TY - GEN
T1 - Charging schedule optimization method for electric buses with PV installed at bus stations
T2 - 2020 International Conference on Smart Grids and Energy Systems, SGES 2020
AU - Tomizawa, Yuki
AU - Ihara, Yuto
AU - Miyazaki, Teru
AU - Iino, Yutaka
AU - Hayashi, Yasuhiro
AU - Yamamoto, Ryota
N1 - Funding Information:
This work was supported by JST-Mirai Program Grant Number JPMJMI17B5, Japan.
Publisher Copyright:
© 2020 IEEE
PY - 2020/11
Y1 - 2020/11
N2 - It has been discussed that electric vehicles should be utilized effectively as movable storage resources. In this research, public electric buses are focused on, which are expected to have controllability with low uncertainty but limitation caused by the rigid bus operation schedule. Recently we reported an analysis of the actual bus operation data and proposed a charging schedule optimization method. The purpose of this research is to create an optimization method that maximizes two indicators related to the benefits of the bus company. Moreover, the sensitivity of the photovoltaic capacity installed at the bus stations is analyzed. An optimization method was created by mixed integer linear programming, and sensitivity analysis simulation was conducted using real city data. This study is based on a realistic simulation with actual bus operation data in a target city. As a result, we confirmed the 107kWh (-15.3%) surplus reduction by the proposed optimization method and the trade-off relationship between the two indicators.
AB - It has been discussed that electric vehicles should be utilized effectively as movable storage resources. In this research, public electric buses are focused on, which are expected to have controllability with low uncertainty but limitation caused by the rigid bus operation schedule. Recently we reported an analysis of the actual bus operation data and proposed a charging schedule optimization method. The purpose of this research is to create an optimization method that maximizes two indicators related to the benefits of the bus company. Moreover, the sensitivity of the photovoltaic capacity installed at the bus stations is analyzed. An optimization method was created by mixed integer linear programming, and sensitivity analysis simulation was conducted using real city data. This study is based on a realistic simulation with actual bus operation data in a target city. As a result, we confirmed the 107kWh (-15.3%) surplus reduction by the proposed optimization method and the trade-off relationship between the two indicators.
KW - Electric bus
KW - Electric vehicle
KW - Mixed integer linear programming
KW - Photovoltaic
KW - Smart city
UR - http://www.scopus.com/inward/record.url?scp=85102733396&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85102733396&partnerID=8YFLogxK
U2 - 10.1109/SGES51519.2020.00035
DO - 10.1109/SGES51519.2020.00035
M3 - Conference contribution
AN - SCOPUS:85102733396
T3 - Proceedings - 2020 International Conference on Smart Grids and Energy Systems, SGES 2020
SP - 157
EP - 162
BT - Proceedings - 2020 International Conference on Smart Grids and Energy Systems, SGES 2020
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 23 November 2020 through 26 November 2020
ER -
