Novel power distribution system voltage frequency static stability margin evaluation method and system

Abstract

The invention discloses a novel power distribution system voltage frequency static stability margin evaluation method and system, and the method comprises the steps: calculating an improved voltage frequency static stability index which reflects the static stability of a system through points on a voltage and frequency two-dimensional plane; respectively taking the maximized voltage stability margin and the minimized frequency stability margin, the maximized voltage stability margin and the maximized frequency stability margin, the maximized frequency stability margin and the minimized voltage stability margin, and the maximized frequency stability margin and the maximized voltage stability margin as targets; constructing a novel voltage frequency static stability margin evaluation model of the power distribution system; solving the evaluation model to obtain a voltage frequency two-dimensional stability margin plane describing the static stability of the system; and calculating to obtain a voltage frequency stability margin evaluation result of the current system. According to the method, the static stability margin evaluation level of the power distribution network is expanded from a single voltage dimension to a voltage frequency two-dimensional plane, and the robustness and accuracy of an evaluation result are comprehensively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system optimization control, and in particular to a novel voltage and frequency static stability margin evaluation method and system for a power distribution system. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] The new distribution system has various elements of "source, grid, load and storage", and can achieve off-grid self-sustaining operation under certain control methods, greatly improving the power grid's ability to guarantee power supply to the distribution area under extreme conditions. However, after being separated from the main grid, the new distribution system faces a completely new operating scenario. Due to the complete loss of short-circuit capacity and rotational inertia support from the main grid, the voltage and frequency stability characteristics of the new distribution system have undergone essential changes, and the dominant factors and assumptions on which the traditional methods rely are difficult to establish. Therefore, it is of great practical significance to study the voltage and frequency stability margin assessment of the new distribution system.

[0004] The existing stability margin assessment methods generally establish frequency and voltage stability margin indicators from the perspective of active and reactive power decoupling. However, there are a large number of power electronic devices in the new distribution system, and the control method based on dq decoupling makes active and reactive power have an intrinsic connection. Therefore, the applicable conditions of the existing indicators are difficult to meet, resulting in the difficulty in accurately calculating the static stability margin of the new distribution system. Summary of the invention

[0005] In order to solve the above problems, the present invention proposes a new method and system for evaluating the static stability margin of voltage and frequency of a new distribution system, and constructs a voltage and frequency static stability margin index system for the static stability margin evaluation problem under extreme operating conditions (such as isolated island self-sustaining operation) of the new distribution system, so as to achieve efficient and accurate evaluation of the static stability margin under different operating conditions of the new distribution system.

[0006] In some embodiments, the following technical solutions are adopted:

[0007] A new method for evaluating the voltage-frequency static stability margin of a power distribution system includes:

[0008] The grid topology, line impedance and node electrical quantity information are obtained as input data, and a static network model of a new distribution system is established. The static network model is corrected according to the system operation status data under uncertain conditions to obtain a corrected static network model.

[0009] Based on the modified static network model, the improved voltage and frequency static stability index is calculated;

[0010] Based on the improved voltage-frequency static stability index, a new distribution system voltage-frequency static stability margin assessment model is constructed with the goals of maximizing voltage stability margin and minimizing frequency stability margin, maximizing voltage stability margin and maximizing frequency stability margin, maximizing frequency stability margin and minimizing voltage stability margin, and maximizing frequency stability margin and maximizing voltage stability margin.

[0011] The evaluation model is solved, and a voltage-frequency two-dimensional stability margin plane describing the static stability of the system is obtained according to the solution result; the Euclidean distance between the voltage frequency point of each node and the boundary curve of the two-dimensional stability margin plane is calculated, and the minimum value of the Euclidean distance is taken as the voltage-frequency stability margin evaluation result of the current system.

[0012] As an optional solution, according to the system operation status data under uncertain conditions, the active power and reactive power injected into the nodes of the static network model are corrected, specifically:

[0013]

[0014] Among them, J, M, N, L are Jacobian matrix block matrices, G f is the response coefficient matrix of active power of power electronic equipment to frequency, G V is the response coefficient matrix of reactive power of power electronic equipment to voltage, K f and K V is the Kalman gain matrix, δP and δQ are the residual terms considering the uncertainty of distributed generation output, which are assumed to conform to the normal distribution; Δf and ΔV are the node frequency deviation and voltage deviation, respectively; ΔP and ΔQ are the correction terms of active power and reactive power injected into the node; P and Q are the corrected active power and reactive power injected into the node; θ and V are the phase and amplitude of the node voltage, respectively, and H, E, O, D are the coefficient matrices of the power flow equation.

[0015] As an optional solution, based on the modified static network model, the improved voltage-frequency static stability index is calculated as follows:

[0016]

[0017] Where Δf i is the frequency offset of the power node i relative to the reference frequency. If the node i is in the meshing control mode, the node frequency takes the frequency value corresponding to the virtual speed. If the node i is in the following meshing control mode, the node frequency takes the frequency value output by the phase-locked loop. ΔV i is the voltage offset at power node i relative to the reference voltage, G i f and G i Vare the response coefficients of the active power injected into node i to the frequency and the reactive power injected into node i to the voltage, which are described in the form of transfer function; L j is the L index of node j, Y ij is the mutual admittance between node i and node j, Y jj is the self-admittance of node j, X ij is the mutual impedance between node i and node j, V j is the voltage at node j, α G A collection of power nodes.

