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*Corresponding Author: Sohrab Mirsaeidi,Young Researchers and Elites Club, Saveh Branch, Islamic Azad University, Saveh, Iran.
Distinction of Permanent and Transient Faults in Microgrids Using Wavelet Transform
Behrooz Moeil1, Majid Gandomkar1, Mehdi Gooran1 and Sohrab Mirsaeidi2,*
1Department of Electrical Engineering, Islamic Azad University of Saveh, Saveh, Iran
2
Young Researchers and Elites Club, Saveh Branch, Islamic Azad University, Saveh, Iran
Received: August 6 2013 Accepted: August 28 2013
ABSTRACT
Nowadays, utilization of distributed generation (DG) has been enhanced because of its advantages such as increase of the reliability, decrease of losses, enhancement of the line capacity, and less environment pollution. Protection of microgrids, which consists of these generation sources, is one of the most essential concerns of distribution operators.
One of the most important issues in this field is protection of microgrid against the permanent and transient faults which improves the reliability of the network. Moreover, wrong detection of these faults can inflict the immense costs to the system. The conventional method in which recloser system was used, had some disadvantages. In this research, an appropriate method has been proposed to detect and remove the faults using wavelet transform.that the mentioned problems have been relieved intensively in the method.
KEYWORDS: Microgrid, Wavelets, Auto recloser.
I. INTRODUCTION
Response to the enhancement of power demand in the developed industrial countries based on the conventional systems of transmission and distribution has been a considerable challenge in case of cost issue. In some conditions, the requirement of restructuring of these systems will be necessary which owing to the existing limitations such as the required location, high expense of these changing for restructuring, and unavailable operational utilities will be highly hard task [1-6].
With appearance of technological improvement in renewable energies and with presence of microsources as distributed energy resources (DERs), the new methodologies have been proposed to solve these kinds of problems in which the requirements of customers and operator concerns of grid have been resolved [7-9].
These microsources, which are connected to the distributed part of grid, is called distributed generation (DG). The utilization of DGs has many advantages like [10-13]: utilization of which as supporter during disruption of the main grid, enhancement of grid reliability, enhancement of network capacity, reducing of distribution feeder losses, correction of voltage drop and voltage sag, increasing of exploitation with heat generation for local loads, and peak erosion.
The cluster of these microsources and local loads, which act as a controllable system and transfer the power and heat to the local area, is called microgrid [14].
Due to the fact that the connection of microsources to the distribution network, the structure of which has been changed from the passive and radial network to multi-source system and active network that the conventional protection systems have not been usable. Hence, the new protection system must be designed. It should be available to operate in islanded mode. The changes of grid from the passive state to active mode are as follows [15-22]:
The capacity of short circuit current increases due to the connection of some DGs to distribution network,
The direction of current is complicated and in some situations becomes inverse because of the location of sources connections and type of the faults,
Time characteristic of fault hanging based on the variety of network dynamic response features,
The fault current rate of converters are limited to two times of their nominal current (For sources that contains the power electronic converters),
The balance of the three-phase loads is changed to unbalance state with connection of single-phase microgrids to the main networks, and
It is possible that the regulation of constant value of protection relay becomes invalid because of the unpredictable dynamic features of power out of DG.
Thus, the protection of microgrid is important and is also one of the main challenges of distribution operator. One of the controversial issues in this field is detection of permanent and transient faults in microgrids which has a considerable effect in reliability indices of network too. One of the most important advantages of microgrids is improvement of network reliability.
II. BACKGROUNDSTUDY
Based on the T.H. Ortmeyer research in [8,9], the system average interruption frequency index (SAIFI) and momentary average interruption frequency index (MAIFI) have considerable impact on evaluation of influences of permanent and transient faults in distribution networks. In this paper the comparative cost indices (SMRCR=MAIFI/SAIFI) has been introduced and also the costs of typical network includes sectionalizer per industrial commercial and residential customers have been studied. The result of paper research declares that the utilization of reclosing must be avoided for the SMRCR magnitudes less than 25 and also the permanent and transient fault consider the same due to the high possibility of wrong operation of reclosing and high magnitude of innate frequency of transient fault.
Based on the [4], reclosing in spinning DGs (which includes the main part of the DGs) can harm the shaft coupler and initiate excitation system; moreover, the electrical or mechanical shock can damage the rotor winding. To prevent this occurrence, DG must be separated from the system between the reclosing intervals that this reclosing of DG causes some sensible interruptions [7].
