Method and system for weak node detection and instability index establishment of new power system

Abstract

The weak node detection and instability index establishment method and system of the new power system map the linkage relationship between the oscillation characteristic samples to different value ranges of the equivalent impedance angle of the inverter, and the relationship between the actual value of the equivalent impedance angle of the inverter and the different value ranges of the equivalent impedance angle of the inverter mapped is used to constitute the stability criterion of the new power system; the node whose power flow entropy weak index is not less than the set threshold value is used as the weak node; under the constraint conditions of the power angle, the voltage, the frequency and the impedance angle, the coupling relationship among the power angle stability margin, the voltage stability margin, the frequency stability margin and the impedance angle stability margin is used to establish a multi-dimensional stability margin space; the actual value of the equivalent impedance angle of the inverter and the equivalent output impedance amplitude of the inverter are used to construct the stability margin index of the weak node; when the stability margin index of the weak node exceeds the multi-dimensional stability margin space, the instability of the new power system is determined.

Description

Technical Field

[0001] This invention belongs to the field of power system stability detection technology, specifically, it relates to a novel method and system for detecting weak nodes and establishing instability indicators in power systems. Background Technology

[0002] In recent years, the technology for identifying instability conditions in novel power systems has received increasing attention. Due to the high proportion of new energy sources and power electronic equipment in novel power systems, they exhibit various types of disturbances during actual operation, constantly affecting their stability. All kinds of disturbances impact both the novel power system and its stability. Existing technologies for identifying instability conditions in novel power systems mainly focus on the system's structure, load characteristics, and power electronic equipment, proposing a series of instability condition identification methods. For example, methods based on complex network theory quickly determine whether instability exists by analyzing the complex structure and inter-node relationships of the novel power system. In addition, methods based on load characteristics analyze the patterns of load changes to determine whether instability risks exist. Furthermore, methods analyze the operating states and control strategies of power electronic equipment to determine whether instability exists. In this area of ​​identifying instability conditions in novel power systems, different types of evaluation indicators have been proposed for network structures with different characteristics. Current evaluation methods mainly focus on the stability analysis and control strategies of novel power systems, proposing various instability condition identification methods and algorithms. For example, frequency domain analysis-based instability condition identification methods can determine whether a new power system exhibits instability by analyzing its frequency response characteristics. Traditional power systems suffer from voltage-power angle-frequency stability combined with broadband oscillation stability, where the dominant instability factors are interdependent, making effective identification difficult. Existing stability analysis techniques primarily focus on the stability analysis and control strategies of new power systems, proposing various instability condition identification methods and algorithms. These include frequency domain analysis-based, control strategy-based, and model predictive control-based methods. However, current models and methods still fall short of meeting the comprehensive needs for analyzing the dominant instability factors in such new power systems in terms of coverage of research objects, multidimensionality of model time scales, effectiveness of computational methods, and accuracy of evaluation indicators. Because the dominant instability factors are interdependent and difficult to identify effectively, more effective instability identification techniques are needed. Regarding weak node identification, among current methods, reliability tracking can identify weak nodes in the system from a reliability perspective. In terms of identification capabilities, the reliability tracking method can point out that a component is weak, but it cannot pinpoint which specific aspect of the component (capacity, failure rate, or repair rate, etc.) is the main cause of the node's weakness. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a novel method and system for detecting weak nodes and establishing instability indicators in power systems. This enables the quantitative identification of weak links in novel power systems. Starting from the transient and stable energy transfer laws of the system, it analyzes the instability relationship between voltage, frequency, power angle, and dynamic impedance, and proposes an analytical strategy for the dominant instability factors of novel power systems.

[0004] The present invention adopts the following technical solution.

[0005] This invention proposes a novel method for detecting weak nodes and establishing instability indicators in power systems, comprising:

[0006] Oscillation characteristic samples of historical oscillation accidents are obtained, and the linkage between the oscillation characteristic samples is mapped to different ranges of the equivalent impedance angle of the inverter. The relationship between the actual value of the equivalent impedance angle of the inverter and the different ranges of the equivalent impedance angle of the inverter obtained by mapping is used to construct a new power system stability criterion.

[0007] Based on a novel power system stability criterion, when the system is determined to be in an unstable state, the proportion of the power flow impact on a branch connected to a node in the total power flow impact received by the node is obtained as the power flow transfer ratio of the node to that branch. Based on the information entropy model, the power flow distribution entropy of the node is determined by using the power flow transfer ratio of the node to each branch. The node branch power flow channel variable is introduced, and the power flow entropy weakness index of the node is determined by using the total power flow impact received by the node and the power flow distribution entropy of the node. Nodes whose power flow entropy weakness index is not less than a set threshold are identified as weak nodes.

[0008] Based on the generator rotor motion equation and the equivalent second-order power angle / frequency equation of the inverter, an energy mapping model of the system's power angle, voltage, frequency, and impedance angle is established. Using oscillation characteristic samples, the constraints of power angle, voltage, frequency, and impedance angle are determined. Under the constraints of power angle, voltage, frequency, and impedance angle, a multi-dimensional stability margin space is established by utilizing the coupling relationship between power angle stability margin, voltage stability margin, frequency stability margin, and impedance angle stability margin.

[0009] By using the actual value of the inverter's equivalent impedance angle and the amplitude of the inverter's equivalent output impedance, a stability margin index for weak nodes is constructed.

[0010] When the stability margin index of a weak node exceeds the multi-dimensional stability margin space, the new power system is deemed to be unstable.

[0011] Preferably, the oscillation characteristic samples include: the active and reactive power output by the inverter, the output voltage and current, and the combined impedance angle of the inverter and the line;

[0012] The phase angle of the sum of the inverter's equivalent output impedance and the line impedance is used as the combined impedance angle of the inverter and the line, satisfying the following relationship:

[0013]

[0014] In the formula, θ is the combined impedance angle of the inverter and the line, R is the sum of the equivalent output resistance of the inverter and the line resistance, and X is the sum of the equivalent output reactance of the inverter and the line reactance.

[0015] Preferably, based on the oscillation characteristic samples, the linkage between the active power P and reactive power Q output by the inverter, the output voltage U1 and current I1, and the combined impedance angle θ of the inverter and the line is mapped to different ranges of the inverter's equivalent impedance angle, using the actual value of the inverter's equivalent impedance angle. The relationship between the value range of the equivalent impedance angle of the inverter obtained by mapping and the value range of different values ​​constitutes a new power system stability criterion, including:

[0016] 1) When the linkage relationship is P↑→Q↓→U1↑→I1↓→θ↑→Q↑, if When the linkage is P↓→Q↑→U1↓→I1↑→θ↓→Q↓, if If the new power system is stable, then it is determined to be stable.

[0017] 2) When the linkage relationship is P↑→Q↓→U1↑→I1↓→θ↓→Q↓, if When the linkage is P↓→Q↑→U1↓→I1↑→θ↑→Q↑, if If this occurs, the new power system is deemed unstable.

[0018] 3) When the linkage relationship is P↑→Q↓→U1↑→I1↓→θ↓→Q↑, if When the linkage is P↓→Q↑→U1↓→I1↑→θ↑→Q↓, if If the new power system is stable, then it is determined to be stable.

[0019] 4) When the linkage relationship is P↑→Q↓→U1↓→I1↑→θ↑→Q↓, if When the linkage is P↓→Q↑→U1↑→I1↓→θ↓→Q↑, if If this occurs, the new power system is deemed unstable.

[0020] 5) When the linkage relationship is P↑→Q↓→U1↓→I1↑→θ↓→Q↑, if When the linkage is P↓→Q↑→U1↑→I1↓→θ↑→Q↓, if If the new power system is stable, then it is determined to be stable.

[0021] 6) When the linkage relationship is P↑→Q↓→U1↓→I1↑→θ↓→Q↓, if When the linkage is P↓→Q↑→U1↑→I1↓→θ↑→Q↑, if If this occurs, the new power system is deemed unstable.

