# Optimal Solution of Environmental Economic Dispatch Problems Using QPGPSO-\(\omega\)
## 4 Results and Discussion
### Case 2 of Only RESs with Resource Variability  
For the mentioned case, resource and load variations within a day were taken into account. Table 4 provides an overview of different time periods, along with the corresponding PD, average solar irradiance, and wind speed values during those specific periods [20, 64, 65].  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Regional** & **Project** & **Capacity** & **Area** & **Irradiance/Rated** \\
**Distribution** & **Project** & **(MW)** & **Area** & **Velocity** \\ \hline \multicolumn{5}{c}{Three Gorgeous Wind-Farm (private)} \\  & Limited & 49.5 & Jhimpir & \\ \cline{2-4}  & Sapphire Wind-Power Company & & \\  & Limited & 52.8 & [PERSON] & Vcut-in = 05 m/s \\ Region 3 & FFC Energy Limited & 49.5 & Jhimpir & Vcut-out = 25 m/s \\ \cline{2-4}  & Zorla Energi Pakistan (private) Limited & 56.4 & Jhimpir & Underestimation = 1 \\ \cline{2-4}  & Yunus Energy Limited & 50 & Jhimpir & Kp factor = 1 \\ \cline{2-4}  & Metro Power Co., Limited & 50 & Jhimpir & \\ \hline \end{tabular}
\end{table}
Table 2: _Cont._  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline
**RES** & **QPGPSO-\(\omega\)** & **QPGPSO-\(\omega\)** & **HPSQ_BA** & **HPSQ_BA** & **MHPSO_BAAC** & **MHPSO_BAAC** & **MHPSO_BAAC\_X** & **MHPSO_BAAC\_X** \\  & **(MW)** & **(USD)** & **(MW)** & **Cost (USD)** & **(MW)** & **Cost (USD)** & **(MW)** & **Cost (USD)** \\ \hline P1 & 26.35 & 1168.798 & 23.715 & 1169.7981 & 26.35 & 1168.798 & 26.35 & 1168.7981 \\ \hline P2 & 62.4 & 2734.124 & 62.4 & 2739.1  
The results presented in Table 5 indicate that the power generation from wind and PV resources exhibits variations throughout the day, due to the availability of these resources.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Period (h)** & **Power Demand (MW)** & **Solar Irradiance (W/m2)** & **Wind Speed (m/s)** \\ \hline  
\hline \end{tabular}
\end{table}
Table 4: Time slots and the system parametric values for case 2.  
Figure 2: Cost convergence curve of RES-based EDPs without constraints.  
As wind speed and solar irradiance fluctuate, the power output from these renewable sources also varies accordingly. On the other hand, the power generation from the biofuel resource remains relatively constant, as its supply is less prone to variations. The results obtained through the QPGPSO-\(\omega\) algorithm for the cost of power production were compared with the techniques introduced in [66]. As observed in the comparison, the results obtained using QPGPSO-\(\omega\) exhibit a slight improvement.  
In Table 5, a comparison is provided between the developed algorithm and techniques utilized for solving RES-based EDPs [63]. The table demonstrates that the developed algorithm exhibits slightly superior results in terms of cost reduction across nearly half of the time slots.  
Furthermore, Figure 3 showcases the convergence curves for case 2, illustrating the progressive reduction in costs over the 23 time slots of the day. The graph visually represents the algorithm's ability to optimize power generation and achieve cost efficiency throughout the different time periods.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Time Period** & \multicolumn{2}{c}{**QPGPSO-\(\omega\)**} & \multicolumn{2}{c}{**HPSOBA**} & \multicolumn{2}{c}{**MHPSO-BAAC**} & \multicolumn{2}{c}{**MHPSO-BAAC-X**} \\ \cline{2-9}
**Hours (h)** & **(MW)** & **(USD)** & **(MW)** & **(USD)** & **(MW)** & **(USD)** & **(MW)** & **(USD)** \\ \hline
00–01 & 200 & 8029.8 & 200 & 8030 & 200.2 & 8030 & 202.15 & 8030 \\ \hline
01–02 & 195.7 & 8060 & 195.7 & 8060.78 & 195.8  
Figure 4 illustrates the variations in cost during the peak (16-20) and low (00-04) load hours. The cost of power generation fluctuated during these time slots, primarily due to the changes in solar radiation.  
Figure 4: Cost convergence curve of RES-based EDPs with load and supply variations for 24 h.  
Figure 3: Cost convergence curve of RES-based EDPs with resource variability.