Low-frequency dynamic modelling and control of matrix converter for power system applications

2012 ◽  
Vol 5 (3) ◽  
pp. 304-314 ◽  
Author(s):  
A. Dasgupta ◽  
P. Sensarma
Keyword(s):  
Power System ◽  
Dynamic Modelling ◽  
Low Frequency ◽  
Matrix Converter ◽  
And Control

Dynamic Modelling of Wind Farm Grid Interaction

2002 ◽  
Vol 26 (4) ◽  
pp. 191-210 ◽  
Author(s):  
Anca D. Hansen ◽  
Poul Sørensen ◽  
Frede Blaabjerg ◽  
John Becho
Keyword(s):  
Power System ◽  
Wind Farm ◽  
Control Strategies ◽  
Dynamic Modelling ◽  
Normal Operation ◽  
Simulation Tool ◽  
Power System Simulation ◽  
Collection System ◽  
Wind Model ◽  
And Control

This paper describes a dynamic model of a wind farm and its nearest utility grid. It is intended to use this model in studies addressing the dynamic interaction between a wind farm and a power system, both during normal operation of the wind farm and during transient grid fault events. The model comprises the substation where the wind farm is connected, the internal power collection system of the wind farm, the electrical, mechanical and aerodynamic models for the wind turbines, and a wind model. The integrated model is built to enable the assessment of power quality and control strategies. It is implemented in the commercial dedicated power system simulation tool DIgSILENT.

scholarly journals Low-Frequency Signal Sampling Method Implemented in a PLC Controller Dedicated to Applications in the Monitoring of Selected Electrical Devices

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 442
Author(s):  
Marcin Jaraczewski ◽  
Ryszard Mielnik ◽  
Tomasz Gębarowski ◽  
Maciej Sułowicz
Keyword(s):  
Power System ◽  
Reactive Power ◽  
Low Frequency ◽  
Sampling Frequency ◽  
Electrical Signal ◽  
Distortion Factor ◽  
Electrical Devices ◽  
Frequency Sampling ◽  
Sampled Signal ◽  
Band Limited

High requirements for power systems, and hence for electrical devices used in industrial processes, make it necessary to ensure adequate power quality. The main parameters of the power system include the rms-values of the current, voltage, and active and reactive power consumed by the loads. In previous articles, the authors investigated the use of low-frequency sampling to measure these parameters of the power system, showing that the method can be easily implemented in simple microcontrollers and PLCs. This article discusses the methods of measuring electrical quantities by devices with low computational efficiency and low sampling frequency up to 1 kHz. It is not obvious that the signal of 50–500 Hz can be processed using the sampling frequency of fs = 47.619 Hz because it defies the Nyquist–Shannon sampling theorem. This theorem states that a reconstruction of a sampled signal is only guaranteed possible for a bandlimit fmax < fs, where fmax is the maximum frequency of a sampled signal. Therefore, theoretically, neither 50 nor 500 Hz can be identified by such a low-frequency sampling. Although, it turns out that if we have a longer period of a stable multi-harmonic signal, which is band-limited (from the bottom and top), it allows us to map this band to the lower frequencies, thus it is possible to use the lower sampling ratio and still get enough precise information of its harmonics and rms value. The use of aliasing for measurement purposes is not often used because it is considered a harmful phenomenon. In our work, it has been used for measurement purposes with good results. The main advantage of this new method is that it achieves a balance between PLC processing power (which is moderate or low) and accuracy in calculating the most important electrical signal indicators such as power, RMS value and sinusoidal-signal distortion factor (e.g., THD). It can be achieved despite an aliasing effect that causes different frequencies to become indistinguishable. The result of the research is a proposal of error reduction in the low-frequency measurement method implemented on compact PLCs. Laboratory tests carried out on a Mitsubishi FX5 compact PLC controller confirmed the correctness of the proposed method of reducing the measurement error.

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