Method and device for distinguishing DC component users based on fundamental wave and harmonic wave phase angle relationship

Abstract

A method and device for identifying DC component users based on the relationship between the fundamental and harmonic phase angles. The power quality analysis module in the IoT power meter reads the fundamental amplitude and phase angle, and the amplitude and phase angle of each harmonic of the secondary current of the current transformer; when the amplitude of each harmonic is less than the amplitude threshold, it is determined to be a non-DC component user. When there is any harmonic amplitude that is not less than the amplitude threshold, for each harmonic that is not less than the amplitude threshold, based on the trigonometric function theorem, the phase angle of each harmonic is processed as a positive value using the period of each harmonic; and the ratio of each harmonic phase angle processed as a positive value to the corresponding harmonic order is calculated; the difference between the ratio and the fundamental frequency impedance angle of the current transformer is calculated as the calculated fundamental phase angle corresponding to each harmonic; when the error between the calculated fundamental phase angle corresponding to each harmonic and the fundamental phase angle is less than the error threshold, it is determined to be a DC component user.

Description

Technical Field

[0001] The present invention belongs to the technical field of power quality detection, and in particular relates to a method and device for distinguishing DC component users based on the phase angle relationship between fundamental waves and harmonics. Background Art

[0002] Driven by the dual carbon goals, the use of electricity instead of coal is rapidly expanding in the industrial heating sector. Power electronic equipment, such as half-wave rectifier heating devices, generate a DC component in the low-voltage distribution network, which accounts for a certain proportion of the fundamental current. The presence of DC can cause half-wave saturation of the current transformer core, leading to a surge in excitation current and secondary current distortion, seriously affecting the accuracy of user energy metering. Therefore, it is crucial to quickly and accurately identify users with DC components within the distribution network.

[0003] Because the DC bias phenomenon in low-voltage current transformers used for metering has only received sufficient attention in the past year or two, there are few related methods. Currently, only rough identification can be performed based on changes in the line loss rate within the substation. Because there are many factors that affect line loss rates, such as line faults, meter damage, and user overcapacity, current identification methods are not very accurate and can only be used to screen out potential DC component users, followed by further manual on-site investigation. Moreover, although the DC component flows from the primary side of the transformer, the secondary side data most directly reflects the characteristics of the transformer being affected by DC, and existing electricity meters often only display this characteristic. Summary of the Invention

[0004] In order to address the deficiencies in the prior art, the present invention provides a method and device for identifying DC component users based on the phase angle relationship between the fundamental wave and harmonics. Based on the phase angle relationship between the fundamental wave and harmonics of the secondary side current of the current transformer under the influence of DC, combined with the power quality analysis function of the new generation of IoT electric energy meters, DC component users are identified.

[0005] The present invention adopts the following technical solutions.

[0006] The present invention proposes a method for distinguishing DC component users based on the relationship between the fundamental wave and the phase angle of the harmonics. The method uses an IoT electric energy meter to measure the user's electricity. The IoT electric energy meter includes a current transformer and a power quality analysis module. The power quality analysis module reads the amplitude and phase angle of the fundamental wave of the secondary current of the current transformer and the amplitude and phase angle of each harmonic. The method includes:

[0007] Step 1: When the amplitude of each harmonic is less than the amplitude threshold, the user corresponding to the IoT electric energy meter is determined to be a non-DC component user. When the amplitude of any harmonic is not less than the amplitude threshold, step 2 is entered;

[0008] Step 2: For each harmonic that is not less than the amplitude threshold, based on the trigonometric function theorem, the phase angle of each harmonic is processed into a positive value using the period of each harmonic; and the ratio of the phase angle of each harmonic processed into a positive value to the corresponding harmonic order is calculated; and the difference between the ratio and the fundamental frequency impedance angle of the current transformer is calculated as the fundamental wave phase angle corresponding to each harmonic;

[0009] Step 3: When the errors between the calculated fundamental phase angle values corresponding to each harmonic and the fundamental phase angle collected by the power quality analysis module are all less than the error threshold, the user is determined to be a DC component user; otherwise, return to step 1.

[0010] The amplitude threshold is 1% of the fundamental amplitude.

[0011] In step 2, the phase angles of each harmonic are processed as positive values using the following relationship:

[0012]

[0013] Where,

[0014] is the phase angle of each harmonic after being processed into a positive value,

[0015] θ i The phase angle of each harmonic read by the power quality analysis module,

[0016] T θ is the period of each harmonic,

[0017] i is the harmonic order.

