CN113030644B - Power distribution network fault positioning method based on multi-data source information fusion - Google Patents
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Abstract
A fault positioning method for a power distribution network with multiple data source information fusion belongs to the technical field of power system analysis, operation and control. The invention aims to provide a power distribution network fault positioning method for information fusion of multiple data sources, which is used for carrying out information fusion on electric quantity and switching value to obtain an accurate fault positioning result. Firstly, carrying out first signal reconstruction by utilizing the electric quantity measured by a limited number of PMU devices and combining a compressed sensing algorithm to obtain a rough fault range, and respectively establishing a Bayesian network for each element in the fault range to obtain the switching value fault degree; and then, carrying out secondary signal reconstruction by utilizing the electric quantity obtained by the limited PMU nodes and the first-order adjacent nodes to obtain the electric quantity fault degree. The two failure degrees are two evidence bodies, and the two evidence bodies are fused by using DS evidence theory to obtain a positioning result. The control of the invention not only fully exploits the adjusting capability of each device, but also avoids the transmission of excessive reactive power, which leads to unnecessary network loss.
Description
Technical Field
The invention belongs to the technical field of analysis, operation and control of an electric power system.
Background
The importance of electric power in daily life is higher and higher, and the power supply reliability is one of the important indexes of the assessment distribution network, and when the power grid breaks down, the production life of people can be influenced, so that the power grid fault location needs to be fast and accurate. Because of a series of reasons such as urban planning, environmental protection, fields and the like, the application of cable feeder lines is more and more complex, the capacitance current to the ground of a neutral point ungrounded system can be greatly increased when a ground fault occurs, the arc current cannot be extinguished by itself, the generated overvoltage is high, and meanwhile, the internal overvoltage is high, so that equipment is damaged. The small-resistance grounding system can quickly and effectively cut off faults, has low overvoltage level, eliminates resonance overvoltage, can use cables and electrical equipment with low insulation level, and is convenient to operate and maintain. Therefore, the distribution network generally starts to adopt a mode that a neutral point is grounded through a small resistor.
The switching value is action information of relay protection, and the existing positioning method using the switching value mainly uses an expert system, a neural network, a Petri network and the like, but is easily affected by protection, misoperation rejection of a circuit breaker and the like, and is difficult to quickly obtain an accurate positioning result.
Disclosure of Invention
The invention aims to provide a power distribution network fault positioning method for information fusion of multiple data sources, which is used for carrying out information fusion on electric quantity and switching value to obtain an accurate fault positioning result.
The method comprises the following steps:
s1, when electrical parameters are established, multi-node distribution is utilized to establish an electrical node equation, and according to kirchhoff voltage law and electrical characteristics, a power grid comprising N bus nodes can establish the following node voltage equation:
collecting positive sequence voltage change value DeltaV before and after fault + Node positive sequence impedance matrixThe positive sequence voltage component and the three-phase voltage are related as follows:
wherein V is i + Refer to the positive sequence voltage component, V i a Refers to the a-phase voltage at node i; when a certain point fails, the injection voltage of the certain point is changed greatly compared with other nodes, impedance parameters in a power grid topological structure are correspondingly changed, the current change value of the certain point is calculated to be nonzero, and the injection current change of other nodes is changed to be zero;
ΔV i + ＝V i +(q) -V i +(h) ，/>i=1, 2Λn, where V i +(q) Refers to the positive sequence component of the voltage before failure, V i +(h) Indicates the positive sequence component of the voltage after the fault, +.>Fault reconstruction current is indicated;
since the voltage, impedance and current are complex in the power system, equation (1) refines as follows:
wherein R is e Subscript represents real part, I m Subscripts represent imaginary parts; the complex number is directly used for solving the problem that the required time is long and the solving effect is poor, and the error can be generated when the phase angle difference is calculated by the phase angle data measured by the PMU;
s2, if absolute values can be taken from two sides of the formula (4) for re-solving, the requirement that complex calculation and measurement information containing phase information are required to be completely synchronized is effectively avoided, the positioning speed and accuracy of a fault area are greatly improved, the absolute values are taken, namely, voltage and impedance are taken, the formula (4) is still established, the vector solved at the moment is the amplitude of positive sequence fault current, the required information is contained, the influence of a phase angle on calculation is eliminated, the calculated amount is small, the error is small, accurate reconstruction can be carried out only by taking the amplitude of the voltage and the impedance, the complex calculation and the measurement information cannot be arranged at all nodes, the complex calculation and the measurement information are configured at M nodes, and M < < N > is simplified as the PMU:
s3, a bus provided with the PMU device is called a source bus, a bus directly connected with the source bus is called a first-order bus of the source bus, a second-order bus adjacent to the first-order bus is called the source bus, at a bus node i provided with the PMU, not only the voltage, the current value and the phase of injection of all lines connected with the node can be obtained, but also the injection voltage value of a first-order adjacent bus j can be obtained through calculation, so that after related parameters are measured through PMU equipment, the injection voltage at the first-order adjacent bus is:
V j ＝cosh(γ ij l ij )·V i -Z ij ·sinh(γ ij l ij )·I i (6)
wherein V is i And I i Is the voltage and current injected into node i, V, measured by a PMU deployed at node i j Is the injection voltage value at the first-order adjacent bus node of node i. l (L) ij Is the length of the transmission line between node i and node j, γ ij Called propagation constant andZ ij is transimpedance and->Wherein Z is in the above two formulas ij And Y ij Impedance and admittance per unit length of the transmission line, respectively;
s4, assuming that N nodes are shared in a certain power grid, arranging PMU devices on the M nodes in total, when a short circuit fault occurs at a certain position of the power grid, calculating positive sequence voltage sag values of M buses according to injection voltages of the M nodes before and after the fault occurs, which are measured by PMU devices, and obtaining positive sequence self-impedance matrix and transimpedance matrix at M PMU configuration nodes according to topological structure parametersThe first signal reconstruction equation is as follows:
wherein,after the signals are reconstructed, the area range surrounded by the node with the maximum reconstruction amplitude and the adjacent buses of the first and second steps is the fault range;
s5, respectively solving injection voltages before and after faults of H first-order adjacent bus nodes of the PMU in the non-fault range according to a formula (6), obtaining positive sequence voltage sag values of the H adjacent buses, and then carrying out M positive sequence voltage drops at the configuration nodes of the M PMUsAdding to obtain M+H positive sequence voltage sag values +.>Obtaining positive sequence self-impedance and transimpedance values of H adjacent joints according to topological structure parameters, and positive sequence self-impedance and transimpedance matrixes at the previous M PMU configuration nodes>Adding to obtain a new positive sequence impedance matrix +.>The second reconstruction equation is updated as follows:
because the voltage amplitude variation and the impedance matrix in the formula (8) are absolute values, the amplitude of the reconstruction element does not represent the voltage current amplitude variation at the node;
s6, establishing a Bayesian network for the elements in the fault range according to the switching value information acquired by the SCADA, and synthesizing expert experience and historical data to obtain fault probability of each elementA rate; aiming at the switching value information in the power grid fault positioning, the Bayesian network is utilized to calculate and obtain the fault probability of each element to be p respectively 1 、p 2 、…、p n Processing the fault degree of the switching value of the ith element by the formula (9) to obtain the fault degree of the switching value of the ith element as follows:
in which a is s <1, representing the credibility of a positioning result based on the switching value, and taking a s ＝0.8；
S7, aiming at electrical quantity information in power grid fault positioning, calculating to obtain signal reconstruction amplitude values of all nodes respectively as q by using a compressed sensing algorithm 1 、q 2 、...、q n The electrical quantity failure degree of the i-th element obtained by processing the element by the formula (10) is as follows:
in which a is e <1, the reliability based on the electric quantity positioning result is higher than the reliability based on the switching value positioning result, and a is taken e ＝0.9；
And S8, when the DS evidence theory is used for positioning faults of the power distribution network, the switching value fault degree obtained by the relay protection system and the Bayesian network and the electric quantity fault degree obtained by the PMU device and the compressed sensing algorithm are evidence bodies in the theory. And fusing the two evidence body data by using a multisensor fusion algorithm based on DS evidence theory.
According to the method, the influence of active fluctuation of the output of the photovoltaic power station on the voltage of the grid-connected point is considered, a certain reactive power is needed to support the grid stably, and especially in the periods of high output of the photovoltaic power station and load peaks, the reactive power demand is higher. The system can support the grid voltage by adjusting the reactive output of the photovoltaic inverter, the reactive compensation device and the form of a transformer tap, wherein the voltage level of a node can be improved by adjusting the tap, but reactive power cannot be generated, and the higher the voltage level adjusted by the method, the larger the reactive power shortage. Therefore, the device with reactive power regulation capability in the research area is used for carrying out coordinated control to maintain the voltage stability of the grid-connected point, so that the control not only fully explores the regulation capability of each device, but also avoids excessive reactive power transmission, thereby causing unnecessary grid loss.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a diagram of the processing mode of the switching value of the present invention;
FIG. 3 is L 19-20 A bayesian network model graph of (a);
FIG. 4 is a graph of the result of a first signal reconstruction for a single-phase ground short;
FIG. 5 is a schematic illustration of a single-phase ground short fault region;
FIG. 6 is a single-phase ground short B 6 Bayesian network topology structure diagram;
fig. 7 is a graph of the result of a single-phase ground short second signal reconstruction.
