Energy storage power station state monitoring method, system and server

Abstract

The application provides a kind of energy storage power station state monitoring method, system and server, related to energy storage monitoring technical field, the method is by calculating the health coefficient of energy storage power station, and the saturation of transformer and load saturation of energy storage power station is obtained using specific calculation method, and then the running state of energy storage power station is monitored in real time using the above data, so as to obtain the abnormal working state of energy storage power station in real time and accurately.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy storage monitoring, in particular to an energy storage power station state monitoring method, system and server. BACKGROUND

[0002] The core function of the energy storage power station is to charge in the time period when the electricity price is low and discharge in the time point when the electricity price is high, so as to obtain corresponding profit or reduce the power cost. With the continuous increase of industrial energy storage installed capacity, the energy storage power station data to be managed also increases accordingly, so it is particularly important to increase specific monitoring analysis on the basis of conventional data monitoring. In the prior art, the real-time acquisition of power station data is mainly in the form of a form or a graphical curve for real-time display, which cannot intuitively obtain the running health status of each site and the reasons affecting the health of the power station. Professional personnel need to analyze and judge through the basic data uploaded by the energy storage power station, which is low in efficiency and easy to miss. SUMMARY

[0003] Therefore, the purpose of the present application is to provide an energy storage power station state monitoring method, system and server. The method calculates the health coefficient of the energy storage power station, and obtains the transformer saturation degree and the load saturation degree of the energy storage power station by using a specific calculation method, and then realizes the real-time monitoring of the running state of the energy storage power station by using the above data, so as to obtain the abnormal working state of the energy storage power station in real time and accurately, and solve the above problems existing in the prior art.

[0004] In a first aspect, the present application provides an energy storage power station state monitoring method, which comprises:

[0005] acquiring power data of the energy storage power station, and determining power grid power data, load power data, power state data and charge-discharge power data corresponding to the energy storage power station based on the power data;

[0006] determining a health coefficient corresponding to the energy storage power station based on the power state data and the charge-discharge power data; wherein the health coefficient is used to represent the working state of the energy storage power station in the charge-discharge process;

[0007] if the health coefficient meets a preset first threshold condition, determining a transformer saturation degree of the energy storage power station based on the power grid power data, and determining a load saturation degree of the energy storage power station based on the load power data; wherein the transformer saturation degree is used to represent the working state of the transformer of the energy storage power station in the charge time period; and the load saturation degree is used to represent the working state of the load of the energy storage power station in the discharge time period;

[0008] determining an abnormal working state corresponding to the energy storage power station by using the transformer saturation degree and the load saturation degree.

[0009] Optionally, the step of acquiring power data of the energy storage power station and determining power grid power data, load power data, state of charge data, and charging and discharging power data corresponding to the energy storage power station based on the power data comprises:

[0010] A transformer AC meter, a battery manager, an energy storage inverter, and a grid-connected cabinet AC meter provided in the energy storage power station are acquired.

[0011] The power grid power data corresponding to the energy storage power station is acquired based on the transformer AC meter.

[0012] The state of charge data corresponding to the battery in the energy storage power station is acquired based on the battery manager.

[0013] The charging and discharging power data corresponding to the energy storage power station is acquired based on the energy storage inverter.

[0014] The load power data corresponding to the energy storage power station is acquired based on the grid-connected cabinet AC meter.

[0015] Optionally, the step of determining the health coefficient corresponding to the energy storage power station based on the state of charge data and the charging and discharging power data comprises:

[0016] The actual charging cutoff SOC value, the actual discharging cutoff SOC value, the set charging cutoff SOC value, and the set discharging cutoff SOC value of the battery in the energy storage power station are determined based on the state of charge data and the charging and discharging power data.

[0017] The health coefficient is calculated according to the actual charging cutoff SOC value, the actual discharging cutoff SOC value, the set charging cutoff SOC value, and the set discharging cutoff SOC value. The health coefficient is calculated by the following formula:

[0018] I = (Ac-Ad) / (Sc-Sd);

[0019] wherein I is the health coefficient, Ac is the actual charging cutoff SOC value, Ad is the actual discharging cutoff SOC value, Sc is the set charging cutoff SOC value, and Sd is the set discharging cutoff SOC value.

[0020] Optionally, the transformer saturation degree of the energy storage power station is determined based on the power grid power data, comprising:

[0021] The charging time period average load power, the installed capacity, the transformer capacity, and the transformer power factor corresponding to the energy storage power station are determined based on the power grid power data.

