Power distribution network current correction method based on harmonic state

Abstract

The invention discloses a power distribution network current correction method based on a harmonic state, and belongs to the technical field of power distribution network regulation, and the method comprises the steps: S1, obtaining the historical operation data of a power distribution network, and calculating a harmonic current and a phase angle corresponding to the harmonic current according to the historical operation data; s2, calculating a harmonic state estimation value of the power distribution network based on the harmonic current and the phase angle corresponding to the harmonic current in combination with a harmonic power flow equation; s3, collecting real-time operation data of the power distribution network, and constructing a harmonic state evaluation correction equation according to the real-time operation data and the harmonic state estimation value of the power distribution network; s4, performing load flow calculation according to the harmonic state evaluation correction equation, the harmonic current and the phase angle corresponding to the harmonic current to obtain a harmonic state correction value of the power distribution network; s5, the power distribution network executes a current correction action according to the power distribution network harmonic state correction value; according to the method, the problem of large deviation between the sensed harmonic state of the power distribution network and the actual harmonic state due to the fact that multiple influence factors of harmonic waves are not considered in the prior art is solved.

Description

Technical Field

[0001] The invention relates to the technical field of distribution network regulation, and in particular to a distribution network current correction method based on harmonic states. Background Art

[0002] With the continuous increase in the number of various nonlinear loads in the distribution network, the harmonic emission level in the power supply area has also increased accordingly, resulting in large harmonic currents, which have an impact on the loss of transmission lines, power quality, the operation of safety devices, etc., and even damage to power equipment in severe cases; In order to solve the above problems, the existing technology usually adopts a harmonic state sensing technology based on the Monte Carlo method, or a harmonic state sensing technology based on the hidden Markov method, wherein the harmonic state sensing technology based on the Monte Carlo method performs multiple sampling according to the probability distribution function of the harmonic current injected into the node to obtain the node harmonic voltage probability density Distribution function, but in the actual working environment of the distribution network, the probability distribution function of the harmonic current injected by the node may be quite different from the actual situation, and the range of the probability density function is too large, which leads to a large deviation between the perceived harmonic state of the distribution network and the actual harmonic state. The harmonic state perception technology based on hidden Markov is limited by the assumption of data independence, and only considers the impact of the distribution network state on the harmonics at the current moment, without considering the joint impact of the distribution network state, parameters and external factors on the harmonics at other moments, which also leads to a large deviation between the perceived harmonic state of the distribution network and the actual harmonic state.

[0003] Chinese patent, publication number: CN115833131A, publication date: March 21, 2023, discloses a distribution network harmonic evaluation method and system based on a hidden Markov model, including: a preset hidden Markov model is used to describe the harmonic emission characteristics of typical loads selected in the distribution network within a certain time series range, and on this basis, the harmonic currents emitted by all loads in the distribution network at any time within the time series range are estimated, and then the harmonic voltages of all loads in the distribution network at any time within the time series range are calculated to achieve harmonic evaluation of the distribution network; however, the invention does not consider the joint influence of distribution network states, parameters and external factors at multiple times on harmonics, resulting in a large deviation between the perceived harmonic state of the distribution network and the actual harmonic state. Summary of the invention

[0004] The purpose of the present invention is to address the problem that the prior art does not take into account the multiple influencing factors of harmonics, resulting in a large deviation between the perceived harmonic state of the distribution network and the actual harmonic state; a distribution network current correction method based on the harmonic state is proposed, and a power flow calculation is performed according to the historical operation data of the distribution network to obtain an estimated value of the harmonic state of the distribution network, and a preliminary estimate is made of the possible harmonic state of the distribution network under the premise of the influence of multiple factors, and a harmonic state evaluation correction equation is constructed according to the estimated value of the harmonic state of the distribution network and the real-time operation data, and the harmonic state correction value of the distribution network is calculated based on the harmonic state evaluation correction equation in combination with the harmonic current, that is, the harmonic current correction value required for the current harmonic state of the distribution network, and finally, the distribution network performs a current correction action according to the harmonic current correction value, which not only accurately perceives the harmonic state of the distribution network, but also significantly improves the stability of the distribution network.

