A system, method, and medium for energy unit system stability assessment

Abstract

The application discloses an energy unit system stability evaluation system, method and medium, relates to the technical field of performance evaluation, and solves the technical problem that in the prior art, only a single dimension of energy is focused, and dynamic coupling mechanisms among a plurality of subsystems in an energy system are not considered, resulting in that the evaluation result of system stability is relatively one-sided, and the accuracy of the evaluation result is affected; the energy data and real-time data of the energy unit are collected; the static stability index of the energy unit system is analyzed according to the energy data; the energy supply quality index of the energy unit system is analyzed according to the real-time data; the static stability margin index of the energy unit system is analyzed according to source-load uncertainty; a probability analysis model is constructed, and the large-interference probability voltage stability index is calculated according to the probability analysis model; the stability of the system can be evaluated from the perspective of multiple dimensions, and the accuracy of the evaluation result is improved.

Description

TECHNICAL FIELD

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

[0002] The energy unit system has the characteristics of multi-coupling and complementary operation, and therefore, when the stability of the energy unit system is tested, the interaction and influence between different types of energy need to be further considered; in centralized regulation, the stability of the system under various complex energy supply and demand scenarios needs to be tested, including the response speed, control accuracy and overall stability of the system under different load conditions and fault conditions; in active operation and maintenance, the overall stability of the system when facing equipment failure and replacement needs to be tested; the energy unit system is generally applied to small hotels, small commercial office parks and small industrial parks, and the stability evaluation of the system can make the operation of the system more stable, reduce the number of failures and maintenance, and effectively improve the economy of the system.

[0003] The prior art (invention patent with application number 2017103808521) discloses a stability evaluation method of a distributed energy system, which comprises the following steps: obtaining recorded data of electric energy of a target functional module related to the stability of the distributed energy system in the distributed energy system; determining the probability distribution of the electric energy in the target functional module according to the obtained recorded data; and determining the energy entropy value of the target functional module according to the probability distribution, so that the stability of the distributed energy system can be evaluated through the energy entropy value; in the prior art, the stability of the energy system is evaluated by calculating the energy entropy value, however, in the prior art, only a single dimension of energy is focused, and the dynamic coupling mechanism between the subsystems in the energy system is not considered; the evaluation result of the system stability is relatively one-sided, which affects the accuracy of the evaluation result.

[0004] The present application provides a stability evaluation system, method and medium of an energy unit system to solve the above technical problems. SUMMARY

[0005] The present application aims to solve at least one of the technical problems existing in the prior art; for this purpose, the present application provides a stability evaluation system, method and medium of an energy unit system to solve the technical problem that in the prior art, only a single dimension of energy is focused, and the dynamic coupling mechanism between the subsystems in the energy system is not considered; the evaluation result of the system stability is relatively one-sided, which affects the accuracy of the evaluation result.

[0006] To achieve the above object, the first aspect of the present application provides a kind of energy unit system stability evaluation system, method and medium, comprising: static index module, and multiple-source data acquisition module connected therewith, dynamic index module;

[0007] Multiple-source data acquisition module: for collecting energy data and real-time data of energy unit;

[0008] Static index evaluation module: for analyzing the static stability index of energy unit system according to energy data;Energy supply quality index of energy unit system is analyzed according to real-time data;The static stability margin index of energy unit system is analyzed according to source load uncertainty;

[0009] Dynamic index evaluation module: for constructing probability analysis model, and calculating large disturbance probability voltage stability index according to probability analysis model.

[0010] Preferably, the static stability index of energy unit system is analyzed according to energy data, comprising:

[0011] Energy data is called;Wherein, 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;

[0012] Circuit data in energy data is extracted, and circuit operation formula is obtained according to circuit data as follows: ;

[0013] The real part and imaginary part of node voltage i and j are substituted into the above formula, and two monomial quadratic equations are obtained by solving;The expression of the two monomial quadratic equations is:

[0014]

[0015] If node voltage is stable, monomial quadratic equation should have solution, and discriminant and static voltage stability index are obtained;Wherein, the discriminant is:

[0016] ;

[0017] The static voltage stability index is:

[0018] ;

[0019] Wherein, Voltage phasor of grid node i is represented; Voltage phasor of grid node j is represented; Conjugate of voltage phasor of node j is represented; Impedance value on branch ij is represented; Load of node i is represented; Load of node j is represented; represents the reactance value on the branch ij; represents the resistance value on the branch ij;

[0020] Extract pipeline data in energy data, calculate the static gas pressure stability index of the energy unit system according to the pipeline data; integrate the static voltage stability index and the static gas pressure stability index into a static stability index.

