CN117175567A - Method and system for abnormal positioning and reliability evaluation of energy storage power station equipment - Google Patents
Method and system for abnormal positioning and reliability evaluation of energy storage power station equipment Download PDFInfo
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Abstract
The application relates to an energy storage power station equipment abnormality positioning and reliability evaluating method and system, and relates to the technical field of data processing, wherein the method comprises the following steps: acquiring a topological structure of an energy storage converter of an energy storage group and a topological structure of a battery room of the energy storage group, determining at least one first monitoring point, and setting first abnormality monitoring equipment, wherein the first abnormality monitoring equipment is used for acquiring performance parameters and working state data of equipment of the energy storage converter; determining at least one second monitoring point, and setting second abnormality monitoring equipment, wherein the second abnormality monitoring equipment is used for acquiring performance parameters and working state data of equipment of the battery chamber; positioning abnormal equipment; the reliability of the energy storage power station is determined through the reliability evaluation model, and the method has the advantages of timely finding equipment faults and improving the reliability and the operation efficiency of the energy storage power station.
Description
Technical Field
The application relates to the technical field of data processing, in particular to an energy storage power station equipment abnormality positioning and reliability evaluation method and system.
Background
In recent years, electrochemical energy storage technology has been widely used in various fields of power generation, auxiliary services, power transmission and distribution, renewable energy access, distributed energy storage, end users, and the like in an electric power system. As a main means for realizing large capacity of the energy storage device, large-scale integration of the energy storage system is a necessary condition for realizing a large-scale energy storage power station, and safe and reliable operation of the energy storage system is an important guarantee for realizing benign development of energy storage, which is a prerequisite for realizing large-scale popularization and application of the energy storage battery. In the existing energy storage power station management, abnormal equipment positioning and reliability evaluation mainly depend on manual statistics of various calculation parameters, manual calculation is carried out according to a calculation formula of each index, the statistics and calculation processes are very complicated, the finding hysteresis condition of abnormal conditions is serious, the energy storage station needs to calculate evaluation indexes once at intervals, a lot of workload is increased, the possibility of errors is high due to manual operation, and the positioning and reliability accuracy of the abnormal equipment is poor.
Therefore, it is necessary to provide an abnormality positioning and reliability evaluating method and system for an energy storage power station device, which are used for timely discovering equipment faults, reducing downtime, and improving the reliability and operation efficiency of the energy storage power station.
Disclosure of Invention
The application provides an energy storage power station equipment abnormality positioning and reliability evaluating method, wherein the energy storage power station comprises at least one energy storage group, and the method comprises the following steps: for each energy storage group, acquiring a topological structure of an energy storage converter of the energy storage group and a topological structure of a battery room of the energy storage group; determining at least one first monitoring point in the energy storage converter based on the topology structure of the energy storage converters of the energy storage group; setting first abnormality monitoring equipment at each first monitoring point, wherein the first abnormality monitoring equipment is used for acquiring performance parameters and working state data of equipment of the energy storage converter; determining at least one second monitoring point of a battery compartment of the energy storage group based on a topology of the battery compartment; setting a second abnormality monitoring device at each second monitoring point, wherein the second abnormality monitoring device is used for acquiring performance parameters and working state data of the battery chamber device; based on the performance parameters and the working state data of the equipment of the energy storage converter and the performance parameters and the working state data of the equipment of the battery chamber, positioning abnormal equipment; establishing a reliability evaluation model; and determining the reliability of the energy storage power station at least based on the equipment performance parameters and the working state data of the energy storage converters corresponding to each energy storage group and the performance parameters and the working state data of the equipment of the battery chamber through the reliability evaluation model.
Still further, the determining at least one first monitoring point in the energy storage converter based on the topology of the energy storage converters of the energy storage group includes: acquiring related information of each device of the energy storage converter, and determining the fault rate of each device of the energy storage converter; generating a plurality of candidate monitoring schemes based on a first constraint condition set through a Monte Carlo model, wherein the candidate monitoring schemes comprise a plurality of candidate monitoring points; for each candidate monitoring scheme, determining fault positioning accuracy of the candidate monitoring scheme under various virtual abnormal scenes; for each candidate monitoring scheme, determining a scheme matching value of the candidate monitoring scheme based on fault positioning accuracy corresponding to the candidate monitoring scheme and fault rate of each equipment of the energy storage converter; and determining a target monitoring scheme from the plurality of candidate monitoring schemes based on scheme matching values corresponding to each of the candidate monitoring schemes, and determining at least one first monitoring point in the energy storage converter based on the target monitoring scheme.
