Energy unit system stability evaluation system and method and medium

Abstract

The invention discloses an energy unit system stability evaluation system and method and a medium, relates to the technical field of performance evaluation, and solves the problems that only single-dimensional energy is focused and a dynamic coupling mechanism among a plurality of subsystems in an energy system is not considered in the prior art. The evaluation result of the system stability is one-sided, and the accuracy of the evaluation result is influenced. The method comprises the following steps: acquiring energy data and real-time data of an energy unit; analyzing a static stability index of the energy unit system according to the energy data; analyzing an energy supply quality index of the energy unit system according to the real-time data; analyzing a static stability margin index of the energy unit system according to the source load uncertainty; constructing a probability analysis model, and calculating a large interference probability voltage stability index according to the probability analysis model; the stability of the system can be evaluated from a multi-dimensional angle direction, and the accuracy of an evaluation result can be improved.

Description

Technical Field

[0001] The present invention belongs to the field of performance evaluation, and relates to energy unit system stability evaluation technology, in particular to an energy unit system stability evaluation system, method and medium. Background Art

[0002] The energy unit system has the characteristics of multi-coupling and complementary operation. Therefore, when conducting stability tests on the energy unit system, it is necessary to further consider the interactions and impacts between different types of energy. In terms of centralized control, it is necessary to test the stability of the system in the face of various complex energy supply and demand scenarios, including the system's response speed, control accuracy and overall stability under different load conditions and fault conditions. In terms of active operation and maintenance, it is necessary to test the overall stability of the system in the face of equipment failure repair and replacement. Energy unit systems are generally used in small hotels, small commercial and office parks, and small industrial parks. Evaluating the stability of the system can make the system operation more stable, reduce the number of failures and repairs, and effectively improve the economy of the system.

[0003] The prior art (invention patent application number: 2017103808521) discloses a distributed energy system stability assessment method, which includes: obtaining recorded data of electric energy of a target functional module in a distributed energy system that is related to the stability of the distributed energy system; determining the probability distribution of electric energy in the target functional module based on the acquired recorded data; determining the energy entropy value of the target functional module based on the probability distribution, and the stability of the distributed energy system can be assessed by the energy entropy value; the prior art assesses the stability of the energy system by calculating the energy entropy value, however, the prior art only focuses on energy in a single dimension, and does not consider the dynamic coupling mechanism between several subsystems in the energy system; resulting in a one-sided assessment result of the system stability, which affects the accuracy of the assessment result.

[0004] The present invention provides an energy unit system stability assessment system, method and medium to solve the above technical problems. Summary of the Invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes an energy unit system stability assessment system, method and medium, which are used to solve the technical problem that the prior art only focuses on a single dimension of energy and does not consider the dynamic coupling mechanism between several subsystems in the energy system; resulting in a one-sided assessment result of the system stability, thereby affecting the accuracy of the assessment result.

[0006] To achieve the above-mentioned object, a first aspect of the present invention provides an energy unit system stability assessment system, method and medium, comprising: a static indicator module, and a multi-source data acquisition module and a dynamic indicator module connected thereto; Multi-source data acquisition module: used to collect energy data and real-time data of energy units; Static indicator evaluation module: used to analyze the static stability indicators of the energy unit system based on energy data; analyze the energy supply quality indicators of the energy unit system based on real-time data; analyze the static stability margin indicators of the energy unit system based on source-load uncertainty; Dynamic index evaluation module: used to build a probability analysis model and calculate the large interference probability voltage stability index based on the probability analysis model.

