Enhance power system security with FACTS devices based on Mayfly Optimization Algorithm

A. Amarendra; L. Ravi Srinivas; R. Srinivasa Rao

Authors

A. Amarendra Electrical and Electronics Department, Gudlavalleru Engineering College, Gudlavalleru, Andhra Pradesh-521356, India
L. Ravi Srinivas Electrical and Electronics Department, Gudlavalleru Engineering College, Gudlavalleru, Andhra Pradesh-521356, India
R. Srinivasa Rao Electrical and Electronics Department, JNTUK College of Engineering, Kakinada, Andhra Pradesh-533003, India

Keywords:

Facts devices, fuel cost, Mayfly Optimization Algorithm (MA), power losses, system security

Abstract

Security of power systems can be defined as their ability to withstand severe disturbances and survive the transition to an acceptable new steady-state condition. The introduction of a flexible AC transmission system (FACTS) in a power system improves stability, reduces power losses, reduces the cost of generation, and improves the system's load ability. In this paper, technological development with modelling of Facts devices is shown to provide system stability, reduce the losses, and reduce the fuel cost. Facts devices like static synchronous compensator (STATCOM), Interline Power Flow Controller (IPFC), unified power flow controller (UPFC) and Thyristor-Controlled Series Compensation (TCSC) are fitted in a proper location of the transmission line to reduce the losses. The best location of Facts devices is hard to identify due to the enormous lines present in the IEEE bus system. An optimization is utilized to find the proper location of Facts devices accurately, leading to improving the power system security. In the proposed method, Mayfly Optimization Algorithm (MA) is applied to determine the optimal location of Facts devices in a power system. Find the best location and reduce outage losses based on the multiple objective functions. The proposed method is tested with the IEEE 30 bus, IEEE 118 bus, and 300 bus systems. The corresponding line loading, line limits, generator limits, bus voltage impact, etc. The projected method is executed in MATLAB and tested with various cases. The proposed method provides a high power demand and system steadiness. It reduces the fuel cost compared to the existing techniques of Particle Swarm Optimization (PSO), Firefly optimization, and Yin-Yang-Pair Optimization (YYPO).

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