Renewable energy consumption capability evaluation system and method of static voltage L index

Abstract

The invention relates to a renewable energy consumption capability evaluation system and method of a static voltage L index, and belongs to the technical field of power grid planning operation. Comprising the following steps: S1, establishing a static voltage stability L index to describe the voltage stability margin of the power system; s2, based on the actual operation characteristics of the power system, establishing a simplified model of an L index; s3, establishing a renewable energy consumption capability evaluation model objective function by taking maximization of renewable energy generation power as an objective; s4, establishing renewable energy source and conventional generator set power constraints; s5, establishing a power balance constraint of the renewable energy consumption capability evaluation model; s6, establishing an operation safety constraint of the renewable energy consumption capability evaluation model; s7, based on the index L, establishing an operation stability constraint of the renewable energy consumption capability evaluation model; and S8, solving the constructed renewable energy consumption capability evaluation model based on a primal dual interior point method to obtain a renewable energy consumption capability evaluation result. According to the invention, by introducing the static voltage stability L index, collaborative evaluation of the renewable energy consumption capability and the static voltage stability of the system is realized, and an effective tool is provided for planning and operation of the power system.

Description

TECHNICAL FIELD

[0001] The application relates to a static voltage L index renewable energy consumption capacity evaluation system and method, and belongs to the technical field of power grid planning and operation. BACKGROUND

[0002] With the transformation of global energy structure to clean, large-scale grid connection of renewable energy represented by wind power and photovoltaic has put forward higher requirements for the safe and stable operation of power systems. The intermittent and volatile characteristics of renewable energy are easy to cause system voltage instability risk, so accurate evaluation of the consumption capacity of power systems containing renewable energy and guarantee of voltage stability have become key technical problems.

[0003] In the prior art, related research has been carried out on the optimal dispatching and consumption capacity evaluation of power systems containing renewable energy. For example, a hydrogen energy storage power system optimal dispatching method considering static voltage stability is disclosed in patent publication No. CN115730698A. In the robust optimization framework, a hydrogen energy storage is used as a medium to establish an electric-hydrogen-gas comprehensive energy system. By coupling the power system and the gas network, static voltage stability constraints (based on L index) and power system flexibility constraints (including line load rate uniformity, flexibility supply and demand balance, etc.) are introduced. A double-layer optimization model is constructed to minimize the wind power reduction rate and carbon emissions, and a linearization method is used to process the nonlinear constraints for solving. The method suppresses the new energy anti-peaking characteristics through the dispatching capacity of hydrogen energy storage. The energy storage is discharged at the load low valley wind power peak period, and the load is discharged at the load high valley wind power low period. At the same time, the L index of each load node is limited in a reasonable range through power flow distribution, which improves the overall static voltage stability of the system and ensures the flexibility of system operation through the flexibility constraints.

[0004] However, the above-mentioned comparative method still has certain limitations: first, although the L index is introduced as a static voltage stability constraint, the L index is not used as a core parameter for consumption capacity evaluation, and the direct correlation mechanism between consumption capacity and voltage stability is not fully reflected; second, when dealing with uncertain factors such as renewable energy power fluctuation, although the robust optimization framework covers multiple scenarios, the evaluation result may be conservative due to the expansion of the uncertainty set range, affecting the accuracy of the consumption capacity; third, the coupling depth of the consumption capacity evaluation model and the voltage stability constraint is insufficient, and the synergistic mechanism of the two has not been systematically studied.

[0005] Therefore, how to construct an evaluation model taking the static voltage stability L index as the core constraint, accurately quantifying the influence of uncertainty, and deeply coupling the consumption capacity and voltage stability has become a technical problem to be solved in the high proportion of renewable energy grid connection scenarios. SUMMARY

[0006] The application aims to provide a static voltage L index renewable energy consumption capacity evaluation system and method, which takes the static voltage stability L index as the core constraint, accurately quantifies the influence of uncertainty, deeply couples the evaluation model of consumption capacity and voltage stability, and solves the technical problems urgently needed to be solved in the prior art.

[0007] The static voltage L index renewable energy consumption capacity evaluation method provided by the application comprises the following steps:

[0008] S1: Establish a static voltage stability L index to describe the voltage stability margin of the power system;

[0009] S2: Based on the actual operation characteristics of the power system, a simplified model of the L index is established;

[0010] S3: A renewable energy consumption capacity evaluation model objective function is established with the maximum renewable energy generation power as the target;

[0011] S4: Renewable energy and conventional generator power constraints are established;

[0012] S5: A power balance constraint of the renewable energy consumption capacity evaluation model is established;

[0013] S6: An operation safety constraint of the renewable energy consumption capacity evaluation model is established;

[0014] S7: Based on the L index, an operation stability constraint of the renewable energy consumption capacity evaluation model is established;

[0015] S8: The renewable energy consumption capacity evaluation model is solved based on the original dual interior point method to obtain the renewable energy consumption capacity evaluation result.