[0018] As an optional solution, it also includes: determining the response coefficient G of the active power injected into node i to the frequency based on the node type and the control strategy i f And the response coefficient G of the reactive power injected into node i to the voltage i V , so that the calculation process takes into account the influence of active and reactive control links, and improves the accuracy of the evaluation results.

[0019] Determine the response factor G i f and G i V The specific method is:

[0020] ① For grid-type power sources, describe them as balancing nodes or PV nodes, and establish the node voltage relationship and output relationship as follows:

[0021] V i =m i k i,da V i,dc (0 <m<1);

[0022]

[0023] Where m represents the duty cycle, k i,da K is the ratio of the maximum modulated AC voltage to the DC voltage, i,ctrl is the control parameter array element, s is the Laplace operator, l is the order, inertia dynamics is ignored under static conditions, and only the coefficient term corresponding to l = 0 can be taken; Δf i is the frequency offset at power node i relative to the reference frequency, V i is the voltage at power node i, P i The active power injected into power node i; V i,dc is the DC voltage at power node i, P i,set is the active power reference value of power node i;

[0024] At this time, the response coefficient Response coefficient G iV =0;

[0025] ②For the grid-following power source, it is described as a PQ node, and the active and reactive output relationship is established as follows:

[0026]

[0027] Among them, F dz Indicates high / low voltage crossing control dead zone, P i The active power injected into power node i, Q i The reactive power injected into power node i;

[0028] At this time, the response coefficient Response Factor

[0029] ③ For SVG, it is described as a PV node, and the node active power and node voltage are as follows:

[0030] V i =V i,set +k i,ctrl ΔQ i ;

[0031] P i =0;

[0032] At this time, the response coefficient G i f =0, response coefficient G i V =1 / k i,ctrl ;

[0033] ④For controllable loads, they are described as PQ nodes, and active power and reactive power are expressed in piecewise function form:

[0034] P j =F j,Pf (Δf j )·P j,set ;

[0035] Q j =F j,QV (ΔV j )·Q j,set ;

[0036] Among them, P j,set and Q j,set are active power and reactive power reference values, F j,Pf and F j,QV They represent the piecewise functions of frequency deviation and voltage deviation respectively, which are determined by the load response strategy of the node;

[0037] At this time, the response coefficient Gi f =(1-F j,Pf (Δf j )) / Δf j , response coefficient G i V =(1-F j,QV (ΔV j )) / ΔV j ;

[0038] ⑤ For energy storage, it is divided into grid-building energy storage and grid-following energy storage according to the control method. In the discharge mode, the expression of grid-building energy storage is consistent with that of grid-building power supply, and the expression of grid-following energy storage is consistent with that of grid-following power supply; in the charging mode, grid-building energy storage is expressed by PV nodes, and grid-following energy storage is expressed by PQ nodes;

[0039] ⑥ For V2G electric vehicles, the same expression as grid-connected energy storage is used;

[0040] ⑦For other passive nodes, the transfer function correction coefficient term G i f and G i V Both are 0.

[0041] As an optional solution, it also includes: constructing a Kalman filter to characterize the power output data, obtaining the upper and lower boundaries of the distributed power node electrical quantities δP, δQ according to the interval range of the historical data, and discretizing the power output probability distribution data using an interval linear interpolation method to obtain an output interval model;

[0042] Kalman filtering is performed on the output range models of different power sources in the new distribution system to obtain the correction terms of active power and reactive power injected into the node, and then the voltage and frequency static stability indicators are recalculated and improved through the time-step rolling optimization method.

[0043] As an optional solution, a new distribution system voltage-frequency static stability margin assessment model is constructed, specifically:

[0044]

[0045] Where Δf i is the frequency offset at power node i relative to the reference frequency, ΔV j is the offset of the voltage at the load node j relative to the reference voltage; To improve the voltage frequency static stability index; α G is the power node set, α L is the set of load nodes.

[0046] As an optional solution, the voltage-frequency static stability margin assessment model of the new distribution system is solved, which specifically includes two stages: the upper cycle and the lower cycle. The lower cycle is used to calculate the static stability margin of each distribution area at the current time step, and the upper cycle considers the system-level control operation instructions to update the operating status data of each distribution area;

[0047] Among them, the lower-level loop takes the boundary power of each distribution area calculated by the upper-level loop as input, traverses each node in the distribution area, calculates the improved voltage-frequency static stability index of the node, and inputs the index result into the new distribution system voltage-frequency static stability margin assessment model. When the calculation meets the constraints and can converge, the calculation result is output and enters the upper-level loop of the next time step. When the calculation does not converge, the node data is corrected and the calculation is iterated again until the convergence conditions are met. The upper-level loop takes the assessment result of the lower-level loop as input, records the assessment result of each time step, and updates the boundary variables according to the control operation data, and passes it to the lower-level model to start the cyclic calculation of the next time step.

