## 8 Optimization Methods

Table 4: _Cont._ \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Refs.**} & **Optimization** & **DR Programs** & \multirow{2}{*}{**Objective Function**} & \multirow{2}{*}{**Constraints**} & \multirow{2}{*}{**Decision Variables**} \\  & **Algorithm** & & **Used** & & & & \\ \hline \multirow{4}{*}{[158]} & Stochastic & \multirow{4}{*}{\(\bullet\)} & \multirow{4}{*}{ToU} & \(\bullet\) & Minimization of & & & \\  & dynamic & & & customer’s energy & \(\bullet\) & EV SoC limits & & \\  & programming & & & & charging & \(\bullet\) & EV charger power & \(\bullet\) & Time index \\  & (SDP) & & & considering & & limits & \(\bullet\) & Residential load \\  & & & & residential power & \(\bullet\) & Grid power & & demand \\  & & & & demand and EV & & injection limits & & \\ \hline \multirow{4}{*}{[159]} & \multirow{4}{*}{\(\bullet\)} & \multirow{4}{*}{ToU} & \(\bullet\) & Minimization of & & & & \\  & & & & overall vehicle & \(\bullet\) & EV charger & \(\bullet\) & Real-time \\  & Deep learning & \(\bullet\) & PS & & energy cost & & efficiency limits & \(\bullet\) & EV availability \\  & (DL) & & & & & & \\ \cline{1-1} \cline{2-10}  & & \multirow{4}{*}{\(\bullet\)} & \multirow{4}{*}{ToU} & \(\bullet\) & Minimization of & \(\bullet\) & Voltage and & \(\bullet\) & Real-time \\  & & & & energy costs in the & & current limits & & electricity tariff \\  & & & & real-time market & \(\bullet\) & EV SoC limits & \(\bullet\) & EV load demand \\ \hline \multirow{4}{*}{[161]} & Robust & \multirow{4}{*}{\(\bullet\)} & \multirow{4}{*}{ToU} & \(\bullet\) & Minimization of & & & \\  & adversarial & & & customer’s electricity bill & \(\bullet\) & RES generation & \(\bullet\) & Dynamic electricity \\  & reinforcement & & & considering & & limits & \(\bullet\) & tariff \\  & learning & (RARL) & & & considering & & EV SoC limits & \(\bullet\) & Appliance \\  & & & & privacy concerns & & & schedule \\ \hline \multirow{4}{*}{[162]} & \multirow{4}{*}{\(\bullet\)} & \multirow{4}{*}{PS} & \(\bullet\) & Minimization of & & & \(\bullet\) & Energy prices \\  & & & & monetary and & \(\bullet\) & EV battery SoC & \(\bullet\) & Load demand \\  & & & non-monetary & & limits & & curve \\  & & & costs in DSM & & & \(\bullet\) & Total cost function \\ \hline \multirow{4}{*}{[163]} & \multirow{4}{*}{\(\bullet\)} & \multirow{4}{*}{ToU} & \(\bullet\) & Minimization of & \(\bullet\) & EV SoC limits & \multirow{4}{*}{\(\bullet\)} & \multirow{4}{*}{Charging reward function} \\  & & & the load demand & & curve of the system & charge/discharge power limits & & \\ \cline{1-1} \cline{2-10}  & & & & & & & \\ \cline{1-1} \cline{2-10}  & & & & & & & \\ \cline{1-1} \cline{2-10}  & & & & & & & EV BESS & \\  & & & & charging cost over & charge/discharge & & \\  & & & the day-ahead time & \(\bullet\) & EV & & EV availability \\  & & & & frame & & charge/discharge rate limits & & \\ \hline \multirow{4}{*}{[164]} & Hierarchical & \multirow{4}{*}{\(\bullet\)} & \multirow{4}{*}{PS} & \(\bullet\) & Minimization of & \(\bullet\) & EV SoC limits & \(\bullet\) & Fuel consumption \\  & reinforcement & & & hydrogen & \(\bullet\) & Fuel cell operation & \(\bullet\) & Fuel cell operation \\  & learning (HRL) & & & consumption & & limits & & status \\ \hline \multirow{4}{*}{[166]} & RL-based & \multirow{4}{*}{\(\bullet\)} & RTP & \(\bullet\) & Minimization of & \(\bullet\) & EV SoC limits & \multirow{4}{*}{\(\bullet\)} & \multirow{4}{*}{Reward function} \\  & pursuit & & & total energy cost & & charge/discharge & & \\  & algorithm (PA) & & & time limits & & & \\ \hline \multirow{4}{*}{[167]} & \multirow{4}{*}{\(\bullet\)} & \multirow{4}{*}{ToU} & \(\bullet\) & Minimization of & & & & \\  & & & electricity cost of & \(\bullet\) & PV generation & & \\ \cline{1-1}  & optimization & & the consumers & & limits & & \\ \cline{1-1}  & algorithm & & considering PV & \(\bullet\) & EV operation time & & \\ \cline{1-1}  & (COA) & & & generation and & limit & & \\ \cline{1-1}  & & & & ToU pricing & & & & \\ \hline \hline \end{tabular}
\end{table}