Fig. 8 is a graph of the result of the first signal reconstruction of the interphase short.
FIG. 9 is a schematic illustration of interphase short circuit fault region coverage;
fig. 10 is a graph of the result of the second signal reconstruction of the interphase short circuit.
Detailed Description
The method comprises the following steps:
s1, when electrical parameters are established, multi-node distribution is utilized to establish an electrical node equation, and according to kirchhoff voltage law and electrical characteristics, a power grid comprising N bus nodes can establish the following node voltage equation:
collecting positive sequence voltage change value DeltaV before and after fault + Node positive sequence impedance matrixPositive sequence voltage divisionThe amount versus three-phase voltage relationship is as follows:
wherein V is i + Refer to the positive sequence voltage component, V i a Refers to the a-phase voltage at node i; when a certain point fails, the injection voltage of the certain point is changed greatly compared with other nodes, impedance parameters in a power grid topological structure are correspondingly changed, the current change value of the certain point is calculated to be nonzero, and the injection current change of other nodes is changed to be zero;
ΔV i + ＝V i +(q) -V i +(h) ，/>i=1, 2Λn, where V i +(q) Refers to the positive sequence component of the voltage before failure, V i +(h) Indicates the positive sequence component of the voltage after the fault, +.>Fault reconstruction current is indicated;
since the voltage, impedance and current are complex in the power system, equation (1) refines as follows:
wherein R is e Subscript represents real part, I m Subscripts represent imaginary parts; the time required for solving the complex number is long and the solving effect is poor, and the error can be generated when the phase angle difference is calculated by the phase angle data measured by the PMUAnd (3) difference.
S2, if absolute values can be taken from two sides of the formula (4) for re-solving, the requirement that complex calculation and measurement information containing phase information are required to be completely synchronized is effectively avoided, the positioning speed and accuracy of a fault area are greatly improved, the absolute values are taken, namely, voltage and impedance are taken, the formula (4) is still established, the vector solved at the moment is the amplitude of positive sequence fault current, the required information is contained, the influence of a phase angle on calculation is eliminated, the calculated amount is small, the error is small, accurate reconstruction can be carried out only by taking the amplitude of the voltage and the impedance, the complex calculation and the measurement information cannot be arranged at all nodes, the complex calculation and the measurement information are configured at M nodes, and M < < N > is simplified as the PMU:
s3, a bus provided with the PMU device is called a source bus, a bus directly connected with the source bus is called a first-order bus of the source bus, a second-order bus adjacent to the first-order bus is called the source bus, at a bus node i provided with the PMU, not only the voltage, the current value and the phase of injection of all lines connected with the node can be obtained, but also the injection voltage value of a first-order adjacent bus j can be obtained through calculation, so that after related parameters are measured through PMU equipment, the injection voltage at the first-order adjacent bus is:
V j ＝cosh(γ ij l ij )·V i -Z ij ·sinh(γ ij l ij )·I i (6)
wherein V is i And I i Is the voltage and current injected into node i, V, measured by a PMU deployed at node i j Is the injection voltage value at the first-order adjacent bus node of node i; l (L) ij Is the length of the transmission line between node i and node j, γ ij Called propagation constant andZ ij is transimpedance and->Wherein Z is in the above two formulas ij And Y ij The impedance and admittance per unit length of the transmission line, respectively.
S4, assuming that N nodes are shared in a certain power grid, arranging PMU devices on the M nodes in total, when a short circuit fault occurs at a certain position of the power grid, calculating positive sequence voltage sag values of M buses according to injection voltages of the M nodes before and after the fault occurs, which are measured by PMU devices, and obtaining positive sequence self-impedance matrix and transimpedance matrix at M PMU configuration nodes according to topological structure parametersThe first signal reconstruction equation is as follows:
wherein,is a sensing matrix; after the signal is reconstructed, the area range surrounded by the node with the largest reconstruction amplitude and the first-order and second-order adjacent buses is the fault range.
S5, respectively solving injection voltages before and after faults of H first-order adjacent bus nodes of the PMU in the non-fault range according to a formula (6), obtaining positive sequence voltage sag values of the H adjacent buses, and then carrying out M positive sequence voltage drops at the configuration nodes of the M PMUsAdding to obtain M+H positive sequence voltage sag values +.>Obtaining positive sequence self-impedance and transimpedance values of H adjacent joints according to topological structure parameters, and positive sequence self-impedance and transimpedance matrixes at the previous M PMU configuration nodes>Adding to obtain a new positive sequence impedance matrix +.>The second reconstruction equation is updated as follows:
because the voltage amplitude variation and the impedance matrix in the formula (8) take absolute values, the amplitude of the reconstruction element does not represent the voltage current amplitude variation at the node.