[0016] Preferably, in step S1, the specific process of establishing the static voltage stability L index comprises:

[0017] S11: The system nodes are divided into a load node set S l and a generator node set S g ;

[0018] S12: The system node voltage equation is arranged as:

[0019]

[0020] In the formula, I l and I g are the current vectors of all load nodes and all generator nodes respectively; V l and V g are the voltage vectors of all load nodes and all generator nodes respectively; Y ll , Ylg Y gl and Y gg are admittance matrix between load nodes, admittance matrix between load nodes and generator nodes, admittance matrix between generator nodes and load nodes and admittance matrix between generator nodes and generator nodes, respectively;

[0021] S13: Let Equations (2) and (3) are derived:

[0022]

[0023] In the formula, V and V represent voltage vector of load node j and generator node k, respectively; ji ∈Z ll (i,j∈S l ) represents element of the i-th row and the j-th column in the load impedance matrix; Z jk ∈Z lg (j∈S l ,k∈S g ) represents impedance between load node j and generator node k; Y jk ∈Y lg (j∈S l ,k∈S g ) represents admittance between load node j and generator node k;

[0024] S14: Define load participation factor matrix F lg = -Z ll Y lg , so as to define equivalent modified voltage

[0025]

[0026] In the formula, F jk is element of the j-th row and the k-th column in F lg ; S

[0027] S15: Introduce transformation admittance matrix transformed power and equivalent power correction amount wherein:

[0028]

[0029] In the formula, S j is complex power of load node j, and are conjugate of Z ij and Z jj , respectively, and and Substitute equation (3) into equation (7), we get equation (8)

[0030]

[0031] wherein, and are respectively conjugate of and

[0032] S16: Finally define the static voltage stability L index as:

[0033]

[0034] wherein, L j is the voltage stability index of node j.

[0035] Preferably, in step S2, the simplified model of L index is:

[0036] Remove the phase angle part of voltage in equation (8), get the preliminary simplified static stability L index:

[0037]

[0038] wherein, R ij and X ij are respectively resistance and reactance of line ij; P i and Q i are respectively active power and reactive power of node i; α L,j represents the set of load nodes connected to node j.

[0039] Considering that the reactance is much larger than the resistance in actual power system, according to the characteristics of actual power grid, equation (9) is further simplified as follows:

[0040]

[0041] wherein, L” j ∈(0,1), that is, the value of L index is kept between 0 and 1, when L j =1, the system is in the boundary state of static voltage instability, and the closer the L index is to zero, the higher the static voltage stability of the system.

[0042] Preferably, the objective function of step S3 is:

[0043] Maximize the renewable energy power as the objective function:

[0044] ​

[0045] where N p and N w are the total number of photovoltaic units and wind units, respectively; P i p is the active power of the ith photovoltaic unit; P i w is the active power of the ith wind unit.

[0046] Preferably, the power constraints of step S4 include:

[0047] (1) Renewable energy power constraints:

[0048]

[0049] where P and P are the theoretical maximum power generation of photovoltaic and wind power, respectively;

[0050] (2) Conventional generating unit power constraints:

[0051]

[0052] where P and P are the lower and upper limits of the active power of the conventional generating unit, respectively; and B are the lower and upper limits of the reactive power of the conventional generating unit, respectively.

[0053] Preferably, the power balance constraints of step S5 are:

[0054]

[0055] where N n is the total number of nodes of the system; and P are the active and reactive power generated by the conventional generating unit at node i; and P are the active and reactive load at node i; G ij and B ij are the real and imaginary parts of the admittance matrix at row i and column j; V i is the voltage amplitude at node i, and θ ij is the phase angle difference between the voltages at nodes i and j.

[0056] Preferably, the operational safety constraints of step S6 include:

[0057] (1) Transmission power constraints:

[0058]

[0059] wherein, Pijis the active power flowing from node i to node j; and Pminand Pmaxare the minimum and maximum active power allowed to flow through branch ij, respectively;

[0060] (2) Voltage magnitude constraint:

[0061]

[0062] wherein, and Vminand Vmaxare the minimum and maximum values of node voltage, respectively.

[0063] Preferably, the operation stability constraint of step S7 is:

[0064] 0≤L j ≤L MAX (17)

[0065]

[0066] wherein, L j is the simplified static voltage stability index of load node j in the system, and L MAX is the upper limit of the allowed static voltage stability index.

