A Long-Term Evaluation on Transmission Line Expansion Planning with Multistage Stochastic Programming

被引:7
|
作者
Han, Sini [1 ]
Kim, Hyeon-Jin [1 ]
Lee, Duehee [1 ]
机构
[1] Konkuk Univ, Dept Elect Engn, Seoul 05029, South Korea
关键词
mixed-integer linear programming; transmission line expansion planning; multistage stochastic optimisation; decomposition method; DUAL DECOMPOSITION; OPTIMIZATION; MAINTENANCE; RELIABILITY; NETWORK; SOLVE; TNEP;
D O I
10.3390/en13081899
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
The purpose of this paper is to apply multistage stochastic programming to the transmission line expansion planning problem, especially when uncertain demand scenarios exist. Since the problem of transmission line expansion planning requires an intensive computational load, dual decomposition is used to decompose the problem into smaller problems. Following this, progressive hedging and proximal bundle methods are used to restore the decomposed solutions to the original problems. Mixed-integer linear programming is involved in the problem to decide where new transmission lines should be constructed or reinforced. However, integer variables in multistage stochastic programming (MSSP) are intractable since integer variables are not restored. Therefore, the branch-and-bound algorithm is applied to multistage stochastic programming methods to force convergence of integer variables.In addition, this paper suggests combining progressive hedging and dual decomposition in stochastic integer programming by sharing penalty parameters. The simulation results tested on the IEEE 30-bus system verify that our combined model sped up the computation and achieved higher accuracy by achieving the minimised cost.
引用
收藏
页数:18
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