[0022] In this context, the symbol ↑ indicates an increase in the oscillation feature sample, the symbol ↓ indicates a decrease in the oscillation feature sample, and a change in the oscillation feature sample to the left of the symbol → will trigger a change in the oscillation feature sample to the right of the symbol →.

[0023] Preferably, the power flow transfer ratio of node a to branch i satisfies the following relationship:

[0024]

[0025] In the formula, Let ΔP be the power flow transfer ratio from node a to branch i. i Let ΔP be the power flow impulse on branch i connected to node a, where i = 1, 2, 3, ..., N, and N is the total number of branches. a Let be the total power flow impact on node a;

[0026] The power flow distribution entropy of node a satisfies the following relationship:

[0027]

[0028] In the formula, Let be the power flow distribution entropy of node a;

[0029] The power flow entropy weakness index of node a satisfies the following relationship:

[0030]

[0031] In the formula, H P (a) is the weak index of power flow entropy at node a, C n For node branch power flow channel variables.

[0032] Preferably, the threshold value range is set to [0,1]. The weak index of power flow entropy of all nodes in the system is calculated and compared with the set threshold. When the number of nodes with a weak index of power flow entropy greater than the set threshold accounts for 10% of the total number of nodes in the system, the optimal set threshold is obtained, and these 10% of nodes are regarded as weak nodes.

[0033] Preferably, based on the generator rotor motion equation and the inverter's equivalent second-order power angle / frequency equation, the active power model of node a satisfies the following relationship:

[0034] P e =ΔP δ (V a ,δ a )+ΔP θ (V a ,θ a )+ΔP δ,θ (V a ,δ a ,θ a )

[0035] In the formula, ΔP δ (V a ,δ a ) is node a, which is determined by voltage V a and work angle δ a The resulting power change, ΔP θ (V a ,θ a ) is node a, which is determined by voltage V a and impedance angle θ a The resulting power change, ΔP δ,θ (V a ,δ a ,θ a ) is node a, which is determined by voltage V a δ a and impedance angle θ a The resulting change in power;

[0036] Based on the active power at node a, the Popov method is used to establish an energy mapping model of the system's power angle, voltage, frequency, and impedance angle, satisfying the following relationships:

[0037] V = ΔV m (δ m V m ,f m ,θ m )+ΔV r (δ r V r ,f r ,θ r )+ΔV e (δe V e ,f e ,θ e )+ΔV L (δ L V L ,f L ,θ L )

[0038] In the formula, V is the energy mapping function of the new power system, ΔV m (δ m V m ,f m ,θ m () represents the synchronous generator m with respect to the power angle δ m Voltage V m Frequency f m Impedance angle θ m Energy mapping function, m = 1, 2, ..., N m N m ΔV represents the total number of synchronous generators in the system. r (δ r V r ,f r ,θ r ) represents the inverter r with respect to the power angle δ r Voltage V r Frequency f r Impedance angle θ r The energy mapping function, r = 1, 2, ..., N r N r ΔV represents the total number of inverters in the system. e (δ e V e ,f e ,θ e ) is the system network at the power angle δ e Voltage V e Frequency f e Impedance angle θ e Energy mapping function; ΔV L (δ L V L ,f L ,θ L ) represents the load L with respect to the power angle δ L Voltage V L Frequency f L Impedance angle θ L The energy mapping function, L = 1, 2, ..., N L N L This represents the total load within the system.

[0039] Preferably, based on the energy mapping model of the system's power angle, voltage, frequency, and impedance angle, the constraints of the power angle, voltage, frequency, and impedance angle are obtained using oscillation characteristic samples, including:

[0040] 1) Nonlinear constraints between the power angle and the synchronous generator rotor angular potential energy, inverter equivalent potential energy, line inductance and / or capacitor potential energy.

[0041] 2) Nonlinear constraints between voltage and the potential energy of line inductance and / or capacitance, energy dissipated by resistance, and potential energy of constant power and / or constant impedance loads.

[0042] 3) Nonlinear constraints between frequency and synchronous generator rotor kinetic energy, inverter equivalent kinetic energy, constant power and / or constant impedance load potential energy.

[0043] 4) Nonlinear constraints between the impedance angle and the potential energy of the inverter filter inductor and / or capacitor, the potential energy of the line inductor and / or capacitor, and the energy dissipated by the resistor.

[0044] Preferably, under the constraints of power angle, voltage, frequency, and impedance angle, a multi-dimensional stability margin space is established by utilizing the coupling relationship between the power angle stability margin, voltage stability margin, frequency stability margin, and impedance angle stability margin, satisfying the following relationship:

[0045] SP(δ,V,f,θ)=P{SP(δ),SP(V),SP(f),SP(θ)}

[0046] In the formula, SP(δ,V,f,θ) is the multi-dimensional stability margin space of the new power system, and P{} is the coupling relationship function between the power angle stability margin SP(δ), voltage stability margin SP(V), frequency stability margin SP(f), and impedance angle stability margin SP(θ).

[0047] The constraints of the multi-dimensional stability margin space of the new power system satisfy the following relationship:

[0048] δ min ≤δ≤δ max

[0049] V min ≤V≤V max

[0050] f min ≤f≤f max

[0051] θ∈{[θ down - τ ,θ up-τ ]}

[0052] In the formula, δ min δmax These are the lower and upper limits of the work angle δ, respectively, V min V max These are the lower and upper limits of voltage V, respectively, and f min f max These represent the lower and upper limits of the frequency f, respectively. The subscript τ indicates the number of different ranges of the equivalent impedance angle of the inverter obtained by mapping. The range of values ​​where τ = 1 corresponds to... The range of values ​​for τ = 2 corresponds to The range of values ​​for τ=3 corresponds to The range of values ​​for τ=4 corresponds to The range of values ​​for τ=5 corresponds to The range of values ​​for τ=6 corresponds to θ down-τ θ is the lower limit of the range τ. up-τ This represents the upper limit of the range τ.

[0053] Preferably, the stability margin index of the weak node is constructed using the actual value of the inverter's equivalent impedance angle and the amplitude of the inverter's equivalent output impedance, satisfying the following relationship:

[0054]

[0055] In the formula, SM(θ) c ,a c ) represents the stability margin index for weak nodes, where θ c a is the stability margin of the inverter's equivalent impedance angle. c This represents the stability margin of the inverter's equivalent impedance magnitude. The subscript τ indicates the number of different ranges of the equivalent impedance angle of the inverter obtained from the mapping. The range of values ​​where τ = 1 corresponds to... The range of values ​​for τ = 2 corresponds to The range of values ​​for τ=3 corresponds to The range of values ​​for τ=4 corresponds to The range of values ​​for τ=5 corresponds to The range of values ​​for τ=6 corresponds to k cτ The stability margin coefficient of the equivalent impedance angle within the range τ is given. Based on the oscillation characteristic samples, the stability range is determined by obtaining the boundaries of the constrained ranges for power angle, voltage, frequency, and impedance angle. a is the actual value of the equivalent impedance angle of the inverter. cτ f is the equivalent output impedance amplitude of the inverter within the range τ. cτ It is a quantization factor between the actual value of the equivalent impedance angle and the amplitude of the equivalent output impedance of the inverter within the range τ. The value range is (0,1), and the value is determined according to the combined impedance angle of the inverter and the line within the range τ.

[0056] Preferably, when the calculated stability margin index of the weak node exceeds a certain boundary of the multi-dimensional stability margin space, the new power system is determined to be unstable; and the instability type of the power system is confirmed by comparing it with the stability classification proposed in the "Definition and Classification of Power System Stability" report published by IEEE / CIGRE, so as to determine the dominant factors of instability of the new power system.

[0057] This invention also proposes a novel system for detecting weak nodes and establishing instability indicators in power systems, comprising:

[0058] The stability criterion establishment module is used to obtain oscillation characteristic samples of historical oscillation accidents, and map the linkage between oscillation characteristic samples to different ranges of the equivalent impedance angle of the inverter. The relationship between the actual value of the equivalent impedance angle of the inverter and the different ranges of the equivalent impedance angle of the inverter obtained by mapping constitutes a new power system stability criterion.

