A complete characterization method for the three-phase feasible region of the unbalanced power grid system model

Abstract

The present invention relates to a complete characterization method of the three-phase feasible domain considering the unbalanced power grid system model. The three-phase feasible domain is defined on the basis of the nonlinear non-convex three-phase AC power flow model and the ZIP comprehensive load modeling, and the unbalanced power grid safety operation constraints including line thermal limit constraints and voltage imbalance constraints are considered; at the same time, the constraints including distributed power sources and flexible loads, including wind power, photovoltaic power generation, energy storage and controllable loads are also considered; a non-hyperbolic dynamic system method is adopted to theoretically prove the one-to-one correspondence between the conventional stable equilibrium manifold of the dynamic system and the three-phase feasible domain. The present invention uses the three-phase feasible domain to propose the existence of the solution to the three-phase AC power flow problem, and applies it to the evaluation of the three-phase feasible domain recovery plan. The present invention accurately characterizes the impact of flexible load access on the feasible domain of the three-phase unbalanced distribution network, and illustrates that flexible loads can improve system flexibility and distributed power penetration.

Description

Technical Field

[0001] The invention belongs to the technical field of static safe operation of unbalanced power grids, in particular to a complete characterization method of a three-phase feasible domain considering an unbalanced power grid system model. Background Art

[0002] With the global energy shortage, more and more distributed generation is connected to the grid, such as wind power and photovoltaic power generation, which may lead to violations of voltage and line thermal limit constraints and other safety operation problems. Flexible loads can effectively solve the problem of safe operation of the grid, provide flexible reserves for the power system, and have the ability to interact with the grid in both directions. The distributed energy system composed of distributed generation and flexible loads is an important part of the future smart grid. Quantifying the improvement of system flexibility by flexible loads is an important research topic. For unbalanced power grids such as low-voltage distribution networks, distributed energy is usually connected to the grid in a small-scale and distributed form, which will cause power quality problems in the system. The access of asymmetric flexible loads makes the three-phase imbalance problem of the distribution network more prominent, causing voltage waveform distortion, increasing grid operation losses, and affecting the normal operation of distribution equipment. Considering the complete safety operation constraints of the unbalanced power grid and the distributed energy model, fully characterizing the three-phase feasible domain, and exploring the impact of flexible loads on system flexibility are of great significance to the study of the safe operation of the unbalanced power grid. However, due to the nonlinearity and non-convexity of the unbalanced system and the complexity of high-dimensional operation constraints, no research has yet fully characterized the three-phase feasible domain.

[0003] In addition, the three-phase optimal power flow (OPF) can ensure the safe operation of the unbalanced network. Due to the ill-conditioned Jacobian matrix, the algorithm may not be able to find a solution. The current technology cannot determine whether there is no solution or the algorithm cannot find a solution. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and propose a complete characterization method of the three-phase feasible domain considering the unbalanced power grid system model. The three-phase feasible domain is used to verify the existence of the solution of the three-phase AC power flow problem under high penetration of distributed generation access, and boundary constraints are given. The three-phase feasible domain can evaluate the restoration plan according to the safety boundary distance of the solution.

[0005] The present invention solves the technical problem by adopting the following technical solutions:

[0006] The advantages and positive effects of the present invention are:

[0007] The complete characterization method of the three-phase feasible region considering the unbalanced power grid system model includes the following steps:

[0008] Step 1: Input the parameters of the unbalanced system in three-phase format and set the constraints;

[0009] Step 2: Create a constraint set according to step 1, use Latin hypercube technology to sample within the constraint set, and obtain the quotient gradient system Q corresponding to the constraint set H (x) initial value of the integral;

[0010] Step 3: Integrate the quotient gradient system in step 2 from the initial value until it converges to a point on the stable equilibrium flow pattern, denoted as x;

[0011] Step 4: Construct the constraint equation H(x). If |H(x)|=0, then x is a point on the conventional stable equilibrium flow pattern, and proceed to step 5; otherwise, x is a point on the degenerate stable equilibrium flow pattern, select another random value within the constraint range, and return to step 3;

[0012] Step 5: Save the feasible solution x, and determine whether all initial sampling solutions have completed the integral calculation, then complete the calculation of the three-phase feasible region; otherwise, take another initial point and return to step 3.