[0048] In other embodiments, the following technical solutions are adopted:

[0049] A new distribution system voltage and frequency static stability margin evaluation system, including:

[0050] The static network model building module is used to obtain the grid topology, line impedance and node electrical quantity information as input data, establish a new type of distribution system static network model, and modify the static network model according to the system operation status data under uncertain conditions to obtain a modified static network model;

[0051] A static stability index calculation module is used to calculate the improved voltage and frequency static stability index based on the modified static network model;

[0052] The static stability margin assessment module is used to construct a new distribution system voltage and frequency static stability margin assessment model based on the improved voltage and frequency static stability index, with the goals of maximizing the voltage stability margin and minimizing the frequency stability margin, maximizing the voltage stability margin and maximizing the frequency stability margin, maximizing the frequency stability margin and minimizing the voltage stability margin, and maximizing the frequency stability margin and maximizing the voltage stability margin; solve the assessment model, and obtain a voltage and frequency two-dimensional stability margin plane that describes the static stability of the system according to the solution result; calculate the Euclidean distance between the voltage and frequency point of each node and the boundary curve of the two-dimensional stability margin plane, and take the minimum value of the Euclidean distance as the voltage and frequency stability margin assessment result of the current system.

[0053] In other embodiments, the following technical solutions are adopted:

[0054] A computer-readable storage medium stores a plurality of instructions, wherein the instructions are suitable for being loaded by a processor of a terminal device and executing the above-mentioned novel distribution system voltage-frequency static stability margin assessment method.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] (1) The present invention aims at the problem of evaluating the static stability margin under the conditions of uncertain operating state and source-grid-load-storage coupling of the new distribution system, and provides an improved voltage-frequency static stability index and stability margin evaluation model. A new distribution system parameter estimation and static stability margin evaluation model under the conditions of uncertain operating state and missing network data is established, and the static stability margin evaluation level of the distribution network is expanded from a single voltage dimension to a two-dimensional voltage-frequency plane, which comprehensively improves the robustness and accuracy of the evaluation results. The present invention adopts rolling execution in the form of scheduled tasks or periodic tasks, which can improve the online application performance of the system.

[0057] (2) Based on the node type and control strategy, the present invention corrects the calculation relationship between node power and voltage frequency. For power supply side resources, power supply nodes with flexible adjustment capabilities are extracted. According to the control strategy of power supply participating in frequency and voltage regulation, a linearized transfer function describing the relationship between power supply output and frequency and voltage is established, and the general transfer function coefficient term of the improved voltage and frequency index is replaced. For load side resources, load nodes with demand response capabilities are extracted. According to the mapping relationship between load power and frequency and voltage, the load node transfer function coefficient term is determined and linearized, and the calculation formula of the improved voltage and frequency static stability index is corrected. For energy storage resources, distributed energy storage, independent energy storage stations, electric vehicle V2G charging stations and other energy storage type nodes are extracted. According to battery capacity, state of charge, power flow, frequency and voltage response strategy, the relationship between energy storage nodes and system frequency and voltage is determined and characterized by a linearized transfer function, and the voltage and frequency stability index calculation formula of relevant key nodes is corrected to improve the calculation accuracy and avoid non-convergence of the calculation process.

[0058] Other features and advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a diagram of the structure and boundary variables of a new power distribution system in an embodiment of the present invention;

[0060] Figure 2 This is a flow chart of a novel method for evaluating voltage-frequency static stability margin of a power distribution system in an embodiment of the present invention;

[0061] Figure 3 This is a diagram of an algorithm for solving a voltage-frequency static stability margin assessment model for a novel power distribution system in an embodiment of the present invention. DETAILED DESCRIPTION

[0062] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in the present invention have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0063] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0064] Embodiment 1

[0065] In one or more embodiments, a novel method for evaluating the static stability of voltage and frequency in a power distribution system is disclosed. The novel power distribution system structure and boundary variables are as follows: Figure 1 As shown. The new distribution system refers to a distribution system that adds interactive elements such as distributed power sources (such as wind power, photovoltaics), controllable loads, and energy storage on the basis of the traditional distribution system. Consistent with the existing dispatching control logic, the new distribution system is divided into two layers, the lower layer is each 10kV distribution area, and the upper layer is the overall distribution system composed of all distribution areas. The boundary variables S of each area in the upper and lower layers are Ui and S Di The exchange power given for the control center and each distribution area respectively.

[0066] This embodiment constructs an improved voltage-frequency static stability index, considers the voltage-frequency response strategy of resources such as power supply, energy storage, and load, determines the index coefficient term, and calculates the static stability margin in the voltage-frequency two-dimensional plane. Considering the uncertainty of the power supply operation point and the inaccuracy of the distribution network parameters, state estimation and parameter update are performed based on linear interpolation point estimation and linear regression methods, and the model robustness and accuracy are improved in a rolling optimization manner.