S6, establishing a Bayesian network for the elements in the fault range according to the switching value information acquired by the SCADA, and synthesizing expert experience and historical data to obtain fault probability of each element; aiming at the switching value information in the power grid fault positioning, the Bayesian network is utilized to calculate and obtain the fault probability of each element to be p respectively 1 、p 2 、…、p n Processing the fault degree of the switching value of the ith element by the formula (9) to obtain the fault degree of the switching value of the ith element as follows:
in which a is s <1, representing the credibility of a positioning result based on the switching value, and taking a s ＝0.8。
S7, aiming at electrical quantity information in power grid fault positioning, calculating to obtain signal reconstruction amplitude values of all nodes respectively as q by using a compressed sensing algorithm 1 、q 2 、...、q n The electrical quantity failure degree of the i-th element obtained by processing the element by the formula (10) is as follows:
in which a is e <1, the reliability of the positioning result based on the electric quantity is higher than that of the positioning junction based on the switching valueConfidence of fruit, take a e ＝0.9。
And S8, when the DS evidence theory is used for positioning faults of the power distribution network, the switching value fault degree obtained by the relay protection system and the Bayesian network and the electric quantity fault degree obtained by the PMU device and the compressed sensing algorithm are evidence bodies in the theory. And fusing the two evidence body data by using a multisensor fusion algorithm based on DS evidence theory.
The present invention will be described in detail below
The invention aims to design a power grid fault positioning method based on multi-data source information fusion, which is used for carrying out information fusion on electric quantity and switching value to obtain an accurate fault positioning result.
And (3) measuring the electrical quantity change condition of the relevant node when the power grid fails through a limited number of PMU devices, extracting failure characteristics by using a compressed sensing algorithm, and obtaining a rough failure range after signal reconstruction. Then, according to the switching value information acquired by the SCADA system, combining with a Bayesian network to obtain switching value fault degree; and meanwhile, calculating to obtain electrical quantity information of adjacent nodes of the PMU device, and carrying out second signal reconstruction to obtain the electrical quantity fault degree. And finally, fusing the two fault degrees by utilizing DS evidence theory to find out a fault element. The method analyzes multiple information sources and obtains a correct positioning result from the fusion of uncertain fault information. The principle of power grid fault location based on information fusion is shown in fig. 1.
(1) And acquiring a fault range. And acquiring electrical quantity information by utilizing the PMU device, and carrying out first signal reconstruction by combining with a compressed sensing algorithm to obtain a rough fault range.
The invention uses a reconstruction algorithm to reconstruct the power system fault signal measured by PMU equipment, thereby achieving the purpose of fault location. The power grid branches are numerous and are distributed in a radial manner, when the electric parameters are established, the electric node equation is established by utilizing multi-node distribution, and according to kirchhoff voltage law and electric characteristics, the power grid comprising N bus nodes can establish the following node voltage equation:
wherein R is e Subscript represents real part, I m The subscript represents the imaginary part. The complex number is directly used for solving the problem that the time is long and the solving effect is poor, and errors can be generated when the phase angle difference is calculated by the phase angle data measured by the PMU.
If the absolute values can be taken from two sides of the formula (4) to solve, the requirement that complex calculation and measurement information containing phase information are required to be completely synchronized is effectively avoided, the positioning speed and accuracy of a fault area are greatly improved, the absolute values are taken, namely the voltage and the impedance take the amplitude values, the formula (4) is still established, the vector solved at the moment is the amplitude value of positive sequence fault current, the required information is contained, the influence of the phase angle on the calculation is eliminated, the calculated amount is small, the error is small, accurate reconstruction can be carried out only by taking the amplitude values of the voltage and the impedance, PMU cannot be arranged at all nodes, the PMU is configured at M nodes, and M < < N, so the method is simplified as follows:
the bus provided with the PMU device is called a source bus, the bus directly connected with the source bus is called a first-order bus of the source bus, the second-order bus adjacent to the first-order bus is called the source bus, at a bus node i provided with the PMU, the voltage, the current value and the phase of the injection of all lines connected with the node can be obtained, and the injection voltage value of a first-order adjacent bus j can be obtained through calculation, so that after related parameters are measured through PMU equipment, the injection voltage at the first-order adjacent bus is:
V j ＝cosh(γ ij l ij )·V i -Z ij ·sinh(γ ij l ij )·I i (6)
wherein V is i And I i Is the voltage and current injected into node i, V, measured by a PMU deployed at node i j Is the injection voltage value at the first-order adjacent bus node of node i. l (L) ij Is the length of the transmission line between node i and node j, γ ij Called propagation constant andZ ij is transimpedance and->Wherein Z is in the above two formulas ij And Y ij The impedance and admittance per unit length of the transmission line, respectively.
