Electric Vehicle Smart Charging to Maximize Renewable Energy Usage in a Single Residence

被引:1
作者
Sastry, Kartik, V [1 ]
Fuller, Thomas F. [2 ]
Grijalva, Santiago [1 ]
Taylor, David G. [1 ]
Leamy, Michael J. [3 ]
机构
[1] Georgia Tech, Sch Elect & Comp Engn, Atlanta, GA USA
[2] Georgia Tech, Sch Chem & Biomol Engn, Atlanta, GA USA
[3] Georgia Tech, Sch Mech Engn, Atlanta, GA 30332 USA
来源
IECON 2021 - 47TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY | 2021年
关键词
electric vehicles; renewable energy; optimal control; convex optimization; residential energy management; OPTIMIZATION;
D O I
10.1109/IECON48115.2021.9589883
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We pose and solve a smart charging problem for a single residence equipped with an electric vehicle (EV), energy storage, and solar panels. The smart charging problem is cast as a quadratic program in order to exploit existing solution algorithms and to efficiently detect problem feasibility. The objective function consists of a weighted sum of four performance metrics: cost of electricity from the utility, usage of renewable energy, charging urgency and battery degradation. Of these, the renewable energy metric is a novel focus of the work and considers both local and remote sources of renewable energy. Benefits of the proposed smart charging strategy to the EV owner are multiple: charging costs can be minimized in a price-uncertain environment, renewable energy usage can be maximized, and battery lifetime can be extended. These benefits are obtained with minimal computational effort due to our convex problem formulation. They also position our proposed smart charging algorithm for both embedded implementation and large scale simulation studies, in contrast to many non-convex formulations existing in the literature.
引用
收藏
页数:6
相关论文
共 22 条
[1]  
Aravena I., 2021, IEEE T SMART GRID, P2021
[2]  
Athans M., 2013, Optimal Control: An Introduction to the Theory and Its Applications
[3]  
Boyd L., 2004, Convex Optimization, DOI DOI 10.1017/CBO9780511804441
[4]  
California ISO, 2016, WHAT DUCK CURV TELLS
[5]   Optimal Charging Strategy Based on Model Predictive Control in Electric Vehicle Parking Lots Considering Voltage Stability [J].
Choi, Beom-Ryeol ;
Lee, Won-Poong ;
Won, Dong-Jun .
ENERGIES, 2018, 11 (07)
[6]   The Impact of Charging Plug-In Hybrid Electric Vehicles on a Residential Distribution Grid [J].
Clement-Nyns, Kristien ;
Haesen, Edwin ;
Driesen, Johan .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2010, 25 (01) :371-380
[7]   Real-time multi-objective optimisation for electric vehicle charging management [J].
Das, Ridoy ;
Wang, Yue ;
Busawon, Krishna ;
Putrus, Ghanim ;
Neaimeh, Myriam .
JOURNAL OF CLEANER PRODUCTION, 2021, 292
[8]   Multi-objective techno-economic-environmental optimisation of electric vehicle for energy services [J].
Das, Ridoy ;
Wang, Yue ;
Putrus, Ghanim ;
Kotter, Richard ;
Marzband, Mousa ;
Herteleer, Bert ;
Warmerdam, Jos .
APPLIED ENERGY, 2020, 257
[9]   Smart Charging Schedules for Highway Travel With Electric Vehicles [J].
del Razo, Victor ;
Jacobsen, Hans-Arno .
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2016, 2 (02) :160-173
[10]   Joint Optimization of Electric Vehicle and Home Energy Scheduling Considering User Comfort Preference [J].
Duong Tung Nguyen ;
Le, Long Bao .
IEEE TRANSACTIONS ON SMART GRID, 2014, 5 (01) :188-199