[0067] The specific process of the method in this embodiment is as follows Figure 2 As shown, the following steps are included:

[0068] Step 1: Obtain basic data such as grid topology, line impedance and node electrical quantity as input data. The new distribution system covers relevant data of nodes such as distributed power sources, controllable loads, and energy storage. On the basis of fully considering the flexible adjustment resource characteristics of the new distribution system such as distributed power sources, energy storage, and controllable loads, a static network model of the new distribution system is established.

[0069] Step 2: Extract the system operating status under uncertain conditions, establish the electrical quantity phasors, block admittance and block impedance matrices of various nodes such as power nodes, load nodes, energy storage nodes, and modify the network model according to the operating status data.

[0070] The revised static network model of the new distribution system is as follows:

[0071]

[0072] Among them, J, M, N, L are Jacobian matrix block matrices, which are composed of block admittance and block impedance matrices; G f is the response coefficient matrix of active power of power electronic equipment to frequency, G V is the response coefficient matrix of reactive power of power electronic equipment to voltage, K f and K V is the Kalman gain matrix, δP and δQ are the residual terms considering the uncertainty of distributed generation output, which are assumed to conform to the normal distribution; Δf and ΔV are the node frequency deviation and voltage deviation respectively;

[0073] P and Q are the active power and reactive power of each node respectively; ΔP and ΔQ are the correction terms of active power and reactive power injected into the node; θ and V are the phase and amplitude of the node voltage, and H, E, O, and D are the coefficient matrices of the power flow equation.

[0074] By using the revised new distribution system static network model and through power flow calculation, the node frequency deviation Δf, voltage deviation ΔV, node injected active power correction term ΔP and node injected reactive power correction term ΔQ can be output respectively.

[0075] Step 3: Based on the node frequency deviation Δf and voltage deviation ΔV output by the modified new distribution system static network model, the improved voltage-frequency static stability index is calculated. Compared with the conventional voltage stability index, the improved index is a two-dimensional index, which reflects the static stability of the system through points on the two-dimensional plane of voltage and frequency. The specific calculation formula is as follows:

[0076]

[0077] Where Δf i is the frequency offset of the power node i relative to the reference frequency. If the node i is in the meshing control mode, the node frequency takes the frequency value corresponding to the virtual speed. If the node i is in the following meshing control mode, the node frequency takes the frequency value output by the phase-locked loop. ΔV i is the voltage offset at power node i relative to the reference voltage, G i f and G i Vare the response coefficients of the active power injected into node i to the frequency and the response coefficients of the reactive power injected into node i to the voltage, which are described in the form of transfer functions. j is the L index of node j, Y ij is the mutual admittance between node i and node j, Y jj is the self-admittance of node j, X ij is the mutual impedance between node i and node j, V j is the voltage at node j, α G A collection of power nodes.

[0078] Step 4: Establish a new distribution system state estimation and parameter update model, consider the voltage-frequency response strategy of power sources, energy storage, loads and other resources, determine the response coefficient terms and calculate the static stability margin in the voltage-frequency two-dimensional plane.

[0079] Specifically, based on the node type and control strategy, the response coefficient G is determined f and G V , so that the calculation process takes into account the influence of active and reactive control links, and improves the accuracy of the evaluation results.

[0080] Node voltage frequency response coefficient G f and G V The specific method for determining is as follows:

[0081] (1) For grid-connected power sources, they are described as balancing nodes or PV nodes. The node voltage relationship is established by considering the duty cycle and maximum current limit. At the same time, the output relationship is established by considering the system frequency establishment method.

[0082] V i =m i k i,da V i,dc (0 <m<1)

[0083] P i =P i,set +K i,ctrl (l) s l Δf i

[0084] Where m represents the duty cycle, k i,da K is the ratio of the maximum modulated AC voltage to the DC voltage, i,ctrl is the control parameter array element, s is the Laplace operator, l is the order, inertia dynamics is ignored under static conditions, and only the coefficient term corresponding to l = 0 can be taken; Δf i is the frequency offset at power node i relative to the reference frequency, V i is the voltage at power node i, P i The active power injected into power node i; Vi,dc is the DC voltage at power node i, P i,set is the active power reference value of power node i;

[0085] At this time, the response coefficient Response coefficient G i V =0.

[0086] (2) For grid-following power sources, they are described as PQ nodes, and the active and reactive output relationships are established based on the node voltage and frequency control method.

[0087]

[0088] Among them, F dz Indicates high / low voltage crossing control dead zone, P i The active power injected into power node i, Q i The reactive power injected into power node i; K i,ctrl For control parameter array elements, the superscript f refers to frequency, and the superscript v refers to voltage.

[0089] At this time, the response coefficient Response Factor

[0090] (3) For SVG, it is described as a PV node, the node active power is 0, and the node voltage is determined by the control strategy.

[0091] V i =V i,set +k i,ctrl ΔQ i

[0092] P i =0

[0093] At this time, the response coefficient G i f =0, response coefficient G i V =1 / k i,ctrl .

[0094] (4) For controllable loads, they are described as PQ nodes, and the active power and reactive power are expressed in piecewise function form.