Assuming that N nodes are shared in a certain power grid, arranging PMU devices on the M nodes, when a short-circuit fault occurs at a certain position of the power grid, calculating positive sequence voltage sag values of M buses according to injection voltages of the M nodes before and after the fault occurs, which are measured by PMU devices, and obtaining positive sequence self-impedance matrix and transimpedance matrix at the M PMU configuration nodes according to topological structure parametersThe first signal reconstruction equation is as follows:
wherein,is a sensing matrix. After the signal is reconstructed, the area range surrounded by the node with the largest reconstruction amplitude and the first-order and second-order adjacent buses is the fault range.
(2) And analyzing the switching value information. And establishing a Bayesian network for the elements in the fault range according to the switching value information acquired by the SCADA, and synthesizing expert experience and historical data to obtain the fault probability of each element.
The invention takes the local power relay protection system shown in fig. 2 as an example to describe the processing mode of the switching value in the proposed method, and reference sign B in the figure 1 Represents a No. 1 node bus, CB 19-20 Representing a circuit breaker between node 19 and node 20 near one end of node 19,L 1-2 representing the line between node 1 and node 2, other numbers being so pushed. The elements in the local system comprise in particular lines L 1-2 5 lines, bus B 2 6 buses, circuit breaker CB 2-3 And 10 circuit breakers.
According to the structure of the local system of the power grid and the relay protection principle thereof, a corresponding Bayesian network can be established for each element in the system. Assume element L 19-20 The element L can be constructed according to the related relay protection action principle when faults occur 19-20 A fault localization bayesian network topology of (c), a topology representation is shown in fig. 3. Connection arcs in a Bayesian network represent the action logic of protection and circuit breakers after a fault has occurred, e.g. line L 19-20 Short-circuit fault occurs, the first action is that the left main protection L 19-20 Lm such that circuit breaker CB 19-20 Tripping; if the main protection at the left end fails, the left end is close to the backup protection L 19- 20 Lp is operated to cause circuit breaker CB 19-20 Tripping; if CB 19-20 Refusing action, line L 2-19 Far left backup protection L 2-19 Ls act to cause circuit breaker CB to 2-19 Tripping. According to this logic can be connected into L 19-20 -L 19-20 Lm(L 19-20 Lp)-CB 19-20 -L 2-19 Ls-CB 2-19 The relationship of other connection arcs can be analogically known.
The accurate assignment of the Bayesian network is the key for obtaining the fault positioning result, and the prior probability of the element fault and the rejection and misoperation probability of the protection (breaker) are obtained according to the equipment reliability data and the historical operation data. And combining the Bayesian theorem to obtain the fault probability of each element.
(3) And analyzing the electrical quantity information. And carrying out secondary signal reconstruction to obtain the fault probability of each node.
According to formula (6), respectively solving the injection voltages before and after the faults of H first-order adjacent bus nodes of the PMU in the non-fault range to obtain positive sequence voltage sag values of the H adjacent buses, and then carrying out M positive sequence voltage drops on the positive sequence voltage sag values and M PMU configuration nodesAdding to obtain M+H positive sequence voltage sag values +.>Obtaining positive sequence self-impedance and transimpedance values of H adjacent joints according to topological structure parameters, and positive sequence self-impedance and transimpedance matrixes at the previous M PMU configuration nodes>Adding to obtain a new positive sequence impedance matrix +.>The second reconstruction equation is updated as follows:
wherein,is a sensing matrix. Because the voltage amplitude variation and the impedance matrix in the formula (8) take absolute values, the amplitude of the reconstruction element does not represent the voltage current amplitude variation at the node.
(4) And further processing various fault characterizations to form an evidence body, namely the switching value fault degree and the electrical quantity fault degree.
Aiming at the switching value information in the power grid fault positioning, the Bayesian network is utilized to calculate and obtain the fault probability of each element to be p respectively 1 、p 2 、…、p n The switching value failure degree of the i-th element obtained by processing the value of the switching value failure degree is as follows:
in which a is s <1, a is taken to represent the credibility based on the switching value positioning result s ＝0.8。
Aiming at electrical quantity information in power grid fault positioning, a compressed sensing algorithm is utilized to calculate and obtain signal reconstruction amplitude values of all nodes to be q respectively 1 、q 2 、…、q n The electrical quantity failure degree of the i-th element obtained by processing the element by the formula (10) is as follows:
in which a is e <1, the reliability of the positioning result based on the electric quantity is higher than that of the positioning result based on the switching value, a e ＝0.9。
(5) And carrying out information fusion based on DS evidence theory.