[0022] The transformer saturation degree is calculated according to the charging time period average load power, the installed capacity, the transformer capacity, and the transformer power factor. The transformer saturation degree is calculated by the following formula:

[0023] TS = ((PTV+PI) / (TC*0.9*PF))*100%.

[0024] wherein, TS is transformer saturation; PTV is average load power of charging time period; PI is installed power; TC is transformer capacity; PF is transformer power factor.

[0025] Optionally, the determining the load saturation of the energy storage power station based on the load power data comprises:

[0026] determining the discharging setting power and the average load power of the discharging time period of the energy storage power station based on the load power data;

[0027] calculating the load saturation according to the discharging setting power and the average load power of the discharging time period; the load saturation is calculated by the following formula:

[0028] LS = (PDS / PDV) * 100%;

[0029] wherein, LS is the load saturation; PDS is the discharging setting power; PDV is the average load power of the discharging time period.

[0030] Optionally, the determining the abnormal working state of the energy storage power station based on the transformer saturation and the load saturation comprises:

[0031] obtaining a second threshold condition corresponding to the transformer saturation and a third threshold condition corresponding to the load saturation;

[0032] if the transformer saturation does not satisfy the corresponding second threshold condition, determining that the energy storage power station is in a transformer load saturation state;

[0033] if the load saturation does not satisfy the corresponding third threshold condition, determining that the energy storage power station is in a load load abnormal state;

[0034] determining the abnormal working state of the energy storage power station based on the transformer load saturation state and the load load abnormal state.

[0035] 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 comprises:

[0036] 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;

[0037] determining the abnormal working state of the energy storage power station based on the abnormal shutdown state.

[0038] Optionally, after the step of determining the health coefficient of the energy storage power station based on the power state data and the charging and discharging power data, the method further comprises:

[0039] If the health coefficient does not satisfy the first threshold condition, it is determined that the energy storage power station is in a normal working state.

[0040] In a second aspect, the present application provides an energy storage power station state monitoring system, comprising:

[0041] 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-discharge power data corresponding to the energy storage power station based on the power data;

[0042] a health coefficient calculation unit configured to determine a health coefficient corresponding to the energy storage power station based on the power state data and the charge-discharge power data; wherein the health coefficient is used to represent the working state of the energy storage power station during the charge-discharge process;

[0043] a saturation degree calculation unit configured to, if the health coefficient satisfies a preset first threshold condition, determine a transformer saturation degree of the energy storage power station based on the grid power data, and determine a load saturation degree of the energy storage power station based on the load power data; wherein the transformer saturation degree is used to represent the working state of the transformer of the energy storage power station in a charging time period; and the load saturation degree is used to represent the working state of the load of the energy storage power station in a discharging time period;

[0044] a working state acquisition unit configured to determine an abnormal working state corresponding to the energy storage power station by using the transformer saturation degree and the load saturation degree.

[0045] In a third aspect, the present application provides a server, comprising a processor and a memory, wherein the memory stores computer executable instructions executable by the processor, and the processor executes the computer executable instructions to implement the steps of the energy storage power station state monitoring method provided in the first aspect.

[0046] In a fourth aspect, the present application provides a storage medium, wherein the storage medium stores computer executable instructions, and the computer executable instructions, when invoked and executed by a processor, cause the processor to implement the steps of the energy storage power station state monitoring method provided in the first aspect.

[0047] The energy storage power station state monitoring method, system and server provided by the embodiment of the present application, in the process of monitoring the state of the energy storage power station, first acquires power data of the energy storage power station, and determines power grid power data, load power data, power state data and charge-discharge power data corresponding to the energy storage power station based on the power data; then determines a health coefficient corresponding to the energy storage power station based on the power state data and the charge-discharge power data; wherein the health coefficient is used to represent the working state of the energy storage power station in the charge-discharge process; if the health coefficient meets a preset first threshold condition, the transformer saturation degree of the energy storage power station is determined based on the power grid power data, and the load saturation degree of the energy storage power station is determined based on the load power data; wherein the transformer saturation degree is used to represent the transformer working state of the energy storage power station in the charge period; the load saturation degree is used to represent the load working state of the energy storage power station in the discharge period; finally, the abnormal working state corresponding to the energy storage power station is determined by using the transformer saturation degree and the load saturation degree. The method calculates the health coefficient of the energy storage power station, and obtains the transformer saturation degree and the load saturation degree of the energy storage power station by using a specific calculation method, and then realizes real-time monitoring of the running state of the energy storage power station by using the above data, so as to obtain the abnormal working state of the energy storage power station in real time and accurately.

