CN109033507A - A kind of Model in Reliability Evaluation of Power Systems method considering the failure of information system function for monitoring - Google Patents

A kind of Model in Reliability Evaluation of Power Systems method considering the failure of information system function for monitoring Download PDF

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CN109033507A
CN109033507A CN201810604923.6A CN201810604923A CN109033507A CN 109033507 A CN109033507 A CN 109033507A CN 201810604923 A CN201810604923 A CN 201810604923A CN 109033507 A CN109033507 A CN 109033507A
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information system
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徐昊
付蓉
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Nanjing Post and Telecommunication University
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Abstract

The invention discloses a kind of Model in Reliability Evaluation of Power Systems method of consideration information system function for monitoring failure, analysis function for monitoring first is related to the logical construction of element, and the logical construction based on element builds up an information system function for monitoring reliability model;Then, it proposes information system component reliable probability, information system function for monitoring reliability is calculated based on function for monitoring reliability model;Then, the influence that analysis information system function for monitoring fails to electric system, chooses The Reliability Indicas of Gereration System;Finally, simulating power system component state and function for monitoring working condition using monte carlo method, the The Reliability Indicas of Gereration System for considering the failure of information system function for monitoring is calculated.This method can be used for the reliability assessment of power information physics emerging system.

Description

A kind of Model in Reliability Evaluation of Power Systems method considering the failure of information system function for monitoring
Technical field
The present invention relates to the technical fields of power network safety operation, particularly, a kind of consideration information system monitoring function The Model in Reliability Evaluation of Power Systems method that can be failed.
Background technique
As the communication technology, automatic technology and control technology continue to develop and are widely applied, electric system is gradually sent out It transforms into as the information physical electric system (Cyber Physical Power System, CPPS) with CPS characteristic feature.With This is continuously improved the interdependency of information system, new threat is also introduced to electric system simultaneously, once information system occurs Integrity problem direct or indirect can have an impact the reliability of power grid, and that causes large area uses electrification.
For a long time, it is often for the fail-safe analysis of electric system and information system separately carries out, but electric power The degree of coupling of system and information system is constantly being deepened, and individually carrying out fail-safe analysis to electric system and information system cannot The safe and stable operation for maintaining power grid, has document to propose the Model in Reliability Evaluation of Power Systems side for power system component failure Method can not be into for the influence from information system failure however, when the reliability to modern power systems is assessed Row analysis, can not accurately electric network reliability be assessed by being analyzed only for electric system itself.It examines at present The Power System Reliability research for considering information system influence is still at an early stage, and CPPS reliability estimation method is less, and not It is enough perfect, especially face the reliability estimation method of multiple functions, scene.
Summary of the invention
Goal of the invention: of the existing technology in order to solve the problems, such as, the present invention provides a kind of consideration information system monitoring function The Model in Reliability Evaluation of Power Systems method that can be failed considers the work of information system function for monitoring in information physical electric system With assessing Power System Reliability.
Technical solution: a kind of Model in Reliability Evaluation of Power Systems method considering the failure of information system function for monitoring, including with Lower step:
Step 1: communication network model is established according to the structure of electric system, inputs data of information system and electric system Data, the data of information system include the component kind that function for monitoring is related to and number, component logic structure, component reliability Probability;The electric power system data include the reliable probability of power system component, system load flow constraint, grid nodes input it is defeated Probability, line impedance out;
Step 2: information system function for monitoring model is the part that function for monitoring is executed in communication network model, including more A module, each module include multiple element, according to the component attributes of inside modules and topological structure establish each module can Entire information system function for monitoring reliability model is established by property model, then by series relationship;By inside modules element it Between logical construction calculate the reliable probability of module in function for monitoring model, then be superimposed the reliable probability of each module and obtain The reliable probability of entire information system function for monitoring model;
Step 3: selecting system load cuts down probability and expectation loses load as power system component reliability index;
Step 4: reliable probability and power system component reliability index based on information system function for monitoring, with illiteracy Special Carlow method simulation information system function for monitoring state and power system component state;
Step 5: the influence that analysis information system function for monitoring fails to electric system is referred to based on Power System Reliability Mark, in conjunction with function for monitoring state and power system component state, the Power System Reliability for accounting for function for monitoring failure is commented Estimate.