[0013] Moreover, the parameters in step 1 include a three-phase transformer model, an unbalanced load and line model, a distributed power source and a flexible load; and the constraints include safe operation constraints and power quality constraints.

[0014] Moreover, the constraint set in step 2 includes: three-phase AC power flow constraint, power exchange constraint at the connection point, voltage constraint, line power flow constraint, voltage unbalance constraint and distributed energy system model;

[0015] The three-phase AC power flow constraints are:

[0016]

[0017] in, is the active and reactive power value of n phases at node i, a, b and c are three phases, is the voltage amplitude of phase n at node i; is the voltage amplitude of phase m at node j, and is the equivalent conductance and equivalent susceptance of the line from phase m of node i to phase n of node j, N B represents the number of system nodes, m and n represent the phase of the nodes, is the active power and reactive power output by the wind turbine generator sets connected to n nodes at node i; is the active power and reactive power output by the photovoltaic generator sets connected to n nodes at node i; and is the active and reactive load of n phases at node i; and is the reactive power of the n-phase discharge and charging power of the energy storage at node i, is the reactive power consumed by the n-phase energy storage at node i; and is the active power and reactive power demand of the n-phase load at node i, and is the active power and reactive power of the n-phase directly controllable load at node i, is the voltage phase angle difference between the n-phase at node i and the m-phase at node j, is the voltage phase angle of phase n at node i, is the voltage phase angle of phase m at node j;

[0018] The power exchange constraint at the connection point is:

[0019]

[0020] in, is the active power exchanged between the n-phase and the upper grid at the connection point PCC, Limit the minimum and maximum values ​​of active power exchanged for the connection point, is the reactive power exchanged between the n-phase at the connection point and the upper grid, Limit the minimum and maximum values ​​of exchange reactive power for the connection point;

[0021] The voltage constraint is:

[0022]

[0023] in, is the minimum and maximum voltage amplitude allowed at node i;

[0024] The line power flow constraint is:

[0025]

[0026] in, and is the apparent power at the beginning and end of the n-phase line l, is the apparent power upper limit of line l, N L is the number of transmission lines;

[0027] The voltage unbalance constraint is:

[0028]

[0029] Among them, among them, are the negative sequence component and positive sequence component of the voltage at node i, VUF dem,i represents the desired voltage imbalance at node i;

[0030] The distributed energy system model includes a distributed generation model and a flexible load model. The distributed generation model includes a wind turbine model and a photovoltaic unit model. The flexible load model includes a direct control load model and an energy storage model:

[0031] Wind turbine model:

[0032]

[0033] in, is the minimum and maximum active power output by the wind turbines connected to n nodes at node i, is the minimum and maximum reactive power output by the photovoltaic generator group with n phases at node i, N W Indicates the number of wind power units;

[0034] Photovoltaic power generation model:

[0035]

[0036] is the maximum and minimum active power output by the photovoltaic generator set of n phases at node i, is the maximum and minimum reactive power output by the photovoltaic generator set at n phases of node i, N PV is the number of photovoltaic units. The wind turbine unit is connected to the distribution network in the form of a generator. There are upper and lower limits on its output active power and reactive power. The connection point of the wind power unit is the PV node, while the photovoltaic unit is usually connected to the distribution network through an inverter. Its output constraints are limited by active power, power factor and inverter capacity. The connection point of the photovoltaic unit is the PQ node. and is the power factor limit and capacity upper limit of the PV unit of phase n at node i,

[0037] Direct control load model:

[0038]

[0039] in, is the minimum and maximum active power of the n-phase directly controllable load at node i, is the minimum and maximum reactive power of the n-phase directly controllable load at node i, is the power factor of the n-phase directly controllable load at node i, energy storage model:

[0040]

[0041] in, is the reactive power of the n-phase energy storage at node i, is the capacity of the n-phase energy storage at node i, is the minimum and maximum value of the active charging of the n-phase energy storage at node i, is the minimum and maximum value of the active discharge of the n-phase energy storage at node i, E i,max 、E i,min is the maximum and minimum value of the energy storage charge at node i, η E,i is the charging efficiency, E set,i is the current value of the stored charge, c E,i is the charging factor,

[0042] At the same time, each constraint in the constraint set is a nonlinear model.

