A Novel Integrated Topology to Interface Electric Vehicles and Renewable Energies with the Grid

Alvarez-Diazcomas, Alfredo; López, Hugo A.; Carrillo-Serrano, Roberto V.; Rodríguez‐Reséndiz, Juvenal; Vázquez, N.; Herrera-Ruíz, Gilberto

doi:10.3390/en12214091

Cited by 18 publications

(11 citation statements)

References 53 publications

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“…Based on the spectral dependence of the photoresponse of GeSi NCs:SiO 2 photodetector, we chose as the illumination source two laser diodes emitting about 200 mW in near-infrared (NIR), one laser diode RLT980-150GS of 150 mW from Roithner Lasertechnik with a wavelength of λ = 980 nm and another laser diode M9-A64-0200 of 200 mW from Thorlabs with a wavelength of λ = 1064 nm. The system is designed to be placed along the roads using an electric grid or independent renewable energy sources but could also be easily implemented in a novel integrated topology for electric vehicles [35]. The laser light and specular/diffuse reflections of light from the asphalt is collimated by using a collimator with a quartz lens and a parabolic mirror as shown in the Figure 4a.…”

Section: Data Acquisition Systemmentioning

confidence: 99%

GeSi Nanocrystals Photo-Sensors for Optical Detection of Slippery Road Conditions Combining Two Classification Algorithms

Palade

Stavarache

Stoïca

et al. 2020

Sensors

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One of the key elements in assessing traffic safety on the roads is the detection of asphalt conditions. In this paper, we propose an optical sensor based on GeSi nanocrystals embedded in SiO2 matrix that discriminates between different slippery road conditions (wet and icy asphalt and asphalt covered with dirty ice) in respect to dry asphalt. The sensor is fabricated by magnetron sputtering deposition followed by rapid thermal annealing. The photodetector has spectral sensitivity in the 360–1350 nm range and the signal-noise ratio is 102–103. The working principle of sensor setup for detection of road conditions is based on the photoresponse (photocurrent) of the sensor under illumination with the light reflected from the asphalt having different reflection coefficients for dry, wet, icy and dirty ice coatings. For this, the asphalt is illuminated sequentially with 980 and 1064 nm laser diodes. A database of these photocurrents is obtained for the different road conditions. We show that the use of both k-nearest neighbor and artificial neural networks classification algorithms enables a more accurate recognition of the class corresponding to a specific road state than in the case of using only one algorithm. This is achieved by comparing the new output sensor data with previously classified data for each algorithm and then by performing an intersection of the algorithms’ results.

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Section: Data Acquisition Systemmentioning

confidence: 99%

GeSi Nanocrystals Photo-Sensors for Optical Detection of Slippery Road Conditions Combining Two Classification Algorithms

Palade

Stavarache

Stoïca

et al. 2020

Sensors

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“…Transformerless inverters have been developed to avoid these limitations [11]. Alfredo Alvarez-Diazcomas et al [12] proposed a bidirectional, multiple-input DC-DC converter topology which allows the interaction of the energy sources with a wide range of voltages. Adyr A. Estévez-Bén et al [13] presented a new predictive-control strategy for the multilevel, current-source inverters' topology to simplify the calculation.…”

Section: Introductionmentioning

confidence: 99%

Power Dispatching of Multi-Microgrid Based on Improved CS Aiming at Economic Optimization on Source-Network-Load-Storage

Wang

Zhao

et al. 2022

Electronics

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The multi-microgrid is gradually springing up with widespread use of the distributed generation. It is of great meaning to have research on the energy mutual optimization of the multi-microgrid to improve the new energy-consumption capacity. In this paper, a comprehensive economic model of the multi-microgrid is proposed for optimizing the power dispatching, and the source-network-load-storage is taken into account. Different from other studies, the special novelty of this paper is the improved cuckoo search (CS) algorithm which is adopted to optimize the power dispatching of the multi-microgrid. Comparing with the particle swarm optimization (PSO) algorithm, the improved CS algorithm has better performance in solving the proposed model. The optimal power supply strategy is determined by predicting the optimal state of charge of the battery in the model of the multi-microgrid. The model effectiveness of the multi-microgrid is confirmed in the case study of Wangjiazhai area. With this method, the optimal power dispatching is determined.

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“…Since microgrids are typically composed of different technologies and energy physics, power electronics converters are essential components that must be included in the MEG systems to integrate various energy networks, which consist of electronic devices able to convert electric energy from one form to another, such as alternating (AC) and direct current (DC), and also allowing the adjustment in energy voltage, current, and frequency [22]. Additionally, power converters can be used to increase maneuver abilities in hybrid systems, especially with renewable sources, by controlling the extracted power in each source and stabilizing the energy flows between components [23].…”

Section: Introductionmentioning

confidence: 99%

Demonstration of Resilient Microgrid with Real-Time Co-Simulation and Programmable Loads

et al. 2022

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In recent years, the foment for sustainable and reliable micro energy grid (MEG) systems has increased significantly, aiming mainly to reduce the dependency on fossil fuels, provide low-cost clean energy, lighten the burden, and increase the stability and reliability of the regional electrical grid by having interconnected and centralized clean energy sources, and ensure energy resilience for the population. A resilient energy system typically consists of a system able to control the energy flow effectively by backing up the intermittent output of renewable sources, reducing the effects of the peak demand on the grid side, considering the impact on dispatch and reliability, and providing resilient features to ensure minimum operation interruptions. This paper aims to demonstrate a real-time simulation of a microgrid capable of predicting and ensuring energy lines run correctly to prevent or shorten outages on the grid when it is subject to different disturbances by using energy management with a fail-safe operation and redundant control. In addition, it presents optimized energy solutions to enhance the situational awareness of energy grid operators based on a graphical and interactive user interface. To expand the MEG’s capability, the setup integrates real implemented hardware components with the emulated components based on real-time simulation using OPAL-RT OP4510. Most hardware components are implemented in the lab to be modular, expandable, and flexible for various test scenarios, including fault imitation. They include but are not limited to the power converter, inverter, battery charger controller, relay drivers, programmable AC and DC loads, PLC, and microcontroller-based controller. In addition, the real-time simulation offers a great variety of power sources and energy storage such as wind turbine emulators and flywheels in addition to the physical sources such as solar panels, supercapacitors, and battery packs.

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A Novel Integrated Topology to Interface Electric Vehicles and Renewable Energies with the Grid

Cited by 18 publications

References 53 publications

GeSi Nanocrystals Photo-Sensors for Optical Detection of Slippery Road Conditions Combining Two Classification Algorithms

GeSi Nanocrystals Photo-Sensors for Optical Detection of Slippery Road Conditions Combining Two Classification Algorithms

Power Dispatching of Multi-Microgrid Based on Improved CS Aiming at Economic Optimization on Source-Network-Load-Storage

Demonstration of Resilient Microgrid with Real-Time Co-Simulation and Programmable Loads

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