Fault monitoring system and method for water-turbine generator set cluster

Abstract

The invention relates to the technical field of generator set monitoring, in particular to a fault monitoring system and method for a water-turbine generator set cluster. According to the method, possible concerned units are determined according to fluctuation of current and output power of the units at an analysis moment; on the basis of operation power distribution of the concerned unit corresponding to other normal units, ideal load increasing power is obtained, and key units with faults are screened through the matching degree of load distribution transfer; and verifying a combined fault condition through load transfer distribution of the combined concerned unit under the condition of initial screening of the non-key unit, and obtaining a fault monitoring result. Condition verification is carried out on unit faults through single and combinatorial analysis of the unit power load decline degree under the abnormal condition and the load distribution matching degree of other units, so that the faults of the multiple unit groups are more accurately positioned.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of generator set monitoring, in particular to a fault monitoring system and method for a hydroelectric generator set cluster. BACKGROUND

[0002] The hydroelectric generator set cluster refers to a configuration in which multiple hydroelectric generator sets are connected in parallel and run in the same hydropower station or the same hydropower system. Generally, the role of the hydroelectric generator set is to convert the kinetic energy of water flow into electric energy, thereby improving the total output power and stability of the system. When multiple sets are connected in parallel, they can be flexibly configured and adjusted according to different water flow conditions, power generation requirements, and requirements of the power system, thereby providing stable power output and maintaining the stability of the overall system.

[0003] Since the hydroelectric generator set cluster is connected by multiple sets in parallel, the generators connected in parallel are connected through a common bus, and the connection impedance and bus impedance between them form multiple current paths. If a fault occurs in a certain set, the current will be shunted, and even the non-fault set will also bear a significant fault-induced current. At this time, if the fault is detected directly through the voltage and current abnormal values of the set, errors will occur in the positioning and judgment of the fault set, thereby affecting the subsequent fault maintenance of the set cluster. SUMMARY

[0004] In order to solve the technical problem that the positioning and judgment of the fault set will be erroneous when the fault is detected directly through the voltage and current abnormal values of the set, thereby affecting the subsequent fault maintenance of the set cluster in the prior art, the purpose of the present application is to provide a fault monitoring system and method for a hydroelectric generator set cluster, and the technical solution adopted is as follows: The present application provides a fault monitoring method for a hydroelectric generator set cluster, which comprises: obtaining current data and output power of each set in the hydroelectric generator set cluster; screening a concerned set according to the peak fluctuation of the current data and the deviation of the output power of each set in the historical time sequence, and obtaining the ideal load increase power of the concerned set corresponding to the non-concerned set according to the output power decrease of the single concerned set and the output power distribution of the non-concerned set; for each concerned set, obtaining the load transfer matching abnormality of the concerned set according to the deviation of the actual output power increase of all non-concerned sets and the ideal load power, and the matching condition of the output power loss of the concerned set; and determining a key set among all concerned sets based on the load transfer matching abnormality; if there is no key set, determining the fault monitoring result according to the power load transfer distribution verification of the non-concerned set corresponding to the combined concerned set.

[0005] Further, the acquisition method of the concerned unit includes: For any one unit, determine the peak period of current data of the unit on the historical time sequence; On each peak period, the difference between the maximum current data and the expected current data is taken as the mutation degree; the time difference between the time corresponding to the maximum current data and the initial time of the peak period is taken as the time consumption degree; the ratio between the mutation degree and the time consumption degree of each peak period is taken as the fluctuation index of each peak period; and the average value of the fluctuation indexes of all peak periods is taken as the current fault significance of the unit. The difference between the expected power of the unit and the output power at the current time is taken as the power deviation index of the unit; and the concern degree of the unit is obtained in combination with the current fault significance and the power deviation index of the unit. The unit with the concern degree greater than the preset concern threshold is taken as the concerned unit.

[0006] Further, the acquisition method of the ideal load growth power includes: For any one concerned unit, the difference between the current output power and the rated power of the concerned unit is taken as the power loss degree of the concerned unit. Each non-concerned unit is sequentially taken as an analysis unit; the ratio between the maximum output power of the analysis unit and the maximum power of the unit cluster is taken as the power proportion coefficient of the analysis unit; and the product of the current margin load and the power proportion coefficient of the analysis unit is taken as the load distribution coefficient of the analysis unit. The ratio between the load distribution coefficient of the analysis unit and the sum of the load distribution coefficients of all non-concerned units is taken as the load distribution weight of the analysis unit. The product of the load distribution weight of the analysis unit and the power loss degree is taken as the ideal load growth power of the concerned unit corresponding to the analysis unit.