[0018] The period of each harmonic satisfies T θ =360° / i.

[0019] In step 2, the calculation formula for the fundamental wave phase angle corresponding to each harmonic is:

[0020]

[0021] Where,

[0022] is the calculated value of the fundamental wave phase angle corresponding to each harmonic,

[0023] β1 is the fundamental frequency impedance angle of the current transformer, which is the factory value of the current transformer.

[0024] The error threshold is set to 10%.

[0025] The present invention also proposes a device for distinguishing DC component users based on the relationship between the fundamental wave and the harmonic phase angle, the device comprising a power quality analysis module, the power quality analysis module reading the amplitude and phase angle of the fundamental wave and the amplitude and phase angle of each harmonic of the secondary current of the current transformer;

[0026] The device further comprises: an amplitude discrimination module and a phase angle discrimination module;

[0027] Amplitude discrimination module, used to determine that the user corresponding to the IoT electric energy meter is not a DC component user when the amplitude of each harmonic is less than the amplitude threshold;

[0028] The phase angle discrimination module is used to, when the amplitude of any harmonic is not less than the amplitude threshold, process the phase angle of each harmonic that is not less than the amplitude threshold as a positive value based on the trigonometric function theorem and the period of each harmonic; calculate the ratio of the phase angle of each harmonic processed as a positive value to the corresponding harmonic order; calculate the difference between the ratio and the fundamental frequency impedance angle of the current transformer as the calculated fundamental phase angle corresponding to each harmonic; and determine that the user is a DC component user when the error between the calculated fundamental phase angle corresponding to each harmonic and the fundamental phase angle collected by the power quality analysis module is less than the error threshold.

[0029] A terminal includes a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method.

[0030] A computer-readable storage medium having a computer program stored thereon, wherein the program implements the steps of the method when executed by a processor.

[0031] The beneficial effect of the present invention is that, compared with the prior art, the present invention gives full play to the advantage that the power quality analysis module in the Internet of Things electric energy meter can read the amplitude and phase angle of the fundamental wave of the secondary current of the current transformer, and the amplitude and phase angle of each harmonic use the phase angle data of the secondary side current of the current transformer, and performs preliminary identification of DC component users based on the relationship between the amplitude of the harmonic and the fundamental wave; then, the fundamental wave phase angle calculation value corresponding to each harmonic is obtained by calculating the phase angle of each harmonic that is not less than the amplitude threshold. When the error between the fundamental wave phase angle calculation value corresponding to each harmonic and the fundamental wave phase angle collected by the power quality analysis module is less than the error threshold, the user is determined to be a DC component user. Through experimental verification, the method of the present invention is easy to implement, improves the recognition accuracy of DC component users, and has the advantages of simple calculation and fast recognition speed.

[0032] The current transformer secondary side phase angle data used in the present invention is collected by an IoT electric energy meter equipped with a power quality module, thereby ensuring the accuracy of the data, eliminating the need for configuring other collection devices, saving manpower and material resources, and reducing the cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a flow chart of the method for identifying DC component users based on the phase angle relationship between the fundamental wave and the harmonic waves proposed by the present invention;

[0034] Figure 2 1 is a graph showing the core excitation characteristic under DC bias in an embodiment of the present invention. DETAILED DESCRIPTION

[0035] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. The embodiments described in this application are only part of the embodiments of the present invention, not all of them. Based on the spirit of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0036] State Grid Corporation of China is currently promoting the use of a new generation of IoT meters. Compared to traditional electricity meters, these meters feature a new power quality analysis module that can read the phase angles of the fundamental and harmonic currents. Therefore, this paper investigates the relationship between the harmonic phase angles of the secondary current of current transformers under the influence of DC. In combination with the power quality analysis capabilities of IoT meters, a method for identifying DC component users based on this harmonic phase angle relationship is proposed.

[0037] The present invention proposes a method for distinguishing DC component users based on the relationship between the fundamental wave and the harmonic phase angle. The method uses an IoT electric energy meter to measure the user's electricity. The IoT electric energy meter includes a current transformer and a power quality analysis module. The power quality analysis module reads the amplitude and phase angle of the fundamental wave of the secondary current of the current transformer, and the amplitude and phase angle of each harmonic. Figure 1 Shown, including:

[0038] Step 1: When the amplitude of each harmonic is less than the amplitude threshold, the user corresponding to the IoT electric energy meter is determined to be a non-DC component user. When the amplitude of any harmonic is not less than the amplitude threshold, step 2 is entered.

