Smart storage and discharge control method, system, device and medium based on smart meter

Abstract

The application discloses an intelligent storage and discharge control method, system, device and medium based on a smart meter, the method comprising: if a converter detects that an energy storage device is connected, sending a collection request to obtain device collection information, counting the device collection information and obtaining storage and discharge action distribution information in combination with peak and valley electricity time periods and sending the storage and discharge action distribution information to the smart meter, if a storage time point in the storage and discharge action distribution information is reached, the smart meter controls the energy storage device to store electricity, and if a discharge time point is reached, the smart meter controls the energy storage device to discharge. The intelligent storage and discharge control method based on the smart meter, which obtains device collection information and statistically analyzes the device collection information to obtain storage and discharge action distribution information, and intelligently controls storage and discharge through the smart meter, can not only accurately match the use demand of a user for the energy storage device, but also effectively relieves the operation pressure of a power grid under high load, and greatly improves the accuracy and control effect of storage and discharge control.

Description

Technical Field

[0001] This invention relates to the field of smart meter technology, and in particular to a smart storage and discharge control method, system, device and medium based on smart meters. Background Technology

[0002] With technological advancements, it has become possible to utilize energy storage devices such as electric vehicles to store electricity during periods of low electricity prices and discharge it during periods of high electricity prices. This energy storage and discharge method not only alleviates the operational pressure of high grid loads but also allows for additional revenue through the price difference. However, current technologies typically involve manual operation of energy storage and discharge, or storing and discharging energy at specific times. This method is not only time-consuming and labor-intensive but also difficult to precisely match users' needs for energy storage devices. Therefore, existing technologies suffer from poor control performance in energy storage and discharge management. Summary of the Invention

[0003] This invention provides a smart energy storage and discharge control method, system, device, and medium based on smart meters, aiming to solve the problem of poor control effect in existing energy storage and discharge control methods.

[0004] In a first aspect, embodiments of the present invention provide a smart energy storage and discharge control method based on a smart meter, wherein the method is applied in a smart energy storage and discharge control system, the smart energy storage and discharge control system including a smart meter and a converter electrically connected to the smart meter, the method comprising: If the converter detects that an energy storage device is connected, it sends a collection request to the energy storage device to obtain the device collection information fed back by the energy storage device according to the collection request; The converter collects data from the device based on preset peak and off-peak electricity periods to obtain corresponding statistical data. The converter obtains storage action allocation information corresponding to the collected statistical information according to the preset storage allocation strategy and the peak and valley electricity periods, and sends it to the smart meter. If the energy storage time point corresponding to the energy storage action in the energy storage action allocation information is reached, the smart meter controls the energy storage port of the energy storage device to connect to the main line for energy storage. If the discharge time point corresponding to the discharge action in the storage action allocation information is reached, the smart meter controls the discharge port of the energy storage device to connect to the main line for discharge according to the preset discharge strategy and the monitoring information of the main line.

[0005] Secondly, embodiments of the present invention also provide an intelligent energy storage and discharge control system based on a smart meter, wherein the system is configured in an intelligent energy storage and discharge control system, the intelligent energy storage and discharge control system including a smart meter and a converter electrically connected to the smart meter, the system being used to execute the intelligent energy storage and discharge control method based on a smart meter as described in the first aspect above.

[0006] Thirdly, embodiments of the present invention also provide a computer device, wherein the device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; When the processor executes the program stored in the memory, it implements the steps of the intelligent storage and discharge control method based on a smart meter as described in the first aspect above.

[0007] Fourthly, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the intelligent storage and discharge control method based on a smart meter as described in the first aspect above.

[0008] This invention provides a smart energy storage and discharge control method, system, device, and medium based on smart meters. The method includes: if a converter detects the access of an energy storage device, it sends a data acquisition request to obtain device data acquisition information; it statistically analyzes the device data acquisition information and combines it with peak and off-peak electricity periods to obtain energy storage and discharge action allocation information, which is then sent to the smart meter; if the energy storage time point in the energy storage and discharge action allocation information is reached, the smart meter controls the energy storage device to store energy; if the discharge time point is reached, the smart meter controls the energy storage device to discharge. This smart energy storage and discharge control method based on smart meters acquires and statistically analyzes device data acquisition information to allocate energy storage and discharge action allocation information, and uses smart meters for intelligent energy storage and discharge control. This not only accurately matches user needs for energy storage devices but also effectively alleviates the operational pressure of high grid loads, significantly improving the accuracy and effectiveness of energy storage and discharge control. Attached Figure Description