[0043] Moreover, the load constrained by the three-phase AC power flow includes a star or delta structure connection, and the star or delta structure connection includes a constant power load, a constant current load and a constant impedance load:

[0044]

[0045] in, and is the active power and reactive power demand of the n-phase load at node i, S n Li is the apparent power injection of the n-phase load at node i, Respectively represent the apparent power injection of the load in star or delta connection; The expressions for the three basic types of active and reactive power of star-shaped loads connected to n nodes i are as follows; Three basic types of active and reactive power expressions for angular loads between phases n and m at node i.

[0046] Moreover, the quotient gradient system in step 2 is:

[0047]

[0048] Among them, Q H (x) is a nonlinear non-hyperbolic dynamic system, and DH(x) is the Jacobian matrix of the equation system H(x).

[0049] 1. Moreover, the specific implementation method of step 4 is: the three-phase parameter variables of the constraint set in step 2 are represented by the control variable u and the state variable y to obtain the active and reactive quantities u that the distributed power source and the flexible load can regulate 1 The three-phase voltage amplitude of the balance node and the three-phase voltage amplitude of the generator node u 2 ,in is the active power output by the photovoltaic generator set connected to n nodes at node i, The reactive power output of the photovoltaic generator set at n phases of node i, The reactive power of the n-phase directly controllable load at node i, is the n-phase discharge power of the energy storage at node i, is the n-phase charging power of the energy storage at node i, is the voltage amplitude of phase n at the connection, The voltage amplitude of the wind turbine node n phase,

[0050] And simplify the unbalanced system constraints in the constraint set:

[0051]

[0052] By adding the slack variable S, the inequality constraint in the unbalanced system constraint is transformed into an equality constraint, and the constraint equation H(x) is obtained:

[0053]

[0054] The present invention defines a three-phase feasible domain on the basis of a nonlinear non-convex three-phase AC power flow model and ZIP comprehensive load modeling, and considers the safe operation constraints of unbalanced power grids including line thermal limit constraints and voltage imbalance constraints; at the same time, it also considers the constraints of distributed power sources and flexible loads, including wind power, photovoltaic power generation, energy storage and controllable loads; a non-hyperbolic dynamic system method is used to theoretically prove the one-to-one correspondence between the conventional stable equilibrium manifold of the dynamic system and the three-phase feasible domain. The present invention uses the three-phase feasible domain to propose the existence of the solution to the three-phase AC power flow problem, and applies it to the evaluation of the three-phase feasible domain recovery plan, which can provide guidance for the three-phase feasible domain recovery and safe operation evaluation. In addition, the present invention accurately depicts the impact of flexible load access on the feasible domain of the three-phase unbalanced distribution network, and illustrates that flexible loads can improve system flexibility and distributed power penetration. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 Schematic diagram of three-phase feasible region of wind power units under different conditions in scenario 1 of an embodiment of the present invention;

[0056] Figure 2 It is a schematic diagram of only the degenerate stable equilibrium manifold remaining in the three-phase feasible domain after the wind power active power output range of scenario 1 in the embodiment of the present invention is further improved;

[0057] Figure 3 This is a schematic diagram of a three-phase feasible region after changing parameters in scenario 1 in an embodiment of the present invention;

[0058] Figure 4 The distributed energy system parameters and configuration diagram of scenario 2 in the embodiment of the present invention;

[0059] Figure 5This is a schematic diagram of the three-phase feasible region with constraints added in scenario 2 in an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The present invention is further described in detail below with reference to the accompanying drawings.

[0061] The three-phase feasible region is nonlinear and non-convex, and accurately describes the nonlinear impact of ignoring line flow constraints and unbalanced voltage constraints on the three-phase feasible region. The results show that ignoring operation constraints will bring great danger to system operation.