[0067] Preferably, in step S8, solving the constructed renewable energy consumption capacity evaluation model based on the primal-dual interior point method specifically includes the following:

[0068] S81: Establish a primal-dual interior point method mathematical model:

[0069] The constructed renewable energy consumption capacity evaluation model is a typical nonlinear programming problem, which is uniformly described in the following form:

[0070]

[0071] wherein, f(x) represents the objective function in the nonlinear programming, g(x) represents the equality constraint condition, and h(x) represents the inequality constraint condition, wherein x∈R N , N is the number of system nodes; h min , x min represents the lower bound of the inequality constraint and the control variable; h max , x max represents the upper bound of the inequality constraint and the control variable; the relaxation variable l, u>0, (l, u)∈R I , I is the number of inequality constraints; the above inequality constraint is rewritten as an equality constraint:

[0072]

[0073] Construct the Lagrange function:

[0074]

[0075] In the formula, y is in R E , E is the number of equality constraints;(z,w,μ l ,μ u ) is in R I ;(y,z,w) is a dual variable, also known as Lagrange multiplier;(l,u) is a relaxation variable;μ l And μ u Are barrier parameters;According to the perturbation KKT first-order optimality condition equation:

[0076]

[0077] In the formula, L, U, Z, W are diagonal matrices with l, u, z, w elements as diagonal elements;e is a unit column vector, e=[1,1,…,1] T In R I ;

[0078] S82: set the original network parameters;

[0079] S83: determine the initial value of the control variable;At the same time, ensure that the Lagrange multiplier vector y>0, z<0, w>0, the relaxation variable l<0, u>0;Set the convergence precision ε=1×10 -6 ; Set a suitable acceleration factor β;

[0080] S84: calculate the complementary gap Gap=l T z-u T w, if Gap<ε, output the optimal solution, and the optimization is finished;Otherwise, jump to S85;

[0081] S85: calculate the barrier function μ, solve equation (22) by Newton method to obtain the control variable increment;

[0082] S86: set the original and dual step length, correct the control variable, and jump to step S84.

[0083] The static voltage L index renewable energy consumption capacity evaluation system described in the application, comprising:

[0084] The index construction module is used for establishing a static voltage stability L index to describe the voltage stability margin of the power system.

[0085] The model simplification module is used for establishing a simplified model of the L index based on the actual operation characteristics of the power system.

[0086] A target function construction module is configured to construct a renewable energy consumption capacity evaluation model target function with the goal of maximizing renewable energy power generation;

[0087] A constraint condition construction module is configured to construct renewable energy and conventional generator unit power constraints, power balance constraints, operation safety constraints, and L-index-based operation stability constraints;

[0088] A solution module is configured to solve the constructed evaluation model based on a primal-dual interior point method to obtain a renewable energy consumption capacity evaluation result.

[0089] Compared with the prior art, the renewable energy consumption capacity evaluation system and method of static voltage L-index has the following beneficial effects:

[0090] 1. Establishing a direct correlation between L-index and consumption capacity: The L-index is used as the core constraint for consumption capacity evaluation in the present application, and through theoretical derivation and example verification, the dynamic balance law between the two is explicitly revealed. The static voltage stability L-index is embedded in the consumption capacity evaluation model as the core constraint, providing a decision-making tool for coordinating consumption capacity and voltage stability by adjusting the L-index limit.

[0091] 2. Improving engineering applicability: In view of the problem of complex and large calculation amount of the existing L-index model, the present application combines the actual operation characteristics of the power system and proposes a two-step simplification strategy. The simplified model retains the physical meaning of the L-index (the value range directly reflects the stability margin), while significantly reducing the calculation complexity, significantly improving the solving efficiency on the premise of ensuring the evaluation accuracy. It meets the real-time demand in engineering application.

[0092] 3. Avoiding evaluation conservatism: In view of the conservatism problem caused by the expansion of the uncertainty set in the existing robust optimization, the present application simplifies the L-index model and uses the high-efficiency solving capability of the primal-dual interior point method to dynamically adapt to the uncertainty such as renewable energy power fluctuation. The model can adjust the conventional unit power and power flow distribution according to the actual operation scene (such as the difference in voltage stability margin of different nodes and the change in renewable energy access position), ensuring that the L-index always meets the constraint while maximizing the consumption capacity. For example, in the verification of different access scenarios (such as significant improvement in consumption capacity when the stability of the weak node is accessed), the model can accurately reflect the actual consumption potential, avoiding the conservative conclusion of "one-size-fits-all", and improving the matching degree between the evaluation result and the actual operation.

[0093] 4. Guidance for renewable energy site selection: The application reveals the internal correlation characteristics of "consumption-stability" by analyzing the influence law of different L index thresholds and renewable energy access locations on consumption capacity (such as access to weak stability nodes can significantly improve consumption capacity), which provides a direct basis for the optimization of renewable energy site selection (preferably access to weak stability nodes to improve consumption capacity) and operation mode adjustment (dynamic allocation of power flow according to L index threshold), supporting the fine planning and operation decision of new power system.

