## 5 Conclusions  
This work addressed the optimal siting and configuration of SPL-CHHP in a distribution network. To ensure good bilateral communication infrastructure, smart meter (SM) allocation was considered in the problem formulation. A techno-economic-based multi-objective function was proposed as the main function. Voltage drop and total investment cost reduction were defined as the technical and economic functions, respectively. The presented SPL-CHHP consists of an electrolyzer, fuel cell, heat exchange, thermal and hydrogen storage, WT, PV, and EVs. LSTM was employed to model system uncertainties. Power, thermal, and hydrogen demand, the output power of WT and PV, and the converged power of CHHP in the different scenarios were predicted via LSTM. A genetic algorithm was utilized to solve the planning problem. TOPSIS was used to choose the best plan among all of the solutions. Simulations were carried out for four scenarios. As can be seen from the results, technical criteria, such as the voltage profile and power loss reduction, were improved in the scenario with a high percentage of SPL-CHHP and SMs. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & **Number of Pareto** & \multirow{2}{*}{**min \((\text{OF}_{1})\)**} & \multirow{2}{*}{**max \((\text{OF}_{1})\)**} & \multirow{2}{*}{**min \((\text{OF}_{2})\)**} & \multirow{2}{*}{**max \((\text{OF}_{2})\)**} & \multirow{2}{*}{**Running Time(s)**} \\  & **Optimal Solutions** & & & & & & \\ \hline GA + AHP & 12 & 0.2401 & 2.905 & 0.2011 & 3.899 & 28,564 \\ GA + \(\varepsilon\)-constraints & 16 & 0.3057 & 3.784 & 0.2089 & 3.6746 & 27,489 \\ GA + TOPSIS & 10 & 0.103 & 3.985 & 0.0725 & 4.717 & 18,705 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of the obtained optimal Pareto fronts from different techniques. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Function and Scenario**} & \multirow{2}{*}{**OF1: Voltage Drop Index**} & \multirow{2}{*}{**Function and Scenario**} & \multicolumn{3}{c}{**OF2: Minimizing Cost Function**} \\  & & & & & & \(\text{OF}_{2}\)=min\((\text{IC}^{\text{CHHP}}\)+\(\text{IC}^{\text{SPL}}\)+ \(\text{\Phi}_{1}\)+\(\text{\Phi}_{2})\) & \\ \hline \multirow{2}{*}{OF1} & Mode & VDI & CF (*1065) & & Mode & CF (*1065) & VDI \\  & 1 & 0.0332 & 1.0289 & 1 & 1.0204 & 0.0185 \\ \multirow{2}{*}{Scenario2} & 2 & 0.0128 & 1.0119 & \multirow{2}{*}{Scenario2} & 2 & 1.0100 & 0.0110 \\  & 3 & 0.0112 & 1.0101 & & 3 & 1.0098 & 0.0102 \\ \multirow{2}{*}{OF1} & 1 & 0.0189 & 1.0126 & \multirow{2}{*}{OF2} & 1 & 1.0179 & 0.0152 \\  & 2 & 0.0025 & 1.0012 & & 2 & 1.0096 & 0.0062 \\ \multirow{2}{*}{Scenario 3} & 3 & 0.0021 & 1.0009 & & 3 & 1.0021 & 0.0032 \\  & 1 & 0.0248 & 1.0158 & & 1 & 1.0178 & 0.0128 \\ \multirow{2}{*}{OF1} & 2 & 0.0058 & 1.0092 & & 2 & 1.0035 & 0.0039 \\  & 3 & 0.0025 & 1.0029 & & 3 & 1.0019 & 0.0020 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Given solution by employing TOPSIS. **Author Contributions:** Conceptualization, H.H. ; edit, review and supervision, B.M.-I. ; Supervision, M.M. All authors have read and agreed to the published version of the manuscript. **Funding:** The authors appreciate the support of Research Affairs Office of the University of Tabriz, Tabriz, Iran (grant number S-1610). **Conflicts of Interest:** The authors confirm that this article content has no conflict of interest.