[0007] Preferably, analyzing the static stability index of the energy unit system based on the energy data includes: Retrieve energy data; energy data includes circuit data and pipeline data; circuit data includes voltage phasor, impedance value and load; pipeline data includes node pressure and pipeline constant; Extract the circuit data from the energy data, and obtain the circuit calculation formula based on the circuit data: ; Substituting the real and imaginary parts of the node voltages i and j into the above equations, two quadratic equations are obtained; the expressions of the two quadratic equations are:

[0008] If the node voltage is stable, the quadratic equation should have a solution, and the discriminant and the static voltage stability index are obtained; wherein, the discriminant is: ; The static voltage stability index is: ; in, represents the voltage phasor of grid node i; represents the voltage phasor of grid node j; represents the conjugate of the voltage phasor at node j; Indicates the impedance value on branch ij; represents the load of node i; represents the load of node j; Represents the reactance value on branch ij; Indicates the resistance value on branch ij; Extract pipeline data from energy data, calculate the static air pressure stability index of the energy unit system based on the pipeline data; integrate the static voltage stability index and the static air pressure stability index into a static stability index.

[0009] The present invention calculates the stability index of the circuit by considering multiple factors in the circuit, which can reflect the relationship between various factors in the power grid and the circuit stability, and can comprehensively evaluate the stability of the power grid; it provides a basis for the subsequent risk assessment of the collapse node of the circuit and provides data support for the stability assessment of the energy unit system.

[0010] Preferably, the calculation of the static air pressure stability index of the energy unit system based on the pipeline data includes: Retrieve pipeline data and calculate the steady-state flow in the natural gas pipeline based on the pipeline data: ; ; ; in, is the pipeline flow rate, is the pipeline constant of the xth pipeline; in the low-pressure network, and are the pressures at nodes i and j respectively; in medium and high voltage networks, and are the square of the pressure at nodes i and j respectively; is the mobility index; It is the switch value of the flow direction of natural gas in the pipeline; is the pressure difference matrix in the pipeline; is the correlation matrix of branch nodes; is the node pressure matrix; low-pressure network is <1.6MPa; medium-pressure network is 1.6MPa~4.0MPa; high-pressure network is >4.0MPa; The load matrix calculated according to Kirchhoff's first law is: ;in, is the load matrix at the load node; is the flow matrix in the pipeline; is the incidence matrix of branch nodes excluding the row number of reference nodes; For a branch with nodes i and j at both ends, the pressure drop f at both ends of the branch is: ; ; If the gas network is stable, is greater than 0, and the static pressure stability index of branch ij is defined as: .

[0011] It should be noted that the ranges of low pressure, medium pressure and high pressure are set according to actual experience. Generally, low pressure is set to <1.6Mpa; medium pressure is 1.6MPa~4.0MPa; and high pressure is >4.0MPa.

[0012] The present invention distinguishes the node pressure of low voltage, medium and high voltage networks and The separate definitions can ensure the applicability and calculation accuracy of the model under different pressure scenarios; and the unified formula expression simplifies the analysis process of complex pipeline networks and reduces the calculation complexity; by real-time monitoring of gas pressure, when it reaches the critical value, timely adjustment and optimization of gas supply measures are made; it is conducive to ensuring the safety of the energy unit system during natural gas transportation.

[0013] Preferably, analyzing the energy supply quality indicators of the energy unit system based on real-time data includes: Retrieve real-time data; real-time data includes: the total number of detection points for harmonic content; the total number of detection points for voltage quality; the test value of impurity content at the natural gas outlet; the maximum and minimum values ​​of the measured temperature at the outlet of the hot and cold network; By formula Calculate the harmonic content of medium and low voltage; where, The number of detection points is obtained to meet the harmonic content; is the total number of detection points for the harmonic content of the power grid system; By formula Calculate the voltage qualification rate of medium and low voltage; where, The number of detection points to meet voltage quality requirements; is the total number of detection points for the voltage quality of the power grid system; By formula Calculate the quality qualification rate of natural gas pipeline network outlet; where: , , Respectively represent the test values ​​of sulfur, hydrogen sulfide, and carbon dioxide impurity contents in natural gas outlet; , , Respectively represent the specified values ​​of sulfur, hydrogen sulfide and carbon dioxide impurity contents in natural gas outlet; By formula Calculate the qualified rate of temperature fluctuation at the outlet of cold and hot network; The maximum temperature measured at the outlet of the hot and cold network; The lowest temperature measured at the outlet of the hot and cold network; The temperature value required by cold and hot users; integrate the harmonic content, voltage qualification rate, natural gas pipeline outlet quality qualification rate and cold and hot network outlet temperature fluctuation qualification rate into energy supply quality indicators; define the energy supply quality qualification rate based on the energy supply quality indicators.

