Electrochemical energy storage power station fault scenario reconstruction method

Abstract

This patent relates to a method for reconstructing fault scenarios in an electrochemical energy storage power station. The method includes the following steps: connecting the control center platform of the electrochemical energy storage power station, fault simulation control software, and a hardware-in-the-loop (HIL) model; constructing an "electric-thermal" fault database for the electrochemical energy storage power station; preprocessing the data; establishing the database; reconstructing fault scenarios in the electrochemical energy storage power station; constructing a mapping matrix between the operating environment and interface response to determine interface excitation and operating status; collecting different types of signals; after the single fault scenario test program is completed, the signal excitation and acquisition module collects and analyzes the operating information of the energy storage power station and the operating test signals of each subsystem again; performing image and numerical analysis on the signal fluctuation impact caused by the fault signal and the fault clearing status, and completing the system integration test. This testing method will effectively improve the fault detection efficiency and operation and maintenance reliability of electrochemical energy storage power stations, and reduce operation and maintenance costs.

Description

Technical Field

[0001] This patent relates to the field of new energy technology, specifically to a method for reconstructing fault scenarios in an electrochemical energy storage power station. Technical Background

[0002] Currently, electrochemical energy storage power stations are often assembled in the form of battery containers. During the system assembly process, at different time points, the transient fault early warning equipment and control system of the battery containers integrated into the electrochemical energy storage power station need to be manually debugged multiple times. Manual debugging is difficult to construct fault simulation scenarios and is limited by detection technology, which can easily lead to incomplete fault testing and debugging of electrochemical energy storage power stations, long testing time, potential safety issues in the operation of electrochemical energy storage power stations, and increased commissioning costs. In addition, current machine debugging fault database coding has large differences, there is no clear standard for fault test selection, and the fault operation scenarios are limited. Summary of the Invention

[0003] This invention proposes a method for reconstructing fault scenarios in electrochemical energy storage power stations, the specific technical solution of which is as follows:

[0004] A method for reconstructing fault scenarios in an electrochemical energy storage power station includes the following steps:

[0005] Step 1: Connect the electrochemical energy storage power station control center platform, fault simulation control software, and hardware-in-the-loop simulation model;

[0006] The control center platform includes: an energy storage container energy management system, a power conversion system, an Ethernet communication interface, a signal converter, and an operation information acquisition device.

[0007] The fault simulation control software includes: a signal graphics card control program, a fault database, an "electric-thermal" fault data acquisition module, an information summarization and classification module, an information sending and receiving device, and a UI operation interface.

[0008] The main body of the semi-physical simulation model is an electrochemical energy storage power station semi-physical model built on the DSATools simulation platform. It is used to send operational fault information or receive test control commands. It also includes: a fault location system, an electrical parameter sampling system, and a thermal data sampling system.

[0009] Step 2: Construct an "electric-thermal" fault database for electrochemical energy storage power stations, and collect "electric-thermal" fault information of energy storage power stations through manual operation and maintenance experience and relay protection equipment;

[0010] Step 3: Preprocess the collected data. Different types of signal data are processed according to custom encoding format, tag code category, signal meaning represented by each data bit, and fault location information. The fault information is decomposed in a multi-dimensional manner to determine whether there is abnormal gas emission, changes in the sensing of sound, smoke, and temperature sensors, and changes in the three-level electrochemical parameters of "battery cluster-battery compartment-power station". A translation optimization algorithm with online learning capability is used to label and encode parameters such as fault location, fault device, fault impact, and fault parameters and load them into the database.

[0011] Step 4: Classify and describe faults, store typical fault information including the operating scenarios and fault locations of energy storage power stations, and classify the fault hazard levels in the database into 1 to 10 levels based on the degree of fault impact using the analytic hierarchy process (AHP) and fuzzy logic. The fault database is then established. This creates a database containing various faults of energy storage power stations and their corresponding descriptions and definitions. The database includes a battery cluster fault database, a battery compartment fault database, and an energy storage power station bus fault database. Each part of the database includes data management, data retrieval, and data storage functions.

[0012] Step 5: Divide the elements of the electrochemical energy storage power station operation scenario reconstruction into two parts: environmental factors and test factors, and set the scenario reconstruction parameters and constraints accordingly.