[0005] In a first aspect, a technical solution provided in an embodiment of the present invention is a method for correcting a current in a distribution network based on a harmonic state, comprising the following steps: S1. Obtain historical operation data of the distribution network, and calculate harmonic current and corresponding phase angle of harmonic current based on the historical operation data; S2, based on the harmonic current and the corresponding phase angle of the harmonic current combined with the harmonic power flow equation, calculate the estimated value of the harmonic state of the distribution network; S3, collecting real-time operation data of the distribution network, and constructing a harmonic state assessment correction equation based on the real-time operation data and the estimated value of the harmonic state of the distribution network; S4, performing power flow calculation according to the harmonic state evaluation correction equation, harmonic current and the corresponding phase angle of the harmonic current to obtain the harmonic state correction value of the distribution network; S5. The distribution network performs a current correction action according to the distribution network harmonic state correction value.

[0006] In this scheme, harmonic currents, phase angles corresponding to harmonic currents, and change characteristics of the harmonic currents and phase angles corresponding to harmonic currents are analyzed from potential characteristics of historical operation data of the distribution network, and possible harmonic states of the distribution network under multiple influencing factors are calculated based on the harmonic currents and phase angles corresponding to harmonic currents in combination with the harmonic power flow equation, i.e., estimated values ​​of harmonic states of the distribution network. Then, a harmonic state evaluation correction equation is constructed according to the estimated values ​​of the harmonic states of the distribution network and the real-time operation data of the distribution network. Then, power flow calculation is performed according to the harmonic state evaluation correction equation, harmonic currents, and phase angles corresponding to harmonic currents, to obtain harmonic current correction values ​​for the harmonic states and influencing factors of the distribution network, i.e., harmonic state correction values ​​of the distribution network, so as to achieve accurate judgment of the real-time harmonic state of the distribution network. Finally, the distribution network performs current correction action according to the harmonic state correction value of the distribution network, which not only accurately senses the harmonic state of the distribution network, but also significantly improves the stability of the distribution network.

[0007] Preferably, in S1, the specific process of calculating the harmonic current and the corresponding phase angle of the harmonic current according to the historical operation data is: S11, performing fundamental wave power flow calculation according to the power data, voltage data, and current data in the historical operation data to obtain the fundamental wave current and the phase angle corresponding to the fundamental wave current; synchronously, extracting a harmonic probability density function based on the harmonic monitoring data in the historical operation data; S12. Calculate the harmonic current and the corresponding phase angle of the harmonic current based on the fundamental current and the corresponding phase angle of the fundamental current combined with the sampling value of the harmonic probability density function.

[0008] In this scheme, based on the essential characteristics of the mutual connection between the fundamental current and the harmonic current, the accurate fundamental current and the corresponding phase angle of the fundamental current are first calculated according to the power data, voltage data, and current data in the historical operation data, and the harmonic probability density function that fully reflects the distribution characteristics of the harmonic current is extracted according to the characteristics of the harmonic monitoring data in the historical operation data. Finally, based on the sampling value of the harmonic probability density function and the fundamental current and its corresponding phase angle, accurate harmonic current and its phase angle are calculated to support the subsequent estimation of the harmonic state of the distribution network.

[0009] Preferably, in S11, the specific process of extracting the harmonic probability density function based on the harmonic monitoring data in the historical operation data is: S111. Draw a historical harmonic voltage curve and a historical harmonic current curve according to the harmonic monitoring data in the historical operation data; S112. Perform curve integration on the historical harmonic voltage curve to obtain the historical voltage distortion rate and the historical voltage phase angle; synchronously, perform curve integration on the historical harmonic current curve to obtain the historical current distortion rate and the historical current phase angle; S113. Integrate the historical voltage distortion rate, the historical voltage phase angle, the historical current distortion rate and the historical current phase angle to obtain a distortion phase angle set, and fit the distortion phase angle set based on a non-parametric kernel density algorithm to obtain a harmonic probability density function.

[0010] In this scheme, the historical harmonic voltage curve and the historical harmonic current curve are integrated to obtain the corresponding distortion rate and phase angle, deeply analyze the current power state of the distribution network, and based on the power state, the distortion rate and phase angle are automatically fitted with a non-parametric kernel density algorithm to obtain the harmonic probability density function, thereby effectively improving the fitting speed and accuracy of the harmonic probability density function.

[0011] Preferably, in S12, the calculation formula for the harmonic current and the phase angle corresponding to the harmonic current is specifically: θ h =θ hs+h(θ1-θ 1s ); In the formula, IHD hs is the hth harmonic distortion rate, is the fundamental current amplitude of the mth node, θ1 is the fundamental current phase angle, θ 1s is the initial phase angle of fundamental current, θ hs is the initial phase angle of harmonic current, is the hth harmonic current amplitude of the mth node, θ h is the phase angle of the hth harmonic current.