Still further, the determining a solution matching value of the candidate monitoring solution based on the fault location accuracy corresponding to the candidate monitoring solution and the fault rate of each device of the energy storage converter includes: for each virtual abnormal scene, calculating fault positioning accuracy of the candidate monitoring scheme under the virtual abnormal scene based on preset fault equipment corresponding to the virtual abnormal scene and abnormal equipment positioned based on the candidate monitoring scheme; determining weights corresponding to fault positioning accuracy under each virtual abnormal scene based on the fault rate of each device of the energy storage converter; and determining a scheme matching value of the candidate monitoring scheme based on the fault positioning accuracy of the candidate monitoring scheme under each virtual abnormal scene and the weight corresponding to the fault positioning accuracy under each virtual abnormal scene.
Further, the first abnormality monitoring device includes a first performance parameter monitoring component and a first operating condition monitoring component; the first performance parameter monitoring component at least comprises a first voltage monitor and a first current monitor; the first working state monitoring assembly at least comprises a first temperature monitor, a first humidity monitor, a first vibration monitor, a first sound monitor and a first gas monitor.
Still further, the determining at least one second monitoring point of the battery compartment based on a topology of the battery compartment of the energy storage group includes: determining the number and the positions of battery packs based on the topological structure of battery chambers of the energy storage group; at least one second monitoring point of the battery compartment is determined based on the number and location of the battery packs.
Further, the second abnormality monitoring device includes a second performance parameter monitoring component and a second operating condition monitoring component; the second performance parameter monitoring component comprises a second voltage monitor and a second current monitor; the second working state monitoring component comprises a second temperature monitor, a second humidity monitor, a second vibration monitor, a second sound monitor, a second gas monitor and a point cloud collector.
Furthermore, the abnormal device positioning based on the performance parameter and the working state data of the device of the energy storage converter and the performance parameter and the working state data of the device of the battery chamber comprises: determining candidate abnormal equipment in the energy storage converter based on performance parameters and working state data of the equipment of the energy storage converter; determining associated equipment of the candidate abnormal equipment based on the topological structure of the energy storage converter of the energy storage group; and determining abnormal equipment in the energy storage converter based on the performance parameters and the working state data of the associated equipment.
Furthermore, the abnormal device positioning based on the performance parameter and the working state data of the device of the energy storage converter and the performance parameter and the working state data of the device of the battery chamber comprises: and determining an abnormal battery pack based on the performance parameters and the working state data of the equipment of the battery chamber.
Further, the reliability evaluation model comprises a plurality of evaluation indexes and weights corresponding to each evaluation index, wherein the weights corresponding to each evaluation index are determined based on a principal component analysis method and a weight determination method considering deviation coefficients, and the plurality of evaluation indexes at least comprise an energy storage converter performance index, an energy storage room performance index, an energy storage converter annual average fault index, an energy storage room annual average fault index, an abnormal equipment positioning reliability index and an energy storage unit charging and discharging energy attenuation rate; the determining, by the reliability evaluation model, the reliability of the energy storage power station based on at least the performance parameter and the working state data of the equipment of the energy storage converter corresponding to each energy storage group and the performance parameter and the working state data of the equipment of the battery chamber, includes: calculating the scores of the energy storage power stations on the multiple evaluation indexes based on the performance parameters and the working state data of the equipment of the energy storage converter and the performance parameters and the working state data of the equipment of the battery chamber corresponding to each energy storage group; and determining the reliability of the energy storage power station based on the scores of the energy storage power station on the plurality of evaluation indexes and the weight corresponding to each evaluation index.
