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Expert System Integrating Rule-Based Reasoning to Voltage Control in Photovoltaic-Systems-Rich Low Voltage Electric Distribution Networks: A Review and Results of a Case Study

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Nowadays, in low voltage electric distribution networks, the distribution network operators are encountering a high number of connected small-scale distributed generation units, mainly photovoltaic prosumers. The intermittent nature of the… Click to show full abstract

Nowadays, in low voltage electric distribution networks, the distribution network operators are encountering a high number of connected small-scale distributed generation units, mainly photovoltaic prosumers. The intermittent nature of the prosumers, together with the degree of uncertainty of the requested and injected powers associated with all end-users from low voltage electric distribution networks, can cause voltage variations that violate the allowable limits. In this context, this paper developed an efficient and resilient expert system integrating rule-based reasoning applied to the on-load tap changer-fitted transformer to improve the efficiency of the voltage control in the PV-rich LV EDNs. An in-depth analysis based on 75 scenarios, resulting from the combinations of three indicators—the penetration degree of the photovoltaic prosumers, the consumption evolution associated with the consumers, and the energy production of the photovoltaic systems—was performed to demonstrate the efficiency of the proposed expert system in a low voltage electric distribution network from a rural area belonging to a Romanian distribution network operator. The success rate of the expert system was 86.7% (65 out of 75 scenarios did not have voltage issues). All voltages were between the allowable limits in 100% of the time slots associated with the analysed period. For the other scenarios (representing 13.3%), voltages were inside the range [−10%, +10%] in at least 95% of the time slots.

Keywords: low voltage; electric distribution; voltage; voltage electric; distribution; expert system

Journal Title: Applied Sciences
Year Published: 2023

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