[0059] The weak node detection module is used to determine the power flow impact ratio of a node to a branch connected to a node when the system is determined to be in an unstable state, based on a new power system stability criterion. It obtains the proportion of the power flow impact on a branch connected to a node in the total power flow impact received by that node, which is used as the power flow transfer ratio of that node to that branch. Based on the information entropy model, it uses the power flow transfer ratio of a node to each branch to determine the power flow distribution entropy of that node. It introduces the node branch power flow channel variable and uses the total power flow impact received by the node and the power flow distribution entropy of that node to determine the node's power flow entropy weakness index. Nodes whose power flow entropy weakness index is not less than a set threshold are considered weak nodes.

[0060] The stability margin index system establishment module is used to establish an energy mapping model of the system's power angle, voltage, frequency, and impedance angle based on the generator rotor motion equation and the inverter's equivalent second-order power angle / frequency equation. It also uses oscillation characteristic samples to determine the constraints on the power angle, voltage, frequency, and impedance angle. Under these constraints, it establishes a multi-dimensional stability margin space by utilizing the coupling relationship between the power angle stability margin, voltage stability margin, frequency stability margin, and impedance angle stability margin. Finally, it constructs stability margin indices for weak nodes using the actual value of the inverter's equivalent impedance angle and the inverter's equivalent output impedance amplitude.

[0061] The instability detection module is used to determine the instability of a new type of power system when the stability margin index of a weak node exceeds the multi-dimensional stability margin space.

[0062] It also includes: an instability-dominant factor detection module, which is used to compare the stability classification proposed in the IEEE / CIGRE report "Definition and Classification of Power System Stability" to confirm the instability type of the power system, so as to identify new types of power systems.

[0063] A terminal includes a processor and a storage medium; the storage medium is used to store instructions; the processor is used to perform operations according to the instructions to execute the steps of a method.

[0064] A computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of a method.

[0065] The beneficial effects of this invention, compared with the prior art, include at least the following: The method proposed in this invention addresses the problems of variable network energy transmission patterns and unclear dominant instability factors caused by the distributed random access of renewable energy in novel power systems. It achieves quantitative identification of weak links in novel power systems, analyzes the instability relationships of voltage-frequency-power angle and dynamic impedance based on the transient and stable energy transfer patterns of the system, and proposes a strategy for analyzing the dominant instability factors of novel power systems, guiding power system planning and transformation. This invention realizes the mapping relationship between the broadband oscillation stability criterion of novel power systems and the three major stability criteria of voltage, frequency, and power angle in traditional power systems. It also realizes the construction of factors affecting the stability of novel power systems and stability conditions, enabling accurate analysis of the relationship between different influencing factors and different types of stability, thereby identifying the main influencing factors of system stability and the types of system instability. Attached Figure Description

[0066] Figure 1 This invention presents a flowchart of a novel method for detecting weak nodes and establishing instability indicators in power systems.

[0067] Figure 2 This is the equivalent circuit of the grid-type inverter in the embodiments of the present invention. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.

[0069] This invention proposes a novel method for detecting weak nodes and establishing instability indicators in power systems, such as... Figure 1 As shown, it includes:

[0070] Step 1: Obtain oscillation characteristic samples of historical oscillation accidents, map the linkage between oscillation characteristic samples to different ranges of the equivalent impedance angle of the inverter, and construct a new power system stability criterion based on the relationship between the actual value of the equivalent impedance angle of the inverter and the different ranges of the equivalent impedance angle of the inverter obtained by mapping.

[0071] Historical oscillation accidents of power electronic equipment within the system are acquired, and the common factors leading to these historical oscillation accidents are used as oscillation feature samples. These oscillation feature samples include: the active and reactive power output of the inverter, the output voltage and current, and the combined impedance angle of the inverter and the line. In this embodiment, oscillation feature samples are extracted by summarizing and analyzing past broadband oscillation phenomena, and the main characteristics of such phenomena are summarized. Some typical oscillation accidents that have occurred in reality, such as the oscillation accident in Guyuan, Hebei Province, the oscillation accident in Texas, USA, the oscillation accident in Hami, Xinjiang, and the oscillation accident in the North Sea, Germany, etc., have common factors leading to these oscillation accidents, which constitute the oscillation feature samples. Specifically:

[0072] 1) The main participants in the oscillation are power electronic equipment and its control system, as well as traditional electrical equipment and transmission networks. In new power systems dominated by such high-proportion power electronic equipment, the source side is connected to the grid through energy routers, which can be regarded as grid-connected inverters or grid-linked inverters that provide sufficient voltage and power support for the system and can further increase the utilization of renewable energy. On the other hand, the load side is connected to the grid through energy routers, which can usually be regarded as a combination of constant impedance load and constant power load. This constant power characteristic makes the entire power system prone to instability.

[0073] 2) Its oscillation mode often begins with small-signal negative damping instability, and then divergently and continuously oscillates over a wide frequency range, ranging from a few Hz to several thousand Hz.

[0074] 3) This type of power system involves multiple generating units and electrical equipment in multiple regions, and the oscillation frequency varies with the topology of the power electronic equipment, exhibiting a multimodal behavior, namely, multiple sources, multiple types, and multiple structures. For modes with lower oscillation frequencies, the oscillation energy is large and the influence range is wide. This is because the interaction between a single mode of oscillation and the power electronic equipment may excite a new oscillation mode, causing the oscillation energy to propagate widely in the power grid, making the oscillation develop from local to global. Thus, broadband oscillations exhibit time-varying characteristics, with the oscillation frequency changing with the time of the power electronic equipment, and also show the characteristic of broadband oscillation energy propagating widely in the power grid.

[0075] To improve detection efficiency, based on the oscillation characteristic samples of typical accidents, it is necessary to select a representative index, such as the equivalent impedance angle of the inverter, and establish a connection between the equivalent impedance angle of the inverter and the oscillation characteristic samples in a mapping manner, thereby comprehensively considering oscillation characteristic factors and establishing a new type of instability index.

[0076] The impedance angle characteristics are analyzed, and an impedance angle model is constructed based on small sample data or zero sample data of the system. Such small sample or zero sample data is generally the equivalent model mapped by the oscillation characteristic samples extracted from the oscillation samples. That is, the oscillation samples are mostly broadband oscillations. In the broadband oscillation range, the main participants are power electronic equipment, which can be equivalent to a power system with a grid-type inverter as the source input. The impedance angle model is established using the equivalent model of the grid-type inverter.

[0077] 1) Impedance angle characteristic analysis

[0078] Based on the characteristics of new power systems, when new energy sources are connected to weak grid systems, grid-connected inverters with grid-based and grid-following control strategies are generally used. Within the wide-frequency oscillation range of the system, the equivalent impedance of the grid-connected inverter changes with the current. The equivalent circuit of the grid-connected inverter is as follows: Figure 2 As shown.

[0079] Figure 2 In the diagram, U1 and U2 are the output voltage and bus voltage of the grid-connected inverter; Z = R + jX is the sum of the inverter's equivalent output impedance Z1 and line impedance Z2; Z = Z1 + Z2, Z1 = R1 + jX1, Z2 = R2 + jX2; R1 and X1 are the inverter's equivalent output resistance and reactance, respectively; R2 and X2 are the line resistance and reactance, respectively; δ is the angular deviation between the inverter's output voltage and the bus voltage.

[0080] according to Figure 2 The apparent power output of the inverter is expressed as:

[0081]

[0082] In the formula, P is the active power output of the inverter; Q is the reactive power output of the inverter.

[0083]

[0084] In the formula, θ is the phase angle of the sum Z of the inverter's equivalent output impedance and the line impedance, which becomes the inverter's combined impedance angle; R is the sum of the inverter's equivalent output resistance and the line resistance; X is the sum of the inverter's equivalent output reactance and the line reactance.