[0012] Preferably, in S2, the harmonic power flow equation is specifically: In the formula, is the node harmonic current phasor set, h represents the harmonic order, m represents the number of nodes, Y is the node admittance matrix, is the node harmonic voltage phasor set, is the set of harmonic current phasors between distribution network branches, is the voltage difference phasor set between adjacent nodes.

[0013] Preferably, in S3, the specific process of constructing the harmonic state assessment correction equation according to the real-time operation data and the estimated value of the harmonic state of the distribution network is: S31, subtracting the real-time operation data from the estimated value of the harmonic state of the distribution network to obtain a difference, and pluralizing the real-time operation data, the estimated value of the harmonic state of the distribution network and the difference to obtain a pre-repair phasor set; S32, constructing constraint equations and objective functions in a rectangular coordinate system based on the pre-repair phasor set; S33, sorting out the constraint equations and the objective function to obtain a harmonic state assessment correction equation.

[0014] In this scheme, the difference between the real-time operating data and the estimated value of the harmonic state of the distribution network is obtained, so that the difference between the estimated value and the real-time measured value can be obtained. At the same time, real-time monitoring of the corresponding distribution network can be realized, and a harmonic state evaluation correction equation can be constructed based on this gap and the corresponding data, thereby effectively improving the state evaluation capability of the harmonic state evaluation correction equation.

[0015] Preferably, in S33, the harmonic state assessment correction equation is specifically: Where N n is the number of nodes, Represents the a, b, and c phase lines of the distribution network. For node i Phase h harmonic voltage measurement value, The hth harmonic is from node i Relative to node k Phase branch resistance, For node k Phase h harmonic correction current, The hth harmonic is from node i Relative to node k Phase harmonic reactance, is the hth harmonic current flowing through branch ij, The hth harmonic corresponds to the kth node The contribution of phase harmonic current to branch ij current, M represents the actual value, E represents the estimated value, x represents the real part of the corresponding data, y represents the imaginary part of the corresponding data, and n represents the number of distribution network branches.

[0016] Preferably, in S4, the specific process of performing power flow calculation according to the harmonic state evaluation correction equation, the harmonic current and the phase angle corresponding to the harmonic current to obtain the harmonic state correction value of the distribution network is: S41, solving the harmonic state assessment correction equation based on the particle swarm algorithm to obtain the optimal correction value of the harmonic current; S42, calculating the harmonic correction current according to the optimal correction amount of the harmonic current, the harmonic current and the corresponding phase angle of the harmonic current; S43, calculating the harmonic state correction value of the distribution network based on the harmonic correction current combined with the harmonic power flow equation.

[0017] In this scheme, since the harmonic state assessment correction equation is usually an underdetermined equation with multiple solutions, the particle swarm algorithm is used to solve the harmonic state assessment correction equation to obtain the optimal correction amount of the harmonic current. At the same time, corresponding constraints can be added in the process of solving the problem according to the different characteristics of the corresponding distribution network to avoid the optimal correction amount of the harmonic current being too large or too small, thereby effectively improving the accuracy of the optimal correction amount of the harmonic current.

[0018] Preferably, in S41, the specific process of solving the harmonic state assessment correction equation based on the particle swarm algorithm to obtain the optimal correction amount of the harmonic current is: S411, establishing the objective function and constraint conditions of the particle swarm algorithm according to the harmonic state evaluation correction equation, and constructing a particle population according to the current data and voltage data corresponding to the harmonic state evaluation correction equation; S412, updating individual particles in the particle population based on the individual update formula of the particle swarm algorithm, and selecting high-quality individual particles according to the constraint conditions of the particle swarm algorithm; S413, evaluating the fitness of high-quality individual particles based on the fitness function constructed based on the objective function of the particle swarm algorithm; S414, judging whether the solution of the harmonic state evaluation correction equation is completed according to the preset stop condition, if so, selecting the optimal individual particle according to the fitness of the high-quality individual particles, if not, executing S412; S415. Outputting the solution of the harmonic state assessment correction equation corresponding to the optimal particle individual as the optimal correction amount of the harmonic current.

[0019] Preferably, after S4 is completed, it is determined whether the power flow calculation is completed based on the number of distribution network harmonic state correction values ​​and a preset cycle threshold value. If so, S5 is executed; if not, S1 is executed.