[0048] Other features and advantages of the present application will be set forth in the descriptions below, and in part will become apparent to those skilled in the art upon examination of the following or can be learned by practice of the present application. The objects and other advantages of the present application can be realized and attained by the structure particularly pointed out in the description, claims and drawings.

[0049] In order to make the above-mentioned objects, characteristics and advantages of the present application more obvious and easy to understand, the following preferred embodiments are specifically described below, and the accompanying drawings are described in detail as follows. BRIEF DESCRIPTION OF DRAWINGS

[0050] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings needed to be used in the specific embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can also obtain other drawings according to these drawings without creative labor.

[0051] Figure 1 The flow chart of the energy storage power station state monitoring method provided by the embodiment of the present application;

[0052] Figure 2 The flow chart of step S101 in the energy storage power station state monitoring method provided by the embodiment of the present application;

[0053] Figure 3The flow chart of step S102 of the energy storage power station state monitoring method provided by the embodiment of the present application;

[0054] Figure 4 The flow chart of determining the transformer saturation degree of the energy storage power station based on the power grid power data in step S103 of the energy storage power station state monitoring method provided by the embodiment of the present application;

[0055] Figure 5 The flow chart of determining the load saturation degree of the energy storage power station based on the load power data in step S103 of the energy storage power station state monitoring method provided by the embodiment of the present application;

[0056] Figure 6 The flow chart of step S104 of the energy storage power station state monitoring method provided by the embodiment of the present application;

[0057] Figure 7 The flow chart after step S601 of the energy storage power station state monitoring method provided by the embodiment of the present application;

[0058] Figure 8 The flow chart of another energy storage power station state monitoring method provided by the embodiment of the present application;

[0059] Figure 9 The structural schematic diagram of the energy storage power station state monitoring system provided by the embodiment of the present application;

[0060] Figure 10 The structural schematic diagram of the server provided by the embodiment of the present application.

[0061] Icon:

[0062] 910-data acquisition unit; 920-health coefficient calculation unit; 930-saturation calculation unit; 940-working state acquisition unit;

[0063] 101-processor; 102-memory; 103-bus; 104-communication interface. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme of the present application will be described clearly and completely in combination with embodiments. Obviously, the described embodiments are some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0065] The core function of the energy storage power station is to charge during a low electricity price period and discharge during a high electricity price period, so as to obtain corresponding profits or reduce power costs. With the increasing of the installed capacity of industrial energy storage, the data of the energy storage power station to be managed also increases accordingly, and therefore, it is particularly important to increase specific monitoring analysis on the basis of conventional data monitoring. In the prior art, the real-time acquisition of the power station data is mainly in the form of a table or a graphical curve for real-time display, and the running health status of each station and the reasons affecting the health of the power station cannot be intuitively obtained, and professional personnel need to analyze and judge the basic data uploaded by the energy storage power station, which is low in efficiency and easy to miss. Based on this, the present application provides an energy storage power station state monitoring method, system and server, which calculates the health coefficient of the energy storage power station, obtains the transformer saturation degree and the load saturation degree of the energy storage power station by using a specific calculation method, and then realizes real-time monitoring of the running state of the energy storage power station by using the above data, so as to obtain the abnormal working state of the energy storage power station in real time and accurately.

[0066] In order to facilitate the understanding of the present embodiment, first, a kind of energy storage power station state monitoring method disclosed in the present application embodiment is introduced in detail, as shown in Figure 1 The method comprises:

[0067] In step S101, the power data of the energy storage power station is acquired, and the corresponding power grid power data, load power data, power state data and charge-discharge power data of the energy storage power station are determined based on the power data.

[0068] The power running data of the alternating current side, the direct current side and the battery cluster are collected in real time by the sensors (such as current / voltage sensors, power transducers), smart meters and SCADA (data acquisition and monitoring control) systems deployed in the energy storage power station. The collection frequency is usually in seconds (1-5 seconds) as a cycle, to ensure the real-time nature of the data and meet the dynamic monitoring requirements.

