Energy storage power station state monitoring method, system and server

Abstract

The invention provides a state monitoring method and system for an energy storage power station and a server, and relates to the technical field of energy storage monitoring, and the method comprises the steps: calculating the health coefficient of the energy storage power station, and obtaining the transformer saturation and load saturation of the energy storage power station through a specific calculation mode; and the operation state of the energy storage power station is monitored in real time by using the data, so that the abnormal working state of the energy storage power station is accurately obtained in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage monitoring, and in particular to a method, system and server for monitoring the status of an energy storage power station. Background Art

[0002] The core function of an energy storage power station is to charge during periods of low electricity prices and discharge during peak periods, thereby generating corresponding profits or reducing electricity costs. As the installed capacity of industrial energy storage continues to increase, the amount of energy storage power station data that needs to be managed has also increased accordingly. Therefore, the need to add specific monitoring and analysis to conventional data monitoring is particularly important. Existing technologies mainly use forms or graphical curves to display real-time power station data. This makes it impossible to intuitively understand the operating health status of each site and the factors affecting the health of the power station. Professionals are required to analyze and judge the basic data uploaded by the energy storage power station, which is inefficient and prone to omissions. Summary of the Invention

[0003] In view of this, the object of the present invention is to provide a method, system, and server for monitoring the status of an energy storage power station. This method calculates the health coefficient of the energy storage power station and uses a specific calculation method to obtain the transformer saturation and load saturation of the energy storage power station. The above data is then used to implement real-time monitoring of the operating status of the energy storage power station, thereby accurately obtaining the abnormal operating status of the energy storage power station in real time, which can solve the above-mentioned problems existing in the prior art.

[0004] In a first aspect, an embodiment of the present invention provides a method for monitoring the state of an energy storage power station, the method comprising: Obtaining power data of the energy storage power station, and determining the grid power data, load power data, power status data, and charge and discharge power data corresponding to the energy storage power station based on the power data; Determine the health factor of the energy storage station based on the state of charge data and the charge and discharge power data. The health factor is used to characterize the working status of the energy storage station during the charge and discharge process. If the health factor meets the preset first threshold condition, the transformer saturation of the energy storage station is determined based on the grid power data, and the load saturation of the energy storage station is determined based on the load power data. The transformer saturation is used to characterize the transformer operating status of the energy storage station during the charging period, and the load saturation is used to characterize the load operating status of the energy storage station during the discharging period. The transformer saturation and load saturation are used to determine the abnormal working state of the energy storage power station.

[0005] Optionally, the steps of obtaining power data of the energy storage power station and determining grid power data, load power data, power state data, and charge and discharge power data corresponding to the energy storage power station based on the power data include: Obtain the AC meters for the transformers, battery managers, energy storage inverters, and grid-connected cabinets installed in the energy storage power station; Obtain the grid power data corresponding to the energy storage power station based on the transformer AC meter; Collect the power status data of the batteries in the energy storage power station based on the battery manager; Obtain the charging and discharging power data corresponding to the energy storage power station based on the energy storage inverter; Obtain the load power data corresponding to the energy storage power station based on the AC meter of the grid-connected cabinet.

[0006] Optionally, the step of determining a health factor corresponding to the energy storage power station based on the state of charge data and the charge and discharge power data includes: Determine an actual charge cut-off SOC value, an actual discharge cut-off SOC value, a set charge cut-off SOC value, and a set discharge cut-off SOC value of a battery in the energy storage power station based on the state of charge data and the charge and discharge power data; The health factor is calculated based on the actual charge cut-off SOC value, the actual discharge cut-off SOC value, the set charge cut-off SOC value, and the set discharge cut-off SOC value. The health factor is calculated using the following formula: I = (Ac-Ad) / (Sc-Sd); Where, I is the health factor; Ac is the actual charge cut-off SOC value; Ad is the actual discharge cut-off SOC value; Sc is the set charge cut-off SOC value; Sd is the set discharge cut-off SOC value.

[0007] Optionally, the transformer saturation of the energy storage power station is determined based on the grid power data, including: Determine the average load power, installed power, transformer capacity, and transformer power factor for the charging period corresponding to the energy storage power station based on grid power data; The transformer saturation is calculated based on the average load power, installed power, transformer capacity, and transformer power factor during the charging period. The transformer saturation is calculated using the following formula: TS=((PTV+PI) / (TC*0.9*PF))*100%; Among them, TS is the transformer saturation; PTV is the average load power during the charging period; PI is the installed power; TC is the transformer capacity; PF is the transformer power factor.