The application also provides an energy storage power station equipment abnormality positioning and reliability evaluating system, wherein the energy storage power station comprises at least one energy storage group, and the system comprises: the abnormality monitoring module is used for acquiring the topological structure of the energy storage converter of the energy storage group and the topological structure of the battery room of the energy storage group for each energy storage group; determining at least one first monitoring point in the energy storage converter based on the topology structure of the energy storage converters of the energy storage group; setting first abnormality monitoring equipment at each first monitoring point, wherein the first abnormality monitoring equipment is used for acquiring performance parameters and working state data of equipment of the energy storage converter; determining at least one second monitoring point of a battery compartment of the energy storage group based on a topology of the battery compartment; setting a second abnormality monitoring device at each second monitoring point, wherein the second abnormality monitoring device is used for acquiring performance parameters and working state data of the battery chamber device; based on the performance parameters and the working state data of the equipment of the energy storage converter and the performance parameters and the working state data of the equipment of the battery chamber, positioning abnormal equipment; the reliability analysis module is used for establishing a reliability evaluation model; and determining the reliability of the energy storage power station at least based on the performance parameters and the working state data of the equipment of the energy storage converter corresponding to each energy storage group and the performance parameters and the working state data of the equipment of the battery chamber through the reliability evaluation model.
Compared with the prior art, the energy storage power station equipment abnormality positioning and reliability evaluating method and system provided by the specification have the following beneficial effects:
1. the method comprises the steps of determining at least one first monitoring point in an energy storage converter, setting first abnormal monitoring equipment at each first monitoring point to monitor the states of all equipment in the energy storage converter, further determining at least one second monitoring point of a battery chamber, setting second abnormal monitoring equipment at each second monitoring point to monitor the states of the battery chamber, providing data support for positioning the abnormal equipment, and combining actual and theoretical indexes by a reliability evaluation model based on at least the performance parameters and working state data of the equipment of the energy storage converter corresponding to each energy storage group and the performance parameters and working state data of the equipment of the battery chamber, so that the reliability of an energy storage power station can be accurately determined, equipment faults can be found timely, downtime can be reduced, and the reliability and the operating efficiency of the energy storage power station can be improved;
2. based on fault positioning accuracy corresponding to the candidate monitoring scheme and fault rate of each equipment of the energy storage converter, the scheme matching value of the candidate monitoring scheme is determined, flexible adjustment of the monitoring scheme can be realized, different monitoring schemes can be adopted for data acquisition for different energy storage power stations, invalid data acquisition is reduced, and the efficiency of abnormal equipment positioning and the accuracy of reliability analysis of the energy storage power stations are improved;
3. based on the topological structure of the energy storage converter of the energy storage group, the associated equipment of the candidate abnormal equipment is determined, and based on the performance parameters and the working state data of the associated equipment, the abnormal equipment in the energy storage converter is determined, so that the tracing to the source of the abnormality is realized, the normal equipment influenced by the abnormal equipment is prevented from being judged to be the abnormal equipment, and more accurate data support is provided for the maintenance and detection of the follow-up abnormal equipment.
Drawings
The present specification will be further elucidated by way of example embodiments, which will be described in detail by means of the accompanying drawings. The embodiments are not limiting, in which like numerals represent like structures, wherein:
FIG. 1 is a block diagram of an energy storage power station equipment anomaly location and reliability assessment system shown in an embodiment of the present application;
FIG. 2 is a flow chart of a method for anomaly location and reliability assessment of energy storage power station equipment shown in an embodiment of the present application;
FIG. 3 is a flow chart illustrating a method of determining at least one first monitoring point within an energy storage converter in accordance with an embodiment of the present application;
fig. 4 is a flow chart illustrating the determination of scheme matching values for candidate monitoring schemes in an embodiment of the application.
Detailed Description
In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the drawings that are required to be used in the description of the embodiments will be briefly described below.
Fig. 1 is a block diagram of an energy storage power station device abnormality positioning and reliability evaluating system according to an embodiment of the present application, where an energy storage power station includes at least one energy storage group, and the energy storage group may include an energy storage converter and at least one battery compartment, where the energy storage converter may control a charging and discharging process of a storage battery to perform ac-dc conversion, and may directly supply power to an ac load in a case where there is no power grid. The PCS is composed of a DC/AC bidirectional converter, a control unit and the like. The PCS controller receives a background control instruction through communication, and controls the converter to charge or discharge the battery according to the sign and the size of the power instruction, so that the active power and the reactive power of the power grid are regulated. The PCS controller is communicated with the BMS through the CAN interface to acquire battery pack state information, so that the battery CAN be charged and discharged in a protective way, the battery operation safety is ensured, the battery chamber CAN be formed by combining a plurality of battery cells in series and parallel, the battery chamber CAN also comprise a plurality of series modules and Battery Protection Units (BPU), the Battery Protection Units (BPU) are also called as battery cluster controllers, namely, the battery protection units comprise a battery cluster Battery Management System (BMS), and the battery pack controller CAN be used for monitoring the voltage, the temperature and the charging state of the battery and CAN also be used for regulating the charging and discharging period of the battery.
