Optimal scheduling of electric vehicle in stochastic AC SCUC problem for large-scale wind power penetration

被引:8
|
作者
Gupta, Pranda Prasanta [1 ]
Jain, Prerna [1 ]
Sharma, Kailash Chand [2 ]
Bhaker, Rohit [1 ]
机构
[1] Malaviya Natl Inst Technol, Dept Elect Engn, Jaipur, Rajasthan, India
[2] Banasthali Vidyapith, Sch Automat, Vanasthali, Rajasthan, India
来源
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS | 2020年 / 30卷 / 04期
关键词
benders decomposition; plug-in electric vehicles; stochastic security-constrained unit commitment; wind uncertainty; CONSTRAINED UNIT COMMITMENT; ENERGY-STORAGE; GENERATION; OPERATION; DISPATCH; SYSTEMS; IMPACT;
D O I
10.1002/2050-7038.12145
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Integration of highly volatile wind generation causes reliability and grid issues for system operator (SO). Plug-in electric vehicles (PEVs) are mobile distributed source of active power that provides opportunity to use their battery storage for wind integration. The coordinated integration of wind volatility and PEVs fleet is studied under security-constrained unit commitment (SCUC) model. In this regard, a stochastic SCUC with PEVs considering wind integration and line contingency is proposed. Wind volatility and PEVs driving behavior uncertainty is modeled through Monte Carlo simulations (MCS) of large number of scenarios with associated probabilities. This scenario has been reduced by Kantorovich distance (KD) matrix-based backward reduction technique. Moreover, pre-line and post-line contingency AC optimal power flow is used for network constraints in SCUC (AC SCUC). Due to consideration of N-1 security criteria and wind power scenarios, the proposed model is mixed integer nonlinear programming (MINLP), which is computationally heavy and is thus solved by a two-stage programming Benders decomposition (BD) approach. Different case studies are examined on modified IEEE reliability test system (RTS). Comparative analysis explores the impact on overall operational costs, PEV cost, wind curtailment, and locational marginal price (LMP) for congestion management. Simulation results validate that the proposed model is technoeconomically suitable for large-scale wind power penetration.
引用
收藏
页数:21
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