A Novel Intelligent Energy Storage Power Station Energy Storage Coordination Control Method and System

Abstract

The present invention discloses a novel intelligent energy storage power station energy storage coordination control method and system. The present invention relates to the technical field of energy storage power stations, and solves the problem that the energy storage power station does not perform reasonable power distribution according to the battery characteristics of each different storage battery. The present invention determines the characteristic interval by deeply analyzing the storage power parameters in different storage power states in historical data, and can accurately grasp the characteristics of the battery in different power stages; on this basis, power distribution is carried out. If the current storage power parameter is in the total interval, accurate power distribution can be directly realized to ensure that the single storage power parameter of each battery to be charged is in the characteristic interval and the total meets the requirements; if it is not in the total interval, according to the size relationship between the CD and the total interval, strategies of increasing or decreasing signals are respectively adopted, such as equalizing based on the ratio of the intermediate value of the characteristic interval or setting the single storage power parameter according to the maximum value, so as to realize the differential and accurate power distribution of the battery under different power states.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage power stations, and in particular to a novel intelligent energy storage power station energy storage coordination control method and system. Background Art

[0002] An energy storage power station is a facility that uses specific technologies and equipment to store and release electrical energy. It plays a vital role in the power system. When the power grid is in a low-load period or there is excess renewable energy generation, the monitoring and management system issues instructions, and the energy storage inverter converts the grid's AC power into DC power, and charges the energy storage unit according to the set charging strategy. The electrical energy is stored in the form of chemical energy (such as batteries) or electric field energy (such as supercapacitors). During this process, the monitoring system monitors the various parameters of the energy storage unit in real time to ensure that the charging process is safe and stable.

[0003] The application with publication number CN117060597A discloses a method and system for coordinated energy storage control of an energy storage power station, which relates to the technical field of coordinated energy storage control. The method comprises: obtaining basic information of N devices corresponding to N devices of a target energy storage power station; determining N first loss coefficients based on the usage time of the N devices and the maintenance information of the N devices; determining a loss deviation center coefficient; obtaining N loss deviations; obtaining N communication transmission distances; determining N first distance coefficients; serializing N sub-control units of a device control module in combination with N1 positive loss deviations and N2 negative loss deviations to obtain a sub-control unit sequence; and performing coordinated energy storage control on the target energy storage power station. The invention solves the technical problem in the prior art that the control of the equipment of the energy storage power station is not coordinated during energy storage operation, resulting in the control result failing to achieve the expected result, and achieves the technical effect of improving the reliability of coordinated energy storage control and improving control accuracy.

[0004] Regarding the synchronous power storage process of multiple storage batteries in an energy storage power station, the total input power of the power station is generally divided evenly into different storage batteries to complete the power storage process of multiple storage batteries. However, due to the differences in charging process and internal resistance of different storage batteries, some storage batteries may not be able to receive the corresponding storage power, resulting in power waste. The energy storage power station does not reasonably distribute power according to the battery characteristics of each different storage battery, resulting in the inability to guarantee the power storage effect of each storage battery. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a novel intelligent energy storage power station energy storage coordination control method and system, which solves the problem that the energy storage power station fails to reasonably distribute power according to the battery characteristics of each different storage battery.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A novel intelligent energy storage power station energy storage coordination control method, comprising the following steps:

[0007] Step 1: Confirm the electricity storage parameters associated with different storage batteries in the energy storage power station. Based on multiple groups of electricity storage parameters associated with a single group of storage batteries in different electricity storage states, confirm the characteristic intervals associated with the corresponding storage batteries in the corresponding electricity storage states. The determination method is as follows:

[0008] S11: From historical data, confirm the different electricity storage parameters associated with the corresponding storage batteries in different electricity storage states, and then extract several groups of electricity storage parameters associated with the corresponding electricity storage states from them. Denote the several groups of electricity storage parameters extracted as the characteristic parameter set. Each different electricity storage state corresponds to a different characteristic parameter set;