As shown in fig. 1, the energy storage power station equipment abnormality positioning and reliability evaluation system may include an abnormality monitoring module and a reliability analysis module.
The abnormality monitoring module can be used for acquiring the topological structure of the energy storage converter of the energy storage group and the topological structure of the battery chamber of the energy storage group for each energy storage group; determining at least one first monitoring point in the energy storage converter based on the topological structure of the energy storage converter of the energy storage group; setting first abnormality monitoring equipment at each first monitoring point, wherein the first abnormality monitoring equipment is used for acquiring performance parameters and working state data of equipment of the energy storage converter; determining at least one second monitoring point of the battery compartment based on a topology of the battery compartment of the energy storage group; setting a second abnormality monitoring device at each second monitoring point, wherein the second abnormality monitoring device is used for acquiring performance parameters and working state data of the battery chamber device; and positioning abnormal equipment based on the performance parameters and the working state data of the equipment of the energy storage converter and the performance parameters and the working state data of the equipment of the battery chamber.
The reliability analysis module can be used for establishing a reliability evaluation model; and determining the reliability of the energy storage power station at least based on the performance parameters and the working state data of the equipment of the energy storage converter corresponding to each energy storage group and the performance parameters and the working state data of the equipment of the battery chamber through a reliability evaluation model.
For further description of the anomaly monitoring module and the reliability analysis module, reference may be made to further description of the method for anomaly localization and reliability evaluation of the energy storage power station device, which is not repeated here.
FIG. 2 is a flow chart of an energy storage power plant equipment anomaly location and reliability assessment method, which may be performed by an energy storage power plant equipment anomaly location and reliability assessment system in some embodiments, in accordance with an embodiment of the present application. As shown in fig. 2, the method for locating anomalies and evaluating reliability of energy storage power station equipment may include the following procedures.
Step 210, for each energy storage group, obtaining a topology structure of an energy storage converter of the energy storage group and a topology structure of a battery room of the energy storage group. In some embodiments, step 210 is performed by an anomaly monitoring module.
The topology of the energy storage converters of the energy storage group is used to characterize the electrical connection between a plurality of devices (e.g., DC/AC bi-directional converters, control units, etc.) of the energy storage converters of the energy storage group.
The topology of the battery cells of the energy storage pack is used to characterize the electrical connection between the plurality of devices (e.g., the plurality of cells, the battery protection unit, etc.) of the energy storage converter of the energy storage pack.
In some embodiments, the anomaly monitoring module may obtain the topology of the energy storage converters of the energy storage bank and the topology of the battery cells of the energy storage bank from an external data source.
Step 220, for each energy storage group, determining at least one first monitoring point within the energy storage converter based on the topology of the energy storage converter of the energy storage group. In some embodiments, step 220 is performed by an anomaly monitoring module.
The first monitoring point may be a location or device in the energy storage converter where anomaly monitoring is required.
In some embodiments, the at least one first monitoring point within the energy storage converter may be determined manually based on experience.
Fig. 3 is a flowchart illustrating determining at least one first monitoring point in an energy storage converter according to an embodiment of the present application, and as shown in fig. 3, in order to improve efficiency, real-time performance and accuracy of discovering abnormal devices, in some embodiments, determining at least one first monitoring point in an energy storage converter based on a topology of an energy storage group of energy storage converters includes:
acquiring relevant information of each device of the energy storage converter, and determining fault rate of each device of the energy storage converter, wherein the relevant information of the devices can comprise information such as names, models, historical fault information of the devices, elements included in the devices and the like;
generating a plurality of candidate monitoring schemes based on a first constraint condition set through a Monte Carlo model, wherein the candidate monitoring schemes comprise a plurality of candidate monitoring points, and the first constraint condition set can at least comprise the minimum number constraint of the monitoring points, the maximum number constraint of the monitoring points corresponding to the same equipment and the like;
for each candidate monitoring scheme, determining fault positioning accuracy of the candidate monitoring scheme under various virtual abnormal scenes;
for each candidate monitoring scheme, determining a scheme matching value of the candidate monitoring scheme based on fault positioning accuracy corresponding to the candidate monitoring scheme and fault rate of each equipment of the energy storage converter;
and determining a target monitoring scheme from the plurality of candidate monitoring schemes based on the scheme matching value corresponding to each candidate monitoring scheme, and determining at least one first monitoring point in the energy storage converter based on the target monitoring scheme.
