.0 & 0.280553 & 53.50 & 439.52 & 0.275273 & 57.95 & 488.96 & 0.289934 & 60.80 & 573.06 & 0.307913 & 59.41 & 574.36 \\ MCP & & & 12.55 & & & 12.89 & & & 13.9458 & & 14.15 & \\  & & & 4490.02 & & & 4672.93 & & & 5212.6 & & 5317.72 & \\ Total PG & & & 500 & & & 500 & & & 500 & & 500 & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Optimal bidding results for the IEEE standard 30-bus without including wind power. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**PSs**} & \multirow{2}{*}{\(\mathbf{\pi_{m}}\)} & \multicolumn{3}{c}{**GA [22]**} & \multicolumn{3}{c}{**PSO [23]**} & \multicolumn{3}{c}{**GSA [16]**} & \multicolumn{3}{c}{**OGSA**} \\ \cline{3-14}  & & \(\mathbf{\phi_{m}}\) & **PG** & **Profit** & \(\mathbf{\phi_{m}}\) & **PG** & **Profit** & \(\mathbf{\phi_{m}}\) & **PG** & **Profit** & \(\mathbf{\phi_{m}}\) & **PG** & **Profit** \\ \hline
1 & 2.0 & 0.043369 & 160 & 1429.56 & 0.048167 & 160 & 1464.98 & 0.049575 & 160 & 1572.05 & 0.049242 & 160 & 1632.5 \\
2 & 1.75 & 0.195359 & 63.36 & 549.71 & 0.197386 & 61.51 & 549.30 & 0.215113 & 59.69 & 574.8 & 0.189561 & 70.19 & 689.57 \\
3 & 1.0 & 0.561368 & 32.04 & 273.38 & 0.59685 & 28.84 & 258.24 & 0.453362 & 35.26 & 0.647421 & 30.11 & 298.72 \\
4 & 3.25 & 0.088848 & 100 & 745.08 & 0.084439 & 100 & 767.22 & 0.104385 & 97.96 & 818.8 & 0.109269 & 99.31 & 866.43 \\
5 & 3.0 & 2.052845 & 46.32 & 341.72 & 0.230275 & 48.85 & 368.05 & 0.251243 & 47.57 & 391.8 & 0.303061 & 44.22 & 384.64 \\ MCP & & & 11.53 & & & 11.76 & & & 12.4253 & & & 12.80 \\ Total Profit for & & & 3681.16 & & & 3775.86 & & & 4074.4 & & 4256.5 & \\ TPS & & & & & & & & & & & & \\ Total PG for TPS & & & 448.05 & & & & 448.05 & & & 448.05 & \\ \(W_{g}\) & & 51.95 & & & 51.95 & & & 51.95 & & & 51.95 \\ \(Q_{c}(w_{g})\) & & 38.1026 & & & 38.8627 & & & 41.0612 & & & 42.2995 & \\ \(L_{c}(w_{g})\) & & 335.4122 & & & 342.1030 & & & 361.4568 & & & 372.3570 & \\ \(IMC(W_{Sn})\) & & 373.5148 & & & 380.9656 & & & 402.5180 & &Findings for IEEE 30- and 57-buses indicates that inclusion of the wind energy in the bidding process has a significant impact on MCP, individual generation dispatch, and complete generation dispatch for conventional power supplies. The utilization of wind power reduces the MCP, thus benefiting the traditional generators. Moreover, when KDM is involved for handling uncertainty related to wind power, overestimation of uncertainty is much lower than underestimation of wind power generation. If the underestimation is positive, this would enable wind power providers to bid the extra power into the real-time market. Furthermore, the bidding strategy proposed in this paper by utilizing OGSA is better suited to obtaining power suppliers' profits in comparison to the GSA [16], GA [22], and PSO [23] techniques. Through comparing simulation outcomes with GSA, PSO and GA, the superiority of the OGSA algorithm is shown.