BITS Faculty Publications
Permanent URI for this communityhttp://localhost:4000/handle/123456789/1867
Browse
3 results
Search Results
Item Optimal scheduling of mobile and stationary electric vehicle charging stations in a distribution system with stochastic loading(Elsevier, 2025-07) Mishra, Puneet; Mathur, Hitesh DattDue to surge in the use of electric vehicles (EVs), electric vehicle charging station (EVCS) load modelling emerges to be vital in designing or revamping existing EV charging facilities. The present work addresses this optimal scheduling problem by proposing a novel probabilistic model to predict the optimum demand at a charging station for fixed time duration and thereafter for variable durations using dynamic fault tree analysis considering the charging urgency of the vehicles. To cater to the increased load demand due to enhanced EV penetration and to mitigate its associated technical challenges, incorporation of Mobile Charging Station (MCS) is proposed in the present work. However, placement of MCS poses a significant challenge of their optimal siting and scheduling. This has been achieved by identifying priority areas for their positioning from a proposed Mobile Charging Station Allocation Indicator (MCSAI) computed based on escalated requirement at an EVCS. Extensive investigations have been conducted for placement of combination of fixed and mobile EVCS in a standard IEEE 33 and 85 bus distribution system and it is shown that the resultant hybrid system leads to a significant improvement of more than 5 %, 15 % and 25, 30 % respectively as measured by indices such as line loss reduction index voltage profile improvement index.Item Performance assessment of a distribution system with electric vehicle charging station and forecasted loads(Springer, 2025-05) Mishra, Puneet; Mathur, Hitesh DattA trend towards green transportation causes huge escalation in the use of electric vehicles. Therefore, proper evaluation of the burden on a charging changing station is immensely essential. This work propounds a novel technique based on probabilistic estimation of the total demand at an Electric Vehicle Charging Station (EVCS) for certain fixed hourly durations of time and then on the basis of vehicle categorisation dependent on the exigency of the vehicles. Based on the probabilistic estimation of EVCS loads, an optimum mix of charging stations is positioned strategically in an IEEE 33 bus distribution system designed on a methodology based on apparent power loss. The system with EVCS positioned at the optimal points is analysed with the help of two assessment indicators, namely line loss reduction index and voltage profile improvement index. The performance of the aforesaid system is strengthened by the addition of distributed generators at the aptly sited locations.Item Probabilistic Modeling and Outage Analysis for Smart Microgrid and Electric Vehicles Ecosystem(IEEE, 2023) Bitragunta, Sainath; Mishra, PuneetIn this work, we propose a simple yet novel prob-abilistic model for a renewable smart-grid and electric vehi-cle (EV) ecosystem supported by cellular vehicle-to-grid (C- V2G) infrastructure. Our stochastic model accounts for two key energy components modeled as random variables: the energy available from renewable sources and energy consumed by the EV. We define novel performance measures, desire probability, and threshold for the ratio of two energy components for this stochastic model. For it, we develop an insightful analysis that includes mathematical derivations for obtaining a single integral expression for the desired probability for a stable green grid- EV ecosystem operation. We present various numerical plots with varying model parameters and obtain useful insights to understand the model and suggest the optimum threshold for stable and safe operation. The model and analysis we develop are useful as the theoretical benchmark for other learning-based practical approaches.