BOHR Journal of Electrical & Electronic Communication Engineering

Demand side management in electric vehicles for smart charging and discharging based on state aggregation and q-learning

C. R. Rajesh — 2024-01-04

Use of traditional energy sources results in significant pollution. International organizations are making many efforts to reduce emissions of carbon dioxide (CO2). According to research, EVs can reduce CO2 emissions by 28% by the year 2030. However, the prohibitive price of EVs and the scarcity of outlets for charging continue to be two of the biggest barriers to the widespread use of electric vehicles. In this paper, a detailed demand-side management approach for a network-connected, solar-powered electric vehicle charging station is provided. The proposed approach reduces the requirement for conventional power sources and addresses the current problem of insufficient EVCS by using a solar-powered EVCS in order to make up for the electricity used during peak demand. Models for PV power plants, industrial loads, residential loads, and charging stations for electric vehicles were created using the real-time data. Additionally, a method based on deep learning was devised to control the microgrid’s supply of electricity and to recharge the battery of the electric vehicle during off-peak hours. Two alternative machine learning techniques for figuring out the level of charge in a device that stores electricity were also put to the test. Finally, a 24-h case study using the suggested demand management system structure was conducted. The data show that peak consumption is offset by using a charging station for electric vehicles during peak periods.

Optimization of grid connected electric vehicle charging and discharging using Taguchi gray relational analysis

Evangelin Jeba — 2024-01-08

In order to reduce emissions, considerable changes have been made to the power dispatching process. These changes have allowed for multi-level coordination of the transmission network as well as the progressive implementation of source grid monitoring and control. Uncontrolled charging and discharge of large electric vehicles (EVs) will have a negative impact on the network of distribution, but grouping EVs and promoting controlled charging and discharge will reduce the cost of the distribution network. As a result, it is crucial to design a schedule control system that is appropriate for both charging and discharging electric vehicles. A set-up framework for capacity for distribution based on the synchronous load rate and the area power usage plan was developed for charging loads in various locations using Taguchi and Gray relational evaluation. In this experimental design, the vehicle’s ECR, range, and battery stress were considered performance measures, while the control strategy, bank SOC, and UC Os were taken into account as control factors. Peak-to-valley disparities and load changes in distribution networks might be successfully decreased, and unnecessary spending could be eliminated, with the usage of this paradigm. The findings demonstrate that the suggested grid optimization for electric vehicles using Taguchi Gray relational analysis may successfully maintain the voltage offset within the permitted deviation from the voltage range and successfully delay the requirement to invest in the allocation network. The Taguchi orthogonal matrix was used for optimization and analyses were performed using Computational Fluid Dynamics (CFD). The maximum temperature, standard deviation of the surface temperature, and pressure loss at the base were taken into account as evaluation criteria, and the outputs were evaluated using Minitab software. Since there is more than one result parameter, an optimization study was carried out with Taguchi-based multi-response Gray Relational Analysis.

A wideband multiple rectangular slotted patch antenna for 5G applications

Rathna Rajendran — 2024-01-11

A microstrip antenna with four slots in the center of the patch for 5G applications focusing on enhancing bandwidth and other key metrics is presented. The proposed antenna with multiple rectangular slots and a partial ground structure intends to address the difficulties that arise from working with the millimeter-wave frequencies of the 5G network. Operating at a frequency of 28.082 GHz, the antenna exhibits remarkable characteristics that position it as a promising candidate for 5G communication systems. The antenna’s design is based on optimization process that involves iterative modifications to its geometry and structure. The final configuration consists of a rectangular patch incorporated with four symmetric rectangular slots, providing the antenna with the capability to achieve a bandwidth of 2.585 GHz. Constructed on a Rogers RT 5858 with desirable electrical properties, the suggested design provides a radiation efficiency of 73.43%, making it well-suited for high-frequency operations. Simulation results obtained using the CST Microwave Studio suite prove the antenna’s outstanding performance. The return loss curve demonstrates a value of approximately

High-pressure automatic vacuum cleaner using Arduino

M. John Bosco — 2024-02-02

In the modern world, household work has been transformed by new technologies. Some machines were designed to automate tasks previously performed by servants, while others employ new energy sources such as electricity and gas to make dwellings cleaner, safer, and more efficient. This paper proposes a high-pressure automatic vacuum cleaner using Arduino to dry-clean an area automatically. The robot covers the entire room or area by using the border analysis technique. The robot travels in a zigzag path and covers the entire area. It analyses the obstacle in the room by using an ultrasonic sensor. The high-pressure pump will suck the dust particles while traveling, thus cleaning the entire room.