This paper presents the design and optimization of a Medium Frequency Transformer (MFT) for use in Solid State Transformer (SST) systems supporting green hydrogen production. Operating at 1 kHz and integrated within an LLC resonant converter, the transformer is optimized for minimal weight and high efficiency while ensuring adequate leakage inductance and insulation performance. A core-type configuration with cylindrical windings was selected based on FEM simulations and mass-efficiency trade-offs. The final prototype, using copper conductors, achieves 97.8% efficiency with a mass below 50 kg and meets the required 7 mH leakage inductance. High-voltage testing, including partial discharge and breakdown tests, confirmed the insulation coordination of the design. The results demonstrate a practical and scalable approach for high-performance SST integration in renewable energy applications.

The energy transition involves integrating numerous pieces of equipment that undergo frequent switching operations and face the risk of lightning strikes. Consequently, power systems are exposed to fast transient switching and lightning surges, necessitating enhanced protection solutions for power equipment. Over the past decade, viable solutions have emerged to mitigate fast transients and safeguard transformers in the form of a ring-core parallel inductor and resistor circuit (R-PIR). Although this device effectively protects medium-voltage transformers from fast transients, a precise and comprehensive model for this component is still lacking, especially considering the importance of refining the R-PIR for broader applications. This paper introduces a detailed model of the R-PIR as a protective device, validated by electromagnetic transient simulations and finite element methods, which are also confirmed by experiments. The main goals of the research work are to investigate the performance and design features of the R-PIR comprehensively and demonstrate how the designed R-PIR protects transformers against fast transients. The research work is validated by experiments conducted in a lab environment. It is concluded that designing the R-PIR within an appropriate frequency range can considerably suppress transient overvoltages to which the transformer is exposed.

For electrolyzer applications, traditional solutions using line frequency transformers plus rectifiers are bulky, heavy and have low controllability. The Solid State Transformer (SST) could be a promising solution to solve the mentioned issues. This paper compares the semiconductor ratings and capacitance of five different Modular Multilevel Converter (MMC) based Solid State Transformer (SST) topologies. The results show that the DRU (Diode Rectifier Unit)-MMC based topologies have the lowest semiconductor ratings and capacitance. Because of the unidirectional power flow requirement, the source side MMC of Back-to-Back (BtB) MMC based SST could be replaced by DRU, thus the cost is drastically saved. Another interesting finding is that the DRU-MMC energy ripple is much lower than half of the energy ripple in BtB MMC, which is different from HVDC MMC.

Green hydrogen production uses renewable energies to energise the electrolysers for hydrogen production. The present paper compares possible solutions and configurations of a medium-frequency transformer (MFT) as part of a solid-state transformer (SST) in green hydrogen production applications. The single-phase and three-phase MFTs are compared and it is shown that a Yd three-phase MFT is the optimum choice for applications that require high power delivery and step-down of the voltage. A summary of previous works about MFT is also provided. Three-phase SST based on modular multilevel converters (MMC) is then described and various cases are investigated to obtain the optimum operational frequency. A 25 MVA, 400 Hz, 25.4 kV / 560V oil-immersed MFT design is presented and is shown that the proposed 400 Hz transformer saves 69% of the active parts' weight compared to a conventional line-frequency transformer (LFT).

One of the major challenges in optical lens design is to ascertain the lens system with the highest image quality. The image quality of the lens system, which is a measure of the performance of the lens, is a function of aberrations. This function is highly nonlinear and leads to the presence of multiple local minima in the design (optimization) landscape. Evolutionary algorithms, specifically Genetic Algorithm, are receiving attention in this field as an efficient global optimization techniques for multi variables and nonlinear objective functions. However, to the best of our knowledge, studies are as yet unavailable to provide an analysis on the performance of GA and the influence of its tuning parameters on the optimization of these systems. Our research has been conducted to supply such information and to provide a guideline on using GA, in GA-aided optical lens designs. The performance of GA has been investigated in a general group of three-lens systems. It is shown that GA is an efficient optimization technique in this field, while applying the suitable tuning parameters of GA is crucial. It has been realized that Gaussian Mutation (Scale of 0.5), combined with Heuristic Crossover, with a Crossover Fraction of 0.6, was the option which yielded good (i.e. the challengeable practically expected) results. However, any variation of these parameters may prevent the system from ever reaching an optimal configuration.