[0009] S12: Based on the characteristic parameter set associated with the corresponding electricity storage state, select the minimum electricity storage parameter and the maximum electricity storage parameter from the set, confirm a group of parameter intervals as the main interval, and confirm the parameter range F of the main interval, where F = maximum electricity storage parameter - minimum electricity storage parameter. Then, based on the total number G of electricity storage parameters in the characteristic parameter set, confirm the interval density M associated with the main interval, where M = F ÷ G;

[0010] Then, perform numerical changes on the main interval to confirm the change interval, and the change interval ∈ main interval. The change intervals associated with each numerical change process are all different. Different numerical change processes confirm different change intervals, and for the parameter range F i and the total number G of electricity storage parameters included in the change interval i are confirmed. Here, i represents different change intervals, and use: M i =F i ÷G i to confirm the interval density M associated with the corresponding change interval i ;

[0011] Based on the different interval densities M associated with different change intervals i , select the change interval corresponding to M i max as the characteristic interval, record the characteristic interval associated with the corresponding storage battery in the corresponding electricity storage state, and then record the different characteristic intervals associated with this storage battery in different electricity storage states in sequence;

[0012] Step 2: Confirm the electricity storage parameters associated with the current moment of the energy storage power station, and based on the characteristic intervals associated with different storage batteries in the corresponding electricity storage states, perform power distribution on multiple storage batteries. The specific sub-steps are as follows:

[0013] Calibrate the electricity storage parameters associated with the energy storage power station at the current moment as CD, then lock the storage batteries with insufficient power and label them as batteries to be charged. Confirm the current stored power of the batteries to be charged, and based on the current stored power, lock the associated characteristic intervals. Perform interval summation processing on the multiple groups of characteristic intervals associated with multiple groups of batteries to be charged, and lock the total interval. The minimum value of the total interval is the sum of the minimum values of multiple characteristic intervals, and the maximum value of the total interval is the sum of the maximum values of multiple characteristic intervals;

[0014] Identify whether the associated electricity storage parameter CD currently satisfies: CD ∈ total interval. If it satisfies, directly perform power distribution so that the single electricity storage parameters associated with the corresponding batteries to be charged all belong to the characteristic intervals and at the same time satisfy that the sum of multiple groups of single electricity storage parameters is equal to CD. Lock the allocated single electricity storage parameters and perform electricity storage control;

[0015] If CD does not satisfy: CD ∈ total interval, then identify whether CD belongs to: CD < total interval or CD > total interval;

[0016] If CD < total interval, directly generate an upward adjustment signal to increase the associated electricity storage parameter at the next moment based on CD, and determine the intermediate value of the corresponding characteristic interval of the corresponding battery to be charged. Label the determined intermediate value as Z k , where k represents different batteries to be charged, and perform ratio processing on the determined multiple groups of intermediate values Z k Confirm the ratio sequence, and evenly divide CD according to the confirmed ratio sequence to confirm the single electricity storage parameters associated with each battery to be charged and perform electricity storage control;

[0017] If CD > total interval, directly generate a downward adjustment signal to decrease the associated electricity storage parameter at the next moment based on CD, and determine the maximum value of the corresponding characteristic interval of the corresponding battery to be charged. Use the determined maximum value as the single electricity storage parameter associated with the corresponding battery to be charged and perform electricity storage control;

[0018] Step 3: Based on the temperature data of each energy storage battery in the energy storage power station, confirm whether there is an energy storage battery with abnormal temperature change, and synchronously calibrate the abnormal energy storage battery. By re-monitoring the temperature of the abnormal energy storage battery, evaluate whether the internal resistance of this abnormal energy storage battery is abnormal and perform signal display. The specific method is as follows:

