CN111476471A - Comprehensive energy fault diagnosis system and method based on comprehensive energy model - Google Patents
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Abstract
The invention discloses a comprehensive energy fault diagnosis system and method based on a comprehensive energy model, which are characterized in that a comprehensive energy whole-network hydrothermal electric station model is constructed, data acquisition of the whole-network hydrothermal electric station model is carried out, longitudinal comparison is carried out on various energy component data and general table data, transverse comparison is carried out on various energy fault type data, the fault rate and the fault duration are statistically analyzed at regular time of various energy fault measuring points, comprehensive evaluation is carried out, comprehensive sequencing is carried out according to the evaluation type and the evaluation fault level, the fault point with the largest influence and the fault reason are obtained, a fault instruction distribution is carried out through a fault driving system, alarm notification is carried out, the fault duration is reduced, and the high quality and reliable energy supply of the comprehensive energy system is realized.
Description
Technical Field
The invention relates to the technical field of comprehensive energy fault diagnosis, in particular to a comprehensive energy fault diagnosis system and method based on a comprehensive energy model.
Background
In order to reduce the time of the comprehensive energy failure and improve the comprehensive energy utilization rate, the common means for improving the comprehensive energy utilization rate is realized by timely energy conversion, optimization control and gate cutoff when the whole network hydrothermal electrical node fails. The method comprises the steps of determining a safe and economic fault diagnosis and analysis scheme during full-load operation of the comprehensive energy in real time on line, mainly considering the influence of fault type occupation on the whole-network hydrothermal electric operation, evaluating the influence of fault duration and fault rate, and determining an optimal fault regulation and control scheme under the condition that the safety of the comprehensive energy system and the normal operation of an optimization and regulation system are met.
And (4) comprehensive energy fault diagnosis and analysis, automatically analyzing the maximum fault grade according to the fault points of the whole network, and obtaining an optimal control scheme by combining a fault expert database.
Under the conditions of lacking 'longitudinally comparing various energy component data with general table data, transversely comparing various energy fault type data, carrying out timing statistics analysis on fault rate and fault duration at various energy fault measurement points and carrying out comprehensive evaluation', the comprehensive fault energy diagnosis method in the prior art has the defects, for example, the problem that the longitudinal comparison of various energy component data with general table data is not carried out in the prior art, so that the fault type statistics is incomplete is caused, the transverse comparison of various energy fault type data is not carried out, so that the problem that the maximum fault point is difficult to find is caused, and the problem that the fault reason analysis fails is caused.
Disclosure of Invention
The invention aims to provide a comprehensive energy fault diagnosis system and method based on a comprehensive energy model, which solve the problem of high comprehensive energy fault rate and slow comprehensive energy fault rate, improve the reliability of a comprehensive energy system, increase the energy utilization rate, improve the automation function of a comprehensive energy alarm system and improve the automation level of the comprehensive energy system.
The invention provides a comprehensive energy fault diagnosis and analysis method based on a comprehensive energy model, which comprises the following steps:
step 1, modeling the whole-network hydrothermal electric station of the comprehensive energy system, collecting model data of the whole-network hydrothermal electric station, acquiring fault measurement data of each fault station, and performing fault classification;
step 2, calculating a total data error rate K (i), a fault type ratio P (i), a fault rate F (i) and a fault duration T (i) of each fault site, wherein the total data error rate K (i) refers to a relative data deviation between energy measurement values of hydrothermal electric energy sub-meters and energy measurement values of hydrothermal electric sub-meters of each fault site, the fault type ratio P (i) refers to a proportion of fault types of the fault sites in all fault types, the fault rate F (i) refers to the number of times of faults of the fault sites, the fault duration T (i) refers to fault duration of the fault sites, and i refers to a site number;
step 3, calculating the fault grade index FC (i) of each fault station by the following formula:
in the formula:
α is the data error rate scaling factor;
β is the fault weight scaling factor;
step 4, sequencing the fault level indexes FC (i) of all the sites obtained in the step 3, and obtaining a control scheme corresponding to the maximum fault level index from an expert system;
and 5, passing and executing the control scheme.
Preferably, the step 1 comprises:
step 1.1, modeling the whole network hydrothermal electric station of the comprehensive energy system to obtain SiRepresenting sites, wherein i ∈ {1, …, X }, i represents a site number, and X represents the total number of sites;
step 1.2, collecting model data of a whole-network hydrothermal electrical station to obtain fault measurement data of a fault station;
step 1.3, the fault measurement data collected in step 1.2 is used for each fault site SiFault classification is performed and a fault class G for each fault is determined.