Specifically, the abnormality monitoring module may determine the failure rate of each device of the energy storage converter based on the relevant information of each device of the energy storage converter in any manner. For example, failure rates of respective devices of the energy storage converter are determined based on information related to the respective devices of the energy storage converter by a machine learning model (e.g., an artificial neural network (Artificial Neural Network, ANN) model, a recurrent neural network (Recurrent Neural Networks, RNN) model, a Long Short-Term Memory (LSTM) model, a bi-directional recurrent neural network (BRNN) model, etc.).
Fig. 4 is a flowchart illustrating a method for determining a solution matching value of a candidate monitoring solution according to an embodiment of the present application, and as shown in fig. 4, in some embodiments, determining a solution matching value of a candidate monitoring solution based on fault location accuracy corresponding to the candidate monitoring solution and a fault rate of each device of an energy storage converter includes:
for each virtual abnormal scene, calculating fault positioning accuracy of the candidate monitoring scheme under the virtual abnormal scene based on preset fault equipment corresponding to the virtual abnormal scene and abnormal equipment positioned based on the candidate monitoring scheme, wherein the preset fault equipment corresponding to the virtual abnormal scene refers to equipment with faults under the virtual abnormal scene, and the abnormal equipment positioned based on the candidate monitoring scheme refers to equipment with faults determined based on the candidate monitoring scheme;
determining a weight corresponding to fault positioning accuracy in each virtual abnormal scene based on the fault rate of each device of the energy storage converter;
and determining a scheme matching value of the candidate monitoring scheme based on the fault positioning accuracy of the candidate monitoring scheme under each virtual abnormal scene and the weight corresponding to the fault positioning accuracy under each virtual abnormal scene.
Specifically, when the abnormal device located by the candidate monitoring scheme is consistent with the preset fault device corresponding to the virtual abnormal scene, the preset fault device may be marked as a located preset fault device, and the fault location accuracy of the candidate monitoring scheme under the virtual abnormal scene may be calculated based on the number of located preset fault devices.
For example, fault location accuracy of a candidate monitoring scheme in a virtual anomaly scenario may be calculated based on the following formula:
wherein A is (i,n) For the fault positioning accuracy of the ith candidate monitoring scheme in the nth virtual abnormal scene, N (accuracy,i,n) For the total number of the located preset fault devices, N (all,i,n) And the total number of the preset fault devices corresponding to the nth virtual abnormal scene.
In some embodiments, for each virtual anomaly scenario, the weight corresponding to the virtual anomaly scenario may be determined based on the failure rate corresponding to each preset failure device under the virtual anomaly scenario.
For example, the weight corresponding to fault location accuracy in a virtual anomaly scenario may be calculated based on the following formula:
wherein a is n R is the weight corresponding to the fault location accuracy in the nth virtual abnormal scene (failure,j) And for the corresponding fault rate of the J preset fault devices in the n virtual abnormal scene after normalization, wherein J is the total number of the preset fault devices in the n virtual abnormal scene.
For example only, the solution match value for the candidate monitoring solution may be calculated based on the following formula:
wherein M is i For V (data,i) A scheme matching value for the i-th candidate monitoring scheme,n is the total number of virtual abnormal scenes, V (data,i) The size of the data volume required to be acquired for the normalized i-th candidate monitoring scheme.
In some embodiments, the anomaly monitoring module may use a candidate monitoring scheme with a maximum scheme matching value as a target monitoring scheme, and determine all first monitoring points in the energy storage converter according to the target monitoring scheme.
At step 230, for each energy storage group, a first anomaly monitoring device is set at each first monitoring point. In some embodiments, step 230 is performed by an anomaly monitoring module.
The first anomaly monitoring device is configured to obtain performance parameters (e.g., current, voltage, power, etc.) and operational status data (e.g., temperature, vibration, sound, fire conditions, etc.) of the devices of the energy storage converter.
In some embodiments, the first anomaly monitoring device includes a first performance parameter monitoring component and a first operating condition monitoring component.
The first performance parameter monitoring component at least comprises a first voltage monitor and a first current monitor.
The first working state monitoring assembly at least comprises a first temperature monitor, a first humidity monitor, a first vibration monitor, a first sound monitor and a first gas monitor.