[0062] A complete characterization method of the three-phase feasible domain of the unbalanced power grid system model is considered, where the three-phase feasible domain is defined on the three-phase space of the active and reactive control variables of the unbalanced point network, and the three phases of the feasible domain are fully characterized separately. The operating points in the three-phase feasible domain meet the requirements of all operating equations and inequalities. It includes the following steps:

[0063] Step 1: Input the parameters of the unbalanced system in three-phase format and set the constraints.

[0064] The parameters of the unbalanced system in this step include: three-phase transformer model, unbalanced load and line model, distributed generation and flexible load; the constraints include safe operation constraints and power quality constraints.

[0065] Step 2: Create a constraint set according to step 1, use Latin hypercube technology to sample within the constraint set, and obtain the quotient gradient system Q corresponding to the constraint set H (x)(Q H (x) = -DH(x) T H(x)) Initial value of the integral.

[0066] The constraint set in this step includes:

[0067] Three-phase AC power flow constraints, power exchange constraints at connection points, voltage constraints, line power flow constraints, voltage unbalance constraints, and distributed energy system models;

[0068] The three-phase AC power flow constraints are:

[0069]

[0070] in, is the active and reactive power value of n phases at node i, a, b and c are three phases, is the voltage amplitude of phase n at node i; is the voltage amplitude of phase m at node j, and is the equivalent conductance and equivalent susceptance of the line from phase m of node i to phase n of node j, N Brepresents the number of system nodes, m and n represent the phase of the nodes, is the active power and reactive power output by the wind turbine generator sets connected to n nodes at node i; is the active power and reactive power output by the photovoltaic generator sets connected to n nodes at node i; and is the active and reactive load of n phases at node i; and is the reactive power of the n-phase discharge and charging power of the energy storage at node i, is the reactive power consumed by the n-phase energy storage at node i; and is the active power and reactive power demand of the n-phase load at node i, and is the active power and reactive power of the n-phase directly controllable load at node i, is the voltage phase angle difference between the n-phase at node i and the m-phase at node j, is the voltage phase angle of phase n at node i, is the voltage phase angle of phase m at node j.

[0071] Based on the three-phase power flow model, the loads constrained by the three-phase AC power flow include star or delta structure connections, which include constant power loads, constant current loads, and constant impedance loads:

[0072]

[0073] in, and is the active power and reactive power demand of the n-phase load at node i, S n Li is the apparent power injection of the n-phase load at node i, Respectively represent the apparent power injection of the load in star or delta connection; The expressions for the three basic types of active and reactive power of star-shaped loads connected to n nodes i are as follows; Three basic types of active and reactive power expressions for angular loads between phases n and m at node i.

[0074] The power exchange constraint at the connection point is:

[0075]

[0076] in, is the active power exchanged between the n-phase and the upper grid at the connection point PCC, Limit the minimum and maximum values ​​of active power exchanged for the connection point, is the reactive power exchanged between the n-phase at the connection point and the upper grid, Limit the minimum and maximum values ​​of exchange reactive power for the connection point.

[0077] The voltage constraint is:

[0078]

[0079] in, is the minimum and maximum voltage amplitude allowed at node i.

[0080] The line power flow constraint is:

[0081]

[0082] in, is the active power exchanged between the n-phase and the upper grid at the connection point (PCC), It is the reactive power exchanged between the n phases at the connection point and the upper grid. and is the apparent power at the beginning and end of the n-phase line l, is the apparent power upper limit of line l, N L is the number of transmission lines.

[0083] The voltage unbalance constraint is:

[0084]

[0085] Among them, among them, are the negative sequence component and positive sequence component of the voltage at node i respectively. dem,i represents the desired voltage imbalance at node i;

[0086] The distributed energy system model includes a distributed generation model and a flexible load model. The distributed generation model includes a wind turbine model and a photovoltaic unit model. The flexible load model includes a direct control load model and an energy storage model:

[0087] Wind turbine model:

[0088]

[0089] in, is the minimum and maximum active power output by the wind turbines connected to n nodes at node i, is the minimum and maximum reactive power output by the photovoltaic generator group with n phases at node i, N W Indicates the number of wind turbines.