[0019] Real-time monitor the temperature data associated with a single energy storage battery and label it as W q , where q represents different energy storage batteries, and perform variance processing on the multiple groups of W q confirmed by real-time monitoring. Confirm the temperature variance. If the temperature variance ≤ Y1, continue to monitor, where Y1 is a preset value. If the temperature variance > Y1, then the multiple groups of temperature data W qPerform mean processing, confirm the average temperature, and evaluate multiple groups of temperature data W q to check if there exists in: (W q - average temperature) > Y2, where Y2 is a preset value. If it exists, label the energy storage battery associated with the corresponding temperature data W q as an abnormal energy storage battery. If not, continue monitoring;

[0020] The specific method for evaluating whether this abnormal energy storage battery has abnormal internal resistance is as follows:

[0021] S33. For the labeled abnormal energy storage battery, define a monitoring period T, where T is a preset value. Record the initial temperature W1 of the abnormal energy storage battery at the start of the monitoring period T and the end temperature W2 of the abnormal energy storage battery at the end. Then, confirm several groups of current parameters generated by this abnormal energy storage battery during the monitoring period T, perform mean processing on the several groups of current parameters to confirm the average current I, and use Q1 = I 2 Rt to confirm the standard heat Q1 generated by this abnormal energy storage battery during this monitoring period T, where R is the preset internal resistance value of this abnormal energy storage battery and t is the total duration of the monitoring period T;

[0022] Then use Q2 = mc (W2 - W1) to confirm the relevant heat Q2 actually generated by this abnormal energy storage battery, where m is the preset battery mass and c is the preset specific heat capacity of the battery material;

[0023] S34. Identify whether the confirmed standard heat Q1 and relevant heat Q2 satisfy: |Q1 - Q2| > Y3, where Y3 is a preset value. If it is satisfied, label this abnormal energy storage battery as an abnormal internal resistance battery and directly generate and display an abnormal internal resistance signal. If not, do not perform any labeling.

[0024] Preferably, a new type of intelligent energy storage power station energy storage coordination control system includes:

[0025] An interval confirmation terminal that confirms the power storage parameters associated with different storage batteries in the energy storage power station. Based on multiple groups of power storage parameters associated with a single storage battery in different power storage states, confirm the characteristic interval associated with the corresponding storage battery in the corresponding power storage state;

[0026] A real-time power distribution terminal that confirms the power storage parameters associated with the energy storage power station at the current moment and distributes power to multiple storage batteries based on the characteristic intervals associated with different storage batteries in the corresponding power storage states;

[0027] Internal resistance abnormality evaluation terminal, based on the temperature data of each energy storage battery in the energy storage power station, confirms whether there is an energy storage battery with abnormal temperature change, and synchronously calibrates the abnormal energy storage battery. By re-monitoring the temperature of the abnormal energy storage battery, it evaluates whether the internal resistance of this abnormal energy storage battery is abnormal and displays the signal.

[0028] The present invention provides a new type of intelligent energy storage power station energy storage coordination control method and system. Compared with the prior art, it has the following beneficial effects:

[0029] Through in-depth analysis of the energy storage parameters in different stored electricity states in historical data, the present invention determines the characteristic intervals, and can accurately grasp the characteristics of the battery in different electricity stages; on this basis, power distribution is carried out. If the current energy storage parameters are in the total interval, accurate power distribution can be directly achieved to ensure that the single energy storage parameter of each battery to be charged is in the characteristic interval and the total meets the requirements, guaranteeing the charging effect; if not in the total interval, according to the size relationship between CD and the total interval, strategies of increasing or decreasing the signal are respectively adopted, and through reasonable calculation methods, such as equal division based on the ratio of the intermediate value of the characteristic interval or setting the single energy storage parameter according to the maximum value, differential and accurate power distribution of the battery in different electricity states is realized, effectively improving the overall charging efficiency and power utilization efficiency of the energy storage power station, avoiding overcharging or undercharging, and prolonging the service life of the battery;