Step 240, for each energy storage group, determining at least one second monitoring point of the battery compartment based on the topology of the battery compartment of the energy storage group. In some embodiments, step 240 is performed by an anomaly monitoring module.
The second monitoring point may be a location or device in the battery compartment where anomaly monitoring is desired.
In some embodiments, the at least one second monitoring point within the battery compartment may be determined manually based on experience.
In some embodiments, determining at least one second monitoring point of the battery compartment based on a topology of the battery compartment of the energy storage group includes:
determining the number and the positions of battery packs based on the topological structure of battery chambers of the energy storage group;
at least one second monitoring point of the battery compartment is determined based on the number and location of the battery packs.
Specifically, each battery pack may correspond to at least one second monitoring point.
Step 250, for each energy storage group, setting a second anomaly monitoring device at each second monitoring point. In some embodiments, step 250 is performed by an anomaly monitoring module.
Wherein the second abnormality monitoring device is used for acquiring performance parameters (such as current, voltage, power and the like) and working state data (such as temperature, vibration, sound, swelling condition, fire condition and the like) of the device of the battery chamber
In some embodiments, the second anomaly monitoring device includes a second performance parameter monitoring component and a second operating condition monitoring component;
the second performance parameter monitoring component comprises a second voltage monitor and a second current monitor;
the second working state monitoring component comprises a second temperature monitor, a second humidity monitor, a second vibration monitor, a second sound monitor, a second gas monitor and a point cloud collector.
Step 260, for each energy storage group, performing abnormal equipment positioning based on the performance parameters and the working state data of the equipment of the energy storage converter and the performance parameters and the working state data of the equipment of the battery chamber. In some embodiments, step 260 is performed by an anomaly monitoring module.
In some embodiments, performing abnormal device localization based on performance parameters and operating state data of a device of the energy storage converter and performance parameters and operating state data of a device of the battery compartment includes:
determining candidate abnormal equipment in the energy storage converter based on performance parameters and working state data of equipment of the energy storage converter, wherein when the temperature, vibration, sound and target gas concentration of a certain first monitoring point are abnormal, the equipment where the first monitoring point is located is the candidate abnormal equipment;
determining associated equipment of the candidate abnormal equipment based on the topological structure of the energy storage converter of the energy storage group, wherein the associated equipment can be upstream equipment of the candidate abnormal equipment, namely an output signal of the associated equipment is input of the candidate abnormal equipment;
and determining abnormal equipment in the energy storage converter based on the performance parameters and the working state data of the related equipment.
Specifically, when none of the associated devices of the candidate abnormal devices is abnormal, the candidate abnormal device is the abnormal device in the energy storage converter. When at least one associated device is also abnormal, the associated device is also used as a candidate abnormal device, the associated device of the newly added candidate abnormal device is determined, the state of the newly added associated device is determined, and the steps are repeated until the abnormal device is found.
In some embodiments, an abnormal battery pack is determined based on performance parameters and operating state data of the device of the battery compartment.
Specifically, the point cloud collector may be configured to collect and process point cloud information of a battery pack, generate actual point cloud information of the battery pack, and determine a battery pack bulge based on similarity between the actual point cloud information and pre-stored standard point cloud information corresponding to the battery pack.
For example, the battery pack bulge degree may be calculated based on the following formula:
wherein D is bulge Is the battery bulge degree, P (l,real) For the coordinates of the first point in the actual point cloud information, P (l,standard) And L is the total number of points corresponding to the battery pack, and is the coordinates of the first point in the standard point cloud information.
And step 270, establishing a reliability evaluation model. In some embodiments, step 270 is performed by a reliability analysis module.
In some embodiments, the reliability evaluation model includes a plurality of evaluation indexes and weights corresponding to each evaluation index, where the weights corresponding to each evaluation index are determined based on a principal component analysis method and a weighting method considering a deviation coefficient, and the plurality of evaluation indexes at least include an energy storage converter performance index, an energy storage chamber performance index, an energy storage converter annual average fault index, an energy storage chamber annual average fault index, an abnormal equipment positioning reliability index, and an energy storage unit charging/discharging energy attenuation rate.
Step 280, determining the reliability of the energy storage power station through a reliability evaluation model at least based on the performance parameters and the working state data of the equipment of the energy storage converter corresponding to each energy storage group and the performance parameters and the working state data of the equipment of the battery chamber. In some embodiments, step 280 is performed by a reliability analysis module.