[0095] P j =F j,Pf (Δf j )·P j,set

[0096] Q j =F j,QV (ΔV j )·Qj,set

[0097] Among them, P j,set and Q j,set are active power and reactive power reference values, F j,Pf and F j,QV They represent the piecewise functions of frequency deviation and voltage deviation respectively, which are determined by the load response strategy of the node;

[0098] At this time, the response coefficient G i f =(1-F j,Pf (Δf j )) / Δf j , response coefficient G i V =(1-F j,QV (ΔV j )) / ΔV j .

[0099] (5) Energy storage is divided into grid-connected energy storage and grid-following energy storage according to the control mode. In the discharge mode, the expression of grid-connected energy storage is consistent with that of grid-connected power source, and the expression of grid-following energy storage is consistent with that of grid-following power source. In the charging mode, grid-connected energy storage is expressed as PV nodes, and grid-following energy storage is expressed as PQ nodes.

[0100] (6) For V2G electric vehicles, the same mathematical model as that of grid-connected energy storage is adopted according to its control strategy.

[0101] (7) For other passive nodes, the transfer function correction coefficient term is 0.

[0102] In addition, since the output data of distributed power sources is uncertain, which will affect the accuracy of the evaluation results, the system state estimation and parameter update are performed based on the operating data.

[0103] Specifically, a Kalman filter is constructed to characterize the power output data. The upper and lower boundaries of the residual δP and δQ of the distributed power node electrical quantity are obtained according to the interval range of historical data. The power output probability distribution data is discretized using the interval linear interpolation method to obtain the output interval model. Kalman filtering is performed on the output interval model of distributed photovoltaic, distributed wind power and other power sources in the new distribution system, and the robustness of the model is improved through time-step rolling optimization.

[0104] Assume ΔS = [ΔP, ΔQ] T , δS=[δP,δQ] and the input noise v all conform to the normal distribution:

[0105] δS~N(0,W),v~N(0,V); wherein X, W and V are covariance variables, the Kalman filter of this embodiment is defined by the following five formulas:

[0106]

[0107] Among them, K m is the Kalman gain, and the caret superscript indicates an estimated value.

[0108] By filtering through the above-mentioned Kalman filter, the updated values ​​of ΔP and ΔQ at the next moment are obtained, so as to update the active power and reactive power of the static network model of the new distribution system, and then continuously optimize the improved voltage and frequency static stability index.

[0109] Step 5: Establish a voltage-frequency static stability margin assessment model for the new distribution system.

[0110] Based on the improved voltage-frequency static stability index, combined with the operation mode, system state estimation and node power transfer function correction term, the system operation state range is obtained according to the power flow results. Within the operation state range, according to the state estimation of the new distribution system considering the uncertainty of power supply, an equation constraint set based on the power flow relationship is established, including:

[0111] S i * =P i -jQ i =V i * I i

[0112]

[0113] Among them, S i * is the conjugate of the apparent power phasor at node i, P i is the active power value of node i, Q i is the reactive power value of node i, V i * is the conjugate of the voltage phasor at node i, I i is the current phasor of node i, Y ik is the admittance matrix element, V k is the voltage value of node k.

[0114] Step 6: Analyze the current operating status of the new distribution system, including normal status, warning status, and fault status, extract the wide operating status range of the system, and based on the calculation results of the improved voltage-frequency static stability index, extract the nodes with larger static stability index calculation values ​​in the distribution area as key load nodes, and construct a key load node set. It should be noted that the selection of key load nodes can be set as needed, for example, nodes with static stability index calculation values ​​greater than a certain threshold can be selected, or the first few nodes with the largest static stability index calculation values ​​can be selected.

[0115] Step 7: For the key load nodes, according to the two-dimensional characterization properties of the improved index on the system static voltage and frequency stability, an inequality constraint set is established by the L index interval, the upper and lower limits of the power output, the controllable load range, the energy storage capacity and the state of charge:

[0116]

[0117] Among them, L represents the L index array of the key load node, S G Represents the power output array, S G,max and S G,min Respectively represent the upper and lower limits of the power output array, S L represents the controllable load array, S L,max and S L,min They represent the maximum and minimum values ​​of the controllable load, respectively, and E es Represents the energy storage capacity array, E max Represents the maximum energy storage capacity array, and SOC represents the state of charge array.

[0118] On the basis of the above equality constraints and inequality constraints, a new distribution system voltage and frequency static stability margin assessment model is established with the goals of maximizing the voltage stability margin and minimizing the frequency stability margin, maximizing the voltage stability margin and maximizing the frequency stability margin, maximizing the frequency stability margin and minimizing the voltage stability margin, and maximizing the frequency stability margin and maximizing the voltage stability margin. Specifically:

[0119]

[0120] st

[0121] h DS (x i ,x j ,u i ,u j )=0

[0122] g DS (x i ,x j ,u i ,u j ,Lj )≤0

[0123] Among them, h DS represents the set of equality constraints, i.e., the set of equality constraints based on the flow relationship established in step 5; g DS represents the inequality constraint set, i.e., the L index interval, power output upper and lower limits, controllable load range, energy storage capacity and charge state constraints established in step 7. i , x j Respectively represent the state variables related to the power supply and load nodes, u i ,u j Respectively represent the input variables related to the power supply and load nodes. For voltage source type nodes, voltage is the input quantity and current is the state quantity; for current source type nodes, current is the input quantity and voltage is the state quantity.