[0007] Further, the acquisition method of the load transfer matching abnormality degree includes: For any one concerned unit, the actual growth amount of the current output power of each non-concerned unit corresponding to the concerned unit is obtained; the power difference between the actual growth amount of each non-concerned unit corresponding to the concerned unit and the ideal load growth power is calculated, and the sum of all power differences is taken as the normal theoretical deviation degree of the concerned unit. The difference between the sum of the actual growth amounts of all non-concerned units corresponding to the concerned unit and the power loss degree of the concerned unit is taken as the distribution deviation degree of the concerned unit. The load transfer matching abnormality degree of the concerned unit is obtained in combination with the normal theoretical deviation degree and the distribution deviation degree of the concerned unit.

[0008] Further, the acquisition method of the key unit comprises: The unit with the load transfer matching abnormality less than the preset fault threshold is taken as the key unit.

[0009] Further, if there is no key unit, the fault monitoring result is determined according to the power load transfer distribution verification of the non-concerned units corresponding to the combined concerned units, comprising: A different combination scheme of the concerned units is acquired. When there is a combination scheme, the output power increase of all the non-concerned units under the combination scheme is consistent with the output power decrease of the concerned units under the combination scheme, and the output power increase of each non-concerned unit is consistent with the ideal load increase power of the concerned units under the combination scheme, the concerned units of the combination scheme are taken as the key units. When there is a key unit, the fault detection result is recorded as existing fault.

[0010] Further, the acquisition method of the peak period comprises: A peak point of the current data on the historical time sequence of the unit is acquired. For any peak point, the time point of the period of the peak point is taken as the time point of the period of the peak point, and the time point of the period of the peak point is taken as the time point of the period of the peak point. The period composed of the time point corresponding to the peak point and all the time points of the period is taken as the peak period of the peak point.

[0011] Further, the margin load is the difference between the maximum output power of the analysis unit and the current output power.

[0012] Further, the different combination schemes of the concerned units comprise: Two or more non-repeated concerned units are selected from all the concerned units, and each selection is taken as a combination scheme.

[0013] The application further provides a fault monitoring system of a hydroelectric generating unit cluster, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and the processor implements the steps of any one of the above methods when executing the computer program.

[0014] The application has the following beneficial effects: The application determines possible attention units by analyzing the fluctuation of the current and output power of the units at the analysis moment, considers the load distribution transfer situation after screening the possible abnormal units, obtains the ideal load growth power based on the operation power distribution of the attention units to other normal units, and further more accurately screens the key units with faults through the matching degree of load distribution transfer. After single fault abnormality analysis, the common load transfer possibility of multi-fault units is considered, the combined fault condition is verified through the load transfer distribution of the combined attention units screened from the non-key units, and more accurate and reliable fault monitoring results are obtained. The application verifies the units with faults by analyzing the power load reduction degree of the units with abnormal conditions and the load distribution matching degree to other units, so that the accurate positioning of the faults of the multi-unit group is more accurate. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0016] Figure 1 A flow chart of a fault monitoring method of a hydroelectric generating unit cluster provided by an embodiment of the present application; Figure 2 A distribution schematic diagram of a hydroelectric generating unit cluster provided by an embodiment of the present application. DETAILED DESCRIPTION

[0017] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following describes the specific implementation, structure, features and effects of a fault monitoring system and method of a hydroelectric generating unit cluster according to the present application in combination with the drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0019] The following specifically describes the specific scheme of the fault monitoring system and method of the hydroelectric generating unit cluster provided by the present application in combination with the drawings.

[0020] Please refer to Figure 1Fig. 1 shows a flow chart of a method for monitoring a fault of a hydroelectric generating set cluster according to an embodiment of the present application, which comprises the following steps: S1: obtaining current data and output power of each hydroelectric generating set in the hydroelectric generating set cluster.

