Title: Swarm intelligent-based congestion management using optimal rescheduling of generators

Authors: S. Surender Reddy; S.A. Wajid

Addresses: Department of Railroad and Electrical Engineering, Woosong University, Daejeon – 300718, Korea ' Kalki Communication Technologies Private Limited (Kalkitech), Bengaluru, Karnataka-560103, India

Abstract: 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.

Keywords: congestion management; generation rescheduling; optimal power flow; OPF; generator sensitivity; evolutionary algorithms; particle swarm optimisation; PSO.

DOI: 10.1504/IJBIC.2019.099172

International Journal of Bio-Inspired Computation, 2019 Vol.13 No.3, pp.159 - 168

Received: 03 Jul 2016
Accepted: 22 May 2017
Published online: 19 Apr 2019 *

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