In some embodiments, determining the reliability of the energy storage power station comprises:
calculating scores of the energy storage power station in a plurality of evaluation indexes based on the performance parameters and the working state data of the equipment of the energy storage converter corresponding to each energy storage group and the performance parameters and the working state data of the equipment of the battery chamber;
and determining the reliability of the energy storage power station based on the scores of the energy storage power station on the multiple evaluation indexes and the weight corresponding to each evaluation index.
For example, the reliability of the energy storage power station may be determined based on the following formula:
wherein S is reliability F is the total number of evaluation indexes, a, for the reliability of the energy storage power station f Is the weight corresponding to the f-th evaluation index, S f And (5) scoring the energy storage power station at the f-th evaluation index.
Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments of this specification. Other variations are possible within the scope of this description. Thus, by way of example, and not limitation, alternative configurations of embodiments of the present specification may be considered as consistent with the teachings of the present specification. Accordingly, the embodiments of the present specification are not limited to only the embodiments explicitly described and depicted in the present specification.
Claims (10)
1. The method for evaluating the abnormal positioning and reliability of the energy storage power station equipment is characterized by comprising the following steps of:
for each of the energy storage groups,
acquiring a topological structure of an energy storage converter of the energy storage group and a topological structure of a battery room of the energy storage group;
determining at least one first monitoring point in the energy storage converter based on the topology structure of the energy storage converters of the energy storage group;
setting first abnormality monitoring equipment at each first monitoring point, wherein the first abnormality monitoring equipment is used for acquiring performance parameters and working state data of equipment of the energy storage converter;
determining at least one second monitoring point of a battery compartment of the energy storage group based on a topology of the battery compartment;
setting a second abnormality monitoring device at each second monitoring point, wherein the second abnormality monitoring device is used for acquiring performance parameters and working state data of the battery chamber device;
based on the performance parameters and the working state data of the equipment of the energy storage converter and the performance parameters and the working state data of the equipment of the battery chamber, positioning abnormal equipment;
establishing a reliability evaluation model;
and determining the reliability of the energy storage power station at least based on the equipment performance parameters and the working state data of the energy storage current transformer corresponding to each energy storage group and the performance parameters and the working state data of the equipment of the battery chamber through the reliability evaluation model.
2. The method of claim 1, wherein determining at least one first monitoring point in the energy storage converter based on a topology of the energy storage converters of the energy storage group comprises:
acquiring related information of each device of the energy storage converter, and determining the fault rate of each device of the energy storage converter;
generating a plurality of candidate monitoring schemes based on a first constraint condition set through a Monte Carlo model, wherein the candidate monitoring schemes comprise a plurality of candidate monitoring points;
for each candidate monitoring scheme, determining fault positioning accuracy of the candidate monitoring scheme under various virtual abnormal scenes;
for each candidate monitoring scheme, determining a scheme matching value of the candidate monitoring scheme based on fault positioning accuracy corresponding to the candidate monitoring scheme and fault rate of each equipment of the energy storage converter;
and determining a target monitoring scheme from the plurality of candidate monitoring schemes based on scheme matching values corresponding to each of the candidate monitoring schemes, and determining at least one first monitoring point in the energy storage converter based on the target monitoring scheme.
3. The method for abnormal positioning and reliability evaluation of energy storage power station equipment according to claim 2, wherein determining the scheme matching value of the candidate monitoring scheme based on the fault positioning accuracy corresponding to the candidate monitoring scheme and the fault rate of each equipment of the energy storage converter comprises:
for each virtual abnormal scene, calculating fault positioning accuracy of the candidate monitoring scheme under the virtual abnormal scene based on preset fault equipment corresponding to the virtual abnormal scene and abnormal equipment positioned based on the candidate monitoring scheme;
determining weights corresponding to fault positioning accuracy under each virtual abnormal scene based on the fault rate of each device of the energy storage converter;
and determining a scheme matching value of the candidate monitoring scheme based on the fault positioning accuracy of the candidate monitoring scheme under each virtual abnormal scene and the weight corresponding to the fault positioning accuracy under each virtual abnormal scene.
4. The energy storage power station equipment anomaly location and reliability evaluation method of claim 1, wherein the first anomaly monitoring equipment comprises a first performance parameter monitoring component and a first working state monitoring component;
the first performance parameter monitoring component at least comprises a first voltage monitor and a first current monitor;
the first working state monitoring assembly at least comprises a first temperature monitor, a first humidity monitor, a first vibration monitor, a first sound monitor and a first gas monitor.
