Meta Heuristic Algorithm Based Multi Objective Optimal Planning of Rapid Charging Stations and Distribution Generators in a Distribution System Coupled with Transportation Network

The application of Electric Vehicles (EVs) is increasing in many countries, causing many researchers to focus on EV Rapid Charging Station (RCS) related issues. The optimal planning of RCS considering only distribution networks is not a reliable approach. Moreover, the RCS location should be conveni...

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Bibliographic Details
Published in:Advances in electrical and electronic engineering 2022-12, Vol.20 (4), p.493-504
Main Authors: Vijay, Vutla, Venkaiah, Chintham, Mallesham, Vinod Kumar Dulla
Format: Article
Language:English
Subjects:
Algorithms
Computer networks
Distributed generation
distributed generator
distribution system
electric vehicle
Electric vehicle charging
Generators
Heuristic methods
Load fluctuation
Optimization
rao 3 algorithm
rapid charging station
Test systems
Transportation networks
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Summary:The application of Electric Vehicles (EVs) is increasing in many countries, causing many researchers to focus on EV Rapid Charging Station (RCS) related issues. The optimal planning of RCS considering only distribution networks is not a reliable approach. Moreover, the RCS location should be convenient to the EV user in a given EV driving range and the performance of the distribution system. In this paper, a multi-objective approach for optimal planning of RCS and Distributed Generators (DG) in a distributed system coupled with a transportation network is analyzed. The proposed optimal planning method aims to achieve reduced active power loss, EV user costs, and voltage deviation for effective RCS and DG planning. The approach includes the analysis of the test system with the base case, solo planning of RCS, planning of DGs with fixed RCS, and simultaneous optimal planning of RCS and DGs. Daily load variation at buses and hourly charging probability of EVs have been used in the analysis. IEEE 33 bus distribution system superimposed with a 25-node transportation network is considered the test system. Rao 3 algorithm is applied for optimization, and the results have been compared with PSO and JAYA algorithms.
ISSN:1336-1376
1804-3119
DOI:10.15598/aeee.v20i4.4594