[0094] 5. Provide a clear stability reference: The L index value range (0-1) directly reflects the system voltage stability margin (closer to 0, more stable), providing a clear quantitative reference for operating personnel to adjust the constraint threshold according to actual needs (such as emergency consumption or stability preservation).

[0095] In summary, the application effectively solves the technical problem of coordinated evaluation of consumption capacity and voltage stability in high-proportion renewable energy grid-connected scenarios, providing key technical support for power system planning and operation. BRIEF DESCRIPTION OF DRAWINGS

[0096] Figure 1 The flowchart of the steps of the method of the application;

[0097] Figure 2 The power grid structure used in the embodiment of the application;

[0098] Figure 3 The structure block diagram of the system of the application. DETAILED DESCRIPTION

[0099] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, not all.

[0100] Embodiment 1:

[0101] The embodiment discloses a renewable energy consumption capacity evaluation method of static voltage L index, including the following steps:

[0102] As shown in Figure 1 The renewable energy consumption capacity evaluation method of static voltage stability L index in the embodiment of the application includes the following steps:

[0103] S1: Establish a static voltage stability L index to describe the voltage stability margin of the power system;

[0104] S2: Based on the actual operation characteristics of the power system, a simplified model of the L index is established;

[0105] S3: Establishing a renewable energy consumption capacity evaluation model objective function with the goal of maximizing renewable energy power generation;

[0106] S4: Establishing renewable energy and conventional generator power constraints;

[0107] S5: Establishing power balance constraints of the renewable energy consumption capacity evaluation model;

[0108] S6: Establishing operation safety constraints of the renewable energy consumption capacity evaluation model;

[0109] S7: Establishing operation stability constraints of the renewable energy consumption capacity evaluation model based on L index;

[0110] S8: Solving the renewable energy consumption capacity evaluation model constructed based on the original dual interior point method to obtain the renewable energy consumption capacity evaluation result.

[0111] Further, in step S1, the static voltage stability L index describing the voltage stability margin of the power system is constructed as follows:

[0112] First, the nodes of the system are divided into two parts, i.e., load nodes and generator nodes:

[0113] 1) The set S of all load nodes l ;

[0114] 2) The set S of all generator nodes g . The node voltage equations of the system are arranged according to the grouping as follows:

[0115]

[0116] In the formula, I l and I g are the current vectors of all load nodes and all generator nodes, respectively; V l and V g are the voltage vectors of all load nodes and all generator nodes, respectively; Y ll , Y lg , Y gl and Y gg are the admittance matrices between load nodes, between load nodes and generator nodes, between generator nodes and load nodes, and between generator nodes and generator nodes, respectively.

[0117] Let Equations (2) and (3) are obtained:

[0118]

[0119] In the formula, and generator node k voltage vectors, respectively; denotes the current vector of load node i; Z ji ∈Z ll (i,j∈S l ) denotes the element of the load impedance matrix in the i-th row and j-th column; Z jk ∈Z lg (j∈S l ,k∈S g ) denotes the impedance between load node j and generator node k; Y jk ∈Y lg (j∈S l ,k∈S g ) denotes the admittance between load node j and generator node k.

[0120] Define the load participation factor matrix F lg = -Z ll Y lg , so as to define the equivalent correction voltage

[0121]

[0122] In the formula, F jk is the element of the j-th row and k-th column in F lg .

[0123] Introduce the transformed admittance matrix Convert the power and the equivalent power correction amount Wherein:

[0124]

[0125] In the formula, S j is the complex power of load node j. Bring Flg、 and into formula (3), and formula (7) is obtained

[0126]

[0127] Further, define the static voltage stability L index as:

[0128]

[0129] Further, in step S2, a simplified model of the L index is established based on the actual operation characteristics of the power system as follows:

[0130] The change of load in the power system has little effect on the node phase angle difference. By removing the phase angle part of the voltage in formula (8), a preliminary simplified static stability L index is obtained:

[0131]

[0132] Among them, R ij and X ij are the resistance and reactance of line ij respectively; P i and Q i are the active power and reactive power of node i respectively; α L,j represents the set of load nodes connected to node j;

[0133] Considering that the reactance in the actual power system is much larger than the resistance, the equation (9) is further simplified according to the characteristics of the actual power grid as follows:

[0134]

[0135] L j ∈(0,1), that is, the value of the L index remains between 0 and 1. When the L index is used as an indicator to measure the static voltage stability of the system, when L j =1, the system is in a boundary state of static voltage instability, and the closer the L index is to zero, the higher the static voltage stability of the system.