Preferably, in the information system function for monitoring reliability model of step 2, according to each component failure to monitoring function The influence of energy determines the logical construction of model;Based on function for monitoring model foundation function for monitoring reliability model, first according to information System element reliable probability calculates the reliable probability of module in function for monitoring model, then calculates information system monitoring function It can reliable probability.
Preferably, step 2 function for monitoring is related to the calculation method of the reliable probability of module are as follows: according to inside modules member Logical construction between part establishes the reliability block diagram of each module, and the structure of reliability block diagram depends on the failure pair of each module The influence of function;Component logic relationship is divided into train, parallel system and voting system using reliability block diagram, if series connection The reliability of system is Rs, the reliability of parallel system is Rb, the reliability of voting system is Rr, calculation formula are as follows:
In formula, n indicates the number of element in train or parallel system or voting system, RiIndicate i-th of element Reliability.
Preferably, load cuts down probability and the optimal load curtailment that is calculated as of expectation mistake load calculates, and Optimal Load is cut It is as follows to subtract the judgment step for calculating and whether starting:
1) according to the electric network state of simulation, including load power, generated output power and Line Flow about beam analysis Whether off-the-line, if it is not, thening follow the steps 2);It is calculated if so, executing optimal load curtailment;
2) Load flow calculation is carried out according to the data under current system conditions;
3) the Line Flow limit value of breaker function for monitoring failure belonging to occurring is set as a sufficiently large numerical value, such as It is set as 10000;
4) the out-of-limit total amount of computing electric power line trend, formula are as follows:
In formula: PolFor the out-of-limit total amount of transmission line of electricity trend;N is system power line number amount;PiFor having for i-th line road Function;Pi_limFor the active limit value in i-th line road;
5) judge PolIt whether is 0, if it is not, then executing optimal load curtailment calculating.
Preferably, the monte carlo method in step 4 is non-sequential Monte Carlo method.
Preferably, step 4 and step 5 specifically includes the following steps:
1) general by component logic structure and component reliability according to the data of information system of input and electric power system data Rate obtains information system function for monitoring reliable probability, carries out non-sequential Monte Carlo sampling, obtains physical system components state With information system function for monitoring state;
2) judge whether function for monitoring fails, if it is not, carrying out step 4;If so, carrying out step 5;
3) consider that power grid is attacked, the primary equipment state after being attacked;
4) primary system element set of final state is obtained;
5) influence that analysis function for monitoring operates normally electric system is considered as no shadow if function for monitoring does not fail It rings;
6) the Model in Reliability Evaluation of Power Systems index for considering function for monitoring is calculated, including load cuts down probability and it is expected to lose negative Lotus amount;
7) value of assumed load reduction coefficient of variation is as loop termination condition;It is cut according to the load being calculated every time Subtract probability calculation load and cuts down coefficient of variation and expectation mistake load;Judge whether load reduction coefficient of variation meets calculating eventually Only condition, if so, calculated load cuts down probability and expectation is lost load and exported;If it is not, then repeating step 2) arrives step 8).
Preferably, step 6) system loading cuts down probability and the calculation method of load is lost in expectation are as follows:
In formula, LOLPIndicate that system loading cuts down probability;EENSIndicate that load is lost in expectation;S is system all working state Set, including information system function for monitoring state and power system component state;piFor system state i probability;CiTo be It unites in the load reduction of state i.
