Finite-Control-Set Model-Predictive Control for a Quasi-Z-Source Four-Leg Inverter Under Unbalanced Load Condition

Bayhan, Sertaç; Trabelsi, Mohamed; Abu‐Rub, Haitham; Malinowski, Mariusz

doi:10.1109/tie.2016.2632062

Cited by 117 publications

(62 citation statements)

References 34 publications

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“…(10) The g c term is multiplied with a weighting factor λ der and added to (9). Moreover, the current limiting term h lim , and switching penalization term sw, are also introduced:…”

Section: B Cost Functionmentioning

confidence: 99%

Weighting Factor Design in Model Predictive Control of Power Electronic Converters: An Artificial Neural Network Approach

Dragičević

Novak

2019

IEEE Trans. Ind. Electron.

287

137

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This paper proposes the use of an artificial neural network (ANN) for solving one of the ongoing research challenges in finite-set model predictive control (FS-MPC) of power electronics converters, i.e. the automated selection of weighting factors in cost function. The first step in this approach is to simulate a detailed converter circuit model or run experiments numerous times using different weighting factor combinations. The key performance metrics (e.g. average switching frequency (fsw) of the converter, total harmonic distortion (THD), etc.) are extracted from each simulation. This data is then used to train the ANN, which serves as a surrogate model of the converter that can provide fast and accurate estimates of the performance metrics for any weighting factor combination. Consequently, any arbitrary user-defined fitness function that combines the output metrics can be defined and the weighting factor combinations that optimize the given function can be explicitly found. The proposed methodology was verified on a practical weighting factor design problem in FS-MPC regulated voltage source converter (VSC) for uninterruptible power supply (UPS) system. Designed weighting factors for two exemplary fitness functions turned out to be robust to load variations and to yield close to expected performance when applied both to detailed simulation model (less than 3% error) and to experimental test bed (less than 10% error). Index Terms-Voltage source converter (VSC), finite set model predictive control (FS-MPC), weighing factor design, artificial neural network (ANN).

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“…(10) The g c term is multiplied with a weighting factor λ der and added to (9). Moreover, the current limiting term h lim , and switching penalization term sw, are also introduced:…”

Section: B Cost Functionmentioning

confidence: 99%

Weighting Factor Design in Model Predictive Control of Power Electronic Converters: An Artificial Neural Network Approach

Dragičević

Novak

2019

IEEE Trans. Ind. Electron.

287

137

View full text Add to dashboard Cite

show abstract

“…Also, the proportional-integral-resonant type controller is used to track the sudden power errors. The study in [141] presents a finite-control-set model predictive control for a three-phase inverter under variable load condition. The control method can eliminates the inductor current doubleline frequency ripple with a modest and in effect approach.…”

Section: Intelligent Technique-based Control Of Microgrid Hybrid Enermentioning

confidence: 99%

State of the Ability in Research on Microgrid Hybrid Energy Systems

Akhtar¹,

Kinmani²,

Jamil³

2019

JESTR

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The power demand with interest in green power has focused researcher to develop the distributed power generation using wind energy, solar energy, etc. With the fast depleting fossil fuel reserves, energy security and environmental concerns there is a huge requirement of alternate sources of energy to fulfill the present energy demand. Distribution generating system can support the weak grids, maintaining grid power, managing balance power and enhancing the power quality. Any research work base depends on the literature survey and the studies carried out by several kinds of research and their support to research field encourages for more scope of research. The important advantages related to microgrids have led to huge efforts to grow their dispersion in the power systems. While microgrid is fast growing but there are still various challenges to efficiently control, design, and operate microgrids when linked to the main grid, and also when in islanded mode, where wide research actions are ongoing to handle these issues. This paper presents a review of issues concerning integration of renewable energy sources to microgrids and offers a description of research in areas related to economic feasibility of microgrids system, including dynamic analysis of microgrid hybrid system in grid-connected mode, application of power electronics, microgrid operation, and control.

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“…From another side, model predictive control (MPC) has been widely employed for controlling four-wire inverters [29][30][31][32]. However, MPC methods require precise models and estimation of the power system parameters for stable and efficient control.…”

Section: Introductionmentioning

confidence: 99%

“…The new proposed controller can provide a multifunctional operation of PV systems, while preserving simple implementation and lower number of components compared to [33], eliminating the need for precise modelling compared to the controllers in [29][30][31][32], and being suitable for low-cost microcontroller implementation. From another side, the new proposed system and controller can provide a more efficient and reliable power system operation through the achieved multifunctionalities of neutral current compensation, maximum energy extraction, and local reactive power supply.…”

mentioning

confidence: 99%

Multifunctional Distributed MPPT Controller for 3P4W Grid-Connected PV Systems in Distribution Network with Unbalanced Loads

et al. 2019

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The integration of photovoltaic (PV) systems with three-phase four-wire (3P4W) distribution networks has imposed several challenges related to existing unbalanced loads, reactive power generation and harmonics content. In this paper, a multifunctional distributed maximum power point (MPPT) controller for grid integration of PV systems is proposed. The proposed distributed MPPT controller is developed based on employing a four-leg three-level T-type multilevel inverter. The proposed inverter performs multifunctionalities, including distributed MPPT, neutral current compensation for the unbalanced loads, supplying reactive power into the grid and the grid integration. Moreover, the proposed inverter overcomes the stochastic behavior of both the PV generation with partial shading problems and its operation with unbalanced loads as well. Furthermore, the new proposed controller injects sinusoidal output currents with decreased levels of total harmonic distortion (THD) into the grid. The tested case study is investigated for the various operating scenarios of PV generation and load demands. The results and tabulated performance comparisons have proven the superior performance of the proposed multifunctional PV generation system. The results show the ability of the proposed controller to efficiently extract distributed MPPT for all PV modules at all the tested scenarios. Additional improvement of the energy efficiency is achieved through the elimination of the neutral current due to existing unbalanced loads.

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Finite-Control-Set Model-Predictive Control for a Quasi-Z-Source Four-Leg Inverter Under Unbalanced Load Condition

Cited by 117 publications

References 34 publications

Weighting Factor Design in Model Predictive Control of Power Electronic Converters: An Artificial Neural Network Approach

Weighting Factor Design in Model Predictive Control of Power Electronic Converters: An Artificial Neural Network Approach

State of the Ability in Research on Microgrid Hybrid Energy Systems

Multifunctional Distributed MPPT Controller for 3P4W Grid-Connected PV Systems in Distribution Network with Unbalanced Loads

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