[0021] The hydroelectric generating set cluster is usually composed of multiple hydroelectric generating sets of the same or different types, and the generators corresponding to each hydroelectric generator are connected in parallel to output current. The main function of the hydroelectric generating set is to generate power to bear the power load, and it provides stable power output by connecting multiple hydroelectric generators in parallel. Please refer to Figure 2 Fig. 2 shows a distribution diagram of a hydroelectric generating set cluster according to an embodiment of the present application.

[0022] Since the hydroelectric generating set cluster meets the corresponding power output requirement by connecting in parallel branch lines, considering the shunt characteristics of parallel connection, if a certain hydroelectric generator fails, it will cause other non-fault hydroelectric generators to also bear current fluctuations. The fault current does not only occur in the hydroelectric generator that fails, but also occurs in the non-fault hydroelectric generators, which makes the fault detection positioning misjudge other hydroelectric generators.

[0023] In order to more accurately locate the hydroelectric generator that may fail, the real-time current data and output power of different hydroelectric generators are monitored in this embodiment. In general, the hydroelectric generating set cluster has a corresponding fault load power redistribution strategy, so the real-time output power load transfer of different hydroelectric generators is monitored, which is convenient for subsequent analysis of the operation state and load distribution matching of multiple hydroelectric generators to locate the fault hydroelectric generator. It should be noted that data acquisition is a technology known to those skilled in the art, which is collected by installing corresponding sensors. Here, the specific installation and collection process is not limited and described.

[0024] S2: screening the concerned hydroelectric generators according to the peak fluctuation of the current data and the deviation degree of the output power of each hydroelectric generator in the historical time sequence, and obtaining the ideal load growth power of the non-concerned hydroelectric generators corresponding to the concerned hydroelectric generators according to the output power decrease degree of the single concerned hydroelectric generator and the output power distribution of the non-concerned hydroelectric generators.

[0025] Since the fault characteristics of the fault hydroelectric generator are not obvious due to current shunt, the possible concerned hydroelectric generators are preliminarily determined by combining the current data and output power of different hydroelectric generators, and then the preliminary load distribution possibility analysis is performed based on the operation load distribution of the other hydroelectric generators under the concerned hydroelectric generators.

[0026] The hydroelectric generator set is generally driven by water flow to rotate the water turbine, and the water turbine drives the generator to rotate through the linkage shaft to combine the excitation system to output current. However, the fault current will increase sharply due to short circuit or grounding fault during the operation of the unit, and the shunt effect generated in parallel will distribute the fault current to other normal units, resulting in significant current surge of multiple units.

[0027] Therefore, in the embodiment of the present application, first, the possible fault attention unit is determined by the current data and output power of different units, and the acquisition method of the attention unit includes: Firstly, for any one unit, the peak period of the current data in the historical time sequence of the unit is determined. Since the fault current of the unit refers to the sharp increase of the operating current caused by the short circuit, grounding and other problems at the fault point when the generator set or power system fails. The power system is usually designed with a protection system, and the protection device will trigger after the current reaches a certain value, and quickly disconnect the fault circuit, thereby limiting the duration of the fault current.

[0028] Therefore, the fault current generally presents a sharp peak, and in the embodiment of the present application, the peak point of the current data in the historical time sequence of the unit is obtained. For any one peak point, the time point of the continuous positive slope before the peak point is taken as the time point of the peak period of the peak point, and the time point of the continuous negative slope after the peak point is taken as the time point of the peak period of the peak point. The peak period of the peak point is obtained by the continuous increasing time before the peak point and the continuous decreasing time after the peak point. The time period composed of the time point corresponding to the peak point and all time points is taken as the peak period of the peak point.

[0029] It should be noted that the acquisition of the peak value and the slope is a well-known technical means for those skilled in the art, and the peak point can be obtained by using a peak detection algorithm, which is not limited and described here.

[0030] Further, in each peak period, the difference between the maximum current data and the expected current data is taken as the mutation degree, and the greater the mutation degree, the more intense the mutation of the operating current. The time difference between the time point corresponding to the maximum current data and the initial time point of the peak period is taken as the time consumption, and the smaller the time consumption, the shorter the time spent on the mutation.

