Electrochemical energy storage power station dispatching management system and dispatching adaptation method

Abstract

The invention discloses an electrochemical energy storage power station dispatching management system and a dispatching adaptation method, relates to the technical field of power station dispatching management, and solves the problem of lack of systematic analysis and utilization of historical data and real-time operation parameters of a power station. According to the method, whether scheduling is needed or not can be rapidly judged through real-time calculation and comparison based on SOC and physical constraint conditions in a normal time period, scheduling signals are generated in time under the condition that the SOC and the physical constraint conditions are close to the upper limit and the lower limit of the constraint, and the charging and discharging power is adjusted; safe operation of the battery is ensured; in the peak period, segmentation is performed according to four stages of power load rising, peak, platform and falling, and the discharge power is calculated by combining the SOC state of the battery in each stage, so that stepped accurate scheduling is realized, the peak power demand can be met, the battery capacity can be reasonably utilized, and the defect that the traditional scheduling lacks dynamic adjustment is made up.

Description

Technical Field

[0001] The present invention relates to the technical field of power station dispatching management, and in particular to an electrochemical energy storage power station dispatching operation and management system and a dispatching adaptation method. Background Art

[0002] With the rapid development of renewable energy power generation and the increasing demand for power system flexibility, the role of electrochemical energy storage power stations in the power system is becoming increasingly critical.

[0003] Patent application publication number CN110365114A discloses a comprehensive management system for energy storage power stations based on multi-module integration. The management system includes a dispatching master station, a telecontrol workstation, an energy storage monitoring backend, and an energy storage grid-connected device. The telecontrol workstation is connected to the energy storage monitoring backend and can exchange information with the backend. The energy storage monitoring backend integrates an EMS module, an AGC module, an AVC module, and a conventional monitoring module. The energy storage grid-connected device is used to receive and respond to control commands processed by the energy storage monitoring backend and upload the execution results to the energy storage monitoring platform and telecontrol workstation.

[0004] Existing energy storage power station scheduling and operation management typically employs a relatively crude scheduling model or relies on manual experience to divide time periods and control charging and discharging. This lacks systematic analysis and utilization of historical power station data and real-time operating parameters. Furthermore, dynamic scheduling cannot be accurately tailored to load characteristics and the status of energy storage batteries during different power consumption periods. This results in low energy storage station operation efficiency, hindering its full potential in shaving peak loads, ensuring grid stability, and improving economic benefits. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides an electrochemical energy storage power station scheduling and operation management system and a scheduling adaptation method, which solves the problem of lack of systematic analysis and utilization of power station historical data and real-time operating parameters, and the inability to accurately perform dynamic scheduling based on power load characteristics and energy storage battery status.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an electrochemical energy storage power station dispatching and operation management system, comprising:

[0007] The energy storage power station information analysis unit is used to classify the different working periods of the energy storage power station according to the power station information transmitted by the power station information collection unit, classify the different periods according to the power consumption to obtain normal periods and peak periods, generate corresponding information, and transmit the two separately;

[0008] The normal period scheduling analysis unit is used to analyze the acquired normal period information, predict the battery charge state according to the formula, and judge it against the physical constraints. If the normal period information is satisfied, normal supervision information is generated; otherwise, a scheduling optimization signal is generated.

[0009] Analyze the scheduling optimization signal, calculate the difference between the predicted battery charge state and the upper and lower limits of the physical constraints, and compare the difference between the two to generate upper and lower scheduling signals and lower limit scheduling signals. At the same time, adjust the charging and discharging power based on the safety threshold as the standard to generate scheduling information, and then transmit it to the scheduling management information output unit;

[0010] The peak period scheduling analysis unit is used to analyze the peak period information obtained, classify it into different levels based on the power load conditions during the peak period, calculate the corresponding discharge power according to the battery charge corresponding to the different levels, and generate scheduling information based on it as a standard, which is then transmitted to the scheduling management information output unit.