[0008] Optionally, determining the load saturation of the energy storage power station based on the load power data includes: Determine the discharge setting power corresponding to the energy storage power station and the average load power during the discharge period based on the load power data; The load saturation is calculated based on the discharge setting power and the average load power during the discharge period. The load saturation is calculated using the following formula: LS=(PDS / PDV)*100%; Where LS is the load saturation; PDS is the discharge setting power; and PDV is the average load power during the discharge period.

[0009] Optionally, the step of determining the abnormal operating state corresponding to the energy storage power station by using the transformer saturation and the load saturation includes: Obtaining a second threshold condition corresponding to transformer saturation and a third threshold condition corresponding to load saturation; If the transformer saturation does not meet the corresponding second threshold condition, it is determined that the energy storage power station is in a transformer load saturation state; If the load saturation does not meet the corresponding third threshold condition, it is determined that the energy storage power station is in an abnormal load state; The abnormal working state corresponding to the energy storage power station is determined based on the transformer load saturation state and the load abnormality state.

[0010] Optionally, after the step of obtaining the second threshold condition corresponding to the transformer saturation and the third threshold condition corresponding to the load saturation, the method further includes: If the transformer saturation satisfies the corresponding second threshold condition and the load saturation satisfies the corresponding third threshold condition, it is determined that the energy storage power station is in an abnormal shutdown state; The abnormal operating state corresponding to the energy storage power station is determined based on the abnormal shutdown state.

[0011] Optionally, after the step of determining the health factor corresponding to the energy storage power station based on the state of charge data and the charge and discharge power data, the method further includes: If the health coefficient does not meet the first threshold condition, it is determined that the energy storage power station is in a normal working state.

[0012] In a second aspect, the present invention provides an energy storage power station status monitoring system, the system comprising: A data acquisition unit, configured to acquire power data of the energy storage power station and determine grid power data, load power data, power status data, and charge and discharge power data corresponding to the energy storage power station based on the power data; A health factor calculation unit, configured to determine the health factor corresponding to the energy storage station based on the state of charge data and the charge and discharge power data; wherein the health factor is used to characterize the working state of the energy storage station during the charge and discharge process; a saturation calculation unit, configured to determine the transformer saturation of the energy storage station based on the grid power data and the load saturation of the energy storage station based on the load power data if the health factor satisfies a preset first threshold condition; wherein the transformer saturation is used to characterize the transformer operating state of the energy storage station during the charging period; and the load saturation is used to characterize the load operating state of the energy storage station during the discharging period; The working state acquisition unit is used to determine the abnormal working state corresponding to the energy storage power station by using the transformer saturation and the load saturation.

[0013] In a third aspect, an embodiment of the present invention further provides a server comprising a processor and a memory, wherein the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the steps of the energy storage power station status monitoring method provided in the first aspect.

[0014] In a fourth aspect, an embodiment of the present invention further provides a storage medium storing computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the steps of the energy storage power station status monitoring method provided in the first aspect.

[0015] An embodiment of the present invention provides a method, system, and server for monitoring the status of an energy storage power station. During the process of monitoring the status of an energy storage power station, the method first obtains power data of the energy storage power station and determines the grid power data, load power data, power state data, and charge and discharge power data corresponding to the energy storage power station based on the power data. Then, based on the power state data and charge and discharge power data, the health factor corresponding to the energy storage power station is determined. The health factor is used to characterize the operating status of the energy storage power station during the charging and discharging process. If the health factor meets a preset first threshold condition, the transformer saturation of the energy storage power station is determined based on the grid power data, and the load saturation of the energy storage power station is determined based on the load power data. The transformer saturation is used to characterize the transformer operating status of the energy storage power station during the charging period, and the load saturation is used to characterize the load operating status of the energy storage power station during the discharging period. Finally, the transformer saturation and load saturation are used to determine the abnormal operating status corresponding to the energy storage power station. The method calculates the health factor of the energy storage power station and obtains the transformer saturation and load saturation of the energy storage power station using a specific calculation method. The method then uses the above data to monitor the operating status of the energy storage power station in real time, thereby accurately and in real time obtaining abnormal operating status of the energy storage power station.