[0014] The present invention simultaneously calculates the key quality parameters of the power subsystem, natural gas subsystem, and cooling / heating subsystem through real-time data, which can avoid the one-sidedness of single-indicator analysis and improve the integrity of the assessment. In addition, by analyzing the energy supply quality of various indicators, the fault point can be quickly located when a fault occurs, which is conducive to ensuring the safe use of the energy unit system.

[0015] Preferably, the energy supply quality qualification rate is defined according to the energy supply quality index, including: The overall energy supply quality qualification rate of the energy unit system is defined as: , ; ; ; in, For the A 0-1 variable representing the mass of each energy type; is the number of output energy types; is the output energy type set; Energy type Medium quality 0-1 variable for item indicator k; For the Energy type mass set; It is a loop index, which is used to connect the collection and variables .

[0016] Preferably, the analyzing the static stability margin index of the energy unit system according to the source-load uncertainty includes: Assume there are n uncertainties, denoted as X; ; Each component is known The mean and standard deviation ; The statistical characteristics of the uncertainty are characterized by taking two points on both sides of the mean of the uncertainty: ; ; ; in, for The third-order center distance, Expressed as the skewness coefficient; By formula Calculate the weight of branch power flow or node voltage ; Through the formula Calculate the mean value of branch flow or node voltage; by formula Calculate the standard deviation of branch power flow or node voltage; where, Indicates branch flow value or node voltage value; Assuming that the node voltage and branch power flow obey the normal distribution, the probability density function of the node voltage and branch power flow is obtained by analysis; By formula , Calculate the static stability margin index of the energy unit system; in, It is the probability density function of the total system power obtained by superimposing the distribution curves of each node; It is the probability density function of the node voltage amplitude obtained by superimposing the distribution curves of each node; Indicates the static stability margin index of the energy unit system power; Indicates the static stability margin index of the energy unit system voltage; is the active power value at the system collapse point; is the initial active power value; is the node voltage at the system breakdown point; is the initial node voltage.

[0017] The present invention takes into account the impact of source-load uncertainty on the energy unit system, fully considers the asymmetry of the distribution when taking points on both sides of the mean, avoids the errors caused by traditional symmetrical sampling (such as the normal assumption), and improves the accuracy of characterizing the actual source-load uncertainty; based on the normal distribution assumption, the probability density functions of the node voltage and branch flow are transformed; it can provide an intuitive stability risk probability assessment.

[0018] Preferably, the constructing of the probability analysis model includes: Assumption Components The failure probability is ; The running status is ; The probability function The expression is: ; Assume the failure rate of each device component in the system and repair rate The expressions are: ; ;in, Expressed as the mean trouble-free operation duration; Expressed as mean time to repair a fault; Integrate all state sets of the energy unit system into a state space ; Among them, the state space content includes: the system state before the fault is determined by the system's network topology, power generation status and load level, and the fault information is determined by the location of the fault, fault type, protection and switch action.

[0019] It should be noted that for a system consisting of m components, Xl=(Xi1,Xi2,...,Xim) is a system operating state in the state space. According to the failure probability and mutual relationship of each component, its joint probability distribution function can be determined .

[0020] Preferably, the calculating of the large interference probability voltage stability index according to the probability analysis model includes: Retrieve the energy unit system state space The calculation formula of the large disturbance stability index of the energy unit system is: ; in, System status probability of occurrence; is the calculated indicator function, which represents a system state The probability of instability.

