Optimal Location and Determination of Fault ‎Current Limiters in the Presence of Distributed ‎Generation Sources Using a Hybrid Genetic Algorithm

Journal of Applied Dynamic Systems and Control

دوره 3، شماره 2، اسفند 2020، صفحه 31-38   

نوع مقاله: Original Article

نویسندگان

Salman Amirkhan^{* 1}؛ Mostafa Rayatpanah Ghadikolaei²؛ Hassan Pourvali Souraki²

¹Department of Electrical Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran

²MAPNA Operation and Maintenance Co. (O&M), Tehran, Iran

چکیده

Nowadays, the presence of distributed generation (DG) units in the distribution network is increasing due to their advantages. Due to the increasing need for electricity, the use of distributed generation sources in the power system is expanding rapidly. On the other hand, in order to respond to the growth of load demand, the network becomes wider and more interconnected. These factors increase the level of fault current in the power system. Sometimes this increase causes the fault current level to exceed the ability to disconnect the protective devices, which can cause serious damage to the equipment in the power system. Using fault current limiters (FCLs) in power system is very promising solution in suppressing short circuit current and leads use of protective equipment with low capacities in the network. In this paper, in order to solve the problem of increasing the fault current, first using sensitivity analysis, network candidate lines are selected to install the fault current limiter, which helps to reduce the time and search space to solve the problem. Simultaneously finding the optimal number, location and amount of impedance for the installation of a resistive superconductor limiter is solved using the multi-objective Non-dominated genetic algorithm with non-dominated sorting (NSGA-II). The method presented in a 20 kV ring sample network, simulated in PSCAD software, is evaluated in the presence of distributed generation sources and its efficiency is shown.

کلیدواژه‌ها

Superconducting fault current limiters؛ Optimal positioning؛ Multi-objective genetic algorithm؛ Non-dominated sorting ‎‎(NSGA-II)؛ Sensitivity analysis؛ Search space reduction

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