Feeder harmonic trajectory estimation method and terminal

Abstract

The invention discloses a feeder harmonic trajectory estimation method and a terminal. The method comprises the following steps: acquiring fundamental wave impedance data of a feeder and estimating harmonic impedance data based on harmonic times; calculating a state quantity approximate value of an equivalent PCC point in the feeder line by using the harmonic impedance data; and establishing a multi-objective function by taking the approximate value of the state quantity as an initial value and taking the virtual and real part estimation error of each harmonic of the equivalent PCC point, the total harmonic estimation error of the equivalent PCC point and the total effective value error of the node to be solved as constraints, and solving the multi-objective function to obtain the distribution transformer harmonic current content rate and the phase angle which are approximate to the real value. Under the condition of no modeling analysis or high-precision measurement of the harmonic state, the harmonic state is observed by using an approximate estimation method, the detection capability of the harmonic of the power distribution network is improved, an estimation result is prevented from deviating from an actual value through multiple constraints, and the observation precision of the harmonic state is improved.

Description

Technical Field

[0001] The present invention relates to the field of harmonic tracking, and in particular to a feeder harmonic trajectory estimation method and a terminal. Background Art

[0002] Nowadays, power electronic equipment accounts for an increasingly larger proportion of residential loads. These household appliances containing power electronic equipment will also generate a certain degree of harmonics during operation. In addition, due to the large-scale access of distributed renewable energy power generation to residents, harmonic pollution has also begun to show distributed characteristics.

[0003] At present, the methods used for harmonic estimation mainly include the least squares method, the improved least squares method, the Kalman filter model and other methods.

[0004] The least squares method is to establish a system observation equation that takes into account the measurement error, and then solve the harmonic state of the entire network based on the known network parameters of the system and some measured data. The improved least squares method includes the robust least squares method, which can obtain more accurate estimation results when there are errors in the measurement data.

[0005] The Kalman filter model is an effective method applied in the time domain. It is a state estimation algorithm that combines prior experience and measurement updates. The basic idea of ​​Kalman filtering is to use the previous state and measurement values ​​to predict and estimate the state of physical quantities.

[0006] These methods basically use physical model-based methods to perform modeling and analysis, describe the relationship between nodes, and estimate the unknown node status through the harmonic status of the monitoring point. However, the insufficient number of monitoring devices in the power grid will result in the harmonic status not being observable across the entire network, making it difficult to establish the measurement equation, and only relatively accurate harmonic current and voltage phase data will produce better results. Summary of the invention

[0007] The technical problem to be solved by the present invention is to provide a feeder harmonic trajectory estimation method and terminal to solve the problem that the harmonic state is difficult to observe.

[0008] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0009] A method for estimating a feeder harmonic trajectory comprises the steps of:

[0010] S1. Obtain fundamental impedance data of the feeder and estimate harmonic impedance data based on the harmonic order;

[0011] S2. Calculate the approximate value of the state quantity of the equivalent PCC point in the feeder using the harmonic impedance data;

[0012] S3. Taking the approximate value of the state quantity as the initial value, and taking the estimated error of the imaginary and real parts of each harmonic at the equivalent PCC point, the estimated error of the total harmonic at the equivalent PCC point, and the total effective value error of the node to be determined as constraints, a multi-objective function is established, and the multi-objective function is solved to obtain the distribution transformer harmonic current content rate and phase angle that are close to the true value.

[0013] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0014] A feeder harmonic trajectory estimation terminal comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor completes the following steps when executing the computer program: characterized in that the terminal comprises the steps of:

[0015] S1. Obtain fundamental impedance data of the feeder and estimate harmonic impedance data based on the harmonic order;

[0016] S2. Calculate the approximate value of the state quantity of the equivalent PCC point in the feeder using the harmonic impedance data;

[0017] S3. Taking the approximate value of the state quantity as the initial value, and taking the estimated error of the imaginary and real parts of each harmonic at the equivalent PCC point, the estimated error of the total harmonic at the equivalent PCC point, and the total effective value error of the node to be determined as constraints, a multi-objective function is established, and the multi-objective function is solved to obtain the distribution transformer harmonic current content rate and phase angle that are close to the true value.