[0069] The power grid power data is obtained by analyzing the interactive power between the power grid and the energy storage power station, mainly including grid-connected active power and grid-connected reactive power. The grid-connected active power (P_grid) reflects the power value of the energy storage power station charging or taking power from the power grid; the grid-connected reactive power (Q_grid) is used to evaluate the power component related to the stability of the power grid voltage.

[0070] The load power data is used to analyze the user load demand in the power supply range of the energy storage power station, mainly including: real-time load active power and load curve characteristics, etc. The real-time load active power (P_load) mainly represents the active power actually consumed by the user; the load curve characteristics represent the load fluctuation law of the peak and valley period.

[0071] The state of charge data is mainly based on the battery charge and discharge data to calculate the state of charge (SOC) of the battery pack. Common methods include: Ah-counting and open circuit voltage method (OCV). Ah-counting mainly calculates the remaining power by accumulating the product of charge and discharge current and time; the open circuit voltage method mainly calibrates the result according to the corresponding relationship between the voltage of the battery after standing and the SOC.

[0072] 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).

[0073] In step S102, the health coefficient corresponding to the energy storage power station is determined based on the state of charge data and the charge and discharge power data; wherein the health coefficient is used to represent the working state of the energy storage power station during the charging and discharging process.

[0074] Since the price difference is fixed, in order to ensure the income, the maximum discharge power needs to be met, that is, the battery is fully charged during the charging period and the battery is empty during the discharging period, so the parameters involved are the actual charge and discharge related data and the set charge and discharge related data. The actual charge and discharge related data and the set charge and discharge related data are obtained based on the state of charge data and the charge and discharge power data, so as to determine the health coefficient according to the difference between the actual scene and the set scene based on the charge and discharge related data.

[0075] In step S103, if the health coefficient meets the preset first threshold condition, the transformer saturation degree of the energy storage power station is determined based on the grid power data, and the load saturation degree of the energy storage power station is determined based on the load power data; wherein the transformer saturation degree is used to represent the working state of the transformer of the energy storage power station during the charging period; the load saturation degree is used to represent the working state of the load of the energy storage power station during the discharging period.

[0076] The first threshold condition is used to determine whether the energy storage power station is in an abnormal working state. When the health coefficient meets the preset first threshold condition, it indicates that the energy storage power station is in an abnormal working state, and the grid power data and the load power data are used to accurately determine the specific form of the abnormal working state. In the specific implementation process, the transformer saturation degree and the load saturation degree of the energy storage power station are determined based on the grid power data and the load power data, respectively, so as to determine the transformer load problem and the load load problem in the energy storage power station by using the transformer saturation degree and the load saturation degree.

[0077] In step S104, the transformer saturation degree and the load saturation degree are used to determine the abnormal working state corresponding to the energy storage power station.

[0078] The transformer saturation degree is used to determine whether the transformer load is saturated, and the load saturation degree is used to determine whether the load load is too small, so as to determine the specific abnormal working state. Specifically, the health coefficient in the method is used to determine whether the energy storage power station is abnormal, and the specific situation of the abnormal working state of the energy storage power station can be obtained through subsequent steps.

[0079] Optionally, the step S101 of obtaining the power data of the energy storage power station and determining the grid power data, the load power data, the power state data and the charge-discharge power data corresponding to the energy storage power station based on the power data comprises: Figure 2 As shown in the figure, it comprises:

[0080] Step S201, obtaining the transformer AC meter, battery manager, energy storage inverter and grid-connected cabinet AC meter arranged in the energy storage power station.

[0081] The transformer AC meter is arranged on the high-voltage side or the low-voltage side of the transformer, and is used to monitor the exchange of electric energy between the grid and the energy storage power station. The battery manager (BMS) is integrated in the battery cluster or battery pack, and is responsible for real-time monitoring of parameters such as voltage, current, temperature and SOC (state of charge) of the battery. The energy storage inverter (PCS) is used to connect the battery system and the AC grid, has a bidirectional power conversion function, and can record the charge-discharge power and the energy flow direction. The grid-connected cabinet AC meter is installed at the output end of the grid-connected cabinet, and is used to measure the actual power supplied by the energy storage power station to the load.

[0082] Each device interacts with data through Modbus RTU / TCP, CAN bus, RS485 or industrial Ethernet protocol, and the data acquisition frequency needs to be set synchronously (such as 1 second / second), to ensure the time consistency of parameter calculation.

[0083] Step S202, obtaining the grid power data corresponding to the energy storage power station based on the transformer AC meter.