The utility model has the advantages that the present invention provides a kind of Model in Reliability Evaluation of Power Systems side of consideration information system function for monitoring failure Method can be used for the reliability assessment of power information physics emerging system, it is contemplated that function for monitoring fails to Power System Reliability Influence, the reliability of information physical electric system is had evaluated, in step 2, it is contemplated that information system breaks down to electric power The influence of system reliability makes the accuracy of the Reliability Index finally obtained have substantial increase, to improve distribution Network planning stroke, reliability of operation.
Detailed description of the invention
Fig. 1 is the flow chart for considering the Model in Reliability Evaluation of Power Systems method of information system function for monitoring failure;
Fig. 2 is the method flow diagram of specific embodiment;
Fig. 3 is IEEE-30 node system figure;
Fig. 4 is communication network architecture figure.
Specific embodiment
The present invention will be further explained below with reference to the attached drawings and specific examples.
As shown in figure 3, the present embodiment chooses IEEE-30 node system as electric system to be assessed, interior joint 1 is Balance nodes, node 2,5,8,11,13 are PV node, and node 3,4,6,7,9,10,12,14-30 are PQ node.Establish its communication Network model, as shown in figure 4, power communication network model is by a backbone network (SDH-BN) and three Local Area Network (SDH- 1, SDH-2 and SDH-3) composition, four networks are SHRN structures.
As shown in Figure 1, the Model in Reliability Evaluation of Power Systems method for considering the failure of information system function for monitoring includes following step It is rapid:
Step 1: communication network model is established according to the structure of electric system, inputs data of information system and electric system Data, the data of information system include the component kind that function for monitoring is related to and number, component logic structure, component reliability Probability;The electric power system data include the reliable probability of power system component, system load flow constraint, grid nodes input it is defeated Probability, line impedance out;
Step 2: information system function for monitoring model is the part that function for monitoring is executed in communication network model, including more A module, each module include multiple element, according to the component attributes of inside modules and topological structure establish each module can Entire information system function for monitoring reliability model is established by property model, then by series relationship;According to each component failure pair The influence of function for monitoring determines the logical construction inside model between each element;First according to information system component reliable probability meter The reliable probability for calculating module in function for monitoring model, the reliable probability for being then superimposed each module obtain entire information system prison Visual function reliable probability.
Function for monitoring is related to the calculation method of the reliable probability of module are as follows: according to the logic knot between inside modules element The reliability block diagram of each module is found in building, and the structure of reliability block diagram depends on influence of the failure of each module to function;Benefit Component logic relationship is divided into train, parallel system and voting system with reliability block diagram, if the reliability of train For Rs, the reliability of parallel system is Rb, the reliability of voting system is Rr, calculation formula are as follows:
In formula, n indicates the number of element in train or parallel system or voting system, RiIndicate i-th of element Reliability.
Step 3: selecting system load cuts down probability and expectation loses load as power system component reliability index, Load, which cuts down probability, indicates that failure or attack cause the probability of adverse consequences (losing load), it is expected that losing load indicates failure or attack Hit the severity for causing adverse consequences;
Step 4: reliable probability and power system component reliability index, use based on information system function for monitoring are non- Sequential Monte Carlo method simulation information system function for monitoring state and power system component state;
Step 5: the influence that analysis information system function for monitoring fails to electric system is referred to based on Power System Reliability Mark, in conjunction with function for monitoring state and power system component state, the Power System Reliability for accounting for function for monitoring failure is commented Estimate.
Load cuts down probability and the optimal load curtailment that is calculated as of expectation mistake load calculates, and optimal load curtailment calculating is The judgment step of no starting is as follows:
1) according to the electric network state of simulation (failure for considering electric system and information system), including load power, power generation Machine output power and Line Flow constraint analyse whether that off-the-line, off-the-line refer to that a part of system and other parts lose together Then step is cut off connection, that is, will cut off with the nonsynchronous load of power grid.If it is not, thening follow the steps 2);If so, Optimal load curtailment is executed to calculate;
2) Load flow calculation is carried out according to the data under current system conditions;
3) the Line Flow limit value of breaker function for monitoring failure belonging to occurring is set as a sufficiently large numerical value, such as It is set as 10000;
4) the out-of-limit total amount of computing electric power line trend, formula are as follows:
In formula: PolFor the out-of-limit total amount of transmission line of electricity trend;N is system power line number amount;PiFor having for i-th line road Function;Pi_limFor the active limit value in i-th line road;
5) judge PolIt whether is 0, if it is not, then executing optimal load curtailment calculating.