[0124] Step 8: Solve the voltage-frequency static stability margin assessment model of the new distribution system, and obtain the voltage-frequency two-dimensional stability margin plane that describes the static stability of the system based on the solution results.

[0125] Specifically, this step calculates the voltage-frequency static stability margin based on the constructed evaluation model; the new distribution system voltage-frequency static stability margin evaluation model of this embodiment includes four parts, and each part is solved separately. The specific solution process is as follows: Figure 3 As shown, it includes two stages: a lower cycle and an upper cycle. The lower cycle is used to calculate the static stability margin of each distribution area at the current time step, and the upper cycle considers the system-level control operation instructions to update the operation status data of each distribution area.

[0126] The lower cycle takes the new distribution system and the boundary power of each distribution area calculated by the upper cycle as input. First, it traverses each node in the distribution area and calculates the improved voltage-frequency static stability index R(Δf,ΔV) of the node. Then the index result is input into the voltage-frequency static stability margin assessment model of the new distribution system. The assessment model is based on the interval model of distributed power sources and loads. When the calculation meets the constraints and can converge, the calculation results are output and enter the upper cycle of the next time step. When the calculation does not converge, the node data is corrected and the calculation is iterated again until the convergence conditions are met.

[0127] The upper loop takes the evaluation results of the lower loop as input, records the evaluation results of each time step, updates the boundary variables according to the control operation data, and passes them to the lower model to start the next time step cycle calculation. When the number of cycles (number of time steps) reaches the upper limit, the final result is output, that is, an optimal voltage frequency point is obtained.

[0128] By solving the four parts of the voltage-frequency static stability margin assessment model of the new distribution system separately, an optimal voltage-frequency point can be obtained. These four points can form a plane, that is, a two-dimensional voltage-frequency stability margin plane that describes the static stability of the system.

[0129] The Euclidean distance between the voltage frequency point of each node and the boundary curve of the two-dimensional stability margin plane is calculated, and the minimum value of the Euclidean distance is taken as the voltage frequency stability margin evaluation result of the current system.

[0130] As an optional solution, in order to improve the online operation capability of the stability margin assessment model, the uncertainty of the upper and lower boundary variables is further considered, and the state estimation is performed based on the system operation data of the previous time step. In order to prevent the data dimension from growing too fast during the calculation process, resulting in non-convergence of the calculation, a clustering method is used to reduce the state variables and operating conditions, reduce the solution dimension, and ensure calculation efficiency. After obtaining the overall system state data under a wide range of operating conditions based on the latest boundary variables, the evaluation model of the local distribution area is updated to realize the rolling calculation of the voltage and frequency stability margin. The implementation methods of the specific processes in this section (such as state estimation, clustering to reduce the solution dimension, etc.) are all achievable by the existing technology and will not be described in detail in this embodiment.

[0131] Embodiment 2

[0132] In one or more embodiments, a novel voltage-frequency static stability margin assessment system for a power distribution system is disclosed, comprising:

[0133] The static network model building module is used to obtain the grid topology, line impedance and node electrical quantity information as input data, establish a new type of distribution system static network model, and modify the static network model according to the system operation status data under uncertain conditions to obtain a modified static network model;

[0134] A static stability index calculation module is used to calculate the improved voltage and frequency static stability index based on the modified static network model;

[0135] The static stability margin assessment module is used to construct a new distribution system voltage and frequency static stability margin assessment model based on the improved voltage and frequency static stability index, with the goals of maximizing the voltage stability margin and minimizing the frequency stability margin, maximizing the voltage stability margin and maximizing the frequency stability margin, maximizing the frequency stability margin and minimizing the voltage stability margin, and maximizing the frequency stability margin and maximizing the voltage stability margin; solve the assessment model, and obtain a voltage and frequency two-dimensional stability margin plane that describes the static stability of the system according to the solution result; calculate the Euclidean distance between the voltage and frequency point of each node and the boundary curve of the two-dimensional stability margin plane, and take the minimum value of the Euclidean distance as the voltage and frequency stability margin assessment result of the current system.

[0136] Among them, based on the modified static network model, the improved voltage and frequency static stability index is calculated, specifically:

[0137]

[0138] Where Δf i is the frequency offset of the power node i relative to the reference frequency. If the node i is in the meshing control mode, the node frequency takes the frequency value corresponding to the virtual speed. If the node i is in the following meshing control mode, the node frequency takes the frequency value output by the phase-locked loop. ΔV i is the voltage offset at power node i relative to the reference voltage, G i f and G i V are the response coefficients of the active power injected into node i to the frequency and the reactive power injected into node i to the voltage, which are described in the form of transfer function; L j is the L index of node j, Y ij is the mutual admittance between node i and node j, Y jj is the self-admittance of node j, X ij is the mutual impedance between node i and node j, V j is the voltage at node j, α G A collection of power nodes.

[0139] The specific implementation of the above modules is the same as that in Example 1 and will not be described in detail here.

