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Combination AFCIs: What they will and will not do
Abstract
All new home branch circuits are required by Code to be electronically protected, either by Ground Fault Circuit Interrupters (GFCIs) or Arc Fault Circuit Interrupters (AFCIs). Areas including kitchens, bathrooms, garages, etc. must be protected by GFCIs, while living areas must be protected by AFCIs. The AFCI is the fourth generation in residential branch circuit protection after fuses, circuit breakers, and GFCIs. National Electrical Code in 2002 first added AFCI protection, for bedrooms outlets. In 2008, coverage was expanded to all living areas, also adding that only “Combination AFCIs” are allowed. Manufacturers and UL claim that arcing across a break in a cord's conductor is hazardous, and that a Combination AFCI will respond to prevent a fire. The author believes the claim is unproven, and will explain why the disallowed Branch/feeder AFCI provides more protection at less cost.
... There are many methods for preventing arc-faults, including the arc-fault circuit interrupters (AFCI), which is a commonly used circuit that detects the high-frequency component of the phenomenon [11]. However, according to a study by Kim et al. [12], AFCIs are prone to accidental tripping because some electrical appliances generate a waveform similar to that of a low-voltage arc-fault. This is not entirely surprising given that the method of detection is based only on a comparison of the problematic waveform. ...
In this research, we focus on low-voltage arc-faults in AC systems. In our previous studies, we demonstrated that arc-faults in AC systems differ from those in DC systems because in an AC system the arc itself is not a gap-jumping electrical arc between two conductors but rather an advanced glowing connection state that occurs exclusively in copper-based connections. In the present study, we improved upon our AC arc-fault generation simulation in MATLAB, matching our previous findings. The arc-fault simulation in MATLAB replicated the exact waveform exhibited in an actual AC arcfault environment. Therefore, we concluded that the phenomenon likely followed the mechanism we proposed in our previous research. We have also detected the phenomenon by using a method we devised in our previous research and refined it to match the mechanism derived from our present findings. The simulation results for our detection method revealed that to obtain the best detection accuracy, the magnetic core of the inductor/current transformer must have low coercivity and may not be saturated before the current waveform has shifted to another polarity. This detection method may yield a greater ratio of accuracy to manufacturing cost given that the main component does not include a high-frequency circuit analyzer.
... The filtered time-domain current signal is then processed, usually by proprietary detection algorithms and carefully tuned threshold setting in a digital signal processor (DSP) or microcontrollers (MCU) [12,13]. Some research, however, has shown that neither branch/feeder AFCIs nor combination AFCIs would accurately detect all series arc faults [14]. This could be in part due to how the threshold of the detection algorithm was tuned and the assumptions made in the filter as to the frequencies in which the arc signature signal appears. ...
... The filtered timedomain current signal is then processed, usually by proprietary detection algorithms and a carefully tuned threshold setting in a digital signal processor (DSP) or microprocessor [20], [22]. Some research, however, has shown that neither branch/feeder AFCI nor combination AFCI would accurately detect all series arc faults [26]. This could be in part due to how the threshold detection algorithm was tuned and the assumptions made in the filter as to the frequencies in which the arc signature signal appears. ...
Arc faults have always been a concern for electrical systems, as they can cause fires, personnel shock hazard, and system failure. Existing commercialized techniques that rely on pattern recognition in the time domain or frequency domain analysis using a Fourier transform do not work well, because the signal-to-noise ratio is low and the arc signal is not periodic. Instead, wavelet transform (WT) provides a time and frequency approach to analyze target signals with multiple resolutions. In this paper, a new approach using WT for arc fault analysis in dc systems is proposed. The process of detecting an arc fault involves signal analysis and then feature identification. The focus of this paper is on the former. Simulation models are synthesized to study the theoretical results of the proposed methodology and traditional fast Fourier transform analysis on arcing faults. Experimental data from the dc system of a photovoltaic array is also shown to validate the approach.
... The filtered time-domain current signal will be processed by specific programs and threshold setting by a Digital Signal Processor (DSP) or microprocessor [10,11]. However, some research has shown that neither Branch/Feeder AFCI nor Combination AFCI would accurately detect the series arc faults [12]. ...
Arc faults have always been a concern for PV systems. Emerging safety standards will soon require PV system to include arc fault detection equipment. Arc faults can cause fires, shock hazard, and system failure. Existing techniques that rely on pattern recognition in the time domain, or amplitude detection in the frequency domain by using a Fourier Transform, don't work well for arcs because the signal to noise ratio is low and the arc signal is not periodic. Instead, wavelet transform analysis provides a time and frequency approach to analyze target signals with multiple resolutions. In this paper, a new approach using wavelet transform for arc fault detection in DC systems is proposed. Simulation models are established to study the theoretical results of the proposed methodology and traditional FFT analysis of arcing faults. Experimental data from an arcing AC system shows the efficacy is not limited to only dc power systems.