Wherein, system loading cuts down probability and the calculation method of load is lost in expectation are as follows:
In formula, LOLPIndicate that system loading cuts down probability;EENSIndicate that load is lost in expectation;S is system all working state Set, including information system function for monitoring state and power system component state;piFor system state i probability;CiTo be It unites in the load reduction of state i.
When electric system or information system break down, operation states of electric power system can be had an impact, so that power train System optimal load flow calculating cannot get optimal solution, at this time need to cut down load, until power grid realizes optimal load flow again, Cutting down the load fallen is to lose load, and Multi simulation running, which is averaged, can obtain expectation mistake load.
During Multi simulation running, there is a situation where that Operation of Electric Systems is normal, then load reduction is zero, calculated load The probability that reduction is not zero, as load cut down probability.
Its step 4 and step 5 specifically includes the following steps:
1) general by component logic structure and component reliability according to the data of information system of input and electric power system data Rate obtains information system function for monitoring reliable probability, carries out non-sequential Monte Carlo sampling, obtains physical system components state With information system function for monitoring state;
2) judge whether function for monitoring fails, if it is not, carrying out step 4;If so, carrying out step 5;
3) consider that power grid is attacked, the primary equipment state after being attacked;
4) primary system element set of final state is obtained;
5) influence that analysis function for monitoring operates normally electric system is considered as no shadow if function for monitoring does not fail It rings;
6) the Model in Reliability Evaluation of Power Systems index for considering function for monitoring is calculated, including load cuts down probability and it is expected to lose negative Lotus amount;
7) value of assumed load reduction coefficient of variation is as loop termination condition;It is cut according to the load being calculated every time Subtract probability calculation load and cuts down coefficient of variation and expectation mistake load;Judge whether load reduction coefficient of variation meets calculating eventually Only condition, if so, calculated load cuts down probability and expectation is lost load and exported;If it is not, then repeating step 2) arrives step 8).Meter Calculating coefficient of variation may determine that the convergence situation of final desired value, that is, converge on the desired value that numerous experiments obtain.
Put aside influence of the element difference to reliability, i.e., the function for monitoring reliable probability phase of each communication node Together, using component logic structure and component reliability probability, the reliable probability by the way that function for monitoring is calculated is desired for 99.941%.
Such as Fig. 2, influence for research information system reliability to Power System Reliability carries out following two groups of emulation pair Than analysis:
Analysis is made the process of power system restoration stable state by scheduling business, is divided into following 2 in the case where power grid is by attacking Kind situation is analyzed:
Case1: thinking that information system function for monitoring is completely reliable, individually carries out reliability assessment to physical system.
Case2: considering effect of the information system to physical system, i.e., right in the case that consideration function for monitoring may fail CPPS carries out reliability assessment.
Power system component state and information system function for monitoring state are obtained first with monte carlo method, are carried out It emulates and calculates reliability index desired value for 1000 times, calculated result is as shown in table 1.
The desired value of 1 reliability index of table
Scene EENS(MW·h/y) LOLP (%)
Case1 1089.20 0.0783
Case2 1917.64 0.0796
The Comparative result of Case1 and Case2 shows: after the influence for considering function for monitoring, Reliability Index will There is substantial increase, traditional completely reliable reliability estimation method of default information system is difficult to obtain exact reliability number According to according to the comparison of reliability index under two kinds of scenes, it is found that the probability for failure occurs does not increase considerably, and reason is Function for monitoring belongs to information system to the indirectly-acting of physical system, but increasing a possibility that extension after failure can be made to occur Greatly, more serious consequence is caused.