[0030] Performing real-time variance and mean processing on the temperature data of the energy storage battery can sensitively capture the battery with abnormal temperature change; by setting the preset values of the temperature variance and (Wq - temperature mean), abnormal batteries can be accurately judged, avoiding misjudgment caused by individual low-temperature data and improving the accuracy of abnormal identification. For abnormal batteries, using parameters such as current and temperature within the monitoring period, combined with the comparison of the standard heat and the actual generated heat, accurately evaluates whether the internal resistance of the battery is abnormal; this process can timely detect problems such as sharp temperature change and slow charging progress during charging caused by the increase in internal resistance, and give early warnings to potential faulty batteries, facilitating operators to maintain or replace in time, ensuring the stable operation of the energy storage power station, reducing the risk of system shutdown caused by battery failure, and improving the reliability and safety of the energy storage power station. Description of the Drawings

[0031] Figure 1 It is a schematic flow chart of the method of the present invention;

[0032] Figure 2 It is a schematic diagram of the calibration of the abnormal energy storage battery of the present invention. Detailed Embodiment

[0033] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0034] First Embodiment

[0035] Please refer to Figure 1 , this application provides a new intelligent energy storage power station energy storage coordination control method, including the following steps:

[0036] Step 1: Confirm the electricity storage parameters associated with different storage batteries in the energy storage power station. Based on multiple groups of electricity storage parameters associated with a single group of storage batteries in different electricity storage states, confirm the characteristic intervals associated with the corresponding storage batteries in the corresponding electricity storage states. Specifically, different electricity storage values are all different during the actual electricity storage process. Therefore, the specific characteristic intervals of electricity storage can be confirmed based on historical parameters, and the corresponding characteristic intervals can be locked. Among them, the specific method for determining the characteristic intervals is as follows:

[0037] S11: From historical data, confirm the different electricity storage parameters associated with the corresponding storage batteries in different electricity storage states, and then extract several groups of electricity storage parameters associated with the corresponding electricity storage states from them (the electricity storage parameters are electricity storage values, and the electricity storage values associated with the corresponding batteries in different electricity states are all different. Each battery has three different electricity storage stages during electricity storage, and the electricity storage characteristics associated with each electricity storage stage are not the same. Therefore, the corresponding characteristic intervals can be determined based on the corresponding electricity storage parameters). Denote the several groups of electricity storage parameters extracted as the characteristic parameter set, and each different electricity storage state corresponds to a different characteristic parameter set;

[0038] S12: Based on the characteristic parameter set associated with the corresponding electricity storage state, select the minimum electricity storage parameter and the maximum electricity storage parameter from the set, confirm a set of parameter intervals as the main interval, and confirm the parameter range F of the main interval, where F = maximum electricity storage parameter - minimum electricity storage parameter. Then, based on the total number G of electricity storage parameters in the characteristic parameter set, confirm the interval density M associated with the main interval, where M = F ÷ G;

[0039] Then, perform numerical changes on the main interval to confirm the change intervals, and the change intervals ∈ main interval. Each change interval associated with each numerical change process is different. Different numerical change processes confirm different change intervals, and for the parameter range F of each change interval i and the total number G of electricity storage parameters included in the change interval iFor confirmation, where i represents different change intervals, use: M i =F i ÷G i Confirm the interval density M associated with the corresponding change interval i ;

[0040] Based on the different interval densities M associated with different change intervals i (where M here i simultaneously includes the interval density M associated with the main interval), select the change interval corresponding to M i max as the characteristic interval, record the characteristic interval associated with the corresponding storage battery under the corresponding stored power state, and then record the different characteristic intervals associated with this storage battery under different stored power states in sequence;

[0041] Specifically, when a set of storage parameters associated with a set of storage batteries A under the corresponding stored power state is ten groups, then based on the minimum and maximum values associated with the ten groups of storage parameters, confirm the first set of main intervals, and based on the interval range of the main intervals and the total number of parameters 10, confirm the interval density of the main intervals;

