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Impact of load variation on power system stability and performance of power system stabilizers: A case study of Peerdawd gas power station, Iraq Hameed, Jawad Hamad; Hashim, Wassan Adnan; Derbel, Nabil
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 14, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v14.i4.pp2119-2133

Abstract

Variable load on the station refers to the fluctuating load on a power plant due to erratic consumer demands. It is known to have an effect on the performance of power system stabilizers, particularly in damping inter-area oscillation. This paper examines how two power system stabilizer (PSS) models and various load conditions affect a power system's voltage and power stability. A dynamic model of the power system station, based on the real case study of the Peerdawd gas power station in north Iraq (PPGS), is utilized to investigate the response of both steady-state and transient-state models: the aggregated excitation control system (Ex2100) and the power system stabilizer (PSS2B). The impact of load variation on voltage stability under normal situations and during disturbances is discussed. Furthermore, the effect of reactive power support from the power plant on the input of the two PSS models is analyzed and discussed. The paper employs a MATLABTM/Simulink-based simulation program, and the results contribute to understanding how load variation influences system damping based on PSS.
Optimizing Mobile Robot Path Planning with a Hybrid Crocodile Hunting and Falcon Optimization Algorithm Hashim, Wassan Adnan; Ahmed, Saadaldeen Rashid; Mahmood, Mohammed Thakir; Almaiah, Mohammed Amin; Shehab, Rami; AlAli, Rommel
Journal of Robotics and Control (JRC) Vol. 6 No. 2 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i2.25586

Abstract

Thorough path planning is critical in unmanned ground vehicle control to reduce path length, computational time, and the number of collisions. This paper aims to introduce a new metaheuristic method called the Hybrid Crocodile Hunting-SearcH and Falcon Optimization (CHS-FO) algorithm. This method combines CHS's exploration and exploitation abilities with FO's rapid convergence rate. In this way, the use of both metaheuristic techniques limits the disadvantage of the individual approach, guaranteeing a high level of both global and local search. We conduct several simulations to compare the performance of the CHS-FO algorithm with conventional algorithms such as A* and Genetic Algorithms (GA). It is found The results show that the CHS-FO algorithm performs 30–50% better in terms of computation time, involves shorter path planning, and improves obstacle avoidance. Eristic also suggests that the path generation algorithm can adapt to environmental constraints and be used in real-world scenarios, such as automating product movement in a warehouse or conducting search and rescue operations for lost vehicles. The primary The proposed CHS-FO architecture makes the robot more independent and better at making choices, which makes it a good choice for developing the next generation of mobile robotic platforms. Goals will encompass the improvement of the algorithm's scalability for use in multiple robots, as well as the integration of the algorithm in a real environment in real time.