As described above, can be seen that mentioned method can be assessed effectively according to embodiment considers that information system function for monitoring loses The Power System Reliability of effect.

Claims (7)

1. it is a kind of consider information system function for monitoring failure Model in Reliability Evaluation of Power Systems method, which is characterized in that including with Lower step:
Step 1: establishing communication network model according to the structure of electric system, input data of information system and electric power system data, The data of information system includes the component kind that function for monitoring is related to and number, component logic structure, component reliability probability; The electric power system data include the reliable probability of power system component, system load flow constraint, grid nodes input and output it is general Rate, line impedance;
Step 2: information system function for monitoring model is the part that function for monitoring is executed in communication network model, including multiple moulds Block, each module include multiple element, and the reliability of each module is established according to the component attributes of inside modules and topological structure Model, then entire information system function for monitoring reliability model is established by series relationship;By between inside modules element Logical construction calculates the reliable probability of module in function for monitoring model, then is superimposed the reliable probability of each module and obtains entirely The reliable probability of information system function for monitoring model;
Step 3: selecting system load cuts down probability and expectation loses load as power system component reliability index;
Step 4: reliable probability and power system component reliability index based on information system function for monitoring use Meng Teka Lip river method simulation information system function for monitoring state and power system component state;
Step 5: the influence that analysis information system function for monitoring fails to electric system is based on The Reliability Indicas of Gereration System, knot Function for monitoring state and power system component state are closed, the Model in Reliability Evaluation of Power Systems of function for monitoring failure is accounted for.
2. the Model in Reliability Evaluation of Power Systems method according to claim 1 for considering the failure of information system function for monitoring, It is characterized in that, in the information system function for monitoring reliability model of step 2, according to each component failure to the shadow of function for monitoring Ring the logical construction for determining model;Based on function for monitoring model foundation function for monitoring reliability model, first according to information system member Part reliable probability calculates the reliable probability of module in function for monitoring model, and it is reliable then to calculate information system function for monitoring Property probability.
3. the Model in Reliability Evaluation of Power Systems method according to claim 1 for considering the failure of information system function for monitoring, It is characterized in that, step 2 function for monitoring is related to the calculation method of the reliable probability of module are as follows: according between inside modules element Logical construction establish the reliability block diagram of each module, the structure of reliability block diagram depends on the failure of each module to function It influences;Component logic relationship is divided into train, parallel system and voting system using reliability block diagram, if train Reliability is Rs, the reliability of parallel system is Rb, the reliability of voting system is Rr, calculation formula are as follows:
In formula, n indicates the number of element in train or parallel system or voting system, RiIndicate the reliable of i-th of element Degree.
4. the Model in Reliability Evaluation of Power Systems method according to claim 1 for considering the failure of information system function for monitoring, It is characterized in that, load cuts down probability and the optimal load curtailment that is calculated as of expectation mistake load calculates, and optimal load curtailment calculates The judgment step whether started is as follows:
1) it is analysed whether according to the electric network state of simulation, including load power, generated output power and Line Flow constraint Off-the-line, if it is not, thening follow the steps 2);It is calculated if so, executing optimal load curtailment;
2) Load flow calculation is carried out according to the data under current system conditions;
3) the Line Flow limit value of breaker function for monitoring failure belonging to occurring is set as a sufficiently large numerical value, such as is set as 10000;
4) the out-of-limit total amount of computing electric power line trend, formula are as follows:
In formula: PolFor the out-of-limit total amount of transmission line of electricity trend;N is system power line number amount;PiFor the active of i-th line road; Pi_limFor the active limit value in i-th line road;
5) judge PolIt whether is 0, if it is not, then executing optimal load curtailment calculating.
5. the Model in Reliability Evaluation of Power Systems method according to claim 1 for considering the failure of information system function for monitoring, It is characterized in that, the monte carlo method in step 4 is non-sequential Monte Carlo method.