[0085] Therefore, active power and reactive power can be expressed as:

[0086]

[0087] In practical systems, since the angle deviation δ between the inverter output voltage and the bus voltage is very small, assuming δ is approximately equal to 0, Q can be equivalent to:

[0088]

[0089] Due to the existence of the inverter's equivalent negative impedance, the combined impedance angle expands from the conventional range of [-π / 2, π / 2] to [-π, π]. For ease of impedance angle characteristic analysis, it is assumed that the equivalent output impedance of the grid-connected inverter takes a fixed value in the third quadrant. Since the line impedance remains fixed in the first quadrant, taking the inverter's equivalent impedance in the third quadrant facilitates impedance angle synthesis and is more conducive to impedance angle characteristic analysis. This is achieved by changing the line impedance Z2 to allow the equivalent impedance to fall within different ranges for analysis. Simultaneously, θ1 is taken as the angle of the inverter's equivalent output impedance Z1.

[0090] Using the relationship between the system's output active power and reactive power:

[0091] P 2 +Q 2 =K1

[0092] Where K1 is a constant.

[0093] Based on the oscillation characteristic samples, the linkage between the active power P and reactive power Q output by the inverter, the output voltage U1 and current I1, and the combined impedance angle θ of the inverter and the line is mapped to different ranges of the inverter's equivalent impedance angle, thus forming a new power system stability criterion. This facilitates the analysis and judgment of the power system's stability performance under load disturbances. The power system stability performance criterion is shown in Table 1.

[0094] Table 1 Stability performance criteria of power systems

[0095]

[0096] When determining the instability of a power system, it is necessary to combine the coupling relationship between the impedance angle stability margin and other margins to determine the specific type of instability.

[0097] Since impedance angle stability involves a dynamic process, its stability type cannot be simply defined by voltage stability or frequency stability. It is primarily influenced by both the equivalent impedance of the grid-connected converter and the grid-side impedance. The equivalent impedance of the grid-connected converter is related to its internal inductance, capacitance, and control parameters, and manifests as internal potential energy during the dynamic process. The grid-side inductance and capacitance parameters manifest as external potential energy during the dynamic process. During the dynamic process, impedance angle stability is mainly affected by the mutual conversion between the internal potential energy exhibited by the converter itself and the external potential energy on the grid side. Impedance angle stability reflects the system's ability to stabilize oscillations at the power equilibrium point; therefore, this type of stability is a power oscillation-type stability dominated by the conversion of potential energy.

[0098] In this embodiment, the inverter equivalent output impedance Z1 is obtained by collecting small sample data or zero sample data of the system. The line impedance Z2 is connected 0.1s after the system stabilizes. This will better match the impedance angle stabilization process and better show the changes in system stability after the reactive power of the system changes. Finally, the impedance angle model of the specific power system case to be analyzed is established by using the different power system stability performance obtained in Table 1.

[0099] By utilizing the impedance angle characteristics of a system model with small or zero samples, and based on the relationship between the system impedance angle and stability, a self-evolving data model of the power system to be analyzed is constructed using small or zero sample data for the specific analysis case. This allows us to obtain the power system stability performance of the specific power system within the impedance angle range.

[0100] This invention maps the linkage between oscillation characteristic samples to different ranges of the equivalent impedance angle of the inverter, forming a novel power system stability criterion. This achieves an organic combination of the novel power system broadband oscillation stability criterion and the traditional three major power system stability criteria of voltage, frequency, and power angle. It can be applied to the analysis of factors and stability conditions affecting system stability. Moreover, the novel power system stability criterion not only characterizes the changing trend of the physical quantities themselves, but also characterizes the influence relationship and direction between the changes of various physical quantities, thereby enabling a more accurate determination of the relationship between different influencing factors and the novel power stability.

[0101] Step 2: Based on the new power system stability criterion, when the system is determined to be in an unstable state, the proportion of the power flow impact on a branch connected to a node in the total power flow impact received by the node is obtained as the power flow transfer ratio of the node to a branch. Based on the information entropy model, the power flow distribution entropy of the node is determined by using the power flow transfer ratio of the node to each branch. The node branch power flow channel variable is introduced, and the power flow entropy weakness index of the node is determined by using the total power flow impact received by the node and the power flow distribution entropy of the node. The nodes whose power flow entropy weakness index is not less than a set threshold are identified as weak nodes.

[0102] This paper analyzes the potential for instability and its causes, including the likelihood and possible causes of instability at various system nodes. Instability is primarily due to the high proportion of renewable energy used in new power systems, accompanied by a high proportion of power electronic equipment. The main cause is the negative resistance effect exhibited by the inverter, where the real part of the system impedance (the sum of the energy router's equivalent impedance and the grid-side impedance) is negative, and instability occurs when this value exceeds a certain threshold. The subsynchronous resonance generated when a grid-connected converter is connected to the grid is related to its interconnection impedance with the grid; different control methods alter the output impedance characteristics of the energy router. For control equipment in new power systems, taking a doubly-fed induction generator (DFIG) as an example, under constant active power output, it can be equivalent to a constant negative resistor; during fault periods, it can be equivalent to a variable negative resistor and a variable negative reactance in parallel, and this impedance value is closely related to the voltage and active / reactive power at the grid connection point. The equivalent resistance of the DFIG is negative at the subsynchronous resonance frequency, and this negative value is related to the rotor itself and control parameters. Its inductive negative resistance characteristic within the subsynchronous frequency band interacts with the grid's capacitive characteristics, causing oscillations. Furthermore, direct-drive wind turbines exhibit "negative resistance and capacitive reactance" at subsynchronous oscillation frequencies, forming a second-order negative damped oscillation loop with the grid's inductive reactance, causing oscillations. The reason for the oscillations in the wind farm is that the wind turbine controller exhibits negative equivalent conductance (resistance), and when its value increases to a certain level, the system becomes unstable.

[0103] Based on the system oscillation mechanism, conditions, and criteria, the broadband oscillation instability boundary of the system is determined. Entropy theory is used to determine whether there are potential instability risks in the system and the causes of instability. The nodes in the system that are prone to oscillation are obtained, and the oscillation conditions of each node in the new power system are analyzed to evaluate the weak nodes in the system.

[0104] Information entropy, also known as Shannon entropy, measures the information uncertainty of a discrete system and characterizes the degree of order or disorder within the system. When n states of a system occur with equal probability, the system has the lowest degree of order and the highest information entropy; when the system is in a unique state, the system has the highest degree of order and the lowest information entropy. Information entropy can be used to determine the stability of a system's state. Specifically, for a given system, the more possible operating states it has, and the more evenly they occur, the higher the degree of disorder and the greater its entropy; conversely, the fewer operating states a system has, and the more concentrated their probability of occurrence is within a few states, the higher its stability and the smaller its entropy. The entropy function for a general system is as follows:

[0105]

[0106] In the formula, H is the entropy function of the system, and ω is a constant; M e X is the total number of operating states of the entropy system; X is the probability of the corresponding operating state occurring.

[0107] In the context of a power system, which is an energy balance system, the stable equilibrium within the system can be described by the entropy change process of the energy distribution. We define the energy entropy H in the power system as the energy increment θ flowing through branch i. i As a pheromone, with the total number of system branches N as the total number of states, we have:

[0108]

[0109] In the formula, N is the total number of branches;

[0110] At this point, the energy entropy H represents the distribution pattern of energy flowing through a node under a certain operating state of the system; the more uniform the distribution, the more stable the system. Considering the influence of branches, branch variables C are introduced, satisfying the following relationship:

[0111]

[0112] Then the energy entropy of the power system at this time is:

[0113]

[0114] In the context of power flow distribution in a power system, suppose that when the power flow through a node a changes, the power flow impact ΔP on the branch i (i = 1, 2, 3, ..., N) connected to node a will change. i for:

[0115] ΔP i =|P i -P i 0 |

[0116] In the formula, P i 0 P represents the power flow in the initial state of branch i; i Let i be the power flow of branch i after node a is subjected to power flow impact;

[0117] Therefore, the total power flow impact on node a is:

[0118]

[0119] In the formula, ΔP a Let ΔP be the total tidal current impact on node a. i Let i be the power flow impact on branch i (i = 1, 2, 3, ..., N) connected to node a.

