Design of an Off-Grid Photovoltaic Carport for a Full Electric Vehicle Recharging

Benedetti, David; Agnelli, Jacopo; Gagliardi, Alessio; Dini, Pierpaolo; Saponara, Sergio

doi:10.1109/eeeic/icpseurope49358.2020.9160655

Cited by 22 publications

(19 citation statements)

References 1 publication

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“…The difference of functions [f (a n ) − f (a n−1 )] for the chosen points represents the interval on the ordinate marked as (∆y). Considering the previous equation and the relevant connections, it can be expressed as in Equation (7).…”

Section: Applied and Implemented Optimization Methodsmentioning

confidence: 99%

“…Planning the required capacity of service systems is described in various research studies [7][8][9][10][11]. Planning capacity is a strategic process of finding optimal solutions depending on the available resources and current business requirements to ensure the highest possible level of service quality, taking into account the factor of cost minimization.…”

Section: Introductionmentioning

confidence: 99%

“…The area of capacity planning and optimization [19] is a research area with specific well-known methods [7], where factors such as system dynamics, random timing of system events, and especially nonlinear relations are the primary trend of further research in this area. The listed factors are the guidelines for our proposed method, which we present in this paper.…”

Section: Introductionmentioning

confidence: 99%

“…Nowadays, there are two approaches to capacity planning: trending capacity planning [20] and capacity modeling [7], the latter being the newer, more modern approach. Trending capacity planning uses historical patterns that include past events.…”

Section: Introductionmentioning

confidence: 99%

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Method for Planning, Optimizing, and Regulating EV Charging Infrastructure

Chowdhury

Klampfer²,

Sredenšek

et al. 2022

Energies

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The paper presents and solves the problems of modeling and designing the required EV charging service capacity for systems with a slow dynamic component. This includes possible bursts within a peak hour interval. A simulation tool with a newly implemented capacity planning method has been developed and implemented for these needs. The method can be used for different system simulations and simultaneously for systems with high, medium, and low service dynamics. The proposed method is based on a normal distribution, a primary mechanism that describes events within a daily interval (24 h) or a peak hour interval (rush hour). The goal of the presented approach, including the proposed method, is to increase the level and quality of the EV charging service system. The near-optimal solution with the presented method can be found manually by changing the service capacity parameter concerning the criterion function. Manual settings limit the number of rejected events, the time spent in the queue, and other service system performance parameters. In addition to manual search for near-optimal solutions, the method also provides automatic search by using the automation procedure of simulation runs and increasing/decreasing the service capacity parameter by a specifically calculated amount.

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Section: Applied and Implemented Optimization Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Method for Planning, Optimizing, and Regulating EV Charging Infrastructure

Chowdhury

Klampfer²,

Sredenšek

et al. 2022

Energies

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“…Wide-bandgap semiconductors, including SiC and GaN, have the characteristics of high breakdown field strength, low switching loss, and high-temperature resistance, which can significantly improve the efficiency and power density of power modules [1]. Due to the wide bandgap characteristic of SiC, it is quite suitable for high-voltage applications such as high-voltage DC power transmission, automotive, and mechatronic applications [2][3][4][5]. To increase the power density of SiC power modules, their sizes are becoming smaller, and the working voltage and temperature are becoming higher, which makes the packaging insulation withstand greater electrical, thermal, and mechanical stress.…”

Section: Introduction 1motivationmentioning

confidence: 99%

Optimization Design of Packaging Insulation for Half-Bridge SiC MOSFET Power Module Based on Multi-Physics Simulation

Wang

Ding

et al. 2022

Energies

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With the development of power modules for high voltage, high temperature, and high power density, their size is becoming smaller, and the packaging insulation experiences higher electrical, thermal, and mechanical stress. Packaging insulation needs to meet the requirement that internal electric field, temperature, and mechanical stress should be as low as possible. Focusing on the coupling principles and optimization design among electrical, thermal, and mechanical stresses in the power module packaging insulation, a multi-objective optimization design method based on Spice circuit, finite element field numerical calculation, and multi-objective gray wolf optimizer (MOGWO) is proposed. The packaging insulation optimal design of a 1.2 kV SiC MOSFET half-bridge power module is presented. First, the high field conductivity characteristics of the substrate ceramic and encapsulation silicone of the packaging insulation material were tested at different temperatures and external field strengths, which provided the key insulation parameters for the calculation of electric field distribution. Secondly, according to the mutual coupling principles among electric–thermal–mechanical stress, the influence of packaging structure parameters on the electric field, temperature, and mechanical stress distribution of packaging insulation was studied by finite element calculation and combined with Spice circuit analysis. Finally, the MOGWO algorithm was used to optimize the electric field, temperature, and mechanical stress in the packaging insulation. The optimal structural parameters of the power module were used to fabricate the corresponding SiC MOSFET module. The fabricated module is compared with a commercial module by the double-pulse experiment and partial discharge experiment to verify the feasibility of the proposed design method.

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