[0021] The application calculates the stability index of the circuit by considering multiple factors in the circuit, can reflect the relationship between various factors in the power grid and the stability of the circuit, and can comprehensively evaluate the stability of the power grid; provides a basis for subsequent risk assessment of the collapse node of the circuit, and provides data support for the stability evaluation of the energy unit system.

[0022] Preferably, the static gas pressure stability index of the energy unit system is calculated according to the pipeline data, including:

[0023] The pipeline data is called, and the steady-state flow in the natural gas pipeline is calculated according to the pipeline data:

[0024] ;

[0025] ;

[0026] ;

[0027] wherein, is the pipeline flow, is the pipeline constant of the xth pipeline; in a low-voltage network, and are the pressures of nodes i and j respectively; in a medium-voltage network, and are the pressure squares of nodes i and j respectively; is the flow index; is the flow direction switch value of natural gas in the pipeline; is the pressure difference matrix in the pipeline; is the associated matrix of branch nodes; is the node pressure matrix; the low-voltage network is <1.6Mpa; the medium-voltage network is 1.6MPa~4.0MPa; the high-voltage network is >4.0MPa;

[0028] The load matrix calculated according to the first law of Kirchhoff is: ; wherein, is the load matrix on the load node; is the flow matrix in the pipeline; is the associated matrix of branch nodes excluding the number of reference node rows;

[0029] For the branch with two end nodes i and j, the pressure drop f of the branch is:

[0030] ;

[0031] ;

[0032] If the gas network is stable, then is greater than 0, and the static gas pressure stability index of the branch ij is defined as: .

[0033] It should be noted that the ranges of low pressure, medium pressure and high pressure are set according to actual experience, and generally, the low pressure is set to be <1.6Mpa; the medium pressure is 1.6MPa~4.0MPa; and the high pressure is >4.0MPa.

[0034] The present application can ensure the applicability and calculation accuracy of the model under different pressure scenarios by distinguishing low pressure, medium and high pressure networks and defining the node pressure and respectively; and simplify the analysis process of complex pipe network by unified formula expression, reduce the calculation complexity; through real-time monitoring of gas pressure, when reaching the critical value, timely adjustment and optimization of gas supply measures; which is conducive to ensuring the safety of energy unit system in the process of natural gas transportation.

[0035] Preferably, the energy supply quality index of the energy unit system according to the real-time data analysis comprises:

[0036] Retrieving real-time data; wherein, the real-time data includes: the total number of detection points of harmonic content; the total number of detection points of voltage quality; the test value of impurity content of natural gas outlet; the maximum and minimum values of measured temperature of cold and hot network outlet;

[0037] The harmonic content of medium and low pressure is calculated by formula ; wherein, is the number of detection points to meet the harmonic content; is the total number of detection points of harmonic content of the power grid system;

[0038] The voltage qualification rate of medium and low pressure is calculated by formula ; wherein, is the number of detection points to meet the voltage quality; is the total number of detection points of voltage quality of the power grid system;

[0039] The outlet quality qualification rate of natural gas pipe network is calculated by formula ; wherein, , , These represent the test values ​​for sulfur, hydrogen sulfide, and carbon dioxide impurities in natural gas exports, respectively. , , These represent the specified values ​​for sulfur, hydrogen sulfide, and carbon dioxide impurities in natural gas exports, respectively.