[0013] Step 6: Reconstructing fault scenarios for electrochemical energy storage power stations; using a fitness evaluation function to reflect the degree of difference from other fault scenarios in the same fault set, and constructing the corresponding fault scenario set Ω, as follows:

[0014] Construct a fault scenario s, which includes n independently operating device entities o1, o2, ... o n Furthermore, given that the operating modes of each entity switch over time during a fault scenario, the expression for the fault scenario matrix s is:

[0015] ,

[0016] The transmission and decoding process of the influencing factors of each fault scenario s is regarded as a combination of fault scenarios with uncertain factors. The differences between each generated fault scenario are calculated, and fitness values ​​are assigned according to the contribution of each fault scenario to the diversity of the fault set. The influence value of each fault scenario is assigned based on the solution x before fault scenario construction and the objective result of fault scenario s.

[0017] ,

[0018] in, , Let be the impact values ​​of adjacent fault scenarios, and i be the target index; calculate the impact values ​​of all s in the fault scenario set based on each i. Subsequently, the diversity of generated fault scenarios can be addressed by considering the geometric distance between each fault scenario. After analysis and sorting, the formula for calculating the geometric distance between adjacent scenes can be expressed as:

[0019] ,

[0020] in, For the ranking position of target i in the set of fault scenarios, after sorting and combining, the fault scenarios with lower rankings are excluded according to the geometric distribution distance between each fault scenario, and a new set of fault scenarios Ω containing fault influencing factors is formed.

[0021] Step 7: During the fault testing of the electrochemical energy storage power station, the signals to be tested include the DC bus signal of the energy storage power station, the grid-connected bus signal, the status signals of the energy storage container and battery cluster, and the bus signal. It is necessary to provide a simulated test environment for the fault signal type, construct the mapping matrix between the operating environment and the interface response, and determine the interface excitation and working status.

[0022] Step 8: The fault simulation control software control signal excitation / acquisition module acquires different types of signals from the encoded database. The signal acquisition board includes: an electrical signal acquisition board for acquiring circuit fluctuation current signals, voltage signals, and frequency signals; and a sensor signal acquisition board for acquiring sound, smoke, and temperature signals inside the battery container. The signal is processed and sent to the energy storage power station control center platform through a signal relay device. The control unit then sends instructions to conduct joint debugging and operation of the energy storage power station fault test system and the power grid system to simulate faults.

[0023] Step 9: After the single-fault scenario test program is completed, the signal excitation / acquisition module will again collect and analyze the energy storage power station operation information and the operation test signals of each subsystem, including: electrical signals such as battery SOC / SOH, power charge and discharge data, and voltage fluctuation rate; sensor signals such as battery compartment temperature, humidity, and noise intensity; PCS energy management signals; and AGC control signals. Finally, the test signal results will be saved to the database, and the next energy storage power station fault test will continue based on the fault scenario reconstruction.

[0024] Step 10: After each fault test item in the fault scenario set Ω is completed, it is displayed one by one on the UI interface of the main control software platform. Image and numerical analysis is performed on the signal fluctuation impact caused by the fault signal and the fault clearing status to complete the system integration test.

[0025] This testing method can rationally configure fault testing schemes through intelligent online learning in the case of partial installation of electrochemical energy storage power stations. Through the fault simulation and commissioning system, and by adopting the scenario reconstruction method, it can automatically perform fault simulation and virtual simulation debugging of the electrochemical energy storage power station in grid-connected / off-grid operation modes. This will effectively improve the fault detection efficiency and operation and maintenance reliability of electrochemical energy storage power stations, and reduce operation and maintenance costs. Attached Figure Description

[0026] Figure 1 This is a test connection diagram for a fault scenario of an electrochemical energy storage power station in the embodiment.

[0027] Figure 2 This is a diagram illustrating the construction of the electrochemical energy storage fault database in this embodiment.

[0028] Figure 3 This is a diagram showing the constituent elements of a fault test scenario for an electrochemical energy storage power station in the embodiment.

[0029] Figure 4 Flowchart of fault scenario reconstruction test for electrochemical energy storage power station. Detailed Implementation

[0030] Example:

[0031] A method for reconstructing fault scenarios in an electrochemical energy storage power station includes the following steps:

[0032] Step 1: Connect the electrochemical energy storage power station control center platform, fault simulation control software, and hardware-in-the-loop simulation model, such as... Figure 1 As shown;

[0033] The control center platform includes: an energy storage container energy management system, a power conversion system, an Ethernet communication interface, a signal converter, and an operation information acquisition device.