[0021] By defining component failure data, the present invention converts equipment reliability into mathematical parameters, supporting quantitative assessment of system availability and risk; integrating multi-dimensional factors such as the system state space to analyze the dynamic characteristics of the system under different operating scenarios, avoiding the limitations of local analysis; and being able to comprehensively evaluate the energy unit system, which is conducive to ensuring the safety of the energy unit system.

[0022] A second aspect of the present invention provides a method for evaluating the stability of an energy unit system, comprising: Step S1: Collect energy data and real-time data of energy units; Step S2: Analyze the static stability index of the energy unit system based on the energy data; analyze the energy supply quality index of the energy unit system based on the real-time data; Step S3: Analyze the static stability margin index of the energy unit system according to the source-load uncertainty; Step S4: construct a probability analysis model, and calculate the large interference probability voltage stability index based on the probability analysis model.

[0023] A third aspect of the present invention provides an energy unit system stability assessment medium, wherein the medium stores computer program instructions, and the program instructions implement the above method steps when executed by a processor.

[0024] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention calculates the stability index of the circuit by considering multiple factors in the circuit, which can reflect the relationship between various factors in the power grid and the circuit stability, and can comprehensively evaluate the stability of the power grid; it provides a basis for the subsequent risk assessment of the collapse node of the circuit and provides data support for the stability assessment of the energy unit system; by distinguishing the node pressure of low-voltage, medium-voltage and high-voltage networks and The separate definitions can ensure the applicability and calculation accuracy of the model under different pressure scenarios; and the unified formula expression simplifies the analysis process of complex pipeline networks and reduces the calculation complexity; by real-time monitoring of the gas pressure, when it reaches the critical value, the gas supply measures are adjusted and optimized in time; it is beneficial to ensure the safety of the energy unit system during the natural gas transportation process; the key quality parameters of the power subsystem, natural gas subsystem and cooling / heating subsystem are calculated simultaneously through real-time data, which can avoid the one-sidedness of single indicator analysis and improve the integrity of the evaluation; and, by analyzing the energy supply quality of various indicators, the fault point can be quickly located when a fault occurs, which is beneficial to ensure the safe use of the energy unit system.

[0025] 2. The present invention takes into account the impact of source-load uncertainty on the energy unit system, fully considers the asymmetry of the distribution when taking points on both sides of the mean, avoids the errors caused by traditional symmetrical sampling (such as the normal assumption), and improves the accuracy of characterizing the uncertainty of the actual source load; based on the normal distribution assumption, the probability density function of the node voltage and branch current is converted; it can provide an intuitive stability risk probability assessment; the present invention defines the fault data of the components, converts the equipment reliability into mathematical parameters, and supports the quantitative assessment of system availability and risk; integrates multi-dimensional factors such as the system state space to analyze the dynamic characteristics of the system in different operating scenarios, avoiding the limitations of local analysis; it can comprehensively evaluate the energy unit system, which is conducive to improving the accuracy of the evaluation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0027] Figure 1 A schematic diagram of the overall steps of the system of the present invention; Figure 2 Schematic diagram of the static stability index and energy supply quality index evaluation steps of the present invention; Figure 3 Schematic diagram of the static stability margin index and dynamic stability analysis steps of the present invention; Figure 4 Schematic diagram of the specific steps of the method of the present invention. DETAILED DESCRIPTION

[0028] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0029] See also Figure 1 , a first aspect of the present invention provides an energy unit system stability assessment system, comprising: a static indicator module, and a multi-source data acquisition module and a dynamic indicator module connected thereto; Multi-source data acquisition module: used to collect energy data and real-time data of energy units; Static indicator evaluation module: used to analyze the static stability indicators of the energy unit system based on energy data; analyze the energy supply quality indicators of the energy unit system based on real-time data; analyze the static stability margin indicators of the energy unit system based on source-load uncertainty; Dynamic index evaluation module: used to build a probability analysis model and calculate the large interference probability voltage stability index based on the probability analysis model.

