Optimal Charging Strategy for Spatially Distributed Electric Vehicles in Power System by Remote Analyser

Title

Optimal Charging Strategy for Spatially Distributed Electric Vehicles in Power System by Remote Analyser

Creator

Venkataswamy R.; Joseph T.M.

Description

The burden on the consumer for the price of fuel for classic vehicles is the root cause for the emergence of the fast growing trend in the power driven vehicles or electric vehicles. Less acceptance of electric vehicles by the customers and the hesitancy to replace traditional fuel powered vehicles by considering the economic factor is a major concern that existing in the current scenario. Therefore, for the proper balancing of the load with respect to the power available among different neighbouring charging stations in a given area, a load scheduling algorithm is used. The optimal route planner for the electric vehicles reaching the charging station is identified and then the power carried by each feeder is calculated by cumulative power of all the charging stations. The identification of the possible route is performed by the spatial network analysis which will be executing at remote analyzer. The location, state of charge, and other details of the electric vehicle through telemetry is used to find the best charging station for the particular vehicle in view of the cost, distance and the time. The performance of the technique is evaluated with and without optimization by considering the logical constraints; and the results are presented. Springer Nature Switzerland AG 2020.

Source

Lecture Notes in Networks and Systems, Vol-80, pp. 400-412.

Date

2020-01-01

Publisher

Springer

Subject

Google maps; Load scheduling; Optimal route planner; Optimization

Coverage

Venkataswamy R., Department of Electrical & Electronics Engineering, Faculty of Engineering, Christ (Deemed to be University), Bangalore, India; Joseph T.M., Department of Electrical & Electronics Engineering, Faculty of Engineering, Christ (Deemed to be University), Bangalore, India

Rights

Restricted Access

Relation

ISSN: 23673370

Format

Online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1007/978-3-030-23162-0_36

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