[0020] In this scheme, in order to avoid the distribution network harmonic state correction value being too large or too small due to accidental abnormal conditions, the corresponding cycle threshold is set according to the actual working conditions of the distribution network to calculate the distribution network harmonic state correction value multiple times, thereby effectively improving the accuracy of the distribution network harmonic state correction value.

[0021] The present invention has at least the following substantial effects: The present application analyzes the harmonic current, the corresponding phase angle of the harmonic current, and the change characteristics of the harmonic current and the corresponding phase angle of the harmonic current from the potential characteristics of the historical operation data of the distribution network, and calculates the possible harmonic state of the distribution network under multiple influencing factors based on the harmonic current and the corresponding phase angle of the harmonic current combined with the harmonic power flow equation, that is, the estimated value of the harmonic state of the distribution network, and then constructs the harmonic state evaluation correction equation according to the estimated value of the harmonic state of the distribution network and the real-time operation data of the distribution network. Since the harmonic state evaluation correction equation is usually an underdetermined equation with multiple solutions, a particle swarm algorithm is used to solve it. The harmonic state assessment correction equation is solved to obtain the harmonic current correction value for the harmonic state and influencing factors of the distribution network, that is, the harmonic state correction value of the distribution network, so as to realize accurate judgment of the real-time harmonic state of the distribution network, and also set the corresponding cycle threshold value according to the actual working condition of the distribution network to calculate the harmonic state correction value of the distribution network multiple times, so as to avoid accidental abnormal conditions causing the harmonic state correction value of the distribution network to be too large or too small. Finally, the distribution network performs a current correction action according to the harmonic state correction value of the distribution network, which not only accurately senses the harmonic state of the distribution network, but also significantly improves the stability of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Other features, objects and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are only for the purpose of illustrating preferred embodiments and are not to be considered as limiting the present invention. Also, the same reference symbols are used throughout the drawings to represent the same parts.

[0023] Figure 1 This is a flow chart of a method for correcting current in a distribution network based on harmonic state according to the present invention; Figure 2 This is a schematic diagram of the distribution network structure; Figure 3 This is a schematic diagram of the 5th harmonic power flow results; Figure 4 Correction results of 5th harmonic power flow for different measurement data. DETAILED DESCRIPTION

[0024] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific implementation method described herein is only an optimal embodiment of the present invention, which is only used to explain the present invention and does not limit the scope of protection of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0025] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the operations (or steps) as sequential processes, many of the operations (or steps) therein can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the drawings; the process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0026] Embodiment 1: like Figure 1 As shown, this embodiment provides a method for correcting current in a distribution network based on harmonic state, comprising the following steps: S1. Obtain historical operation data of the distribution network, and calculate harmonic currents and corresponding phase angles of harmonic currents based on the historical operation data.

[0027] S11, performing fundamental wave power flow calculation according to the power data, voltage data, and current data in the historical operation data to obtain the fundamental wave current and the phase angle corresponding to the fundamental wave current; Simultaneously, a harmonic probability density function is extracted based on the harmonic monitoring data in the historical operation data.

[0028] S111. Draw a historical harmonic voltage curve and a historical harmonic current curve according to the harmonic monitoring data in the historical operation data; S112, performing curve integration on the historical harmonic voltage curve to obtain a historical voltage distortion rate and a historical voltage phase angle; Synchronously, the historical harmonic current curve is subjected to curve integration to obtain the historical current distortion rate and the historical current phase angle; S113, the historical voltage distortion rate, the historical voltage phase angle, the historical current distortion rate and the historical current phase angle are integrated to obtain a distortion phase angle set, and the distortion phase angle set is fitted based on a non-parametric kernel density algorithm to obtain a harmonic probability density function.

