# Voltage Optimization in PV-Rich Distribution Networks--A Review
## 5 Conclusions  
This paper aims to systematize and categorize scientific papers that are dealing with the optimization of voltage in the DN using the reactive power management of PV inverters. Additionally, the papers are categorized according to the optimization problem formulation and applied solution methods. It can be observed that the original voltage optimization problem is nonlinear due to a quadratic objective function and nonlinear power flow equations. Additionally, some authors propose a mixed-integer nonlinear formulation due to integer variables such as the OLTC tap setting. To solve such complex optimization problems, some authors use analytical methods and some use computational ones. In this review paper, the authors tried to point out the advantages and shortcomings of both approaches without favoring one. When analytical methods are used, the compromise regarding the transformation of the original problem into a standard one is present but the analytical approach enables the straightforward method to find the optimum of a well-defined optimization problem (although special attention is required in order to determine whether a calculated optimum is local or global). On the other hand, computational intelligence methods can solve complex optimization problems without the transformation of the original formulation but they required higher computational performance as well as more computational time. One of the trends in applying computational intelligence methods is using well-known power flow calculation tools in order to feed the computational intelligence method with multiple power flow solutions. This principle is recognized as co-simulation. The research potential of the reviewed field lies in the fact that more and more inverter-based sources are installed in distribution networks worldwide. The importance of voltage optimization is specifically stressed in microgrids where voltage supports depend mainly on the inverter-based source. Since the PV active power production depends on variable and stochastic sun irradiation, further research direction in the field of voltage optimization will strive to create an adequate probabilistic formulation of the OPF problem which is computationally more demanding since large numbers of possible scenarios need to be analyzed. Some probabilistic OPF solutions are already created for the transmission system environment but their replication in the distribution network (or microgrid) is not straightforward. It is hard to foresee which solution methodology (analytical or computational \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Reference** & **Test Network Model** & **Voltage Level** & **Balanced/Unbalanced** \\ \hline
[71] & Real UK 1 & LV–0.4 kV & Unbalanced \\
[72] & IEEE–15 bus & MV–11 kV & Unbalanced \\
[74] & IEEE–8500 bus & MV and LV & Both \\
[75] & Real Australian–565 bus & MV–22 kV and LV–415 V & Both \\
[68] & 22 bus & MV–11.4 kV & Balanced \\
[78] & 17 bus & MV–25 kV & Balanced \\
[56,113] & IEEE–37 bus & MV–4.16 kV & Unbalanced \\
[56] & Real Californian utility & N/A & Unbalanced \\
[54] & feeder–2884 bus & N/A & Unbalanced \\
[34] & Illustrative model & LV & N/A \\
[84] & K1 feeder–1747 bus in the & MV and LV & N/A \\
[69,116] & 33 bus & MV–12.66 kV & N/A \\
[69] & 830 bus & N/A & N/A \\
[37,91] & Real South Korean–20 bus & MV–22.9 kV & Balanced \\
[59] & Real South Italian–16 bus & LV & Unbalanced \\
[39] & Real Irish suburban–85 bus & LV & N/A \\
[58] & Modified PG\&E–69 bus & MV & Balanced \\
[114] & CIGRE–12 bus & MV & N/A \\
[116] & 118 bus & MV & N/A \\ \hline \hline \end{tabular}
\end{table} 
Table 7: \(Cont.\)intelligence) will show better performance in a probabilistic environment and there is still plenty of research challenges and gaps present for further research. Conceptualization, M.D. and K.F. ; methodology, M.D. and K.F. ; formal analysis, M.D., K.F. and D.T. ; investigation, M.D. ; writing--original draft preparation, M.D., K.F. and D.T. ; writing--review and editing, D.T. and M.B. ; funding acquisition, D.T.