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Journal : Proceeding of the Electrical Engineering Computer Science and Informatics

PSS Design Based on Fuzzy Controller with Particle Swarm Optimization Tuning Ermanu A. Hakim; Nur Kasan; Nurhadi Nurhadi
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (286.568 KB) | DOI: 10.11591/eecsi.v5.1709

Abstract

The research was conducted for implementing of PSS (Power system stabilizer) which was designed based on the fuzzy logic controller (FLPSS). This approach has a main purpose for stabilizing and improving the damping of synchronous machine. The speed and active power deviation were used as fuzzy controller's inputs. The controller's output was forwarded into AVR subsequently. In order to achieve optimal setting, the optimal criteria of the Integral of Time were multiplied by the Absolute Error (ITAE). The performance of the proposed PSS under small disturbances, system parameters and loading conditions was tested. The experiment's results showed the usefulness of the specified method for damping out the system oscillations.
Design of Hybrid System Power Management Based Operational Control System to Meet Load Demand Zulfatman Has; Nurhadi Nurhadi; Fachmy Faizal
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v5.1713

Abstract

Renewable energy is an energy of unlimited sources that covering wind, sunshine and water, which can be used as sources of renewable power plants. These power plants give several advantages, but also some disadvantages, such as expensive generation costs, etc. The difficulty of being raised, due instability of renewable energy resources (RER). Aim of this study is to design power management of a hybrid system based on operational control system due to load demand. In this study, Power Management of Hybrid System used 3 power plants: Photovoltaic (PV), Wind Power, and Micro Hydro Power Plant (PLTmH), while Battery was employed as storage system. Main focus of the work was to determine the activation of each plant using Artificial Neural Network (ANN) method to fulfill the load demand. Matlab Simulink was employed to developed and simulate the ANN on the system. From results of simulation can be concluded that ANN can reach target accuracy level in 80%. When interconnecting the entire plant, the ANN experienced a misreading due to the voltage drop in each generator that affected the ANN input.