[0084] During the data acquisition process of the transformer AC meter, the measurement parameters involved can be collected: three-phase voltage (Ua, Ub, Uc), three-phase current (Ia, Ib, Ic), frequency (f) and power factor (cosφ). Subsequently, three-phase balance verification can be performed, and the three-phase current unbalance degree (such as the maximum phase current deviation ≤ 10%) can be calculated; power factor verification can also be performed to ensure that the power factor on the grid side is above 0.95, avoiding reactive power loss.

[0085] The grid power data acquisition process involves the calculation of active power and reactive power, and the specific calculation process is not described again. The obtained power data can be filtered to improve data reliability, and specifically, sliding average or Kalman filtering algorithm can be used to eliminate transient fluctuations.

[0086] Step S203, based on the battery manager, the corresponding state of charge data of the battery in the energy storage power station is collected.

[0087] The battery manager data collection basic parameters can involve: single battery voltage, battery pack total voltage, charge and discharge current, battery temperature, etc. The collection process of the state of charge data can be realized by using the ampere-hour integration method, OCV-SOC curve calibration, etc. In specific scenarios, the health state also needs to be considered, which needs to be combined with the battery cycle number, charge and discharge depth and temperature history to estimate the battery capacity attenuation rate, so as to be merged into the state of charge data.

[0088] Step S204, based on the energy storage inverter, the corresponding charge and discharge power data of the energy storage power station is obtained.

[0089] The energy storage inverter data collection key parameters can involve: DC side voltage, DC side current, AC side power and working mode. The charge and discharge direction judgment is involved in the process of obtaining the charge and discharge power data. Specifically, for the charging mode, the DC side current flows to the battery, and the AC side power is negative; for the discharging mode, the DC side current flows out of the battery, and the AC side power is positive. In the process of power calculation, the DC side power is directly obtained according to the product of its corresponding voltage value and current value, and will not be described here.

[0090] Step S205, based on the grid-connected cabinet AC electric meter, the corresponding load power data of the energy storage power station is obtained.

[0091] The grid-connected cabinet AC electric meter data collection process involves measurements that can include: three-phase voltage, three-phase current, active power, reactive power and frequency. In actual scenarios, data synchronization needs to be considered, and by aligning with the power grid power data timestamp, the accuracy of power flow calculation is ensured.

[0092] In the process of obtaining load power data, 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 as peak); the load type judgment process involves industrial load (high fluctuation), commercial load (regularity), and residential load (obvious period), and can be combined with historical data and meteorological factors (such as temperature, holidays) to predict the load trend in the future time period, so as to obtain specific load power data.

[0093] Optionally, the 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, as shown in Figure 3 , includes:

[0094] Step S301, based on the state of charge data and the charge and discharge power data, 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 of the battery in the energy storage power station are determined;

[0095] Step S302, calculate the health coefficient according to the actual charging cut-off SOC value, the actual discharging cut-off SOC value, the set charging cut-off SOC value and the set discharging cut-off SOC value.

[0096] The health coefficient is calculated by the following formula:

[0097] I = (Ac-Ad) / (Sc-Sd);

[0098] Wherein, I is the health coefficient; Ac is the actual charging cut-off SOC value; Ad is the actual discharging cut-off SOC value; Sc is the set charging cut-off SOC value; Sd is the set discharging cut-off SOC value.

[0099] At this time, the health coefficient = 1 represents health, and less than 1 represents unhealth. The energy storage power station charges as much as possible during the valley time price period and discharges as much as possible during the peak time price period in the healthy state. If the health coefficient is less than 1, it needs to be considered whether the transformer load saturation (charging is not full), the small load (discharging is not empty) or the abnormal shutdown caused by equipment failure.

[0100] The judgment process of whether the transformer load is saturated is described below. Optionally, the transformer saturation of the energy storage power station is determined based on the grid power data, as shown in Figure 4 , including:

[0101] Step S401, determine the charging time period average load power, installed capacity, transformer capacity and transformer power factor corresponding to the energy storage power station based on the grid power data;

[0102] Step S402, calculate the transformer saturation according to the charging time period average load power, installed capacity, transformer capacity and transformer power factor.

[0103] The transformer saturation is calculated by the following formula:

[0104] TS = ((PTV+PI) / (TC*0.9*PF))*100%;

[0105] Wherein, TS is the transformer saturation; PTV is the charging time period average load power; PI is the installed capacity; TC is the transformer capacity; PF is the transformer power factor.

