Model predictive control of distributed generation inverter in a microgrid
This paper presents a new control method to regulate various parameters such as voltage, current and power of the inverter interfaced with Distributed Generation (DG) in a microgrid. Model Predictive Control (MPC) is used to control the inverter of the DG using a state-space model of the inverter ba...
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sg-ntu-dr.10356-974052020-03-07T13:24:47Z Model predictive control of distributed generation inverter in a microgrid John, Thomas So, P. L. Wang, Y. Tan, K. T. School of Electrical and Electronic Engineering 2014 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia) DRNTU::Engineering::Electrical and electronic engineering::Electric power This paper presents a new control method to regulate various parameters such as voltage, current and power of the inverter interfaced with Distributed Generation (DG) in a microgrid. Model Predictive Control (MPC) is used to control the inverter of the DG using a state-space model of the inverter based microgrid. The operation of the microgrid is tested under grid-connected and stand-alone conditions. MATLAB/Simulink is used to simulate the proposed microgrid under these two operating conditions. Simulation results show that the DG inverter can operate effectively with MPC in the microgrid to provide the desired voltage, current and power under grid-connected and stand-alone conditions. ASTAR (Agency for Sci., Tech. and Research, S’pore) Accepted version 2015-08-25T07:24:35Z 2019-12-06T19:42:17Z 2015-08-25T07:24:35Z 2019-12-06T19:42:17Z 2014 2014 Conference Paper John, T., Wang, Y., Tan, K.T., & So, P.L. (2014). Model predictive control of distributed generation inverter in a microgrid. 2014 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia), 657-662. https://hdl.handle.net/10356/97405 http://hdl.handle.net/10220/38519 10.1109/ISGT-Asia.2014.6873870 en © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/ISGT-Asia.2014.6873870]. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Electric power John, Thomas So, P. L. Wang, Y. Tan, K. T. Model predictive control of distributed generation inverter in a microgrid |
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This paper presents a new control method to regulate various parameters such as voltage, current and power of the inverter interfaced with Distributed Generation (DG) in a microgrid. Model Predictive Control (MPC) is used to control the inverter of the DG using a state-space model of the inverter based microgrid. The operation of the microgrid is tested under grid-connected and stand-alone conditions. MATLAB/Simulink is used to simulate the proposed microgrid under these two operating conditions. Simulation results show that the DG inverter can operate effectively with MPC in the microgrid to provide the desired voltage, current and power under grid-connected and stand-alone conditions. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering John, Thomas So, P. L. Wang, Y. Tan, K. T. |
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Conference or Workshop Item |
author |
John, Thomas So, P. L. Wang, Y. Tan, K. T. |
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John, Thomas |
title |
Model predictive control of distributed generation inverter in a microgrid |
title_short |
Model predictive control of distributed generation inverter in a microgrid |
title_full |
Model predictive control of distributed generation inverter in a microgrid |
title_fullStr |
Model predictive control of distributed generation inverter in a microgrid |
title_full_unstemmed |
Model predictive control of distributed generation inverter in a microgrid |
title_sort |
model predictive control of distributed generation inverter in a microgrid |
publishDate |
2015 |
url |
https://hdl.handle.net/10356/97405 http://hdl.handle.net/10220/38519 |
_version_ |
1681039057971314688 |