[0011] As a further solution of the present invention, it also includes a power station information collection unit and a dispatch management information output unit;

[0012] A power station information collection unit is used to collect power station information of the energy storage power station, wherein the power station information includes operating parameters and historical data, and transmit it to the energy storage power station information analysis unit;

[0013] The scheduling management information output unit is used to display the acquired normal supervision information and scheduling information to the corresponding management personnel.

[0014] As a further solution of the present invention, the energy storage power station information analysis unit classifies different time periods according to power consumption to obtain normal time periods and peak time periods, and generates corresponding information in the following specific manner:

[0015] Extract data from the power station's historical data based on a time period of T, split it into unit time granularity, obtain the power consumption for each unit time period, and compare it with the preset value set by the operator;

[0016] If the value is greater than the preset value, it is marked as a high-power consumption period, and if it is less than the preset value, it is marked as a normal power consumption period. After completing the classification of all unit time periods, the peak period and normal period information are summarized and generated respectively, and then transmitted to the peak period and normal period scheduling analysis units accordingly.

[0017] As a further solution of the present invention, the normal period scheduling analysis unit analyzes the acquired normal period information in the following specific manner:

[0018] Get the normal time period corresponding to the time period T, and at the same time get the battery charge state SOC of the energy storage power station corresponding to time t t , and the corresponding battery charge and discharge power Pt , then according to the formula Calculate the battery state of charge SOC at time t+1 t+1 , and η represents the charge and discharge efficiency of the battery, Δt refers to the time interval, E rated Indicates the rated capacity of the battery;

[0019] The battery state of charge SOC t+1 Compare with the upper and lower limits of the corresponding physical constraints to determine the specific SOC min ≤SOC t+1 ≤SOC max ,If the above physical constraints are met, normal supervision information is generated, otherwise a scheduling optimization signal is generated.

[0020] As a further solution of the present invention, the specific manner in which the normal period scheduling analysis unit analyzes the scheduling optimization signal is as follows:

[0021] Calculate battery state of charge SOC t+1 With SOC min and SOC max The difference between the lower limit and the upper limit is determined, and the relationship between the battery charge state and the upper and lower limits is determined. If the difference between the lower limit is greater than the difference between the upper limit, an upper limit scheduling signal is generated. Conversely, if the difference between the lower limit is less than the difference between the upper limit, a lower limit scheduling signal is generated.

[0022] As a further solution of the present invention, the normal period scheduling analysis unit adjusts the charging and discharging power based on the safety threshold, and generates scheduling information in the following specific manner:

[0023] Analyze the upper limit dispatch signal to obtain the battery charging power corresponding to the energy storage power station, adjust the battery charging power based on the safety threshold, and generate dispatch information;

[0024] The lower limit dispatch signal is analyzed to obtain the battery discharge power corresponding to the energy storage power station, and the battery discharge power is adjusted based on the safety threshold to generate dispatch information.

[0025] As a further solution of the present invention, the peak period analysis unit analyzes the acquired peak period information in the following specific manner:

[0026] According to the changing trend of power load during peak hours, it is divided into four steps. The first step is the rising period, the second step is the peak period, the third step is the peak plateau period, and the fourth step is the falling period, which are marked as i=1, 2, 3, and 4 respectively. At the same time, the SOC status of the energy storage battery in each step is obtained and dynamically adjusted according to the battery charge state.

[0027] As a further solution of the present invention, the peak period analysis unit performs dynamic adjustment according to the battery charge state in the following specific manner:

[0028] According to the formula Calculate the discharge power P corresponding to different steps i dischaerge，i , where Δt i is the step duration corresponding to step i, E capacity is the capacity of the energy storage power station, SOC star，t is the battery state of charge at the beginning of step i, SOC end，t is the battery charge state at the end of step i, and the calculated discharge power P dischaerge，i Dispatch energy storage power stations according to standards and generate dispatch information.

