Multi-objective Dynamic Reactive Power Optimization Based on OLTC and Reactive Power Compensation

被引:3
作者
Cai, Xiang [1 ]
Huang, Qingjun [1 ]
Zhou, Xiudong [1 ]
Zhu, Yuan [1 ]
Sun, Shiyi [1 ]
Zhu, Junwei [1 ]
机构
[1] State Key Lab Disaster Prevent & Reduct Power Gri, Changsha, Peoples R China
来源
2022 4TH ASIA ENERGY AND ELECTRICAL ENGINEERING SYMPOSIUM (AEEES 2022) | 2022年
关键词
distribution network; multi-objective dynamic optimization; second order cone relaxation; FLOW;
D O I
10.1109/AEEES54426.2022.9759406
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
Reactive power optimization is to minimize the active power losses of the distribution network by coordinating on-load tap-changing(OLTC) transformer and reactive power compensation(RPC) equipment, such as capacitor banks(CB) and static var compensator(SVC), etc.. Aside from power losses, minimizing voltage deviation is also an important aspect of reactive power optimization. Traditional reactive power optimization only considers the optimization effect of a single period, not the overall day's optimization. In view of this, a multi-objective dynamic reactive power optimization model is established in this paper, with the objective of minimizing the active power losses and voltage deviation, and the constraints of OLTC and RPC equipment. The second-order cone relaxation (SOCR) is used to convert the mixed integer nonlinear programming (MINLP) problem into the mixed integer second-order cone programming (MISOCP) problem, and the multi-objective variable-weight method is adapted to achieve the multi-objective dynamic reactive power optimization. Case studies are carried out on the modified IEEE 33-node system to verify the feasibility and effectiveness of the proposed method.
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页码:825 / 831
页数:7
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