Preference is given toSaid step 2 comprises a step 2.1 of calculating each faulty station S according to the following formulaiThe overall data error rate of (k), (i):
in the formula:
l is failure site SiTotal energy node count of the summary table;
Da,tofor failed station SiTotal energy value of node a, wherein a ∈ {1, …, L };
m is a fault site SiThe sub-table of (1) divides the total number of energy nodes;
Db,pofor failed station SiB, wherein b ∈ {1, …, M }.
Preferably, said step 2 comprises a step 2.2 of calculating each faulty station S with the following formulaiThe fault type ratio of (a) to (b):
in the formula:
n is fault site SiTotal number of fault types;
j is the fault type number, j ∈ {1, …, N };
Tjfor failed station SiThe total fault node fault value of the fault type j;
γjfor failed station SiFault type j of (a) has a fault coefficient ratio, γjWith set fault type j fault class GjAre reciprocal of each other.
Preferably, the step 2 includes a step 2.3, before calculating the fault rate and the fault duration, performing effective fault checking by using the following formula:
in the formula:
tsttime of occurrence of the fault;
tedtime of fault end;
tincollecting a time interval for fault information data;
Δ t is the time of fault duration;
Δtminchecking a threshold for a valid fault;
b (t) indicates a failure state, b (t) 0 indicates no failure, and b (t) 1 indicates a failure;
if the formula is met, an effective fault occurs once, and the fault duration time delta t is the effective fault duration time.
Preferably, said step 2 comprises a step 2.4 of calculating each faulty station S with the following formulaiFailure rate of (f), (i):
in the formula:
n is fault site SiTotal number of types of faults that occurred;
j is the fault type number, j ∈ {1, …, N };
fjfor failed station SiNumber of valid failures of the type of failure j that occurred.
Preferably, said step 2 comprises a step 2.5 of calculating each faulty station S with the following formulaiTime period t (i) of failure:
in the formula:
n is fault site SiTotal number of types of faults that occurred;
j is the fault type number, j ∈ {1, …, N };
Δtjfor failed station SiThe effective fault duration of the type of fault j that occurs.
Preferably, data error rate scaling factor α has a value of 0.75,
the fault weight scaling factor β has a value of 0.667.
Preferably, step 4 obtains the control scheme corresponding to the maximum fault level indicator according to the following formula:
in the formula:
ST[FC(i)]inputting the fault grade evaluation indexes of all fault sites as a function sorted according to the value, and returning a result irkIs i1,…,ixThe index F (i) of the fault level indicates the number of fault sites with the value from large to small, x is the number of sites with faults, and the fault sites
Fault level index FC (i)1) Maximum value of (c), failed site
Is a fault site with priority alarm and regulation;
FT (i) is a fault type function, the input is a fault site number i, and the return result j is the fault type of the current fault site;
ES (j) is an expert system, inputs the fault type j, and returns a result P LocA control scheme for a current fault type;
and the step 5 of passing and executing the control scheme means that the control scheme generated in the step 4 is used for distributing fault instructions through the fault driving system, sequentially executing the fault plan, returning a fault diagnosis success quality code and sending an alarm.
The present invention also provides an integrated energy fault diagnosis system using an integrated energy fault diagnosis analysis method based on an integrated energy model, which is applicable to an integrated energy system, the integrated energy fault diagnosis system including: the comprehensive energy system full-network modeling simulation platform, the wide-area measurement system and the communication network, wherein the fault diagnosis system further comprises: the fault data processing module and the fault driving system; the comprehensive energy system whole-network modeling simulation platform is used for modeling a comprehensive energy system whole-network hydrothermal electrical site; the wide area measurement system is used for collecting fault measurement data according to the comprehensive energy system whole-network hydrothermal electric station model; the fault data processing module is used for calculating fault information data to form fault level index value sequencing and selecting a control scheme from the expert system according to the fault level index value sequencing; the fault driving system is used for sequentially executing a fault plan through a control scheme and sending an alarm.
Compared with the prior art, the invention has the advantages that the fault type statistics is comprehensive by longitudinally comparing various energy component data with general table data, the maximum fault point searching is rapid and accurate by transversely comparing various energy fault type data, the fault rate and the fault duration are statistically analyzed at the timing of various energy fault measuring points, the comprehensive evaluation is carried out, the comprehensive ordering is carried out according to the evaluation type and the evaluation fault level, the fault point with the largest influence and the fault reason are obtained, the fault driving system is used for distributing fault instructions, giving an alarm and informing, so that the fault duration is reduced, the fault positioning is more accurate, the problem that the comprehensive energy fault rate is high and the problem that the comprehensive energy fault rate is slow is solved, the reliability of the comprehensive energy system is improved, the energy utilization rate is increased, the automation function of the comprehensive energy alarm system is improved, and the automation level of the comprehensive energy system is improved.
