Optimal Location and Determination of Fault Current Limiters in the Presence of Distributed Generation Sources Using a Hybrid Genetic Algorithm
محورهای موضوعی : Electrical EngineeringSalman Amirkhan 1 , Mostafa Rayatpanah Ghadikolaei 2 , Hassan Pourvali Souraki 3
1 - Department of Electrical Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran
2 - MAPNA Operation and Maintenance Co. (O&M), Tehran, Iran
3 - MAPNA Operation and Maintenance Co. (O&M), Tehran, Iran
کلید واژه: Sensitivity analysis, Multi-objective genetic algorithm, optimal positioning, Superconducting fault current limiters, Non-dominated sorting (NSGA-II), Search space reduction,
چکیده مقاله :
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.
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