[0018] The beneficial effect of the present invention is that due to the nonlinearity and instability of feeder harmonics, the present invention provides a feeder harmonic trajectory estimation method and terminal, which estimates the harmonic impedance by using the fundamental impedance to approximate the harmonic impedance, and calculates the approximate value of the state quantity of the equivalent PCC point in the feeder as the initial value of the multi-objective equation, wherein the multi-objective equation is constrained by the estimation errors of the imaginary and real parts of each harmonic of the equivalent PCC point, the estimation error of the total harmonic of the equivalent PCC point, and the total effective value error of the node to be calculated, and the distribution transformer harmonic current content rate and phase angle gradually approach the true value during the solution process, that is, in the absence of modeling analysis or high-precision measurement of the harmonic state, the approximate estimation method is used to realize the observation of the harmonic state, thereby improving the detection capability of the distribution network harmonics, and at the same time, through multiple constraints, it is possible to avoid the estimation result from deviating from the actual value, thereby improving the observation accuracy of the harmonic state. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flow chart of a feeder harmonic trajectory estimation method in an embodiment of the present invention;

[0020] Figure 2 Schematic diagram of a distribution network feeder in an embodiment of the present invention;

[0021] Figure 3Schematic diagram of a feeder harmonic trajectory estimation terminal in an embodiment of the present invention;

[0022] Description of labels:

[0023] 1. A feeder harmonic trajectory estimation terminal; 2. A memory; 3. A processor. DETAILED DESCRIPTION

[0024] In order to explain the technical content, achieved objectives and effects of the present invention in detail, the following is an explanation in conjunction with the implementation modes and the accompanying drawings.

[0025] Please refer to Figure 1 and Figure 2 , a feeder harmonic trajectory estimation method, comprising the steps of:

[0026] S1. Obtain fundamental impedance data of the feeder and estimate harmonic impedance data based on the harmonic order;

[0027] S2. Calculate the approximate value of the state quantity of the equivalent PCC point in the feeder using the harmonic impedance data;

[0028] S3. Taking the approximate value of the state quantity as the initial value, and taking the estimated error of the imaginary and real parts of each harmonic at the equivalent PCC point, the estimated error of the total harmonic at the equivalent PCC point, and the total effective value error of the node to be determined as constraints, a multi-objective function is established, and the multi-objective function is solved to obtain the distribution transformer harmonic current content rate and phase angle that are close to the true value.

[0029] It is understandable that in the distribution network, since harmonic impedance is difficult to obtain accurately, this method uses fundamental impedance to approximate harmonic impedance. The fundamental impedance data of the feeder can be obtained through the SCADA system of the power grid. The present invention provides a feeder harmonic trajectory estimation method and terminal, which uses fundamental impedance to approximate the harmonic impedance, and calculates the approximate value of the state quantity of the equivalent PCC point in the feeder as the initial value of the multi-objective equation, wherein the multi-objective equation is constrained by the estimation error of the imaginary and real parts of each harmonic of the equivalent PCC point, the estimation error of the total harmonic of the equivalent PCC point, and the total effective value error of the node to be calculated, and the distribution transformer harmonic current content rate and phase angle gradually approach the true value in the solution process, that is, in the absence of modeling analysis or high-precision measurement of harmonic state, the observation of harmonic state is realized by using the approximate estimation method, which improves the detection capability of the harmonics of the distribution network, and at the same time, through multiple constraints, it avoids the deviation of the estimation result from the actual value, and improves the observation accuracy of the harmonic state.

[0030] In the harmonic trajectory estimation method described in the present invention, the equivalent PCC point is a simplified reference for harmonic analysis. Specifically, the equivalent PCC point is regarded as the common connection point of the entire feeder outlet, which is used to simplify the harmonic transmission path of complex nodes in the distribution network. By obtaining the state quantity of the equivalent PCC point (such as the imaginary and real parts of the harmonic current), the harmonic state of different nodes in the network can be inferred. The introduction of the equivalent PCC point simplifies the analysis of the harmonic status of the entire distribution network and avoids the complexity of measuring each node separately.

[0031] In an embodiment of the present invention, step S1 specifically includes the following steps:

[0032] Obtain the fundamental impedance data of the feeder. Specifically, obtain the system topology, harmonic measurement data in the distribution network, and the fundamental impedance of the line. The formula is as follows:

[0033] z L =r L +jx L ;

[0034] In the formula, Z L is the total impedance of the line; r L is the fundamental impedance of the line; L is the fundamental reactance of the line; j is a complex unit;

[0035] The harmonic impedance data is estimated based on the harmonic order, and the formula is as follows:

[0036] z Lh =r L +jhx L ;

[0037] Where h is the harmonic order.

