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Ljubomir Majdandzic
The Environmental Protection and Energy Efficiency Fund
Computer Science & IT Electrical & Electronics Engineering

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Protection Coordination and Anti Islanding Protection Solution for Biomass Power Plant Connected on Distribution Network Srete N Nikolovski; Marko Vukobratović; Ljubomir Majdandzic
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 6: December 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (632.69 KB) | DOI: 10.11591/ijece.v6i6.pp2526-2537

Abstract

Protection coordination as well as anti-island protection play significant role in the process of biomass power plant connection on the distribution network. Distribution generation island operation in Croatia is unacceptable according to the existing National grid code Paper presents a protection coordination of all passive protections used in the real biomass power plant and connected distriubution network feeder. Short-circuits three phase, two phase and single line to ground faults and generator islanding simulations have been performed and simulated in the time domain at the different network  locations using DIgSILENT Power Factory software. The time-current plots coordination of protective devices are made using Smart PDC module in Easy Power Protector software tool.
ANFIS Used as a Maximum Power Point Tracking Algorithm for a Photovoltaic System Dragan Mlakić; Ljubomir Majdandžić; Srete Nikolovski
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1129.211 KB) | DOI: 10.11591/ijece.v8i2.pp867-879

Abstract

Photovoltaic (PV) modules play an important role in modern distribution networks; however, from the beginning, PV modules have mostly been used in order to produce clean, green energy and to make a profit. Working effectively during the day, PV systems tend to achieve a maximum power point accomplished by inverters with built-in Maximum Power Point Tracking (MPPT) algorithms. This paper presents an Adaptive Neuro-Fuzzy Inference System (ANFIS), as a method for predicting an MPP based on data on solar exposure and the surrounding temperature. The advantages of the proposed method are a fast response, non-invasive sampling, total harmonic distortion reduction, more efficient usage of PV modules and a simple training of the ANFIS algorithm. To demonstrate the effectiveness and accuracy of the ANFIS in relation to the MPPT algorithm, a practical sample case of 10 kW PV system and its measurements are used as a model for simulation. Modelling and simulations are performed using all available components provided by technical data. The results obtained from the simulations point to the more efficient usage of the ANFIS model proposed as an MPPT algorithm for PV modules in comparison to other existing methods.
Co-Authors Dragan Mlakić Marko Vukobratović Srete N Nikolovski Srete Nikolovski