[0120] Based on a novel power system stability criterion, when the system is determined to be in an unstable state, the proportion of the power flow impact on a branch connected to a node to the total power flow impact received by that node is obtained as the power flow transfer ratio of that node to that branch. In this embodiment, the power flow transfer ratio of node a to branch i is... The following relationship must be satisfied:

[0121]

[0122] In the formula, Let ΔP be the power flow transfer ratio from node a to branch i. i Let ΔP be the power flow impulse on branch i connected to node a, where i = 1, 2, 3, ..., N, and N is the total number of branches. a Let be the total power flow impact on node a.

[0123] Based on the information entropy model, the power flow distribution entropy of a node is determined by using the power flow transfer ratio of a node to each branch. In this embodiment, the power flow distribution entropy of node a satisfies the following relationship:

[0124]

[0125] In the formula, Let be the power flow distribution entropy of node a. Let be the power flow transfer ratio of node a to branch i.

[0126] By introducing the power flow channel variable of a node branch, and using the total power flow impact on a node and the power flow distribution entropy of the node, the power flow entropy weakness index of the node is determined. In the example, the power flow entropy weakness index of node a satisfies the following relationship:

[0127]

[0128] In the formula, H P (a) is the weak index of power flow entropy at node a, C n For node branch power flow channel variables;

[0129] The magnitude of the power flow distribution entropy of the defined nodes reflects the distribution characteristics of the power flow in the system after different nodes are subjected to power flow shocks. If the entropy value is larger, it indicates that the power flow shocks suffered by the nodes are distributed more evenly among the lines. Conversely, if the entropy value is smaller, it indicates that the power flow shocks are concentrated on a few lines, which can easily cause the lines that bear most of the power flow shocks to be overloaded or overloaded.

[0130] Nodes whose power flow entropy weakness index is not less than a set threshold are considered weak nodes. The set threshold ranges from [0,1]. The larger the power flow entropy weakness index of a node that exceeds this range, the more likely the node region is to experience faults such as overload or overload. The power flow entropy weakness index of all nodes in the system is calculated and compared with the set threshold. When the number of nodes whose power flow entropy weakness index is greater than the set threshold accounts for 10% of the total number of nodes in the system, the optimal set threshold is obtained, and these 10% of nodes are considered weak nodes.

[0131] Based on the power flow entropy weakness index, it can be seen that the greater the power flow impact on a node, and the more unevenly the impact is distributed among adjacent lines, the more prone the area where the node is located is to power flow overload and faults, thus identifying it as a weak node; conversely, the less the power flow impact on the system, the smaller the impact on the system. A power flow entropy weakness index is constructed using entropy theory to complete the quantitative assessment of weak nodes in the power system.

[0132] With a high proportion of new energy sources and power electronic equipment integrated into the power system, the system oscillation frequency range is wider. This study analyzes the reasons why broadband oscillations occur within the system under specific operating conditions or fault disturbances, leading to system instability. The principle of identifying weak links in new power systems is to determine the broadband oscillation instability boundary based on the system oscillation mechanism, conditions, and criteria, thereby determining whether there are potential instability risks and the causes of instability, and identifying the links in the system prone to oscillation. By analyzing the failure rate, maintenance history, and availability of various key equipment in the power system, weak links in the system are assessed. The performance of the system under different operating conditions, especially its operation under weak link conditions, is analyzed, and entropy theory is used to quantitatively evaluate the system's weak links.

[0133] Step 3: Based on the generator rotor motion equation and the equivalent second-order power angle / frequency equation of the inverter, establish the energy mapping model of the system's power angle, voltage, frequency, and impedance angle, and use oscillation characteristic samples to determine the constraints of power angle, voltage, frequency, and impedance angle; under the constraints of power angle, voltage, frequency, and impedance angle, establish a multi-dimensional stability margin space by utilizing the coupling relationship between power angle stability margin, voltage stability margin, frequency stability margin, and impedance angle stability margin.

[0134] Specifically, step 3 includes:

[0135] Step 3.1: Based on the generator rotor motion equation and the equivalent second-order power angle / frequency equation of the inverter, establish the energy mapping model of the system's power angle, voltage, frequency, and impedance angle, and use oscillation characteristic samples to determine the constraints of the power angle, voltage, frequency, and impedance angle.

[0136] A power system comprises nodes in a "source-grid-load" system, namely power sources, the grid, and electrical loads. Energy conversion and transmission are involved among these three entities. We can analyze the essential relationships between power angle stability, voltage stability, frequency stability, impedance angle stability, and energy conversion by examining the kinetic / potential energy conversion laws among them, thereby achieving the goal of analyzing the instability probability of each node in the power system. A new mapping relationship between power angle, voltage, frequency, impedance angle, and energy is constructed using system motion equations and network topology. The source-side system motion equations are established based on the generator rotor motion equations and the equivalent second-order power angle / frequency equations of the inverter:

[0137]

[0138] In the formula, T is the generator's inertial time constant. P is the first derivative of the electrical angular velocity. M P is the rotor mechanical power. e Let D be the active power of the system and D be the damping coefficient. for ω0 is the electrical angular velocity under rated operating conditions.

[0139] Treating the system impedance angle as a variable, the grid-side energy expands from solely including the energy caused by the node voltage power angle to include the energy caused by changes in both the power angle and impedance angle. Based on the generator rotor motion equation and the inverter's equivalent second-order power angle / frequency equation, the active power model of node a satisfies the following relationship:

[0140] P e =ΔP δ (V a ,δ a )+ΔP θ (V a ,θ a )+ΔP δ,θ (V a ,δ a ,θ a )

[0141] In the formula, ΔP δ (V a ,δ a ) is node a, which is determined by voltage V a and work angle δ a The resulting power change, ΔP θ (V a ,θ a ) is node a, which is determined by voltage V a and impedance angle θ a The resulting power change, ΔP δ,θ (V a ,δ a ,θa ) is node a, which is determined by voltage V a δ a and impedance angle θ a The resulting change in power.

[0142] Based on the active power model of node a, the energy mapping model of the system's power angle, voltage, frequency, and impedance angle is established using the Popov method, satisfying the following relationship:

[0143] V = ΔV m (δ m V m ,f m ,θ m )+ΔV r (δ r V r ,f r ,θ r )+ΔV e (δ e V e ,f e ,θ e )+ΔV L (δ L V L ,f L ,θ L )

[0144] In the formula, V is the energy mapping function of the new power system, ΔV m (δ m V m ,f m ,θ m () represents the synchronous generator m with respect to the power angle δ m Voltage V m Frequency f m Impedance angle θ m Energy mapping function, m = 1, 2, ..., N m N m ΔV represents the total number of synchronous generators in the system. r (δ r V r ,f r ,θ r ) represents the inverter r with respect to the power angle δ r Voltage V r Frequency f r Impedance angle θ r The energy mapping function, r = 1, 2, ..., N r N r ΔV represents the total number of inverters in the system. e (δ e V e ,fe ,θ e ) is the system network at the power angle δ e Voltage V e Frequency f e Impedance angle θ e Energy mapping function; ΔV L (δ L V L ,f L ,θ L ) represents the load L with respect to the power angle δ L Voltage V L Frequency f L Impedance angle θ L The energy mapping function, L = 1, 2, ..., N L N L This represents the total load within the system.

[0145] Based on the energy mapping model of the system's power angle, voltage, frequency, and impedance angle, and using oscillation characteristic samples, the constraints of the power angle, voltage, frequency, and impedance angle are obtained, including:

[0146] 1) Nonlinear constraints between the power angle and the synchronous generator rotor angular potential energy, inverter equivalent potential energy, line inductance and / or capacitor potential energy.

[0147] 2) Nonlinear constraints between voltage and the potential energy of line inductance and / or capacitance, energy dissipated by resistance, and potential energy of constant power and / or constant impedance loads.

[0148] 3) Nonlinear constraints between frequency and synchronous generator rotor kinetic energy, inverter equivalent kinetic energy, constant power and / or constant impedance load potential energy.

