A Stochastic Resource-Planning Scheme for PHEV Charging Station Considering Energy Portfolio Optimization and Price-Responsive Demand

被引:54
作者
Ding, Zhaohao [1 ]
Lu, Ying [1 ]
Zhang, Lizi [1 ]
Lee, Wei-Jen [2 ]
Chen, Dayu [3 ]
机构
[1] North China Elect Power Univ, Acad Modern Elect Power Res, Beijing 102206, Peoples R China
[2] Univ Texas Arlington, Energy Syst Res Ctr, Arlington, TX 76019 USA
[3] China Huaneng Grp, Tech Econ Res Inst, Beijing 100031, Peoples R China
关键词
Demand-side management; plug-in hybrid electric vehicle (PHEV) charging station; price elasticity; stochastic optimization; unit commitment; RISK-AVERSION; SYSTEM;
D O I
10.1109/TIA.2018.2851205
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Plug-in hybrid electric vehicle (PHEV) charging station is playing a critical role in the rapid development of PHEVs. The unique characteristics of charging demands provide flexibility for the resource planning of PHEV charging station, while its internal generation resources and procurement decisions from utility grid offer various options to meet the charging demand. To achieve the maximum benefits while managing the associated risk, the operator of PHEV charging station should optimally schedule those resources on both supply and demand sides. In this paper, a stochastic resource-planning scheme for PHEV charging stations is proposed, while two types of PHEV charging loads, including price-responsive commercial charging customers and the contracted controllable charging fleets, are taken into the account. Energy supply decisions on energy procurement in multiple markets and internal generation scheduling are co-optimized with demand-side decisions on charging service pricing and controllable demands allocation. The uncertainties from spot market price and availability of renewable generations are considered in the proposed model. A numerical case study is also provided to illustrate the effectiveness of the proposed scheme.
引用
收藏
页码:5590 / 5598
页数:9
相关论文
共 51 条
[1]  
[Anonymous], P IEEE PES GEN M
[2]  
[Anonymous], 2014, Matlab
[3]  
[Anonymous], 2017, CHIN REN EN OUTL 201
[4]  
[Anonymous], GLOB EL VEH OUTL 201
[5]  
[Anonymous], 2017, ILOG CPLEX OPT STUD
[6]  
[Anonymous], 2003, STOCHASTIC PROGRAMMI
[7]  
[Anonymous], 2017, OAK RIDGE NATL LAB
[8]  
[Anonymous], SHENZH COMPL SWITCH
[9]  
[Anonymous], ERCOT MARKET INFORM
[10]  
[Anonymous], P POW GEN SYST REN E