Improving the performance of the MSOGI FLL method in network frequency detection under short circuit conditions

Number of pages: 85 File Format: word File Code: 32183
Year: 2014 University Degree: Master's degree Category: Electrical Engineering
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    Master's degree thesis report

    In the field of electrical engineering, power orientation

    Abstract

         Nowadays, the discussion of system control and monitoring is one of the most important discussions in the power network, and we need to know the exact state of the power network in order to design control devices. By knowing the status of the network at any moment, you can be aware of changes in voltage, current, and frequency, and you can prevent these parameters from leaving the working point with proper performance. One of the parameters that must be recognized is the network frequency, which is discussed in this thesis. The proposed methods for frequency detection based on phase-locked loops, such as the primary phase-locked loop, PLL1 (phase-locked loop) with a simultaneous reference frame, PLL with two separate simultaneous reference frames, and PLL with two second-order generalized integrators are common methods. How to get from the phase-locked loop to the frequency-locked loop (FLL2) and the methods based on the frequency-locked loop include FLL with two second-order generalized trap integrals and FLL with several second-order generalized trap integrals. The mentioned methods have evolved and each method is more efficient than the previous method. Finally, in this thesis, a method to improve the performance of the FLL method with generalized second-order multiple integrators in network frequency detection under short-circuit conditions is presented and its efficiency is compared and analyzed with conventional methods. In order to ensure the existence of a pure sinusoidal current or voltage signal or in other words a better quality of power, the point to be considered is that the power system should operate without significant loss in its performance. The performance of the system worsens due to voltage fluctuations, frequency changes and waveform changes including harmonics and inter-harmonics [1]. Therefore, in order to improve the power quality (topics related to the discussion of frequency in power quality include harmonics in the power system) fast and accurate estimation of the frequency of the supply voltage is required for an integrated power system [2]. In a power system due to the presence of noise and higher harmonics, the accurate and fast estimation of the frequency may be damaged and disturbed. Due to the power mismatch between production and load demand, a change in the frequency of the system occurs compared to its normal value, and restoring the frequency to its initial value requires calling a corrective operation. [3-4]. The problem of frequency estimation is considered using a large number of numerical methods such as Newton-Raphson, weighted least squares and adaptive filtering FIR3 through discrete samples of the system voltage. One of the simplest methods to determine the system frequency resulting from a pure sinusoidal voltage waveform in the power system is to use "zero crossing detection" and calculate the number of cycles in a time interval. However, signal processing techniques such as discrete Fourier transforms, least square error technique, Kalman filter and adaptive notch filters are used to estimate the frequency of noisy signals in the power system. A large number of numerical techniques based on the expansion of the measurement range, including the least square error method, Cramer-Rao bounds method, and maximum likelihood estimation, as well as their practical implementations, have been reported in articles and written texts. However, these methods provide incorrect results due to the presence of noise and harmonics and other variable conditions of the system such as the change in the fault starting angle and the change in the fault resistance. As a result, receiving incorrect results in the mentioned conditions is one of the weaknesses of these methods [5]. As a result, a review of new methods such as PLL blocks and its evolution, respectively, the initial phase-locked loop, PLL (phase-locked loop) with simultaneous reference frame, PLL with two simultaneous reference frames

    Finite Impulse Response

    is isolated and the second-order generalized wind PLL integrator is important. Then how to obtain the FLL block can be described.The goal of all researchers is to obtain the frequency in the shortest possible time with high accuracy in different network conditions. Among the various conditions of the network, the presence of harmonics, imbalance and noise can be mentioned as an example.

    The works that have been done so far to detect the frequency of the network in the power system are methods based on frequency locking loops, which for networks that have imbalance, the FLL method with two generalized second-order integrators can detect the frequency well [6].

    Although the FLL method with two second-order generalized integrators produces an accurate estimate of the main voltage component under unbalanced conditions, it is not able to accurately estimate the harmonic components of the voltage. Therefore, if the network has harmonics, a method should be provided that is able to detect harmonic components as well. In a more recent method, a multiple detector system is used to extract the harmonic components of frequency in power systems, and for this reason it is called FLL with multiple second-order generalized trap integrals[4]. As a result, the FLL method with multiple second-order generalized trap integrals can give a proper diagnosis of the frequency when the network has harmonics and imbalance. According to the simulation results of the articles related to this method, which will be discussed in the next chapter, it shows that the frequency detection time in harmonic and unbalance conditions is 100 milliseconds, which in terms of the power system takes five sinus cycles [4]. Low order such as the third and fifth harmonics pass through the filter due to their proximity to the network frequency and cause the distortion to remain in the main component [6]. The FLL method with several second-order generalized integrals is the latest method presented for frequency detection, in which with the help of a few SOGI blocks, we will be able to accurately detect sequence components even under severe distortions. Today, frequency detection time is one of the most important parameters in measurement systems. The lower detection time we have, we will be able to perform better control so that the frequency returns to the initial value in the desired network [7]. style="direction: rtl;"> and initial responses are analyzed. In these studies and investigations, it was observed that if the frequency jump of the gamma parameter (one of the adjustable coefficients that determines the speed of detection and was considered constant in previous works) is increased so that changes can be followed more quickly and then when the gamma frequency is fixed, it can return to its initial value. It reduced the frequency detection.