[0031] Therefore, the ratio between the mutation degree and the time consumption of each peak period is taken as the fluctuation index of each peak period, and the greater the fluctuation index, the sharper the current fluctuation, and the more likely the peak current is the fault current. The average of the fluctuation indexes of all peak periods in the time sequence is taken as the current fault significance of the unit, and the greater the current fault significance, the more likely the unit has a fault current.

[0032] But the unit that does not exist fault current does not necessarily produce fault, the shunt effect can cause normal unit to also appear fault current, so further judgment is needed. Generally, the operation of the fault unit will be affected, causing its output power to decrease, and the unit receiving shunt will be less affected by the presence of protection devices, so further analysis is needed in combination with power deviation.

[0033] Further, the difference between the expected power of the unit and the output power at the current time is taken as the power deviation index of the unit. The greater the power deviation index, the greater the real-time output power decrease value of the unit, and the more obvious the power decrease. It can be understood that the expected power is the output power of the generator unit under normal circumstances. In the embodiment of the present application, considering that the output power increases with the increase of the speed of the motor rotor, the two are positively correlated, so a motor speed-output power model is established based on the speed parameter of the motor, and the electronic speed of the unit is input into the model to obtain the expected power. In other embodiments of the present application, the implementer of the expected power can set it according to the specific implementation scene requirements, which is not limited here.

[0034] In combination with the current fault salience and power deviation index of the unit, the attention degree of the unit is obtained. In the embodiment of the present application, the product of the current fault salience and power deviation index of the unit is taken as the attention degree of the unit. The greater the attention degree, the higher the possibility that the unit is a fault-producing unit.

[0035] After normalization processing of the attention degree, the possible fault-producing unit is marked. The unit with an attention degree greater than a preset attention threshold is taken as the attention unit. In the embodiment of the present application, the preset attention threshold is set to 0.85, and the specific value can be adjusted by the implementer, which is not limited here. It should be noted that normalization is a well-known technical means for those skilled in the art, and the selection of normalization can be linear normalization or standard normalization, and the specific normalization method is not limited here.

[0036] The attention unit is a preliminary abnormality screening for different unit operating states, but the operating state of the hydroelectric generator unit is associated with the load bearing capacity. Only through the abnormality of the operating state, it cannot be accurately determined whether there is a fault. For example, the measurement signal may be affected by high-frequency interference during collection and transmission, causing misjudgment or missed detection, so it is also necessary to combine the functional output results of the hydroelectric generator unit for comprehensive evaluation.

[0037] If a certain unit fails, the corresponding power generation capacity will be limited and unable to bear the corresponding load, resulting in a decrease in its output power. Due to the parallel relationship between different units, the normal units will maintain normal load output. In order to maintain the stability of the output power between different units in the unit cluster, there is a corresponding load distribution strategy for the failed unit. Under this strategy, the power lost by the failed unit will be transferred to other normal units, and the output power of the normal units will be appropriately increased to fill the vacancy. Therefore, the load transfer situation of different units in the cluster can be verified.

[0038] Based on this feature, the failure of the concerned unit can be functionally verified. First, the load to which each normal unit should be allocated needs to be analyzed. Preferably, in the embodiments of the present application, the method for obtaining the ideal load growth power includes: First, for any concerned unit, the difference between the current output power and the rated power of the concerned unit is taken as the power loss degree of the concerned unit. Generally, the output power of the unit that actually fails decreases to a relatively high degree.

[0039] In turn, each non-concerned unit is taken as an analysis unit, and the failure of the concerned unit is analyzed. Generally, the load distribution strategy of the unit distributes the power through the maximum output capacity of different units and the real-time margin.

[0040] Therefore, the ratio of the maximum output power of the analysis unit to the maximum power of the unit cluster is taken as the power proportion coefficient of the analysis unit, and the product of the current margin load of the analysis unit and the power proportion coefficient is taken as the load distribution coefficient of the analysis unit. In the embodiments of the present application, the margin load is the difference between the maximum output power of the analysis unit and the current output power. According to the load distribution strategy of the cluster, the proportion of the normal unit when receiving the transferred power of the failed unit is calculated based on the maximum power, which is used to determine the amount of transferred power that each normal unit should theoretically receive in the subsequent process. The greater the load distribution coefficient, the stronger the load bearing capacity of the analysis unit.