[0030] See also Figure 2 , collect energy data and real-time data of energy units, where energy data includes: circuit data and pipeline data; circuit data includes: voltage phasor, impedance value and load; pipeline data includes: node pressure and pipeline constant; Extract the circuit data from the energy data, and obtain the circuit calculation formula based on the circuit data: ; Substituting the real and imaginary parts of the node voltages i and j into the above equations, two quadratic equations are obtained; the expressions of the two quadratic equations are:

[0031] If the node voltage is stable, the quadratic equation should have a solution, and the discriminant and the static voltage stability index are obtained; wherein, the discriminant is: ; The static voltage stability index is: ; in, represents the voltage phasor of grid node i; represents the voltage phasor of grid node j; represents the conjugate of the voltage phasor at node j; Indicates the impedance value on branch ij; represents the load of node i; represents the load of node j; Represents the reactance value on branch ij; Indicates the resistance value on branch ij.

[0032] It should be noted that is the voltage stability index of the branch from node i to node j, The smaller it is, the better the stability of the system is. The larger the value, the worse the voltage stability of the system; if , then the system voltage will collapse; Static voltage stability index of the entire power grid system Take the maximum value of the voltage stability index of all branches, that is: ; It is the most fragile static voltage stability indicator among all branches. When the system voltage collapses, it starts from the weakest point. Therefore: .

[0033] Extract pipeline data from energy data and calculate the steady-state flow in the natural gas pipeline based on the pipeline data: ; ; ; in, is the pipeline flow rate, is the pipeline constant of the xth pipeline; in the low-pressure network, and are the pressures at nodes i and j respectively; in medium and high voltage networks, and are the square of the pressure at nodes i and j respectively; is the mobility index; It is the switch value of the flow direction of natural gas in the pipeline; is the pressure difference matrix in the pipeline; is the correlation matrix of branch nodes; is the node pressure matrix; low-pressure network is <1.6MPa; medium-pressure network is 1.6MPa~4.0MPa; high-pressure network is >4.0MPa; The load matrix calculated according to Kirchhoff's first law is: ;in, is the load matrix at the load node; is the flow matrix in the pipeline; is the incidence matrix of branch nodes excluding the row number of reference nodes; For a branch with nodes i and j at both ends, the pressure drop f at both ends of the branch is: ; ; If the gas network is stable, is greater than 0, and the static pressure stability index of branch ij is defined as: ; Integrate the static voltage stability index and the static air pressure stability index into the static stability index.

[0034] It should be noted that when When, if The gas network is stable; when When, if The gas network is stable.

[0035] Retrieve real-time data; real-time data includes: the total number of detection points for harmonic content; the total number of detection points for voltage quality; the test value of impurity content at the natural gas outlet; the maximum and minimum values ​​of the measured temperature at the outlet of the hot and cold network; By formula Calculate the harmonic content of medium and low voltage; where, The number of detection points is obtained to meet the harmonic content; is the total number of detection points for the harmonic content of the power grid system; By formula Calculate the voltage qualification rate of medium and low voltage; where, The number of detection points to meet voltage quality requirements; is the total number of detection points for the voltage quality of the power grid system; By formula Calculate the quality qualification rate of natural gas pipeline network outlet; where: , , Respectively represent the test values ​​of sulfur, hydrogen sulfide, and carbon dioxide impurity contents in natural gas outlet; , , Respectively represent the specified values ​​of sulfur, hydrogen sulfide and carbon dioxide impurity contents in natural gas outlet; By formula Calculate the qualified rate of temperature fluctuation at the outlet of cold and hot network; The maximum temperature measured at the outlet of the hot and cold network; The lowest temperature measured at the outlet of the hot and cold network; The temperature value required by cold and hot users; In summary, the overall energy supply quality qualification rate of the energy unit system is defined as: , ; ; ; in, For the A 0-1 variable representing the mass of each energy type; is the number of output energy types; is the output energy type set; Energy type Medium quality 0-1 variable for item indicator k; For the Energy type mass set; It is a loop index, which is used to connect the collection and variables .

