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Journal : Sinergi

Distributed Generation installed by the Phasor Measurement Unit to improve voltage Azriyenni Azhari Zakri; Rangga Eka Saputra; Makmur Saini; Hidayat Hidayat
SINERGI Vol 26, No 1 (2022)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2022.1.006

Abstract

This study is intended to design a system connected to the Distributed Generation (DG) sourced from solar cells, using Matlab/Simulink. A Phasor Measurement Unit (PMU) is installed in the DG system to monitor the phasor voltage and current. Furthermore, the system comprises four buses with two 20 kV load voltages, two amplifying transformers, and four transmission lines. The DG's role is to keep the power supply to the load stable and improve power efficiency by reducing power losses on the network. However, in this network, the DG increases the current on each bus. Thus, affecting voltage increase on each bus, consequently increasing the stress experienced by both loads. The DG-connected system simulation on PMU-3 & PMU-4 has a minute error value of 0.02% and is slightly higher than the unconnected simulation. This comparison also shows the positive sequence values of the phasor currents as well as phasor voltages before and after the DG connection. The DG system connected to the PMU has monitored voltage and current for PLN and DG systems based on the simulation results. Therefore, installing the DG can increase the line voltage, especially on the load.
Modeling and implementing a load management system for a solar home system based on Fuzzy Logic Makmur Saini; Muhammad Ruswandi Djalal; Muhammad Azhar; Golda Evangelista Patrix
SINERGI Vol 27, No 2 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.2.014

Abstract

Solar Home System is one of the technologies for utilizing solar power at home. To optimize the performance of PLTS, it is necessary to regulate the use of electrical energy. In this research, an effort is made to control the load using fuzzy logic to regulate the power consumption used by the load so that energy can be utilized effectively. The fuzzy logic method works based on the input given so that the desired results can be as expected. To test the effectiveness of the fuzzy logic method, this study was tested with two types of loads: lighting and fan loads. For lighting loads, it uses two light sensor inputs, and for air conditioning, it uses two temperature sensor inputs and a PIR sensor. The test results show that in the experiment of setting the light load using fuzzy logic, the average power usage at the load is 11.31 watts. In contrast, without fuzzy logic, the average power usage value for the load is 14.29 watts. In the fan load control experiment using fuzzy logic, the energy consumption setting was obtained according to the room temperature input and the number of people in the room. The test results received power usage without using fuzzy logic, where the average fan power usage value is 4.32 Watts, while without fuzzy logic, the average power usage value is 2.97 Watts. For one sensor input, the average power usage value of the average fan is 3.02 Watts; without fuzzy logic, the average power usage value is 2.93 Watts for two sensor inputs.