[0029] The electrochemical energy storage power station scheduling adaptation method specifically includes the following steps:

[0030] Step 1: Collect historical data and operating parameters of the energy storage power station, and classify different time periods according to power consumption to obtain normal time periods and peak time periods;

[0031] Step 2: Schedule the normal period, predict the battery charge state according to the formula, and judge it against the physical constraints. If it meets the requirements, generate normal supervision information, otherwise generate a scheduling optimization signal;

[0032] Step 3: Analyze the scheduling optimization signal, calculate the difference between the predicted battery state of charge and the upper and lower limits of the physical constraints, and compare the difference between the two to generate upper and lower scheduling signals and lower limit scheduling signals. At the same time, adjust the charging and discharging power based on the safety threshold to generate scheduling information;

[0033] Step 4: Perform scheduling processing during peak hours, classify the electricity load into different levels based on the peak hours, calculate the corresponding discharge power according to the battery charge corresponding to the different levels, and generate scheduling information based on this standard.

[0034] The present invention provides an electrochemical energy storage power station dispatching and operation management system and a dispatching adaptation method. Compared with the existing technology, it has the following advantages:

[0035] The present invention performs multi-level and refined processing on the historical data of energy storage power stations, from periodic data to unit historical data, and then to unit time period electricity consumption records. Combined with the preset value comparison method, it can accurately divide peak periods and normal periods, providing a reliable basis for subsequent targeted scheduling. Compared with traditional empirical division methods, this method improves the scientificity and accuracy of time period classification.

[0036] During normal periods, the present invention can quickly determine whether scheduling is needed based on real-time calculation and comparison of SOC and physical constraints. It can timely generate scheduling signals and adjust the charging and discharging power for situations approaching the upper and lower limits of the constraints to ensure safe operation of the battery. During peak periods, the power load is divided into four stages: rising, peak, platform, and falling. The discharge power is calculated in combination with the battery SOC status at each stage to achieve step-by-step precise scheduling, which can not only meet peak power demand but also reasonably utilize battery capacity, thereby improving the operating efficiency and economic benefits of the energy storage power station in different periods and making up for the defect of traditional scheduling that lacks dynamic adjustment. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a block diagram of the system principle of the present invention;

[0038] Figure 2 It is a diagram of the steps of the present invention. DETAILED DESCRIPTION

[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0040] Example 1

[0041] See also Figure 1 The present application provides an electrochemical energy storage power station dispatching and operation management system, including a power station information acquisition unit, an energy storage power station information analysis unit, a normal period dispatching and analysis unit, a peak period dispatching and analysis unit and a dispatching management information output unit, and combines Figure 1 It can be known that the functional units are electrically connected in a unidirectional manner.

[0042] The power station information collection unit is used to collect power station information of the energy storage power station and transmit it to the energy storage power station information analysis unit. The power station information here specifically includes historical data and operating parameters of the energy storage power station.

[0043] The energy storage power station information analysis unit is used to classify the operating time periods of the energy storage power station according to the acquired power station information and generate time period classification information, and the time period classification information includes peak time period information and normal time period information. The specific classification processing method is as follows:

[0044] First, obtain historical data from the power station information system. Take time T as a cycle (for example, T is set to one month, that is, statistics are collected based on natural months), extract the corresponding periodic historical data, and then further refine the periodic historical data to obtain the unit historical data. The unit historical data here can be set according to actual needs. For example, one day is used as a unit of historical data (that is, the data of each day is an independent unit), and for each unit of historical data, obtain its corresponding electricity consumption record. The electricity consumption record records in detail the electricity consumption at each moment in the unit time;

[0045] The electricity consumption records in each unit's historical data are divided into preset unit time periods (e.g., one hour as a unit time period). The electricity consumption corresponding to each unit time period is then obtained and compared with the preset value set by the operator. For example, the operator sets the preset value to 50 kWh per hour (determined based on the scale of the power station, historical electricity consumption, etc.);

[0046] If the power consumption in a certain unit time period is greater than 50 kWh, the period is marked as a high power consumption period; if it is less than 50 kWh, it is marked as a normal power consumption period. According to the above method, all unit time periods (24-hour periods) within a unit time (such as a day) are classified;

[0047] Classify all time periods marked as high power consumption periods to generate peak period information; classify all time periods marked as normal power consumption periods to generate normal period information. Finally, transmit the peak period information to the peak period scheduling analysis unit for targeted scheduling analysis and formulation of reasonable response strategies; transmit the normal period information to the normal period scheduling analysis unit for corresponding scheduling analysis.