[0149] 4) Nonlinear constraints between the impedance angle and the potential energy of the inverter filter inductor and / or capacitor, the potential energy of the line inductor and / or capacitor, and the energy dissipated by the resistor.

[0150] In the embodiments, when establishing the mapping relationship, characteristic parameters of the system when power angle stability problem, voltage stability problem, frequency stability problem and impedance angle stability problem are extracted from the oscillation characteristic samples.

[0151] Step 3.2: Under the constraints of power angle, voltage, frequency, and impedance angle, a multi-dimensional stability margin space is established by utilizing the coupling relationship between the power angle stability margin, voltage stability margin, frequency stability margin, and impedance angle stability margin, satisfying the following relationship:

[0152] SP(δ,V,f,θ)=P{SP(δ),SP(V),SP(f),SP(θ)}

[0153] In the formula, SP(δ,V,f,θ) is the multi-dimensional stability margin space of the new power system, and P{} is the coupling relationship function between the power angle stability margin SP(δ), voltage stability margin SP(V), frequency stability margin SP(f), and impedance angle stability margin SP(θ).

[0154] The constraints of the multi-dimensional stability margin space of the new power system satisfy the following relationship:

[0155] δ min ≤δ≤δ max

[0156] V min ≤V≤V max

[0157] f min ≤f≤f max

[0158] θ∈{[θ down - τ ,θ up-τ ]}

[0159] In the formula, δ min δ max These are the lower and upper limits of the work angle δ, respectively, V min V max These are the lower and upper limits of voltage V, respectively, and f min f max These represent the lower and upper limits of the frequency f, respectively. The subscript τ indicates the number of different ranges of the equivalent impedance angle of the inverter obtained by mapping. The range of values ​​where τ = 1 corresponds to... The range of values ​​for τ = 2 corresponds to The range of values ​​for τ=3 corresponds to The range of values ​​for τ=4 corresponds to The range of values ​​for τ=5 corresponds to The range of values ​​for τ=6 corresponds to θ down-τ θ is the lower limit of the range τ. up-τ This represents the upper limit of the range τ.

[0160] Instability in novel power systems is often characterized by supply-demand mismatch and increasing dynamic / potential energy coupling, making it difficult to determine the conditions for system instability solely based on these symptoms. Current impedance-based and state-equation techniques suffer from high computational complexity, weak engineering applicability, and low accuracy, hindering accurate and efficient determination of system stability. More optimized analytical strategies are needed. Therefore, this invention constructs a multi-dimensional stability margin space based on energy mapping relationships, comprehensively reflecting the energy mapping relationships between power angle, voltage, frequency, and impedance angle, as well as stability margins. This effectively improves the reliability of stability determination results for novel power systems.

[0161] Step 4: Using the actual value of the inverter's equivalent impedance angle and the amplitude of the inverter's equivalent output impedance, construct the stability margin index for the weak node, satisfying the following relationship:

[0162]

[0163] In the formula, SM(θ) c ,a c ) represents the stability margin index for weak nodes, where θ c a is the stability margin of the inverter's equivalent impedance angle. c This represents the stability margin of the inverter's equivalent impedance magnitude. The subscript τ indicates the number of different ranges of the equivalent impedance angle of the inverter obtained from the mapping. The range of values ​​where τ = 1 corresponds to... The range of values ​​for τ = 2 corresponds to The range of values ​​for τ=3 corresponds to The range of values ​​for τ=4 corresponds to The range of values ​​for τ=5 corresponds to The range of values ​​for τ=6 corresponds to k cτ The stability margin coefficient of the equivalent impedance angle within the range τ is given. Based on the oscillation characteristic samples, the boundary of the stable range under the constraints of power angle, voltage, frequency, and impedance angle is obtained, and k is determined. cτ The larger the value of k, the wider the stability margin of the equivalent impedance angle within the range τ. Typically, k... cτ Take 1, a is the actual value of the equivalent impedance angle of the inverter. cτ f is the equivalent output impedance amplitude of the inverter within the range τ. cτ The quantization factor is a quantization factor between the actual value of the equivalent impedance angle of the inverter and the amplitude of the equivalent output impedance within the range τ. The value range is (0,1), and the value is determined according to the combined impedance angle of the inverter and the line within the range τ. The quantization factor establishes a relationship between the equivalent impedance angle of the inverter and the combined impedance angle of the inverter and the line, so as to realize a simpler and more intuitive judgment of system stability.

[0164] The novel distributed random access power systems for renewable energy lead to volatile network energy transmission patterns and unclear instability factors. This invention employs a method to achieve self-evolutionary learning using small-sample or zero-sample data. Existing sample data is analyzed to extract its characteristics and impedance angle properties. An impedance angle model is constructed using the system's small-sample or zero-sample data. The impedance angle of the system model is obtained from the small-sample or zero-sample data. Based on the relationship between the system impedance angle and stability, the self-evolutionary data of the system's small-sample or zero-sample data is obtained.

[0165] Step 5: When the stability margin index of the weak node exceeds the multi-dimensional stability margin space, the new power system is determined to be unstable.

[0166] The new power system stability criterion shown in Table 1 judges the stability performance of the system based on the equivalent impedance angle of the inverter. The multi-dimensional stability margin space combines the equivalent impedance angle of the inverter, which can judge the stability performance of the system, with the power angle, voltage, and frequency in the traditional power system. The coupling index between the power angle stability margin, voltage stability margin, frequency stability margin, and impedance angle stability margin is used as the comprehensive stability margin index. Thus, the constructed impedance angle margin is associated with the traditional power angle stability margin, voltage stability margin, and frequency stability margin through mapping to establish a multi-dimensional stability margin space, realizing the quantitative evaluation of the multi-dimensional stability margin of the new power system.

[0167] When the calculated stability margin index of the weak node exceeds a certain boundary of the multi-dimensional stability margin space, the novel power system is deemed unstable. Furthermore, the instability type of the power system is confirmed by comparing it with the stability classification proposed in the IEEE / CIGRE report "Definitions and Classifications of Power System Stability," thereby identifying the dominant factors causing the instability of the novel power system, i.e., achieving instability type identification, including:

[0168] ① The stability margin of grid-connected converters decreases as the grid strength increases.

[0169] The stronger the power grid, the smaller the amplitude of the line impedance, and the smaller the phase angle difference between the system impedance and Z, meaning Z is closer to the line impedance. When the converter is operating, it exhibits negative impedance characteristics. When the system impedance is in this range, the system is more prone to instability than stability. However, when the power grid strength is weaker, it means the amplitude of the line impedance is larger, and the system impedance Z is closer to the line impedance, making it less susceptible to changes. In this case, the system is more likely to stabilize.

[0170] ② The stability margin of grid-connected converters increases with the increase of grid strength.

[0171] The greater the power grid strength, the smaller the amplitude of the line impedance, the easier it is for the system impedance Z to fall into the stable region, and the stronger the system stability.

[0172] ③ The stability is worst in purely inductive power grids.

[0173] The smaller the phase angle difference between and , the faster the amplitude of increases with the increase of the impedance angle, the greater the change in reactive power generated or absorbed by new energy sources, and the easier it is for the system's reactive power to lose balance. When the inductive component of is larger, the phase angle difference between and is smaller, and according to the above analysis, the system is more prone to instability.

[0174] ④ The oscillation problem of the converter connected to the grid increases with the increase of its output active power.

[0175] When the active power output of new energy sources increases, the power angle increases, the stability range decreases, and the risk of oscillation in the new power system increases.

[0176] This invention also proposes a novel system for detecting weak nodes and establishing instability indicators in power systems, comprising:

[0177] The stability criterion establishment module is used to obtain oscillation characteristic samples of historical oscillation accidents, and map the linkage between oscillation characteristic samples to different ranges of the equivalent impedance angle of the inverter. The relationship between the actual value of the equivalent impedance angle of the inverter and the different ranges of the equivalent impedance angle of the inverter obtained by mapping constitutes a new power system stability criterion.