[0042] If its main interval is calibrated as [1, 10], then the subsequent change intervals can be adjusted to: [1, 9], [1, 8], ……, [1, 2], [2, 9], [2, 8], etc. After the change intervals are obtained, they still belong to the corresponding main interval. Different change intervals correspond to different interval densities. The larger the interval density, the stronger the corresponding interval characteristics. Thus, the characteristic interval associated with the specific stored power state can be locked and recorded, which is convenient for subsequent parameter verification, adjustment, and analysis;

[0043] Step 2: Confirm the electricity storage parameters associated with the current moment of the energy storage power station, and based on the characteristic intervals associated with different storage batteries under the corresponding stored power states, perform power distribution for multiple storage batteries and ensure the charging status of each storage battery. The specific sub-steps for power distribution are as follows:

[0044] S21: Calibrate the electricity storage parameters associated with the energy storage power station at the current moment as CD, then lock the storage batteries with insufficient power, label them as batteries to be charged, confirm the stored power of the batteries to be charged at the current moment, and based on the current stored power, lock the associated characteristic intervals. Perform interval summation processing on the multiple groups of characteristic intervals associated with multiple batteries to be charged, and lock the total interval. The minimum value of the total interval is the sum of the minimum values of multiple characteristic intervals, and the maximum value of the total interval is the sum of the maximum values of multiple characteristic intervals;

[0045] Identify whether the currently associated electricity storage parameter CD meets the condition: CD ∈ total range. If it meets the condition, directly perform electricity distribution so that the single electricity storage parameters associated with the corresponding batteries to be charged all belong to the characteristic range, and at the same time satisfy that the sum value of multiple groups of single electricity storage parameters is equal to CD. Lock the allocated single electricity storage parameters and perform electricity storage control to ensure that each battery to be charged can store electricity under the determined single electricity storage parameter state, so that each battery to be charged can achieve a better charging effect;

[0046] If CD does not meet the condition: CD ∈ total range, then identify whether CD belongs to: CD < total range or CD > total range. If CD < total range, directly generate an upward adjustment signal to increase the associated electricity storage parameter at the next moment based on CD, and determine the intermediate value of the corresponding characteristic range of the battery to be charged, and calibrate the determined intermediate value as Z k , where k represents different batteries to be charged, and perform ratio processing on the determined multiple groups of intermediate values Z k to confirm the ratio sequence, and evenly divide CD according to the confirmed ratio sequence to confirm the single electricity storage parameters associated with each battery to be charged and perform electricity storage control. Specifically, assume the confirmed ratio sequence is 1:1.2:1.5, after adjustment it is 10:12:15, and after confirmation, the corresponding electricity storage parameter CD is 74. Then after equal division processing, the single electricity storage parameters associated with each different battery to be charged are: 20, 24, and 30. Therefore, each battery to be charged can perform specific electricity storage control according to the associated single electricity storage parameter to complete the electricity storage process of the corresponding battery to be charged;

[0047] If CD > total range, directly generate a downward adjustment signal to decrease the associated electricity storage parameter at the next moment based on CD, and determine the maximum value of the corresponding characteristic range of the battery to be charged. Use the determined maximum value as the single electricity storage parameter associated with the corresponding battery to be charged and perform electricity storage control. Subsequently, the electricity parameters for real-time charging of the energy storage power station are decreased in real-time until the corresponding downward adjustment signal no longer exists, and then stop the corresponding processing process to achieve a better control effect and simultaneously ensure the charging effect of each battery to be charged;

[0048] Step 3: Based on the temperature data of each energy storage battery in the energy storage power station, confirm whether there is an energy storage battery with abnormal temperature change, and simultaneously calibrate the abnormal energy storage battery. By re-monitoring the temperature of the abnormal energy storage battery, evaluate whether the internal resistance of this abnormal energy storage battery is abnormal and perform signal display. The specific method for calibrating the abnormal energy storage battery is:

[0049] S31. Combine Figure 2 to monitor the temperature data associated with a single energy storage battery in real-time and calibrate it as W q , where q represents different energy storage batteries, and perform real-time monitoring on multiple groups of Wq Perform variance processing to confirm the temperature variance. If the temperature variance ≤ Y1, continue monitoring, where Y1 is a preset value, and its specific value is determined by the operator according to experience. If the temperature variance > Y1, then the multiple groups of temperature data W being monitored q Perform mean processing to confirm the temperature mean and evaluate the multiple groups of temperature data W q to check if there exists: (W q - temperature mean) > Y2, where Y2 is a preset value, and its specific value is determined by the operator according to experience. If it exists, then mark the energy storage battery associated with the corresponding temperature data W q as an abnormal energy storage battery. If it does not exist, continue monitoring. Specifically, when a certain temperature data is too low, it will also cause the variance of the corresponding temperature data to exceed the standard, but the situation where the abnormal energy storage battery cannot be identified. Therefore, such a situation belongs to the case where (W q - temperature mean) > Y2 does not exist, and then continue the relevant monitoring without performing relevant processing;

[0050] The specific method for evaluating whether this abnormal energy storage battery has abnormal internal resistance is as follows:

[0051] S33. For the marked abnormal energy storage battery, define a set of monitoring periods T, where T is a preset value, generally taking 1 min. Record the initial temperature W1 of the abnormal energy storage battery at the start of the monitoring period T and the end temperature W2 of the abnormal energy storage battery at the end. Then confirm several groups of current parameters generated by this abnormal energy storage battery during the monitoring period T, perform mean processing on the several groups of current parameters to confirm the mean current I, and use Q1 = I 2 Rt to confirm the standard heat Q1 generated by this abnormal energy storage battery during this monitoring period T, where R is the preset internal resistance value of this abnormal energy storage battery, and t is the total duration of the monitoring period T;

[0052] Then use Q2 = mc (W2 - W1) to confirm the relevant heat Q2 actually generated by this abnormal energy storage battery, where m is the preset battery mass and c is the preset specific heat capacity of the battery material;

[0053] S34. Identify whether the confirmed standard heat Q1 and relevant heat Q2 satisfy: |Q1 - Q2| > Y3, where Y3 is a preset value, and its specific value is determined by the operator according to experience. If it is satisfied, then mark this abnormal energy storage battery as an abnormal internal resistance battery and directly generate an abnormal internal resistance signal for display. If it is not satisfied, no marking is performed;

[0054] Specifically, with the increase of years of use, the internal resistance of the battery will undergo relevant changes. When the internal resistance value increases, the temperature of the corresponding battery will change too drastically during charging, resulting in the corresponding battery The use effect becomes worse and cannot achieve better use and processing effects. At the same time, when its internal resistance increases, it will cause the charging progress to be slow. Therefore, for such batteries with excessive internal resistance, they need to be processed in real time and the signals displayed in real time to facilitate external operators to fully understand the use status of the energy storage battery.

[0055] Second embodiment

[0056] A new type of intelligent energy storage power station energy storage coordination control system, including:

[0057] The interval confirmation end confirms the power storage parameters associated with different storage batteries in the energy storage power station, and confirms the characteristic interval associated with the corresponding storage battery under the corresponding storage power state based on multiple groups of storage parameters associated with a single group of storage batteries under different storage power states;

[0058] The real-time power distribution terminal confirms the power storage parameters associated with the energy storage power station at the current moment, and distributes power to multiple storage batteries based on the characteristic intervals associated with different storage batteries under the corresponding storage power states;

[0059] The internal resistance abnormality assessment end, based on the temperature data of each energy storage battery in the energy storage power station, confirms whether there are energy storage batteries with abnormal temperature changes, and simultaneously calibrates the abnormal energy storage batteries. By re-monitoring the temperature of the abnormal energy storage batteries, it is assessed whether the abnormal energy storage batteries have abnormal internal resistance and a signal is displayed.

