Application of improved invasive weed optimization technique for optimally setting directional overcurrent relays in power systems

• Published in: Applied soft computing Vol. 79; pp. 1 - 13
• Main Authors: S.T.P., Srinivas, K., Shanti Swarup
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.06.2019
• Subjects: Directional overcurrent relays; Heuristic programming; Invasive weed optimization; Nonlinear programming; Optimal relay coordination; Optimal relay coordination; Heuristic programming; Directional overcurrent relays; Nonlinear programming; Invasive weed optimization
• ISSN: 1568-4946; 1872-9681
• DOI: 10.1016/j.asoc.2019.03.045

This paper aims to study the application of a heuristic optimization technique namely, Invasive Weed Optimization (IWO) technique for optimal protection coordination in power systems. The optimal relay coordination problem is formulated as a nonlinear constrained optimization, which is solved using Improved IWO (IIWO). The proposed IIWO algorithm modifies the standard deviation expression of the weed population. The simulation results show that IIWO has faster and better convergence compared with standard IWO. To further improve the computational efficiency, a hybrid IIWO method is also proposed which is obtained by defining sequential quadratic programming (SQP) as a subroutine in IIWO for searching local solutions, thus eliminate weaker weeds in the colonization process. The proposed techniques are tested on both the 9-bus test system and IEEE- 30 bus systems and the performance is compared. Relay coordination algorithm is developed in MATLAB, and the results are found to be effective and reliable. •Introduction of the application of invasive weed optimization (IWO) algorithm to DOcR coordination problem.•Proposing a variant of IWO, called IIWO, which modifies the standard deviation expression to fit for DOcR coordination problem which provides faster and better convergence.•Proposing a Hybrid IIWO algorithm to find global solution to the subject problem.•Test the proposed algorithms on two test systems viz. the 9 bus, and IEEE 30 bus systems.•Provide a computational and statistical analysis of the obtained results to establish the superiority of the proposed heuristic and hybrid heuristic models.