6. the Model in Reliability Evaluation of Power Systems method according to claim 1 for considering the failure of information system function for monitoring, Be characterized in that, step 4 and step 5 specifically includes the following steps:
1) it according to the data of information system of input and electric power system data, is obtained by component logic structure and component reliability probability To information system function for monitoring reliable probability, non-sequential Monte Carlo sampling is carried out, physical system components state and letter are obtained Cease system monitoring functional status;
2) judge whether function for monitoring fails, if it is not, carrying out step 4;If so, carrying out step 5;
3) consider that power grid is attacked, the primary equipment state after being attacked;
4) primary system element set of final state is obtained;
5) influence that analysis function for monitoring operates normally electric system is considered as no influence if function for monitoring does not fail;
6) the Model in Reliability Evaluation of Power Systems index for considering function for monitoring is calculated, including load cuts down probability and load is lost in expectation Amount;
7) value of assumed load reduction coefficient of variation is as loop termination condition;It is cut down according to the load being calculated every time general Rate calculated load cuts down coefficient of variation and load is lost in expectation;Judge whether load reduction coefficient of variation meets calculating and terminate item Part, if so, calculated load cuts down probability and expectation is lost load and exported;If it is not, then repeating step 2) arrives step 8).
7. the Model in Reliability Evaluation of Power Systems method according to claim 6 for considering the failure of information system function for monitoring, It is characterized in that, step 6) system loading cuts down probability and the calculation method of load is lost in expectation are as follows:
In formula, LOLPIndicate that system loading cuts down probability;EENSIndicate that load is lost in expectation;S is the collection of system all working state It closes, including information system function for monitoring state and power system component state;piFor system state i probability;CiExist for system The load reduction of state i.
CN201810604923.6A 2018-06-13 2018-06-13 A kind of Model in Reliability Evaluation of Power Systems method considering the failure of information system function for monitoring Withdrawn CN109033507A (en)

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CN109858768A (en) * 2018-12-31 2019-06-07 浙江大学华南工业技术研究院 Consider the comprehensive energy electric-thermal net methods of risk assessment of comprehensive time-varying outage model
CN110021933A (en) * 2019-05-09 2019-07-16 南京邮电大学 Consider the power information system control function reliability estimation method of component faults
CN110112745A (en) * 2019-05-24 2019-08-09 全球能源互联网研究院有限公司 Electric network information physical system means of defence, device, equipment and storage medium
CN111400890A (en) * 2020-03-11 2020-07-10 湖南大学 Attack-defense structure-based power grid upgrading method for resisting malicious data attack
CN113589780A (en) * 2021-06-30 2021-11-02 国网电力科学研究院武汉能效测评有限公司 Reliability analysis system and method of energy utilization control system based on component architecture
WO2022183722A1 (en) * 2021-03-02 2022-09-09 中国电力科学研究院有限公司 Method and apparatus for analyzing reliability of super-large scale battery energy storage power station information physical system

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109858768A (en) * 2018-12-31 2019-06-07 浙江大学华南工业技术研究院 Consider the comprehensive energy electric-thermal net methods of risk assessment of comprehensive time-varying outage model
CN110021933A (en) * 2019-05-09 2019-07-16 南京邮电大学 Consider the power information system control function reliability estimation method of component faults
CN110112745A (en) * 2019-05-24 2019-08-09 全球能源互联网研究院有限公司 Electric network information physical system means of defence, device, equipment and storage medium
CN111400890A (en) * 2020-03-11 2020-07-10 湖南大学 Attack-defense structure-based power grid upgrading method for resisting malicious data attack
WO2022183722A1 (en) * 2021-03-02 2022-09-09 中国电力科学研究院有限公司 Method and apparatus for analyzing reliability of super-large scale battery energy storage power station information physical system
CN113589780A (en) * 2021-06-30 2021-11-02 国网电力科学研究院武汉能效测评有限公司 Reliability analysis system and method of energy utilization control system based on component architecture

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Application publication date: 20181218