[0060] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0061] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A novel intelligent energy storage power station energy storage coordination control method, characterized in that: The following steps are involved: Step 1: confirm the power storage parameters associated with different storage batteries in the energy storage power station, and confirm the characteristic interval associated with the corresponding storage battery under the corresponding storage power state based on multiple groups of power storage parameters associated with a single group of storage batteries under different storage power states; Step 2: Confirm the power storage parameters associated with the energy storage power station at the current moment, and distribute power to multiple storage batteries based on the characteristic intervals associated with different storage batteries under the corresponding storage power states. The specific sub-steps are: The power storage parameter associated with the energy storage power station at the current moment is calibrated as CD, and then the storage battery that is not fully charged is locked and calibrated as a battery to be charged, and the current storage power of the battery to be charged is confirmed, and the associated characteristic interval is locked based on the current storage power, and multiple groups of characteristic intervals associated with multiple groups of batteries to be charged are summed up, and the sum interval is locked, and the minimum value of the sum interval is the sum of the minimum values ​​of multiple characteristic intervals, and the maximum value of the sum interval is the sum of the maximum values ​​of multiple characteristic intervals; Identify whether the currently associated power storage parameter CD satisfies: CD∈sum interval. If so, directly distribute the electric energy so that the corresponding single power storage parameters associated with the battery to be charged all belong to the characteristic interval and the sum of multiple groups of single power storage parameters is equal to CD. Lock the allocated single power storage parameters and perform power storage control. Step 3: Based on the temperature data of each energy storage battery in the energy storage power station, confirm whether there are energy storage batteries with abnormal temperature changes, and simultaneously calibrate the abnormal energy storage batteries. By re-monitoring the temperature of the abnormal energy storage batteries, assess whether the abnormal energy storage batteries have abnormal internal resistance and display signals.

2. A novel intelligent energy storage power station energy storage coordination control method according to claim 1, characterized in that: In the step 1, the characteristic intervals associated with different storage power states of the storage battery are determined as follows: S11, confirming different power storage parameters associated with the corresponding storage battery under different power storage states from the historical data, and then extracting several groups of power storage parameters associated with the corresponding power storage states, recording the extracted several groups of power storage parameters as characteristic parameter sets, and each different power storage state corresponds to a different characteristic parameter set; S12, based on the characteristic parameter set associated with the corresponding power storage state, a minimum power storage parameter and a maximum power storage parameter are selected from the set, a set of parameter intervals are determined as the main interval, and a parameter range F of the main interval is determined, where F=maximum power storage parameter-minimum power storage parameter, and then based on the total number G of power storage parameters in the characteristic parameter set, an interval density M associated with the main interval is determined, where M=F÷G; Then, the value of the main interval is changed, and the change interval is confirmed, and the change interval ∈ the main interval. The change interval associated with each value change process is different. Different value change processes confirm different change intervals, and the parameter range F of each change interval is i And the total number of storage parameters included in the variation interval G i Confirm, where i represents different change intervals, using: M i =F i ÷G i Confirm the interval density M associated with the corresponding change interval i ; Based on the different interval densities M associated with different change intervals i , select M i The variation interval corresponding to max is taken as the characteristic interval, and the characteristic interval associated with the corresponding storage battery in the corresponding storage power state is recorded, and then the different characteristic intervals associated with the storage battery in different storage power states are recorded in turn.

3. A new type of intelligent energy storage power station energy storage coordination control method according to claim 1, characterized in that: If CD does not satisfy: CD∈sum interval, then identify CD as belonging to: CD<sum interval or CD>sum interval; If CD is less than the total interval, an upward adjustment signal is directly generated, so that the storage parameter associated with the next moment is adjusted upward based on CD, and the middle value of the corresponding characteristic interval of the corresponding battery to be charged is determined, and the determined middle value is calibrated as Z k , where k represents different batteries to be charged, and the determined multiple sets of intermediate values ​​Z k Perform ratio processing, confirm the ratio sequence, and evenly divide the CD according to the confirmed ratio sequence, confirm the single power storage parameter associated with each battery to be charged and perform power storage control.