[0140] Embodiment 3

[0141] In one or more embodiments, a computer-readable storage medium is disclosed, in which a plurality of instructions are stored, wherein the instructions are suitable for being loaded by a processor of a terminal device and executing the novel distribution system voltage-frequency static stability margin assessment method described in Example 1.

[0142] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A novel voltage-frequency static stability margin evaluation method for a power distribution system, characterized in that: include: The grid topology, line impedance and node electrical quantity information are obtained as input data, and a static network model of a new distribution system is established. The static network model is corrected according to the system operation status data under uncertain conditions to obtain a corrected static network model. Based on the modified static network model, the improved voltage and frequency static stability index is calculated; Based on the improved voltage-frequency static stability index, a new distribution system voltage-frequency static stability margin assessment model is constructed with the goals of maximizing voltage stability margin and minimizing frequency stability margin, maximizing voltage stability margin and maximizing frequency stability margin, maximizing frequency stability margin and minimizing voltage stability margin, and maximizing frequency stability margin and maximizing voltage stability margin. The evaluation model is solved, and a voltage-frequency two-dimensional stability margin plane describing the static stability of the system is obtained according to the solution result; the Euclidean distance between the voltage frequency point of each node and the boundary curve of the two-dimensional stability margin plane is calculated, and the minimum value of the Euclidean distance is taken as the voltage-frequency stability margin evaluation result of the current system.

2. A novel method for evaluating voltage-frequency static stability margin of power distribution system according to claim 1, characterized in that: According to the system operation status data under uncertain conditions, the active power and reactive power injected into the nodes of the static network model are corrected, specifically: Among them, J, M, N, L are Jacobian matrix block matrices, G f is the response coefficient matrix of active power of power electronic equipment to frequency, G V is the response coefficient matrix of reactive power of power electronic equipment to voltage, K f and K V is the Kalman gain matrix, δP and δQ are the residual terms considering the uncertainty of distributed generation output, which are assumed to conform to the normal distribution; Δf and ΔV are the node frequency deviation and voltage deviation, respectively; ΔP and ΔQ are the correction terms of active power and reactive power injected into the node; P and Q are the corrected active power and reactive power injected into the node; θ and V are the phase and amplitude of the node voltage, respectively, and H, E, O, D are the coefficient matrices of the power flow equation.

3. A novel method for evaluating voltage-frequency static stability margin of power distribution system according to claim 1, characterized in that: Based on the modified static network model, the improved voltage-frequency static stability index is calculated, specifically: Where Δf i is the frequency offset of the power node i relative to the reference frequency. If the node i is in the meshing control mode, the node frequency takes the frequency value corresponding to the virtual speed. If the node i is in the following meshing control mode, the node frequency takes the frequency value output by the phase-locked loop. ΔV i is the voltage offset at power node i relative to the reference voltage, G i f and G i V are the response coefficients of the active power injected into node i to the frequency and the reactive power injected into node i to the voltage, which are described in the form of transfer function; L j is the L index of node j, Y ij is the mutual admittance between node i and node j, Y jj is the self-admittance of node j, X ij is the mutual impedance between node i and node j, V j is the voltage at node j, α G A collection of power supply nodes.

4. A novel method for evaluating voltage-frequency static stability margin of power distribution system as claimed in claim 3, characterized in that: It also includes: determining the response coefficient G of the active power injected by node i to the frequency based on the node type and control strategy i f And the response coefficient G of the reactive power injected into node i to the voltage i V ; Determine the response factor G i f and G i V The specific method is: ① For grid-type power sources, describe them as balancing nodes or PV nodes, and establish the node voltage relationship and output relationship as follows: V i =m i k i,da V i,dc (0 <m<1); Where m represents the duty cycle, k i,da K is the ratio of the maximum modulated AC voltage to the DC voltage, i,ctrl is the control parameter array element, s is the Laplace operator, l is the order, inertia dynamics is ignored under static conditions, and only the coefficient term corresponding to l = 0 can be taken; Δf i is the frequency offset at power node i relative to the reference frequency, V i is the voltage at power node i, P i The active power injected into power node i; V i,dc is the DC voltage at power node i, P i,set is the active power reference value of power node i; At this time, the response coefficient Response coefficient G i V =0; ②For the grid-following power source, it is described as a PQ node, and the active and reactive output relationship is established as follows: Among them, F dz Indicates high / low voltage crossing control dead zone, P i The active power injected into power node i, Q i The reactive power injected into power node i; At this time, the response coefficient Response Factor ③ For SVG, it is described as a PV node, and the node active power and node voltage are as follows: V i =V i,set +k i,ctrl ΔQ i ; P i ＝0； At this time, the response coefficient G i f =0, response coefficient G i V =1 / k i,ctrl ; ④For controllable loads, they are described as PQ nodes, and active power and reactive power are expressed in piecewise function form: P j =F j,Pf (Δf j )·P j,set ; Q j =F j,QV (ΔV j )·Q j,set ; Among them, P j,set and Q j,set are active power and reactive power reference values, F j,Pf and F j,QV They represent the piecewise functions of frequency deviation and voltage deviation respectively, which are determined by the load response strategy of the node; At this time, the response coefficient G i f =(1-F j,Pf (Δf j )) / Δf j , response coefficient G i V =(1-F j,QV (ΔV j )) / ΔV j ; ⑤ For energy storage, it is divided into grid-building energy storage and grid-following energy storage according to the control method. In the discharge mode, the expression of grid-building energy storage is consistent with that of grid-building power supply, and the expression of grid-following energy storage is consistent with that of grid-following power supply; in the charging mode, grid-building energy storage is expressed by PV nodes, and grid-following energy storage is expressed by PQ nodes; ⑥ For V2G electric vehicles, the same expression as grid-connected energy storage is used; ⑦For other passive nodes, the transfer function correction coefficient term G i f and G i V Both are 0.

