Constrained Modulated Model Predictive Control for a Three-Phase Three-Level Voltage Source Inverter

Andino, Josue; Ayala, Paúl; Llanos, Jacqueline; Naunay, Diego; Martínez, Wilmar; Arcos-Avilés, Diego

doi:10.1109/access.2022.3144669

Cited by 31 publications

(7 citation statements)

References 40 publications

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“…Based on Condition 1, a graph of the root trajectory of P(z) is given under different k p s. The maximum k p = 2.68 can be obtained according to Figure 5. According to (15), the FRC controls P 0 (z) as a generalized controlled object, and the Bode diagram of P 0 (z) is given in Figure 6. With increasing k p , the phase change in P 0 (z) in the middle− and low−frequency bands becomes smaller; however, at the same time, the stability of P 0 (z) decreases.…”

Section: Parameter Design Of An Frc 421 Frc Gain Coefficient K Pmentioning

confidence: 99%

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A Fast Repetitive Control Strategy for a Power Conversion System

Zhou,

Sun,

Chen

et al. 2024

Electronics

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With the expansion of renewable energy sources, the stable and high-quality operation of microgrids composed of new energy sources has attracted widespread attention. Among them, the power conversion system (PCS), as an important part of microgrids, plays a crucial role in their operation and management. The PCS operation modes are classified into grid-connected and off-grid modes. However, in off-grid mode, due to the access of nonlinear and unbalanced loads, the output voltage quality of a PCS is worse, and the voltage waveform distortion is serious. To solve these problems, a fast repetitive control (FRC) strategy is proposed for a power conversion system with an Active Neutral Point Clamped (ANPC) architecture of three levels. The voltage loop control strategy can be applied to the voltage/frequency (V/f) mode and the grid-forming mode. The control strategy can effectively realize the suppression of the harmonics of the output voltage and has a 100% capability to carry unbalanced loads. Finally, a 1725 kVA PCS prototype is developed, and the proposed control strategy is verified using the MT3200 HIL semiphysical simulator of ModelingTech in the V/f mode as an example. This practically verifies the feasibility and validity of the proposed control strategy, which has a certain degree of engineering practicability and reference due to the simplicity of the design and the ease of realization.

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Section: Parameter Design Of An Frc 421 Frc Gain Coefficient K Pmentioning

confidence: 99%

“…Model Predictive Control (MPC) [14,15]: Carrier-based modulated MPC strategies have demonstrated potential for harmonic suppression and operation with unbalanced loads. However, effective MPC controller design requires careful consideration of dynamic system characteristics, constraints, performance metrics, and computational complexity.…”

mentioning

confidence: 99%

A Fast Repetitive Control Strategy for a Power Conversion System

Zhou,

Sun,

Chen

et al. 2024

Electronics

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“…However, the advantages given by the explicit satisfaction of constraints and the inherent optimality in the formulation of MPC techniques usually comes at the expense of high-computational requirements and having accurate plant models for the purpose of prediction. To dispense with some of these assumptions, Neural Networks (NNs) have also been incorporated in different MPC schemes in [185], [186], [187], [188], [189], and [190]. Similar approaches based on fuzzy control to approximate models and/or parameters were recently studied in [191], [192], [193], [194], [195], and [196].…”

Section: E: Other Primary Control Techniques In Vppsmentioning

confidence: 99%

Control Systems for Low-Inertia Power Grids: A Survey on Virtual Power Plants

et al. 2023

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Virtual Power Plants (VPPs) have emerged as a modern real-time energy management architecture that seeks to synergistically coordinate an aggregation of renewable and non-renewable generation systems to overcome some of the fundamental limitations of traditional power grids dominated by synchronous machines. In this survey paper, we review the different existing and emerging feedback control mechanisms and architectures used for the real-time operation of VPPs. In contrast to other works that have mostly focused on the optimal dispatch and economical aspects of VPPs in the hourly and daily time scales, in this paper we focus on the dynamic nature of the system during the faster sub-hourly time scales. The virtual (i.e., software-based) component of a VPP, combined with the power plant (i.e., physics-based) components of the power grid, make VPPs prominent examples of cyber-physical systems, where both continuous-time and discrete-time dynamics play critical roles in the stability and transient properties of the system. We elaborate on this interpretation of VPPs as hybrid dynamical systems, and we further discuss open research problems and potential research directions in feedback control systems that could contribute to the safe development and deployment of autonomous VPPs.INDEX TERMS Smart grids, renewable energy, virtual power plant, feedback control, multi-agent hybrid dynamical systems.

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“…Artificial neural networks (ANNs), one of the machinelearning techniques whose architecture has been originally inspired by the operation of biological neural networks, are mathematical models that use learning algorithms to make intelligent decisions based on historical data, such as input-to-output mapping. Similar to the human brain, ANNs are composed of a set of processing units, so-called neurons, which have the capability of performing massively parallel computations; neurons are arranged into two or more layers and linked via weighted connections [46]. Nowadays, they are more and more widely used in power electronics applications, with profound and successful contributions to the identification and control of dynamic systems [47]- [48].…”

Section: B Ann-based Control Policymentioning

confidence: 99%