[0136] In step S3, the objective function of the renewable energy absorption capacity evaluation model is established as follows:

[0137] Maximizing renewable energy power is used as the objective function:

[0138]

[0139] Where N p and N w are the total number of photovoltaic units and wind turbine units in the system respectively; P i p is the active power of the i-th photovoltaic unit; P i w is the active power of the i-th wind turbine.

[0140] Furthermore, in step S4, the power constraints of renewable energy and conventional generators for establishing the renewable energy absorption capacity assessment model are as follows:

[0141] 1) Renewable energy power constraints

[0142]

[0143] Where, and The theoretical maximum power generation of photovoltaic power generation and wind power generation, respectively.

[0144] 2) Active power constraint of conventional generator set

[0145]

[0146] wherein, and are the lower and upper limits of active power of the conventional generator set, respectively; and are the lower and upper limits of reactive power of the conventional generator set, respectively.

[0147] Further, in step S5, the power balance constraint of the renewable energy consumption capacity evaluation model is established as follows:

[0148]

[0149] wherein, N n is the total number of nodes of the system; and are the active power and reactive power generated by the conventional generator set of node i, respectively; and are the active load and reactive load of node i, respectively; G ij and B ij are the real part and imaginary part of the i-row and j-column of the node admittance matrix, respectively; V i is the voltage amplitude of node i, and θ ij is the phase angle difference of the voltage between nodes i and j.

[0150] In step S6, the operation safety constraint of the renewable energy consumption capacity evaluation model is established as follows:

[0151] 1) Transmission power constraint

[0152]

[0153] wherein, is the active power flowing from node i to node j; and are the minimum and maximum active power allowed to flow through branch i-j, respectively.

[0154] 2) Node voltage amplitude constraint

[0155]

[0156] wherein, and are the minimum and maximum values of the node voltage, respectively.

[0157] Furthermore, in step S7, the operation stability constraints of the renewable energy absorption capacity evaluation model are established based on the L index as follows:

[0158] 0≤L j ≤L MAX (17)

[0159]

[0160] Where, L j is the simplified static voltage stability index of load node j in the system.

[0161] Furthermore, in step S8, the constructed renewable energy absorption capacity evaluation model considering the static voltage stability L index is solved based on the primal-dual interior point method as follows:

[0162] Step 801: Establish a primal-dual interior point method mathematical model:

[0163] The constructed renewable energy absorption capacity assessment model considering the static voltage stability L index is a typical nonlinear programming problem, which can be uniformly described in the following general form:

[0164]

[0165] Where f(x) represents the objective function in nonlinear programming, g(x) represents the equality constraint, and h(x) represents the inequality constraint, where x∈R N , N is the number of system nodes; h min , x min represents the lower bound of the inequality constraint and the control variable; h max , x max Indicates the upper bound of the inequality constraint and the control variable. Introduce slack variables l,u>0,(l,u)∈R I , I is the number of inequality constraints; rewrite the above inequality constraints into equality constraints:

[0166]

[0167] Construct the Lagrangian function:

[0168]

[0169] Where y∈R E , E is the number of equality constraints; (z,w,μ l ,μ u )∈R I ; (y, z, w) are dual variables, also known as Lagrange multipliers; (l, u) are slack variables; μ l and μ uThe barrier function is a barrier parameter. According to the perturbed Karush-Kuhn-Tucker (Perturbed Karush-Kuhn-Tucker) first-order optimality condition equation:

[0170]

[0171] In the formula, L, U, Z, W are diagonal matrices with l, u, z, w as diagonal elements respectively; e is a unit column vector, e = [1, 1, …, 1] T ∈R I .

[0172] Step 802: setting the original network parameters;

[0173] Step 803: initialization. Determine the initial value of the control variable; at the same time, ensure that the Lagrange multiplier vector y>0, z<0, w>0, the relaxation variable l<0, u>0; set the convergence precision ε = 1 × 10 -6 ; set a suitable acceleration factor β;

[0174] Step 804: calculate the complementary gap Gap = l T z-u T w. If Gap < ε, output the optimal solution, and the optimization is completed; otherwise, jump to step 805;

[0175] Step 805: calculate the barrier function μ, solve equation (22) by Newton method to obtain the control variable increment;

[0176] Step 806: set the original and dual step length, correct the control variable, and jump to step 804.

[0177] The above method can evaluate the renewable energy consumption capacity while considering the system static voltage stability problem, use the static voltage stability L index to judge whether the system can maintain static voltage stability while evaluating the renewable energy consumption capacity, and can give the static voltage stability margin of the system, and provide reference value for the renewable energy consumption capacity evaluation problem under the new type of power system.