[0090] Photovoltaic power generation model:

[0091]

[0092] is the maximum and minimum active power output by the photovoltaic generator set of n phases at node i, is the maximum and minimum reactive power output by the photovoltaic generator set at n phases of node i, N PV is the number of photovoltaic units. The wind turbine unit is connected to the distribution network in the form of a generator. There are upper and lower limits on its output active power and reactive power. The connection point of the wind power unit is the PV node. The photovoltaic unit is usually connected to the distribution network through an inverter. Its output constraints are limited by active power, power factor and inverter capacity. The connection point of the photovoltaic unit is the PQ node. and is the power factor limit and capacity upper limit of the PV unit of phase n at node i.

[0093] Direct control load model:

[0094]

[0095] in, is the minimum and maximum active power of the n-phase directly controllable load at node i, is the minimum and maximum reactive power of the n-phase directly controllable load at node i, is the power factor of the n-phase directly controllable load at node i.

[0096] Energy storage model:

[0097]

[0098] in, is the reactive power of the n-phase energy storage at node i, is the capacity of the n-phase energy storage at node i, is the minimum and maximum value of the active charging of the n-phase energy storage at node i, is the minimum and maximum value of the active discharge of the n-phase energy storage at node i, E i,max 、E i,min is the maximum and minimum value of the energy storage charge at node i, η E,i is the charging efficiency, E set,i is the current value of the stored charge, c E,i is the charging coefficient. At the same time, each constraint in the constraint set is a nonlinear model.

[0099] In order to characterize the three-phase feasible region of the unbalanced distribution network system model, a dynamic system is established according to the constraint equation H(x), that is, the quotient gradient system established in this step:

[0100]

[0101] Among them, QH (x) is a nonlinear, non-hyperbolic dynamic system, and DH(x) is the Jacobian matrix of the equation system H(x). Since the number of constraints in the constraint equation is less than the number of variables, in dynamic theory, the system is a nonlinear, non-hyperbolic dynamic system.

[0102] For a dynamic system, the equilibrium manifold refers to the one that satisfies Q H -1 Every path-connected branch of (x), that is, any point on the equilibrium manifold, can satisfy Q H (x)=0. For an equilibrium manifold, if for any point x on it, the real part of the eigenvalues ​​corresponding to the eigenvectors of DH(x) in the normal space are all negative, then the equilibrium manifold is a stable equilibrium manifold. For a stable equilibrium manifold, if H(x)=0 is satisfied, then it is a regular stable equilibrium manifold. If for a stable equilibrium manifold, if H(x) is not 0, but satisfies DH(x) T H(x) = 0, then it is a degenerate stable equilibrium manifold. Therefore, according to the above principle, steps 3, 4 and 5 are obtained.

[0103] Step 3: Integrate the quotient gradient system in step 2 from the initial value until it converges to a point on the stable equilibrium flow pattern, denoted as x.

[0104] The integration link of this step has global convergence and can converge to a stable equilibrium manifold from any initial point.

[0105] Step 4: Construct the constraint equation H(x). If |H(x)|=0, then x is a point on the conventional stable equilibrium flow pattern, and proceed to step 5; otherwise, x is a point on the degenerate stable equilibrium flow pattern, select another random value within the constraint range, and return to step 3.

[0106] 2. The three-phase parameter variables of the constraint set in step 2 are expressed using the control variable u and the state variable y to obtain the active and reactive quantities u that can be regulated by the distributed power source and the flexible load. 1 The three-phase voltage amplitude of the balance node and the three-phase voltage amplitude of the generator node u 2 ,in is the active power output by the photovoltaic generator set connected to n nodes at node i, The reactive power output of the photovoltaic generator set at n phases of node i, The reactive power of the n-phase directly controllable load at node i, is the n-phase discharge power of the energy storage at node i, is the n-phase charging power of the energy storage at node i, is the voltage amplitude of phase n at the connection, The voltage amplitude of the n-phase of the wind turbine node is calculated, and the constraint of the unbalanced system is simplified as follows:

[0107]

[0108] By adding the slack variable S, the inequality constraint in the unbalanced system constraint is transformed into an equality constraint, and the constraint equation H(x) is obtained:

[0109]

[0110] Step 5, save the feasible solution x, and determine whether all initial sample solutions have completed the integral calculation, then complete the calculation of the three-phase feasible region; otherwise, take another initial point and return to step 3. According to the method of the present invention, the IEEE 13-node example is tested in scenario 1 and scenario 2.

