Optimal Scheduling of Electric Vehicles in Residential Distribution Systems

Badugu, Jayababu; Sandhya, G.; Reddy, G. Nageswara; Kumar, K.Vimala

doi:10.1109/iccpct58313.2023.10245703

2023 International Conference on Circuit Power and Computing Technologies (ICCPCT) 2023

DOI: 10.1109/iccpct58313.2023.10245703

|View full text |Cite

Optimal Scheduling of Electric Vehicles in Residential Distribution Systems

Jayababu Badugu,

G. Sandhya,

G. Nageswara Reddy

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Relationship

Self Cite1

Independent1

Authors

Journals

Cited by 2 publications

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Minimizing electric vehicle charging costs in the microgrid using the BFGS Quasi-Newton Method

Badugu,

Sandhya,

Nageswarareddy

et al. 2024

E3S Web Conf.

Self Cite

View full text Add to dashboard Cite

Electric vehicles (EVs) offer a compelling solution for mitigating pollution, addressing environmental alterations, and enhancing energy security. This research presents a methodology employing the Broyden Fletcher Gold- farb Shanno quasi-Newton technique to streamline the charging costs associated with plug-in electric vehicles (PEVs). The initial step involves formulating an objective function directed at minimizing the expenses tied to PEV charging. This function takes into account crucial constraints pertaining to charger specifications, state of charge limitations, and voltage levels. Subsequently, we de- tail the application of the BFGS Quasi-Newton algorithm in computing node topology voltages within a microgrid featuring distributed energy resources (DERs). The findings demonstrate that the BFGS-enabled method outperforms alternative approaches in minimizing the cost of charging PEVs

show abstract

Minimizing electric vehicle charging costs in the microgrid using the BFGS Quasi-Newton Method

Badugu,

Sandhya,

Nageswarareddy

et al. 2024

E3S Web Conf.

Self Cite

View full text Add to dashboard Cite

show abstract

DSM Solutions for Distribution Networks with Electric Vehicle Integration

Badugu,

Manikanta,

Hemanth Kumar

et al. 2024

E3S Web of Conf.

View full text Add to dashboard Cite

Electric vehicles (EVs) are known for being zero emissions and environmentally friendly, making them extremely popular for transportation. In general, electric vehicles are often charged in residential areas. Due to this uncoordinated charging of electric vehicles, the low-voltage distribution network must face many challenges to maintain the new load conditions without blackouts and voltage fluctuations. Failure to properly measure and address these impacts of EVs on the distribution network will result in replacement and reinforcement of the distribution system, which is costly and time-consuming. This study introduces a Demand Side Management (DSM) approach aimed at minimizing overhead in residential distribution systems with electric vehicle (EV) integration. DSM emerges as the optimal strategy for mitigating severe power spikes within the distribution network. The study compares the effects of uncoordinated planned EV loads with those achieved through the implementation of the DSM strategy in a residential distribution system. The analysis encompasses the system's stability and end-user satisfaction as key parameters

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Optimal Scheduling of Electric Vehicles in Residential Distribution Systems

Cited by 2 publications

References 10 publications

Minimizing electric vehicle charging costs in the microgrid using the BFGS Quasi-Newton Method

Minimizing electric vehicle charging costs in the microgrid using the BFGS Quasi-Newton Method

DSM Solutions for Distribution Networks with Electric Vehicle Integration

Contact Info

Product

Resources

About