5. The method of any one of claims 1-4, wherein determining at least one second monitoring point of the battery compartment based on a topology of the battery compartment of the energy storage group comprises:
determining the number and the positions of battery packs based on the topological structure of battery chambers of the energy storage group;
at least one second monitoring point of the battery compartment is determined based on the number and location of the battery packs.
6. The method for locating anomalies and evaluating the reliability of energy storage power station equipment according to claim 5, wherein the second anomaly monitoring device comprises a second performance parameter monitoring component and a second operating state monitoring component;
the second performance parameter monitoring component comprises a second voltage monitor and a second current monitor;
the second working state monitoring component comprises a second temperature monitor, a second humidity monitor, a second vibration monitor, a second sound monitor, a second gas monitor and a point cloud collector.
7. The method for locating and evaluating the reliability of an energy storage power station device according to claim 6, wherein the locating the abnormal device based on the performance parameter and the working state data of the energy storage converter device and the performance parameter and the working state data of the battery chamber device comprises:
determining candidate abnormal equipment in the energy storage converter based on performance parameters and working state data of the equipment of the energy storage converter;
determining associated equipment of the candidate abnormal equipment based on the topological structure of the energy storage converter of the energy storage group;
and determining abnormal equipment in the energy storage converter based on the performance parameters and the working state data of the associated equipment.
8. The method for locating and evaluating the reliability of an energy storage power station device according to any one of claims 1 to 4, wherein the locating of the abnormal device based on the performance parameter and the operation state data of the device of the energy storage converter and the performance parameter and the operation state data of the device of the battery compartment comprises:
and determining an abnormal battery pack based on the performance parameters and the working state data of the equipment of the battery chamber.
9. The method for positioning abnormality and evaluating reliability of energy storage power station equipment according to any one of claims 1 to 4, wherein the reliability evaluation model comprises a plurality of evaluation indexes and weights corresponding to each evaluation index, wherein the weights corresponding to each evaluation index are determined based on a principal component analysis method and a weight determination method considering a deviation coefficient, and the plurality of evaluation indexes at least comprise an energy storage converter performance index, an energy storage chamber performance index, an energy storage converter annual average fault index, an energy storage chamber annual average fault index, an abnormal equipment positioning reliability index and an energy storage unit charging/discharging energy attenuation rate;
the determining, by the reliability evaluation model, the reliability of the energy storage power station based on at least the performance parameter and the working state data of the equipment of the energy storage converter corresponding to each energy storage group and the performance parameter and the working state data of the equipment of the battery chamber, includes:
calculating the scores of the energy storage power stations on the multiple evaluation indexes based on the performance parameters and the working state data of the equipment of the energy storage converter and the performance parameters and the working state data of the equipment of the battery chamber corresponding to each energy storage group;
and determining the reliability of the energy storage power station based on the scores of the energy storage power station on the plurality of evaluation indexes and the weight corresponding to each evaluation index.
10. The evaluation system of an energy storage power station equipment anomaly localization and reliability evaluation method according to any one of claims 1-9, wherein the energy storage power station comprises at least one energy storage group, comprising:
the abnormality monitoring module is used for acquiring the topological structure of the energy storage converter of the energy storage group and the topological structure of the battery room of the energy storage group for each energy storage group; determining at least one first monitoring point in the energy storage converter based on the topology structure of the energy storage converters of the energy storage group; setting first abnormality monitoring equipment at each first monitoring point, wherein the first abnormality monitoring equipment is used for acquiring performance parameters and working state data of equipment of the energy storage converter; determining at least one second monitoring point of a battery compartment of the energy storage group based on a topology of the battery compartment; setting a second abnormality monitoring device at each second monitoring point, wherein the second abnormality monitoring device is used for acquiring performance parameters and working state data of the battery chamber device; based on the performance parameters and the working state data of the equipment of the energy storage converter and the performance parameters and the working state data of the equipment of the battery chamber, positioning abnormal equipment;
the reliability analysis module is used for establishing a reliability evaluation model; and determining the reliability of the energy storage power station at least based on the performance parameters and the working state data of the equipment of the energy storage converter corresponding to each energy storage group and the performance parameters and the working state data of the equipment of the battery chamber through the reliability evaluation model.
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