scholarly journals APPLICATION OF FUZZY SYSTEM TO CONTROL VOLTAGE IN MULTI NODES POWER SYSTEM

2010 ◽  
Vol 13 (2) ◽  
pp. 29-36
Author(s):  
Anh Huy Quyen ◽  
Anh Viet Truong ◽  
Nhung Thi Hong Le
Keyword(s):  
Power System ◽  
Control Systems ◽  
Power Quality ◽  
Fuzzy System ◽  
Power Loss ◽  
Control Voltage ◽  
Transmission Network ◽  
Combined Control ◽  
Ieee Standard ◽  
Control Devices

Control voltage in power system is always necessary to guarantee power quality and reduce power loss of productivity. This paper presents the construction of voltage control fuzzy system in transmission network with variety control devices, used fuzzy Mamdani controllers. Fuzzy controllers associated and combined control actives to create an unified fuzzy control systems capable of automatically controlling the voltage at the nodes in power system by retaining nodes voltage in a while desired values with the satisfying restrictive conditions. Through the investigative results on 30bus IEEE standard network demonstrated the effectiveness of the proposed fuzzy algorithm compared with conventional techniques sensitive tree.

Operation of Voltage Reactive Power Control Devices based on Cooperation between Two-Voltage Class Transmission Network with PV Systems to Reduce Power Loss

2020 ◽  
Vol 140 (6) ◽  
pp. 484-494
Author(s):  
Akihisa Kaneko ◽  
Shinya Yoshizawa ◽  
Yasuhiro Hayashi ◽  
Shuhei Sugimura ◽  
Yoshinobu Ueda ◽  
...  
Keyword(s):  
Power Control ◽  
Power Loss ◽  
Reactive Power ◽  
Transmission Network ◽  
Reactive Power Control ◽  
Pv Systems ◽  
Control Devices

Predictive, Deadbeat, and Combined Controls

2018 ◽  
Author(s):  
Sadegh Vaez-Zadeh
Keyword(s):  
Control Systems ◽  
Predictive Control ◽  
Direct Torque Control ◽  
Fast Response ◽  
Torque Control ◽  
Control Methods ◽  
Electric Motors ◽  
Operating Cycle ◽  
Combined Control ◽  
The One

In this chapter, three control methods recently developed for or applied to electric motors in general and to permanent magnet synchronous (PMS) motors, in particular, are presented. The methods include model predictive control (MPC), deadbeat control (DBC), and combined vector and direct torque control (CC). The fundamental principles of the methods are explained, the machine models appropriate to the methods are derived, and the control systems are explained. The PMS motor performances under the control systems are also investigated. It is elaborated that MPC is capable of controlling the motor under an optimal performance according to a defined objective function. DBC, on the other hand, provides a very fast response in a single operating cycle. Finally, combined control produces motor dynamics faster than one under VC, with a smoother performance than the one under DTC.

scholarly journals Optical Voltage Transformer Based on FBG-PZT for Power Quality Measurement

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2699
Author(s):  
Marceli N. Gonçalves ◽  
Marcelo M. Werneck
Keyword(s):  
Power System ◽  
Power Quality ◽  
Distribution System ◽  
Electrical Power ◽  
Quality Measurement ◽  
Pockels Effect ◽  
Electrical Power System ◽  
Voltage Transformer ◽  
Technical Literature ◽  
Distribution Lines

Optical Current Transformers (OCTs) and Optical Voltage Transformers (OVTs) are an alternative to the conventional transformers for protection and metering purposes with a much smaller footprint and weight. Their advantages were widely discussed in scientific and technical literature and commercial applications based on the well-known Faraday and Pockels effect. However, the literature is still scarce in studies evaluating the use of optical transformers for power quality purposes, an important issue of power system designed to analyze the various phenomena that cause power quality disturbances. In this paper, we constructed a temperature-independent prototype of an optical voltage transformer based on fiber Bragg grating (FBG) and piezoelectric ceramics (PZT), adequate to be used in field surveys at 13.8 kV distribution lines. The OVT was tested under several disturbances defined in IEEE standards that can occur in the electrical power system, especially short-duration voltage variations such as SAG, SWELL, and INTERRUPTION. The results demonstrated that the proposed OVT presents a dynamic response capable of satisfactorily measuring such disturbances and that it can be used as a power quality monitor for a 13.8 kV distribution system. Test on the proposed system concluded that it was capable to reproduce up to the 41st harmonic without significative distortion and impulsive surges up to 2.5 kHz. As an advantage, when compared with conventional systems to monitor power quality, the prototype can be remote-monitored, and therefore, be installed at strategic locations on distribution lines to be monitored kilometers away, without the need to be electrically powered.

scholarly journals An Improved Particle Swarm Optimization Algorithm Using Eagle Strategy for Power Loss Minimization

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Hamza Yapıcı ◽  
Nurettin Çetinkaya
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Power System ◽  
Power Loss ◽  
Particle Swarm Optimization Algorithm ◽  
Reactive Power ◽  
Particle Swarm ◽  
Power Losses ◽  
Swarm Optimization ◽  
Eagle Strategy

The power loss in electrical power systems is an important issue. Many techniques are used to reduce active power losses in a power system where the controlling of reactive power is one of the methods for decreasing the losses in any power system. In this paper, an improved particle swarm optimization algorithm using eagle strategy (ESPSO) is proposed for solving reactive power optimization problem to minimize the power losses. All simulations and numerical analysis have been performed on IEEE 30-bus power system, IEEE 118-bus power system, and a real power distribution subsystem. Moreover, the proposed method is tested on some benchmark functions. Results obtained in this study are compared with commonly used algorithms: particle swarm optimization (PSO) algorithm, genetic algorithm (GA), artificial bee colony (ABC) algorithm, firefly algorithm (FA), differential evolution (DE), and hybrid genetic algorithm with particle swarm optimization (hGAPSO). Results obtained in all simulations and analysis show that the proposed method is superior and more effective compared to the other methods.

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