[0041] Further, the ratio between the load distribution coefficient of the analysis unit and the sum of the load distribution coefficients of all non-concerned units is taken as the load distribution weight of the analysis unit. The greater the weight, the greater the loss load distributed to the analysis unit through the normalization processing of the total distribution. Then, the theoretical increase value of the output power loss of the concerned unit is obtained.

[0042] Finally, the product of the load distribution weight of the analysis unit and the power loss degree is taken as the ideal load growth power of the corresponding analysis unit of the concerned unit. According to the power loss degree of the concerned unit and the load distribution coefficient of each normal unit, the amount of transferred power that each normal unit should theoretically receive from the failed unit is obtained as a reference for comparison and verification with the actual transferred power.

[0043] S3: for each concerned unit, obtaining a load transfer matching abnormality degree of the concerned unit according to the deviation between the actual output power increase of all non-concerned units and the ideal load power, and the matching condition of the output power loss of the concerned unit; determining a key unit among all concerned units based on the load transfer matching abnormality degree.

[0044] For any concerned unit, if it fails, the lost output power will be transferred to other units, that is, if the actual load increase of a normal unit at a corresponding moment equals to the load that should be allocated, and the total load increase of all normal units equals to the total load lost by the unit, it is proved that the unit fails, otherwise, it does not fail. By monitoring the actual load power increase of each normal unit, the difference between the actual load power increase and the theoretical increase can be compared to further verify and determine the failed unit.

[0045] Therefore, by comparing the actual load increase of other normal units under the concerned unit with the theoretically calculated load increase, and the matching between the power loss of the concerned unit and the actual total received power of the normal units, the abnormality degree of the actual load transfer matching is comprehensively evaluated. Preferably, in the embodiment of the present application, the method for obtaining the load transfer matching abnormality degree comprises: Firstly, for any concerned unit, the actual increase of the output power of each non-concerned unit corresponding to the concerned unit is obtained, which reflects the real load change. In the embodiment of the present application, the actual increase can be obtained by the difference between the output power at the current moment and the output power at the non-peak period.

[0046] After calculating the power difference between the actual increase of each non-concerned unit corresponding to the concerned unit and the ideal load increase power, the sum of all power differences is taken as the normal theoretical deviation degree of the concerned unit. The normal theoretical deviation degree represents the difference between the actual load increase of each normal unit and the theoretical amount, and the smaller the value is, the smaller the difference is, and the more reasonable the allocation is.

[0047] Further, the difference between the sum of the actual increases of all non-concerned units corresponding to the concerned unit and the power loss degree of the concerned unit is taken as the allocation deviation degree of the concerned unit. The sum of the actual increases reflects the actual total load increase of all normal units, and the allocation deviation degree represents the difference between the total load loss and the total allocation. The smaller the value is, the more balanced the load loss and the allocation of the failed unit are under the allocation strategy, which reflects that the corresponding concerned unit is more likely to be the failed unit.

[0048] Therefore, the load transfer matching abnormality degree of the concerned unit is obtained by combining the normal theoretical deviation degree and the distribution deviation degree. In the embodiment of the present application, the product of the normal theoretical deviation degree and the distribution deviation degree is taken as the load transfer matching abnormality degree of the concerned unit. The smaller the load transfer matching abnormality degree is, the more reasonable the matching is, and the higher the possibility of the concerned unit being the faulty unit is.

[0049] Therefore, the key unit is marked by the load transfer matching abnormality degree. In the embodiment of the present application, the unit whose load transfer matching abnormality degree is less than a preset fault threshold value is taken as the key unit, that is, the possible faulty unit. The preset fault threshold value can be set to 0.2, and the specific value can be adjusted according to the specific implementation, which is not limited herein.

[0050] S4: If there is no key unit, the fault monitoring result is determined according to the power load transfer distribution verification of the non-concerned units corresponding to the combined concerned units.

[0051] Through the determination of the key unit, the verification of the single faulty unit in the unit cluster is completed. If there is no case satisfying the threshold condition after the verification of any key unit, it is possible that multiple units have failed. If multiple units have failed, the load distribution of different faulty units will be superimposed under the corresponding distribution strategy, and in this case, each normal unit has to bear the load distribution from all the faulty units.