[0038] From the above description, it can be seen that the harmonic impedance is estimated through the relationship between the fundamental impedance and the harmonic order, which simplifies the calculation method of the harmonic impedance, reduces the dependence on harmonic measurement equipment, and reduces the implementation cost of the system.

[0039] In an embodiment of the present invention, step S2 specifically includes the steps of:

[0040] A two-port network is established using the harmonic impedance data to obtain a parameter set, and an impedance parameter matrix of a measurement vector and a state vector is constructed according to the parameter set. Based on the impedance parameter matrix, an approximate value of the state quantity of the equivalent PCC point in the feeder is obtained, and the formula is as follows:

[0041]

[0042] Where U x ,I xare the harmonic voltage vector and injected harmonic current vector of the measurement node respectively; U z ,I z are the harmonic voltage vector and injected harmonic current vector of the state node respectively;

[0043] K is the relationship between the measurement vector Z and the state vector X, characterized by an m*n-dimensional impedance parameter matrix, expressed as follows:

[0044]

[0045] In the formula, k ij A parameter set is obtained by calculating the two-port network using the harmonic impedance data.

[0046] From the above description, it can be seen that by establishing a two-port network and using the impedance parameter matrix, the relationship between the measurement vector and the state vector can be effectively described, further improving the accuracy of the approximate value of the harmonic state quantity; by expressing the relationship between measurement and state through the impedance matrix, the algorithm is applicable to complex distribution network structures, enhancing the versatility and applicability of the system.

[0047] In an embodiment of the present invention, step S3 specifically includes the following steps:

[0048] S31, using the approximate value of the state quantity as the initial value, calculate and obtain the branch harmonic current phasor measured at the equivalent PCC point, the formula is as follows:

[0049]

[0050] In the formula, is the hth branch harmonic current phasor measured at the equivalent PCC point; is the hth injected harmonic current phasor of the mth distribution transformer belonging to the feeder sub-diagram, where M represents the number of distribution transformers in the feeder diagram;

[0051] S32, converting the branch harmonic current phasor measured at the equivalent PCC point into the form of real part and imaginary part according to the phase angle of the injected harmonic current, the formula is as follows:

[0052]

[0053] In the formula, I pcc,h,re and I pcc,h,im are the real and imaginary parts of the h-th branch harmonic current measured at the equivalent PCC point; θ m,h The phase angle of the hth harmonic current injected into the mth distribution transformer in the feeder topology diagram. The phase angle has a period of 2π and a range of -π-π.

[0054] In order to study the harmonic spectrum emitted by each distribution transformer to the power grid and analyze the harmonic injection of each distribution transformer to the power grid, the harmonic current content rate is introduced, and the formula is as follows:

[0055]

[0056] In the formula, I m,l HRI is the effective value of the fundamental current of the mth distribution transformer in the feeder sub-diagram; m,h is the hth harmonic current content rate of the mth distribution transformer belonging to the feeder sub-diagram;

[0057] However, considering that the basic current monitoring of distribution transformers is usually the total effective value of current, it is also necessary to convert the fundamental current effective value to the total effective value of current, that is, calculate the fundamental current effective value in the total effective value of current, and obtain the relationship between the branch harmonic current phasor measured at the equivalent PCC point and the total effective value of current. The formula is as follows:

[0058]

[0059] In the formula, I RMS is the total effective value of current; I1 is the effective value of the fundamental wave of current; HRI h is the hth harmonic current content rate;

[0060] After substituting, we get the following formula:

[0061]

[0062] In the formula, I m,RMS is the total effective value of the current of the mth distribution transformer belonging to the feeder sub-diagram; HRI m,h is the hth harmonic current content rate of the mth distribution transformer belonging to the feeder sub-diagram;

[0063] S33. A multi-objective function is established with the estimated errors of the imaginary and real parts of each harmonic at the equivalent PCC point, the estimated error of the total harmonic at the equivalent PCC point, and the total effective value error of the node to be determined as constraints, and the multi-objective function is solved to obtain the distribution transformer harmonic current content rate and phase angle that are close to the true value.

[0064]

[0065] Where minF is the objective function; I pcc,h,rms is the hth harmonic effective value at the equivalent PCC point; I pcc,rms is the total effective value of harmonics at the equivalent PCC point; z represents the variable to be determined, Z represents the set of variables to be determined, η is the weight of f4; α and β are random numbers with a value range of 0.5-1; I m,h,f and θ m,h,f is the approximate value of the state quantity calculated in step S2; z,1rmsis the effective value of the primary current of the variable z to be determined; HRI z,h It is the harmonic current content rate of the hth order of the zth distribution transformer belonging to the feeder sub-diagram.