[0034] The fault simulation control software includes: a signal graphics card control program, a fault database, an "electric-thermal" fault data acquisition module, an information summarization and classification module, an information sending and receiving device, and a UI operation interface.

[0035] The main body of the semi-physical simulation model is an electrochemical energy storage power station semi-physical model built on the DSATools simulation platform. It is used to send operational fault information or receive test control commands. It also includes: a fault location system, an electrical parameter sampling system, and a thermal data sampling system.

[0036] Step 2: Construct an "electric-thermal" fault database for electrochemical energy storage power stations, such as... Figure 2 As shown, the energy storage power station collects "electrical-thermal" fault information through manual operation and maintenance experience and relay protection equipment.

[0037] Step 3: Preprocess the collected data. Process different types of signal data according to the custom encoding format, tag code category, signal meaning represented by each data bit, and fault location information. Decompose the fault information in a multi-dimensional manner to determine whether there is abnormal gas emission, the changes in the sensing of sound, smoke, and temperature sensors, and the changes in the three-level electrochemical parameters of "battery cluster-battery compartment-power station". Use a translation optimization algorithm with online learning capabilities to label and encode parameters such as fault location, fault device, fault impact, and fault parameters and load them into the database.

[0038] Step 4: Classify and describe faults, and store typical fault information including the operating scenarios and fault locations of energy storage power stations. Based on the degree of fault impact, use the analytic hierarchy process (AHP) and fuzzy logic to classify the fault hazard levels in the database into 1 to 10 levels. The fault database is then established to facilitate the retrieval of fault-related information later. This establishes a database containing various faults of energy storage power stations and their corresponding descriptions and definitions. The database includes a battery cluster fault database, a battery compartment fault database, and an energy storage power station bus fault database. Each part of the database includes data management, data retrieval, and data storage functions. The database also includes: operation and handling methods corresponding to various faults, fault reconstruction systems, energy storage power station control system models, and fault model simulation signals. During actual assembly and testing, the established database can be used to perform virtual reconstruction fault testing of different energy storage power station control systems.

[0039] Step 5: Divide the elements of the electrochemical energy storage power station operation scenario reconstruction into two parts: environmental factors and testing factors, such as... Figure 3 As shown, the scene reconstruction parameters and constraints are set in a standardized manner accordingly;

[0040] Step 6: Reconstructing fault scenarios for electrochemical energy storage power stations, such as... Figure 4 As shown; the fault generation scenario is a combination of various uncertain possible outcomes. The goal of fault scenario generation is to obtain a population containing as many different fault scenarios as possible after a finite number of iterations; a fitness evaluation function is used to reflect the degree of difference from other fault scenarios in the same fault scenario set, and the corresponding fault scenario set Ω is constructed; as detailed below:

[0041] Construct a fault scenario s, which includes n independently operating device entities o1, o2, ... o n Furthermore, given that the operating modes of each entity switch over time during a fault scenario, the expression for the fault scenario matrix s is:

[0042] ,

[0043] The transmission and decoding process of the influencing factors of each fault scenario s is regarded as a combination of fault scenarios with uncertain factors. The differences between each generated fault scenario are calculated, and fitness values ​​are assigned according to the contribution of each fault scenario to the diversity of the fault set. The influence value of each fault scenario is assigned based on the solution x before fault scenario construction and the objective result of fault scenario s.

[0044] ,

[0045] in, , Let be the impact values ​​of adjacent fault scenarios, and i be the target index; calculate the impact values ​​of all s in the fault scenario set based on each i. Subsequently, the diversity of generated fault scenarios can be addressed by considering the geometric distance between each fault scenario. After analysis and sorting, the formula for calculating the geometric distance between adjacent scenes can be expressed as:

[0046] ,

[0047] in, For the ranking position of target i in the set of fault scenarios, after sorting and combining, the fault scenarios with lower rankings are excluded according to the geometric distribution distance between each fault scenario, and a new set of fault scenarios Ω containing fault influencing factors is formed.