Fig.1. The time of DG seclusion from the network
To protect the permanent and transient faults in microgrid, the auto reclosing system has been proposed in [10]. In this procedure, the most faults of distribution networks (about 90%) are transient single-phase to ground faults. Hence, in these types of faults a phase that is in fault situation is cut off and the healthy phases will operate in normal situation.
After it, the reclosing process will occurred in the phase that the fault has occurred in it. The time of relieving faults is acceptable until two seconds and the balance of the system will keep in acceptable situation. This single-phase separation causes that customers, who are supplied by two other healthy phases, continue their working without any transient disruption. But this method has its specific problems such as: peril of losing of transient stability of the system, dangerous of secondary shocks due to the reclosing on permanent fault, possibility of presence of the inability of circuit breaker operation in frequent reclosing, and possibility of frequent variations occurrence. In this paper, the fast methodology of transient and permanent fault detecting based on the waveform transformation has been represented.
With this method the reclosing operation is optimized and the frequent shocks to the system are avoided.
III. WAVELETTRANSFORMATION
The measured signals of voltage and current in power systems are in time domain. In case of analyze these signals, sometimes we needs to transform them to frequency domain. For this aim, the Fourier and wavelet transformation can be used. The application of Fourier transformation is for static signals. But the short time Fourier transformation can be utilized for analysis of non-static and non-periodic signals. The short time Fourier transformation represents the time frequency information of signal. The waveform transformation is utilized for analysis of non-periodic and non-static signals. The predominance of this methodology against the short time Fourier transformation is that it can illustrate the time location of disturbances. The Fourier transformation is not sensible to usual and regular behavior of signals and it is just sensible to irregular and disturbances of signal. The wavelet transformation is divided into two groups of continuous and discrete transforms. The precision and efficiency of discrete wavelet transformation is more than the continuous.
The equations of continuous wavelet transformation and its reverse transform is as follows:
(1) ( , ) = 1
| |
∗ −
( ) (2) ( ) = ∬ ( , ){
| |
. }
Where ψ(t) is mother wavelet and x(t) is the main signal, a and b are criterion and relocation factors respectively that both of them change continuously by time. Also, the discrete wavelet transformation can be described as follows:
(3) ( , ) = 1
( ) ( − )
Where ψ(t) is mother wavelet and parameters of a and b are the functions of signal index of j. In the above equation, a=a0j
, b=nb0a0j
and k are integer that illustrate the number of signal points. It is to be noted that the discrete waveform has not meaning the discrete t, actually it means the discrete amount of scale and relocation.
IV. SIGNALANALYSIS
In the wavelet transformation, there are two methods for analysis the signal. The first way is usual analysis of the signal which divided it into two flat ranges: approximate and detail according to wavelet transformation under mother wavelet. Then, in the second level, the approximate range is divided into approximate and detail ranges and this process will continue till the appropriate range is obtained. The second methodology is wavelet packet that will have the more precise decomposition of non-static signals. The reason of this method utilization is it is possible that the information in one time range be a lot and in the other time range be low. When the information of a time range is little, the more precise analysis can give more details. In the proposed method the signal is divided into two flat range of: Coefficients Approximate (CA) and Coefficients Detail (CD) by wavelet transformation under mother wavelet. After it, the CA range is divided into two ranges of CA2 and CD2 and CD range is divided into two ranges of CA3 and CD3. This process will continue until the appropriate range is obtained. The description of wavelet factor analysis is as follows:
Fig.2. Right side: Analysis of waveform factors, left side: Analysis of waveform factors V. ARCMODELING
Due to most of transient faults like: single-phase to ground fault, insulator refraction and transient fault causes by isolation refraction of air gap between phases, the fault is modeled as arc. So, In this paper, the transient fault has been modeled as arc. The modeling of arc is really difficult owing to the fact that the general fault waveform is affected by factors like: fault situation, loading before fault occurrence, source parameters and atmospheric conditions. An appropriate arc modeling has been carried out in some researches by Johns and Storm. The arc is divided into primary and secondary arcs generally based on their paper. The primary arc is available during the fault occurrence and secondary arc is available after the operation of breaker and occurs by coupling between the damaged phase and healthy phase. In the past times, the arc was modeled by a short circuit solely or short circuit with a low linear resistance. For primary and secondary arcs, the Storm and Johns models are more appropriate and feasible. The characteristics of arc direction and restoration have a considerable role in modeling and determining distinguish of the arc. The features of dynamic transfers and arc voltage are illustrated in the following figures for primary and secondary arcs:
Fig.3. The characteristics of dynamic direction and voltage of arc. Left side: primary arc, right side: secondary arc.