[0016] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the present invention. The purposes and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0017] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 A flow chart of a method for monitoring the status of an energy storage power station provided by an embodiment of the present invention; Figure 2 A flowchart of step S101 in a method for monitoring the state of an energy storage power station provided in an embodiment of the present invention; Figure 3 A flowchart of step S102 of a method for monitoring the state of an energy storage power station provided in an embodiment of the present invention; Figure 4 A flowchart of determining the transformer saturation of an energy storage power station based on grid power data in step S103 of a method for monitoring the state of an energy storage power station provided by an embodiment of the present invention; Figure 5 A flowchart of determining the load saturation of an energy storage power station based on load power data in step S103 of a method for monitoring the state of an energy storage power station provided by an embodiment of the present invention; Figure 6 A flowchart of step S104 of a method for monitoring the state of an energy storage power station provided in an embodiment of the present invention; Figure 7 This is a flowchart after step S601 in a method for monitoring the state of an energy storage power station provided by an embodiment of the present invention; Figure 8 A flow chart of another energy storage power station status monitoring method provided by an embodiment of the present invention; Figure 9 A schematic diagram of the structure of an energy storage power station status monitoring system provided by an embodiment of the present invention; Figure 10 A schematic diagram of the structure of a server provided in an embodiment of the present invention.

[0020] icon: 910 - data acquisition unit; 920 - health coefficient calculation unit; 930 - saturation calculation unit; 940 - working status acquisition unit; 101 - processor; 102 - memory; 103 - bus; 104 - communication interface. DETAILED DESCRIPTION

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0022] The core function of an energy storage power station is to charge during periods of low electricity prices and discharge during peak electricity price periods, thereby obtaining corresponding profits or reducing electricity costs. As the installed capacity of industrial energy storage continues to increase, the amount of energy storage power station data that needs to be managed has also increased accordingly. Therefore, it is particularly important to add specific monitoring and analysis needs on the basis of conventional data monitoring. In the process of obtaining power station data in real time, the existing technology mainly adopts a form or a graphical curve to display it in real time. It is impossible to intuitively obtain the operating health status of each site and the reasons affecting the health of the power station. Professionals are required to analyze and judge based on the basic data uploaded by the energy storage power station, which is inefficient and easy to miss. Based on this, the present invention provides a method, system and server for monitoring the status of an energy storage power station. The method calculates the health coefficient of the energy storage power station and uses a specific calculation method to obtain the transformer saturation and load saturation of the energy storage power station, and then uses the above data to realize real-time monitoring of the operating status of the energy storage power station, thereby obtaining the abnormal working status of the energy storage power station in real time and accurately.

[0023] To facilitate understanding of this embodiment, a method for monitoring the state of an energy storage power station disclosed in an embodiment of the present invention is first described in detail. Figure 1 As shown, the method includes: Step S101 : acquiring power data of an energy storage power station, and determining grid power data, load power data, power state data, and charge and discharge power data corresponding to the energy storage power station based on the power data.

[0024] Sensors deployed within the energy storage plant (such as current / voltage sensors and power transmitters), smart meters, and SCADA (Supervisory Control and Data Acquisition) systems collect real-time power operation data from the AC and DC sides, as well as the battery cluster. This data is typically collected on a one- to five-second basis, ensuring real-time data availability and meeting dynamic monitoring requirements.

[0025] Grid power data is obtained by analyzing the interaction between the grid and the energy storage power station. It mainly includes grid-connected active power and grid-connected reactive power. Grid-connected active power (P_grid) reflects the power value of the energy storage power station charging or drawing power from the grid; grid-connected reactive power (Q_grid) is used to evaluate the power component related to grid voltage stability.

[0026] Load power data is used to analyze user load demand within the energy storage power station's power supply range. It primarily includes real-time load active power and load curve characteristics. Real-time load active power (P_load) primarily represents the actual active power consumed by users, while load curve characteristics characterize load fluctuations during peak and valley periods.