[0178] The weak node detection module is used to determine the power flow impact ratio of a node to a branch connected to a node when the system is determined to be in an unstable state, based on a new power system stability criterion. It obtains the proportion of the power flow impact on a branch connected to a node in the total power flow impact received by that node, which is used as the power flow transfer ratio of that node to that branch. Based on the information entropy model, it uses the power flow transfer ratio of a node to each branch to determine the power flow distribution entropy of that node. It introduces the node branch power flow channel variable and uses the total power flow impact received by the node and the power flow distribution entropy of that node to determine the node's power flow entropy weakness index. Nodes whose power flow entropy weakness index is not less than a set threshold are considered weak nodes.

[0179] The stability margin index system establishment module is used to establish an energy mapping model of the system's power angle, voltage, frequency, and impedance angle based on the generator rotor motion equation and the inverter's equivalent second-order power angle / frequency equation. It also uses oscillation characteristic samples to determine the constraints on the power angle, voltage, frequency, and impedance angle. Under these constraints, it establishes a multi-dimensional stability margin space by utilizing the coupling relationship between the power angle stability margin, voltage stability margin, frequency stability margin, and impedance angle stability margin. Finally, it constructs stability margin indices for weak nodes using the actual value of the inverter's equivalent impedance angle and the inverter's equivalent output impedance amplitude.

[0180] The instability detection module is used to determine the instability of a new type of power system when the stability margin index of a weak node exceeds the multi-dimensional stability margin space.

[0181] It also includes: an instability-dominant factor detection module, which is used to compare the stability classification proposed in the IEEE / CIGRE report "Definition and Classification of Power System Stability" to confirm the instability type of the power system, so as to identify new types of power systems.

[0182] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0183] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0184] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0185] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0186] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for weak node detection and instability index establishment of a new power system, characterized in that, The method comprises the following steps: Obtaining oscillation characteristic samples of historical oscillation accidents, mapping the linkage relationship between the oscillation characteristic samples to different value ranges of the equivalent impedance angle of the inverter, and constructing a new power system stability criterion based on the relationship between the actual value of the equivalent impedance angle of the inverter and the different value ranges of the equivalent impedance angle of the inverter obtained by mapping; Based on the new power system stability criterion, when it is determined that the system is in an unstable state, the proportion of the power flow impact quantity on a branch connected to a certain node in the total power flow impact quantity at the certain node is obtained as the power flow transfer ratio of the certain node to the branch; Based on the information entropy model, the power flow distribution entropy of the certain node is determined by using the power flow transfer ratios of the certain node to each branch; the power flow entropy weak index of the node is determined by introducing the node-branch power flow channel variable and using the total power flow impact quantity received by the certain node and the power flow distribution entropy of the certain node; and the node with the power flow entropy weak index not less than a set threshold is taken as a weak node; Based on the generator rotor motion equation and the equivalent power angle / frequency second-order equation of the inverter, an energy mapping model of the system power angle, voltage, frequency and impedance angle is established, and the constraint conditions of the power angle, voltage, frequency and impedance angle are determined by using the oscillation characteristic samples; under the constraint conditions of the power angle, voltage, frequency and impedance angle, a multi-dimensional stability margin space is established by using the coupling relationship among the power angle stability margin, the voltage stability margin, the frequency stability margin and the impedance angle stability margin; The stability margin index of the weak node is constructed by using the actual value of the equivalent impedance angle of the inverter and the equivalent output impedance amplitude of the inverter; When the stability margin index of the weak node exceeds the multi-dimensional stability margin space, it is determined that the new power system is unstable.

2. The weak node detection and instability index establishment method of the new power system according to claim 1, wherein the oscillation characteristic samples comprise active power and reactive power output by the inverter, voltage and current output by the inverter, and a synthesized impedance angle of the inverter and the line; wherein the phase angle of the sum of the equivalent output impedance of the inverter and the line impedance is taken as the synthesized impedance angle of the inverter and the line, and the following relationship is satisfied: wherein θ is the synthesized impedance angle of the inverter and the line, R is the sum of the equivalent output resistance of the inverter and the line resistance, and X is the sum of the equivalent output reactance of the inverter and the line reactance.

3. The weak node detection and instability index establishment method of the new power system according to claim 2, wherein the symbol ↑ represents an increase in the oscillation characteristic sample, the symbol ↓ represents a decrease in the oscillation characteristic sample, and the change in the oscillation characteristic sample on the left side of the symbol → will cause the change in the oscillation characteristic sample on the right side of the symbol →.

4. The weak node detection and instability index establishment method of the new power system according to claim 1, wherein the power flow transfer ratio of node a to branch i satisfies the following relationship: According to the oscillation characteristic sample, the linkage relationship among the active power P and the reactive power Q of the inverter output, the output voltage U1 and the output current I1, and the synthetic impedance angle θ of the inverter and the line is mapped to different value ranges of the equivalent impedance angle of the inverter, so as to obtain the actual value of the equivalent impedance angle of the inverter The relationship between the different value ranges of the equivalent impedance angle of the inverter obtained by the mapping and the new power system stability criterion are constituted, which comprises: 1) when the linkage is P↑→Q↓→U1↑→I1↓→θ↑→Q↑, if , then the new power system is determined to be stable; when the linkage is P↓→Q↑→U1↓→I1↑→θ↓→Q↓, if , then the new power system is determined to be stable; 2) when the linkage is P↑→Q↓→U1↑→I1↓→θ↓→Q↓, if , then the new power system is determined to be unstable; when the linkage is P↓→Q↑→U1↓→I1↑→θ↑→Q↑, if , then the new power system is determined to be unstable; 3) when the linkage is P↑→Q↓→U1↑→I1↓→θ↓→Q↑, if , then the new power system is determined to be stable; when the linkage is P↓→Q↑→U1↓→I1↑→θ↑→Q↓, if , then the new power system is determined to be stable; 4) when the linkage is P↑→Q↓→U1↓→I1↑→θ↑→Q↓, if , then the new power system is determined to be unstable; when the linkage is P↓→Q↑→U1↑→I1↓→θ↓→Q↑, if , then the new power system is determined to be unstable; 5) when the linkage is P↑→Q↓→U1↓→I1↑→θ↓→Q↑, if , then the new power system is determined to be stable; when the linkage is P↓→Q↑→U1↑→I1↓→θ↑→Q↓, if , then the new power system is determined to be stable; 6) when the linkage is P↑→Q↓→U1↓→I1↑→θ↓→Q↓, if , then the new power system is determined to be unstable; when the linkage is P↓→Q↑→U1↑→I1↓→θ↑→Q↑, if , then the new power system is determined to be unstable; the power flow distribution entropy of node a satisfies the following relationship: the power flow entropy weak index of node a satisfies the following relationship:

5. The weak node detection and instability index establishment method of the new power system according to claim 1, wherein wherein is the power flow transfer ratio of branch i to node a, ΔP i is the power flow impact on branch i connected to node a, i = 1, 2, 3, …, N, N is the total number of branches, ΔP a is the total power flow impact on node a; ​ In the formula, is the power flow distribution entropy of node a; ​ In the formula, H P (a) is the weak index of power flow entropy of node a, C n is the node branch power flow channel variable. ​ The threshold value range is set as [0, 1]; the power flow entropy weakness index of all nodes in the system is calculated and compared with the set threshold value; when the number of nodes with the power flow entropy weakness index greater than the set threshold value accounts for 10% of the total number of nodes in the system, the optimal set threshold value is obtained, and the 10% nodes are taken as the weak nodes.