4. A new type of intelligent energy storage power station energy storage coordination control method according to claim 3, characterized in that: If CD>total interval, a downward adjustment signal is directly generated to reduce the associated power storage parameter at the next moment based on CD, and the maximum value of the corresponding characteristic interval of the corresponding battery to be charged is determined. The determined maximum value is used as the single power storage parameter associated with the corresponding battery to be charged and power storage control is performed.

5. A novel intelligent energy storage power station energy storage coordination control method according to claim 1, characterized in that: In step 3, the specific method of calibrating the abnormal energy storage battery is: The temperature data associated with a single energy storage battery is monitored in real time and calibrated as W q , where q represents different energy storage batteries, and multiple groups of W monitored in real time q Perform variance processing to confirm the temperature variance. If the temperature variance is ≤ Y1, continue monitoring, where Y1 is the preset value. If the temperature variance is > Y1, the monitored multiple sets of temperature data W q Perform mean processing, confirm the temperature mean, and evaluate multiple sets of temperature data W q Does it exist in: (W q -temperature mean)>Y2, where Y2 is the preset value. If it exists, the corresponding temperature data W q The associated energy storage battery is marked as an abnormal energy storage battery, and if it does not exist, it is continuously monitored.

6. A novel intelligent energy storage power station energy storage coordination control method according to claim 5, characterized in that: In step 3, the specific method for evaluating whether the abnormal energy storage battery has abnormal internal resistance is as follows: S33. For the abnormal energy storage battery calibrated, define a set of monitoring periods T, where T is a preset value, record the initial temperature W1 of the abnormal energy storage battery at the beginning of the monitoring period T and the terminal temperature W2 of the abnormal energy storage battery at the end, and then confirm several sets of current parameters generated by the abnormal energy storage battery within the monitoring period T, average the several sets of current parameters, confirm the average current I, and use Q1=I 2 Rt confirms the standard heat Q1 generated by the abnormal energy storage battery during the monitoring period T, where R is the preset internal resistance value of the abnormal energy storage battery, and t is the total duration of the monitoring period T; Then Q2=mc(W2-W1) is used to confirm the relevant heat Q2 actually generated by this abnormal energy storage battery, where m is the preset battery mass and c is the preset battery specific heat capacity of the battery material; S34. Identify whether the confirmed standard heat Q1 and related heat Q2 satisfy: |Q1-Q2|>Y3, where Y3 is a preset value. If so, the abnormal energy storage battery is calibrated as an abnormal internal resistance battery, and an abnormal internal resistance signal is directly generated for display. If not, no calibration is performed.

7. A novel intelligent energy storage power station energy storage coordination control system, the control system operates according to a novel intelligent energy storage power station energy storage coordination control method according to any one of claims 1 to 6, characterized in that: include: The interval confirmation end confirms the power storage parameters associated with different storage batteries in the energy storage power station, and confirms the characteristic interval associated with the corresponding storage battery under the corresponding storage power state based on multiple groups of storage parameters associated with a single group of storage batteries under different storage power states; The real-time power distribution terminal confirms the power storage parameters associated with the energy storage power station at the current moment, and distributes power to multiple storage batteries based on the characteristic intervals associated with different storage batteries under the corresponding storage power states; The internal resistance abnormality assessment end, based on the temperature data of each energy storage battery in the energy storage power station, confirms whether there are energy storage batteries with abnormal temperature changes, and simultaneously calibrates the abnormal energy storage batteries. By re-monitoring the temperature of the abnormal energy storage batteries, it is assessed whether the abnormal energy storage batteries have abnormal internal resistance and a signal is displayed.

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