Gate Drive Circuit Design

Baliga, B. Jayant

doi:10.1016/b978-1-4557-3143-5.00007-9

Cited by 2 publications

(1 citation statement)

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“…A comparison between the size and weight of SSTs and LFTs confirms that the SST structure provides remarkable volume savings, i.e., one-third of LFTs [17,18]. In contrast to traditional setups that are manufactured from copper and iron windings, SSTs have silicon carbide (SiC) windings which is a significant factor in reducing weight [19].…”

Section: Introductionmentioning

confidence: 87%

Comparison of Efficiency-Based Optimal Load Distribution for Modular SSTs with Biologically Inspired Optimization Algorithms

et al. 2022

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The battle of currents between AC and DC reignited as a result of the development in the field of power electronics. The efficiency of DC distribution systems is highly dependent on the efficiency of distribution converter, which calls for optimized schemes for the efficiency enhancement of distribution converters. Modular solid-state transformers (SSTs) play a vital role in DC distribution networks and renewable energy systems (RES). This paper deals with efficiency-based load distribution for solid-state transformers (SSTs) in DC distribution networks. The aim is to achieve a set of minimum inputs that are consistent with the output while considering the constraints and efficiency. As the main feature of modularity is associated with a three-stage structure of SSTs, this modular structure is optimized using ant lion optimizer (ALO) and validated by applying it to the EIA (Energy Information Agency) DC distribution network which contains SSTs. In the DC distribution grid, modular SSTs provide the promising conversion of DC power from medium voltage to lower DC range (400V). The proposed algorithm is simulated in MATLAB and also compared with two other metaheuristic algorithms. The obtained results prove that the proposed method can significantly reduce the input requirements for producing the same output while satisfying the specified constraints.

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Section: Introductionmentioning

confidence: 87%