6. The weak node detection and instability index establishment method of the new power system according to claim 3, characterized in that, Based on the generator rotor motion equation and the equivalent power angle / frequency second-order equation of the inverter, the active power model of node a satisfies the following relationship: P e = ΔP δ (V a , δ a ) + ΔP θ (V a , θ a ) + ΔP δ,θ (V a , δ a , θ a ) In the formula, ΔP δ (V a ,δ a ) is node a, which is determined by voltage V a and work angle δ a The resulting power change, ΔP θ (V a ,θ a ) is node a, which is determined by voltage V a and impedance angle θ a The resulting power change, ΔP δ,θ (V a ,δ a ,θ a ) is node a, which is determined by voltage V a δ a and impedance angle θ a The resulting change in power; Based on the active power of node a, the energy mapping model of the power angle, voltage, frequency and impedance angle of the system is established by using the Popov method, and satisfies the following relationship: V = ΔV m (δ m ,V m ,f m ,θ m )+ ΔV r (δ r ,V r ,f r ,θ r )+ ΔV e (δ e ,V e ,f e ,θ e )+ ΔV L (δ L ,V L ,f L ,θ L ) where V is the energy mapping function of the new power system, ΔV m (δ m ,V m ,f m ,θ m ) is the energy mapping function of the synchronous generator m with respect to the power angle δ m , voltage V m , frequency f m , impedance angle θ m , m = 1, 2, …, N m , N m is the total number of synchronous generators in the system; ΔV r (δ r ,V r ,f r ,θ r ) is the energy mapping function of the inverter r with respect to the power angle δ r , voltage V r , frequency f r , impedance angle θ r , r = 1, 2, …, N r , N r is the total number of inverters in the system; ΔV e (δ e ,V e ,f e ,θ e ) is the energy mapping function of the system network with respect to the power angle δ e , voltage V e , frequency f e , impedance angle θ e ; ΔV L (δ L ,V L ,f L ,θ L ) is the energy mapping function of the load L with respect to the power angle δ L , voltage V L , frequency f L , impedance angle θ L , L = 1, 2, …, N L , N L is the total number of loads in the system.

7. The weak node detection and instability index establishment method of the new power system according to claim 6, characterized in that, Based on the energy mapping model of the power angle, voltage, frequency and impedance angle of the system, the constraint conditions of the power angle, voltage, frequency and impedance angle are obtained by using the oscillation characteristic sample, including: 1) the nonlinear constraint condition between the power angle and the synchronous generator rotor angular potential energy, the inverter equivalent potential energy, the line inductance and / or capacitance potential energy; 2) the nonlinear constraint condition between the voltage and the line inductance and / or capacitance potential energy, the resistance dissipation energy, the constant power and / or constant impedance load potential energy; 3) the nonlinear constraint condition between the frequency and the synchronous generator rotor kinetic energy, the inverter equivalent kinetic energy, the constant power and / or constant impedance load potential energy; 4) the nonlinear constraint condition between the impedance angle and the inverter filter inductance and / or capacitance potential energy, the line inductance and / or capacitance potential energy, and the resistance dissipation energy.

8. The weak node detection and instability index establishment method of the new power system according to claim 7, characterized in that, Under the constraint conditions of the power angle, voltage, frequency and impedance angle, the multi-dimensional stability margin space is established by using the coupling relationship between the power angle stability margin, the voltage stability margin, the frequency stability margin and the impedance angle stability margin, and satisfies the following relationship: SP(δ, V, f, θ) = P{SP(δ), SP(V), SP(f), SP(θ)} In the formula, SP(δ, V, f, θ) is the multi-dimensional stability margin space of the new power system, and P{} is the coupling relationship function between the power angle stability margin SP(δ), the voltage stability margin SP(V), the frequency stability margin SP(f) and the impedance angle stability margin SP(θ); The constraint condition of the multi-dimensional stability margin space of the new power system satisfies the following relationship: δ min ≤ δ ≤ δ max V min ≤V≤V max f min ≤f≤f max wherein δ min , δ max are lower and upper limits of the power angle δ, V min , V max are lower and upper limits of the voltage V, f min , f max are lower and upper limits of the frequency f, and the subscript τ is the number of the different value range of the equivalent impedance angle of the inverter obtained by mapping, the value range corresponding to τ = 1 corresponds to the value range corresponding to τ = 2 corresponds to the value range corresponding to τ = 3 corresponds to the value range corresponding to τ = 4 corresponds to the value range corresponding to τ = 5 corresponds to the value range corresponding to τ = 6 corresponds to θ down-τ is the lower limit of the value range τ, and θ up-τ is the upper limit of the value range τ.

9. The weak node detection and instability index establishment method of the new power system according to claim 3, characterized in that, The stability margin index of the weak node is constructed by using the equivalent impedance angle actual value of the inverter and the equivalent output impedance amplitude of the inverter, and satisfies the following relationship: In the formula, SM(θ c ,a c ) is the stability margin index of the weak node, wherein θ c is the stability margin of the equivalent impedance angle of the inverter, a c is the stability margin of the equivalent impedance amplitude of the inverter, the subscript τ is the number of the different value range of the equivalent impedance angle of the inverter obtained by mapping, the value range corresponding to τ=1 is the value range corresponding to τ=2 is the value range corresponding to τ=3 is the value range corresponding to τ=4 is the value range corresponding to τ=5 is the value range corresponding to τ=6 is k cτ is the stability margin coefficient of the equivalent impedance angle in the value range τ, the boundary of the stability range under the constraint condition of the power angle, the voltage, the frequency and the impedance angle is determined according to the oscillation characteristic sample, is the actual value of the equivalent impedance angle of the inverter, a cτ is the equivalent output impedance amplitude of the inverter in the value range τ, f cτ is the quantization factor between the actual value of the equivalent impedance angle of the inverter and the equivalent output impedance amplitude in the value range τ, the value range is (0, 1), and the value is determined according to the combined impedance angle of the inverter and the line in the value range τ.

10. The weak node detection and instability index establishment method of the new power system according to claim 1, characterized in that, When the stability margin index of the weak node calculated exceeds a certain boundary of the multi-dimensional stability margin space, it is determined that the new power system is unstable; and the type of instability of the new power system is determined by comparing the stability classification proposed in the report "Power System Stability Definition and Classification" issued by IEEE / CIGRE to confirm the type of instability of the power system.

11. A novel power system weak node detection and instability index establishment system, characterized in that, Comprise: The stability criterion establishment module is used to obtain oscillation characteristic samples of historical oscillation accidents, map the linkage relationship between the oscillation characteristic samples as different value ranges of the equivalent impedance angle of the inverter, and constitute the stability criterion of the new power system by the relationship between the actual value of the equivalent impedance angle of the inverter and the different value ranges of the equivalent impedance angle of the inverter mapped. The weak node detection module is used to obtain the proportion of the power flow impact quantity on a branch connected to a node in the total power flow impact quantity on the node as the power flow transfer ratio of the node to the branch when it is determined that the system is in an unstable state based on the stability criterion of the new power system. Based on the information entropy model, the power flow transfer ratio of the node to each branch is used to determine the power flow distribution entropy of the node; the node branch power flow channel variable is introduced, and the total power flow impact quantity on the node and the power flow distribution entropy of the node are used to determine the power flow entropy weak index of the node; and the node with the power flow entropy weak index not less than a set threshold is taken as the weak node. The stability margin index system establishment module is used to establish an energy mapping model of the power angle, voltage, frequency and impedance angle of the system based on the generator rotor motion equation and the equivalent power angle / frequency second-order equation of the inverter, and determine the constraint conditions of the power angle, voltage, frequency and impedance angle by using the oscillation characteristic samples; under the constraint conditions of the power angle, voltage, frequency and impedance angle, the multi-dimensional stability margin space is established by using the coupling relationship among the power angle stability margin, voltage stability margin, frequency stability margin and impedance angle stability margin; and the stability margin index of the weak node is constructed by using the actual value of the equivalent impedance angle of the inverter and the equivalent output impedance amplitude of the inverter. The instability detection module is used to determine that the new power system is unstable when the stability margin index of the weak node exceeds the multi-dimensional stability margin space.

12. The system for weak node detection and instability index establishment of novel power system according to claim 11, characterized in that, Further comprise: The instability dominant factor detection module is used to determine the type of instability of the new power system by comparing the stability classification proposed in the report "Power System Stability Definition and Classification" issued by IEEE / CIGRE to confirm the type of instability of the power system. 13.A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is used to operate according to the instructions to perform the steps of the method of any one of claims 1-10.

14. A computer readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the steps of the method of any one of claims 1-10.

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