TY - CHAP
T1 - Three Fleet Smart Charging Categories of Electric Vehicles for the Grid Power Regulation
AU - Huang, Pei
AU - Sun, Yongjun
PY - 2023
Y1 - 2023
N2 - The use of electric vehicles (EVs) has been on the rise during the past decade, and the number is expected to keep increasing in the future. The large EV charging loads, if not well regulated, will cause great stress on the existing grid infrastructures, as they are not designed to host such large power flow. The use of smart EV charging can be a resource-efficient and cost-effective way to enhance the local power balance, and it can mitigate power issues while avoiding expensive upgrading of the existing infrastructure. In this regard, some studies have developed dedicated EV smart charging controls. Most of the existing EV smart charging controls can be categorized into three approaches according to their optimization principles: individual, bottom-up, and top-down. Until now, systematic comparison and analysis of the different approaches are still lacking. It is still unknown whether a control approach performs better than others and, if yes, why is it so. This chapter aims to fill in such knowledge gaps by conducting a systematic comparison of these three different control approaches and analyzing their performances in depth. A representative control algorithm will be selected from each control approach; then, the selected algorithms will be applied for optimizing EV charging loads in a building community in Sweden. Their power regulation performances will be comparatively investigated in two perspectives: minimize peak power exchanges with the grid and maximize PV power self-consumption. The computational performances are also investigated. The study results show that the top-down coordinated approach is superior to bottom-up coordinated approach and individual independent approach in terms of demand response performances, nevertheless the computational loads are much higher. This may make the convergence difficult. Control strategies also have large impacts on the power regulation performances. This chapter will help pave the way for the developments of more sophisticated control algorithms for EV smart charging in the future. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
AB - The use of electric vehicles (EVs) has been on the rise during the past decade, and the number is expected to keep increasing in the future. The large EV charging loads, if not well regulated, will cause great stress on the existing grid infrastructures, as they are not designed to host such large power flow. The use of smart EV charging can be a resource-efficient and cost-effective way to enhance the local power balance, and it can mitigate power issues while avoiding expensive upgrading of the existing infrastructure. In this regard, some studies have developed dedicated EV smart charging controls. Most of the existing EV smart charging controls can be categorized into three approaches according to their optimization principles: individual, bottom-up, and top-down. Until now, systematic comparison and analysis of the different approaches are still lacking. It is still unknown whether a control approach performs better than others and, if yes, why is it so. This chapter aims to fill in such knowledge gaps by conducting a systematic comparison of these three different control approaches and analyzing their performances in depth. A representative control algorithm will be selected from each control approach; then, the selected algorithms will be applied for optimizing EV charging loads in a building community in Sweden. Their power regulation performances will be comparatively investigated in two perspectives: minimize peak power exchanges with the grid and maximize PV power self-consumption. The computational performances are also investigated. The study results show that the top-down coordinated approach is superior to bottom-up coordinated approach and individual independent approach in terms of demand response performances, nevertheless the computational loads are much higher. This may make the convergence difficult. Control strategies also have large impacts on the power regulation performances. This chapter will help pave the way for the developments of more sophisticated control algorithms for EV smart charging in the future. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
KW - Bottom-up coordinated approach
KW - Electric vehicle
KW - Grid power regulation
KW - Individual independent approach
KW - PV
KW - Top-down coordinated approach
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U2 - 10.1007/978-981-99-1222-3_8
DO - 10.1007/978-981-99-1222-3_8
M3 - RGC 12 - Chapter in an edited book (Author)
SN - 978-981-99-1221-6
T3 - Sustainable Development Goals Series
SP - 187
EP - 207
BT - Future Urban Energy System for Buildings
A2 - Zhang, Xingxing
A2 - Huang, Pei
A2 - Sun, Yongjun
PB - Springer
CY - Singapore
ER -
