Reactive power compensation using D-STATCOM based on model predictive control

Reactive power compensation and harmonics control are becoming important tasks to sustain the quality of power supply in microgrids. A distribution static synchronous compensator (D-STATCOM) is a device which is generally used to provide compensation of the reactive power, and it also has the functi...

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Bibliographic Details
Main Author: Li, Weiyi
Other Authors: Gooi Hoay Beng
Format: Final Year Project (FYP)
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/10356/75118
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author Li, Weiyi
author2 Gooi Hoay Beng
author_facet Gooi Hoay Beng
Li, Weiyi
author_sort Li, Weiyi
collection NTU
description Reactive power compensation and harmonics control are becoming important tasks to sustain the quality of power supply in microgrids. A distribution static synchronous compensator (D-STATCOM) is a device which is generally used to provide compensation of the reactive power, and it also has the function of controlling harmonics in microgrids. However, the traditional hysteresis method used to control the D-STATCOM has some shortcomings. Using the model predictive control (MPC) based D-STATCOM can get better reactive power compensation effects and reduce the harmonics. In this project, the mathematical model of the integrated system was formulated and built up on the Simulink platform. Then the instantaneous reactive power (IRP) theory was used to calculate the reference current. After that, the principle of the hysteresis based D-STATCOM and MPC based D-STATCOM were discussed and built in the Simulink platform. Finally the discrete time simulation and real-time simulation were carried out on the Simulink platform and OPAL-RT. Their performances were also compared and discussed.
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spelling ntu-10356/751182023-07-07T17:50:23Z Reactive power compensation using D-STATCOM based on model predictive control Li, Weiyi Gooi Hoay Beng School of Electrical and Electronic Engineering DRNTU::Engineering Reactive power compensation and harmonics control are becoming important tasks to sustain the quality of power supply in microgrids. A distribution static synchronous compensator (D-STATCOM) is a device which is generally used to provide compensation of the reactive power, and it also has the function of controlling harmonics in microgrids. However, the traditional hysteresis method used to control the D-STATCOM has some shortcomings. Using the model predictive control (MPC) based D-STATCOM can get better reactive power compensation effects and reduce the harmonics. In this project, the mathematical model of the integrated system was formulated and built up on the Simulink platform. Then the instantaneous reactive power (IRP) theory was used to calculate the reference current. After that, the principle of the hysteresis based D-STATCOM and MPC based D-STATCOM were discussed and built in the Simulink platform. Finally the discrete time simulation and real-time simulation were carried out on the Simulink platform and OPAL-RT. Their performances were also compared and discussed. Bachelor of Engineering 2018-05-28T06:38:06Z 2018-05-28T06:38:06Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/75118 en Nanyang Technological University 57 p. application/pdf
spellingShingle DRNTU::Engineering
Li, Weiyi
Reactive power compensation using D-STATCOM based on model predictive control
title Reactive power compensation using D-STATCOM based on model predictive control
title_full Reactive power compensation using D-STATCOM based on model predictive control
title_fullStr Reactive power compensation using D-STATCOM based on model predictive control
title_full_unstemmed Reactive power compensation using D-STATCOM based on model predictive control
title_short Reactive power compensation using D-STATCOM based on model predictive control
title_sort reactive power compensation using d statcom based on model predictive control
topic DRNTU::Engineering
url http://hdl.handle.net/10356/75118
work_keys_str_mv AT liweiyi reactivepowercompensationusingdstatcombasedonmodelpredictivecontrol