[0036] It should be noted that in the integrated energy cabin system, the energy supply quality indicators mainly consider the quality of electricity, cold, heat and gas energy supply, and the indicator systems are constructed here separately; among them, the main inspection items of electricity quality include voltage deviation, frequency deviation, etc.; the quality of natural gas mainly inspects the content of total sulfur, hydrogen sulfide and carbon dioxide; the quality of thermal energy mainly inspects the temperature fluctuations at the outlet of the cold and hot network.

[0037] See also Figure 3 , assuming there are n uncertainties, denoted as X; ; Each component is known The mean and standard deviation ; The statistical characteristics of the uncertainty are characterized by taking two points on both sides of the mean of the uncertainty: ; ; ; in, for The third-order center distance, Expressed as the skewness coefficient; By formula Calculate the weight of branch power flow or node voltage ; Through the formula Calculate the mean value of branch flow or node voltage; by formula Calculate the standard deviation of branch power flow or node voltage; where, Indicates branch flow value or node voltage value; Assuming that the node voltage and branch power flow obey the normal distribution, the probability density function of the node voltage and branch power flow is obtained by analysis; By formula , Calculate the static stability margin index of the energy unit system; in, It is the probability density function of the total system power obtained by superimposing the distribution curves of each node; It is the probability density function of the node voltage amplitude obtained by superimposing the distribution curves of each node; Indicates the static stability margin index of the energy unit system power; Indicates the static stability margin index of the energy unit system voltage; is the active power value at the system collapse point; is the initial active power value; is the node voltage at the system breakdown point; is the initial node voltage.

[0038] Assumption Components The failure probability is ; The running status is ; The probability function The expression is: ; Assume the failure rate of each device component in the system and repair rate The expressions are: ; ;in, Expressed as the mean trouble-free operation duration; Expressed as mean time to repair a fault; Integrate all state sets of the energy unit system into a state space ; Among them, the state space content includes: the system state before the fault is determined by the system's network topology, power generation status and load level, and the fault information is determined by the location of the fault, fault type, protection and switch action.

[0039] Retrieve the energy unit system state space The calculation formula of the large disturbance stability index of the energy unit system is: ; in, System status probability of occurrence; is the calculated indicator function, which represents a system state The probability of instability.

[0040] It should be noted that the voltage instability criterion is that the system bus voltage cannot gradually recover or the final stable range is lower than the normal value of 0.8pu, or the time below the normal value of 0.75pu is longer than 1 second; in terms of the thermal subsystem, the instability criterion is selected as: the branch line friction resistance is greater than 300Pa / m; the hot water flow rate is greater than 3.5m / s; the water supply pipeline pressure is lower than the hot water vaporization pressure; in terms of the natural gas subsystem, the specified high calorific value, total sulfur, hydrogen sulfide and other indicators are verified, and the gas network pressure is greater than the maximum tolerance value of 0.9pu.

[0041] A second embodiment of the present invention provides a method for evaluating the stability of an energy unit system, comprising: Step S1: Collect energy data and real-time data of energy units; Step S2: Analyze the static stability index of the energy unit system based on the energy data; analyze the energy supply quality index of the energy unit system based on the real-time data; Step S3: Analyze the static stability margin index of the energy unit system according to the source-load uncertainty; Step S4: construct a probability analysis model, and calculate the large interference probability voltage stability index based on the probability analysis model.

[0042] The third aspect of the present invention provides an energy unit system stability assessment medium, wherein the medium stores computer program instructions, which, when executed by a processor, implement the method steps of the second aspect of the present invention.

[0043] Some of the data in the above formula are calculated by removing the dimensions and taking their numerical values. The formula is a formula that is closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0044] The working principle of the present invention is as follows: the present invention collects energy data and real-time data of energy units; analyzes the static stability index of the energy unit system based on the energy data; analyzes the energy supply quality index of the energy unit system based on the real-time data; analyzes the static stability margin index of the energy unit system based on the uncertainty of source and load; constructs a probability analysis model, and calculates the large interference probability voltage stability index based on the probability analysis model.

