Automated Distributed Electric Vehicle Controller for Residential Demand Side Management

被引:51
作者
Faddel, Samy [1 ]
Mohammed, Osama A. [1 ]
机构
[1] Florida Int Univ, Dept Elect & Comp Engn, Energy Syst Res Lab, Miami, FL 33174 USA
关键词
Decentralized controller; demand side management (DSM); electric vehicles (EVs); time of use (TOU); ENERGY MANAGEMENT; LOAD;
D O I
10.1109/TIA.2018.2866255
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Electric vehicles (EVs) are recently gaining traction in the power sector due to various challenges and opportunities they provide to utility operators. For electric utilities that incorporate demand side management (DSM) programs, EVs could become either a burden or an advantage depending on their charging control strategy and the signaling of the DSM program. This paper proposes a decentralized fuzzy-based controller to successfully integrate and coordinate the charging of EVs that ensures fair charging of EVs at different point of connections (POCs) in the distribution grid where voltage conditions might not be the same. The controller operates in an autonomous mode that reduces the monetary cost of the communication overhead and preserves bandwidth. The proposed controller takes into consideration the owner requirements in terms of energy needed and time to charge, the voltage at the POC with the grid, and the pricing signal coming from the utility. The controller is tested under different DSM programs that exist in the literature. This paper also proposes a new DSM program that is capable of benefiting from EVs as prosumers that can provide grid services. The controller's performance was validated through MATLAB simulations that showed the controller's ability to successfully coordinate the charging of EVs in a fair manner and achieve flat system peaks without any rebound effect. The controller was also successfully tested in the presence of voltage control units, such as capacitor banks, and in the presence of distributed generations.
引用
收藏
页码:16 / 25
页数:10
相关论文
共 26 条
[21]   Responsive End-User-Based Demand Side Management in Multimicrogrid Environment [J].
Nunna, Kumar H. S. V. S. ;
Doolla, Suryanarayana .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2014, 10 (02) :1262-1272
[22]   Assessment of Demand-Response-Driven Load Pattern Elasticity Using a Combined Approach for Smart Households [J].
Paterakis, Nikolaos G. ;
Tascikaraoglu, Akin ;
Erdinc, Ozan ;
Bakirtzis, Anastasios G. ;
Catalao, Joao P. S. .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2016, 12 (04) :1529-1539
[23]  
Price J.E., 2013, IEEE Power and Energy Society General Meeting, P1, DOI DOI 10.1109/PESMG.2013.6672349
[24]   Tackling the Load Uncertainty Challenges for Energy Consumption Scheduling in Smart Grid [J].
Samadi, Pedram ;
Mohsenian-Rad, Hamed ;
Wong, Vincent W. S. ;
Schober, Robert .
IEEE TRANSACTIONS ON SMART GRID, 2013, 4 (02) :1007-1016
[25]  
Silva F.D., 2013, 2013 IEEE Power Energy Society General Meeting, P1
[26]  
Tong SJ, 2015, INT CONF SMART GRID, P325, DOI 10.1109/SmartGridComm.2015.7436321