[0029] In this embodiment, when obtaining the historical operation data of the distribution network, it is also necessary to mark the power data, voltage data, and current data corresponding to different nodes and different devices according to the topological structure of the distribution network, so as to facilitate the subsequent rapid positioning according to the corresponding relationship between the data and the nodes and devices; in addition, a corresponding monitoring device is installed at the low-voltage side outlet of the distribution transformer to collect the harmonic monitoring data in the historical operation data, and a historical harmonic voltage curve and a historical harmonic current curve are drawn according to the harmonic monitoring data. After the waveform is drawn, the Fourier method is used to perform curve integration on the waveform to obtain the corresponding distortion rate and phase angle of each harmonic of the distribution network corresponding to the node and integrate them to obtain a distortion phase angle set, and then a kernel density algorithm that does not require subjective assumptions about the harmonic probability distribution and load dependence form is used to fit the distortion phase angle set to obtain a harmonic probability density function, wherein the kernel density algorithm specifically adopts a non-parametric kernel density algorithm, and the kernel density estimation formula corresponding to the non-parametric kernel density algorithm is as follows: Where f(x) is the kernel density estimation formula, c is the bandwidth, n is the sample size, K(·) is the kernel function, x is the density point of interest, and x i is the observation point corresponding to the i-th sample point; the kernel function K(·) is specifically a Gaussian kernel function, which is specifically as follows: The bandwidth is calculated based on the Silverman rule of thumb. The bandwidth calculation formula is as follows: h=1.06*min(σ,IQR / 1.34)n -1 / 5 ; Wherein, σ is the standard deviation of the sample data, and IQR is the interquartile range of the data; when the distortion phase angle set is fitted to obtain the fitting curve, that is, the harmonic probability density function is obtained, a conventional curve sampling method, such as an equal parameter sampling method, can be used to sample the fitting curve to obtain its sampling value.

[0030] S12. Calculate the harmonic current and the corresponding phase angle of the harmonic current based on the fundamental current and the corresponding phase angle of the fundamental current combined with the sampling value of the harmonic probability density function.

[0031] In one embodiment, the calculation formula of the harmonic current and the phase angle corresponding to the harmonic current is specifically: θ h =θ hs +h(θ1-θ 1s ); In the formula, IHD hs is the hth harmonic distortion rate, is the fundamental current amplitude of the mth node, θ1 is the fundamental current phase angle, θ 1s is the initial phase angle of fundamental current, θ hs is the initial phase angle of harmonic current, is the hth harmonic current amplitude of the mth node, θ h is the phase angle of the hth harmonic current.

[0032] S2. Based on the harmonic current and the corresponding phase angle of the harmonic current combined with the harmonic power flow equation, the estimated value of the harmonic state of the distribution network is calculated.

[0033] In one embodiment, the harmonic power flow equation is specifically: In the formula, is the node harmonic current phasor set, h represents the harmonic order, m represents the number of nodes, Y is the node admittance matrix, is the node harmonic voltage phasor set, is the set of harmonic current phasors between distribution network branches, is the voltage difference phasor set between adjacent nodes.

[0034] S3. Collecting real-time operation data of the distribution network, and constructing a harmonic state assessment correction equation based on the real-time operation data and the estimated value of the harmonic state of the distribution network.

[0035] S31, subtracting the real-time operation data from the estimated value of the harmonic state of the distribution network to obtain a difference, and pluralizing the real-time operation data, the estimated value of the harmonic state of the distribution network and the difference to obtain a pre-repair phasor set; S32, constructing constraint equations and objective functions in a rectangular coordinate system based on the pre-repair phasor set; S33, sorting out the constraint equations and the objective function to obtain a harmonic state assessment correction equation.

[0036] In one embodiment, the harmonic state assessment correction equation is specifically: Where N n is the number of nodes, Represents the a, b, and c phase lines of the distribution network. For node i Phase h harmonic voltage measurement value, The hth harmonic is from node i Relative to node k Phase branch resistance, For node k Phase h harmonic correction current, The hth harmonic is from node i Relative to node k Phase harmonic reactance, is the hth harmonic current flowing through branch ij, The hth harmonic corresponds to the kth node The contribution of phase harmonic current to branch ij current, M represents the actual value, E represents the estimated value, x represents the real part of the corresponding data, y represents the imaginary part of the corresponding data, and n represents the number of distribution network branches.

[0037] In this embodiment, according to the topological structure of the distribution network, the voltage data and current data in the real-time operation data of the nodes and branches where the monitoring equipment is installed are collected and the difference is obtained by subtracting the estimated value of the harmonic state of the distribution network. The main reason for this difference is the inaccurate perception of the harmonic current. In addition, when the real-time operation data is in the form of a phasor, the difference between the real-time operation data and the estimated value of the harmonic state of the distribution network satisfies the rectangular constraint condition in the rectangular coordinate system. The rectangular constraint condition is as follows: The parameter definitions in the formula are consistent with those in the harmonic state assessment correction equation. It should be noted that the rectangular constraint condition is only applicable to data in phasor form, so the non-phasor data needs to be complexified and converted into phasor form.

