scholarly journals Design and implementation of a stability control system for TCP/AQM network

2021 ◽  
Vol 22 (1) ◽  
pp. 129
Author(s):  
Salam Waley Shneen ◽  
Mohammed Qasim Sulttan ◽  
Manal Kadhim Oudah
Keyword(s):  
Optimization Technique ◽  
Control Unit ◽  
Pso Algorithm ◽  
Congestion Management ◽  
Ip Networks ◽  
Stability Control ◽  
Pi Controller ◽  
New Approach ◽  
Mathematical System ◽  
Stability Control System

<p><span>In this work, we used a new approach as active queue management (AQM) to avoid data congestion in TCP/IP networks. The new approach is PSO-PI controller which use the proportional-integral controller as a control unit and particle swarm optimization (PSO) algorithm as an optimization technique to improve the performance of the PI controller and therefore improving the performance of TCP/IP networks as a required goal. The optimization control (PSO-PI) is characterized by access to design and choosing the optimal parameters of </span>(K_1 and K_p) <span>to reach optimal solutions in a short way (fewer iterations). The implementation of the PSO algorithm is achieving by using the mathematical system model and M-file and SIMULINK in Mathlab program. Simulation results show good congestion management performance with PSO-PI controller better than the PI controller as AQM in TCP networks, and the proposed method was very fast and required few iterations.</span></p>

scholarly journals Output voltage regulation of synchronous generator using PSO algorithm-based PI controller

2021 ◽  
Vol 12 (2) ◽  
pp. 1216
Author(s):  
Fatiha Habbi ◽  
Nour El Houda Gabour ◽  
El Ghalia Boudissa ◽  
M’hamed Bounekhla
Keyword(s):  
Output Voltage ◽  
Optimization Technique ◽  
Synchronous Generator ◽  
Pso Algorithm ◽  
Voltage Regulation ◽  
Pi Controller ◽  
Reference Voltage ◽  
Adopted Model ◽  
Fixed Reference ◽  
Terminal Voltage

In this paper a regulation of the terminal voltage of synchronous generator (SG) has been developed. Here, the nonlinear model of the SG is used directly without requirement for a linearized mathematical model of the generator. A proportional integral PI-controller is used to adjust the duty cycle of the DC chopper of step-down type for controlling the field voltage and consequently the output voltage of the generator. Furthermore, Particle swarm optimization (PSO) algorithm is employed as an optimization technique for tuning the optimal parameters of the PI controller (Kp and Ki). This is achieved by the minimization of the quadratic output error between the reference voltage and the output voltage calculated from the adopted model at the same time. In order to test the performance of the PSO-PI controller, results are compared with the genetic algorithm (GA). Moreover, to reduce the overshoot resulting in the response of the terminal voltage, a varied reference voltage is adopted. Results obtained show the superiority of the varied reference voltage to decrease the overshoot versus the fixed reference voltage.

Development of Trunk Transmission Online Integrated Stability Control System (ISC) for New Generation Grid

2017 ◽  
Vol 137 (6) ◽  
pp. 434-445 ◽  
Author(s):  
Hiroshi Yoshida ◽  
Ryuji Tachi ◽  
Koya Takafuji ◽  
Hironori Imaeda ◽  
Masaru Takeishi ◽  
...  
Keyword(s):  
Control System ◽  
Stability Control ◽  
Stability Control System ◽  
New Generation

Development of On-line Integrated Stability Control System (ISC) for Long-distance Bulk Power Transmission

2013 ◽  
Vol 133 (4) ◽  
pp. 313-323 ◽  
Author(s):  
Kuniaki Anzai ◽  
Kimihiko Shimomura ◽  
Soshi Yoshiyama ◽  
Hiroyuki Taguchi ◽  
Masaru Takeishi ◽  
...  
Keyword(s):  
Control System ◽  
Power Transmission ◽  
Stability Control ◽  
Long Distance ◽  
Stability Control System ◽  
On Line ◽  
Bulk Power

scholarly journals An Optimized PV Control System Based on the Emperor Penguin Optimizer

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 751
Author(s):  
Mariam A. Sameh ◽  
Mostafa I. Marei ◽  
M. A. Badr ◽  
Mahmoud A. Attia
Keyword(s):  
Duty Cycle ◽  
Optimization Technique ◽  
Pso Algorithm ◽  
Boost Converter ◽  
Emperor Penguin ◽  
Pv System ◽  
Partial Shading ◽  
Pv Systems ◽  
Point Tracking ◽  
Grid Connected Inverter