[0039] In a non-limiting preferred embodiment, the amplitudes of the fundamental wave and the second, third, and fourth harmonics displayed on the IoT power meter are read. If the amplitudes of the second, third, and fourth harmonics are all less than 1% of the amplitude of the fundamental wave, it is considered that there are no harmonic components and the user corresponding to the IoT power meter is not a DC component user. Otherwise, the process proceeds to step 2.

[0040] Specifically, according to the minimum value of the proportion of harmonics to fundamental waves obtained by actual measurement, the amplitude threshold is determined to be 1% of the fundamental wave amplitude.

[0041] Step 2: For each harmonic that is not less than the amplitude threshold, based on the trigonometric function theorem, the phase angle of each harmonic is processed into a positive value using the period of each harmonic; and the ratio of the phase angle of each harmonic processed into a positive value to the corresponding harmonic order is calculated; and the difference between the ratio and the fundamental frequency impedance angle of the current transformer is calculated as the fundamental wave phase angle calculation value corresponding to each harmonic.

[0042] Specifically, the phase angles of each harmonic after being processed into positive values are: The value read by the IoT electric energy meter for each harmonic phase angle is θ i , the harmonic period corresponding to each harmonic is T θ , i is the harmonic order, and the phase angle of each harmonic is treated as a positive value according to the following relationship:

[0043]

[0044] Where,

[0045] is the phase angle of each harmonic after being processed into a positive value,

[0046] θ i The phase angle of each harmonic read by the power quality analysis module,

[0047] T θ is the period of each harmonic,

[0048] i is the harmonic order.

[0049] The period of each harmonic satisfies T θ =360° / i.

[0050] In a non-limiting preferred embodiment, the phase angle values of each harmonic read by the IoT electricity meter are positive and negative. In order to unify the format and facilitate subsequent calculations, the second harmonic phase angle is the value read by the IoT electricity meter plus 360 degrees (i.e., twice the harmonic period of 180 degrees), the third harmonic phase angle is the value read by the IoT electricity meter plus 480 degrees (i.e., four times the harmonic period of 120 degrees), and the fourth harmonic phase angle is the value read by the IoT electricity meter plus 540 degrees (i.e., six times the harmonic period of 90 degrees).

[0051] Figure 2 It is a characteristic curve diagram of the core excitation under DC bias, including the characteristic curve of magnetic flux density N and phase angle θ, the characteristic curve of magnetic flux density B and magnetic field intensity H, and the characteristic curve of magnetic field intensity H and phase angle θ.

[0052] like Figure 2As shown in the figure, the core material of the current transformer is silicon steel sheet. Before the core magnetic flux density N reaches the saturation point, the core magnetic permeability is large and the magnetic flux density B and the magnetic field strength H are approximately linear. When the magnetic flux density B exceeds the saturation point, the core magnetic permeability will decrease rapidly. Therefore, Figure 2 The two linear straight lines shown represent the BH relationship, namely the non-saturation magnetic permeability μ1 and the saturation magnetic permeability μ2.

[0053] Figure 2 In, H bias is the bias magnetic field intensity caused by DC flux, H u is the peak value of the magnetic field intensity at the knee point of the current transformer, H dc is the equivalent magnetic field intensity corresponding to the DC component, and α is the flux angle.

[0054] When a DC current I flows through the current transformer dc When the iron core generates a corresponding DC magnetic flux density B dc , plus the original peak value B ac The AC magnetic flux density, the maximum value of the total magnetic flux density in the iron core is B m Will exceed the knee point flux density B k , the core enters the saturation zone. Figure 2 Where n is the phase angle difference between the peak point of the core magnetic flux density and the coordinate origin, and its expression is as follows:

[0055]

[0056] Where,

[0057] is the fundamental phase angle of the secondary current of the current transformer,

[0058] β1 is the impedance angle of the current transformer secondary load at the fundamental frequency.

[0059] The larger the DC current, the larger the value of the flux angle α. When the DC is zero, α≈0.

[0060] according to Figure 2 The magnetic field intensity H in one cycle can be obtained s The expression of (t) is as follows:

[0061]

[0062] Where ω is the angular frequency.

