Bi-Level Optimization for Available Transfer Capability Evaluation in Deregulated Electricity Market

被引:20
|
作者
Wang, Beibei [1 ]
Fang, Xin [2 ]
Zhao, Xiayang [3 ]
Chen, Houhe [4 ]
机构
[1] Southeast Univ, Sch Elect Engn, Nanjing 210018, Jiangsu, Peoples R China
[2] Univ Tennessee, Dept Elect Engn & Comp Sci, Knoxville, TN 37996 USA
[3] State Grid Int Dev Corp, Beijing 100120, Peoples R China
[4] Northeast Dianli Univ, Dept Elect Engn, Chuanying 132012, Jilin, Peoples R China
关键词
available transfer capability (ATC); deregulated electricity market; bi-level optimization; economic dispatch (ED); mathematic program with equilibrium constraints (MPEC); mixed-integer linear programming (MILP);
D O I
10.3390/en81212370
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Available transfer capability (ATC) is the transfer capability remaining in the physical transmission network for further commercial activity over and above already committed uses which needs to be posted in the electricity market to facilitate competition. ATC evaluation is a complicated task including the determination of total transfer capability (TTC) and existing transfer capability (ETC). In the deregulated electricity market, ETC is decided by the independent system operator's (ISO's) economic dispatch (ED). TTC can then be obtained by a continuation power flow (CPF) method or by an optimal power flow (OPF) method, based on the given ED solutions as well as the ETC. In this paper, a bi-level optimization framework for the ATC evaluation is proposed in which ATC results can be obtained simultaneously with the ED and ETC results in the deregulated electricity market. In this bi-level optimization model, ATC evaluation is formulated as the upper level problem and the ISO's ED is the lower level problem. The bi-level model is first converted to a mathematic program with equilibrium constraints (MPEC) by recasting the lower level problem as its Karush-Kuhn-Tucher (KKT) optimality condition. Then, the MPEC is transformed into a mixed-integer linear programming (MILP) problem, which can be solved with the help of available optimization software. In addition, case studies on PJM 5-bus, IEEE 30-bus, and IEEE 118-bus systems are presented to demonstrate the proposed methodology.
引用
收藏
页码:13344 / 13360
页数:17
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