[0027] State of charge data is primarily used to calculate the battery pack's State of Charge (SOC) based on battery charge and discharge data. Common methods include the Ah-Counting method and the Open Circuit Voltage (OCV) method. The Ah-Counting method calculates the remaining charge by multiplying the cumulative charge and discharge current by time. The OCV method calibrates the battery's SOC based on the relationship between the battery's voltage after rest and the SOC.

[0028] The charge and discharge power data can directly collect the real-time power of the battery pack during charging and discharging, and distinguish the power characteristics of the charging period (energy storage state) and the discharging period (power supply state).

[0029] Step S102: determining a health factor corresponding to the energy storage station based on the state of charge data and the charge and discharge power data; wherein the health factor is used to characterize the working state of the energy storage station during the charge and discharge process.

[0030] Since the price difference is fixed, maximizing discharge capacity is required to ensure profitability. That is, the battery is fully charged during the charging period and empty during the discharging period. Therefore, the parameters involved are actual charge and discharge data and configured charge and discharge data. These data are derived from state of charge data and charge and discharge power data. The health factor is determined based on the difference between the actual and configured charge and discharge data.

[0031] In step S103, if the health factor satisfies a preset first threshold condition, the transformer saturation of the energy storage station is determined based on the grid power data, and the load saturation of the energy storage station is determined based on the load power data. The transformer saturation is used to characterize the transformer operating state of the energy storage station during the charging period, and the load saturation is used to characterize the load operating state of the energy storage station during the discharging period.

[0032] The first threshold condition is used to determine whether the energy storage station is in an abnormal operating state. When the health factor meets the preset first threshold condition, it indicates that the energy storage station is in an abnormal operating state. Grid power data and load power data are needed to accurately determine the specific form of the abnormal operating state. In the specific implementation process, the transformer saturation and load saturation of the energy storage station are determined based on the grid power data and load power data, respectively. The transformer saturation and load saturation can then be used to identify transformer overload issues and load overload issues in the energy storage station.

[0033] Step S104: determining the abnormal working state corresponding to the energy storage power station by using the transformer saturation and the load saturation.

[0034] Transformer saturation is used to determine whether the transformer load is saturated, and load saturation is used to determine whether the load is too low, thereby determining the specific abnormal operating state. Specifically, the health factor in this method is used to determine whether the energy storage power station is abnormal, and the specific details of the abnormal operating state of the energy storage power station can be obtained through subsequent steps.

[0035] Optionally, the step S101 of acquiring power data of the energy storage power station and determining the grid power data, load power data, power state data and charge and discharge power data corresponding to the energy storage power station based on the power data is as follows: Figure 2 Shown, including: Step S201: Acquire the AC meter of the transformer, the battery manager, the energy storage inverter, and the AC meter of the grid-connected cabinet provided in the energy storage power station.

[0036] Transformer AC meters are deployed on the high-voltage or low-voltage side of the transformer to monitor the energy exchange between the grid and the energy storage station. A battery management system (BMS), integrated into the battery cluster or battery pack, monitors battery voltage, current, temperature, and state of charge (SOC) in real time. The power storage inverter (PCS) connects the battery system to the AC grid, providing bidirectional power conversion and recording charge and discharge power and energy flow. A grid-connected cabinet AC meter is installed at the grid cabinet output to measure the actual power delivered by the energy storage station to the load.

[0037] Each device exchanges data through protocols such as Modbus RTU / TCP, CAN bus, RS485 or industrial Ethernet. The data acquisition frequency must be set synchronously (such as 1 second / time) to ensure the time consistency of parameter calculation.

[0038] Step S202: Obtaining grid power data corresponding to the energy storage power station based on the transformer AC meter.

[0039] During the transformer AC meter data collection process, the following measurement parameters can be collected: three-phase voltage (Ua, Ub, Uc), three-phase current (Ia, Ib, Ic), frequency (f), and power factor (cosφ). This can then be verified for three-phase balance, calculating the degree of three-phase current imbalance (e.g., maximum phase current deviation ≤ 10%). A power factor check can also be performed to ensure the grid-side power factor is above 0.95 to minimize reactive power losses.

[0040] The process of acquiring grid power data involves calculating active and reactive power, which will not be detailed here. The resulting power data can be filtered to improve its reliability. Specifically, a sliding average or Kalman filter algorithm can be used to eliminate instantaneous fluctuations.

