%0 Journal Article
%T Voltage Unbalance Assessment of Solar PV Integrated Low Voltage Distribution System in Sri Lanka Using Monte Carlo Simulation
%J Journal of Solar Energy Research
%I University of Tehran
%Z 2588-3097
%A Perera, Thilini
%A Udayakumar, Chamnida
%D 2023
%\ 04/01/2023
%V 8
%N 2
%P 1357-1366
%! Voltage Unbalance Assessment of Solar PV Integrated Low Voltage Distribution System in Sri Lanka Using Monte Carlo Simulation
%K Rooftop solar PV
%K voltage unbalance
%K LV distribution system
%R 10.22059/jser.2023.350730.1262
%X Rooftop solar PV integration into the distribution systems brings benefits to both consumers and utility organizations. These ever-increasing, unplanned generating points in the form of rooftop solar PVs can have undesirable effects on the performance of the system. From the technical point of view, maximum rooftop solar PV hosting capacity mainly depends on whether the parameters such as power loss, overvoltage, and voltage unbalance are kept within the permissible level while increasing the rooftop solar PVs' capacities. Rooftop solar PVs are owned by individual households and their locations in the distribution system are unpredictable. The locations and capacities of rooftop solar PVs are the two parameters that influence the above parameters. This paper proposes a stochastic approach to allocate rooftop solar PVs in a distribution system using the Monte Carlo method. An algorithm is developed to allocate rooftop solar PVs in a distribution system and assess the overvoltage and voltage unbalance of the distribution system. Practical data of possible rooftop solar PV capacities are used for the determination of probabilities of occurrence of rooftop solar PV with the given rating. The proposed method is tested using a Low Voltage distribution system in a sub-urban area. The results show that the voltage unbalance and overvoltage at feeder endpoints are mostly affected due to the increase in solar PV integration. The results also show an increase in the solar PV penetration level by more than 40%.
%U https://jser.ut.ac.ir/article_90745_322c390ef87e96273cc277c8b31dec29.pdf