Optical Analysis of the UPQC using PI Controller in Power flow System

2021 ◽  
Author(s):  
Mamidala Vijay Karthik ◽  
M.Kalyan Chakravarthi ◽  
Lis M Yapanto ◽  
D Selvapandian ◽  
R. Harish ◽  
...  
Keyword(s):  
Power Flow ◽  
Flow System ◽  
Pi Controller ◽  
Optical Analysis

A New Robust H∞ Control Power

2017 ◽  
pp. 1695-1718
Author(s):  
Samir Abdelmalek ◽  
Hocine Belmili
Keyword(s):  
Power Flow ◽  
Reactive Power ◽  
Controller Design ◽  
Pi Controller ◽  
Control Technique ◽  
Wind Energy Conversion Systems ◽  
Grid Connection ◽  
Energy Conversion Systems ◽  
Sensitivity Problem ◽  
Doubly Fed

Attention has been paid by many researchers to address the various challenges of grid connection of DFIG-based Wind Energy Conversion Systems (WECS). This chapter focuses on the design of a robust H8 controller for the power flow between the stator of the Doubly-Fed Induction Generator (DFIG) and the grid. The robust H8 controller design is formulated as a mixed-sensitivity problem. A mathematical model of the DFIG written in an appropriate d-q reference frame is established to carry out simulations. The proposed power control scheme is elaborated and compared with a conventional Proportional-Integral (PI) controller based on vector control technique. The results show interesting performance of the controlled system in terms of the power reference tracking (the active and reactive power) and robustness against parameter variations compared with the conventional PI controller.

scholarly journals Structural Condition for Controllable Power Flow System Containing Controllable and Fluctuating Power Devices

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1627 ◽  
Author(s):  
Saher Javaid ◽  
Mineo Kaneko ◽  
Yasuo Tan
Keyword(s):  
Power System ◽  
Flow Control ◽  
Power Flow ◽  
Flow System ◽  
Power Balance ◽  
Power Demand ◽  
Power Devices ◽  
Power Sources ◽  
Power Flow Control ◽  
Power Fluctuations

This paper discusses a structural property for a power system to continue a safe operation under power fluctuation caused by fluctuating power sources and loads. Concerns over global climate change and gas emissions have motivated development and integration of renewable energy sources such as wind and solar to fulfill power demand. The energy generated from these sources exhibits fluctuations and uncertainty which is uncontrollable. In addition, the power fluctuations caused by power loads also have the same consequences on power system. To mitigate the effects of uncontrollable power fluctuations, a power flow control is presented which allocates power levels for controllable power sources and loads and connections between power devices. One basic function for the power flow control is to balance the generated power with the power demand. However, due to the structural limitations, i.e., the power level limitations of controllable sources and loads and the limitation of power flow channels, the power balance may not be achieved. This paper proposes two theorems about the structural conditions for a power system to have a feasible solution which achieves the power balance between power sources and power loads. The discussions in this paper will provide a solid theoretical background for designing a power flow system which proves robustness against fluctuations caused by fluctuating power devices.

scholarly journals Artificial-neural-network based unified power flow controller for mitigation of power oscillations

2021 ◽  
Vol 24 (3) ◽  
pp. 1323
Author(s):  
Vireshkumar Mathad ◽  
Gururaj Kulkarni
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Power Flow ◽  
Reactive Power ◽  
Pi Controller ◽  
Unified Power Flow Controller ◽  
Power Oscillations ◽  
Artificial Neural ◽  
Flow Controller ◽  
Power Flow Controller

The series and shunt control scheme of unified power flow controller (UPFC) impacts the performance and stability of the power system during power swing. UPFC is the most versatile and voltage source converter device as it can control the real and reactive power of the transmission system simultaneously or selectively. When any system is subjected to any disturbance or fault, there are many challenges in damping power oscillation using conventional methods. This paper presents the neural network-based controller that replaces the proportional-integral (PI) controller to minimize the power oscillations. The performance of the artificial neural network (ANN) controller is evaluated on IEEE 9 bus system and compared with a conventional PI controller.

scholarly journals Power Quality Improvement Using Distributed Power Flow Controller with BWO-Based FOPID Controller

2021 ◽  
Vol 13 (20) ◽  
pp. 11194
Author(s):  
B. Srikanth Goud ◽  
Ch. Rami Reddy ◽  
Mohit Bajaj ◽  
Ehab E. Elattar ◽  
Salah Kamel
Keyword(s):  
Power Quality ◽  
Power Flow ◽  
Pi Controller ◽  
Optimization Techniques ◽  
Fine Tuning ◽  
Black Widow ◽  
Distributed Power ◽  
Flow Controller ◽  
Distributed Power Flow ◽  
Power Flow Controller

The integration of hybrid renewable energy sources (HRESs) into the grid is currently being encouraged to meet the increasing demand for electric power and reduce fossil fuels which are causing environmental-related problems. Integration of HRESs into the grid can create some power quality (PQ) problems. To mitigate PQ problems and improve the performance of grid-connected HRESs some flexible devices should be used. This paper presents a distributed power flow controller (DPFC), as a type of flexible device to mitigate some PQ problems, including voltage sag, swell, disruptions, and eliminating the harmonics in a hybrid power system (HPS). The HPS presented in this work comprises a photo voltaic (PV) system, wind turbine (WT) and battery energy storage system (BESS). As a result, black widow optimization (BWO) with DPFC with real and reactive power (DPFC-PQ) is built in this paper to solve the PQ issues in HRES systems. The main aim of the work is to mitigate PQ problems and compensate for load demand in the HRES scheme. The controller used to drive this DPFC-PQ is a fractional-order PID (FOPID) controller optimized by the black widow optimization (BWO) technique. To assess the capability of BWO in fine-tuning the FOPID controller parameters, twelve optimization techniques were presented: P&O, PSO, Cuckoo, GA, GSA, BBO, Whale, ESA, RFA, ASO, and EVORFA. Additionally, a comparison between the FOPID controller and the classical PI controller is introduced. The results showed that the proposed BWO-FOPID controller for DFPC had mitigated the PQ problems in grid-connected HRESs. The system’s performance with the presented BWO-FOPID controller is compared with eleven optimization techniques used to optimize the FOPID controller and also compared with the conventional PI controller. The design of the proposed system is implemented in the MATLAB/Simulink platform and performances were analyzed.

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