[0038] When the monitoring device can only monitor node harmonic voltage or branch harmonic current, it is necessary to reconstruct the right-angle constraint condition, and the reconstructed right-angle constraint condition is as follows: In the formula, Indicates the hth harmonic node i The actual value of the phase harmonic voltage measurement amplitude, Indicates the hth harmonic branch ij Actual value of the phase harmonic current measurement amplitude.

[0039] S4. Calculate the power flow based on the harmonic state evaluation correction equation, harmonic current and the corresponding phase angle of the harmonic current to obtain the harmonic state correction value of the distribution network.

[0040] S41. Solve the harmonic state assessment correction equation based on the particle swarm algorithm to obtain the optimal correction value of the harmonic current.

[0041] S411, establishing the objective function and constraint conditions of the particle swarm algorithm according to the harmonic state evaluation correction equation, and constructing a particle population according to the current data and voltage data corresponding to the harmonic state evaluation correction equation; S412, updating individual particles in the particle population based on the individual update formula of the particle swarm algorithm, and selecting high-quality individual particles according to the constraint conditions of the particle swarm algorithm; S413, evaluating the fitness of high-quality individual particles based on the fitness function constructed based on the objective function of the particle swarm algorithm; S414, judging whether the solution of the harmonic state evaluation correction equation is completed according to the preset stop condition, if so, selecting the optimal individual particle according to the fitness of the high-quality individual particles, if not, executing S412; S415. Outputting the solution of the harmonic state assessment correction equation corresponding to the optimal particle individual as the optimal correction amount of the harmonic current.

[0042] S42, calculating a harmonic correction current according to the optimal correction amount of the harmonic current, the harmonic current and the phase angle corresponding to the harmonic current; S43. Calculate the harmonic state correction value of the distribution network based on the harmonic correction current in combination with the harmonic power flow equation.

[0043] In this embodiment, the particle swarm algorithm is used to solve the harmonic state evaluation correction equation to obtain the real part of the optimal correction value of the harmonic current With the imaginary part It is also necessary to combine the harmonic correction current formula, the harmonic current and the corresponding phase angle of the harmonic current to calculate the harmonic correction current. The harmonic correction current formula is as follows: In the formula, is the set of harmonic correction currents, is the optimal set of harmonic current correction values, It is a set of harmonic currents and corresponding phase angles of harmonic currents. After the calculation of the harmonic correction current is completed, it is necessary to perform flow calculation again based on the harmonic correction current to determine the correction values ​​corresponding to different nodes of the distribution network, and determine the input current or output current of the corresponding node based on the correction values ​​corresponding to different nodes of the distribution network to achieve control of the operating status of the distribution network.

[0044] S5. The distribution network performs a current correction action according to the distribution network harmonic state correction value.

[0045] To verify the specific effect of this embodiment, the following Figure 2The distribution network shown in the figure is verified. The distribution network is specifically an IEEE 33-node distribution system. The voltage levels of the system are divided into three levels: 35Kv, 10Kv, and 0.38Kv. Node 0 is a 35Kv high-voltage input distribution network system node. Branch 01 has a PUM harmonic monitoring device, and the branch harmonic current phasor can be obtained. Node 5 is equipped with a TTU harmonic monitoring device, and the harmonic voltage amplitude of the 5 nodes can be obtained. Assuming that the load harmonic spectrum of each node is consistent, the fitting function described in this embodiment is used. First, nodes 3, 5, 18, and 27 are selected for analysis. First, nodes 3, 5, 18, and 27 are randomly selected once to perform a deterministic harmonic flow calculation. The result is regarded as the actual harmonic state of the distribution network. In the absence of measurement data, only probabilistic harmonic flow calculation is performed, and 1×10 3 Monte Carlo simulation calculations are performed and the simulation results are statistically analyzed to obtain the following Figure 3 The fifth harmonic power flow results shown in the pink area show that without measurement data, the probabilistic harmonic power flow calculation results have high uncertainty. On this basis, the actual measurement data of the 0-1 branch harmonic current is introduced. And 1×10 3 Monte Carlo simulation is performed, and the harmonic power flow calculation result is corrected according to the method described in this embodiment. The corrected result is as follows: Figure 3 As shown in the middle blue area, it can be found that after the measured data is corrected according to the method described in this embodiment, the uncertainty of the probabilistic harmonic power flow calculation is effectively reduced, making the harmonic estimation result closer to the actual harmonic state.