[0040] Through formula Calculate the pass rate of temperature fluctuation at the outlets of the cold and hot networks; among which, This represents the highest measured temperature at the outlet of the hot and cold network. This is the lowest measured temperature at the outlet of the hot and cold network; The required temperature values ​​for cold and hot users; the harmonic content, voltage qualification rate, natural gas pipeline outlet quality qualification rate, and cold and hot network outlet temperature fluctuation qualification rate are integrated into energy supply quality indicators; the energy supply quality qualification rate is defined based on the energy supply quality indicators.

[0041] This invention calculates key quality parameters of the power subsystem, natural gas subsystem, and cold / heating subsystem simultaneously using real-time data, which avoids the one-sidedness of single-index analysis and improves the completeness of the assessment. Furthermore, analyzing the energy supply quality of each index can quickly locate the fault point when a fault occurs, which is conducive to ensuring the safe use of the energy unit system.

[0042] Preferably, the step of defining the energy supply quality pass rate based on energy supply quality indicators includes:

[0043] The overall energy quality qualification rate of an energy unit system is defined as:

[0044] , ;

[0045] ; ;

[0046] in, For the first A 0-1 variable representing the mass of a given energy type; Number of output energy types; For the set of output energy types; Energy type Medium quality The 0-1 variable of the project indicator k; For the first A mass set of energy types; A circular index, its purpose is to join collections. and variables .

[0047] Preferably, the static stability margin index of the energy unit system based on source-load uncertainty analysis includes:

[0048] Suppose there are n uncertain quantities, denoted as X; ; the mean value of each component and the standard deviation are known;

[0049] The statistical characteristics of the uncertain quantity are characterized by taking two points on both sides of the mean value of the uncertain quantity:

[0050] ;

[0051] ;

[0052] ;

[0053] wherein, is the third central moment of , and denotes the skewness coefficient;

[0054] The weight of the branch power flow or the node voltage is calculated by the formula ; the mean value of the branch power flow or the node voltage is calculated by the formula ; and the standard deviation of the branch power flow or the node voltage is calculated by the formula ; wherein, denotes the branch power flow value or the node voltage value;

[0055] Suppose the node voltage and the branch power flow are subject to normal distribution, then the probability density function of the node voltage and the branch power flow is analyzed;

[0056] The static stability margin index of the energy unit system is calculated by the formula , ; wherein,

[0057] is the total power probability density function of the system obtained by superimposing the distribution curves of each node; is the probability density function of the node voltage amplitude obtained by superimposing the distribution curves of each node; denotes the static stability margin index of the power of the energy unit system; denotes the static stability margin index of the voltage of the energy unit system; is the active power value at the system collapse point; is the initial active power value; is the node voltage at the system collapse point; is the initial node voltage.

[0058] ​​​The present application considers the influence 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 error caused by traditional symmetric sampling (such as normal assumption), and improves the characterization accuracy of actual source load uncertainty; based on the normal distribution assumption, the probability density function of node voltage and branch flow; can provide intuitive stability risk probability evaluation.

[0059] Preferably, the constructed probability analysis model comprises:

[0060] Assumed element The failure probability of the element is ; the operating state is ; The expression of the probability function is:

[0061] ;

[0062] Assuming that the failure rate of each device element of the system is and the repair rate is The expressions of the failure rate and the repair rate are respectively: ; ; wherein, represents the average uninterrupted operation duration; represents the average fault repair time;

[0063] The entire state set of the energy unit system is integrated into a state space ; wherein, the state space content includes: the system state before failure is determined by the network topology, power generation condition and load level of the system, and the failure information is determined by the location of the failure, the type of the failure, the protection and the switching action.

[0064] It should be noted that: for a system including m elements, Xl=(Xi1,Xi2,...,Xim) is a system operating state in the state space, according to the failure probability and the mutual relationship of each element, the joint probability distribution function .

[0065] Preferably, the probability voltage stability index of large disturbance is calculated according to the probability analysis model, comprising:

[0066] The state space of the energy unit system is called ; the calculation formula of the large disturbance stability index of the energy unit system is: ;

[0067] wherein, is the occurrence probability of the system state ; is the index function calculated, indicating a certain system state Probability of instability.