When DS evidence theory is applied to power grid fault location, switching value fault degree obtained by a relay protection system and a Bayesian network and electric quantity fault degree obtained by a PMU device and a compressed sensing algorithm are evidence bodies in the theory.
(6) And diagnosing the fusion result according to a preset threshold to obtain a final result.
The decision method is based on basic probability assignment: the probability assignment values for the three states of each element are determined by:
in the formula (11), G s (A maxi ) Expressed as the maximum value of the basic assignment probability, G s (A maxj ) Representing the basic assignment probability sub-maximum. The formula indicates that the basic assignment probability determined by the decision should be larger than epsilon 1 The method comprises the steps of carrying out a first treatment on the surface of the The basic assignment probability determined and other basic assignment probabilities are larger than epsilon 2 . Epsilon in 1 ，ε 2 For the preset threshold, the values are respectively 0.6 and 0.1, and the probability distribution value of a certain element in the recognition frame for a certain state satisfies the formula (11), and the element is judged to be in the state.
Building a simulation model, and verifying a control effect:
according to the invention, the validity of the proposed method is verified through an IEEE33 node system, in order to analyze whether the method can effectively and accurately perform fault location through the system, system construction is performed in PSCAD power system simulation software, and single-phase grounding short circuits and inter-phase short circuits are respectively arranged at a bus and a line for analysis.
(1) Single phase grounding short circuit
The fault settings were as follows: bus B 6 Single-phase earth short-circuit fault occurs, and circuit breaker CB connected to bus bar 6-5 Refusing action and circuit breaker CB 6-26 False alarm of action information, line L 5-6 Bus B 5 Side and line L 6-26 Bus B 26 The side near backup protection starts. The protection and breaker action events collected when a fault occurred are shown in table 1. In this case, a 33-node system is used, the reference node is removed, the signal dimension N is 32, the number of non-zero elements is generally 2, and in order to satisfy the above condition, the number of measurement points M should be greater than or equal to 6. PMU devices are configured at six nodes 8, 13, 16, 21, 24, 31 in the system for data collection and extraction of positive sequence voltage components. And calculating the voltage amplitude change before and after the fault, and carrying out first signal reconstruction by utilizing a compressed sensing technology in combination with node impedance. The reconstruction results are shown in fig. 4, where the x-axis represents node number and the y-axis represents reconstruction element amplitude. As can be seen from fig. 4, the fault range is a region range surrounded by the first-order and second-order adjacent buses of 5 nodes, as shown in fig. 5. The bus 6 with the fault is contained therein, and the validity of the fault area determination is verified.
TABLE 1
According to the method of the invention, a respective Bayesian network is established for all elements within the determined fault range. The bayesian network topology of bus 6 is shown in fig. 6. And (3) based on the equipment reliability data and the historical operation data, obtaining the prior probability of element faults and the protection (circuit breaker) refusal and misoperation probability, and assigning the prior probability of each node in the Bayesian network. And then obtaining the fault probability of each element according to the prior probability of the element node and the conditional probability of the relay protection node, and obtaining the switching value fault degree of each element after the fault probability is processed by the formula (9) as shown in the table 2.
TABLE 2
And (3) calculating the voltage of the first-order adjacent bus node of the source bus of the non-fault area by using PMU collecting information of the non-fault area, recording the calculated voltage, reconstructing a second signal as shown in fig. 7, and determining the degree of electric quantity faults. The node 31 in the fault area has a reconstructed signal amplitude, which belongs to errors. And (3) taking the amplitude of the reconstruction signal of each bus in the fault area, wherein the larger the amplitude is, the larger the fault probability is, if the two bus nodes are adjacent, the fault probability of the line between the two nodes is obtained based on the average peak value, and the electrical quantity fault degree of each element is obtained through the processing of the formula (10).
Fusion results were obtained using a multisensor data fusion algorithm, as shown in table 3. Based on the preset threshold and the information fusion result, the failure element can be determined as B by using the formula (25) 6 Namely, the No. 6 bus fails, and the decision result is correct. If the positioning is performed based on the switching value information only, the CB 6-5 Refusing movement and CB 6-26 False alarm of action information, element B 6 And B is connected with 26 、L 6-26 The probability of failure of element L is very similar 5-4 、L 2-4 Is incorrect; if the positioning is performed only according to the electric quantity, B in the reconstructed signal 6 And L 5-6 The reconstruction amplitude of the (a) is not different, and the fault range cannot be further narrowed; after switching value and electric value positioning results are converted into respective fault degrees and fused by DS evidence theory,the decision yields the correct result, verifying the feasibility of the method presented herein.
