A computational algorithm based on biogeography‐based optimization method for computing power system security constrains with multi FACTS devices. (5th February 2020)

• Record Type: Journal Article
• Authors: Kumar, M. Manoj; Alli Rani, A.; Sundaravazhuthi, V.
• Is Part Of: Computational intelligence. Volume 36:Number 4(2020)
• Page Start: 1493
• Page End: 1511
• Publication Date: 2020-02-05
• Subjects: biogeography based optimization -- FACTS device -- unified power flow controller -- classical BBO -- IEEE‐30 bus test system; Artificial intelligence -- Periodicals; Computational linguistics -- Periodicals; 006.3
• DOI: 10.1111/coin.12282
• Languages: English
• ISSNs: 0824-7935

Abstract

Abstract: A major role is played by the analysis of power system security in heightening system security and in system collapse condition avoidance. This article presents a cutting edge mechanism which is devised applying transmission line loadings as well as variance in bus voltage magnitude. The use of flexible alternating current transmission systems devices improves the objectives of generation fuel charges in addition to the severity index proposed which were investigated considering the contingency circumstances of generator(s) or/and transmission channel(s). To boost system security in spite of contingency circumstances in the existence of unified power flow controller or UPFC, it would be most appropriate to pinpoint a most advantageous position to install aforementioned device. We propose a model of UPFC where power insertion is done by using voltage source. Also a procedure to incorporate the same and a strategy to find optimum position has been proposed which uses line overload sensitivity indices. This work mainly focused on establishment of available transfer capability on the heavily congested line. The proposed congestion management scheme alleviates the heavy stress in transmission line and provides an ample corridor for the power to flow. Biogeography‐based optimization or BBO in short, is a technique which is a growing recognized optimization method which has been lucratively engaged in solving intricate optimization problem in dissimilar fields. The BBO provides better results than the metaheuristic counter parts such as Genetic Algorithm and Particle Swarm Optimization. The effectiveness of proposed BBO has been tested on standard IEEE 30 bus system and the results are compared with classic methods and other metaheuristic methods. This is established through the MATLAB package. Improved bus voltage profile was also attained and it can be inferred from the outcome that the prospective approach can drastically enhance security of power system when comparing with other optimization methods.