## 6 Conclusions  
A multi-objective RPP in power systems considering load demand and wind power generation uncertainties to minimize reactive power investment cost, reduce active power losses, improve voltage stability level, and enhance loadability factor is presented in this paper. The \(\varepsilon\)-Constraint method is used to solve the probabilistic multi-objective RPP. For this purpose, using the L-index, the VAR compensation buses are found at the first stage. Then, to distinguish the exact difference between the deterministic and probabilistic VAR planning studies, five different cases are investigated. In order to test the efficiency of the proposed method, the IEEE 30-bus test system is implemented in GAMS software under five various conditions. The simulation results show that the proposed probabilistic multi-objective RPP considering load demand and wind power generation uncertainties is effective in reducing the VAR installation cost, improving the voltage stability of the system, and enhancing the loadability, simultaneously. All authors participated equally in conceptualization, methodology, implementation, and writing--review and editing the paper. Also, All authors have read and agreed to the published version of the manuscript. This research received no external funding. The authors declare no conflict of interest. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Case** & \(f_{1}\)**(**S**)** & \(f_{2}\) & \(f_{3}\) & \(P_{loss}\)**(MW)** \\ \hline B & \(4.9361\times 10^{6}\) & 0.1533 & 0.1653 & 9.3494 \\ C & \(2.2510\times 10^{6}\) & 0.1606 & 0.1688 & 9.5049 \\ D & \(7.5741\times 10^{5}\) & 0.1570 & 0.2100 & 8.5777 \\ E & \(3.4683\times 10^{5}\) & 0.1539 & 0.2107 & 8.5575 \\ F & \(3.4345\times 10^{5}\) & 0.1525 & 0.2108 & 8.4807 \\ \hline \hline \end{tabular}
\end{table} 
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