Model Predictive Control Based Dynamic Power Loss Prediction for Hybrid Energy Storage System in DC Microgrids

Zhang, Xibeng; Wang, Benfei; Gamage, Don; Ukil, Abhisek

doi:10.1109/tie.2021.3108701

Cited by 24 publications

(6 citation statements)

References 25 publications

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“…In addition, since the output power of the distributed power supply is intermittent, its load is also very large. Therefore, it is necessary to add an energy storage system to the microgrid to reduce power fluctuations, thereby ensuring the power balance of the AC-DC hybrid microgrid [10][11][12]. Generally speaking, in an AC microgrid, the energy storage unit acts as a current source to maintain the balance of supply and demand between the power supply and the load.…”

Section: Hybrid Energy Storage Multi-microgrid Structurementioning

confidence: 99%

Power adaptive control of hybrid energy storage multi-microgrid based on edge computing

Luo¹,

Huang²,

Lai³

et al. 2023

Third International Conference on Digital Signal and Computer Communications (DSCC 2023)

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In a microgrid, paralleling multiple bidirectional interface converters can effectively improve the power exchange capability on both sides of the microgrid. However, the power adaptive control problem of paralleling multiple bidirectional interface converters significantly increases the difficulty of microgrid control. The access to the energy storage system can buffer the power fluctuations of the microgrid and reduce the difficulty of power control. In order to ensure the stable operation of the microgrid and improve the power adaptive control accuracy, a hybrid energy storage multi-microgrid power adaptive control method based on edge computing is proposed. The structure of hybrid energy storage multi-microgrid is analyzed, and an automatic management platform for hybrid energy storage multi-microgrid is constructed based on edge computing technology. On this basis, the DC sub-network bus voltage regulation is introduced to adjust the frequency of the reference output voltage of the interface converter to complete the adaptive control of the power exchange on both sides of the AC-DC hybrid microgrid. It is considered to connect the energy storage system in the hybrid microgrid, and realize the power adaptive control of the hybrid energy storage multi-microgrid through power exchange control and autonomous power frequency division adaptive control. The experimental results show that the hybrid energy storage multi-microgrid power control effect of the proposed method is better, and the active power control error is small. It can effectively ensure the stable operation of the hybrid energy storage multi-microgrid and improve the power adaptive control accuracy.

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Section: Hybrid Energy Storage Multi-microgrid Structurementioning

confidence: 99%

Power adaptive control of hybrid energy storage multi-microgrid based on edge computing

Luo¹,

Huang²,

Lai³

et al. 2023

Third International Conference on Digital Signal and Computer Communications (DSCC 2023)

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“…MPC is a kind of lead control method that uses a dynamic model of the system to predict its future response and has the advantages of fast dynamic response and simple design. It has been used widely in the fields of motor control [20][21][22], aircraft [23] and power converters [24][25][26][27][28][29][30][31][32][33][34][35]. In [26], a control method of a five-level grid-connected photovoltaic inverter based on the model predictive control is applied for controlling active and reactive powers injected into the grid.…”

Section: Introductionmentioning

confidence: 99%

“…The proposed MPC method simplifies the controller design considerably. In [34], a dual-layer model predictive control method is proposed to control the charging/discharging behaviors efficiently. Considering the above analysis, the dynamic performance and robustness of the system are improved by using this lead control method.…”

Section: Introductionmentioning

confidence: 99%

A Robust CCS Predictive Current Control for Photovoltaic Energy Storage System Based on a Nonlinear Disturbance Observer

et al. 2023

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This article introduces a new control strategy for a bidirectional DC/DC converter used in photovoltaic energy storage systems (PV-ESSs), aimed to address the DC bus voltage deviation problem. The purpose of this paper is to design and practically implement a robust continuous control set predictive current control (CCS-PCC) method based on a nonlinear disturbance observer (NDO) to tightly regulate the common DC bus voltage in islanded DC microgrids. The CCS-PCC controller is used to replace the current loop PI controller, which effectively overcomes the shortcomings of the traditional linear lag control and improves the dynamic performance of the system. At the same time, the CCS-PCC method solves the inherent defect of finite control set predictive current control (FCS-PCC), where the switching frequency is not fixed. It effectively reduces the current ripple and realizes constant frequency control. In order to effectively suppress the DC bus voltage fluctuation during transients, the nonlinear disturbance observer is designed and combined with CCS-PCC. The feedforward method based on the NDO was utilized to enhance the disturbance rejection capability of the system. The simulation and experimental results show the feasibility and effectiveness of the proposed CCS-PCC+NDO approach, both during transient and steady-state operating conditions.

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“…Much has been achieved in research for the modeling of converters and the design of their compensators. 6,7 Researchers have proposed model predictive control (MPC) to improve the output features; e.g., an event-triggered model predictive control (MPC) method for power converters 8,9 and a dual-layer MPC method were proposed to mitigate the voltage fluctuations. 10,11 Besides, some scholars developed order-reduction methods to achieve simplified control designs for the ease of implementation.…”

Section: Introductionmentioning

confidence: 99%

“…6,7 Researchers have proposed model predictive control (MPC) to improve the output features; e.g., an event-triggered model predictive control (MPC) method for power converters 8,9 and a dual-layer MPC method were proposed to mitigate the voltage fluctuations. 10,11 Besides, some scholars developed order-reduction methods to achieve simplified control designs for the ease of implementation. For example, the Z-source inverter has been modeled as a 4th-order system.…”

Section: Introductionmentioning

confidence: 99%

Design and experimental verification of a simplified controller for high‐order converters

Zhang

Chen

2023

Circuit Theory & Apps

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The modeling of high-order converter systems and design of their closed-loop controllers are difficult due to their high nonlinearity, hence high-order systems, large number of zero-poles, and complex frequency-domain characteristics. To ease the design methodologies, this paper studies high-order power converters and proposes a modeling and control method for such converter systems with order reduction. As an example, the 7th-order non-electrolytic capacitor-I-Z-Source converter (NEC-I-ZSC) is employed to implement the proposed design method. Operational analysis and small signal modeling of the NEC-I-ZSC are conducted, and a reduced-order controller is then devised. Experimental verification is conducted, which prove the feasibility and effectiveness of the proposed design method.

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Model Predictive Control Based Dynamic Power Loss Prediction for Hybrid Energy Storage System in DC Microgrids

Cited by 24 publications

References 25 publications

Power adaptive control of hybrid energy storage multi-microgrid based on edge computing

Power adaptive control of hybrid energy storage multi-microgrid based on edge computing

A Robust CCS Predictive Current Control for Photovoltaic Energy Storage System Based on a Nonlinear Disturbance Observer

Design and experimental verification of a simplified controller for high‐order converters

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