During the day, photovoltaic (PV) systems are exposed to different sunlight conditions in addition to partial shading (PS). Accordingly, maximum power point tracking (MPPT) techniques have become essential for PV systems to secure harvesting the maximum possible power from the PV modules. In this paper, optimized control is performed through the application of relatively newly developed optimization algorithms to PV systems under Partial Shading (PS) conditions. The initial value of the duty cycle of the boost converter is optimized for maximizing the amount of power extracted from the PV arrays. The emperor penguin optimizer (EPO) is proposed not only to optimize the initial setting of duty cycle but to tune the gains of controllers used for the boost converter and the grid-connected inverter of the PV system. In addition, the performance of the proposed system based on the EPO algorithm is compared with another newly developed optimization technique based on the cuttlefish algorithm (CFA). Moreover, particle swarm optimization (PSO) algorithm is used as a reference algorithm to compare results with both EPO and CFA. PSO is chosen since it is an old, well-tested, and effective algorithm. For the evaluation of performance of the proposed PV system using the proposed algorithms under different PS conditions, results are recorded and introduced.

scholarly journals Solving the Real Power Limitations in the Dynamic Economic Dispatch of Large-Scale Thermal Power Units under the Effects of Valve-Point Loading and Ramp-Rate Limitations

2021 ◽  
Vol 13 (3) ◽  
pp. 1274
Author(s):  
Loau Al-Bahrani ◽  
Mehdi Seyedmahmoudian ◽  
Ben Horan ◽  
Alex Stojcevski
Keyword(s):  
Large Scale ◽  
Thermal Power ◽  
Optimization Technique ◽  
Economic Dispatch ◽  
Pso Algorithm ◽  
Search Space ◽  
Economic Benefits ◽  
Optimization Techniques ◽  
Ramp Rate ◽  
Dynamic Economic Dispatch

Few non-traditional optimization techniques are applied to the dynamic economic dispatch (DED) of large-scale thermal power units (TPUs), e.g., 1000 TPUs, that consider the effects of valve-point loading with ramp-rate limitations. This is a complicated multiple mode problem. In this investigation, a novel optimization technique, namely, a multi-gradient particle swarm optimization (MG-PSO) algorithm with two stages for exploring and exploiting the search space area, is employed as an optimization tool. The M particles (explorers) in the first stage are used to explore new neighborhoods, whereas the M particles (exploiters) in the second stage are used to exploit the best neighborhood. The M particles’ negative gradient variation in both stages causes the equilibrium between the global and local search space capabilities. This algorithm’s authentication is demonstrated on five medium-scale to very large-scale power systems. The MG-PSO algorithm effectively reduces the difficulty of handling the large-scale DED problem, and simulation results confirm this algorithm’s suitability for such a complicated multi-objective problem at varying fitness performance measures and consistency. This algorithm is also applied to estimate the required generation in 24 h to meet load demand changes. This investigation provides useful technical references for economic dispatch operators to update their power system programs in order to achieve economic benefits.

scholarly journals Continuous Automotive Software Updates through Container Image Layers

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 739
Author(s):  
Nicholas Ayres ◽  
Lipika Deka ◽  
Daniel Paluszczyszyn
Keyword(s):  
Embedded System ◽  
Ad Hoc ◽  
New Technologies ◽  
Electronic Control Unit ◽  
Control Unit ◽  
New Approach ◽  
Automotive Software ◽  
Software Updating ◽  
Software Updates ◽  
Functional Software

The vehicle-embedded system also known as the electronic control unit (ECU) has transformed the humble motorcar, making it more efficient, environmentally friendly, and safer, but has led to a system which is highly dependent on software. As new technologies and features are included with each new vehicle model, the increased reliance on software will no doubt continue. It is an undeniable fact that all software contains bugs, errors, and potential vulnerabilities, which when discovered must be addressed in a timely manner, primarily through patching and updates, to preserve vehicle and occupant safety and integrity. However, current automotive software updating practices are ad hoc at best and often follow the same inefficient fix mechanisms associated with a physical component failure of return or recall. Increasing vehicle connectivity heralds the potential for over the air (OtA) software updates, but rigid ECU hardware design does not often facilitate or enable OtA updating. To address the associated issues regarding automotive ECU-based software updates, a new approach in how automotive software is deployed to the ECU is required. This paper presents how lightweight virtualisation technologies known as containers can promote efficient automotive ECU software updates. ECU functional software can be deployed to a container built from an associated image. Container images promote efficiency in download size and times through layer sharing, similar to ECU difference or delta flashing. Through containers, connectivity and OtA future software updates can be completed without inconveniences to the consumer or incurring expense to the manufacturer.

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