[0041] Step S203: The battery manager collects the power state data corresponding to the batteries in the energy storage power station.

[0042] Basic parameters collected by the battery manager include: single cell voltage, total battery pack voltage, charge / discharge current, and battery temperature. State of charge data can be collected using ampere-hour integration and OCV-SOC curve calibration. In specific scenarios, the state of health (SOH) must also be considered. This health status is calculated by combining battery cycle count, charge / discharge depth, and temperature history to estimate the battery capacity decay rate, which can then be incorporated into the SOH data.

[0043] Step S204: acquiring charging and discharging power data corresponding to the energy storage power station based on the energy storage inverter.

[0044] Key parameters for energy storage inverter data collection include: DC side voltage, DC side current, AC side power, and operating mode. The process of acquiring charge and discharge power data involves determining the charge and discharge direction. Specifically, in charging mode, the DC side current flows into the battery, and the AC side power is negative; in discharging mode, the DC side current flows out of the battery, and the AC side power is positive. During power calculation, the DC side power is directly obtained by multiplying its corresponding voltage and current values, and will not be further explained.

[0045] Step S205: Obtain load power data corresponding to the energy storage power station based on the AC meter of the grid cabinet.

[0046] The AC meter data collection process for power distribution cabinets involves measurements such as three-phase voltage, three-phase current, active power, reactive power, and frequency. In practical scenarios, data synchronization is necessary to ensure accurate power flow calculations by aligning the timestamps of the data with the grid power data.

[0047] During the load power data acquisition process, the load characteristics can be analyzed, and the real-time load power curve can be used to identify peak and valley periods (such as 8-10 am and 6-9 pm). The load type judgment process involves industrial load (high volatility), commercial load (strong regularity), and residential load (obvious time period). Historical data can be combined with meteorological factors (such as temperature and holidays) to predict load trends in future time periods, thereby obtaining specific load power data.

[0048] Optionally, step S102 of determining the health coefficient corresponding to the energy storage power station based on the state of charge data and the charge and discharge power data is as follows: Figure 3 Shown, including: Step S301, determining an actual charge cut-off SOC value, an actual discharge cut-off SOC value, a set charge cut-off SOC value, and a set discharge cut-off SOC value of a battery in an energy storage power station based on the state of charge data and the charge and discharge power data; Step S302 , calculating a health factor according to the actual charge cut-off SOC value, the actual discharge cut-off SOC value, the set charge cut-off SOC value, and the set discharge cut-off SOC value.

[0049] The health factor is calculated using the following formula: I = (Ac-Ad) / (Sc-Sd); Where, I is the health factor; Ac is the actual charge cut-off SOC value; Ad is the actual discharge cut-off SOC value; Sc is the set charge cut-off SOC value; Sd is the set discharge cut-off SOC value.

[0050] In this case, a health factor of 1 indicates a healthy state, while a health factor of less than 1 indicates an unhealthy state. A healthy energy storage plant charges as much as possible during off-peak periods and discharges as much as possible during peak periods. If the health factor is less than 1, consider possible reasons for an abnormal shutdown, such as transformer load saturation (incomplete charging), low power load (incomplete discharge), or equipment failure.

[0051] The following describes the process of judging whether the transformer load is saturated. Optionally, the transformer saturation of the energy storage power station can be determined based on the grid power data, such as Figure 4 Shown, including: Step S401: determining the average load power, installed power, transformer capacity, and transformer power factor of the energy storage power station during the charging period based on the grid power data; Step S402 : calculating the transformer saturation according to the average load power, installed power, transformer capacity, and transformer power factor during the charging period.

[0052] The transformer saturation is calculated using the following formula: TS=((PTV+PI) / (TC*0.9*PF))*100%; Among them, TS is the transformer saturation; PTV is the average load power during the charging period; PI is the installed power; TC is the transformer capacity; PF is the transformer power factor.

[0053] The following describes the process of judging whether the load power consumption is small. Optionally, the load saturation of the energy storage power station is determined based on the load power data, such as Figure 5 As shown, including; Step S501: determining the discharge setting power and the average load power during the discharge period corresponding to the energy storage power station based on the load power data; Step S502 : Calculate the load saturation according to the set discharge power and the average load power during the discharge period.