[0046] In order to further verify the effectiveness of the method described in this implementation, the 5-node harmonic voltage amplitude measurement data was introduced and combined with the 0-1 branch harmonic current phasor measurement data to perform a 1×10 3 The Monte Carlo simulation is performed and the harmonic calculation results are corrected according to the method described in this embodiment to obtain the following: Figure 4 The green part shows the correction results of the 5th harmonic power flow using different measurement data. It can be seen that with the increase of measurement data, the calculation results of the probabilistic harmonic voltage can be closer to the actual harmonic state of the distribution network.

[0047] This embodiment has at least the following substantial effects: This embodiment parses the harmonic current, the corresponding phase angle of the harmonic current, and the change characteristics of the harmonic current and the corresponding phase angle of the harmonic current from the potential characteristics of the historical operation data of the distribution network, and calculates the possible harmonic state of the distribution network under multiple influencing factors based on the harmonic current and the corresponding phase angle of the harmonic current combined with the harmonic power flow equation, that is, the estimated value of the harmonic state of the distribution network, and then constructs the harmonic state evaluation correction equation according to the estimated value of the harmonic state of the distribution network and the real-time operation data of the distribution network. Since the harmonic state evaluation correction equation is usually an underdetermined equation with multiple solutions, a particle swarm algorithm is used Solving the harmonic state assessment correction equation obtains the harmonic current correction value for the harmonic state and influencing factors of the distribution network, that is, the harmonic state correction value of the distribution network, so as to accurately judge the real-time harmonic state of the distribution network, and also sets the corresponding cycle threshold value according to the actual working condition of the distribution network to calculate the harmonic state correction value of the distribution network multiple times, so as to avoid accidental abnormal conditions causing the harmonic state correction value of the distribution network to be too large or too small. Finally, the distribution network performs a current correction action according to the harmonic state correction value of the distribution network, which not only accurately senses the harmonic state of the distribution network, but also significantly improves the stability of the distribution network.

[0048] The above specific embodiments are preferred embodiments of the present invention, and are not intended to limit the specific implementation scope of the present invention. The scope of the present invention includes but is not limited to the present specific embodiments. All equivalent changes made in accordance with the shape, structure, and method of the present invention are within the protection scope of the present invention.

Claims

1. A method for current correction in a distribution network based on harmonic state, characterized in that: The method comprises the following steps: S1. Obtain historical operation data of the distribution network, and calculate harmonic current and corresponding phase angle of harmonic current based on the historical operation data; S2, based on the harmonic current and the corresponding phase angle of the harmonic current combined with the harmonic power flow equation, calculate the estimated value of the harmonic state of the distribution network; S3, collecting real-time operation data of the distribution network, and constructing a harmonic state assessment correction equation based on the real-time operation data and the estimated value of the harmonic state of the distribution network; S4, performing power flow calculation according to the harmonic state evaluation correction equation, harmonic current and the corresponding phase angle of the harmonic current to obtain the harmonic state correction value of the distribution network; S5. The distribution network performs a current correction action according to the distribution network harmonic state correction value.

2. A method for correcting current in a distribution network based on harmonic state according to claim 1, characterized in that: In S1, the specific process of calculating the harmonic current and the corresponding phase angle of the harmonic current according to the historical operation data is as follows: S11, performing fundamental wave power flow calculation according to the power data, voltage data, and current data in the historical operation data to obtain the fundamental wave current and the phase angle corresponding to the fundamental wave current; synchronously, extracting a harmonic probability density function based on the harmonic monitoring data in the historical operation data; S12. Calculate the harmonic current and the corresponding phase angle of the harmonic current based on the fundamental current and the corresponding phase angle of the fundamental current combined with the sampling value of the harmonic probability density function.

3. A method for correcting current in a distribution network based on harmonic state according to claim 2, characterized in that: In S11, the specific process of extracting the harmonic probability density function based on the harmonic monitoring data in the historical operation data is: S111. Draw a historical harmonic voltage curve and a historical harmonic current curve according to the harmonic monitoring data in the historical operation data; S112, performing curve integration on the historical harmonic voltage curve to obtain a historical voltage distortion rate and a historical voltage phase angle; Synchronously, performing curve integration change on the historical harmonic current curve to obtain a historical current distortion rate and a historical current phase angle; S113, integrating the historical voltage distortion rate, historical voltage phase angle, historical current distortion rate and historical current phase angle to obtain a distortion phase angle set, and fitting the distortion phase angle set based on a non-parametric kernel density algorithm to obtain a harmonic probability density function.