[0068] The present application converts device reliability into mathematical parameters by defining failure data of elements, supports quantitative evaluation of system availability and risk, analyzes dynamic characteristics of the system under different operating scenarios by integrating system state space and other multi-dimensional factors, avoids the limitations of local analysis, can comprehensively evaluate the energy unit system, and is beneficial to ensure the safety of the energy unit system.

[0069] The second aspect of the present application provides an energy unit system stability evaluation method, comprising:

[0070] Step S1: collecting energy data and real-time data of the energy unit;

[0071] Step S2: analyzing the static stability index of the energy unit system according to the energy data; analyzing the energy supply quality index of the energy unit system according to the real-time data;

[0072] Step S3: analyzing the static stability margin index of the energy unit system according to the source-load uncertainty;

[0073] Step S4: constructing a probability analysis model, and calculating the large disturbance probability voltage stability index according to the probability analysis model.

[0074] The third aspect of the present application provides an energy unit system stability evaluation medium, wherein the medium stores computer program instructions, and the program instructions are executed by a processor to realize the above method steps.

[0075] Compared with the prior art, the present application has the following beneficial effects:

[0076] 1. The present application calculates the stability index of the circuit by considering multiple factors in the circuit, can reflect the relationship between each factor in the power grid and the stability of the circuit, and can comprehensively evaluate the stability of the power grid; provides a basis for subsequent collapse node risk evaluation of the circuit, and provides data support for stability evaluation of the energy unit system; by distinguishing low-voltage, medium-voltage and high-voltage networks, the node pressure and can be defined respectively, which can ensure the applicability and calculation accuracy of the model under different pressure scenarios; and by simplifying the analysis process of the complex pipe network through a unified formula, the calculation complexity is reduced; by monitoring the gas pressure in real time, when the critical value is reached, the gas supply measures are adjusted and optimized in time; which is beneficial to ensure the safety of the energy unit system during natural gas transportation; by calculating the key quality parameters of the power subsystem, the natural gas subsystem and the cold / heat subsystem at the same time, the one-sidedness of single index analysis can be avoided, and the completeness of the evaluation can be improved; and by analyzing the energy supply quality of each index, the fault point can be quickly located when a fault occurs, which is beneficial to ensure the safe use of the energy unit system.

[0077] 2.The present application considers the influence 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 error caused by traditional symmetric sampling (such as normal assumption), and improves the characterization accuracy of the actual source load uncertainty; based on the normal distribution assumption, the probability density function of the node voltage and branch flow; can provide intuitive stability risk probability evaluation; the present application converts the device reliability into mathematical parameters by defining the fault data of the element, supports the quantitative evaluation of system availability and risk; integrate system state space and other multi-dimensional factor analysis of system dynamic characteristics under different operating scenarios, avoid the limitations of local analysis; can comprehensively evaluate the energy unit system, which is beneficial to improve the accuracy of the evaluation results. BRIEF DESCRIPTION OF DRAWINGS

[0078] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0079] Figure 1 It is a schematic diagram of the overall steps of the system of the present application;

[0080] Figure 2 It is a schematic diagram of the static stability index and energy supply quality index evaluation step of the present application;

[0081] Figure 3 It is a schematic diagram of the static stability margin index and dynamic stability analysis step of the present application;

[0082] Figure 4 It is a schematic diagram of the specific steps of the method of the present application. DETAILED DESCRIPTION

[0083] The technical solutions of the present application will be described clearly and completely below in combination with the embodiments. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0084] Please refer to Figure 1 , the first aspect embodiment of the present application provides a kind of energy unit system stability evaluation system, comprising: static index module, and multiple source data acquisition module connected with it, dynamic index module;

[0085] The multi-source data collection module is configured to collect energy data and real-time data of the energy unit, wherein the energy data comprises circuit data and pipeline data, the circuit data comprises voltage phasor, impedance value and load, and the pipeline data comprises node pressure and pipeline constant.

[0086] The static index evaluation module is configured to analyze static stability index of the energy unit system according to the energy data, to analyze energy supply quality index of the energy unit system according to the real-time data, and to analyze static stability margin index of the energy unit system according to source-load uncertainty.