Drawings
FIG. 1 is a schematic flow chart of a comprehensive energy fault diagnosis and analysis method based on a comprehensive energy model according to the disclosure;
fig. 2 is a schematic diagram of the integrated energy fault analysis implementation process of the present invention.
Detailed Description
The technical scheme of the invention is further explained in detail by combining the drawings in the specification.
The invention discloses a comprehensive Energy fault diagnosis System and method based on a comprehensive Energy model, which is suitable for an Integrated Energy System (IES), wherein the IES whole network comprises a plurality of hydrothermal electric stations S to correct and integrateThe numerical subscripts being the number of the respective hydrothermal electric stations S, e.g. S9Indicating site No. 9 in the IES. One hydro-thermal electric station S comprises a plurality of total energy nodes of the total energy, namely the total energy quantity of a total table end, wherein the total energy refers to the total table energy measurement value of the total table end, and the energy statistics of one hydro-thermal electric station S at the total table end is the total energy DtoOne water-heating electric station S comprises a plurality of sub-meter sub-energy nodes, namely, the sub-meter number of the sub-meter end, wherein the sub-energy refers to the sub-meter energy measurement value of the sub-meter end, and the energy of one water-heating electric station S at the sub-meter end is counted as the sub-energy Dpo。
The invention provides a comprehensive energy fault diagnosis method based on a comprehensive energy model, which is shown in the attached figure 1 and comprises the following steps:
step 1: modeling the whole-network hydrothermal electric station of the comprehensive energy system, collecting model data of the whole-network hydrothermal electric station, acquiring fault measurement data of each fault station, and performing fault classification.
Specifically, step 1.1, IES full-network hydrothermal electrical station S is subjected to modeling simulation platformiModeling is performed with SiRepresents sites, where i ∈ {1, …, X }, i represents a site number, and X represents the total number of sites.
Hydrothermal electrical site modeling belongs to the prior art, for example, comprehensive energy system modeling and benefit evaluation system overview and prospect [ J ] (great, et al. electric network technology, 2018,42(06): 1697-.
And step 1.2, acquiring fault measurement data through a wide area measurement system.
Step 1.3, for each fault site SiPerforming fault classification, the fault classification being a fault level indicatorThe basis of the evaluation includes, but is not limited to, generator failure, transformer failure, load failure, ac switch failure, ac knife-switch failure, ac bus failure, electrical load failure, air conditioning unit failure, gas compressor failure, gas boiler failure, gas pipeline failure, gas load failure, gas tank failure, gas valve failure, thermal compressor failure, heat pipe network failure, heat source failure, thermal load failure, thermal valve failure, relay pump failure, water pipeline failure, water load failure, water tower meter failure, water valve failure, microgrid inverter failure; and determining a fault grade G of each fault, wherein the smaller the value of the fault grade is, the larger the weight proportion is, the weight proportion is 100% when the fault grade is 1 grade, the weight proportion is 66.7% when the fault grade is 1.5 grade, and the like.
Step 1.4, as shown in fig. 2, the IES receives the fault analysis command issued by the scheduling center, and the whole network performs model correctness checking and measurement validity checking, if the measurement validity check fails, the system automatically performs measurement revision work, screens dead data and bad data, retains valid data, and returning the revised measurement data of the dispatching center, the dispatching center updates the measurement data according to the returned measurement data, if the model check fails and is directly returned to the dispatching center model error quality code, the dispatching center receives the model error quality code and then issues a model calling instruction, the IES returns the whole network model, the dispatching center modifies the model, and issuing a model modification instruction, returning the IES modification model to the model modification success instruction, performing data summarization on the whole network data by the scheduling center at the moment, and repeating the operation of the step 1.4, if the verification is successful, continuing to execute the following steps.
Step 2: calculating each fault site SiThe total data error rate after fault classification K (i), the fault type ratio P (i), the fault rate F (i) and the fault time length T (i), wherein,
the total data error rate K (i) refers to the deviation of each total energy and each fractional energy data;
the fault type proportion P (i) refers to the weight ratio of each fault type in the total type;
the failure rate F (i) refers to the effective number of failures occurring, and
the fault duration t (i) refers to the duration of time during which a valid fault occurs.