[0178] To verify the effectiveness of the present application, the following specific application examples are as follows:

[0179] In this embodiment, the improved IEEE30 node power transmission network example is selected, on the basis of the original system, the photovoltaic power plant is set at the 5th node, and the wind power plant is set at the 28th node, as shown in Figure 2 The relevant boundary condition setting is shown in Table 1. The node number and the corresponding parameters of the line are shown in Table 1.

[0180] Table 1 Boundary condition setting of the embodiment

[0181]

[0182]

[0183] In order to better reflect the characteristics of the solving strategy of the renewable energy consumption capacity evaluation model considering static voltage stability L index based on the original dual interior point method constructed by the present application, three main control groups are set in the present embodiment, which are as follows:

[0184] Control group 1: comparison between the present application and the traditional consumption model

[0185] Model 1: consumption model considering L index, which is the renewable energy consumption capacity evaluation model considering L index established by the present application, wherein L max = 0.4 in the static voltage stability L index constraint.

[0186] Model 2: traditional consumption model, which is the consumption model established by the present application without considering static voltage stability constraint, i.e. ignoring equation (18).

[0187] The voltage comparison between the consumption model considering L index and the traditional consumption model is as follows:

[0188] Table 2: voltage amplitude comparison of control group 1

[0189]

[0190]

[0191] The comparison of the consumption situation after evaluation between the consumption model considering L index and the traditional consumption model is as follows:

[0192] Table 3: comparison of consumption situation of control group 1

[0193]

[0194] The total consumption of the system in the consumption model considering L index is 3.5583 p.u., and the consumption rate is 84.72%; the consumption of the system in the traditional consumption model is 3.8919 p.u., and the consumption rate is 92.66%. Through the comparison of the data in Table 2 and Table 3, it can be seen that when considering L index, due to the limitation of L index, the consumption level of the system will be greatly reduced.

[0195] Control group 2: comparison of consumption situations under different static voltage stability constraint boundaries of the present application

[0196] Based on the consumption model considering L index set by the present application, L max is adjusted, and the consumption model under different L max is solved by the above solving strategy. The comparison of the consumption situations under different L max is as follows:

[0197] Table 4 different L max The accommodation situation under the setting

[0198]

[0199]

[0200] Control group 3: renewable energy site selection and static voltage stability and the relationship between renewable energy accommodation capacity

[0201] By setting different renewable energy access scenarios, the influence of different renewable energy access scenarios on L index and accommodation capacity is analyzed, and L max = 0.40, the installed capacity of photovoltaic generator is 2.0000 p.u., and the installed capacity of wind turbine generator is 2.2000 p.u.

[0202] Table 5 accommodation capacity under the setting of control group 3 scenario

[0203] Scenario Photovoltaic access node Wind power access node Photovoltaic curtailment Wind power curtailment Total curtailment Scenario 1 4 15 2.0000 p.u. 1.4658 p.u. 3.4658 p.u. Scenario 2 15 4 1.4229 p.u. 2.2000 p.u. 3.6229 p.u. Scenario 3 14 29 0.8220 p.u. 0.4467 p.u. 1.2687 p.u. Scenario 4 29 14 0.4467 p.u. 0.8235 p.u. 1.2702 p.u. Scenario 5 15 14 0.9015 p.u. 0.6202 p.u. 1.5217 p.u. Scenario 6 14 15 0.4561 p.u. 1.1235 p.u. 1.5796 p.u.

[0204] According to the set accommodation scenario, the accommodation model considering the L index is used for calculation and analysis, and the accommodation situation of the above six scenarios is shown in Table 5. In scenario 1 and scenario 2, renewable energy is accessed in the two nodes with the highest L index (i.e. the weakest static voltage stability) under the traditional model analysis; in scenario 3 and scenario 4, renewable energy is accessed in the two nodes with the lowest L index (i.e. the strongest static voltage stability) under the traditional model analysis; and in scenario 5 and scenario 6, renewable energy is accessed in the two nodes with the highest and lowest L index of the system.

[0205] Conclusion: When renewable energy is accessed in the nodes with weak static voltage stability (such as scenario 1 and scenario 2), the accommodation capacity is higher (3.4658-3.6229 p.u.); and when renewable energy is accessed in the nodes with strong stability (such as scenario 3 and scenario 4), the accommodation capacity is significantly reduced (1.2687-1.2702 p.u.). It shows that the application can guide the optimal site selection of renewable energy, and preferentially access in the nodes with weak stability to improve the accommodation capacity.

[0206] In summary, by introducing the static voltage stability L index, the application realizes the coordinated evaluation of renewable energy accommodation capacity and system static voltage stability, and provides an effective tool for the planning and operation of new power systems.

[0207] After calculation and analysis by the accommodation model considering the L index, when renewable energy is accessed in the nodes with the weakest static voltage stability, the accommodation capacity of the system is strong; and when renewable energy is accessed in the nodes with the strongest static voltage stability, the accommodation capacity of renewable energy is significantly reduced.