4. A method for correcting current in a distribution network based on harmonic state according to claim 2, characterized in that: In S12, the calculation formula of the harmonic current and the phase angle corresponding to the harmonic current is specifically: i h =θ hs +h(θ1-θ 1s ); In the formula, IHD hs is the hth harmonic distortion rate, is the fundamental current amplitude of the mth node, θ1 is the fundamental current phase angle, θ 1s is the initial phase angle of fundamental current, θ hs is the initial phase angle of harmonic current, is the hth harmonic current amplitude of the mth node, θ h is the phase angle of the hth harmonic current.

5. A method for correcting current in a distribution network based on harmonic state according to claim 1, characterized in that: In S2, the harmonic power flow equation is specifically: In the formula, is the node harmonic current phasor set, h represents the harmonic order, m represents the number of nodes, Y is the node admittance matrix, is the node harmonic voltage phasor set, is the harmonic current phasor set between distribution network branches, is the voltage difference phasor set between adjacent nodes.

6. A method for correcting current in a distribution network based on harmonic state according to claim 1, characterized in that: In S3, the specific process of constructing the harmonic state assessment correction equation according to the real-time operation data and the estimated value of the harmonic state of the distribution network is: S31, subtracting the real-time operation data from the estimated value of the harmonic state of the distribution network to obtain a difference, and pluralizing the real-time operation data, the estimated value of the harmonic state of the distribution network and the difference to obtain a pre-repair phasor set; S32, constructing constraint equations and objective functions in a rectangular coordinate system based on the pre-repair phasor set; S33, sorting out the constraint equations and the objective function to obtain a harmonic state assessment correction equation.

7. A method for correcting current in a distribution network based on harmonic state according to claim 6, characterized in that: In S33, the harmonic state assessment correction equation is specifically: Where N n is the number of nodes, Represents the a, b, and c phase lines of the distribution network. For node i Phase h harmonic voltage measurement value, The hth harmonic is from node i Relative to node k Phase branch resistance, For node k Phase h harmonic correction current, The hth harmonic is from node i Relative to node k Phase harmonic reactance, is the hth harmonic current flowing through branch ij, The hth harmonic corresponds to the kth node The contribution of phase harmonic current to branch ij current, M represents the actual value, E represents the estimated value, x represents the real part of the corresponding data, y represents the imaginary part of the corresponding data, and n represents the number of distribution network branches.

8. A method for correcting current in a distribution network based on harmonic state according to claim 1, characterized in that: In S4, the specific process of calculating the power flow according to the harmonic state evaluation correction equation, the harmonic current and the phase angle corresponding to the harmonic current to obtain the harmonic state correction value of the distribution network is: S41, solving the harmonic state assessment correction equation based on the particle swarm algorithm to obtain the optimal correction value of the harmonic current; S42, calculating a harmonic correction current according to the optimal correction amount of the harmonic current, the harmonic current and the phase angle corresponding to the harmonic current; S43. Calculate the harmonic state correction value of the distribution network based on the harmonic correction current in combination with the harmonic power flow equation.

9. A method for correcting current in a distribution network based on harmonic state according to claim 8, characterized in that: In S41, the specific process of solving the harmonic state assessment correction equation based on the particle swarm algorithm to obtain the optimal correction value of the harmonic current is: S411, establishing the objective function and constraint conditions of the particle swarm algorithm according to the harmonic state evaluation correction equation, and constructing a particle population according to the current data and voltage data corresponding to the harmonic state evaluation correction equation; S412, updating individual particles in the particle population based on the individual update formula of the particle swarm algorithm, and selecting high-quality individual particles according to the constraint conditions of the particle swarm algorithm; S413, evaluating the fitness of high-quality individual particles based on a fitness function constructed based on the particle swarm algorithm objective function; S414, judging whether the solution of the harmonic state evaluation correction equation is completed according to the preset stop condition, if so, selecting the optimal particle individual according to the fitness of the high-quality particle individual, if not, executing S412; S415. Outputting the solution of the harmonic state assessment correction equation corresponding to the optimal particle individual as the optimal correction amount of the harmonic current.

10. A method for correcting current in a distribution network based on harmonic state according to claim 1, characterized in that: After the step S4 is completed, it is determined whether the power flow calculation is completed based on the number of distribution network harmonic state correction values ​​and the preset cycle threshold value. If so, S5 is executed; if not, S1 is executed.

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