[0054] The load saturation is calculated using the following formula: LS=(PDS / PDV)*100%; Where LS is the load saturation; PDS is the discharge setting power; and PDV is the average load power during the discharge period.

[0055] The above means achieve accurate calculation of transformer saturation and load saturation. On this basis, the step S104 of determining the abnormal working state corresponding to the energy storage power station is performed using the transformer saturation and load saturation. Figure 6 Shown, including: Step S601, obtaining a second threshold condition corresponding to transformer saturation and a third threshold condition corresponding to load saturation; Step S602: If the transformer saturation does not meet the corresponding second threshold condition, it is determined that the energy storage power station is in a transformer load saturation state; Step S603: If the load saturation does not meet the corresponding third threshold condition, it is determined that the energy storage power station is in an abnormal load state; Step S604 : determining an abnormal operating state corresponding to the energy storage power station based on the transformer load saturation state and the load abnormality state.

[0056] After obtaining the transformer saturation and load saturation, the corresponding second threshold conditions and third threshold conditions are obtained respectively. If the transformer saturation does not meet the corresponding second threshold condition, it is determined that the energy storage power station is in a transformer load saturation state; and if the load saturation does not meet the corresponding third threshold condition, it is determined that the energy storage power station is in a load abnormality state. For example, the second threshold condition is to determine whether the value of the transformer saturation is less than or equal to 1. If not, it indicates that the energy storage power station is in a transformer load saturation state. Similarly, the third threshold condition is to determine whether the load saturation is less than or equal to 1. If not, it indicates that the energy storage power station is in a load abnormality state.

[0057] Optionally, after step S601 of obtaining the second threshold condition corresponding to the transformer saturation and the third threshold condition corresponding to the load saturation, as shown in FIG. Figure 7 As shown, the method further includes: Step S701: If the transformer saturation satisfies the corresponding second threshold condition and the load saturation satisfies the corresponding third threshold condition, it is determined that the energy storage power station is in an abnormal shutdown state; Step S702: determining an abnormal operating state corresponding to the energy storage power station based on the abnormal shutdown state.

[0058] If the transformer saturation value is greater than 1 and the load saturation value is also greater than 1, it indicates that the energy storage power station is in an abnormal shutdown state. By utilizing the second and third threshold conditions described above, the three abnormal operating states corresponding to the energy storage power station can be accurately determined. This method can automatically determine, thus solving the problem of low efficiency and easy omissions caused by manual analysis.

[0059] Optionally, after the step of determining the health coefficient corresponding to the energy storage power station based on the power state data and the charge and discharge power data, the method further includes: if the health coefficient does not meet the first threshold condition, determining that the energy storage power station is in a normal working state. Figure 8 As shown, it is worth mentioning that Figure 8 The first threshold condition in is to determine whether the health coefficient is not equal to 1. If so, it indicates that the energy storage power station is unhealthy; if not, the health coefficient is equal to 1, indicating that the energy storage power station is in a healthy state.

[0060] As can be seen from the energy storage power station status monitoring method mentioned in the above embodiment, this method calculates the health coefficient of the energy storage power station and uses a specific calculation method to obtain the transformer saturation and load saturation of the energy storage power station, and then uses the above data to realize real-time monitoring of the operating status of the energy storage power station, thereby obtaining the abnormal operating status of the energy storage power station in real time and accurately.

[0061] Corresponding to the energy storage power station state monitoring method provided in the above embodiment, the embodiment of the present invention provides an energy storage power station state monitoring system, such as Figure 9 As shown, the system includes: The data acquisition unit 910 is used to acquire power data of the energy storage power station and determine the grid power data, load power data, power state data, and charge and discharge power data corresponding to the energy storage power station based on the power data; A health coefficient calculation unit 920 is configured to determine a health coefficient corresponding to the energy storage station based on the state of charge data and the charge and discharge power data; wherein the health coefficient is used to characterize the working state of the energy storage station during the charge and discharge process; The saturation calculation unit 930 is configured to determine the transformer saturation of the energy storage station based on the grid power data and the load saturation of the energy storage station based on the load power data if the health coefficient meets a preset first threshold condition. The transformer saturation is used to characterize the transformer operating state of the energy storage station during the charging period, and the load saturation is used to characterize the load operating state of the energy storage station during the discharging period. The working state acquisition unit 940 is configured to determine the abnormal working state corresponding to the energy storage power station by using the transformer saturation and the load saturation.

