Optimal Charging Schedule for Electric Vehicles in a Microgrid with Renewable Energy Sources using DigSilent Power Factory and Matlab

Kumar, G. Hemath; Gautam, Devansh; Kumar, Pawan

doi:10.1109/iprecon52453.2021.9640703

Cited by 5 publications

(2 citation statements)

References 7 publications

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“…This tool facilitates the analysis of electrical systems, allowing to obtain load flows, fault analysis and stability analysis, among others. It is used in the analysis of generation, transmission, distribution, industrial systems and distributed generation [11], [12].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the generation and protection capabilities of a grid-connected microgrid

Rosero¹,

Rey²,

Osma³

2024

RE&PQJ

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Microgrids have been recognized for benefits to the electrical system such as improved reliability and reduced transmission costs and pollutant emissions. The study of microgrids makes it necessary to know and quantify the performance of technical aspects and identify characteristics to improve their performance. The paper proposes to evaluate the performance of generation and protection of a microgrid connected to the grid based on a procedure that includes the definition of indicators, the use of Power Factory software to obtain results and the weighting of indicators based on the DEMATEL technique. The laboratory microgrid studied is located at the Universidad Industrial de Santander and has three 1.5 kW photovoltaic systems and meets demands of 5 and 10 kWh/day. The results show that its generation and protection capacities have a high performance.

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Section: Introductionmentioning

confidence: 99%

Evaluation of the generation and protection capabilities of a grid-connected microgrid

Rosero¹,

Rey²,

Osma³

2024

RE&PQJ

View full text Add to dashboard Cite

show abstract

“…Utilizing renewable energy resources (RESs) for electric vehicle charging stations presents a cost-effective alternative, reducing reliance on the grid and contributing power back to it. Integrating solar power generation systems on electric vehicle battery swapping stations can further minimize power losses and enhance voltage levels in the power distribution system [2], [3]. The smart grid concept emerges as an effective technology to address environmental concerns.…”

mentioning

confidence: 99%

Optimal Battery Charging Schedule for a Battery Swapping Station of an Electric Bus With a PV Integration Considering Energy Costs and Peak-to-Average Ratio

Boonraksa,

Pinthurat

et al. 2024

IEEE Access

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Across the globe, the adoption of electric vehicles (EVs), particularly in mass transit systems such as electric buses (E-bus), is on the rise in modern cities. This surge is attributed to their environmentally friendly nature, zero carbon emissions, and absence of engine noise. However, the charging of E-bus batteries could impact the peak demand on the main grid and its overall serviceability, especially when numerous batteries are charged simultaneously. This scenario may also lead to increased energy costs. To address the previously mentioned issue, battery swapping is employed at the charging station in lieu of conventional battery charging. In this paper, the battery swapping approach is utilized to establish the optimal battery charging schedule for E-buses, taking into account both energy costs and the peak-to-average ratio (PAR). The E-bus battery swapping stations incorporate photovoltaic (PV) power generation as their energy source. Three metaheuristic algorithms-namely, the binary bat algorithm (BBA), whale optimization algorithm (WOA), and grey wolf optimizer (GWO)-are employed to identify the optimal conditions. The simulation results demonstrate that integrating the optimal battery charging schedule with a PV power generation system in an E-bus battery swapping station can effectively lower energy costs and the PAR when compared to traditional battery charging methods at charging stations. The optimal charging schedule derived through the GWO technique outperforms those obtained from the WOA and BBA techniques. This resulted in a notable reduction in peak demand from 758.41 to 580.73 kW, corresponding to a 23.43% decrease in peak demand. The integration of the GWO with battery charging scheduling and PV installation resulted in a significant 27.63% reduction in energy costs. As per the simulation results, an optimized battery swapping schedule has the potential to lower energy costs and enhance serviceability for the E-bus battery swapping station.INDEX TERMS Battery charging scheduling, battery swapping stations, electric buses, metaheuristic algorithm, peak-to-average ratio. I. INTRODUCTIONAdvancements in electric vehicle (EV) and battery technology have spurred increased usage, supported by governmental advocacy for clean energy, prompting a shift from internal combustion engine cars to electric vehicles. The development of smart cities includes the expansion of electric bus mass transit systems. Major cities are witnessing a growing preference for electric vehicles over traditional internal combustion engine vehicles, particularly in the form of electric buses (Ebus), offering reductions in diesel fuel usage and air pollution

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Optimal PV Sizing of the PV-Based Battery Swapping Stations on the Radial Distribution System using Whale Optimization Algorithm

Boonraksa

Marungsri

et al. 2022

2022 International Conference on Power, Energy and Innovations (ICPEI)

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Optimal Charging Schedule for Electric Vehicles in a Microgrid with Renewable Energy Sources using DigSilent Power Factory and Matlab

Cited by 5 publications

References 7 publications

Evaluation of the generation and protection capabilities of a grid-connected microgrid

Evaluation of the generation and protection capabilities of a grid-connected microgrid

Optimal Battery Charging Schedule for a Battery Swapping Station of an Electric Bus With a PV Integration Considering Energy Costs and Peak-to-Average Ratio

Optimal PV Sizing of the PV-Based Battery Swapping Stations on the Radial Distribution System using Whale Optimization Algorithm

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