[0052] Therefore, in the case where no key unit is determined in step S3, the distribution verification is performed based on the combined concerned units to determine the possibility of the existence of a fault. In the embodiment of the present application, different combination schemes of the concerned units are obtained, that is, 2 or more non-repeated concerned units are selected from all the concerned units, and each selection is taken as a combination scheme. For example, if the concerned units are A, B and C, the combination schemes include A+B, A+C, B+C and A+B+C.

[0053] When there is a combination scheme, the output power increase of all the non-concerned units under the combination scheme is consistent with the output power decrease of the concerned units under the combination scheme, and the output power increase of each non-concerned unit is consistent with the ideal load increase power of the concerned units under the combination scheme, the fault detection result is recorded as the existence of a fault, that is, the combined fault hypothesis is made by the combined distribution condition, and as an example, the expression of the verification condition under a certain combination scheme is: ; in the formula, represents the actual increase amount of the output power of the i th non-concerned unit under the combination scheme, represents the actual decrease amount of the output power of the i th concerned unit under the combination scheme, represents the ideal increase amount of the output power of the i th non-concerned unit under the combination scheme, represents the ideal decrease amount of the output power of the i th concerned unit under the combination scheme. an ideal load growth power of the non-concerned unit, for each non-concerned unit, an actual growth load thereof The sum of the loads allocated to the multiple fault units should be satisfied. an actual growth amount of all non-concerned unit output powers under the combination scheme, and a value a power loss degree of the first concerned unit under the combination scheme, a total actual load transfer amount The sum of the load loss transfer amounts of all the fault units should be satisfied.

[0054] If there is a combination satisfying the above conditions, it is indicated that the multiple concerned units under the combination are fault units, and therefore the concerned units of the combination scheme are taken as the key units. For the monitoring time point at which the key units exist, it can be recorded that there is a fault. If there is no combination satisfying the verification condition, the possible key concerned units are recalculated and re-verified for the monitoring results of other time points.

[0055] In the embodiment of the present application, if the result is that there is a fault in the monitoring of the fault units of the hydroelectric generator unit cluster, the key units are marked as fault units, and during the maintenance process, the fault units need to be quickly taken off the network while the remaining normal units continue to operate. The relevant maintenance personnel judge whether it is an electrical fault (stator / rotor problem), a mechanical fault (bearing, blade, gear), or a sensor monitoring fault to accurately locate the fault source, thereby saving maintenance costs and improving the accuracy and reliability of the hydroelectric generator unit fault diagnosis.

[0056] To sum up, the present application determines the possible concerned units by analyzing the fluctuations of the current and output power of the units at the analysis time point, and after screening the possible abnormal units, the ideal load growth power is obtained based on the operation power distribution of the concerned units to other normal units, and the key units with faults are further accurately screened by the matching degree of the load distribution transfer. After single fault abnormality analysis, the common load transfer possibility of multiple fault units is considered, the load transfer distribution of the combination concerned units is verified for the combination fault condition through the preliminary screening of the non-key units, and more accurate and reliable fault monitoring results are obtained. The present application verifies the conditions of the unit fault by analyzing the power load drop degree of the abnormal condition units and the load distribution matching degree to other units through single and combination analysis, so that the precise positioning of the fault of the multiple unit cluster is more accurate.

[0057] The present application also provides a hydroelectric generator unit cluster fault monitoring system, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of any one of the above methods when executing the computer program.

[0058] It is to be noted that the sequential order of the above-described embodiments of the present application only for the purpose of description, but not the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0059] Each of the embodiments in the specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the difference from other embodiments.

Claims

1. A fault monitoring method for a cluster of hydro-generator units, characterized in that, The method includes: Acquire the current data and output power of each unit in the hydro-generator cluster; Based on the peak fluctuations and output power deviations of each unit in the historical time series current data, select units of interest; based on the output power decline of individual units of interest and the output power distribution of non-units of interest, obtain the ideal load increase power of non-units of interest corresponding to the units of interest. For each unit of interest, the load transfer matching anomaly degree of the unit of interest is obtained based on the deviation between the actual output power growth and the ideal load power of all non-units of interest, as well as the matching situation with the output power loss of the unit of interest; and the key units are identified among all units of interest based on the load transfer matching anomaly degree. If there are no key units, the fault monitoring results are determined based on the power load transfer and allocation verification of the non-key units corresponding to the combined key units.