[0111] In scenario 1, the phase voltage range of all buses in the 13-bus example is [0.95, 1.00] pu, and the reference voltage is set to [1.001.001.00] T pu. Two wind turbines are connected to nodes 632 and 675. The active output power range of the wind turbine at node 632 is [0, 0.8] pu, and the reactive power is [0, 0.5] pu. The active output power limit of the wind turbine at node 675 is [0, 1.2] pu, and the reactive power is [0, 1] pu. The VUF expectation value of all nodes is 4%. The thermal limit of all lines is set to 5 MVA. The standard power of the system is 0.167 MVA. The distributed energy system configuration and parameters of scenario 2 are shown in the attached figure. Figure 4 As shown, the active power will be [3.8753.8753.875] T pu, reactive is [1.8481.8481.848] T The load demand of pu is added to the original distributed load (10 nodes), and 40% of the load of 634 nodes and 10 nodes is assumed to be directly controlled load. The rest of the operating parameters are the same as scenario 1.

[0112] Figure 1 (a) is the three-phase feasible domain of the active and reactive power space of the wind power unit at 675 nodes under the following scenario 1 using the method of the present invention, wherein the outer dotted line is the frame constraint of the wind power unit output, and the boundary constraints are also marked in the figure. Figure 1 The light grey part in (b) is the three-phase feasible region after ignoring the voltage unbalance constraint. Compared with the original three-phase feasible region, the error is larger, and the errors of the three phases are different;

[0113] Figure 2When the wind power active power output range of 675 nodes is further increased to [1.2, 2.0] pu, only the degenerate stable equilibrium manifold remains in the three-phase feasible domain. According to the theory proposed in the present invention, the system has no feasible solution at this time, and the voltage of some nodes, wind power output and connection point exchange power in the system exceed the limit.

[0114] Figure 3 (a) is the recovery of the three-phase feasible region after the constant PQ load is increased to 1.4 times. Figure 3 (b) is the recovery of the three-phase feasible domain after all types of B-phase loads are increased to 1.75 times. It can be seen from the figure that the contribution of 1.4 times the constant PQ load to the output power of C phase can reach the upper limit of the capacity constraint, but the feasible domain of B phase is still very small; after the 1.75 times B-phase load is restored, the feasible domain of B phase is better. If the three-phase output power of wind power is required to reach 8.00pu at this time, both recovery strategies can find operating solutions, which are marked as "A1, B1, C1" and "A2, B2, C2" in the three-phase feasible domain. According to the position of the operating point in the domain characterized by the method proposed in the present invention, the two recovery strategies have different effects on the safe operation of phases A and B: the former has higher requirements for the operation of phase B (at the boundary, it is easy to violate the constraints), and the latter has higher requirements for the operation of phase a.

[0115] Figure 4 Configuration and parameter setting of distributed generation and flexible load for IEEE 13-node example in scenario 2.

[0116] Figure 5 The dark gray part of (a) is the three-phase feasible domain of 13 nodes (excluding flexible constraints) with added line thermal limit constraints in scenario 2. When observed in the three-phase power space of photovoltaic power generation, the light gray part is the three-phase feasible domain ignoring the line thermal limit constraints. Compared with the two, the feasible domain area of ​​the latter is greatly increased and the three-phase increases are different. Figure 5 (b) is the three-phase feasible domain after adding flexible load when the photovoltaic output is reduced due to the line thermal limit constraint, which shows that flexible load has a promoting effect on the penetration rate of distributed power generation. The method proposed in the present invention accurately depicts the positive impact of flexible load on the three-phase feasible domain.

