2021
DOI: 10.1007/s40435-020-00747-3
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Dynamic voltage stability for embedded electrical networks in marine vessels using FACTS devices

Abstract: Sophisticated techniques are required for getting accuracy in high frequency power losses of magnetic. This paper presents a high frequency power loss measurement platform (full bridge) that provides accurate assessing of losses in magnetic components. This is obtained by a construction of a thermal shunt with radiator to measure the losses of the bridge. An aluminum strip is used as a "thermal resistor". Two NTC resistors measure the temperature drop across the aluminum strip. The magnetic device loss equals … Show more

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Cited by 3 publications
(4 citation statements)
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“…is the reference frame, then the model of PMSG generators and PWM rectifier can be expressed in the reference frame as follows [53][54][55]:…”
Section: Drive-train Modelmentioning
confidence: 99%
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“…is the reference frame, then the model of PMSG generators and PWM rectifier can be expressed in the reference frame as follows [53][54][55]:…”
Section: Drive-train Modelmentioning
confidence: 99%
“…In this control, the voltage orientation strategy is used to regulate the DC voltage link of PWM rectifier. This technique is described and detailed in various research papers [54,58]. Moreover, the principle of the VOC strategy is based on orienting the current and voltage vectors in the same direction for obtaining a unity power factor.…”
Section:  mentioning
confidence: 99%
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“…Fractional Levy light-BatAlgorithm [20], Hybrid Cuckoo-Search-Algorithm [21], Modified-Differential evolution [22], Combined pso-based CPF [23], numerous-sensitivity-based-approaches [24], genetic algorithm [25][26][27][28][29][30][31][32], refined-power-flow-algorithm [33], multiverse optimizer [34], reactive power dispatch problem [35], adaptive grass hooper optimization [36], Heuristic-Techniques [37], MILP-based-OPF [38], AWO-optimization [39], Gravitational-search-assisted algorithm [40][41][42], whale-optimization-algorithm [43,44], novel-lightning search-algorithm [45], PSO-adaptive-G.S.A. hybrid-algorithm [46], self-adaptive-DE-algorithm [47], fuzzy-harmony search algorithm [48], imperialisticcompetitive-algorithm [49], quasi-oppositional-chemical reaction optimization [50], brain-storm-optimization-algorithm [51], hybrid immune algorithm [52], teachinglearning-based-optimization [53], marine-vessels-analysis [54], optimal-power-flowproblem [55], evolutionary-particle swarm optimization [56], blended-moth flame optimization [57], population-based-evolutionary-optimization [58], MOPSO-algorithm [59], particle-swarm...…”
Section: Introductionmentioning
confidence: 99%