[0062] As can be seen from the energy storage power station status monitoring system mentioned in the above embodiment, the system calculates the health coefficient of the energy storage power station and uses a specific calculation method to obtain the transformer saturation and load saturation of the energy storage power station. Then, the above data is used to realize real-time monitoring of the operating status of the energy storage power station, thereby obtaining the abnormal operating status of the energy storage power station in real time and accurately.

[0063] The energy storage power station status monitoring system provided in the embodiment of the present invention has the same implementation principles and technical effects as the aforementioned energy storage power station status monitoring method embodiment. For the sake of brief description, any matters not mentioned in the system embodiment can be referred to the corresponding content in the aforementioned energy storage power station status monitoring method embodiment.

[0064] This embodiment also provides a server, the structural diagram of which is as follows: Figure 10 As shown, the device includes a processor 101 and a memory 102; wherein the memory 102 is used to store one or more computer instructions, and the one or more computer instructions are executed by the processor to implement the steps of the above-mentioned energy storage power station status monitoring method.

[0065] Figure 10 The server shown further includes a bus 103 and a communication interface 104 , and the processor 101 , the communication interface 104 and the memory 102 are connected via the bus 103 .

[0066] The memory 102 may include a high-speed random access memory (RAM) and may also include a non-volatile memory, such as at least one disk storage. The bus 103 may be an ISA bus, a PCI bus, or an EISA bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 10 It is represented by only one bidirectional arrow, but it does not mean that there is only one bus or one type of bus.

[0067] The communication interface 104 is used to connect to at least one user terminal and other network units through a network interface, and send the encapsulated IPv4 message or IPv4 message to the user terminal through the network interface.

[0068] The processor 101 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by an integrated logic circuit of hardware in the processor 101 or by instructions in the form of software. The above-mentioned processor 101 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The various methods, steps, and logic block diagrams disclosed in the embodiments of the present disclosure can be implemented or executed. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present disclosure can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in memory 102, and processor 101 reads information in memory 102 and, in conjunction with its hardware, completes the steps of the method of the aforementioned embodiment.

[0069] An embodiment of the present invention further provides a storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the energy storage power station status monitoring method in the aforementioned embodiment are executed.

[0070] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, equipment and methods can be implemented in other ways. The system embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interface, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0071] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0072] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0073] If the functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0074] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed by the present invention, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for monitoring the status of an energy storage power station, characterized in that: The method comprises: Acquire power data of the energy storage power station, and determine grid power data, load power data, power state data, and charge and discharge power data corresponding to the energy storage power station based on the power data; Determining a health factor corresponding to the energy storage power station based on the state of charge data and the charge and discharge power data; wherein the health factor is used to characterize the working state of the energy storage power station during the charge and discharge process; If the health factor satisfies a preset first threshold condition, the transformer saturation of the energy storage power station is determined based on the grid power data, and the load saturation of the energy storage power station is determined based on the load power data; wherein the transformer saturation is used to characterize the transformer operating state of the energy storage power station during the charging time period; and the load saturation is used to characterize the load operating state of the energy storage power station during the discharging time period; The abnormal working state corresponding to the energy storage power station is determined using the transformer saturation and the load saturation.

2. The energy storage power station status monitoring method according to claim 1, characterized in that: The steps of obtaining power data of an energy storage power station and determining grid power data, load power data, power state data, and charge and discharge power data corresponding to the energy storage power station based on the power data include: Obtaining the transformer AC meter, battery manager, energy storage inverter, and grid cabinet AC meter provided in the energy storage power station; Acquiring the grid power data corresponding to the energy storage power station based on the transformer AC meter; Collecting the power state data corresponding to the batteries in the energy storage power station based on the battery manager; Acquiring the charging and discharging power data corresponding to the energy storage power station based on the energy storage inverter; The load power data corresponding to the energy storage power station is obtained based on the AC meter of the grid cabinet.

