## 5 Conclusions  
The voltage quality has been identified by DNOs as one of the main factors that can decrease the hosting capacity to accommodate the growing number of PV prosumers. The reverse power flows from the LVEDN toward the EDS represent the reason for various voltage issues, leading to uncertainties on the voltage level of the nodes. Thus, new methodologies should be developed to solve the voltage issues caused by PV prosumers based on the devices integrated into the LVEDN. One of the most efficient devices to ensure the resilience of voltage control is represented by the OLTC, which equips the MV/LV distribution transformers. One of the most challenging issues in the operation of the OLTC in the LV EDNs is the determination of the optimal tap position, which leads to a fit 95% of the time between the admissible limits of the phase voltage in all nodes following the performance standards, in conditions when the reverse power flows can occur. In this paper, an efficient expert system, including rule-based reasoning (RBES), has been developed to solve the voltage issues caused by PV prosumers, having as advantages the \"fast scanning\" of the input data, identification of voltage issues that come up, and determination of a solution associated with the tap position of an OLTC that does not violate the voltage constraints in the PV-rich network based on the deviations between the reference voltage and the voltages recorded in the nodes in each time slot, recognizing the excesses of the allowable limits, regardless of the power flow's direction. These advantages offer RBES efficiency and resilience. Efficiency is associated with their ability to meet the demands of the end-users regarding voltage quality, and resilience is characterized by the response to harmful events represented by sudden voltage variations due to the intermittent regime of the small-scale renewable sources (prosumers). Testing the RBES was conducted considering an aerial LVEDN supplied by an EDS whose MV bus (20 kV) represents the CCP with the network of a Romanian DNO that carries out its distribution service in the respective area. More scenarios (75) have been considered in the case study, characterized by the combinations between the penetration degree, consumption evolution, and energy production of the PV systems from the month that includes the analysed day. The success rate of the RBES was 86.7% (65 out of 75 scenarios did not have the voltage issues anymore). For the remaining 10 associated with the highest values of PD (40% and 50%), high energy production and all considered consumptions the voltage have been mitigated, being close to the upper allowable limit, but at least 95% of the time slots were inside the range [\(-\)10%, +10%], according to the European Power Quality Standard. The comparison with another method based on the multi-objective optimization with two criteria (minimization of the energy losses and voltage deviations in the nodes of the LVEDN) demonstrated the efficiency of the RBES, quantified through smaller energy losses and the total number of tap position changes. Even under these conditions, the implementation of RBES in the real application integrated into the LVEDN depends on the speed and sampling step of the data transmission from the smart meters installed at the end-user level (in the study case, the sampling step was 60 min according to the setting implemented by the DNO at the level of the SMS) and the performance of the processing module from the data concentrator at the EDS level. Regarding the expected costs to implement the proposed voltage control solution, DNOs should consider an investment cost of 7000 euros and an approximated cost per tap position change of 0.01 euros, according to [54]. In addition, the costs allocated to the maintenance operations should be integrated into the economic analysis, but these are \begin{table}
\begin{tabular}{c c c} \hline
**No.** & **Algorithm** & **ACT [seconds]** \\ \hline
1 & RBES (Proposed) & 0.265 \\
2 & MM & 0.253 \\ \hline \end{tabular}
\end{table}