The equations of arc calculations are as follows:
(4) =1
( − )
Where τ is constant time of arc, g and G are instantaneous and static conductance of arc respectively.
The constant direction of arc is introduced as follows:
(5) =| | (6) = + . | | Where:
(7) = 0.9 . + 0.4
(8) = 40 Ω
. + 0.8 Ω
In single-phase to ground modeling of arc, the amounts depend on duration time of arc severely. The duration time of arc is determined as the function of time as follows:
(9) τ = . ( ) Where τ is the time duration of initial arc and a is the factor of negative factor.
VI. THEARCMODELINGINATP-EMTPSOFTWARE
The arc model, which is mentioned above, has been utilized successfully in EHV networks. Moreover, this model can be used in 10 kV distribution network by regulating its parameters [12]. This model is available in ATP-EMTP software.
The dynamic model of arc is divided into Thevenin and Iterated models:
In Thevenin model, the components of electrical arc are represented as a di-pole element which is achieved by Thevenin equations.
Fig.4. The equivalent circuit of arc Thevenin
In this method, just one arc can be available in network. More than one arc in ancillary networks can be possible by separate time components. The equations of calculation of arc current in this method are as follows:
(10) = . 1 + . Where g can be obtained by Laplace equations:
(11) ( )= 1 1 + . . ( )
The other method is Iterated method which has not the limitation of Thevenin method. With utilizing the differential equations continuously, the more precise results will be yielded, but this method has a lower speed against the Thevenin method. The equivalent circuit has been illustrated in following:
Figure 5. Equivalent circuit of Iterated arc
The following equation is replaced in iarc equation in Thevenin status and other equations will remain in their previous form:
(12) = .
Generally, the dynamic models which are capable to investigate the interaction of fault arc in electrical circuits during fault occurrence will be appropriate. So, this modeling method can be used as a prosper method to achieve the main factors of arc interactions in power system and introduce its distinguish condition
VII. SIMULATIONANDCALCULATIONMETHODS
The system that the simulation will be carried out based on it is extracted according to [2] and with some changes has been illustrated in Fig. 6. Its parameters have been presented in Table 1.
Fig.6. The studied microgrid TABLE1.
THE PARAMETERS OF GRID ELEMENTS
Parameters Utilities
50 Hz Grid frequency
20kV Grid voltage
5 MVA Power of each DG
3MW,2MVAR Load 1,2
0.1W,0.1MVAR Load 3
4 km Line length
0.02 Ω Line resistance
10 mH Line Inductance
0.1 µF Line Capacitor
As it is obvious, this network has two DGs and three different loads which are connected as microgrid to the main grid.
In this microgrid, each one of two ancillary grids can operate in islanded mode in emergency conditions.
In this paper, the Imode is utilized for analysis because it can obliterate every similarity and common factors fault waveforms due to the fact that the features of unique transient fault against the other faults or breaker operation is lower.
Equation 13 is to determine the :
(13) = − 2 +
If the frequency components of fault signals be higher, the difference between fault and other frequency components (like breaker operation) will be clearer. Consequently, the higher degree of decomposition of wavelet has result in higher range of difference and investigation.
In this method, the utilized rate of voltage frequency is 20 MHz. To detect the type of the fault, the transient oscillations travelling wave and generated power frequency after fault have been used.
In this research, the single-phase to ground fault is utilized that contains more than 90% of distribution network.
VIII. SYSTEMOFFAULTDETECTIONANDREMOVAL
As it is mentioned before, the way of fault detection is based on the analysis of high frequency of voltage and current which detect and separate the transient fault from permanent fault by natural substance of fault. To determine the type of fault (transient or permanent) the wavelet packet transform (WPT) is utilized.