[0106] The judgment process of whether the load power is small is described below. Optionally, the load saturation of the energy storage power station is determined based on the load power data, as shown in Figure 5 , including;

[0107] Step S501, determine the discharging set power and discharging time period load average power corresponding to the energy storage power station based on the load power data;

[0108] Step S502, according to the discharge setting power and the discharge time period load average power, the load saturation is calculated.

[0109] The load saturation is calculated by the following formula:

[0110] LS=(PDS / PDV)*100%;

[0111] Wherein, LS is the load saturation; PDS is the discharge setting power; PDV is the discharge time period load average power.

[0112] The above-mentioned means realizes the accurate calculation of the transformer saturation and the load saturation, and on this basis, the transformer saturation and the load saturation are used to determine the abnormal working state of the energy storage power station. As shown in step S104, Figure 6 As shown, it includes:

[0113] Step S601, a second threshold condition corresponding to the transformer saturation and a third threshold condition corresponding to the load saturation are obtained;

[0114] Step S602, if the transformer saturation does not satisfy the corresponding second threshold condition, it is determined that the energy storage power station is in a transformer load saturation state;

[0115] Step S603, if the load saturation does not satisfy the corresponding third threshold condition, it is determined that the energy storage power station is in a load load abnormal state;

[0116] Step S604, the transformer load saturation state and the load load abnormal state are used to determine the abnormal working state of the energy storage power station.

[0117] After obtaining the transformer saturation and the load saturation, the second threshold condition corresponding thereto and the third threshold condition corresponding thereto are obtained respectively. If the transformer saturation does not satisfy 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 satisfy the corresponding third threshold condition, it is determined that the energy storage power station is in a load load abnormal state. For example, the second threshold condition is to judge 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 judge 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 load abnormal state.

[0118] Optionally, after the 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 Figure 7 The method further includes:

[0119] In step S701, if the transformer saturation degree satisfies the corresponding second threshold condition and the load saturation degree satisfies the corresponding third threshold condition, it is determined that the energy storage power station is in an abnormal shutdown state.

[0120] In step S702, the abnormal working state of the energy storage power station is determined based on the abnormal shutdown state.

[0121] If the value of the transformer saturation degree is greater than 1 and the value of the load saturation degree is also greater than 1, it indicates that the energy storage power station is in an abnormal shutdown state. By using the second threshold condition and the third threshold condition, the three abnormal working states of the energy storage power station can be accurately determined, and the method can be automatically determined, thereby solving the problem of low efficiency and easy omission caused by manual analysis.

[0122] Optionally, after the step of determining the health coefficient of the energy storage power station based on the power state data and the charging and discharging power data, the method further includes: if the health coefficient does not satisfy the first threshold condition, determining that the energy storage power station is in a normal working state. As shown in Figure 8 It is worth mentioning that the first threshold condition in the above embodiment is to determine whether the health coefficient is not equal to 1. If yes, it indicates that the energy storage power station is not healthy; if no, the health coefficient is equal to 1, indicating that the energy storage power station is in a healthy state. Figure 8

[0123] From the above-mentioned energy storage power station state monitoring method, the method calculates the health coefficient of the energy storage power station, and obtains the transformer saturation degree and the load saturation degree of the energy storage power station by using a specific calculation method, and then realizes real-time monitoring of the running state of the energy storage power station by using the above data, so as to realize real-time and accurate acquisition of the abnormal working state of the energy storage power station.

[0124] Corresponding to the energy storage power station state monitoring method provided in the foregoing embodiment, the embodiment of the present application provides an energy storage power station state monitoring system, as shown in Figure 9 The system includes:

[0125] The data acquisition unit 910 is configured to acquire power data of the energy storage power station, and determine grid power data, load power data, power state data, and charging and discharging power data of the energy storage power station based on the power data;

[0126] The health coefficient calculation unit 920 is configured to determine a health coefficient of the energy storage power station based on the power state data and the charging and discharging power data; wherein the health coefficient is used to represent the working state of the energy storage power station in the charging and discharging process;

[0127] ​The saturation calculation unit 930 is configured to, if the health coefficient satisfies the preset first threshold condition, determine a transformer saturation of the energy storage power station based on the grid power data, and determine a load saturation of the energy storage power station based on the load power data; wherein the transformer saturation is used to represent a transformer working state of the energy storage power station in a charging time period; and the load saturation is used to represent a load working state of the energy storage power station in a discharging time period.