3. The energy storage power station status monitoring method according to claim 1, characterized in that: The step of determining a health coefficient corresponding to the energy storage power station based on the state of charge data and the charge and discharge power data includes: Determine an actual charge cut-off SOC value, an actual discharge cut-off SOC value, a set charge cut-off SOC value, and a set discharge cut-off SOC value of a battery in the energy storage power station based on the state of charge data and the charge and discharge power data; The health factor is calculated according to the actual charge cut-off SOC value, the actual discharge cut-off SOC value, the set charge cut-off SOC value, and the set discharge cut-off SOC value; the health factor is calculated by the following formula: I = (Ac-Ad) / (Sc-Sd); Wherein, I is the health coefficient; Ac is the actual charge cut-off SOC value; Ad is the actual discharge cut-off SOC value; Sc is the set charge cut-off SOC value; and Sd is the set discharge cut-off SOC value.

4. The energy storage power station status monitoring method according to claim 1, characterized in that: Determining the transformer saturation of the energy storage power station based on the grid power data includes: Determine, based on the grid power data, the average load power, installed power, transformer capacity, and transformer power factor during the charging period corresponding to the energy storage power station; The transformer saturation is calculated based on the average load power during the charging period, the installed power, the transformer capacity, and the transformer power factor. The transformer saturation is calculated using the following formula: TS=((PTV+PI) / (TC*0.9*PF))*100%; Wherein, TS is the transformer saturation; PTV is the average load power during the charging period; PI is the installed power; TC is the transformer capacity; and PF is the transformer power factor.

5. The energy storage power station status monitoring method according to claim 1, characterized in that: Determining the load saturation of the energy storage power station based on the load power data includes: Determine the discharge setting power and the average load power during the discharge period corresponding to the energy storage power station based on the load power data; The load saturation is calculated according to the discharge setting power and the average load power during the discharge time period; the load saturation is calculated using the following formula: LS=(PDS / PDV)*100%; Wherein, LS is the load saturation; PDS is the discharge setting power; and PDV is the average load power during the discharge time period.

6. The energy storage power station status monitoring method according to claim 1, characterized in that: The step of determining the abnormal working state corresponding to the energy storage power station by using the transformer saturation and the load saturation includes: Obtaining a second threshold condition corresponding to the transformer saturation and a third threshold condition corresponding to the load saturation; If the transformer saturation does not meet the corresponding second threshold condition, determining that the energy storage power station is in a transformer load saturation state; If the load saturation does not meet the corresponding third threshold condition, determining that the energy storage power station is in an abnormal load state; The abnormal operating state corresponding to the energy storage power station is determined based on the transformer load saturation state and the load abnormal state.

7. The energy storage power station status monitoring method according to claim 6, characterized in that: After the step of obtaining the second threshold condition corresponding to the transformer saturation and the third threshold condition corresponding to the load saturation, the method further includes: If the transformer saturation satisfies the corresponding second threshold condition and the load saturation satisfies the corresponding third threshold condition, determining that the energy storage power station is in an abnormal shutdown state; The abnormal operating state corresponding to the energy storage power station is determined based on the abnormal shutdown state.

8. The method for monitoring the state of an energy storage power station according to any one of claims 1 to 7, characterized in that: After the step of determining a health factor corresponding to the energy storage power station based on the state of charge data and the charge and discharge power data, the method further includes: If the health coefficient does not meet the first threshold condition, it is determined that the energy storage power station is in a normal working state.

9. A state monitoring system for an energy storage power station, characterized in that: The system comprises: a data acquisition unit, configured to acquire power data of the energy storage power station, and determine grid power data, load power data, power state data, and charge and discharge power data corresponding to the energy storage power station based on the power data; a health coefficient calculation unit, configured to determine a health coefficient corresponding to the energy storage station based on the state of charge data and the charge and discharge power data; wherein the health coefficient is used to characterize the working state of the energy storage station during the charge and discharge process; a saturation calculation unit, configured to determine, if the health coefficient satisfies a preset first threshold condition, a transformer saturation of the energy storage station based on the grid power data, and determine a load saturation of the energy storage station based on the load power data; wherein the transformer saturation is used to characterize the transformer operating state of the energy storage station during a charging period; and the load saturation is used to characterize the load operating state of the energy storage station during a discharging period; A working state acquisition unit is used to determine an abnormal working state corresponding to the energy storage power station by using the transformer saturation and the load saturation.

10. A server, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the steps of the energy storage power station status monitoring method according to any one of claims 1 to 8.

Images