scholarly journals Modeling of Discrete Networked Control Systems in State Space for Electrical Power System with Time Delays: نمذجة نظم التحكم الشبكية المتقطعة في فضاء الحالة لنظام قدرة كهربائية مع وجود التأخيرات الزمنية

2021 ◽  
Vol 5 (5) ◽  
pp. 50-30
Author(s):  
Mohamad Morhaf Bachar Alnifawi, Bassem Omran, Jomana Mahmoud Mohamad Morhaf Bachar Alnifawi, Bassem Omran, Jomana Mahmoud
Keyword(s):  
Time Delay ◽  
Power System ◽  
Time Delays ◽  
Negative Impact ◽  
Electrical Power ◽  
Linear Quadratic Regulator ◽  
Electrical Power System ◽  
Linear Quadratic ◽  
Lqr Controller ◽  
The Stability

Electrical power systems distributed over wide geographical areas are exposed to a set of factors that affect their stability. The most important factors are the time delays between their subsystems. In this paper, a flexible modeling method was concluded consisting of a set of generalized rules and conditions that apply to any network controlled system to ensure its stability with time delays between the elements of the controlled network. In addition, a linear quadratic regulator (LQR) controller was implemented. The aim of the LQR controller is to reduce the negative impact of the time delay on the stability of the electrical power system. The study was applied to a networked electrical power system consisting of three-generation stations distributed in three separate geographical areas. Computer simulations using MATLAB showed a remarkable improvement in the stability of the discrete networked system through the speed of damping the vibrations in the system, and the system ability to be stable at certain limits of the time delay.

scholarly journals Improvement of Transient Stability Using Different-Different FACTS Devices

2020 ◽  
Vol 5 (2) ◽  
pp. 35-37
Author(s):  
Vipin Kumar Pandey ◽  
Dr. Malay S Das ◽  
Dr. Anula Khare
Keyword(s):  
Power System ◽  
Transient Stability ◽  
Electrical Power ◽  
Power Demand ◽  
Electrical Power System ◽  
Industrial Growth ◽  
Voltage Instability ◽  
Facts Devices ◽  
Transfer Capability ◽  
The Stability

Due to increase in population and industrial growth, insufficient energy resources to generate or transmit the power in power system, increase in load causes power demand in the electrical power system. These power demand leads to voltage instability, increase the losses, reduces the power transfer capability and stability of the power system. To overcome this stability problem FACTS devices are optimally located in the power system to examine the stability of the system. To locate the FACTS devices different optimization algorithms are used in order to improve the stability of the electrical power system.

Study of the LQR Controller for Magnetic Flywheel Rotor System

2012 ◽  
Vol 150 ◽  
pp. 221-226 ◽  
Author(s):  
Xiang Long Wen ◽  
Chun Sheng Song ◽  
Cao Cao ◽  
Guo Ping Ding
Keyword(s):  
High Speed ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
Rotor System ◽  
Linear Quadratic ◽  
Gyroscopic Effect ◽  
Lqr Controller ◽  
The Stability ◽  
Gyroscopic Effects ◽  
Flywheel Rotor

Gyroscopic effects in the flywheel rotor greatly influence rotor stability especially at high speed. When the pole-zero position moves to right of s-plane, the damping of the pole is getting smaller, and the stability of system is getting worse with the increasing of rotor speed when the decentralized PD control law is used only. The LQR (linear quadratic regulator) control method is used to reduce gyroscopic effect and forced vibration. The simulation results show that LQR controller have a good performance on the reduction of gyroscopic effect and vibration of magnetic flywheel rotor system.

scholarly journals Hierarchical Lateral Control Scheme for Autonomous Vehicle with Uneven Time Delays Induced by Vision Sensors

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2544 ◽  
Author(s):  
Qi Liu ◽  
Yahui Liu ◽  
Congzhi Liu ◽  
Baiming Chen ◽  
Wenhao Zhang ◽  
...  
Keyword(s):  
Time Delays ◽  
Low Cost ◽  
Computational Cost ◽  
Linear Quadratic Regulator ◽  
Threshold Method ◽  
Linear Quadratic ◽  
Lateral Control ◽  
Online Computation ◽  
Control Scheme ◽  
Lqr Controller

Vision-based sensors are widely used in lateral control of autonomous vehicles, but the large computational cost of the visual algorithms often induces uneven time delays. In this paper, a hierarchical vision-based lateral control scheme is proposed, where the upper controller is designed by robust H∞-based linear quadratic regulator (LQR) algorithm to compensate sensor-induced delays, and the lower controller is based on logic threshold method, in order to achieve strong convergence of the steering angle. Firstly, the vehicle lateral model is built, and the nonlinear uncertainties induced by time delays are linearized with Taylor expansion. Secondly, the state space of the system is augmented to describe such uncertainties with polytopic inclusions, which is controlled by an H∞-based LQR controller with a low cost of online computation. Then, a lower controller is designed for the control of the steering motor. According to the results of the vehicle experiment as well as the hardware-in-the-loop (HIL) experiment, the proposed control scheme shows good performance in vehicle’s lateral control task, and exhibits better robustness compared with a conventional LQR controller. The proposed control scheme provides a feasible solution for the lateral control of autonomous driving.