[0208] Embodiment 2:

[0209] As shown in the figure, the renewable energy consumption capacity evaluation system of the static voltage L index of the application comprises: Figure 3

[0210] An index construction module is configured to establish a static voltage stability L index to describe the voltage stability margin of the power system.

[0211] A model simplification module is configured to establish a simplified model of the L index based on the actual operation characteristics of the power system.

[0212] A target function construction module is configured to maximize the renewable energy generation power as the target to establish a renewable energy consumption capacity evaluation model target function.

[0213] A constraint condition construction module is configured to establish renewable energy and conventional generator power constraints, power balance constraints, operation safety constraints and operation stability constraints based on the L index.

[0214] A solution module is configured to solve the constructed evaluation model based on the original dual interior point method to obtain the renewable energy consumption capacity evaluation result.

[0215] The system of the embodiment is based on the method in embodiment 1, and realizes the coordinated evaluation of the renewable energy consumption capacity and the static voltage stability of the system, thereby providing an effective tool for the planning and operation of the power system.

[0216] The above is only the preferred specific implementation of the application, but the protection scope of the application is not limited to this, any person skilled in the art can make equivalent replacement or change according to the technical solution and the inventive concept of the application within the technical range disclosed by the application, which should be covered in the protection scope of the application.​

Claims

1. A method for evaluating renewable energy absorption capacity based on static voltage L index, characterized in that: The steps include: S1: Establish a static voltage stability index L to describe the voltage stability margin of the power system; S2: Based on the actual operating characteristics of the power system, a simplified model of the L index is established; S3: With the goal of maximizing renewable energy power generation, establish the objective function of the renewable energy absorption capacity evaluation model; S4: Establish power constraints for renewable energy and conventional generators; S5: Establish power balance constraints for renewable energy absorption capacity assessment models; S6: Establish operational safety constraints for renewable energy absorption capacity assessment models; S7: Based on the L index, establish the operational stability constraints of the renewable energy absorption capacity evaluation model; S8: Solve the constructed renewable energy absorption capacity assessment model based on the primal-dual interior point method to obtain the renewable energy absorption capacity assessment results.

2. The method for evaluating renewable energy absorption capacity based on the static voltage L index according to claim 1, characterized in that: In step S1, the specific process of establishing the static voltage stability L index includes: S11: Divide the system nodes into load node sets S l and the generator node set S g ; S12: Arrange the system node voltage equations as: Where, I l and I g are the current vectors of all load nodes and all generator nodes respectively; V l and V g are the voltage vectors of all load nodes and all generator nodes respectively; Y ll ,Y lg ,Y gl and Y gg They are respectively the admittance matrix between load nodes, the admittance matrix between load nodes and generator nodes, the admittance matrix between generator nodes and load nodes, and the admittance matrix between generator nodes and generator nodes; S13: Order Formula (2) and formula (3) are obtained: Where, denote the voltage vectors of load node j and generator node k respectively; represents the current vector of load node i; Z ji ∈Z ll (i,j∈S l ) represents the element in the jth row and ith column of the load impedance matrix; Z jk ∈Z lg (j∈S l ,k∈S g ) represents the impedance between the load node j and the generator node k; Y jk ∈Y lg (j∈S l ,k∈S g ) represents the admittance between load node j and generator node k; S14: Define the load participation factor matrix F lg =-Z ll Y lg , thereby defining the equivalent correction voltage Where, F jk F lg The element at row j and column k in ; S15: Introducing the Transformation Admittance Matrix Conversion power and equivalent power correction in: Where S j is the complex power of load node j, and Z ij and Z jj The conjugate of and Substituting into formula (3), we get formula (7) in, and For and conjugation of; S16: The static voltage stability L index is finally defined as: Among them, L j is the voltage stability index of node j.

3. The method for evaluating renewable energy absorption capacity based on the static voltage L index according to claim 2, characterized in that: In step S2, the simplified model of the L indicator is: Removing the phase angle of the voltage in equation (8) yields a simplified static stability L index: Among them, R ij and X ij are the resistance and reactance of line ij respectively; P i and Q i are the active power and reactive power of node i respectively; α L,j represents the set of load nodes connected to node j; Considering that the reactance in the actual power system is much larger than the resistance, the equation (9) is further simplified according to the characteristics of the actual power grid as follows: Among them, L" j ∈(0,1), that is, the value of the L index is kept between 0 and 1. When the L index is used as an indicator to measure the static voltage stability of the system, when L j =1, the system is in a boundary state of static voltage instability, and the closer the L index is to zero, the higher the static voltage stability of the system.