[0117] for Figures 1 to 5 For comparison. Figure 1 (a) shows the three-phase feasible domain of 13 nodes in the scenario fully described by the method proposed in the present invention. It can be seen from the figure that the three-phase feasible domain of the actual output of the wind power unit is nonlinear and non-convex, and is much smaller than the frame constraint. Figure 1 (b) and Figure 5(a) shows that ignoring the system voltage imbalance constraint and line thermal limit constraint will make the characterization of the system three-phase feasible region more radical, making the system operate in an unsafe situation. From the results, it can be seen that the three phases of the proposed feasible region are affected differently, such as Figure 5 (a) The feasible region of phase C is most sensitive to the tightening of the thermal limit, which proves the necessity of characterizing the three phases of the feasible region of the unbalanced system separately. Figures 2 to 3 It shows that the system has no solution when the distributed generation has a high penetration rate. According to the theory proposed by the present invention, the system cannot find a solution because the solution does not exist, not because the algorithm cannot find a solution. The increased load demand helps distributed generation to increase its penetration rate. Therefore, two strategies for restoring the three-phase feasible domain are proposed, and the restoration effect is evaluated using the proposed three-phase feasible domain. Operators can choose the solution to restore the three-phase feasible domain according to different safety requirements. In order to meet the operating requirements of the thermal limit, it is often necessary to reduce the output of distributed generation, which is not conducive to the flexible operation of the system. Figure 5 The important role of flexible load in the reduction of distributed generation is given, and the proposed three-phase feasible region characterization method can be used as a reference for the configuration and control plan of distributed generation and flexible load.

[0118] It should be emphasized that the embodiments described in the present invention are illustrative rather than restrictive. Therefore, the present invention includes but is not limited to the embodiments described in the specific implementation manner. Any other implementation manners derived by those skilled in the art based on the technical solution of the present invention also fall within the scope of protection of the present invention.

Claims

1. A complete characterization method of the three-phase feasible region considering the unbalanced power grid system model, Features: The following steps are involved: Step 1: Input the parameters of the unbalanced system in three-phase format and set the constraints; In step 1, the parameters include three-phase transformer model, unbalanced load and line model, distributed generation and flexible load; the constraints include safe operation constraints and power quality constraints; Step 2: Create a constraint set according to step 1, use Latin hypercube technology to sample within the constraint set, and obtain the quotient gradient system Q corresponding to the constraint set H (x) initial value of the integral; The constraint set in step 2 includes: three-phase AC power flow constraints, power exchange constraints at the connection point, voltage constraints, line power flow constraints, voltage unbalance constraints and distributed energy system model; The distributed energy system model includes a distributed power generation model and a flexible load model. The distributed power generation model includes a wind turbine model and a photovoltaic unit model. The flexible load model includes a direct control load model and an energy storage model. Step 3: Integrate the quotient gradient system in step 2 from the initial value until it converges to a point on the stable equilibrium flow pattern, denoted as x; Step 4: Construct the constraint equation H(x). If |H(x)|=0, then x is a point on the conventional stable equilibrium flow pattern, and proceed to step 5; otherwise, x is a point on the degenerate stable equilibrium flow pattern, select another random value within the constraint range, and return to step 3; Step 5: Save the feasible solution x, and determine whether all initial sampling solutions have completed the integral calculation, then complete the calculation of the three-phase feasible region; otherwise, take another initial point and return to step 3.

