Bisection Algorithm based Indirect Finite Control Set Model Predictive Control for Modular Multilevel Converters

Hamayoon, Saad; Hovd, Morten; Suul, Jon Are

doi:10.1109/compel52922.2021.9646053

Cited by 3 publications

(6 citation statements)

References 16 publications

(30 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This would require only four simulations per time step. It is noted here that Recently, a new cost function was proposed in [17], which eliminates the need for having any kind of additional control over the differential current reference in order to regulate the average summation voltages in both arms. In the second stage of the proposed method, the four options are evaluated by this new cost function which is reproduced below:…”

Section: Problem Formulation For Proposed Methodsmentioning

confidence: 99%

“…The third term would only act if the sum of average summation voltages of both arms is not equal to 2V dc and the fourth term would only act when their difference is not 0. The detailed explanation of the above cost function can be found in [17].…”

Section: Problem Formulation For Proposed Methodsmentioning

confidence: 99%

“…Recently, some other variants of indirect FCS-MPC methods have been presented to address the issue of slow dynamic performance, while keeping the computational complexity low [14]- [17]. In [14], the steady-state and transient state are handled individually.…”

Section: Introductionmentioning

confidence: 99%

“…However, when dealing with MMCs having hundreds of SMs per arm, these methods would have to consider more number of options to ensure proper operation, thus increasing the computational complexity. In [16], backstepping is combined with reduced indirect FCS-MPC and the work in [17] applies a bisection algorithm in the first stage and reduced indirect FCS-MPC in the second stage. These methods simplify the first stage by assuming that the total number of inserted SMs are always equal to N (total number of SMs/arm).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Non-Linear Model Predictive Control for Modular Multilevel Converters

Hamayoon

Hovd

Suul

2022

2022 International Power Electronics Conference (IPEC-Himeji 2022- ECCE Asia)

Self Cite

View full text Add to dashboard Cite

In this paper, non-linear model predictive control (NMPC) without an explicit modulator is applied to modular multilevel converters (MMCs) in the abc reference frame. NMPC can easily be extended for longer prediction horizons as opposed to finite control set model predictive control (FCS-MPC). However, NMPC applied to power converters in previous studies uses a modulator, which limits the transient response compared to FCS-MPC. Therefore, to avoid the modulator, two strategies are presented. In the first strategy, the continuous solution (number of inserted submodules per arm) obtained from NMPC is simply rounded off to the nearest integer for both the arms of each phase. In the second strategy, the optimal solution obtained from the NMPC is further evaluated by rounding it up and down for both arms. This requires four simulations per time step, independently from the number of SMs per arm. The evaluation of the four cases is conducted only for the initial time step within the prediction horizon. Then the solution that minimizes a pre-defined cost function is applied to MMC. The second strategy offers the fastest response and provides similar dynamic performance as indirect FCS-MPC, while both strategies offer similar steady-sate performance. Simulations are performed to validate the performance of the proposed methods compared to the FCS-MPC.

show abstract

Section: Problem Formulation For Proposed Methodsmentioning

confidence: 99%

Section: Problem Formulation For Proposed Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Non-Linear Model Predictive Control for Modular Multilevel Converters

Hamayoon

Hovd

Suul

2022

2022 International Power Electronics Conference (IPEC-Himeji 2022- ECCE Asia)

Self Cite

View full text Add to dashboard Cite

show abstract

“…The cost function adopted in this work was first introduced in [28]. The advantage of such a cost function is that it eliminates the need for having any kind of additional control over circulating current reference in order to regulate the summation of capacitor voltages.…”

Section: A Cost Functionmentioning

confidence: 99%

Fault Detection, Localization and Clearance for MMC based on Indirect Finite Control Set Model Predictive Control

Hamayoon,

Hovd,

Suul

2023

2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE)

Self Cite

View full text Add to dashboard Cite

In this paper, indirect finite control set model predictive control (I-FCS-MPC) is used for detecting, localizing, and tolerating open-circuit failures in the transistors without the use of arm voltage sensors. The fault is detected by the main controller whereas the localization is performed in the local controller which is used for the sorting algorithm. The main controller utilizes the discrete mathematical model to estimate the arm voltages using state measurements from present and previous sampling instants. The arm voltage command given by the main controller in the previous sampling instant is then compared with the estimated arm voltage to detect the fault. The fault signal is sent to the local controller where a counter is increased for the potential faulty submodules (SMs). The fault is then localized to the specific SM whose count first goes above a threshold value. Finally, this SM is bypassed using a bypass switch and a redundant SM is inserted in its place. The proposed fault detection and localization method does not require any additional sensors. Simulation results demonstrate that the fault can be detected, localized, and cleared within one fourth of the fundamental period.

show abstract