In particular, each faulty station S is calculated in step 2.1 as followsiThe overall data error rate of (k), (i):
in the formula:
l is failure site SiTotal energy node count of the summary table;
Da,tofor failed station SiTotal energy value of node a, wherein a ∈ {1, …, L };
m is a fault site SiThe sub-table of (1) divides the total number of energy nodes;
Db,pofor failed station SiThe fractional energy value of node b of (1), wherein b ∈ {1, …, M };
k (i) for each failed site SiLongitudinal comparison of hydrothermal electrical energy component data with summary data, the larger the value of k (i) indicates the greater the deviation of the data.
In particular, each faulty station S is calculated in step 2.2 as followsiThe fault type ratio of (a) to (b):
in the formula:
n is fault site SiTotal number of fault types;
j is the fault type number, j ∈ {1, …, N };
Tjthe total fault value of the fault node is a fault type j, and the total fault value refers to the energy values of all the generated fault meters;
γjthe fault coefficient ratio is the fault type j, the fault coefficient ratio refers to the weight coefficient of the grade participating in the fault calculation, and the fault coefficient ratio gamma isjFailure with failure type j, etcStage GjIs inverse relation, i.e. gammaj＝1/Gj；
P (i) for each failed site SiA lateral comparison of fault type data, a larger value of p (i) indicates a larger fault weight ratio.
Specifically, in step 2.3, the failed site S is addressed with the following formulaiAnd (3) carrying out effective fault checking on the fault after fault classification:
in the formula:
tsttime of occurrence of the fault;
tedtime of fault end;
tincollecting a time interval for fault information data;
Δ t is the time of fault duration;
Δtminchecking a threshold for a valid fault;
b (t) indicates a failure state, b (t) 0 indicates no failure, and b (t) 1 indicates a failure;
if the formula is met, an effective fault occurs once, and the fault duration time delta t is the effective fault duration time. That is, when changing from a no-fault state to a fault state and the duration is greater than the active fault check threshold, e.g., 15 seconds, an active fault is counted, and the fault duration Δ t is counted as an active fault duration.
Specifically, in step 2.4, the failed site S is addressed with the following formulaiFailure rate of (f), (i):
in the formula:
n is fault site SiTotal number of fault types;
j is the fault type number, j ∈ {1, …, N };
fjthe number of valid faults of the fault type j;
f (i) characterizing the failed site SiThe larger the value of f (i), the greater the failure probability.
Specifically, in step 2.5 the failed site S is addressed with the following formulaiTime period t (i) of failure:
in the formula:
n is the total number of fault types;
j is the fault type number, j ∈ {1, …, N };
Δtjan effective fault duration for fault type j;
t (i) characterise the respective failed site SiA larger value of t (i) indicates a longer fault time.
And step 3: comprehensive evaluation all hydrothermal electrical fault stations S of whole networkiFault class index of (FC), (i)
In the formula:
i is a fault site SiNumbering;
FC (i) is a failed site SiA fault level indicator of (a);
k (i) is a failed site SiA fractional total data error rate of;
p (i) is a failed site SiFault type fraction of (2);
f (i) is a failed site SiThe failure rate of (c);
t (i) is a failed site SiThe fault duration of (c);
α is a data error rate scaling factor, and a preferred value of α is set to 0.75 based on daily site total error rate weight, energy type, and/or other factors;
β is a fault weight scaling factor, and a preferred value of the fault weight scaling factor β is set to 0.667 based on the fault rate weight, the type of fault, and/or other factors.
The fault grade index formula is obtained by accumulating according to fault analysis statistical results and daily user demand experience, and one energy station S can be fully embodied according to the four indexesiAnd in the most comprehensive fault condition, the fault grade index is used as the most important fault judging basis of one energy station.
And 4, step 4: and sequencing the fault sites according to the size of the comprehensive energy evaluation fault level index values. And (3) taking the fault site with the largest evaluation fault level index value FC (i) as a priority alarm and control station, and selecting an optimal control scheme from a fault expert system according to the fault type of the station. The invention is characterized in that the expert system is sequenced according to the evaluation fault grade index values of the comprehensive energy resources, and an optimal control scheme which takes priority alarm and station regulation as the primary target is obtained from the expert system instead of the optimal control scheme aiming at a specific fault type, so that the expert system is not detailed any more, namely, any expert system meeting the requirements of the specific comprehensive energy resource system can be used.
