Control of Grid Connected Inverters Using Minimum Variance Adaptive Architecture

Rojan Bhattarai; Niroj Gurung; Sukumar Kamalasadan

doi:10.1109/PEDES.2016.7914532

Control of Grid Connected Inverters Using Minimum Variance Adaptive Architecture

Rojan Bhattarai
, Niroj Gurung
, Sukumar Kamalasadan

Energy & Environmental Science & Technology

Research output: Contribution to conference › Paper › peer-review

3 Scopus citations

Abstract

This paper presents a system identification based minimum variance architecture for active and reactive power control of a Grid Connected Inverter (GCI). The controller is adaptive as the parameters in the control law are updated online based on identification that relate the output (active and reactive power) and the input (direct and quadrature axis voltage references). The main advantage of the proposed controller is the simplicity in design and its adaptability under varying operating conditions. The paper discusses the design of the controller and presents the simulation results from tests performed using MATLAB SimPowerSystems along with the Hardware-in-the-loop (HIL) implementation. The results show that the proposed controller can be a better alternative to the existing cascaded PI based vector control for grid connected inverters.

Original language	English
Pages	1-6
Number of pages	6
DOIs	https://doi.org/10.1109/PEDES.2016.7914532
State	Published - Apr 27 2017
Event	2016 IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2016 - Trivandrum, Kerala, India Duration: Dec 14 2016 → Dec 17 2016

Conference

Conference	2016 IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2016
Country/Territory	India
City	Trivandrum, Kerala
Period	12/14/16 → 12/17/16

Keywords

Grid Connected Inverters
Minimum Variance Control
Recursive Least Square Identification
Renewable energy
Vector control

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10.1109/PEDES.2016.7914532

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abstract = "This paper presents a system identification based minimum variance architecture for active and reactive power control of a Grid Connected Inverter (GCI). The controller is adaptive as the parameters in the control law are updated online based on identification that relate the output (active and reactive power) and the input (direct and quadrature axis voltage references). The main advantage of the proposed controller is the simplicity in design and its adaptability under varying operating conditions. The paper discusses the design of the controller and presents the simulation results from tests performed using MATLAB SimPowerSystems along with the Hardware-in-the-loop (HIL) implementation. The results show that the proposed controller can be a better alternative to the existing cascaded PI based vector control for grid connected inverters.",

keywords = "Grid Connected Inverters, Minimum Variance Control, Recursive Least Square Identification, Renewable energy, Vector control",

author = "Rojan Bhattarai and Niroj Gurung and Sukumar Kamalasadan",

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AU - Bhattarai, Rojan

AU - Gurung, Niroj

AU - Kamalasadan, Sukumar

PY - 2017/4/27

Y1 - 2017/4/27

N2 - This paper presents a system identification based minimum variance architecture for active and reactive power control of a Grid Connected Inverter (GCI). The controller is adaptive as the parameters in the control law are updated online based on identification that relate the output (active and reactive power) and the input (direct and quadrature axis voltage references). The main advantage of the proposed controller is the simplicity in design and its adaptability under varying operating conditions. The paper discusses the design of the controller and presents the simulation results from tests performed using MATLAB SimPowerSystems along with the Hardware-in-the-loop (HIL) implementation. The results show that the proposed controller can be a better alternative to the existing cascaded PI based vector control for grid connected inverters.

AB - This paper presents a system identification based minimum variance architecture for active and reactive power control of a Grid Connected Inverter (GCI). The controller is adaptive as the parameters in the control law are updated online based on identification that relate the output (active and reactive power) and the input (direct and quadrature axis voltage references). The main advantage of the proposed controller is the simplicity in design and its adaptability under varying operating conditions. The paper discusses the design of the controller and presents the simulation results from tests performed using MATLAB SimPowerSystems along with the Hardware-in-the-loop (HIL) implementation. The results show that the proposed controller can be a better alternative to the existing cascaded PI based vector control for grid connected inverters.

KW - Grid Connected Inverters

KW - Minimum Variance Control

KW - Recursive Least Square Identification

KW - Renewable energy

KW - Vector control

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T2 - 2016 IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2016

Y2 - 14 December 2016 through 17 December 2016

ER -

Control of Grid Connected Inverters Using Minimum Variance Adaptive Architecture

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