The proposed protection scheme of this paper is divided into transient and permanent fault identification unite (TPIU) and optimize reclosing time unite (ORTU). The first part detects the type of the fault by use of WPT analysis of current waveform and also conformance of Fig. 7 flowchart and the second part detects the removal time of secondary arc, the travelling waves after transient fault occurrence, and optimize time of reconnecting the circuit by using the same analysis of current waveform. In this system, the high frequencies of current signal are obtained by circuit breaker and its nature is analyzed by WPT. The type of fault and reconnection time in each transient fault condition has been detected with consideration of threshold magnitude of each condition.
The fault waveform in permanent and transient conditions is illustrated in Fig. 9 and 10 and also the WPT waveform from which are illustrated in Fig. 11 and 12.
Fig.7. Flowchart of TPIU
Fig.8. Flowchart of ORTU
Fig.9. Waveform of transient fault current
Fig.10. Waveform of permanent fault current
Fig.11. WPT waveform of transient fault current
Fig.12. WPT waveform of permanent fault current
As it is obvious in Fig. 13 and 14, there is some noises in obtained WPT waveform from fault current signal in transient signal after fault occurrence; whereas, these noises are not observed in obtained WPT waveform from analyzed signal of current in permanent fault. As it is clear from TPIU flowchart, this system sends tripping command to breaker and after a short time constant compares the WPT magnitude with initial threshold magnitude. If the WPT magnitude was lower than the threshold magnitude, it will distinct the fault as permanent type and will deactivate the ORTU and recloser units and will behave with fault as permanent fault. Otherwise, it detects the fault as transient fault and behaves with it as transient fault and activates the ORTU and recloser units.
Fig.13. The WPT waveform from permanent fault current and its limitation amount for TPIU
Fig.14. The obtained WPT waveform from transient fault current and its limitation amount for TPIU
If the fault was detected in transient form, the ORTU unit will be activated after detection of it. In this time, the new threshold magnitude will be introduced. With comparison of new WPT magnitude and new threshold magnitude in specific time intervals, the system will wait to send the reconnection command of breaker when the remain noises become zero which are represented of secondary arc and travelling waves damping. The mentioned time is mere right time of reconnecting of breaker.
Fig.15. The balanced WPT waveform from permanent fault current and its threshold magnitude for ORTU The Fig. 16 shows the waveform for two conditions of transient and permanent fault. As it is expected, this waveform obliterates the combined features of these two kinds of fault to detect the fault more precisely.
Fig.16. Top figure: I_mode for permanent fault, and bottom figure: I_mode for transient fault
The Fig. 17 shows the WPT waveform per different levels of waveform signal decomposition. As it is clear, the higher range of decomposition of signal waveform lead to more precise waveform of WPT.
Fig.17. Different levels of WPT
WPT waveform of current and voltage of other clusters, which no fault has occurred, is always zero and shows no fault occurrence. This waveform is zero for voltage magnitude but for its current is as following figures.
Fig.18. The waveform of WPT of current for direction of main grid and for permanent fault
Fig.19. The waveform of WPT of current for direction of microgrid and for transient fault
WPT waveform of voltage of the cluster which the fault has occurred in is like the waveform of WPT current direction of main grid. As it is obvious from the figure, the type of fault is detectable but the time of secondary arc removal and travelling wave is not detectable.
All the mentioned points are true for both clusters of microgrid but to protect the main grid, the proportional protection design with the structure of distribution network is required.
IX. CONCLUSION
In this paper, a new novel methodology for detection of transient and permanent faults and also the optimized method of reclosing operation have been presented. This method has got sample from the main waveform by use of wavelet transformation decomposition and detect the type of the fault by transient and permanent identification unite (TPIU) and analysis of high frequency indices of fault current which have been obtained from circuit by circuit breaker.
After it, the detection of optimized reconnection time interval has been carried out for transient faults by use of optimize reclosing time unite (ORTU), the time of secondary arc removal and travelling waves based on the some analysis method and finally the reconnection command will send to breaker.
This scheme reduces the damages occurrence of previous methods and also decreases the possibility of fault occurrence in the fault type detection.
This method utilizes the expansion of wavelet transformation which is one of the best tools for analysis of static frequency signals and detection the occurrence the irregularities in signal.
From the advantages of this methodology, the deficiency of sensitivity to fault type, fault resistance and angle of fault occurrence can be mentioned. Moreover, the degree of short circuit current and precise adjustment of sources does not have any influence on the proposed methodology.
Acknowledgment
The authors declare that they have no conflicts of interest in the research.
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