Namely, the IES full-network fault handling scheme is generated according to the following formula:
in the formula:
ST[FC(i)]inputting the fault grade evaluation indexes of all fault sites as a function sorted according to the value, and returning a result irkIs i1,…,ixThe index F (i) of the fault level indicates the number of fault sites with the value from large to small, x is the number of sites with faults, and the fault sites
Fault level index FC (i)1) The value of (a) is the largest,trouble station
Is a fault site with priority alarm and regulation;
FT (i) is a fault type function, the input is a fault site number i, and the return result j is the fault type of the current fault site;
ES (j) is an expert system function, the input is a fault type j, and the returned result P LocAn optimal control (oc as subscript) scheme for the current fault type;
and 5: and 4, distributing fault instructions through the fault driving system according to the optimal control scheme generated in the step 4, sequentially executing a fault plan, returning a fault analysis success quality code to the IES dispatching center, and sending an alarm.
The invention also provides a comprehensive energy fault diagnosis system based on the comprehensive energy model, which is suitable for the comprehensive energy system and comprises the following components: the system comprises a comprehensive energy system whole-network modeling simulation platform, a wide-area measurement system, a communication network, a fault data processing module and a fault driving system. The integrated energy system whole-network modeling simulation platform is used for modeling an IES whole-network hydrothermal electrical site; the wide area measurement system is used for collecting fault information data according to an IES full-network hydrothermal electrical site model; the fault data processing module is used for calculating fault information data to form fault level index value sequencing and selecting an optimal control scheme from the expert system according to the fault level index value sequencing; and the fault driving system is used for sequentially executing a fault plan through an optimal control scheme, returning a fault analysis success quality code to the IES dispatching center and sending an alarm.
Compared with the prior art, the invention has the advantages that the fault type statistics is comprehensive by longitudinally comparing various energy component data with general table data, the maximum fault point searching is rapid and accurate by transversely comparing various energy fault type data, the fault rate and the fault duration are statistically analyzed at the timing of various energy fault measuring points, the comprehensive evaluation is carried out, the comprehensive ordering is carried out according to the evaluation type and the evaluation fault level, the fault point with the largest influence and the fault reason are obtained, the fault driving system is used for distributing fault instructions, giving an alarm and informing, so that the fault duration is reduced, the fault positioning is more accurate, the problem that the comprehensive energy fault rate is high and the problem that the comprehensive energy fault rate is slow is solved, the reliability of the comprehensive energy system is improved, the energy utilization rate is increased, the automation function of the comprehensive energy alarm system is improved, and the automation level of the comprehensive energy system is improved.
The foregoing is illustrative of the preferred embodiment of the present invention and is not to be construed as limiting thereof, since any modification or variation thereof within the spirit of the invention is intended to be covered thereby.
Claims (10)
1. A comprehensive energy fault diagnosis and analysis method based on a comprehensive energy model is characterized by comprising the following steps:
step 1, modeling the whole-network hydrothermal electric station of the comprehensive energy system, collecting model data of the whole-network hydrothermal electric station, acquiring fault measurement data of each fault station, and performing fault classification;
step 2, calculating a total data error rate K (i), a fault type ratio P (i), a fault rate F (i) and a fault duration T (i) of each fault site, wherein the total data error rate K (i) refers to a relative data deviation between energy measurement values of hydrothermal electric energy sub-meters and energy measurement values of hydrothermal electric sub-meters of each fault site, the fault type ratio P (i) refers to a proportion of fault types of the fault sites in all fault types, the fault rate F (i) refers to the number of times of faults of the fault sites, the fault duration T (i) refers to fault duration of the fault sites, and i refers to a site number;
step 3, calculating the fault grade index FC (i) of each fault station by the following formula:
in the formula:
α is the data error rate scaling factor;
β is the fault weight scaling factor;
step 4, sequencing the fault level indexes FC (i) of all the sites obtained in the step 3, and obtaining a control scheme corresponding to the maximum fault level index from an expert system;
and 5, passing and executing the control scheme.
2. The integrated energy fault diagnosis analysis method according to claim 1,
the step 1 comprises the following steps:
step 1.1, modeling the whole network hydrothermal electric station of the comprehensive energy system to obtain SiRepresenting sites, wherein i ∈ {1, …, X }, i represents a site number, and X represents the total number of sites;
step 1.2, collecting model data of a whole-network hydrothermal electrical station to obtain fault measurement data of a fault station;
step 1.3, the fault measurement data collected in step 1.2 is used for each fault site SiFault classification is performed and a fault class G for each fault is determined.
