Now showing 1 - 2 of 2
  • Publication
    Dynamic model of distribution network cell using artificial intelligence approach
    The aim of this project is to develop a dynamic model of distribution network cell (DNC) using artificial intelligence approach. The increasing number of distributed generation (DG) technology has lead to difficulty in modeling the DNC model. The simple load modeling is no longer reliable in presenting the DNC model. In this project,the equivalent dynamic model of DNC consists of the converter-connected generator and the composite load model. The model was developed in the form of seven order state-space model. This model was adopted from Samila Mat Zali in 2012. The parameter estimation of the model was developed using fuzzy system. The parameter value was updated through adaptive neuro-fuzzy inference system (ANFIS). The active and reactive power responses from the fuzzy model were compared with the response from the full DNC model at various types of disturbances. The response of full DNC model was obtained from the UK 11 kV distribution network model. The model was built in DigSILENT PowerFactory software. The full DNC model was also adopted from Samila Mat Zali in 2012. The performance of the fuzzy model was validated by calculating the value of root means square error (RMSE) and the best fit value. Later, the performance of the fuzzy model was also compared with the system identification model by Samila Mat Zali in 2012. The results obtained shown that the fuzzy model was more simple as only a few parameters involved in developing the equivalent model. This simplicity was reflected in the low computational time. The efficiency was also good based on the low RMSE value and high best fit value. In conclusion, the equivalent dynamic model of DNC based on fuzzy system approach was successfully developed.
  • Publication
    Determination of soft starter firing angle performance to mitigate motor high inrush current using current limitation method
    ( 2020-03-20) ;
    Azizan, Muhammad Mokhzaini
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    Md Esa, Suhaireza Binti
    Inrush current in the simplest form can also be determined as current drawn by an induction motor during startup period. This starting current will shoot up about 5 to 7 times the rated current. However, this high current usually occur in the starting period only. To overcome this, several techniques can be implemented to reduce the high current. The configuration of soft starter just involving some power semiconductor device act as switches that control the current flow from power source to the motor. The switches is in form of thyristor and are connected back-to-back because the system conduct in AC system. The current output can be controlled by varying the firing angle. This changing of firing angle will be managed by a firing angle control circuit. This soft starter was connected between power source and motor. The thyristors that built in soft starter act like a gate to control the voltage applied to the motor. The firing angle for current limitation soft starter was changed to several angle and what can be concluded that the high current succeed to mitigate with increasing the firing angle. The current drawn for this type of starter is steadily constant. The lower current during starting took longer time for motor to reach its rated speed. This type of starter successfully reduces inrush current about 42 percent. Finally what can be concluded is that the soft starter was proven to mitigate inrush current. Type of soft starter that going to implement is depending on the application of motor. When the application need to control the torque is more suitable to use current limitation soft starter because the current is steadily control.