EPE Association: EPE 2022 - LS7b: Grid Connected Converters

EPE 2022 - LS7b: Grid Connected Converters
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2022 ECCE Europe - Conference > EPE 2022 - Topic 02: Power Converter Topologies and Design > EPE 2022 - LS7b: Grid Connected Converters

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   Constant DC power infeed grid forming with improved ability to ride-through unbalanced low-voltage faults
By Tayssir HASSAN [View]
[Download]

Abstract: A new optimized grid-forming control strategy based on matching control is presented, which can beused in an unbalanced system and provides minimum frequency support by utilizing the energy stored inthe dc-link capacitor. Simulation and measurements in different scenarios and under asymmetrical gridfaults evaluate the proposed strategy.

   Difference in the design process of LCL filters for grid connected VSI when using SiC/GaN instead of Si semiconductors
By Dennis KAMPEN [View]
[Download]

Abstract: Although the design of LCL filters has been discussed extensively in recent years, the different requirements for the design process when using SiC/GaN semiconductors instead of classical Si semiconductors have not been presented in detail. Due to the higher switching frequency, new EMI limits in lower frequency range and other influencing factors, there are some differences, which must be taken into account in the design process. This enables a more resource-saving use of materials as well as a faster development time.

   Estimation of Battery Parameters in Cascaded Half-Bridge Converters with Reduced Voltage Sensors
By Nima TASHAKOR [View]
[Download]

Abstract: Although modular multilevel converters (MMC) and cascaded half-bridge (CHB) converters are an established concept in HVDC, MMCs and CHBs have started to find new applications, including modular converters with integrated energy storage systems. Despite various advantages of the low-voltage modularity, a complex and expensive monitoring/control system can hinder finding a foothold in many emerging applications that are more cost-driven, such as the e-mobility market. Estimators and observers can reduce the monitoring cost and complexity by reducing the number of required sensors and communication bandwidth. However, estimation methods rarely consider MMCs with integrated battery, and most available methods neglect all resistances. This paper fills this gap by developing an online estimation technique for parameters of all battery modules in an MMC. The proposed method exploits the slow dynamics of the battery to use a simpler and less computationally demanding algorithm that can easily be implemented in low-end controllers. Based on the developed model of the system, the iterative algorithm can estimate the voltage and internal resistance of every module through measuring the output voltage and current of the battery pack and avoid direct measurements from the modules. As a result of substantial reduction in the number of monitoring sensors for estimating the battery parameters, the proposed technique is simpler and less costly in comparison with other sensor-based techniques. Furthermore, the proposed technique accelerates convergence using optimal learning rate value. Simulations validate the ability of the proposed estimation technique under different scenarios. The estimation technique can identify both internal resistance and open-circuit voltage of the batteries with approximately 2 \% accuracy.

EPE 2022 - LS7b: Grid Connected Converters
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2022 ECCE Europe - Conference > EPE 2022 - Topic 02: Power Converter Topologies and Design > EPE 2022 - LS7b: Grid Connected Converters
	[return to parent folder]

	Constant DC power infeed grid forming with improved ability to ride-through unbalanced low-voltage faults By Tayssir HASSAN	[View] [Download]
Abstract: A new optimized grid-forming control strategy based on matching control is presented, which can beused in an unbalanced system and provides minimum frequency support by utilizing the energy stored inthe dc-link capacitor. Simulation and measurements in different scenarios and under asymmetrical gridfaults evaluate the proposed strategy.

	Difference in the design process of LCL filters for grid connected VSI when using SiC/GaN instead of Si semiconductors By Dennis KAMPEN	[View] [Download]
Abstract: Although the design of LCL filters has been discussed extensively in recent years, the different requirements for the design process when using SiC/GaN semiconductors instead of classical Si semiconductors have not been presented in detail. Due to the higher switching frequency, new EMI limits in lower frequency range and other influencing factors, there are some differences, which must be taken into account in the design process. This enables a more resource-saving use of materials as well as a faster development time.

	Estimation of Battery Parameters in Cascaded Half-Bridge Converters with Reduced Voltage Sensors By Nima TASHAKOR	[View] [Download]
Abstract: Although modular multilevel converters (MMC) and cascaded half-bridge (CHB) converters are an established concept in HVDC, MMCs and CHBs have started to find new applications, including modular converters with integrated energy storage systems. Despite various advantages of the low-voltage modularity, a complex and expensive monitoring/control system can hinder finding a foothold in many emerging applications that are more cost-driven, such as the e-mobility market. Estimators and observers can reduce the monitoring cost and complexity by reducing the number of required sensors and communication bandwidth. However, estimation methods rarely consider MMCs with integrated battery, and most available methods neglect all resistances. This paper fills this gap by developing an online estimation technique for parameters of all battery modules in an MMC. The proposed method exploits the slow dynamics of the battery to use a simpler and less computationally demanding algorithm that can easily be implemented in low-end controllers. Based on the developed model of the system, the iterative algorithm can estimate the voltage and internal resistance of every module through measuring the output voltage and current of the battery pack and avoid direct measurements from the modules. As a result of substantial reduction in the number of monitoring sensors for estimating the battery parameters, the proposed technique is simpler and less costly in comparison with other sensor-based techniques. Furthermore, the proposed technique accelerates convergence using optimal learning rate value. Simulations validate the ability of the proposed estimation technique under different scenarios. The estimation technique can identify both internal resistance and open-circuit voltage of the batteries with approximately 2 \% accuracy.