[0066] From the above description, it can be seen that the estimation error of the imaginary and real parts of each harmonic at the equivalent PCC point, the estimation error of the total harmonic at the equivalent PCC point, and the total effective value error of the node to be calculated are used as multi-objective functions to constrain the harmonic amplitude and phase angle of the particle within a certain range of approximate values, thereby reducing the gap between the calculated results and the actual values.

[0067] In an embodiment of the present invention, step S3 further includes:

[0068] The inertia weight, cognitive coefficient and social learning coefficient of the particle swarm algorithm are dynamically adjusted, and the objective function is optimized using the adjusted particle swarm algorithm to minimize the gap between the calculated harmonic current and phase angle and the corresponding actual value.

[0069] It is understandable that the particle swarm algorithm (Particle Swarm Algorithm, PSO) is an optimization algorithm based on swarm intelligence. Its essence is to perform random search based on group collaboration. It has the advantages of global heuristics, simple structure, mature and efficient, simple implementation, etc. It is widely used to solve problems such as constrained optimization, multi-objective optimization and dynamic optimization. However, since the traditional particle swarm algorithm is prone to fall into local optimality, the present invention improves it by dynamically adjusting the inertia weight, cognitive coefficient and social learning coefficient, so that the particles gradually reduce the learning of the local optimality and increase the learning of the global optimality, so that the particles can get rid of the interference of local extremes as much as possible, and improve the optimality of the solution. The key formula of the particle swarm algorithm is as follows:

[0070]

[0071] Where: v i (k), x i (k) represent the velocity and position of particle i at the kth iteration respectively; P ibest , g best Represent the historical optimal position of particle i and the historical optimal position of all particles respectively; r1 and r2 are random numbers between 0 and 1; n gen represents the total number of iterations; ω is the inertia weight; c1 and c2 are the cognitive coefficient and social learning coefficient respectively.

[0072] From the above description, we can see that the approximate value of the state quantity is used as the initial value of the particle swarm algorithm, and then the inertia weight, cognitive coefficient and social learning coefficient are dynamically adjusted according to the number of iterations. The linear decreasing inertia weight is used to improve the inertia weight, and the value of ω is related to the number of iterations. In the early stage of the search, ω is large, which enhances the global search ability, while in the later stage of the search, ω decreases rapidly, enhancing the local search ability to lock the optimal solution with a greater possibility. The personal cognitive coefficient and social learning coefficient adopt decreasing and increasing characteristics respectively, so that the particles gradually learn less from the local optimum and learn more from the global optimum, so that the particles can get rid of the interference of local extreme values ​​as much as possible, thereby improving the accuracy of the solution.

[0073] Please refer to Figure 3 A feeder harmonic trajectory estimation terminal 1 includes a memory 2, a processor 3, and a computer program stored in the memory 2 and executable on the processor 3. When the processor 3 executes the computer program, the steps in the feeder harmonic trajectory estimation method are completed.

[0074] The present invention provides a feeder harmonic trajectory estimation method and terminal, which are mainly used to estimate the nonlinear unstable harmonic state, and are specifically described below in conjunction with an embodiment:

[0075] Embodiment 1 of the present invention is:

[0076] A method for estimating a feeder harmonic trajectory comprises the steps of:

[0077] S1. Obtain fundamental impedance data of the feeder and estimate harmonic impedance data based on the harmonic order;

[0078] S2. Calculate the approximate value of the state quantity of the equivalent PCC point in the feeder using the harmonic impedance data;

[0079] S3. Take the approximate value of the state quantity as the initial value, and establish a multi-objective function with the estimated error of the imaginary and real parts of each harmonic at the equivalent PCC point, the estimated error of the total harmonic at the equivalent PCC point, and the total effective value error of the node to be determined as constraints. Solve the multi-objective function to obtain the distribution transformer harmonic current content and phase angle that are close to the true value.