[0048] Assume that we acquire historical data on a monthly basis (T = one month). Using one day as the unit of historical data, we obtain daily electricity consumption records. The day is divided into hourly time periods. The operator sets a preset value of 40 kWh per hour. On a particular day, the electricity consumption during the 6:00 PM to 7:00 PM period is 45 kWh, exceeding the preset value of 40 kWh, and this period is marked as a high-consumption period. Meanwhile, the electricity consumption during the 10:00 AM to 11:00 AM period is 30 kWh, less than the preset value, and is marked as a normal-consumption period. After this classification is performed on all 24 time periods for that day, all high-consumption periods are classified as peak-consumption periods and transmitted to the peak-consumption scheduling and analysis unit; normal-consumption periods are classified as normal-consumption periods and transmitted to the normal-consumption scheduling and analysis unit.

[0049] Normal period scheduling analysis unit, which is used to manage the energy storage power station scheduling based on the acquired normal period information. The specific scheduling management method is as follows:

[0050] Get the normal time period corresponding to the time period T, and at the same time get the battery charge state SOC of the energy storage power station corresponding to time t t , and the corresponding battery charge and discharge power P t , then according to the formula Calculate the battery state of charge SOC at time t+1 t+1 , and in the above formula, η represents the charge and discharge efficiency of the battery, Δt refers to the time interval, that is, the time from time t to time t+1, E rated Indicates the rated capacity of the battery, and the battery state of charge SOC t+1 Compare with the corresponding physical constraints to determine the SOC min ≤SOC t+1 ≤SOC max , and the SOC here min and SOC max and are the lower and upper limits of the battery state of charge, respectively, such as SOC min =0.2, i.e. 20%, SOC max =0.8, i.e. 80%. If the above physical constraints are met, it means that the energy storage power station does not need to be dispatched and managed, and normal supervision information is generated. On the contrary, if the above physical constraints are not met, a dispatch optimization signal is generated.

[0051] Then analyze the generated scheduling optimization signal and calculate the battery state of charge SOC t+1 With SOC min and SOC max The difference between the battery state of charge and the upper and lower limits can be determined. If SOC t+1 With SOC min The difference is greater than SOC t+1 With SOC max If the SOC is close to the upper limit of the physical constraint, an upper limit scheduling signal will be generated. t+1 With SOC min The difference is less than SOC t+1 With SOC max The difference between indicates that the battery state of charge is close to the lower limit of the physical constraint, and a lower limit scheduling signal is generated;

[0052] Analyze the generated upper limit dispatch signal to obtain the battery charging power corresponding to the energy storage power station, adjust the battery charging power based on the safety threshold, and generate dispatch information;

[0053] Analyze the generated lower limit dispatch signal to obtain the battery discharge power corresponding to the energy storage station, adjust the battery discharge power based on the safety threshold, and generate dispatch information;

[0054] For example, SOC t+1 =0.75, SOC min =0.2, SOC max =0.8, 0.75-0.2=0.55, 0.8-0.75=0.05, 0.55>0.05, then the upper limit dispatch signal is generated. According to the upper limit dispatch signal, the battery charging power corresponding to the energy storage power station is obtained, and then the battery charging power is adjusted based on the safety threshold. For example, the current charging power is P charge =10kW, the safety threshold limits the charging power to no more than 8kW, then the charging power is adjusted to 8kW, and the corresponding scheduling information is generated.