2. The fault monitoring method for a cluster of hydro-generator units according to claim 1, characterized in that, The method for acquiring the units of interest includes: For any given unit, determine the peak period of the current data of that unit in the historical time series; During each peak period, the difference between the maximum current data and the expected current data is used as the degree of change; the time difference between the time corresponding to the maximum current data and the initial time of the peak period is used as the time consumption; the ratio between the degree of change and the time consumption of each peak period is used as the fluctuation index of each peak period; and the average of the fluctuation indices of all peak periods is used as the current fault significance of the unit. The difference between the unit's expected power and its current output power is used as the unit's power deviation index; combined with the unit's current fault significance and power deviation index, the unit's attention level is determined. Units with a level of attention exceeding a preset attention threshold will be designated as units under attention.

3. The fault monitoring method for a cluster of hydro-generator units according to claim 1, characterized in that, The method for obtaining the ideal load increase power includes: For any unit of interest, the difference between the current output power and the rated power of the unit of interest is taken as the power loss of the unit of interest. Each non-focused unit is sequentially designated as an analysis unit. The ratio of the maximum output power of the analysis unit to the maximum power of the unit cluster is used as the power ratio coefficient of the analysis unit. The product of the current margin load of the analysis unit and the power ratio coefficient is used as the load allocation coefficient of the analysis unit. The ratio of the load allocation factor of the analyzed unit to the sum of the load allocation factors of all non-focused units is used as the load allocation weight of the analyzed unit. The product of the load allocation weight of the analyzed unit and the power loss degree is taken as the ideal load increase power of the analyzed unit corresponding to the unit of interest.

4. The fault monitoring method for a cluster of hydro-generator units according to claim 3, characterized in that, The method for obtaining the load transfer matching anomaly degree includes: For any unit of interest, obtain the actual increase in the current output power of each non-unit of interest corresponding to the unit of interest; calculate the power difference between the actual increase in the output power of each non-unit of interest corresponding to the unit of interest and the ideal load increase power, and use the sum of all power differences as the normal theoretical deviation of the unit of interest. The difference between the sum of the actual growth of all non-focused units corresponding to the focus unit and the power loss of the focus unit is taken as the allocation deviation of the focus unit. By combining the normal theoretical deviation and the distribution deviation of the unit of interest, the load transfer matching anomaly of the unit of interest is obtained.

5. The fault monitoring method for a cluster of hydro-generator units according to claim 1, characterized in that, The methods for obtaining the key generating units include: Units with load transfer matching anomalies less than a preset fault threshold are designated as key units.

6. The fault monitoring method for a cluster of hydro-turbine generator units according to claim 1, characterized in that, If there are no key generating units, the fault monitoring results are determined based on the power load transfer and allocation verification of the non-key generating units corresponding to the combined key generating units, including: Obtain different combination schemes for the units of interest; When there exists a combination scheme that satisfies the same amount of output power increase of all non-focused units under the combination scheme as the same amount of output power decrease of the focus units under the combination scheme, and satisfies the same amount of output power increase of each non-focused unit as the same amount of ideal load increase of the focus units under the combination scheme, the focus units of the combination scheme are designated as key units. When a key unit exists, the fault detection result is recorded as a fault exists.

7. The fault monitoring method for a cluster of hydro-generator units according to claim 2, characterized in that, The method for obtaining the peak time period includes: Obtain the peak point of the historical time-series current data for this unit; For any peak point, the time interval of the peak point is defined as the consecutive times with positive slopes before the peak point; and the time interval of the peak point is defined as the consecutive times with negative slopes after the peak point. The time period consisting of the time corresponding to the peak point and all other time periods is taken as the peak time period of the peak point.

8. The fault monitoring method for a cluster of hydro-generator units according to claim 3, characterized in that, The margin load is the difference between the maximum output power of the analysis unit and its current output power.

9. The fault monitoring method for a cluster of hydro-generator units according to claim 1, characterized in that, The different combinations of the units of interest include: Select two or more non-overlapping units from all units of interest, and treat each selection as a combination scheme.

10. A fault monitoring system for a cluster of hydro-turbine generator units, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the fault monitoring method for a hydro-generator cluster as described in any one of claims 1 to 9.

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