[0063] Applying Ampere's circuit theorem and further performing Fourier decomposition on Equation (2), we can obtain the second harmonic phase angle in the excitation current: Third harmonic phase angle Fourth harmonic phase angle The expressions are as follows:

[0064]

[0065]

[0066]

[0067] is the harmonic phase angle, where i is the harmonic order, then the relationship between the harmonic phase angle and n is:

[0068]

[0069] Because the secondary current of the current transformer is equal to the primary current minus the excitation current, and the primary current consists only of the fundamental wave and DC components, the harmonic components in the excitation current are the harmonic components in the secondary current.

[0070] Through the above analysis, the difference between the phase angle of each harmonic after being processed into a positive value and the impedance angle of the secondary load of the current transformer at the fundamental frequency is calculated to obtain the calculated fundamental wave phase angle corresponding to each harmonic.

[0071] Specifically, the calculation formula for the fundamental wave phase angle calculation value corresponding to each harmonic is:

[0072]

[0073] Where,

[0074] is the calculated value of the fundamental wave phase angle corresponding to each harmonic,

[0075] β1 is the fundamental frequency impedance angle of the current transformer, which is the factory value of the current transformer.

[0076] In a non-limiting preferred embodiment, the phase angles of the fundamental wave and the second, third, and fourth harmonics on the IoT electric energy meter are read. The fundamental wave phase angle differences between the second, third, and fourth harmonics in the secondary current and the fundamental wave phase angle are as follows:

[0077]

[0078]

[0079]

[0080] Where, They are the second harmonic phase angle, third harmonic phase angle, and fourth harmonic phase angle in the secondary current respectively.

[0081] Step 3: When the errors between the calculated fundamental phase angle values corresponding to each harmonic and the fundamental phase angle collected by the power quality analysis module are all less than the error threshold, the user is determined to be a DC component user; otherwise, return to step 1.

[0082] In a non-limiting preferred embodiment, to relax the criteria and ensure that all DC users can be identified, an error coefficient is introduced. When the error between the fundamental wave phase angle difference corresponding to each harmonic and the fundamental wave phase angle is less than 10%, the user corresponding to the IoT energy meter is considered a DC user. Because the phase angle relationship between each harmonic and the fundamental wave is simultaneously calculated in step 4, misidentification caused by non-DC factors due to a harmonic and the fundamental wave meeting the error threshold is avoided.

[0083] The method proposed in the present invention was tested, and the result data are shown in Table 1:

[0084] Table 1 Test results data

[0085]

[0086] It can be seen from Table 1 that under different proportions of DC components, the error percentage between the fundamental phase angle value calculated using the measured values of the second, third, and fourth harmonic phase angles and the measured value of the fundamental phase angle is less than 7%. Therefore, the method proposed in the present invention has high accuracy and reliability.

[0087] The present invention also proposes a device for distinguishing DC component users based on the relationship between the fundamental wave and the harmonic phase angle, the device comprising a power quality analysis module, the power quality analysis module reading the amplitude and phase angle of the fundamental wave and the amplitude and phase angle of each harmonic of the secondary current of the current transformer;

[0088] The device further comprises: an amplitude discrimination module and a phase angle discrimination module;

[0089] Amplitude discrimination module, used to determine that the user corresponding to the IoT electric energy meter is not a DC component user when the amplitude of each harmonic is less than the amplitude threshold;

[0090] The phase angle discrimination module is used to, when the amplitude of any harmonic is not less than the amplitude threshold, process the phase angle of each harmonic that is not less than the amplitude threshold as a positive value based on the trigonometric function theorem and the period of each harmonic; calculate the ratio of the phase angle of each harmonic processed as a positive value to the corresponding harmonic order; calculate the difference between the ratio and the fundamental frequency impedance angle of the current transformer as the calculated fundamental phase angle corresponding to each harmonic; and determine that the user is a DC component user when the error between the calculated fundamental phase angle corresponding to each harmonic and the fundamental phase angle collected by the power quality analysis module is less than the error threshold.

[0091] The present invention proposes a method for identifying DC component users based on the relationship between fundamental and harmonic phase angles. The method collects current fundamental and harmonic data of the current through an Internet of Things electric energy meter. When the amplitude of each harmonic is greater than an amplitude threshold and the difference between each fundamental phase angle calculation value and the actual fundamental phase angle value is less than an error threshold, the user is determined to be a DC component user. The method uses the difference between each harmonic phase angle processing value and the impedance angle of the secondary load of the current transformer at the fundamental frequency to obtain multiple fundamental phase angle calculation values, and each harmonic phase angle is pre-processed according to the period of each harmonic phase angle to obtain the processed value of each harmonic phase angle.