scholarly journals Linear quadratic regulator applied to low-frequency oscillation damping using the current sensitivity model

2020 ◽  
Author(s):  
Elenilson De Vargas Fortes ◽  
Marcus Vinícius Silvério Costa ◽  
Leonardo H. Macedo ◽  
Percival Bueno de Araujo
Keyword(s):  
Power Systems ◽  
Electrical Power ◽  
Low Frequency ◽  
Linear Quadratic Regulator ◽  
Test System ◽  
Small Signal Stability ◽  
Electrical Power System ◽  
Linear Quadratic ◽  
Low Frequency Oscillation ◽  
Current Sensitivity

This paper proposes the use of the linear quadratic regulator, a systematic method in which the controller is obtained by minimizing a quadratic performance index, to ensure the desired damping rates of the low-frequency oscillatory modes present in an electrical power system. The current sensitivity model is used to represent the dynamics of the system. To validate the proposed technique, simulations were carried out using a single machine infinite bus system. From the results obtained, it was evidenced the excellent performance of the proposed controller, since it was able to damp the low-frequency oscillatory mode present in the test system, accrediting it as a powerful tool in the study and analysis of small-signal stability in electric power systems.

scholarly journals Preventive protection of marine electrical power system from the transition of generating sets to motoring mode

2021 ◽  
Vol 244 ◽  
pp. 08007
Author(s):  
Alecsandr Saushev ◽  
Nikolai Shirokov
Keyword(s):  
Time Delay ◽  
Power System ◽  
Control Method ◽  
Operation Mode ◽  
Electrical Power ◽  
Electric Power System ◽  
Practical Implementation ◽  
Electrical Machine ◽  
Structural Adaptation ◽  
Electrical Power System

The approaches that ensure the trouble-free operation of marine power system in abnormal modes were considered. Such modes are usually associated with the system elements failure during operation. Particular attention was paid to the processes occurring in the circuit during transition of one of the generators to the motoring operation mode. The relevance of the considered marine power system issue was substantiated. According to the research results, using time-delay when generating a signal to disable a failed unit operating with reverse power can contribute to defect development in the primary motor. Moreover, time-delay can also lead to zero voltage in the marine electric power system. This circumstance creates the possibility of an emergency that can potentially lead to a shipping accident with the most serious consequences. The problem of timely shutdown of a faulty electrical machine before its transition to the motoring mode is defined in the research, as well as the overload prevention problem for primary motors remaining in working condition. An original diagnostic indicator was proposed based on study, which allows identifying the inoperative state of generator unit during operation. The new approach was developed, which implements the preventive control method for the marine power system in case of element failure. The forecasting of the system operation modes in case of a generator set failure, and its structural adaptation to the occurred malfunction is carried out. In contrast to the existing methods, the practical implementation of the proposed solution will allow accident-free transition of marine power system to a partially operational state without the emergency. This will have a beneficial effect on the safety of ship as a whole.

Gradient Ascent Optimization for Fault Detection in Electrical Power System Based on Wavelet Transformation

2019 ◽  
Vol 14 ◽  
Author(s):  
Iyappan Murugesan ◽  
Karpagam Sathish
Keyword(s):  
Feature Extraction ◽  
Fault Detection ◽  
Power System ◽  
Electrical Power ◽  
Daubechies Wavelet ◽  
Electrical Power System ◽  
Gradient Ascent ◽  
Neural Learning ◽  
Weight Value ◽  
Transmission And Distribution

: This paper presents electrical power system comprises many complex and interrelating elements that are susceptible to the disturbance or electrical fault. The faults in electrical power system transmission line (TL) are detected and classified. But, the existing techniques like artificial neural network (ANN) failed to improve the Fault Detection (FD) performance during transmission and distribution. In order to reduce the power loss rate (PLR), Daubechies Wavelet Transform based Gradient Ascent Deep Neural Learning (DWT-GADNL) Technique is introduced for FDin electrical power sub-station. DWT-GADNL Technique comprises three step, normalization, feature extraction and FD through optimization. Initially sample power TL signal is taken. After that in first step, min-max normalization process is carried out to estimate the various rated values of transmission lines. Then in second step, Daubechies Wavelet Transform (DWT) is employed for decomposition of normalized TLsignal to different components for feature extraction with higher accuracy. Finally in third step, Gradient Ascent Deep Neural Learning is an optimization process for detecting the local maximum (i.e., fault) from the extracted values with help of error function and weight value. When maximum error with low weight value is identified, the fault is detected with lesser time consumption. DWT-GADNL Technique is measured with PLR, feature extraction accuracy (FEA), and fault detection time (FDT). The simulation result shows that DWT-GADNL Technique is able to improve the performance of FEA and reduces FDT and PLR during the transmission and distribution when compared to state-of-the-art works.

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