4. The method for evaluating renewable energy absorption capacity based on the static voltage L index according to claim 3 is characterized in that: The objective function of step S3 is: Maximizing renewable energy power is used as the objective function: Where N p and N w are the total number of photovoltaic units and wind turbine units in the system respectively; P i p is the active power of the i-th photovoltaic unit; P i w is the active power of the i-th wind turbine.

5. The method for evaluating renewable energy absorption capacity based on the static voltage L index according to claim 4 is characterized in that: The power constraint in step S4 includes: (1) Renewable energy power constraints: Where, and are the theoretical maximum power generation of photovoltaic power generation and wind power generation respectively; (2) Power constraints of conventional generator sets: Where, and They are respectively the lower and upper limits of active power of conventional generator sets; and They are the lower and upper limits of reactive power of conventional generator sets respectively.

6. The method for evaluating renewable energy absorption capacity based on the static voltage L index according to claim 5, characterized in that: The power balance constraint in step S5 is: Where N n is the total number of nodes in the system; P i g and are the active power and reactive power generated by the conventional generator set at node i; P i l and are the active load and reactive load of node i respectively; G ij and B ij are the real and imaginary parts of the node admittance matrix in row i and column j, respectively; V i is the voltage amplitude at node i, θ ij is the phase angle difference of the voltage between nodes ij.

7. The method for evaluating renewable energy absorption capacity based on the static voltage L index according to claim 6, characterized in that: The operational safety constraints of step S6 include: (1) Transmission power constraints: Where, is the active power flowing from node i to node j; and are the minimum and maximum active powers allowed to flow through branch ij respectively; (2) Voltage amplitude constraint: In i min ≤V i ≤V i max (16) Where, and are the minimum and maximum values ​​of the node voltage, respectively.

8. The method for evaluating renewable energy absorption capacity based on the static voltage L index according to claim 7, characterized in that: The operational stability constraint of step S7 is: 0≤L j ≤L MAX (17) Where, L j is the simplified static voltage stability index of load node j in the system, L MAX It is the upper limit of the static voltage stability index allowed.

9. The method for evaluating renewable energy absorption capacity based on the static voltage L index according to any one of claims 1 to 8, characterized in that: In step S8, solving the constructed renewable energy absorption capacity assessment model based on the primal-dual interior point method specifically includes the following steps: S81: Establish the mathematical model of the primal-dual interior point method: The constructed renewable energy absorption capacity assessment model is a typical nonlinear programming problem, which can be described in the following form: Where f(x) represents the objective function in nonlinear programming, g(x) represents the equality constraint, and h(x) represents the inequality constraint, where x∈R N , N is the number of system nodes; h min , x min represents the lower bound of the inequality constraint and the control variable; h max , x max Indicates the upper bound of the inequality constraints and control variables; introduces slack variables l,u>0,(l,u)∈R I , I is the number of inequality constraints; rewrite the above inequality constraints into equality constraints: Construct the Lagrangian function: Where y∈R E , E is the number of equality constraints; (z,w,μ l ,μ u )∈R I ; (y, z, w) are dual variables, also known as Lagrange multipliers; (l, u) are slack variables; μ l and μ u is the barrier parameter; according to the perturbation KKT first-order optimality condition equation: Where L, U, Z, and W are diagonal matrices with the elements of l, u, z, and w as diagonal elements respectively; e is the unit column vector, e = [1, 1, ..., 1] T ∈R I ; S82: Set original network parameters; S83: Determine the initial value of the control variable; at the same time, ensure that the Lagrange multiplier vector y>0, z<0, w>0, and the slack variables l<0, u>0; set the convergence accuracy ε=1×10 -6 ; Set the appropriate acceleration factor β; S84: Calculate the complementary gap Gap=l T zu T w, if Gap<ε, output the optimal solution and the optimization ends; otherwise jump to S85; S85: Calculate the barrier function μ and solve equation (22) using Newton's method to obtain the control variable increment; S86: Set the primal and dual step sizes, modify the control variables, and jump to step S84.

10. A system for evaluating renewable energy absorption capacity based on a static voltage L index, based on the method for evaluating renewable energy absorption capacity based on a static voltage L index according to any one of claims 1 to 9, characterized in that: include: An indicator construction module is used to establish a static voltage stability L indicator to describe the voltage stability margin of the power system; Model simplification module, used to establish a simplified model of the L index based on the actual operating characteristics of the power system; An objective function building module is used to establish an objective function for the renewable energy absorption capacity evaluation model with the goal of maximizing renewable energy power generation; Constraint construction module, used to establish power constraints of renewable energy and conventional generators, power balance constraints, operation safety constraints and operation stability constraints based on L indicators; The solution module is used to solve the constructed evaluation model based on the primal-dual interior point method to obtain the evaluation results of renewable energy absorption capacity.

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