[0092] The present disclosure may be a system, method and / or computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0093] A computer-readable storage medium can be a tangible device that can hold and store instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination thereof. As used herein, a computer-readable storage medium is not to be construed as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through an electrical wire.

[0094] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions to be stored in the computer-readable storage medium in each computing / processing device.

[0095] The computer program instructions for performing the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Smalltalk, C++, and conventional procedural programming languages such as "C" language or similar programming languages. Computer-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., utilizing an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be personalized by utilizing the state information of the computer-readable program instructions. The electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0096] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A method for identifying DC component users based on the relationship between the fundamental wave and the phase angle of the harmonics, using an IoT electric energy meter to measure the user's electricity consumption. The IoT electric energy meter includes a current transformer and a power quality analysis module. The power quality analysis module reads the amplitude and phase angle of the fundamental wave of the secondary current of the current transformer and the amplitude and phase angle of each harmonic; characterized in that: include: Step 1: When the amplitude of each harmonic is less than the amplitude threshold, the user corresponding to the IoT electric energy meter is determined to be a non-DC component user. When the amplitude of any harmonic is not less than the amplitude threshold, step 2 is entered; Step 2: For each harmonic that is not less than the amplitude threshold, based on the trigonometric theorem, the phase angle of each harmonic is processed into a positive value using the period of each harmonic; and the ratio of the phase angle of each harmonic processed into a positive value to the corresponding harmonic order is calculated; Calculating the difference between the ratio and the fundamental frequency impedance angle of the current transformer as the fundamental wave phase angle calculation value corresponding to each harmonic; Step 3: When the errors between the calculated fundamental phase angle values corresponding to each harmonic and the fundamental phase angle collected by the power quality analysis module are all less than the error threshold, the user is determined to be a DC component user; otherwise, return to step 1.

2. The method for identifying DC component users based on the phase angle relationship between fundamental wave and harmonic wave according to claim 1, characterized in that: The amplitude threshold is 1% of the fundamental amplitude.

3. The method for identifying DC component users based on the phase angle relationship between fundamental wave and harmonic wave according to claim 1, characterized in that: In step 2, the phase angles of each harmonic are processed as positive values using the following relationship: Where, is the phase angle of each harmonic after being processed into a positive value, θ i The phase angle of each harmonic read by the power quality analysis module, T θ is the period of each harmonic, i is the harmonic order.

4. The method for identifying DC component users based on the phase angle relationship between fundamental wave and harmonic wave according to claim 3, characterized in that: The period of each harmonic satisfies T θ =360° / i.

5. The method for identifying DC component users based on the phase angle relationship between fundamental wave and harmonic wave according to claim 3, characterized in that: In step 2, the calculation formula for the fundamental wave phase angle corresponding to each harmonic is: Where, is the calculated value of the fundamental wave phase angle corresponding to each harmonic, β1 is the fundamental frequency impedance angle of the current transformer, which is the factory value of the current transformer.

6. The method for identifying DC component users based on the phase angle relationship between fundamental wave and harmonic wave according to claim 1, characterized in that: The error threshold is set to 10%.

7. A device for identifying DC component users based on the relationship between the fundamental wave and the phase angle of the harmonics using the method according to any one of claims 1 to 6, the device comprising a power quality analysis module, the power quality analysis module reading the amplitude and phase angle of the fundamental wave and the amplitude and phase angle of each harmonic of the secondary current of the current transformer; characterized in that: The device further comprises: an amplitude discrimination module and a phase angle discrimination module; Amplitude discrimination module, used to determine that the user corresponding to the IoT electric energy meter is not a DC component user when the amplitude of each harmonic is less than the amplitude threshold; The phase angle discrimination module is used to, when the amplitude of any harmonic is not less than the amplitude threshold, process the phase angle of each harmonic that is not less than the amplitude threshold as a positive value based on the trigonometric function theorem and the period of each harmonic; calculate the ratio of the phase angle of each harmonic processed as a positive value to the corresponding harmonic order; calculate the difference between the ratio and the fundamental frequency impedance angle of the current transformer as the calculated fundamental phase angle corresponding to each harmonic; and determine that the user is a DC component user when the error between the calculated fundamental phase angle corresponding to each harmonic and the fundamental phase angle collected by the power quality analysis module is less than the error threshold.

8. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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