2. The complete characterization method of the three-phase feasible region considering the unbalanced power grid system model according to claim 1, Features: The three-phase AC power flow constraint in step 2 is: in, is the active and reactive power value of n phases at node i, a, b and c are three phases, is the voltage amplitude of phase n at node i; is the voltage amplitude of phase m at node j, and is the equivalent conductance and equivalent susceptance of the line from phase m of node i to phase n of node j, N B represents the number of system nodes, m and n represent the phase of the nodes, is the active power and reactive power output by the wind turbine generator sets connected to n nodes at node i; is the active power and reactive power output by the photovoltaic generator sets connected to n nodes at node i; and is the active and reactive load of n phases at node i; and is the reactive power of the n-phase discharge and charging power of the energy storage at node i, is the reactive power consumed by the n-phase energy storage at node i; and is the active power and reactive power demand of the n-phase load at node i, and is the active power and reactive power of the n-phase directly controllable load at node i, is the voltage phase angle difference between the n-phase at node i and the m-phase at node j, is the voltage phase angle of phase n at node i, is the voltage phase angle of phase m at node j; The power exchange constraint at the connection point is: in, is the active power exchanged between the n-phase and the upper grid at the connection point PCC, Limit the minimum and maximum values ​​of active power exchanged for the connection point, is the reactive power exchanged between the n-phase at the connection point and the upper grid, Limit the minimum and maximum values ​​of exchange reactive power for the connection point; The voltage constraint is: in, is the minimum and maximum voltage amplitude allowed at node i; The line power flow constraint is: in, and is the apparent power at the beginning and end of the n-phase line l, is the apparent power upper limit of line l, N L is the number of transmission lines; The voltage unbalance constraint is: Among them, among them, are the negative sequence component and positive sequence component of the voltage at node i, VUF dem,i represents the desired voltage imbalance at node i; Wind turbine model: in, is the minimum and maximum active power output by the wind turbines connected to n nodes at node i, is the minimum and maximum reactive power output by the photovoltaic generator group with n phases at node i, N W Indicates the number of wind power units; Photovoltaic power generation model: is the maximum and minimum active power output by the photovoltaic generator set of n phases at node i, is the maximum and minimum reactive power output by the photovoltaic generator set at n phases of node i, N PV is the number of photovoltaic units. The wind turbine unit is connected to the distribution network in the form of a generator. There are upper and lower limits on its output active power and reactive power. The connection point of the wind power unit is the PV node, while the photovoltaic unit is usually connected to the distribution network through an inverter. Its output constraints are limited by active power, power factor and inverter capacity. The connection point of the photovoltaic unit is the PQ node. and is the power factor limit and capacity upper limit of the PV unit of phase n at node i, Direct control load model: in, is the minimum and maximum active power of the n-phase directly controllable load at node i, is the minimum and maximum reactive power of the n-phase directly controllable load at node i, is the power factor of the n-phase directly controllable load at node i, Energy storage model: in, is the reactive power of the n-phase energy storage at node i, is the capacity of the n-phase energy storage at node i, is the minimum and maximum value of the active charging of the n-phase energy storage at node i, is the minimum and maximum value of the active discharge of the n-phase energy storage at node i, E i,max 、E i,min is the maximum and minimum value of the energy storage charge at node i, η E,i is the charging efficiency, E set,i is the current value of the stored charge, c E,i is the charging factor, At the same time, each constraint in the constraint set is a nonlinear model.

3. The complete characterization method of the three-phase feasible region considering the unbalanced power grid system model according to claim 2, Features: The loads constrained by the three-phase AC power flow include star or delta structure connections, and the star or delta structure connections include constant power loads, constant current loads, and constant impedance loads: in, and is the active power and reactive power demand of the n-phase load at node i, S n Li is the apparent power injection of the n-phase load at node i, Respectively represent the apparent power injection of the load in star or delta connection; The expressions for the three basic types of active and reactive power of star-shaped loads connected to n nodes i are as follows; Three basic types of active and reactive power expressions for angular loads between phases n and m at node i.

4. The complete characterization method of the three-phase feasible region considering the unbalanced power grid system model according to claim 1, Features: The quotient gradient system in step 2 is: Among them, Q H (x) is a non-linear and non-hyperbolic dynamical system, and DH(x) is the Jacobian matrix of the system of equations H(x).

5. The complete characterization method of the three-phase feasible region considering the unbalanced power grid system model according to claim 1, Features: The specific implementation method of step 4 is: the three-phase parameter variables of the constraint set in step 2 are represented by the control variable u and the state variable y to obtain the active and reactive quantities u that can be regulated by the distributed power source and the flexible load. 1 The three-phase voltage amplitude of the balance node and the three-phase voltage amplitude of the generator node u 2 ,in is the active power output by the photovoltaic generator set connected to n nodes at node i, The reactive power output of the photovoltaic generator set at n phases of node i, The reactive power of the n-phase directly controllable load at node i, is the n-phase discharge power of the energy storage at node i, is the n-phase charging power of the energy storage at node i, is the voltage amplitude of phase n at the connection, The voltage amplitude of the wind turbine node n phase, Simplify the unbalanced system constraints in the constraint set: By adding the slack variable S, the inequality constraint in the unbalanced system constraint is transformed into an equality constraint, and the constraint equation H(x) is obtained:

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