## 4 Optimization Techniques
### Optimization Techniques Regarding Design and Topology
It shows the deep interest of the research community regarding power flow uncertainty optimization with stochastic modeling, fuzzy logic, and robust programming. The trend of research is shifting in favor of battery storage optimization and the integration of plug-in hybrid vehicle load in the grid. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Ref.**} & \multicolumn{2}{c}{**Approach**} & \multicolumn{2}{c}{**Problem**} & \multirow{2}{*}{**Optimization Methods and Techniques**} & \multicolumn{2}{c}{**Recommended**} \\ \cline{2-2} \cline{5-8}
**No.** & **SO** & **MO** & **PF** & **UC** & **DN** & & **Method/Technique** \\ \hline
[26] & ✗ & ✓ & ✓ & ✗ & ✗ & ✗ & Memetic Algorithm (MA) & \multicolumn{2}{c}{IMA} \\  & & & & & & & Multi-objective Particle Swarm Optimization (MOPSO), PID for & & \\
[27] & ✗ & ✓ & ✓ & ✗ & ✗ & ✗ & \multicolumn{2}{c}{converter, PI and Fuzzy Logic Controller (FLC) for battery} & \multicolumn{2}{c}{MOPSO for converter FLC for battery} \\  & & & & & & changing/discharging & & \\
[28] & ✓ & ✗ & ✓ & ✗ & ✗ & \multicolumn{2}{c}{Centralized and decentralized OFF using Kriging model of power} & \multicolumn{2}{c}{A decentralized approach using PET} \\  & & & & & & electronic transformer (PET) & & \\
[29] & ✓ & ✗ & ✓ & ✗ & ✗ & \multicolumn{2}{c}{FLC for load management} & \multicolumn{2}{c}{FLC} \\
[30] & ✗ & ✓ & ✓ & ✗ & ✗ & \multicolumn{2}{c}{FLC using MOPSO, Multi-Objective Genetic Algorithm (MOGA)} & \multicolumn{2}{c}{MOGA} \\
[31] & ✓ & ✗ & ✓ & ✗ & ✗ & \multicolumn{2}{c}{Stochastic model, solved using scenario reduction (SR) and Benders} & \multicolumn{2}{c}{SAME} \\
[32] & ✓ & ✗ & ✓ & ✗ & ✗ & \multicolumn{2}{c}{DPN using interior point method (IP)} & \multicolumn{2}{c}{SAME} \\
[33] & ✓ & ✗ & ✓ & ✗ & \multicolumn{2}{c}{APC-CCF using IP, UTP algorithm} & \multicolumn{2}{c}{AC/DCOF using IP} \\
[34] & ✓ & ✗ & ✓ & ✗ & ✗ & \multicolumn{2}{c}{Exptation programming model, chaotic particle swarm} & \multicolumn{2}{c}{SPot Price Method} \\
[35] & ✗ & ✓ & ✓ & ✗ & \multicolumn{2}{c}{Optimization algorithm (CGRO), TOU, spot price method} & \multicolumn{2}{c}{SPO Price Method} \\
[36] & ✓ & ✗ & ✓ & ✗ & \multicolumn{2}{c}{Probabilistic model using Monte Carlo (MC) and SR} & \multicolumn{2}{c}{SAME} \\  & & & & & & Conventional \(\sigma\)d, hybrid AC/DC microgrid, plug-in hybrid & \\
[37] & ✗ & ✓ & ✗ & ✗ & \multicolumn{2}{c}{electric vehicles (PIFEV) load optimal power flow with GAMS} & \multicolumn{2}{c}{MILP} \\  & & & & & & software & \\
[38] & ✓ & ✗ & ✓ & ✗ & \multicolumn{2}{c}{Compartmentalization strategy margorids solved with pinning} & \multicolumn{2}{c}{SAME} \\  & & & & & synchronization technique for optimal power flow & & \\
[39] & ✓ & ✗ & ✓ & ✗ & \multicolumn{2}{c}{Subjects solved with multicluster and multicolumn{2}{c}} & \multicolumn{2}{c}{multirow}{-}{-} \\  & & & & & theory-based optimization model for optimal power balance of 3 & \\  & & & & & phase hybrid microgrid & \\
[40] & ✗ & ✓ & ✓ & ✗ & \multicolumn{2}{c}{Use of HOMER software to reduce the cost of energy and} & \multicolumn{2}{c}{} \\
[41] & ✗ & ✓ & ✓ & ✗ & \multicolumn{2}{c}{environmental emissions from hybrid microgrid for the designated} & \multicolumn{2}{c}{SAME} \\  & & & & & load & \\
[42] & ✗ & ✓ & ✓ & ✗ & \multicolumn{2}{c}{Reducing the cost of energy and environmental emissions using} & \multicolumn{2}{c}{PSO} \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Optimization approach; problem, methods, and techniques applied; and recommended method.