Computationally efficient model predictive direct power control with online finite set model inductance estimation technique for grid-connected photovoltaic inverters

Issa Hammoud; Khaled Morsy; Mohamed Abdelrahem; Ralph Kennel

doi:10.1109/PRECEDE.2019.8753263

Computationally efficient model predictive direct power control with online finite set model inductance estimation technique for grid-connected photovoltaic inverters

Issa Hammoud
, Khaled Morsy
, Mohamed Abdelrahem
, Ralph Kennel

Chair of High-Power Converter Systems

Technical University of Munich

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

2 Scopus citations

Abstract

Model predictive direct power control (MP-DPC) is considered as a convenient control approach for grid-connected inverters, as it eliminates the need for internal control loops and external modulators. In this paper, a computationally efficient MP-DPC scheme is presented, which overcomes the main drawback of the traditional scheme by reducing the calculation burden. Based on the values of the reference and actual power, the reference voltage vector of the inverter can be calculated. By locating this reference voltage vector in the α - β reference frame, only three iterations are required. Hence, the cost function is optimized with a reduced calculation load. The dynamic behavior of the computationally efficient MP-DPC, traditional MP-DPC, and lookup table direct power control (LT-DPC) for grid-connected photovoltaic inverters is compared by simulation results. Furthermore, a novel online inductance estimation technique is proposed to enhance the robustness of the control scheme against any inductance variation.

Original language	English
Title of host publication	Proceedings - PRECEDE 2019
Subtitle of host publication	2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538694145
DOIs	https://doi.org/10.1109/PRECEDE.2019.8753263
State	Published - May 2019
Event	2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2019 - Quanzhou, China Duration: 31 May 2019 → 2 Jun 2019

Publication series

Name	Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics

Conference

Conference	2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2019
Country/Territory	China
City	Quanzhou
Period	31/05/19 → 2/06/19

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Finite set model inductance estimation
Grid-connected inverter
Look-up table direct power control
Model predictive direct power control
Photovoltaic

Access to Document

10.1109/PRECEDE.2019.8753263

Cite this

Hammoud, I., Morsy, K., Abdelrahem, M., & Kennel, R. (2019). Computationally efficient model predictive direct power control with online finite set model inductance estimation technique for grid-connected photovoltaic inverters. In Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics Article 8753263 (Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PRECEDE.2019.8753263

Hammoud, Issa ; Morsy, Khaled ; Abdelrahem, Mohamed et al. / Computationally efficient model predictive direct power control with online finite set model inductance estimation technique for grid-connected photovoltaic inverters. Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics. Institute of Electrical and Electronics Engineers Inc., 2019. (Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics).

@inproceedings{a488c30a8a0b404e8be4774895f2e7f8,

title = "Computationally efficient model predictive direct power control with online finite set model inductance estimation technique for grid-connected photovoltaic inverters",

abstract = "Model predictive direct power control (MP-DPC) is considered as a convenient control approach for grid-connected inverters, as it eliminates the need for internal control loops and external modulators. In this paper, a computationally efficient MP-DPC scheme is presented, which overcomes the main drawback of the traditional scheme by reducing the calculation burden. Based on the values of the reference and actual power, the reference voltage vector of the inverter can be calculated. By locating this reference voltage vector in the α - β reference frame, only three iterations are required. Hence, the cost function is optimized with a reduced calculation load. The dynamic behavior of the computationally efficient MP-DPC, traditional MP-DPC, and lookup table direct power control (LT-DPC) for grid-connected photovoltaic inverters is compared by simulation results. Furthermore, a novel online inductance estimation technique is proposed to enhance the robustness of the control scheme against any inductance variation.",

keywords = "Finite set model inductance estimation, Grid-connected inverter, Look-up table direct power control, Model predictive direct power control, Photovoltaic",

author = "Issa Hammoud and Khaled Morsy and Mohamed Abdelrahem and Ralph Kennel",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2019 ; Conference date: 31-05-2019 Through 02-06-2019",

year = "2019",

month = may,

doi = "10.1109/PRECEDE.2019.8753263",

language = "English",

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Hammoud, I, Morsy, K, Abdelrahem, M & Kennel, R 2019, Computationally efficient model predictive direct power control with online finite set model inductance estimation technique for grid-connected photovoltaic inverters. in Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics., 8753263, Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2019, Quanzhou, China, 31/05/19. https://doi.org/10.1109/PRECEDE.2019.8753263

Computationally efficient model predictive direct power control with online finite set model inductance estimation technique for grid-connected photovoltaic inverters. / Hammoud, Issa; Morsy, Khaled; Abdelrahem, Mohamed et al.
Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics. Institute of Electrical and Electronics Engineers Inc., 2019. 8753263 (Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics).

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

TY - GEN

T1 - Computationally efficient model predictive direct power control with online finite set model inductance estimation technique for grid-connected photovoltaic inverters

AU - Hammoud, Issa

AU - Morsy, Khaled

AU - Abdelrahem, Mohamed

AU - Kennel, Ralph

PY - 2019/5

Y1 - 2019/5

N2 - Model predictive direct power control (MP-DPC) is considered as a convenient control approach for grid-connected inverters, as it eliminates the need for internal control loops and external modulators. In this paper, a computationally efficient MP-DPC scheme is presented, which overcomes the main drawback of the traditional scheme by reducing the calculation burden. Based on the values of the reference and actual power, the reference voltage vector of the inverter can be calculated. By locating this reference voltage vector in the α - β reference frame, only three iterations are required. Hence, the cost function is optimized with a reduced calculation load. The dynamic behavior of the computationally efficient MP-DPC, traditional MP-DPC, and lookup table direct power control (LT-DPC) for grid-connected photovoltaic inverters is compared by simulation results. Furthermore, a novel online inductance estimation technique is proposed to enhance the robustness of the control scheme against any inductance variation.

AB - Model predictive direct power control (MP-DPC) is considered as a convenient control approach for grid-connected inverters, as it eliminates the need for internal control loops and external modulators. In this paper, a computationally efficient MP-DPC scheme is presented, which overcomes the main drawback of the traditional scheme by reducing the calculation burden. Based on the values of the reference and actual power, the reference voltage vector of the inverter can be calculated. By locating this reference voltage vector in the α - β reference frame, only three iterations are required. Hence, the cost function is optimized with a reduced calculation load. The dynamic behavior of the computationally efficient MP-DPC, traditional MP-DPC, and lookup table direct power control (LT-DPC) for grid-connected photovoltaic inverters is compared by simulation results. Furthermore, a novel online inductance estimation technique is proposed to enhance the robustness of the control scheme against any inductance variation.

KW - Finite set model inductance estimation

KW - Grid-connected inverter

KW - Look-up table direct power control

KW - Model predictive direct power control

KW - Photovoltaic

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M3 - Conference contribution

AN - SCOPUS:85069520972

T3 - Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics

BT - Proceedings - PRECEDE 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2019

Y2 - 31 May 2019 through 2 June 2019

ER -

Hammoud I, Morsy K, Abdelrahem M, Kennel R. Computationally efficient model predictive direct power control with online finite set model inductance estimation technique for grid-connected photovoltaic inverters. In Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics. Institute of Electrical and Electronics Engineers Inc. 2019. 8753263. (Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics). doi: 10.1109/PRECEDE.2019.8753263

Computationally efficient model predictive direct power control with online finite set model inductance estimation technique for grid-connected photovoltaic inverters

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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