[0055] On the contrary, if SOC t+1 With SOC min The difference is less than SOC t+1 With SOC max The difference between SOC and , indicates that the battery state of charge is close to the lower limit of physical constraints. t+1 =0.25, SOC min =0.2, SOC max =0.8, 0.25-0.2=0.05, 0.8-0.25=0.55, 0.05<0.55, then a lower limit dispatch signal is generated. For the lower limit dispatch signal, the battery discharge power corresponding to the energy storage station is obtained and adjusted based on the safety threshold. Assume that the current discharge power is P discharge =15kW, the safety threshold stipulates that the discharge power cannot exceed 12kW, so the discharge power is adjusted to 12kW, and the corresponding scheduling information is generated at the same time.

[0056] At the same time, the generated scheduling information is transmitted to the scheduling management information output unit.

[0057] The scheduling management information output unit is used to display the obtained scheduling information to the corresponding management personnel.

[0058] Example 2

[0059] As the second embodiment of the present invention, it is implemented on the basis of the first embodiment, and differs from the first embodiment in the following aspects:

[0060] The peak period scheduling analysis unit is used to perform scheduling optimization based on the acquired peak period information. The specific scheduling optimization processing method is as follows:

[0061] Peak hour information is obtained and segmented into different periods. The specific segmentation processing method is as follows:

[0062] Obtain the power load corresponding to the peak period, and segment it based on the power load. The period corresponding to the rising period of the power load is classified as the first level, the period corresponding to the peak period of the power load is classified as the second level, the period corresponding to the peak plateau period of the power load is classified as the third level, and the period corresponding to the decreasing period of the power load is classified as the fourth level. Different levels are labeled as i, and i=1, 2, 3, 4. Specifically, i=1 represents the first level, i=2 represents the second level, and so on. At the same time, the battery charge state corresponding to the energy storage batteries of different levels is obtained, and dynamic adjustment is performed according to the battery charge state;

[0063] First, obtain the power load data corresponding to the peak period (for example, 18:00-22:00 on summer weekdays). Based on this data, segment the power load according to its changing trend.

[0064] Periods when electricity load is increasing are classified as Tier 1. For example, between 6:00 PM and 7:00 PM, as people return home from get off work and various appliances gradually turn on, electricity load increases. This period falls into Tier 1.

[0065] The second tier is defined as periods when electricity load reaches its peak. For example, between 7:00 PM and 8:00 PM, when most household electrical appliances are turned on and electricity load reaches its peak for the day, this period falls into the second tier.

[0066] Periods where the power load remains near its peak and relatively stable are classified as Tier 3. For example, between 8:00 PM and 9:00 PM, although electrical equipment continues to operate, the overall load fluctuates slightly, remaining at a peak plateau, thus falling into Tier 3.

[0067] The period when electricity load begins to decrease is classified as Tier 4. For example, between 21:00 and 22:00, as some appliances are turned off, electricity load gradually decreases, which is Tier 4.

[0068] According to the formula Calculate the discharge power P corresponding to different steps i dischaerge，i , where Δt i is the step duration corresponding to step i, E capacity is the capacity of the energy storage power station, SOC star，t is the battery state of charge at the beginning of step i, SOC end，t is the battery charge state at the end of step i, and the calculated discharge power P dischaerge，i The energy storage power station is dispatched according to the standard, the dispatch information is generated, and the dispatch information is transmitted to the dispatch management information output unit.

[0069] For example, at the first level, SOC star，170%, SOC end，1 is 60%, the energy storage power station capacity E capacity is 1000kWh, step duration Δt i For 1 hour, the discharge power P calculated according to the formula is dischaerge，1 If the power is 50kW, the calculated value will be used as the standard for scheduling.

[0070] The scheduling management information output unit is used to display the generated scheduling information to the corresponding management personnel.

[0071] Example 3

[0072] As the third embodiment of the present invention, the focus is on combining the implementation processes of the first and second embodiments.