TABLE 3 Table 3
(2) Interphase short circuit
The fault settings were as follows: line L 19-20 Interphase short-circuit fault occurs at the position and circuit breaker CB 19-20 Refusing action, line L 2-19 Bus B 2 The side remote backup protection starts. When a fault occurs, protection and breaker action information is shown in table 4. Positive sequence voltages of 6 PMU device configuration points are collected, amplitude changes before and after faults are calculated, node impedance is combined, first signal reconstruction is conducted through a compressed sensing technology, data statistics is conducted, and a reconstruction result is shown in fig. 8. As can be seen from the reconstruction result of FIG. 8, the fault range is the area range surrounded by the first and second adjacent buses of the No. 19 node, as shown in FIG. 9, the fault line L is set 19-20 And the validity of the fault area determination is verified.
TABLE 4 Table 4
A respective bayesian network is established for all elements within the determined fault range. Wherein the line L 19-20 The bayesian network topology of (2) is shown in fig. 3. And according to the equipment reliability data and the historical operation data, the prior probability of element faults and the protection (circuit breaker) refusal and misoperation probability are obtained, and the prior probability of each node in the Bayesian network is assigned. And then the fault probability of each element is obtained according to the prior probability of the element node and the conditional probability of the relay protection node, and the switching value fault degree of each element is obtained after the fault probability is processed by the formula (23) and is shown in the table 5.
TABLE 5
And (3) calculating the voltage of a source bus and a first-order adjacent bus node of the non-fault area by using PMU collecting information of the non-fault area, recording the calculated voltage, and then carrying out second signal reconstruction to determine the degree of electric quantity faults, as shown in fig. 10. And (4) obtaining the reconstructed signal amplitude of each bus in the fault area, and obtaining the electrical quantity fault degree of each element through the processing of the formula (10), wherein the electrical quantity fault degree is shown in table 6.
TABLE 6
Fusion results were obtained using a multisensor data fusion algorithm, as shown in table 7. Epsilon 1 ，ε 2 The values are respectively 0.6 and 0.1 for the preset threshold, and the fault element can be determined to be L according to the preset threshold and the information fusion result by utilizing the formula (11) 19-20 The decision result is correct. If the positioning is performed based on the switching value information only, the CB 19-20 Refusing movement, element L 2-19 And L is equal to 19-20 The fault probability of (1) is almost the same, element L 2-19 Is incorrect; if the positioning is performed only according to the electric quantity, B in the reconstructed signal 19 、B 20 L and L 19-20 The reconstructed magnitudes of (a) are very similar, the fault range cannot be further narrowed; after switching value and electric value positioning results are converted into respective fault degrees and fused by DS evidence theory, a correct result is decided, and feasibility of the method is verified.
TABLE 7
The small-resistance grounding system can quickly and effectively cut off faults, has low overvoltage level, eliminates resonance overvoltage, can use cables and electrical equipment with low insulation level, and is convenient to operate and maintain. Therefore, the distribution network generally starts to adopt a mode that a neutral point is grounded through a small resistor. The common relay protection configuration based on the small-resistance grounding distribution network generally adopts two-section current protection as main protection and backup protection of interphase faults, and adopts two-section zero-sequence current protection as main protection and backup protection of grounding faults. According to the switching value information acquired by SCADA, namely protection action information, a Bayesian network is established for the elements in the fault range, and the prior probability of element faults and the rejection and misoperation probability of protection (circuit breaker) are obtained according to the equipment reliability data and the historical operation data as the basis. And finally, combining the Bayesian theorem to obtain the fault probability of each element.