[0087] The dynamic index evaluation module is configured to construct a probability analysis model and to calculate large disturbance probability voltage stability index according to the probability analysis model.

[0088] Please refer to Figure 2 The multi-source data collection module is configured to collect energy data and real-time data of the energy unit, wherein the energy data comprises circuit data and pipeline data, the circuit data comprises voltage phasor, impedance value and load, and the pipeline data comprises node pressure and pipeline constant.

[0089] The circuit data in the energy data is extracted, and a circuit operation formula is obtained according to the circuit data. ;

[0090] The real part and the imaginary part of the node voltages i and j are substituted into the above formula, and two monomial quadratic equations are obtained by solving; the two monomial quadratic equations are expressed as:

[0091]

[0092] If the node voltage is stable, the monomial quadratic equation should have a solution, and a discriminant and a static voltage stability index are obtained; wherein the discriminant is:

[0093] ;

[0094] The static voltage stability index is:

[0095] ;

[0096] Wherein, represents the voltage phasor of the grid node i; represents the voltage phasor of the grid node j; represents the conjugate of the voltage phasor of the node j; represents the impedance value on the branch ij; represents the load of the node i; represents the load of the node j; represents the reactance value on the branch ij; represents the resistance value on the branch ij.

[0097] It should be noted that, is the voltage stability index of the branch from the node i to the node j, The smaller, the better the stability of the system; The larger, the worse the voltage stability of the system; if , the voltage of the system will collapse;

[0098] The static voltage stability index of the whole power grid system Take the maximum value of the voltage stability index of all branches, that is: ; The weakest static voltage stability index in all branches, when the system voltage collapses, it starts from the weakest point, so: .

[0099] Extract the pipeline data in the energy data, and calculate the steady-state flow in the natural gas pipeline according to the pipeline data:

[0100] ;

[0101] ;

[0102] ;

[0103] Wherein, is the pipeline flow, is the pipeline constant of the xth pipeline; in the low-voltage network, and are the pressures of nodes i and j respectively; in the medium and high-voltage network, and are the pressure squares of nodes i and j respectively; is the flow index; is the flow direction switch quantity of natural gas in the pipeline; is the pressure difference matrix in the pipeline; is the associated matrix of branch nodes; is the node pressure matrix; the low-voltage network is <1.6Mpa; the medium-voltage network is 1.6MPa~4.0MPa; the high-voltage network is >4.0MPa;

[0104] The load matrix calculated according to the first law of Kirchhoff is: ; wherein, is the load matrix on the load node; is the flow matrix in the pipeline; is the associated matrix of branch nodes excluding the number of reference node rows;

[0105] For a branch with two end nodes i and j, the pressure drop f of the two ends of the branch is:

[0106] ;

[0107] ;

[0108] If the gas network is stable, then is greater than 0, the static gas pressure stability index of branch ij is defined as: ; The static voltage stability index and the static gas pressure stability index are integrated into a static stability index.

[0109] It should be noted that when , if , the gas network is stable; when , if , the gas network is stable.

[0110] Real-time data is retrieved; wherein the real-time data includes: the total number of detection points of harmonic content; the total number of detection points of voltage quality; the test value of impurity content at the natural gas outlet; the maximum and minimum values of the measured temperature at the cold and hot network outlets;

[0111] The harmonic content of the medium and low voltage is calculated by the formula ; wherein is the number of detection points to meet the harmonic content; is the total number of detection points of the harmonic content of the power grid system;

[0112] The voltage qualification rate of the medium and low voltage is calculated by the formula ; wherein is the number of detection points to meet the voltage quality; is the total number of detection points of the voltage quality of the power grid system;

[0113] The natural gas pipeline outlet quality qualification rate is calculated by the formula ; wherein , , respectively represent the test values of the sulfur, hydrogen sulfide, and carbon dioxide impurity content at the natural gas outlet; , , respectively represent the specified values of the sulfur, hydrogen sulfide, and carbon dioxide impurity content at the natural gas outlet;

[0114] The cold and hot network outlet temperature fluctuation qualification rate is calculated by the formula ; wherein is the maximum value of the measured temperature at the cold and hot network outlets; is the minimum value of the measured temperature at the cold and hot network outlets; is the required temperature value of the cold and hot users;

[0115] In summary, the overall energy supply quality qualification rate of the energy unit system is defined as:

[0116] , ;

[0117] ; ;

[0118] where, is a 0-1 variable of the quality of the th energy type; is the number of output energy types; is the set of output energy types; is the quality of the th item of the th energy type; is the set of the quality of the th energy type; is the loop index, which acts on the connection set and the variable .