[0128] The working state acquisition unit 940 is configured to determine an abnormal working state of the energy storage power station by using the transformer saturation and the load saturation.

[0129] It can be known from the energy storage power station state monitoring system mentioned in the above embodiment that the system can realize real-time monitoring of the running state of the energy storage power station by calculating the health coefficient of the energy storage power station, obtaining the transformer saturation and the load saturation of the energy storage power station by using a specific calculation method, and then using the above data, so as to obtain the abnormal working state of the energy storage power station in real time and accurately.

[0130] The energy storage power station state monitoring system provided in the embodiment has the same implementation principle and technical effects as the energy storage power station state monitoring method, and for brevity of description, the part of the system embodiment not mentioned can be referred to the corresponding content in the energy storage power station state monitoring method.

[0131] The embodiment also provides a server, and a structure diagram of the server is shown in Figure 10 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 realize the steps of the energy storage power station state monitoring method.

[0132] Figure 10 The server shown in the figure also includes a bus 103 and a communication interface 104, and the processor 101, the communication interface 104 and the memory 102 are connected through the bus 103.

[0133] The memory 102 can include a high-speed random access memory (RAM) and can also include a non-volatile memory, such as at least one disk memory. The bus 103 can be an ISA bus, a PCI bus or an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 10 Only one bidirectional arrow is used to represent, but it does not mean that there is only one bus or one type of bus.

[0134] The communication interface 104 is configured to connect with at least one user terminal and other network units through a network interface, and transmit the encapsulated IPv4 packet or the IPv4 packet to the user terminal through the network interface.

[0135] The processor 101 can be an integrated circuit chip with processing capability. In implementation process, each step of the above method can be completed by integrated logic circuit or software form instruction in the processor 101. The processor 101 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; or can be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component. Each method, step and logic block in the embodiments of the present disclosure can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in combination with the embodiments of the present disclosure can be directly embodied as a hardware code processor to execute, or be executed by a combination of hardware and software modules in the code processor. The software module can be located in a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, or other mature storage medium in the art. The storage medium is located in the memory 102, and the processor 101 reads the information in the memory 102 and combines the hardware to complete the steps of the method of the above embodiments.

[0136] The embodiment of the present application further provides a storage medium, and the storage medium stores a computer program. When the computer program is run by a processor, the steps of the energy storage station state monitoring method in the above embodiment are executed.

[0137] In several embodiments provided in the present application, it should be understood that the disclosed system, device, apparatus and method can be implemented in other manners. The above described system embodiments are merely illustrative. For example, the division of the units is only a logical function division. There can be another division manner for the actual implementation, or a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between different units, or the among different units, can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0138] The units described as separated components can or can not be physically separated, and the components displayed as units can or can not be physical units, i.e., can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purposes of the embodiments of the present application.

[0139] In addition, each functional unit in the various embodiments of the present application can be integrated in one processing unit, or each unit can exist physically as a separate unit, or two or more units can be integrated in one unit.

[0140] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a non-volatile computer readable storage medium executable by a processor. Based on this understanding, the technical solutions of the present application or the parts of the present application that essentially contribute to the prior art or the parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various program code storage media.

[0141] Finally, it should be noted that the above-described embodiments are merely specific embodiments of the present application, which are used to illustrate the technical solutions of the present application, but not to limit the same. The protection scope of the present application is not limited thereto. Although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that any person skilled in the art can still modify or easily think of changes to the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some of the technical features, within the technical scope disclosed by the present application. The modifications, changes or replacements do not cause the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for monitoring the status of an energy storage power station, characterized in that, The method includes: Acquire power data of the energy storage power station, and determine the grid power data, load power data, power status data and charge / discharge power data corresponding to the energy storage power station based on the power data; The health coefficient of the energy storage power station is determined based on the power status data and the charge / discharge power data; wherein, the health coefficient is used to characterize the working status of the energy storage power station during the charge / discharge process. If the health coefficient meets the preset first threshold condition, then 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 status of the energy storage power station during the charging period; the load saturation is used to characterize the load operating status of the energy storage power station during the discharging period. Determining the abnormal operating state of the energy storage power station using the transformer saturation and the load saturation includes: Obtain the second threshold condition corresponding to the transformer saturation and the third threshold condition corresponding to the load saturation; If the transformer saturation does not meet the corresponding second threshold condition, then the energy storage power station is determined to be in a transformer load saturation state. If the load saturation does not meet the corresponding third threshold condition, then the energy storage power station is determined to be in an abnormal load state. The abnormal operating state of the energy storage power station is determined based on the transformer load saturation state and the load abnormal state. 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 meets the corresponding second threshold condition and the load saturation meets the corresponding third threshold condition, then the energy storage power station is determined to be in an abnormal shutdown state. The abnormal operating state of the energy storage power station is determined based on the abnormal shutdown state.