[0045] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An energy unit system stability assessment system, characterized in that: include: Static indicator module, and the connected multi-source data acquisition module and dynamic indicator module; Multi-source data acquisition module: used to collect energy data and real-time data of energy units; Static indicator evaluation module: used to analyze the static stability indicators of the energy unit system based on energy data; analyze the energy supply quality indicators of the energy unit system based on real-time data; analyze the static stability margin indicators of the energy unit system based on source-load uncertainty; Dynamic index evaluation module: used to build a probability analysis model and calculate the large interference probability voltage stability index based on the probability analysis model.

2. The energy unit system stability assessment system according to claim 1, characterized in that: The analysis of the static stability index of the energy unit system based on the energy data includes: Retrieve energy data; energy data includes circuit data and pipeline data; circuit data includes voltage phasor, impedance value and load; pipeline data includes node pressure and pipeline constant; Extract the circuit data from the energy data, and obtain the circuit calculation formula based on the circuit data: ; Substituting the real and imaginary parts of the node voltages i and j into the above equations, two quadratic equations are obtained; the expressions of the two quadratic equations are: ； If the node voltage is stable, the quadratic equation should have a solution, and the discriminant and the static voltage stability index are obtained; wherein, the discriminant is: ; The static voltage stability index is: ； in, represents the voltage phasor of grid node i; represents the voltage phasor of grid node j; represents the conjugate of the voltage phasor at node j; Indicates the impedance value on branch ij; represents the load of node i; represents the load of node j; Represents the reactance value on branch ij; Indicates the resistance value on branch ij; Extract pipeline data from energy data, calculate the static air pressure stability index of the energy unit system based on the pipeline data; integrate the static voltage stability index and the static air pressure stability index into a static stability index.

3. The energy unit system stability assessment system according to claim 2, characterized in that: The calculation of the static air pressure stability index of the energy unit system based on the pipeline data includes: Retrieve pipeline data and calculate the steady-state flow in the natural gas pipeline based on the pipeline data: ； ； ； in, is the pipeline flow rate, is the pipeline constant of the xth pipeline; in the low-pressure network, and are the pressures at nodes i and j respectively; in medium and high voltage networks, and are the square of the pressure at nodes i and j respectively; is the mobility index; It is the switch value of the flow direction of natural gas in the pipeline; is the pressure difference matrix in the pipeline; is the correlation matrix of branch nodes; is the node pressure matrix; low-pressure network is <1.6MPa; medium-pressure network is 1.6MPa~4.0MPa; high-pressure network is >4.0MPa; The load matrix calculated according to Kirchhoff's first law is: ;in, is the load matrix at the load node; is the flow matrix in the pipeline; is the incidence matrix of branch nodes excluding the row number of reference nodes; For a branch with nodes i and j at both ends, the pressure drop f at both ends of the branch is: ； ； If the gas network is stable, is greater than 0, and the static pressure stability index of branch ij is defined as: .

4. The energy unit system stability assessment system according to claim 1, characterized in that: The energy supply quality indicators of the energy unit system are analyzed based on real-time data, including: Retrieve real-time data; real-time data includes: the total number of detection points for harmonic content; the total number of detection points for voltage quality; the test value of impurity content at the natural gas outlet; the maximum and minimum values ​​of the measured temperature at the outlet of the hot and cold network; By formula Calculate the harmonic content of medium and low voltage; where, The number of detection points is obtained to meet the harmonic content; is the total number of detection points for the harmonic content of the power grid system; By formula Calculate the voltage qualification rate of medium and low voltage; where, The number of detection points to meet voltage quality requirements; is the total number of detection points for the voltage quality of the power grid system; By formula Calculate the quality qualification rate of natural gas pipeline network outlet; where: , , Respectively represent the test values ​​of sulfur, hydrogen sulfide, and carbon dioxide impurity contents in natural gas outlet; , , Respectively represent the specified values ​​of sulfur, hydrogen sulfide and carbon dioxide impurity contents in natural gas outlet; By formula Calculate the qualified rate of temperature fluctuation at the outlet of cold and hot network; The maximum temperature measured at the outlet of the hot and cold network; The lowest temperature measured at the outlet of the hot and cold network; The temperature value required by cold and hot users; integrate the harmonic content, voltage qualification rate, natural gas pipeline outlet quality qualification rate and cold and hot network outlet temperature fluctuation qualification rate into energy supply quality indicators; define the energy supply quality qualification rate based on the energy supply quality indicators.