[0119] 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 in this regard, the indicator system is constructed; among them, the main examination items of power quality include voltage deviation, frequency deviation, etc.; the main examination items of natural gas quality include total sulfur, hydrogen sulfide, and carbon dioxide content; the main examination items of heat energy quality include cold and heat network outlet temperature fluctuation.

[0120] Please refer to Figure 3 , assuming that there are n uncertain quantities, denoted as X; ; the mean and standard deviation of each component are known;

[0121] The statistical characteristics of the uncertain quantity are characterized by taking two points on both sides of the mean value of the uncertain quantity:

[0122] ;

[0123] ;

[0124] ;

[0125] where, is the third-order central distance of , and denotes the skewness coefficient;

[0126] The weight of branch power flow or node voltage is calculated by formula ; the mean value of branch power flow or node voltage is calculated by formula ; the mean value of branch power flow or node voltage is calculated by formula The standard deviation of branch power flow or node voltage is calculated; wherein, represents the branch power flow value or node voltage value;

[0127] Assuming that the node voltage and branch power flow obey normal distribution, the probability density function of node voltage and branch power flow is analyzed;

[0128] The static stability margin index of the energy unit system is calculated by the formula ,

[0129] wherein, is the system total power probability density function obtained by superimposing the distribution curves of each node; is the probability density function of the node voltage amplitude obtained by superimposing the distribution curves of each node; represents the static stability margin index of the energy unit system power; represents 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 collapse point; is the initial node voltage.

[0130] Assuming that the failure probability of the element is , and the operating state is ; The expression of the probability function of the element

[0131] ;

[0132] Assuming that the failure rate and the repair rate of each device element of the system are respectively: ; ; wherein, represents the average failure-free operation duration; represents the average failure repair time;

[0133] The entire state set of the energy unit system is integrated into a state space ; wherein, the state space content includes: the system state before failure is determined by the network topology, power generation condition and load level of the system, and the failure information is determined by the location of failure, failure type, protection and switch action.

[0134] The state space of the energy unit system is called ; the calculation formula of the large disturbance stability index of the energy unit system is: ;​

[0135] wherein, is the probability of system state occurrence; is the calculated index function, indicating the probability of instability of a certain system state .

[0136] 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 0.8pu of the normal value, or the time when the normal value is lower than 0.75pu is longer than 1 second; for the thermal subsystem, the instability criterion is selected as: the specific resistance of the branch and trunk line is greater than 300Pa / m; the hot water flow rate is greater than 3.5m / s; the supply water pipeline pressure is lower than the hot water vaporization pressure; for the natural gas subsystem, the specified high heat release, total sulfur, hydrogen sulfide and other indicators are checked, and the gas network pressure is greater than 0.9pu of the maximum bearing value.

[0137] The second aspect embodiment of the present application provides an energy unit system stability evaluation method, comprising:

[0138] Step S1: collecting energy data and real-time data of the energy unit;

[0139] Step S2: analyzing the static stability index of the energy unit system according to the energy data; analyzing the energy supply quality index of the energy unit system according to the real-time data;

[0140] Step S3: analyzing the static stability margin index of the energy unit system according to the source-load uncertainty;

[0141] Step S4: constructing a probability analysis model, and calculating the large disturbance probability voltage stability index according to the probability analysis model.

[0142] The third aspect embodiment of the present application provides an energy unit system stability evaluation medium, and the medium stores computer program instructions, which realize the method steps of the second aspect embodiment when executed by a processor.