             After the analyzes and seeing the effect of changing the parameter K (damping coefficient in frequency detection which was considered as one in previous works) on the time and accuracy of frequency detection, it was observed that if the K coefficient is set for the detection of the main component and separate harmonic components, the damping time can be reduced and the accuracy can be increased. As a result, he first adjusts the amount of gamma changes during the frequency jump and chooses the best mode, and then by harmonizing the K factor of the main component and the harmonic components, the detection time is reduced and the accuracy remains at the optimal level. power network. Knowing the status of the network at any moment can change the voltage and frequency can be notified and the proper functioning of the abatement work out the parameters of the point

  • Contents & References of Improving the performance of the MSOGI FLL method in network frequency detection under short circuit conditions

    List:

    The first chapter. 1

    Introduction.  1

    Foreword. 1

    1-2- Thesis achievements. 4

    The second chapter. 7

    A review of past works. 7

    2-1- Evolution of PLLs in frequency detection and reaching FLLs. 7

    2-2- frequency detection using the locked loop circuit in the initial phase. 8

         2-2-1- ring with digital locking phase. 9

         2-2-2- loop with analog phase locking. 10

    2-2-3- phase detector. 11

    2-3- Synchronous reference frame PLL (SRF PLL). 13

    2-4- PLL with two separate simultaneous reference frames (DDSRF PLL). 15

    2-5- PLL with two second order generalized integrators (DSOGI PLL). 18

    2-6- FLL with two second order generalized integrators (DSOGI FLL). 21

    2-7- Comparison of the mentioned frequency detection methods.  27

    The third chapter. 29

    Study and review of FLL method with generalized second order multiple integrators. 29

    3-1- Introduction. 29 3-2- FLL with several generalized second-order integrators (MSOGI FLL. 30 3-2-1- Simulation of MSOGI FLL 30 3-2-2- Block diagram of Clark transform. 30 3-2-3- Network diagram block Harmonic Decomposition (HDN) 3-2-4 Block of Generalized Integral (SOGI) 3-2-5 Block of Frequency Locking (FLL) 3-2-6 Block of Positive and Negative Sequence Calculation (PNSC).

    Basic method simulation

    Single-phase 37

    3-5th harmonic 39

    40

         11th harmonic occurred.

         20-3-6 subharmonic occurred.

         3-3-7 occurred interharmonic. 43

         Harmonics, subharmonic, and short circuit occurred. 44

          3-3-9- Examining the range of harmonics. 45

          3-3-10- Examining the range of interharmonic 160 Hz and subharmonic 20 Hz. 46

    Chapter Four. 47

    Proposition to improve the performance of MSOGI FLL method in frequency detection. 47

    4-1- Introduction. 47

    4-2- Proposing methods to reduce frequency detection time. 49

    4-2-1- Gamma change, frequency change time. 49

           4-2-2- Separation of coefficient K.53

    4-3- Method of connecting in series (waterfall) SOGI. 58

    The fifth chapter. 60

    Simulation of the improved MSOGI FLL method under short circuit conditions. 60

    5-1- Simulation of MSOGI FLL method with pre-filter (WPF). 60

    5-2- Simulation of the improved method. 61

          5-2-1- Gamma change block, frequency change time. 61

    5-2-2- Isolation of damping coefficient (K). 62

    3-5- Simulation results of the improved method. 64

          5-3-1- Single-phase short circuit occurred. 65

          5-3-2- Third harmonic and short circuit occurred. 66

          5-3-3- 5th harmonic and short circuit occurred. 67

          5-3-4- 7th harmonic and short circuit occurred. 68

          5-3-5- 11th harmonic and short circuit occurred. 69

          5-3-6- 20 Hz subharmonic and single-phase short circuit occurred. 70

          5-3-7- 160 Hz inter-harmonic and single-phase short circuit occurred. 71

          5-3-8- harmonics, sub-harmonic, inter-harmonic and short circuit occurred. 72

           5-3-9- Examining the range of harmonics. 73

           5-3-10- Examining the range of interharmonic 160 Hz and subharmonic 20 Hz. 74

    5-4- Summary. 75

    Sixth chapter. 76

    Conclusions and suggestions. 76

    6-1- Conclusion. 76

    Suggestions. 77

    References. 78

     

     

     

    Source:

     

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Improving the performance of the MSOGI FLL method in network frequency detection under short circuit conditions