[0048] Step 7: During the fault testing of the electrochemical energy storage power station, the signals under test include the DC bus signal of the energy storage power station, the grid-connected bus signal, the status signals of the energy storage container and battery cluster, and the bus signal. A simulated test environment needs to be provided for each fault signal type, and a mapping matrix between the operating environment and interface response needs to be constructed to determine the interface excitation and operating status. The specific process includes:

[0049] Step 7.1: Input relevant parameters for individual battery cells, battery containers, and energy storage power stations;

[0050] Step 7.2: Select the power plant operation mode and conduct performance tests;

[0051] Step 7.3: Construct the mapping matrix and test data storage unit;

[0052] Step 7.4: Determine if the conditions for fault simulation are met. If they are met, proceed to step 6.11; otherwise, proceed to step 6.5.

[0053] Step 7.5: Conduct a routine operation simulation under the combined heat and power (CHP) system;

[0054] Step 7.6: Save the environmental parameters and simulation data, such as the power plant operation mode, to the data storage unit;

[0055] Step 7.7: Determine if the termination condition is met. If it is, end directly; otherwise, go to step 6.2.

[0056] Step 7.11: Select the fault category and fault node;

[0057] Step 7.12: Read the fault database of the electrochemical energy storage power station;

[0058] Step 7.13: Extract the mandatory fault categories and sampled fault categories based on the fault impact level to generate the scenario set Ω for this reconstruction;

[0059] Step 7.14: Run the fault categories in the scenario set Ω one by one, and collect the bus electrical quantity data and the operation data of each container in the energy storage power station;

[0060] Step 7.15: Calculate the maximum fluctuation rate of bus voltage and frequency, and the corresponding parameters such as operating temperature and output power of the device;

[0061] Step 7.16: The software control center samples and analyzes the fault data and issues corresponding fault clearance instructions;

[0062] Step 7.17: Determine if all scenes in the scene set Ω have finished running. If they have, proceed to step 6.6; otherwise, proceed to step 6.18.

[0063] Step 7.18: Update the environmental factors for the operation scenario of the energy storage power station;

[0064] Step 7.19: Update the test factors for the energy storage power station operation scenario; then return to step 6.14;

[0065] Step 8: The fault simulation control software control signal excitation / acquisition module acquires different types of signals from the encoded database. The signal acquisition board includes: an electrical signal acquisition board for acquiring circuit fluctuation current signals, voltage signals, and frequency signals; and a sensor signal acquisition board for acquiring sound, smoke, and temperature signals inside the battery container. The signal is processed and sent to the energy storage power station control center platform through a signal relay device. The control unit then sends instructions to conduct joint debugging and operation of the energy storage power station fault test system and the power grid system to simulate faults.

[0066] Step 9: After the single-fault scenario test program is completed, the signal excitation / acquisition module will again collect and analyze the energy storage power station operation information and the operation test signals of each subsystem, including: electrical signals such as battery SOC / SOH, power charge and discharge data, and voltage fluctuation rate; sensor signals such as battery compartment temperature, humidity, and noise intensity; PCS energy management signals; and AGC control signals. Finally, the test signal results will be saved to the database, and the next energy storage power station fault test will continue based on the fault scenario reconstruction.

[0067] Step 10: After each fault test item in the fault scenario set Ω is completed, it is displayed one by one on the UI interface of the main control software platform. Image and numerical analysis is performed on the signal fluctuation impact caused by the fault signal and the fault clearing status to complete the system integration test.

