5 research outputs found
Enhancement transient stability of power system using UPFC with M-PSO
Get PDFDuring the last years, the demand for electric power has increased dramatically, while the expansion of energy production and transmission has been brutally expanded due to resource and environmental constraints. So, many transmission lines were loaded deeply; thus, the stability of power system became a limiting factor for the transmission of electric power. Therefore, maintaining safe and stable operation of electrical grids is an important and challenging issue. The FACTs devices that provide opportunities to control the power and damping oscillations are used. Therefore, this paper sheds light on the modified particle swarm optimization (M-PSO) algorithm is used such in the paper to discover the design optimal the Proportional Integral controller (PI-C) parameters that improve the stability the Multi-Machine Power System (MMPS) with Unified Power Flow Controller (UPFC) by employing the MATLAB environment. Performance, the power system under event of fault, is investigating by utilizes the proposed two strategies to simulate the operational characteristics of power system by the UPFC using: first, the conventional (PI-C) based on PSO (PI-C-PSO) method; secondly, (PI-C) based on modified PSO (PI-C-M-PSO) method. The simulation results show the behavior of power system with and without UPFC, that the proposed (PI-C-M-PSO) technicality has enhanced response the system compared for other techniques, that since it gives undershoot and over-shoot previously existence minimized in the transitions, it has a ripple lower. The obtained results show that the transient stability of the simulation model has improved significantly with this technique.Copyright © 2020 Institute of Advanced Engineering and Science.
All rights reserved
Study and Analysis of Adaptive PI Control for Pitch Angle on Wind Turbine System
Get PDFIn the current work, a study is proposed using the engineering program MATLAB through computer tests of a simulation model for modifying the tilt angle in wind turbines, with a study of the effect of changing the angle of the wind turbine on the mechanical energy resulting from changing wind speed. Variable wind speeds reduce turbine efficiency; pitch control mitigates this. A PI-based pitch controller adjusts blade angles to maintain optimal ?.20 kW model achieved 15% higher power output at variable speeds. ? (tip-speed ratio) and Cp, ? the ratio of blade tip speed to wind speed, determines turbine efficiency. Unlike prior fixed-speed models, our variable-speed design adapts to turbulent winds via real-time pitch adjustment. This approach aids in stabilizing grid integration for renewable energy systems. While pitch control improves turbine efficiency, existing studies lack real-time adaptive strategies for variable wind speeds. our work optimizes pitch angles dynamically using MATLAB simulations. We propose a data-driven pitch control model for 5 kW and 20 kW turbines, validated under turbulent wind conditions. This study aims to maximize power output by correlating pitch angle (?) and tip-speed ratio (?) via MATLAB simulations. As a research contribution, the turbine characteristic curve is examined, as changes occur with changes in lambda, and the Cp Max is obtained at the optimal lambda. Assuming that beta is chosen from the curves to determine how it changes and its effect on operation at a given Cp, a given lambda is determined from the curve. Torque can be recognized as the first variable, both mathematically and physically. A change in torque affects speed, and thus affects lambda. Since there is a relationship between turbine speed and wind speed with lambda, turbine speed also depends on mechanical speed. The aim of the study is to design and build a simulation model using a mathematical representation of a wind turbine to study the effect of tilt angle control on handling changes in wind speed. The research contributions include the design of two models: one with a capacity of 5 kW and the other with a capacity of 20 kW. The first model uses a constant speed, while the second uses a variable wind speed. To stabilize the output at rated power, the turbine is angled. Using the wind turbine simulation model and some proposed tests, we can determine the behavior of the system as speed changes
A pursuit-evasion game robot controller design based on a neural network with an improved optimization algorithm
No full textA pursuit-evasion game (PEG) is a type of game that utilizes one or several cooperative pursuers to capture one or several evaders. The PEG game concept has been used in different multi-robot applications such as transportation or navigation applications, search and rescue, surveillance applications such as collision avoidance and air traffic control systems, multi-defense applications such as missile guidance systems, and medical applications such as analyzing biological behaviors. Regardless of the benefits of PEG, one of the main drawbacks of such systems is the computational burden and the immense time required to learn such systems. For this reason, this work proposes a neural network game based on the pursuit-evasion game, where the leader (evader) robot tries to eat several particles/apples distributed inside a closed game environment with boundary and inner obstacles. In contrast, a follower (pursuer) robot tries to capture the leader robot and stop the particle-eating process. The leader and follower robots were designed based on a differential two-wheel robot (DTWR). The neural network is presented to control and learn the leader and follower robot directions with respect to the boundary and inside obstacles in the game environment. The neural network weights are learned using an improved sine cosine algorithm based on chaotic theory (ISCACT). The ISCACT is proposed to solve and avoid the proposed game of being trapped in the local minimum problem. The ISCACT is tested based on five multimodal benchmark functions. The ISCACT has been used in two cases, the first case arises when ISCACT is used in the follower robot’s learning process. In the second case, the ISCACT has been used in the leader robot’s learning process. The results for the first and second cases prove the superiority of the ISCACT compared with other existing works in enhancing the PEG performance time and reducing the computational burden for multi-robot applications
Comparison of Transient Stability Response for MMPS using UPFC with PI and Fuzzy Logic Controller
Get PDFThe increasing pressure on the power system increases the complexity that is becoming a concern for the stability of the power system and mainly for transitory stability. To operate the system in the event of faults, Flexible AC Transmission System (FACTS) devices are used that provide opportunities to control power and vibrations damping. This paper deals with the two control strategies of the Unified Power Flow Controller (UPFC) to damping the system oscillations stability. The stability of the Multi-Machine Power System (MMPS) was analysed with the presence of UPFC. The first strategy is the traditional PI controller (PI-C) with UPFC, and the second strategy is the proposed Fuzzy Logic controller (FL-C) proposed for UPFC device along with PI controller. The MATLAB R2014a was used in all simulations. Based on the results, FL-C for UPFC device along with the PI controller has proven its superiority by has enhanced response to the system, thus minimized in the transitions overshoot and undershoot, and has lower ripple compared to traditional PI-C, both with and without UPFC