[0073] Example 4

[0074] See also Figure 2 , the present application provides a scheduling adaptation method for an electrochemical energy storage power station, the method specifically comprising the following steps:

[0075] Step 1: Collect historical data and operating parameters of the energy storage power station, and classify different time periods according to power consumption to obtain normal time periods and peak time periods. The specific processing method is the same as the processing method of the energy storage power station information analysis unit in Example 1;

[0076] Step 2: Perform scheduling processing for the normal period, predict the battery charge state according to the formula, and judge it against the physical constraints. If it meets the requirements, generate normal supervision information, otherwise generate a scheduling optimization signal. The specific processing method is the same as the processing method of the normal period scheduling analysis unit in Example 1;

[0077] Step 3: Analyze the scheduling optimization signal, calculate the difference between the predicted battery state of charge and the upper and lower limits of the physical constraints, and compare the difference between the two to generate upper and lower scheduling signals and a lower limit scheduling signal. At the same time, adjust the charging and discharging power based on the safety threshold to generate scheduling information. The specific processing method is the same as that of the normal period scheduling analysis unit in Example 1.

[0078] Step 4: Perform scheduling processing during peak hours, classify the electricity load into different levels based on the peak hours, calculate the corresponding discharge power according to the battery charge corresponding to the different levels, and generate scheduling information based on this standard. The specific processing method is the same as the processing method of the peak hour scheduling analysis unit in Example 1.

[0079] Some of the data in the above formulas are calculated based on their numerical values ​​and are not substituted into parameter units for calculation. At the same time, the contents not described in detail in this specification belong to the existing technology known to those skilled in the art.

[0080] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. 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. The electrochemical energy storage power station dispatching and management system is characterized by: include: The energy storage power station information analysis unit is used to classify the different working periods of the energy storage power station according to the power station information transmitted by the power station information collection unit, classify the different periods according to the power consumption to obtain normal periods and peak periods, generate corresponding information, and transmit the two separately; The normal period scheduling analysis unit is used to analyze the acquired normal period information, predict the battery charge state according to the formula, and judge it against the physical constraints. If the normal period information is satisfied, normal supervision information is generated; otherwise, a scheduling optimization signal is generated. Analyze the scheduling optimization signal, calculate the difference between the predicted battery charge state and the upper and lower limits of the physical constraints, and compare the difference between the two to generate upper and lower scheduling signals and lower limit scheduling signals. At the same time, adjust the charging and discharging power based on the safety threshold as the standard to generate scheduling information, and then transmit it to the scheduling management information output unit; The peak period scheduling analysis unit is used to analyze the peak period information obtained, classify it into different levels based on the power load conditions during the peak period, calculate the corresponding discharge power according to the battery charge corresponding to the different levels, and generate scheduling information based on it as a standard, which is then transmitted to the scheduling management information output unit.

2. The electrochemical energy storage power station dispatching and operation management system according to claim 1, characterized in that: It also includes a power station information collection unit and a dispatching management information output unit; A power station information collection unit is used to collect power station information of the energy storage power station, wherein the power station information includes operating parameters and historical data, and transmit it to the energy storage power station information analysis unit; The scheduling management information output unit is used to display the acquired normal supervision information and scheduling information to the corresponding management personnel.

3. The electrochemical energy storage power station dispatching and operation management system according to claim 1, characterized in that: The energy storage power station information analysis unit classifies different time periods into normal time periods and peak time periods according to power consumption, and generates corresponding information in the following specific manner: Extract data from the power station's historical data based on a time period of T, split it into unit time granularity, obtain the power consumption for each unit time period, and compare it with the preset value set by the operator; If the value is greater than the preset value, it is marked as a high-power consumption period, and if it is less than the preset value, it is marked as a normal power consumption period. After completing the classification of all unit time periods, the peak period and normal period information are summarized and generated respectively, and then transmitted to the peak period and normal period scheduling analysis units accordingly.