Residential fires of electrical origin have been a major concern for a long time. A fire can be initiated by excessive current (due to an overload or a short circuit) or arcing current. Therefore, both the Canadian Electrical Code (CE Code) Part I and the National Electrical Code (NEC) require the installation of overcurrent protection devices (OCPDs) to detect and clear excessive current. Conversely, arcing current is too low for OCPDs to detect. It could take an electric arc minutes, days, weeks, months, or even years to initiate a fire. Therefore, a new solution was required for detecting those slowly developing arcs. Thus, arc-fault circuit-interrupters (AFCIs) were born. AFCIs are capable of detecting an arcing condition (while still developing) and de-energizing the circuit before the arcing circuit ignites.
The gradually increased proportion of power electronic devices and the distributed energy resource (DER), in the distribution network, induced more harmonic and pulse signals to be injected into the grid. Arc faults, as the critical and common faults in the distribution system, are the potential reasons for the safety of the personnel and equipment. Furthermore, intensely chaotic characteristics of the arc current and the harmonic generated from the power electronic devices pollute the fault signature, which may cause misjudgment or malfunctions of arc detection devices. Therefore, to identify the arc fault rapidly and accurately, this article starts with the mechanism of the arc formation. It analyzes the fault signature with resistive, inductive, and capacitive loads to reduce the detection of blind spots. Then, the time-frequency is utilized to analyze the fault current of each load type to capture the common feature in the frequency domain. Comparing multiple tests shows that the proposed approach can accurately and robustly identify the arc fault in different operation conditions.
Electrical faults cause fire or shock hazards in homes and offices. Flexible power cords are particularly susceptible to metal or insulation degradation that may lead to a variety of electrical faults. This paper introduces a new Smart Plug 2.0 device which offers all-in-one protection against short circuit, overload, arc, and ground faults in addition to the wireless power control and monitor function of conventional Smart Plug devices. It offers microsecond-scale time resolution to detect and respond to a fault condition, and significantly reduces the electrothermal stress on household electrical wires and loads. A new arc fault detection method is developed using machine learning models based on load current
di/dt
events. Comparing to other solid-state circuit breaker (SSCB) designs which typically respond to overcurrent conditions only, Smart Plug 2.0 integrates additional protective functions into the same hardware structure with minimal cost penalty. A 120V/10A solid-state Smart Plug 2.0 prototype using power MOSEFTs is designed and tested. It has experimentally demonstrated the comprehensive protection features against all types of electrical faults.
Series Arc Fault is one of the disturbances of arcing jump is caused by gas ionization between two ends of damaged conductors or broken wire forming a gap in the insulator. Series arc fault is the primary driver of electrical fire. However, lack of knowledge of the disturbance of series arc fault causes the problem of electrical fire not be mitigated. Magnitude current is not capable to detect of series arc fault. Therefore, this paper proposes fast fourier transform (FFT) to detect series AC arc fault in low voltage using microcontroller ARM STM32F7NGH in real time. A cheap and high speed of microcontroller ARM STM32F7NGH can be used for FFT computation to transform signal in time domain to frequency domain. Moreover, in this paper, protection of series AC arc fault is proposed in the real time mode. In this experimental process, some various experiments are tested to evaluate the reliability of FFT and protection with various load starts from 1 A, 2 A, 3 A, 4 A in resistive load. The result of this experiment shows that series AC arc fault protection with STM32F7 microcontroller and FFT algorithm can be utilized to ensure series AC arc fault properly.
This paper presents a method for the detection of series arc faults in electrical circuits, which has been developed starting from an experimental characterization of the arc fault phenomenon and an arcing current study in several test conditions. Starting from this, the authors have found that is it possible to suitably detect arc faults by means of a high-resolution low-frequency harmonic analysis of current signal, based on chirp zeta transform, and a proper set of indicators. The proposed method effectiveness is shown by means of experimental tests, which were carried in both arcing and nonarcing conditions and in the presence of different loads, chosen according to the UL 1699 standard requirements.
In this paper a novel set of indicators is presented for arc faults detection in electrical circuits. The indicators are defined starting from an experimental characterization of the arc fault phenomenon and the study of the arcing current in several test conditions, which were chosen in accordance with the UL 1699 Standard requirements. The proposed parameters are measured by means of a high resolution low frequency spectral analysis of the arcing current, which allows to achieve a good spectral resolution even with short observation windows.