[0143] Some data in the above formula are calculated by removing the dimension and taking the numerical value, and the formula is obtained by software simulation of a large amount of collected data to obtain a formula closest to the real situation; the preset parameters and the preset threshold in the formula are set by a person skilled in the art according to the actual situation or obtained by a large amount of data simulation.

[0144] The working principle of the present application is as follows: the energy data and real-time data of the energy unit are collected; the static stability index of the energy unit system is analyzed according to the energy data; the energy supply quality index of the energy unit system is analyzed according to the real-time data; the static stability margin index of the energy unit system is analyzed according to the source-load uncertainty; a probability analysis model is constructed, and the large disturbance probability voltage stability index is calculated according to the probability analysis model.

[0145] The above embodiments are used to illustrate the technical solutions of the present application but not to limit the present application. Although the present application is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or equivalent replaced without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. An energy unit system stability assessment system, characterized by, Comprise: Static index module, and the multi-source data acquisition module connected with it, dynamic index module; Multi-source data acquisition module: for collecting energy data and real-time data of energy unit; Static index evaluation module: for analyzing static stability index of energy unit system according to energy data; analyzing energy supply quality index of energy unit system according to real-time data; analyzing static stability margin index of energy unit system according to source load uncertainty; Dynamic index evaluation module: for constructing probability analysis model, calculating large disturbance probability voltage stability index according to probability analysis model; The static stability index of energy unit system is analyzed according to energy data, comprising: Call energy data; wherein, 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; Extracting circuit data from the energy data, and obtaining a circuit operation formula according to the circuit data is: ; The real part and the imaginary part of node voltage i and j are substituted into the formula, and two one-variable quadratic equations are solved; the expression of the two one-variable quadratic equations is: ; If the node voltage is stable, the monomial quadratic equation should have a solution, and a discriminant and a static voltage stability index are obtained; wherein the discriminant is: ; The static voltage stability index is: ； wherein, Viprepresents a voltage phasor of grid node i; Vjrepresents a voltage phasor of grid node j; Vj*represents a conjugate of the voltage phasor of node j; Zijrepresents an impedance value on branch ij; Pirepresents a load of node i; Pjrepresents a load of node j; Xijrepresents a reactance value on branch ij; Rijrepresents a resistance value on branch ij; Extract the pipeline data in the energy data, calculate the static gas pressure stability index of the energy unit system according to the pipeline data; integrate the static voltage stability index and the static gas pressure stability index into the static stability index; The energy supply quality index of energy unit system is analyzed according to real-time data, comprising: Call real-time data; wherein, real-time data includes: total number of detection points of harmonic content; total number of detection points of voltage quality; test value of impurity content of natural gas outlet; maximum and minimum values of measured temperature of cold and hot network outlet; The harmonic content of the medium and low voltage is calculated by the formula wherein, to meet the harmonic content to obtain the number of detection points; total number of detection points of the harmonic content of the power grid system; The voltage qualification rate of medium and low voltage is calculated by formula wherein, the number of detection points for meeting the voltage quality; the total number of detection points for the voltage quality of the power grid system; The natural gas pipeline network outlet quality qualification rate is calculated by the formula wherein, , , respectively represent the test values of the sulfur, hydrogen sulfide, and carbon dioxide impurity contents of the natural gas outlet; , , respectively represent the specified values of the sulfur, hydrogen sulfide, and carbon dioxide impurity contents of the natural gas outlet; Through formula Calculate the pass rate of temperature fluctuation at the outlets of the cold and hot networks; among which, This represents the highest measured temperature at the outlet of the hot and cold network. This is the lowest measured temperature at the outlet of the hot and cold network; The required temperature values ​​for cold and hot users; the harmonic content, voltage qualification rate, natural gas pipeline outlet quality qualification rate, and cold and hot network outlet temperature fluctuation qualification rate are integrated into energy supply quality indicators; the energy supply quality qualification rate is defined based on the energy supply quality indicators.

