Swarm intelligent-based congestion management using optimal rescheduling of generators

被引:10
|
作者
Reddy, S. Surender [1 ]
Wajid, S. A. [2 ]
机构
[1] Woosong Univ, Dept Railrd & Elect Engn, Daejeon 300718, South Korea
[2] Kalki Commun Technol Private Ltd Kalkitech, Bengaluru 560103, Karnataka, India
关键词
congestion management; generation rescheduling; optimal power flow; OPF; generator sensitivity; evolutionary algorithms; particle swarm optimisation; PSO; ECONOMIC-DISPATCH; OPTIMIZATION; MARKETS;
D O I
10.1504/IJBIC.2019.10020480
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Congestion management (CM) refers to the controlling of transmission system such that the power transfer/flow limits are observed. In the restructured electrical system, the challenges of CM for the system operator (SO) is to maintain the desired level of system reliability and security in the short and long terms, while improving the market/system efficiency. In this paper, the CM problem is tackled by using the centralised optimisation, i.e., optimal rescheduling of generators, which in turn is solved by using the Swarm intelligent techniques. Here, the CM problem is solved by using the particle swarm optimisation (PSO), fitness distance ratio-PSO (FDR-PSO) and fuzzy adaptive-PSO (FA-PSO). First, the generators are selected based on sensitivity to the over-loaded transmission line, and then these generators are rescheduled to remove the congestion in the transmission line. The suitability and effectiveness of the proposed CM approach is examined on the standard IEEE 30 bus and practical Indian 75 bus systems.
引用
收藏
页码:159 / 168
页数:10
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