Unintentional arc faults due to damaged power line cords and loose connections can cause serious fires; thus, they are a safety hazard in residential areas. Therefore, arc fault circuit interrupters are being increasingly used in homes to protect against arcs that may cause fires. In this paper, we analyzed the ignition characteristics of series arcs on the basis of load current. Furthermore, we recommended suitable arc clearing times through characteristics analysis in the Korean residential electric environment. We determined the arc clearing time via the carbonized path arc clearing time test using an ultraviolet signal detecting system according to the test method of the UL 1699 standard. In the experiments, heat-resistant indoor PVC insulated (HIV) wires, which is a type of residential electrical wire, were used as the wire specimens.
This paper employs the discrete wavelet transform (DWT) and an artificial neural network to identify the occurrence of serial arc faults on indoor low voltage power lines. Electric arc faults on power lines must be detected in order to turn off the electric power sources before fire events occur. However, since the characteristics of line current waveforms during serial arc faults are complicated, smart detection technology is required to have high accurate recognition. The DWT is utilized to obtain the time-domain characteristics of line current waveforms, and the signal energy of some sub-bands is useful information to reflect the serial arc fault patterns. And then, a radial basis function neural network (RBFNN) is trained by using the data of signal energy obtained from DWT. After the training process, the RBFNN has excellent ability to identify the serial arc-fault conditions. At last, the accumulative RBFNN outputs of 30 power cycle line current data are used to certify the occurring of a serial arc fault on the line. This study also compares the results of detecting serial arc faults with a commercial arc-fault circuit interrupter (AFCI) to reveal the goodness of the purposed method.
This paper presents an experimental characterization of the arc fault phenomenon, for both AC and DC systems, focusing the attention on series arcs. The aim of the study is to find some current characteristics, which can be significant for the purpose of arc detection. The arcing current signal is analyzed in both time and frequency domain. For the AC analysis, the test conditions are chosen in accordance with the “unwanted tripping tests” and the “operation inhibition tests” reported in the Standard UL 1699. The DC study is carried out on the currents waveforms acquired during some on-field tests on a PV plant. Starting from the study herein presented, the authors have found that is it possible to suitably detect the arc faults, in both AC and DC systems, by using an high resolution low frequency harmonic current analysis.
Wire connections and plug contacts at receptacles account for the
majority of electrical power contacts in most residential structures.
Average current and duty cycle for these wiring devices have been
increasing over the past decades as more appliances, portable heating
equipment, and electronics are added to typical user loading. Receptacle
contact and connection failures contribute significantly to fire losses
in the United States. This paper provides comparative data on long-term
test performance of copper-wired screw and push-in wiring terminals and
on insertion plug contacts of receptacles presently on the market
Laboratory experiments have shown that, when a current-carrying,
loose copper wire connection is exposed to mechanical vibrations, a
layer of Cu2O grows to form a bridge between the contact
members, bonding them to one another. Due to the strongly negative
temperature coefficient of Cu2O at high temperatures, the
current is concentrated in a thin, glowing filament at or near the
surface of the oxide bridge. The maximum temperature of this filament
was found to be 1200-1300°C. Under the action of this hot filament a
rapid oxidation of the copper continues until, in the end, most of the
circumference of the copper wires has been converted to Cu2O
to a depth of a few tenths of a mm. As the corrosion proceeds the power
dissipation increases to values which can cause fire hazards if a
similar situation occurs in electrical apparatus or installations.
According to statistics, loose connections or broken wires are known to
be the cause of many fires. The phenomenon described explains how a
temperature high enough to initiate a fire can arise even when the
current through the connection is limited by the load impedance to
values of less than 1 ampere
Laboratory experiments are reported that show that when a
current-carrying loose copper wire connection is exposed to mechanical
vibrations, a layer of Cu2O grows to form a bridge between
the contact members, bonding them to one another. Due to the strongly
negative temperature coefficient of Cu2O at high
temperatures, the current is concentrated in a thin, glowing filament at
or near the surface of the oxide bridge. The maximum temperature of this
filament was found to be 1200-1300°C. Under the action of this hot
filament, a rapid oxidation of the copper continues until most of the
circumference of the copper wires is converted to Cu2O to a
depth of a few tenths of a millimeter. As the corrosion proceeds, the
power dissipation increases to values that can cause fire hazards. The
phenomenon described explains how a temperature high enough to initiate
a fire can arise, even when the current through the connection is
limited by the load impedance to values less than 1 A
Glowing Contact Areas in Loose Copper Wire Connections
- J Sletback
- R Kristensen
- H Sundklakk
- G Navik
- M Runde
"Glowing Contact Areas in Loose Copper Wire
Connections," J. Sletback, R. Kristensen, H. Sundklakk,
Norwegian Institute of Technology; and G. Navik, M.
Runde, Norwegian Electric Power Research Institute;
Proceedings of the Thirty-Seventh IEEE Holm
Conference on Electrical Contacts, 1991.