An Input-Series-Output-Parallel Cascaded Converter System Applied to DC Microgrids

Lv, Mingjiu; Wang, Peng; Wei, Yaoquan; Chen, Wen; Li, Jianlin; Jia, Pengyu; Wei, Qingxuan

doi:10.3390/sym15061174

Cited by 3 publications

(1 citation statement)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In contrast to alternative systems of cascading converters, the output voltage as well as the voltage and current sharing of each module are controlled by the dynamical effects of the buck-boost converter [7]. In [8], the goals of the dynamic droop control are to meet the DC microgrid's needs for voltage management and current sharing. It suggests configuring large-signal PI controllers in a way that can maintain optimum power sharing even when power stage parameters change and realize near-time optimal transient improvement in single converters.…”

Section: Introductionmentioning

confidence: 99%

A Distributed Architecture of Parallel Buck-Boost Converters and Cascaded Control of DC Microgrids-Real Time Implementation

Mesbah,

Sayed,

Ahmed

et al. 2024

IEEE Access

View full text Add to dashboard Cite

To enhance the stability and reliability of the system, the converters' parallel operation can be cascaded to address the constraints posed by the substantial integration of renewable resources. Buckboost DC-DC converters are often controlled via a cascaded control approach to allow parallel operation. The converter's output current and its voltage will be controlled by nested loop control. This study proposes adaptive droop control parameters that are updated and verified online using the principal current sharing loops to minimize the fluctuation in load current sharing. When the converters in the microgrid are paralleled, load sharing will be accomplished using the droop control approach in addition to nested proportional-integral-based voltage and current control loops. To restore the correct voltage across the DC microgrid, an outer addition voltage secondary loop will be used, rectifying any voltage disparities caused by the droop management strategy. Several common load resistances and input voltage variations are used to test the suggested method. Using a linearized model, this work assesses the stability and performance of the proposed method. It then confirms the findings with an adequate model created in MATLAB/SIMULINK, Real-Time Simulation Fundamentals, and hardware-based experiments.

show abstract

Section: Introductionmentioning

confidence: 99%

A Distributed Architecture of Parallel Buck-Boost Converters and Cascaded Control of DC Microgrids-Real Time Implementation

Mesbah,

Sayed,

Ahmed

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

ANFIS‐Controlled Boost and Bidirectional Buck‐Boost DC‐DC Converters for Solar PV, Fuel Cell, and BESS‐Based Microgrid Application

Aeggegn,

Nyakoe,

Wekesa

2024

International Transactions on Electrical Energy Systems

View full text Add to dashboard Cite

DC‐DC converters are essential for integrating distributed energy resources into microgrid (MG) systems. These converters are designed to incorporate intermittent renewable energy sources such as solar photovoltaic (PV) panels, fuel cells (FCs), and battery energy storage systems (BESSs) into the grid. However, conventional DC‐DC converters have limitations including lower efficiency, voltage ripple, insufficient voltage regulation, and compatibility issues. This article presents boost and bidirectional buck‐boost converters for direct current microgrid (DCMG) applications, employing an adaptive neuro‐fuzzy inference system (ANFIS) for control. These proposed converter configurations adeptly manage wide input voltage fluctuations from intermittent sources, consistently supplying power to the DC bus at 500 V and 120 V for boost and buck operations, respectively, with an efficiency of 98.8%. The output voltage result shows that the ANFIS‐based boost converter has 10% overshoot as compared to 41% and 50% overshoot in proportional integral (PI) and fuzzy logic controller (FLC), respectively. In both buck and boost modes, the converters’ voltage gain is influenced by duty ratio adjustments only, not sensitive to dynamic input voltage and flexible manipulation of the output voltage for BESS charging. Moreover, the designed converters accommodate load variations within the MG. To assess the converters’ ability to regulate output voltage effectively, PI, FLC, and ANFIS controllers are implemented and compared. And the ANFIS controller demonstrates superior performance, offering faster response times and enhanced stability. Evaluations are conducted through simulations in the MATLAB/Simulink environment.

show abstract

Survey of Optimization Techniques for Microgrids Using High-Efficiency Converters

Peña,

Arevalo,

Ortiz

et al. 2024

Energies

View full text Add to dashboard Cite

Microgrids play a crucial role in modern energy systems by integrating diverse energy sources and enhancing grid resilience. This study addresses the optimization of microgrids through the deployment of high-efficiency converters, aiming to improve energy management and operational efficiency. This study explores the pivotal role of AC-DC and DC-DC bidirectional converters in facilitating energy conversion and management across various sources and storage systems within microgrids. Advanced control methodologies, including model-based predictive control and artificial intelligence, are analyzed for their ability to dynamically adapt to fluctuations in power generation and demand, thereby enhancing microgrid performance. The findings highlight that implementing high-efficiency converters not only enhances power stability and quality but also reduces operational costs and carbon emissions, thereby reinforcing microgrids as a sustainable and effective solution for contemporary energy management challenges. This research contributes to advancing the understanding and implementation of efficient energy systems in microgrids, promoting their widespread adoption in diverse applications.

show abstract

An Input-Series-Output-Parallel Cascaded Converter System Applied to DC Microgrids

Cited by 3 publications

References 30 publications

A Distributed Architecture of Parallel Buck-Boost Converters and Cascaded Control of DC Microgrids-Real Time Implementation

A Distributed Architecture of Parallel Buck-Boost Converters and Cascaded Control of DC Microgrids-Real Time Implementation

ANFIS‐Controlled Boost and Bidirectional Buck‐Boost DC‐DC Converters for Solar PV, Fuel Cell, and BESS‐Based Microgrid Application

Survey of Optimization Techniques for Microgrids Using High-Efficiency Converters

Contact Info

Product

Resources

About