Claims (1)
1. A power distribution network fault positioning method based on multi-data source information fusion is characterized by comprising the following steps of: the method comprises the following steps:
s1, when electrical parameters are established, multi-node distribution is utilized to establish an electrical node equation, and according to kirchhoff voltage law and electrical characteristics, a power grid comprising N bus nodes can establish the following node voltage equation:
collecting positive sequence voltage change value DeltaV before and after fault + Node positive sequence impedance matrixThe positive sequence voltage component and the three-phase voltage are related as follows:
wherein V is i + Refer to the positive sequence voltage component, V i a Refers to the a-phase voltage at node i; in the event of a failure at a point,compared with other nodes, the injection voltage of the point can be greatly changed, impedance parameters in the power grid topological structure can be correspondingly changed, the current change value of the point is calculated to be nonzero, and the injection current changes of other nodes are changed to be zero;
wherein V is i +(q) Refers to the positive sequence component of the voltage before failure, V i +(h) Refers to the positive sequence component of voltage after failure, I i + Fault reconstruction current is indicated;
since the voltage, impedance and current are complex in the power system, equation (1) refines as follows:
wherein R is e Subscript represents real part, I m Subscripts represent imaginary parts; the complex number is directly used for solving the problem that the required time is long and the solving effect is poor, and the error can be generated when the phase angle difference is calculated by the phase angle data measured by the PMU;
s2, if absolute values can be taken from two sides of the formula (4) for re-solving, the requirement that complex calculation and measurement information containing phase information are required to be completely synchronized is effectively avoided, the positioning speed and accuracy of a fault area are greatly improved, the absolute values are taken, namely, voltage and impedance are taken, the formula (4) is still established, the vector solved at the moment is the amplitude of positive sequence fault current, the required information is contained, the influence of a phase angle on calculation is eliminated, the calculated amount is small, the error is small, accurate reconstruction can be carried out only by taking the amplitude of the voltage and the impedance, the complex calculation and the measurement information cannot be arranged at all nodes, the complex calculation and the measurement information are configured at M nodes, and M < < N > is simplified as the PMU:
s3, a bus provided with the PMU device is called a source bus, a bus directly connected with the source bus is called a first-order bus of the source bus, a second-order bus adjacent to the first-order bus is called the source bus, at a bus node i provided with the PMU, not only the voltage, the current value and the phase of injection of all lines connected with the node can be obtained, but also the injection voltage value of a first-order adjacent bus j can be obtained through calculation, so that after related parameters are measured through PMU equipment, the injection voltage at the first-order adjacent bus is:
V j ＝cosh(γ ij l ij )·V i -Z ij ·sinh(γ ij l ij )·I i (6)
wherein V is i And I i Is the voltage and current injected into node i, V, measured by a PMU deployed at node i j Is the injection voltage value at the first-order adjacent bus node of node i; l (L) ij Is the length of the transmission line between node i and node j, γ ij Called propagation constant andZ ij is transimpedance and->Wherein Z is in the above two formulas ij And Y ij Impedance and admittance per unit length of the transmission line, respectively;
s4, assuming that N nodes are shared in a certain power grid, arranging PMU devices on the M nodes in total, when a short circuit fault occurs at a certain position of the power grid, calculating positive sequence voltage sag values of M buses according to injection voltages of the M nodes before and after the fault occurs, which are measured by PMU devices, and obtaining positive sequence self-impedance matrix and transimpedance matrix at M PMU configuration nodes according to topological structure parametersThe first signal reconstruction equation is as follows:
wherein,is a sensing matrix; after the signal is reconstructed, the area range surrounded by the node with the maximum reconstruction amplitude and the first-order and second-order adjacent buses is the fault range;
s5, respectively solving injection voltages before and after faults of H first-order adjacent bus nodes of the PMU in the non-fault range according to a formula (6), obtaining positive sequence voltage sag values of the H adjacent buses, and then carrying out M positive sequence voltage drops at the configuration nodes of the M PMUsAdding to obtain M+H positive sequence voltage sag values +.>Obtaining positive sequence self-impedance and transimpedance values of H adjacent joints according to topological structure parameters, and positive sequence self-impedance and transimpedance matrixes at the previous M PMU configuration nodes>Adding to obtain a new positive sequence impedance matrix +.>The second reconstruction equation is updated as follows:
because the voltage amplitude variation and the impedance matrix in the formula (8) are absolute values, the amplitude of the reconstruction element does not represent the voltage current amplitude variation at the node;
s6, establishing a Bayesian network for the elements in the fault range according to the switching value information acquired by the SCADAThe expert experience and the historical data are synthesized to obtain the fault probability of each element; aiming at the switching value information in the power grid fault positioning, the Bayesian network is utilized to calculate and obtain the fault probability of each element to be p respectively 1 、p 2 、…、p n Processing the fault degree of the switching value of the ith element by the formula (9) to obtain the fault degree of the switching value of the ith element as follows:
in which a is s <1, representing the credibility of a positioning result based on the switching value, and taking a s ＝0.8；
S7, aiming at electrical quantity information in power grid fault positioning, calculating to obtain signal reconstruction amplitude values of all nodes respectively as q by using a compressed sensing algorithm 1 、q 2 、...、q n The electrical quantity failure degree of the i-th element obtained by processing the element by the formula (10) is as follows:
in which a is e <1, the reliability based on the electric quantity positioning result is higher than the reliability based on the switching value positioning result, and a is taken e ＝0.9；
And S8, when the DS evidence theory is used for power distribution network fault location, the switching value fault degree obtained by the relay protection system and the Bayesian network and the electric quantity fault degree obtained by the PMU device and the compressed sensing algorithm are evidence bodies in the theory, and the two evidence body data are fused by utilizing a multisensor fusion algorithm based on the DS evidence theory.
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