5. The energy unit system stability assessment system according to claim 4, characterized in that: The energy supply quality qualification rate is defined according to the energy supply quality index, including: The overall energy supply quality qualification rate of the energy unit system is defined as: ， ； ； ； in, For the A 0-1 variable representing the mass of each energy type; is the number of output energy types; is the output energy type set; Energy type Medium quality 0-1 variable for item indicator k; For the Energy type mass set; It is a loop index, which is used to connect the collection and variables .

6. The energy unit system stability assessment system according to claim 1, characterized in that: The analysis of the static stability margin index of the energy unit system based on source-load uncertainty includes: Assume there are n uncertainties, denoted as X; ; Each component is known The mean and standard deviation ; The statistical characteristics of the uncertainty are characterized by taking two points on both sides of the mean of the uncertainty: ； ； ； in, for The third-order center distance, Expressed as the skewness coefficient; By formula Calculate the weight of branch power flow or node voltage ; Through the formula Calculate the mean value of branch flow or node voltage; by formula Calculate the standard deviation of branch power flow or node voltage; where, Indicates branch flow value or node voltage value; Assuming that the node voltage and branch power flow obey the normal distribution, the probability density function of the node voltage and branch power flow is obtained by analysis; By formula , Calculate the static stability margin index of the energy unit system; in, It is the probability density function of the total system power obtained by superimposing the distribution curves of each node; It is the probability density function of the node voltage amplitude obtained by superimposing the distribution curves of each node; Indicates the static stability margin index of the energy unit system power; Indicates the static stability margin index of the energy unit system voltage; is the active power value at the system collapse point; is the initial active power value; is the node voltage at the system breakdown point; is the initial node voltage.

7. The energy unit system stability assessment system according to claim 1, characterized in that: The constructing of the probability analysis model includes: Assumption Components The failure probability is ; The running status is ; The probability function The expression is: ； Assume the failure rate of each device component in the system and repair rate The expressions are: ; ;in, Expressed as the mean trouble-free operation duration; Expressed as mean time to repair a fault; Integrate all state sets of the energy unit system into a state space ; Among them, the state space content includes: the system state before the fault is determined by the system's network topology, power generation status and load level, and the fault information is determined by the location of the fault, fault type, protection and switch action.

8. The energy unit system stability assessment system according to claim 1, characterized in that: The calculating of the large interference probability voltage stability index according to the probability analysis model includes: Retrieve the energy unit system state space The calculation formula of the large disturbance stability index of the energy unit system is: ; in, System status probability of occurrence; is the calculated indicator function, which represents a system state The probability of instability.

9. A method for evaluating the stability of an energy unit system, applied to an energy unit system stability evaluation system according to any one of claims 1 to 8, characterized in that: include: Step S1: Collect energy data and real-time data of energy units; Step S2: Analyze the static stability index of the energy unit system based on the energy data; Analyze the energy supply quality indicators of the energy unit system based on real-time data; Step S3: Analyze the static stability margin index of the energy unit system according to the source-load uncertainty; Step S4: construct a probability analysis model, and calculate the large interference probability voltage stability index based on the probability analysis model.

10. An energy unit system stability assessment medium, characterized in that: The medium stores computer program instructions, which implement the method steps of claim 9 when executed by a processor.

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