4. The electrochemical energy storage power station dispatching and operation management system according to claim 1, characterized in that: The specific manner in which the normal period scheduling analysis unit analyzes the acquired normal period information is as follows: Get the normal time period corresponding to the time period T, and at the same time get the battery charge state SOC of the energy storage power station corresponding to time t t , and the corresponding battery charge and discharge power P t , then according to the formula Calculate the battery state of charge SOC at time t+1 t+1 , and η represents the charge and discharge efficiency of the battery, Δt refers to the time interval, E rated Indicates the rated capacity of the battery; The battery state of charge SOC t+1 Compare with the upper and lower limits of the corresponding physical constraints to determine the specific SOC min ≤SOC t+1 ≤SOC max ,If the above physical constraints are met, normal supervision information is generated, otherwise a scheduling optimization signal is generated.

5. The electrochemical energy storage power station dispatching and operation management system according to claim 1, characterized in that: The specific method in which the normal period scheduling analysis unit analyzes the scheduling optimization signal is as follows: Calculate battery state of charge SOC t+1 With SOC min and SOC max The difference between the lower limit and the upper limit is determined, and the relationship between the battery charge state and the upper and lower limits is determined. If the difference between the lower limit is greater than the difference between the upper limit, an upper limit scheduling signal is generated. Conversely, if the difference between the lower limit is less than the difference between the upper limit, a lower limit scheduling signal is generated.

6. The electrochemical energy storage power station dispatching and operation management system according to claim 1, characterized in that: The normal period scheduling analysis unit adjusts the charge and discharge power based on the safety threshold and generates scheduling information in the following manner: Analyze the upper limit dispatch signal to obtain the battery charging power corresponding to the energy storage power station, adjust the battery charging power based on the safety threshold, and generate dispatch information; The lower limit dispatch signal is analyzed to obtain the battery discharge power corresponding to the energy storage power station, and the battery discharge power is adjusted based on the safety threshold to generate dispatch information.

7. The electrochemical energy storage power station dispatching and operation management system according to claim 1, characterized in that: The peak period analysis unit analyzes the acquired peak period information in the following specific manner: According to the changing trend of power load during peak hours, it is divided into four steps. The first step is the rising period, the second step is the peak period, the third step is the peak plateau period, and the fourth step is the falling period, which are marked as i=1, 2, 3, and 4 respectively. At the same time, the SOC status of the energy storage battery in each step is obtained and dynamically adjusted according to the battery charge state.

8. The electrochemical energy storage power station dispatching and operation management system according to claim 7, characterized in that: The specific manner in which the peak period analysis unit dynamically adjusts according to the battery charge state is as follows: According to the formula Calculate the discharge power P corresponding to different steps i dischaerge，i , where Δt i is the step duration corresponding to step i, E capacity is the capacity of the energy storage power station, SOC star，t is the battery state of charge at the beginning of step i, SOC end，t is the battery charge state at the end of step i, and the calculated discharge power P dischaerge，i Dispatch energy storage power stations according to standards and generate dispatch information.

9. A method for scheduling and adapting an electrochemical energy storage power station, the method being executed by the electrochemical energy storage power station scheduling and operation management system according to any one of claims 1 to 8, characterized in that: The method specifically comprises the following steps: Step 1: Collect historical data and operating parameters of the energy storage power station, and classify different time periods according to power consumption to obtain normal time periods and peak time periods; Step 2: Schedule the normal period, predict the battery charge state according to the formula, and judge it against the physical constraints. If it meets the requirements, generate normal supervision information, otherwise generate a scheduling optimization signal; Step 3: Analyze the scheduling optimization signal, calculate the difference between the predicted battery state of charge and the upper and lower limits of the physical constraints, and compare the difference between the two to generate upper and lower scheduling signals and lower limit scheduling signals. At the same time, adjust the charging and discharging power based on the safety threshold to generate scheduling information; Step 4: Perform scheduling processing during peak hours, classify the electricity load into different levels based on the peak hours, calculate the corresponding discharge power according to the battery charge corresponding to the different levels, and generate scheduling information based on this standard.

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