A novel symbiotic organisms search algorithm for congestion management in deregulated environment. Issue 1 (2nd January 2017)

• Record Type: Journal Article
• Authors: Verma, Sumit; Saha, Subhodip; Mukherjee, V.
• Is Part Of: Journal of experimental & theoretical artificial intelligence. Volume 29:Issue 1(2017)
• Page Start: 59
• Page End: 79
• Publication Date: 2017-01-02
• Subjects: Congestion management -- deregulation -- independent system operator -- optimal power flow -- price bids -- symbiotic organism; Artificial intelligence -- Periodicals; 006.3
• DOI: 10.1080/0952813X.2015.1116141
• Languages: English
• ISSNs: 0952-813X

Abstract

Abstract: In today's competitive electricity market, managing transmission congestion in deregulated power system has created challenges for independent system operators to operate the transmission lines reliably within the limits. This paper proposes a new meta-heuristic algorithm, called as symbiotic organisms search (SOS) algorithm, for congestion management (CM) problem in pool-based electricity market by real power rescheduling of generators. Inspired by interactions among organisms in ecosystem, SOS algorithm is a recent population-based algorithm which does not require any algorithm specific control parameters unlike other algorithms. Various security constraints such as load bus voltage and line loading are taken into account while dealing with the CM problem. In this paper, the proposed SOS algorithm is applied on modified IEEE 30- and 57-bus test power system for the solution of CM problem. The results, thus, obtained are compared to those reported in the recent state-of-the-art literature. The efficacy of the proposed SOS algorithm for obtaining the higher quality solution is also established.