3. The integrated energy fault diagnosis analysis method according to claim 2,
said step 2 comprises a step 2.1 of calculating the respective failed site S according to the following formulaiThe overall data error rate of (k), (i):
in the formula:
l is failure site SiTotal energy node count of the summary table;
Da,tofor failed station SiTotal energy value of node a, wherein a ∈ {1, …, L };
m is a fault site SiThe sub-table of (1) divides the total number of energy nodes;
Db,pofor this reasonBarrier site SiB, wherein b ∈ {1, …, M }.
4. The integrated energy fault diagnosis analysis method according to claim 2,
said step 2 comprises a step 2.2 of calculating each faulty station S according to the following formulaiThe fault type ratio of (a) to (b):
in the formula:
n is fault site SiTotal number of fault types;
j is the fault type number, j ∈ {1, …, N };
Tjfor failed station SiThe total fault node fault value of the fault type j;
γjfor failed station SiFault type j of (a) has a fault coefficient ratio, γjWith set fault type j fault class GjAre reciprocal of each other.
5. The integrated energy fault diagnosis analysis method according to claim 2,
the step 2 includes a step 2.3, before calculating the fault rate and the fault duration, effective fault checking is performed by adopting the following formula:
in the formula:
tsttime of occurrence of the fault;
tedtime of fault end;
tincollecting a time interval for fault information data;
Δ t is the time of fault duration;
Δtminchecking a threshold for a valid fault;
b (t) indicates a failure state, b (t) 0 indicates no failure, and b (t) 1 indicates a failure;
if the formula is met, an effective fault occurs once, and the fault duration time delta t is the effective fault duration time.
6. The integrated energy fault diagnosis analysis method according to claim 5,
said step 2 comprises a step 2.4 of calculating each faulty station S according to the following formulaiFailure rate of (f), (i):
in the formula:
n is fault site SiTotal number of types of faults that occurred;
j is the fault type number, j ∈ {1, …, N };
fjfor failed station SiNumber of valid failures of the type of failure j that occurred.
7. The integrated energy fault diagnosis analysis method according to claim 5 or 6,
said step 2 comprises a step 2.5 of calculating each faulty station S according to the following formulaiTime period t (i) of failure:
in the formula:
n is fault site SiTotal number of types of faults that occurred;
j is the fault type number, j ∈ {1, …, N };
Δtjfor failed station SiThe effective fault duration of the type of fault j that occurs.
8. The integrated energy fault diagnosis analysis method according to any one of claims 2 to 8,
the data error rate scaling factor α has a value of 0.75,
the fault weight scaling factor β has a value of 0.667.
9. The integrated energy fault diagnosis analysis method according to claim 8,
step 4, obtaining a control scheme corresponding to the maximum fault level index according to the following formula:
in the formula:
ST[FC(i)]inputting the fault grade evaluation indexes of all fault sites as a function sorted according to the value, and returning a result irkIs i1,…,ixThe index F (i) of the fault level indicates the number of fault sites with the value from large to small, x is the number of sites with faults, and the fault sites
Fault level index FC (i)1) Maximum value of (c), failed site
Is a fault site with priority alarm and regulation;
FT (i) is a fault type function, the input is a fault site number i, and the return result j is the fault type of the current fault site;
ES (j) is an expert system, inputs the fault type j, and returns a result P LocA control scheme for a current fault type;
and the step 5 of passing and executing the control scheme means that the control scheme generated in the step 4 is used for distributing fault instructions through the fault driving system, sequentially executing the fault plan, returning a fault diagnosis success quality code and sending an alarm.
10. An integrated energy fault diagnosis system using the integrated energy fault diagnosis analysis method based on the integrated energy model according to any one of claims 1 to 9, applied to an integrated energy system, the integrated energy fault diagnosis system comprising: comprehensive energy system full-network modeling simulation platform, wide area measurement system, communication network, its characterized in that:
the fault diagnosis system further includes: the fault data processing module and the fault driving system;
the comprehensive energy system whole-network modeling simulation platform is used for modeling a comprehensive energy system whole-network hydrothermal electrical site;
the wide area measurement system is used for collecting fault measurement data according to the comprehensive energy system whole-network hydrothermal electric station model;
the fault data processing module is used for calculating fault measurement data to form fault level index value sequencing and selecting a control scheme from the expert system according to the fault level index value sequencing;
the fault driving system is used for sequentially executing a fault plan through a control scheme and sending an alarm.
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