[0080] That is, in this embodiment, the harmonic impedance is estimated by using the fundamental impedance to approximate the state quantity of the equivalent PCC point in the feeder, and the approximate value of the state quantity of the equivalent PCC point is calculated as the initial value of the multi-objective equation, wherein the multi-objective equation is constrained by the estimation errors of the imaginary and real parts of each harmonic of the equivalent PCC point, the estimation error of the total harmonic of the equivalent PCC point, and the total effective value error of the node to be calculated, and the harmonic current content rate and phase angle of the distribution transformer gradually approach the true value during the solution process, that is, in the absence of modeling analysis or high-precision measurement of the harmonic state, the approximate estimation method is used to realize the observation of the harmonic state, thereby improving the detection capability of the distribution network harmonics. At the same time, through multiple constraints, the deviation of the estimation result from the actual value is avoided, thereby improving the observation accuracy of the harmonic state.

[0081] Please refer to Figure 1 and Figure 2 , Embodiment 2 of the present invention is:

[0082] Based on the first embodiment, the method specifically includes the steps of:

[0083] S1. Obtain the system topology, harmonic measurement data in the distribution network, and line fundamental impedance. The formula is as follows:

[0084] z L =r L +jx L ;

[0085] In the formula, Z L is the total impedance of the line; r L is the fundamental impedance of the line; L is the fundamental reactance of the line; j is a complex unit;

[0086] The harmonic impedance data is estimated based on the harmonic order, and the formula is as follows:

[0087] z Lh =r L +jhx L ;

[0088] Where h is the harmonic order.

[0089] S2. Use the harmonic impedance data to establish a two-port network and obtain a parameter set. According to the parameter set, an impedance parameter matrix of the measurement vector and the state vector is constructed. Based on the impedance parameter matrix, the approximate state value of the equivalent PCC point in the feeder is obtained. The formula is as follows:

[0090]

[0091] Where U x ,I x are the harmonic voltage vector and injected harmonic current vector of the measurement node respectively; U z ,I zare the harmonic voltage vector and injected harmonic current vector of the state node respectively;

[0092] K is the relationship between the measurement vector Z and the state vector X, characterized by an m*n-dimensional impedance parameter matrix, expressed as follows:

[0093]

[0094] In the formula, k ij Parameter set calculated for building a two-port network using harmonic impedance data.

[0095] S3. Establishing the multi-objective function is as follows:

[0096] S31. Using the approximate value of the state quantity as the initial value, calculate the branch harmonic current phasor measured at the equivalent PCC point. The formula is as follows:

[0097]

[0098] In the formula, is the hth branch harmonic current phasor measured at the equivalent PCC point; is the hth injected harmonic current phasor of the mth distribution transformer belonging to the feeder sub-diagram, where M represents the number of distribution transformers in the feeder diagram;

[0099] S32. According to the phase angle of the injected harmonic current, the branch harmonic current phasor measured at the equivalent PCC point is converted into the form of real and imaginary parts. The formula is as follows:

[0100]

[0101] In the formula, I pcc,h,re and I pcc,h,im are the real and imaginary parts of the h-th branch harmonic current measured at the equivalent PCC point; θ m,h The phase angle of the hth harmonic current injected into the mth distribution transformer in the feeder topology diagram. The phase angle has a period of 2π and a range of -π-π.

[0102] In order to study the harmonic spectrum emitted by each distribution transformer to the power grid and analyze the harmonic injection of each distribution transformer to the power grid, the harmonic current content rate is introduced, and the formula is as follows:

[0103]

[0104] In the formula, I m,l HRI is the effective value of the fundamental current of the mth distribution transformer in the feeder sub-diagram; m,h is the hth harmonic current content rate of the mth distribution transformer belonging to the feeder sub-diagram;

[0105] However, considering that the basic current monitoring of distribution transformers is usually the total effective value of current, it is also necessary to convert the fundamental current effective value to the total effective value of current, that is, calculate the fundamental current effective value in the total effective value of current, and obtain the relationship between the branch harmonic current phasor measured at the equivalent PCC point and the total effective value of current. The formula is as follows:

[0106]

[0107] In the formula, I RMS is the total effective value of current; I1 is the effective value of the fundamental wave of current; HRI h is the hth harmonic current content rate;

[0108] After substituting, we get the following formula:

[0109]

[0110] In the formula, I m,RMS is the total effective value of the current of the mth distribution transformer belonging to the feeder sub-diagram; HRI m,h is the hth harmonic current content rate of the mth distribution transformer belonging to the feeder sub-diagram;

[0111] S33. A multi-objective function is established with the estimated errors of the imaginary and real parts of each harmonic at the equivalent PCC point, the estimated error of the total harmonic at the equivalent PCC point, and the total effective value error of the node to be determined as constraints. The multi-objective function is solved to obtain the distribution transformer harmonic current content and phase angle that are close to the true value.