Claims

1. A method for reconstructing failure scenarios of an electrochemical energy storage power plant, characterized in that, The process includes the following: Step 1: Connect the electrochemical energy storage power station control center platform, fault simulation control software, and hardware-in-the-loop simulation model; The control center platform includes: an energy storage container energy management system, a power conversion system, an Ethernet communication interface, a signal converter, and an operation information acquisition device. The fault simulation control software includes: a signal graphics card control program, a fault database, an "electric-thermal" fault data acquisition module, an information summarization and classification module, an information sending and receiving device, and a UI operation interface. The main body of the semi-physical simulation model is an electrochemical energy storage power station semi-physical model built on the DSATools simulation platform. It is used to send operational fault information or receive test control commands. It also includes: a fault location system, an electrical parameter sampling system, and a thermal data sampling system. Step 2: Construct an "electric-thermal" fault database for electrochemical energy storage power stations, and collect "electric-thermal" fault information of energy storage power stations through manual operation and maintenance experience and relay protection equipment; Step 3: Preprocess the collected data. Different types of signal data are processed according to custom encoding format, tag code category, signal meaning represented by each data bit, and fault location information. The fault information is decomposed in a multi-dimensional manner to determine whether there is abnormal gas emission, the changes in the sensing of sound, smoke, and temperature sensors, and the changes in the three-level electrochemical parameters of "battery cluster-battery compartment-power station". A translation optimization algorithm with online learning capability is used to label and encode the fault location, fault device, fault impact, and fault parameter parameters and load them into the database. Step 4: Classify and describe faults, store typical fault information including the operating scenarios and fault locations of energy storage power stations, and classify the fault hazard levels in the database into 1 to 10 levels based on the degree of fault impact using the analytic hierarchy process (AHP) and fuzzy logic. The fault database is then established. This creates a database containing various faults of energy storage power stations and their corresponding descriptions and definitions. The database includes a battery cluster fault database, a battery compartment fault database, and an energy storage power station bus fault database. Each part of the database includes data management, data retrieval, and data storage functions. Step 5: Divide the elements of the electrochemical energy storage power station operation scenario reconstruction into two parts: environmental factors and test factors, and set the scenario reconstruction parameters and constraints accordingly. Step 6: Reconstructing fault scenarios for electrochemical energy storage power stations; using a fitness evaluation function to reflect the degree of difference from other fault scenarios in the same fault scenario set, and constructing the corresponding fault scenario set Ω; details are as follows: Construct a fault scenario s, which includes n independently operating device entities o1, o2, ... o n Furthermore, given that the operating modes of each entity switch over time during a fault scenario, the expression for the fault scenario matrix s is: ， The transmission and decoding process of the influencing factors of each fault scenario s is regarded as a combination of fault scenarios with uncertain factors. The differences between each generated fault scenario are calculated, and fitness values ​​are assigned according to the contribution of each fault scenario to the diversity of the fault set. The influence value of each fault scenario is assigned based on the solution x before fault scenario construction and the objective result of fault scenario s. ， Where i is the target index; based on each i, the index of all s in the fault scenario set is calculated. Subsequently, the diversity of generated fault scenarios can be addressed by considering the geometric distance between each fault scenario. After analysis and sorting, the formula for calculating the geometric distance between adjacent scenes can be expressed as: ， in, , These represent the impact values ​​of adjacent fault scenarios. For the ranking position of target i in the set of fault scenarios, after sorting and combining, the fault scenarios with lower rankings are excluded according to the geometric distribution distance between each fault scenario, and a new set of fault scenarios Ω containing fault influencing factors is formed. Step 7: During the fault testing of the electrochemical energy storage power station, the signals to be tested include the DC bus signal of the energy storage power station, the grid-connected bus signal, the status signals of the energy storage container and battery cluster, and the bus signal. It is necessary to provide a simulated test environment for the fault signal type, construct the mapping matrix between the operating environment and the interface response, and determine the interface excitation and working status. Step 8: The fault simulation control software control signal excitation / acquisition module acquires different types of signals from the encoded database. The signal acquisition board includes: an electrical signal acquisition board for acquiring circuit fluctuation current signals, voltage signals, and frequency signals; and a sensor signal acquisition board for acquiring sound, smoke, and temperature signals inside the battery container. The signal is processed and sent to the energy storage power station control center platform through a signal relay device. The control unit then sends instructions to conduct joint debugging and operation of the energy storage power station fault test system and the power grid system to simulate faults. Step 9: After the single-fault scenario test program is completed, the signal excitation / acquisition module will again collect and analyze the energy storage power station operation information and the operation test signals of each subsystem, including: electrical signals such as battery SOC / SOH, power charge and discharge data, and voltage fluctuation rate; sensor signals such as battery compartment temperature, humidity, and noise intensity; PCS energy management signals; and AGC control signals. Finally, the test signal results will be saved to the database, and the next energy storage power station fault test will continue based on the fault scenario reconstruction. Step 10: After each fault test item in the fault scenario set Ω is completed, it is displayed one by one on the UI interface of the main control software platform. Image and numerical analysis is performed on the signal fluctuation impact caused by the fault signal and the fault clearing status to complete the system integration test.

2. The method of claim 1, wherein, The database in step 4 also includes: operation and handling methods corresponding to various faults, fault reconstruction system, energy storage power station control system model and fault model simulation signals.

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