Integrated Day-Ahead Scheduling Considering Active Management in Future Smart Distribution System

被引:46
|
作者
Gao, Hongjun [1 ]
Wang, Lingfeng [2 ]
Liu, Junyong [1 ]
Wei, Zhenbo [1 ]
机构
[1] Sichuan Univ, Coll Elect Engn & Informat Technol, Chengdu 610065, Sichuan, Peoples R China
[2] Univ Wisconsin, Dept Elect Engn & Comp Sci, Milwaukee, WI 53211 USA
基金
美国国家科学基金会; 国家高技术研究发展计划(863计划);
关键词
Smart distribution system; integrated scheduling; mixed integer second-order cone programming (MISOCP); relaxed power flow model (RPFM); active management; stochastic robust model; column-and-constraint generation algorithm (CCG); FLOW MODEL RELAXATIONS; OPTIMAL POWER-FLOW; DISTRIBUTION NETWORKS; HIGH PENETRATION; ENERGY-STORAGE; WIND POWER; PART I; RECONFIGURATION; OPTIMIZATION; GENERATION;
D O I
10.1109/TPWRS.2018.2844830
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
Day-ahead scheduling has played a significant role in the operation of distribution systems, aiming at minimizing the total operation cost. With the excessive integration of information and communication technologies and intelligent electronic devices, distribution system operators may seek to optimally control the active management elements to increase the economic and technical performance of future smart distribution systems. This paper focuses on an integrated day-ahead scheduling scheme that is formulated as a mixed integer second-order cone programming problem to obtain the optimal solution by means of the relaxed power flow model (RPFM). The detailed technical constraints for all the elements are accommodated based on the RPFM-based optimization method. Meanwhile, active management cost and punishment cost of wind power curtailed and customer energy not supplied are also considered in the design objectives of this paper. In order to address the uncertainties, a stochastic robust optimization method is first introduced to decide the active management elements (including capacitor hank, electrical storage system, controllable load, and switch) as the robust decision scheme. Afterwards, the column-and-constraint generation algorithm is applied to solve the proposed stochastic robust two-stage optimization model. Numerical results based on the IEEE 33-bus, PG&E 69-bus, and practical 152-bus systems are obtained to verify the effectiveness of the proposed method.
引用
收藏
页码:6049 / 6061
页数:13
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