2. The energy unit system stability assessment system of claim 1, wherein, The static gas pressure stability index of energy unit system is calculated according to pipeline data, comprising: Call pipeline data, calculate the steady-state flow in natural gas pipeline according to pipeline data: ； ； ； wherein, is the pipeline flow, is the pipeline constant of the xth pipeline; in low-pressure networks, and are the pressures of nodes i and j, respectively; in medium- and high-pressure networks, and are the pressure squares of nodes i and j, respectively; is the flow index; is the flow direction switch quantity of natural gas in the pipeline; is the pressure difference matrix in the pipeline; is the incidence matrix of branch nodes; is the node pressure matrix; low-pressure networks are <1.6 MPa; medium-pressure networks are 1.6 MPa~4.0 MPa; high-pressure networks are >4.0 MPa; The load matrix is calculated according to the first law of Kirschoff: ; wherein, is the load matrix on the load node; is the flow matrix in the pipeline; is the incidence matrix of the branch nodes excluding the number of reference node rows; For the 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, then is greater than 0, the static gas pressure stability index of the branch ij is defined as: .

3. The system for evaluating stability of an energy unit system according to claim 1, wherein The energy supply quality index is defined according to the energy supply quality index, comprising: Define the overall energy supply quality qualification rate of energy unit system as: ， ； ； ； wherein, is a 0-1 variable for the quality of the th energy type; is the number of output energy types; is the set of output energy types; is the energy type th item indicator k of the quality of the th energy type; is the set of th energy type qualities; is a loop index that acts on the concatenation of the sets and the variable .

4. The energy unit system stability assessment system of claim 1, wherein, The static stability margin index of energy unit system is analyzed according to source load uncertainty, comprising: Suppose there are n uncertain quantities, denoted as X; ; the mean and standard deviation of each quantity are known; The statistical characteristics of the uncertainty quantity are represented by taking two points on both sides of the mean value of the uncertainty quantity: ； ； ； wherein is a third order center distance of is expressed as a skewness coefficient; Through formula Weighting of branch power flow or node voltage ; through formula Calculate the mean value of branch power flow or node voltage; using the formula Calculate the standard deviation of branch power flow or node voltage; where, This indicates the branch power flow value or node voltage value; Assuming that node voltage and branch flow are subject to normal distribution, the probability density function of node voltage and branch flow is analyzed; The static stability margin index of the energy unit system is calculated by the formula , ​ wherein, is the total power probability density function of the system obtained by superimposing the distribution curves of each node; is the probability density function of the node voltage amplitude obtained by superimposing the distribution curves of each node; represents the static stability margin index of the energy unit system power; represents 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 collapse point; is the initial node voltage.

5. The energy unit system stability assessment system of claim 1, wherein, The probability analysis model is constructed, comprising: Assume the element has a failure probability of ; the operating state is ; The probability function of is expressed as: ； Assume the failure rate of each device element of the system and repair rate are expressed as: ; ; wherein, is expressed as the mean duration of failure-free operation; is expressed as the mean failure repair time; Integrating the entire set of states of the energy unit system into a state space ; wherein the state space content includes: the pre-fault system state is determined by the network topology, generation conditions and load levels of the system, and the fault information is determined by the location of the fault occurrence, the fault type, the protection and switch action situation.

6. The energy unit system stability assessment system of claim 1, wherein, The large disturbance probability voltage stability index is calculated according to the probability analysis model, comprising: Calling energy unit system state space The calculation formula of the energy unit system large disturbance stability index is: ; wherein is the probability of occurrence of a system state . is the calculated indicator function, representing the probability of instability of a certain system state .

7. A method for evaluating stability of an energy unit system, applied to the system for evaluating stability of an energy unit system according to any one of claims 1-6, characterized in that, Comprise: Step S1: collect energy data and real-time data of energy unit; Step S2: analyze the static stability index of energy unit system according to energy data; Analyze the energy supply quality index of energy unit system according to real-time data; Step S3: analyze the static stability margin index of energy unit system according to source load uncertainty; Step S4: construct probability analysis model, calculate large disturbance probability voltage stability index according to probability analysis model.

8. An energy unit system stability assessment medium, characterized by, The medium stores computer program instructions, which are executed by the processor to realize the method steps of claim 7.

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