5. A novel method for evaluating voltage-frequency static stability margin of power distribution system according to claim 1, characterized in that: Also includes: A Kalman filter is constructed to characterize the power output data. The upper and lower boundaries of the electrical quantities δP and δQ of the distributed power node are obtained according to the interval range of the historical data. The power output probability distribution data is discretized using the interval linear interpolation method to obtain the output interval model. Kalman filtering is performed on the output range models of different power sources in the new distribution system to obtain the correction terms of active power and reactive power injected into the node, and then the voltage and frequency static stability indicators are recalculated and improved through the time-step rolling optimization method.

6. A novel method for evaluating voltage-frequency static stability margin of power distribution system according to claim 1, characterized in that: A new distribution system voltage and frequency static stability margin assessment model is constructed, specifically: Where Δf i is the frequency offset at power node i relative to the reference frequency, ΔV j is the offset of the voltage at the load node j relative to the reference voltage; To improve the voltage frequency static stability index; α G is the power node set, α L is the set of load nodes.

7. A novel method for evaluating voltage-frequency static stability margin of power distribution system according to claim 1, characterized in that: The voltage-frequency static stability margin assessment model of the new distribution system is solved, which specifically includes two stages: the upper cycle and the lower cycle. The lower cycle is used to calculate the static stability margin of each distribution area at the current time step, and the upper cycle considers the system-level control operation instructions to update the operating status data of each distribution area. Among them, the lower-level loop takes the boundary power of each distribution area calculated by the upper-level loop as input, traverses each node in the distribution area, calculates the improved voltage-frequency static stability index of the node, and inputs the index result into the new distribution system voltage-frequency static stability margin assessment model. When the calculation meets the constraints and can converge, the calculation result is output and enters the upper-level loop of the next time step. When the calculation does not converge, the node data is corrected and the calculation is iterated again until the convergence conditions are met. The upper-level loop takes the assessment result of the lower-level loop as input, records the assessment result of each time step, and updates the boundary variables according to the control operation data, and passes it to the lower-level model to start the cyclic calculation of the next time step.

8. A new distribution system voltage frequency static stability margin assessment system, characterized in that: include: The static network model building module is used to obtain the grid topology, line impedance and node electrical quantity information as input data, establish a new type of distribution system static network model, and modify the static network model according to the system operation status data under uncertain conditions to obtain a modified static network model; A static stability index calculation module is used to calculate the improved voltage and frequency static stability index based on the modified static network model; The static stability margin assessment module is used to construct a new distribution system voltage and frequency static stability margin assessment model based on the improved voltage and frequency static stability index, with the goals of maximizing the voltage stability margin and minimizing the frequency stability margin, maximizing the voltage stability margin and maximizing the frequency stability margin, maximizing the frequency stability margin and minimizing the voltage stability margin, and maximizing the frequency stability margin and maximizing the voltage stability margin; solve the assessment model, and obtain a voltage and frequency two-dimensional stability margin plane that describes the static stability of the system according to the solution result; calculate the Euclidean distance between the voltage and frequency point of each node and the boundary curve of the two-dimensional stability margin plane, and take the minimum value of the Euclidean distance as the voltage and frequency stability margin assessment result of the current system.

9. A novel distribution system voltage-frequency static stability margin assessment system as claimed in claim 8, characterized in that: Based on the modified static network model, the improved voltage-frequency static stability index is calculated, specifically: Where Δf i is the frequency offset of the power node i relative to the reference frequency. If the node i is in the meshing control mode, the node frequency takes the frequency value corresponding to the virtual speed. If the node i is in the following meshing control mode, the node frequency takes the frequency value output by the phase-locked loop. ΔV i is the voltage offset at power node i relative to the reference voltage; G i f and G i V are the response coefficients of the active power injected into node i to the frequency and the reactive power injected into node i to the voltage, which are described in the form of transfer function; L j is the L index of node j, Y ij is the mutual admittance between node i and node j, Y jj is the self-admittance of node j, X ij is the mutual impedance between node i and node j, V j is the voltage at node j, α G A collection of power supply nodes.

10. A computer-readable storage medium storing a plurality of instructions, characterized in that: The instructions are suitable for being loaded by a processor of a terminal device and executing the novel voltage-frequency static stability margin assessment method for a power distribution system as described in any one of claims 1-7.

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