[0112]

[0113] Where minF is the objective function; I pcc,h,rms is the hth harmonic effective value at the equivalent PCC point; I pcc,rms is the total effective value of harmonics at the equivalent PCC point; z represents the variable to be determined, Z represents the set of variables to be determined, η is the weight of f4; α and β are random numbers with a value range of 0.5-1; I m,h,f and θ m,h,f is the approximate value of the state quantity calculated in step S2; z,1rms is the effective value of the primary current of the variable z to be determined; HRI z,h It is the harmonic current content rate of the hth order of the zth distribution transformer belonging to the feeder sub-diagram.

[0114] That is, in this embodiment, the estimation error of the imaginary and real parts of each harmonic at the equivalent PCC point, the estimation error of the total harmonic at the equivalent PCC point, and the total effective value error of the node to be determined are used as multi-objective functions to constrain the harmonic amplitude and phase angle of the particle within a certain range of approximate values, thereby reducing the gap between the calculated results and the actual values.

[0115] Embodiment 3 of the present invention is:

[0116] Based on the second embodiment, step S3 further includes:

[0117] The inertia weight, cognitive coefficient and social learning coefficient of the particle swarm algorithm are dynamically adjusted, and the objective function is optimized using the adjusted particle swarm algorithm to minimize the gap between the calculated harmonic current and phase angle and the corresponding actual values.

[0118] The key formula of the particle swarm algorithm is as follows:

[0119]

[0120] Where: v i (k), x i (k) represent the velocity and position of particle i at the kth iteration respectively; P ibest , g best Represent the historical optimal position of particle i and the historical optimal position of all particles respectively; r1 and r2 are random numbers between 0 and 1; n gen represents the total number of iterations; ω is the inertia weight; c1 and c2 are the cognitive coefficient and social learning coefficient respectively.

[0121] That is, in this embodiment, the approximate value of the state quantity is used as the initial value of the particle swarm algorithm, and then the inertia weight, cognitive coefficient and social learning coefficient are dynamically adjusted according to the number of iterations. The inertia weight is improved by using a linear decreasing inertia weight, and the value of ω is related to the number of iterations. In the early stage of the search, ω is large, which enhances the global search ability, while in the later stage of the search, ω decreases rapidly, enhancing the local search ability to lock the optimal solution with a greater possibility. The personal cognitive coefficient and the social learning coefficient adopt decreasing and increasing characteristics respectively, so that the particles gradually learn less from the local optimum and learn more from the global optimum, so that the particles can get rid of the interference of the local extreme value as much as possible, thereby improving the accuracy of the solution.

[0122] Please refer to Figure 2 , Embodiment 4 of the present invention is:

[0123] A feeder harmonic trajectory estimation terminal 1 includes a memory 2, a processor 3, and a computer program stored in the memory 2 and executable on the processor 3. When the processor 3 executes the computer program, the steps in any one of the feeder harmonic trajectory estimation methods in embodiments 1 to 3 are completed.

[0124] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A feeder harmonic trajectory estimation method, characterized in that: Includes steps: S1. Obtain fundamental impedance data of the feeder and estimate harmonic impedance data based on the harmonic order; S2. Calculate the approximate value of the state quantity of the equivalent PCC point in the feeder using the harmonic impedance data; S3. Taking the approximate value of the state quantity as the initial value, and taking the estimated error of the imaginary and real parts of each harmonic at the equivalent PCC point, the estimated error of the total harmonic at the equivalent PCC point, and the total effective value error of the node to be determined as constraints, a multi-objective function is established, and the multi-objective function is solved to obtain the distribution transformer harmonic current content rate and phase angle that are close to the true value.

2. A feeder harmonic trajectory estimation method according to claim 1, characterized in that: The step S1 specifically includes the following steps: Get the fundamental impedance data of the feeder, the formula is as follows: z L =r L +jx L ; In the formula, Z L is the total impedance of the line; r L is the fundamental impedance of the line; 、x L is the fundamental reactance of the line; j is a complex unit; The harmonic impedance data is estimated based on the harmonic order, and the formula is as follows: with Lh =r L +jhx L ; Where h is the harmonic order.

