Open AccessMulti‐objective optimal planning of FCSs and DGs in distribution system with future EV load enhancement
Author(s) -
Battapothula Gurappa,
Yammani Chandrasekhar,
Maheswarapu Sydulu
Publication year - 2019
Publication title -
iet electrical systems in transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.588
H-Index - 26
eISSN - 2042-9746
pISSN - 2042-9738
DOI - 10.1049/iet-est.2018.5066
Subject(s) - sizing , mathematical optimization , population , automotive engineering , power (physics) , energy consumption , voltage , operator (biology) , computer science , engineering , simulation , electrical engineering , mathematics , physics , art , biochemistry , chemistry , demography , repressor , quantum mechanics , sociology , transcription factor , visual arts , gene
Current trends suggest that electrical vehicle (EV) is a promising technology for road transportation. There is a substantial increase in the number of EVs due to improved energy efficiency and reduction in environmental impact as compared with internal combustion engine vehicles. The improper planning of fast charging stations (FCSs) and distributed generations (DGs) hurts the distribution system. So the distribution system operator has a significant challenge to identify the optimal location and sizing of FCSs in the distribution power network. This study presents optimal planning of FCSs and DGs with the account of the present and future increase in EV population. A multi‐objective optimisation problem is formulated for optimal planning of FCSs and DGs with the objective of minimising the voltage deviation, distribution network power loss, DGs cost and the energy consumption of EV users. This problem is solved for different levels of increase in EV population for different cases. A novel hybrid shuffled frog leap‐teaching and learning based optimisation algorithm is proposed and implemented to solve the considered multi‐objective problem. The performance of the proposed algorithm is compared with prior‐art algorithms in the literature.