An Average Model Predictive Control of Quasi-Z-Source Modular Cascaded Photovoltaic Converter

Yushan Liu; Yaosuo Xue; Mohammad B. Shadmand

doi:10.1109/ECCE.2018.8557968

An Average Model Predictive Control of Quasi-Z-Source Modular Cascaded Photovoltaic Converter

Yushan Liu
, Yaosuo Xue
, Mohammad B. Shadmand

School of Automation Science and Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

An average model predictive control (AMPC) is proposed for dc grid integration of the front-end isolated quasi-Z-source modular cascaded converter (qZS-MCC) photovoltaic (PV) power system. The qZS-MCC deals with PV maximum power point tracking (MPPT), dc grid integration, and de-link voltage balance by the post-stage qZS half-bridge (HB) dc-dc converters, while a unified duty cycle is used in the front-end isolation converters of all submodules (SMs). Thus, it reduces the control resources while overcoming the dc-bus voltage limit because of the PV panel insulation demand. The proposed AMPC of qZS-MCC PV power system predicts the shoot-through duty cycle of each SM for dc-link voltage control, and the total modulation index for dc grid-connected current control; only one proportional-integral (PI) regulator for PV MPPT is required in each SM. Thus, PI regulators are significantly reduced, whereas system dynamic responses are improved, with low computation and simple implementation. Simulation and downscaled experimental results demonstrate the effectiveness of the proposed control.

Original language	English
Title of host publication	2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	6270-6274
Number of pages	5
ISBN (Electronic)	9781479973118
DOIs	https://doi.org/10.1109/ECCE.2018.8557968
State	Published - 3 Dec 2018
Event	10th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2018 - Portland, United States Duration: 23 Sep 2018 → 27 Sep 2018

Publication series

Name	2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018

Conference

Conference	10th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2018
Country/Territory	United States
City	Portland
Period	23/09/18 → 27/09/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

DC-DC power conversion
Model predictive control
Photovoltaic power system
Quasi-Z-source converter

Access to Document

10.1109/ECCE.2018.8557968

Cite this

Liu, Y., Xue, Y., & Shadmand, M. B. (2018). An Average Model Predictive Control of Quasi-Z-Source Modular Cascaded Photovoltaic Converter. In 2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018 (pp. 6270-6274). Article 8557968 (2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ECCE.2018.8557968

@inproceedings{f992f9e929b84849a1a9a3377b53a3e2,

title = "An Average Model Predictive Control of Quasi-Z-Source Modular Cascaded Photovoltaic Converter",

abstract = "An average model predictive control (AMPC) is proposed for dc grid integration of the front-end isolated quasi-Z-source modular cascaded converter (qZS-MCC) photovoltaic (PV) power system. The qZS-MCC deals with PV maximum power point tracking (MPPT), dc grid integration, and de-link voltage balance by the post-stage qZS half-bridge (HB) dc-dc converters, while a unified duty cycle is used in the front-end isolation converters of all submodules (SMs). Thus, it reduces the control resources while overcoming the dc-bus voltage limit because of the PV panel insulation demand. The proposed AMPC of qZS-MCC PV power system predicts the shoot-through duty cycle of each SM for dc-link voltage control, and the total modulation index for dc grid-connected current control; only one proportional-integral (PI) regulator for PV MPPT is required in each SM. Thus, PI regulators are significantly reduced, whereas system dynamic responses are improved, with low computation and simple implementation. Simulation and downscaled experimental results demonstrate the effectiveness of the proposed control.",

keywords = "DC-DC power conversion, Model predictive control, Photovoltaic power system, Quasi-Z-source converter",

author = "Yushan Liu and Yaosuo Xue and Shadmand, \{Mohammad B.\}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 10th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2018 ; Conference date: 23-09-2018 Through 27-09-2018",

year = "2018",

month = dec,

day = "3",

doi = "10.1109/ECCE.2018.8557968",

language = "英语",

series = "2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Liu, Y, Xue, Y & Shadmand, MB 2018, An Average Model Predictive Control of Quasi-Z-Source Modular Cascaded Photovoltaic Converter. in 2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018., 8557968, 2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018, Institute of Electrical and Electronics Engineers Inc., pp. 6270-6274, 10th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2018, Portland, United States, 23/09/18. https://doi.org/10.1109/ECCE.2018.8557968

An Average Model Predictive Control of Quasi-Z-Source Modular Cascaded Photovoltaic Converter. / Liu, Yushan; Xue, Yaosuo; Shadmand, Mohammad B.
2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 6270-6274 8557968 (2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An Average Model Predictive Control of Quasi-Z-Source Modular Cascaded Photovoltaic Converter

AU - Liu, Yushan

AU - Xue, Yaosuo

AU - Shadmand, Mohammad B.

PY - 2018/12/3

Y1 - 2018/12/3

N2 - An average model predictive control (AMPC) is proposed for dc grid integration of the front-end isolated quasi-Z-source modular cascaded converter (qZS-MCC) photovoltaic (PV) power system. The qZS-MCC deals with PV maximum power point tracking (MPPT), dc grid integration, and de-link voltage balance by the post-stage qZS half-bridge (HB) dc-dc converters, while a unified duty cycle is used in the front-end isolation converters of all submodules (SMs). Thus, it reduces the control resources while overcoming the dc-bus voltage limit because of the PV panel insulation demand. The proposed AMPC of qZS-MCC PV power system predicts the shoot-through duty cycle of each SM for dc-link voltage control, and the total modulation index for dc grid-connected current control; only one proportional-integral (PI) regulator for PV MPPT is required in each SM. Thus, PI regulators are significantly reduced, whereas system dynamic responses are improved, with low computation and simple implementation. Simulation and downscaled experimental results demonstrate the effectiveness of the proposed control.

AB - An average model predictive control (AMPC) is proposed for dc grid integration of the front-end isolated quasi-Z-source modular cascaded converter (qZS-MCC) photovoltaic (PV) power system. The qZS-MCC deals with PV maximum power point tracking (MPPT), dc grid integration, and de-link voltage balance by the post-stage qZS half-bridge (HB) dc-dc converters, while a unified duty cycle is used in the front-end isolation converters of all submodules (SMs). Thus, it reduces the control resources while overcoming the dc-bus voltage limit because of the PV panel insulation demand. The proposed AMPC of qZS-MCC PV power system predicts the shoot-through duty cycle of each SM for dc-link voltage control, and the total modulation index for dc grid-connected current control; only one proportional-integral (PI) regulator for PV MPPT is required in each SM. Thus, PI regulators are significantly reduced, whereas system dynamic responses are improved, with low computation and simple implementation. Simulation and downscaled experimental results demonstrate the effectiveness of the proposed control.

KW - DC-DC power conversion

KW - Model predictive control

KW - Photovoltaic power system

KW - Quasi-Z-source converter

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DO - 10.1109/ECCE.2018.8557968

M3 - 会议稿件

AN - SCOPUS:85060275429

T3 - 2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018

SP - 6270

EP - 6274

BT - 2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 10th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2018

Y2 - 23 September 2018 through 27 September 2018

ER -

An Average Model Predictive Control of Quasi-Z-Source Modular Cascaded Photovoltaic Converter

Abstract

Publication series

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UN SDGs

Keywords

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