3. A feeder harmonic trajectory estimation method according to claim 2, characterized in that: The step S2 specifically includes the following steps: A two-port network is established using the harmonic impedance data to obtain a parameter set, and an impedance parameter matrix of a measurement vector and a state vector is constructed according to the parameter set. Based on the impedance parameter matrix, an approximate value of the state quantity of the equivalent PCC point in the feeder is obtained, and the formula is as follows: Where U x ,I x are the harmonic voltage vector and injected harmonic current vector of the measurement node respectively; U z ,I z are the harmonic voltage vector and injected harmonic current vector of the state node respectively; K is the relationship between the measurement vector Z and the state vector X, characterized by an m*n-dimensional impedance parameter matrix, expressed as follows: In the formula, k ij A parameter set is obtained by calculating the two-port network using the harmonic impedance data.

4. A feeder harmonic trajectory estimation method according to claim 3, characterized in that: The step S3 specifically comprises the following steps: S31, using the approximate value of the state quantity as the initial value, calculate and obtain the branch harmonic current phasor measured at the equivalent PCC point, the formula is as follows: In the formula, is the hth branch harmonic current phasor measured at the equivalent PCC point; is the hth injected harmonic current phasor of the mth distribution transformer belonging to the feeder sub-diagram, where M represents the number of distribution transformers in the feeder diagram; S32, converting the branch harmonic current phasor measured at the equivalent PCC point into the form of real part and imaginary part according to the phase angle of the injected harmonic current, the formula is as follows: In the formula, I pcc,h,re and I pcc,h,im are the real and imaginary parts of the h-th branch harmonic current measured at the equivalent PCC point; θ m,h is the phase angle of the hth harmonic current injected into the mth distribution transformer in the feeder topology diagram. The phase angle has a period of 2π and is in the range of [-π,π]; Introducing the harmonic current content rate, the formula is as follows: In the formula, I m,l HRI is the effective value of the fundamental current of the mth distribution transformer in the feeder sub-diagram; m,h is the hth harmonic current content rate of the mth distribution transformer belonging to the feeder sub-diagram; Calculate the fundamental current effective value in the total effective value of the current, and obtain the relationship between the branch harmonic current phasor measured at the equivalent PCC point and the total effective value of the current. The formula is as follows: In the formula, I RMS is the total effective value of current; I1 is the effective value of the fundamental wave of current; HRI h is the hth harmonic current content rate; In the formula, I m,RMS is the total effective value of the current of the mth distribution transformer belonging to the feeder sub-diagram; HRIm, h is the hth harmonic current content rate of the mth distribution transformer belonging to the feeder sub-diagram; S33, establishing a multi-objective function with the estimated errors of the imaginary and real parts of each harmonic at the equivalent PCC point, the estimated error of the total harmonic at the equivalent PCC point, and the total effective value error of the node to be determined as constraints, and solving the multi-objective function to obtain the distribution transformer harmonic current content rate and phase angle close to the true value; Where minF is the objective function; I pcc,h,rms is the hth harmonic effective value at the equivalent PCC point; I pcc,rms is the total effective value of harmonics at the equivalent PCC point; z represents the variable to be determined, Z represents the set of variables to be determined, η is the weight of f4; α and β are random numbers with a value range of 0.5-1; I m,h,f and θ m,h,f is the approximate value of the state quantity calculated in step S2; z,1rms is the effective value of the primary current of the variable z to be determined; HRIz, h It is the harmonic current content rate of the hth order of the zth distribution transformer belonging to the feeder sub-diagram.

5. A feeder harmonic trajectory estimation method according to claim 1 or 4, characterized in that: The step S3 further comprises: The inertia weight, cognitive coefficient and social learning coefficient of the particle swarm algorithm are dynamically adjusted, and the objective function is optimized using the adjusted particle swarm algorithm to minimize the gap between the calculated harmonic current and phase angle and the corresponding actual value.

6. A feeder harmonic trajectory estimation terminal, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor completes the following steps when executing the computer program: the method is characterized in that the steps include: S1. Obtain fundamental impedance data of the feeder and estimate harmonic impedance data based on the harmonic order; S2. Calculate the approximate value of the state quantity of the equivalent PCC point in the feeder using the harmonic impedance data; S3. Taking the approximate value of the state quantity as the initial value, and taking the estimated error of the imaginary and real parts of each harmonic at the equivalent PCC point, the estimated error of the total harmonic at the equivalent PCC point, and the total effective value error of the node to be determined as constraints, a multi-objective function is established, and the multi-objective function is solved to obtain the distribution transformer harmonic current content rate and phase angle that are close to the true value.