2. The energy storage power station status monitoring method according to claim 1, characterized in that, The steps of acquiring power data from an energy storage power station and determining, based on the power data, grid power data, load power data, energy status data, and charge / discharge power data corresponding to the energy storage power station include: Acquire the AC power meters of the transformer, battery manager, energy storage inverter, and grid-connected cabinet installed in the energy storage power station; The power grid power data corresponding to the energy storage power station is obtained based on the transformer AC meter. The battery manager collects the power status data corresponding to the batteries in the energy storage power station. The charging and discharging power data corresponding to the energy storage power station are obtained 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-connected cabinet.

3. The energy storage power station status monitoring method according to claim 1, characterized in that, The steps for determining the health coefficient of the energy storage power station based on the power status data and the charge / discharge power data include: Based on the state of charge data and the charge / discharge power data, determine the actual charge cutoff SOC value, the actual discharge cutoff SOC value, the set charge cutoff SOC value, and the set discharge cutoff SOC value of the battery in the energy storage power station. The health coefficient is calculated based on the actual charging cutoff SOC value, the actual discharging cutoff SOC value, the set charging cutoff SOC value, and the set discharging cutoff SOC value; the health coefficient is calculated using the following formula: I = (Ac - Ad) / (Sc - Sd); Wherein, I is the health coefficient; Ac is the actual charging cutoff SOC value; Ad is the actual discharging cutoff SOC value; Sc is the set charging cutoff SOC value; and Sd is the set discharging cutoff 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: Based on the power grid data, the average load power, installed power, transformer capacity, and transformer power factor of the energy storage power station during the corresponding charging time period are determined. 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: Based on the load power data, determine the discharge setting power and average load power during the discharge time period corresponding to the energy storage power station; The load saturation is calculated based on the set discharge power and the average load power during the discharge time period; the load saturation is obtained by the following formula: LS = (PDS / PDV) * 100%; Wherein, LS is the load saturation; PDS is the discharge set power; and PDV is the average load power during the discharge time period.

6. The energy storage power station status monitoring method according to any one of claims 1 to 5, characterized in that, After determining the health coefficient of the energy storage power station based on the power status data and the charge / discharge power data, the method further includes: If the health coefficient does not meet the first threshold condition, then the energy storage power station is determined to be in normal working condition.

7. A status monitoring system for an energy storage power station, characterized in that, The system includes: The data acquisition unit is used to acquire the power data of the energy storage power station, and determine the grid power data, load power data, power status data and charge / discharge power data corresponding to the energy storage power station based on the power data. A health coefficient calculation unit is used to determine the health coefficient of the energy storage power station based on the power status data and the charge / discharge power data; wherein, the health coefficient is used to characterize the working status of the energy storage power station during the charge / discharge process; The saturation calculation unit is used to determine the transformer saturation of the energy storage power station based on the grid power data and the load saturation of the energy storage power station based on the load power data if the health coefficient meets a preset first threshold condition; wherein, the transformer saturation is used to characterize the transformer operating state of the energy storage power station during the charging period; and the load saturation is used to characterize the load operating state of the energy storage power station during the discharging period. The working status acquisition unit is used to determine the abnormal working status of the energy storage power station by using the transformer saturation and the load saturation. The operating status acquisition unit is further configured to: acquire 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, determine 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, determine that the energy storage power station is in a load abnormality state; and determine the abnormal operating status of the energy storage power station based on the transformer load saturation state and the load abnormality state. An abnormal operating state determination module is used to determine that the energy storage power station is in an abnormal shutdown state if the transformer saturation meets the corresponding second threshold condition and the load saturation meets the corresponding third threshold condition; and to determine the abnormal operating state of the energy storage power station based on the abnormal shutdown state.

8. A server, characterized in that, The device includes a processor and a memory, the memory storing computer-executable instructions that can be executed by the processor, the processor executing 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 6.

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