7. A feeder harmonic trajectory estimation terminal according to claim 6, characterized in that: The step S1 specifically includes the following steps: Get the fundamental impedance data of the feeder, the formula is as follows: z L =r L +jx L ; In the formula, Z L is the total impedance of the line; r L is the fundamental impedance of the line; 、x L is the fundamental reactance of the line; j is a complex unit; The harmonic impedance data is estimated based on the harmonic order, and the formula is as follows: with Lh =r L +jhx L ; Where h is the harmonic order.

8. A feeder harmonic trajectory estimation terminal according to claim 7, characterized in that: The step S2 specifically includes the following steps: A two-port network is established using the harmonic impedance data to obtain a parameter set, and an impedance parameter matrix of a measurement vector and a state vector is constructed according to the parameter set. Based on the impedance parameter matrix, an approximate value of the state quantity of the equivalent PCC point in the feeder is obtained, and the formula is as follows: Where U x ,I x are the harmonic voltage vector and injected harmonic current vector of the measurement node respectively; U z ,I z are the harmonic voltage vector and injected harmonic current vector of the state node respectively; K is the relationship between the measurement vector Z and the state vector X, characterized by an m*n-dimensional impedance parameter matrix, expressed as follows: In the formula, k ij A parameter set is obtained by calculating the two-port network using the harmonic impedance data.

9. A feeder harmonic trajectory estimation terminal according to claim 8, characterized in that: The step S3 specifically comprises the following steps: S31, using the approximate value of the state quantity as the initial value, calculate and obtain the branch harmonic current phasor measured at the equivalent PCC point, the formula is as follows: In the formula, is the hth branch harmonic current phasor measured at the equivalent PCC point; is the hth injected harmonic current phasor of the mth distribution transformer belonging to the feeder sub-diagram, where M represents the number of distribution transformers in the feeder diagram; S32, converting the branch harmonic current phasor measured at the equivalent PCC point into the form of real part and imaginary part according to the phase angle of the injected harmonic current, the formula is as follows: In the formula, I pcc,h,re and I pcc,h,im are the real and imaginary parts of the h-th branch harmonic current measured at the equivalent PCC point; θ m,h is the phase angle of the hth harmonic current injected into the mth distribution transformer in the feeder topology diagram. The phase angle has a period of 2π and is in the range of [-π,π]; Introducing the harmonic current content rate, the formula is as follows: In the formula, I m,l HRI is the effective value of the fundamental current of the mth distribution transformer in the feeder sub-diagram; m,h is the hth harmonic current content rate of the mth distribution transformer belonging to the feeder sub-diagram; Calculate the fundamental current effective value in the total effective value of the current, and obtain the relationship between the branch harmonic current phasor measured at the equivalent PCC point and the total effective value of the current. The formula is as follows: In the formula, I RMS is the total effective value of current; I1 is the effective value of the fundamental wave of current; HRI h is the hth harmonic current content rate; In the formula, I m,RMS is the total effective value of the current of the mth distribution transformer belonging to the feeder sub-diagram; HRIm, h is the hth harmonic current content rate of the mth distribution transformer belonging to the feeder sub-diagram; S33, establishing a multi-objective function with the estimated errors of the imaginary and real parts of each harmonic at the equivalent PCC point, the estimated error of the total harmonic at the equivalent PCC point, and the total effective value error of the node to be determined as constraints, and solving the multi-objective function to obtain the distribution transformer harmonic current content rate and phase angle close to the true value; Where minF is the objective function; I pcc,h,rms is the hth harmonic effective value at the equivalent PCC point; I pcc,rms is the total effective value of harmonics at the equivalent PCC point; z represents the variable to be determined, Z represents the set of variables to be determined, η is the weight of f4; α and β are random numbers with a value range of 0.5-1; I m,h,f and θ m,h,f is the approximate value of the state quantity calculated in step S2; z,1rms is the effective value of the primary current of the variable z to be determined; HRIz, h It is the harmonic current content rate of the hth order of the zth distribution transformer belonging to the feeder sub-diagram.

10. A feeder harmonic trajectory estimation terminal according to claim 6 or 9, characterized in that: The step S3 further comprises: The inertia weight, cognitive coefficient and social learning coefficient of the particle swarm algorithm are dynamically adjusted, and the objective function is optimized using the adjusted particle swarm algorithm to minimize the gap between the calculated harmonic current and phase angle and the corresponding actual value.

Images