[0009] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 A flowchart illustrating the intelligent energy storage and discharge control method based on a smart meter provided in this embodiment of the invention; Figure 2A schematic diagram illustrating an application scenario of the intelligent energy storage and discharge control method based on a smart meter provided in an embodiment of the present invention; Figure 3 A schematic block diagram of an intelligent energy storage and discharge control system based on a smart meter, provided for an embodiment of the present invention; Figure 4 This is a schematic block diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0011] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0012] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0013] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0014] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0015] This invention provides an intelligent energy storage and discharge control method based on a smart meter, which is applied in an intelligent energy storage and discharge control system. The intelligent energy storage and discharge control system includes a smart meter and a converter electrically connected to the smart meter. The smart meter and the converter execute a stored software program to implement the aforementioned intelligent energy storage and discharge control method based on the smart meter. Figure 2As shown, the smart meter 10 is a meter terminal that can detect the voltage and current in the main line 11 and control the energy storage and discharging of the energy storage device through its internally configured processing module and switching devices. The processing module can be an MCU chip or an FPGA chip, and the switching devices can be IGBTs, transistors, etc. The smart meter 10 communicates with the energy storage device 20 and the converter 30 to transmit data. The smart meter 10 can communicate with the energy storage device 20 and the converter 30 through wired communication, Bluetooth communication, radio frequency communication, or WiFi communication. The smart meter 10 and converter 30 can be integrated into the charging pile. One end of the converter 30 in the charging pile is connected to the smart meter 10, and the other end is electrically connected to the energy storage device 20 through its configured connection interface. The converter 30 is a conversion and processing device configured in the charging pile for processing information collected by the device and converting power. The converter 30 is used to communicate with the energy storage device and acquire and analyze the information collected by the device. The conversion circuit configured in the converter 30 can convert AC power to DC power during energy storage and convert DC power to AC power during discharge. The energy storage device 20 is a device with a rechargeable battery that can store electrical energy, typically such as an electric vehicle.

[0016] like Figure 1 As shown, the method includes steps S110 to S150.

[0017] S110. If the converter detects that the energy storage device is connected, it sends a collection request to the energy storage device to obtain the device collection information fed back by the energy storage device according to the collection request.

[0018] Specifically, the converter detects the continuity of the connection interface. If an energy storage device is connected to the interface, the power supply circuit corresponding to the interface is activated. The converter can then detect whether the energy storage device is connected by checking the continuity of the power supply circuit. If the energy storage device is detected to be connected via electrical connection, a data acquisition request is sent to the energy storage device via communication connection. During the process of establishing an electrical connection between the energy storage device and the converter, a wired communication connection can be established between the device and the converter via the connection interface, or the electrical connection and communication connection can be established independently (e.g., wireless connection via Bluetooth, radio frequency, etc.).

[0019] After the converter sends a data acquisition request to the energy storage device, the device can return corresponding data acquisition information based on the request. This information includes the device's maximum energy storage capacity, maximum discharge capacity, and discharge information. For example, the data acquisition request can specify a data acquisition duration. The energy storage device will then obtain the discharge rates at multiple data acquisition points within the specified duration as its discharge information, combine this information with the maximum energy storage capacity and maximum discharge capacity, and return it as the final data acquisition information. If the data acquisition duration is 60 days, the energy storage device will obtain discharge information from multiple data acquisition points within those 60 days and return it as feedback.

[0020] S120. The converter collects information from the device according to the preset peak and valley electricity periods to obtain corresponding collection statistics.

[0021] After receiving the information collected by the device, the converter performs time-segmented statistical analysis on the device discharge information in the collected information according to the pre-configured peak and valley electricity periods, thereby obtaining the corresponding collected statistical information.

[0022] In a more specific embodiment, step S120 includes the following sub-steps: determining the discharge rate at each collection point in the device's collected information to obtain the usage status at each collection point; and statistically analyzing the usage status of the collection points corresponding to each time period in the peak-valley power period to obtain the corresponding collection statistics information.

[0023] Specifically, the information collected by the device includes the discharge rate corresponding to each collection point. This discharge rate is the rate at which the device drives the energy storage device (such as driving a new energy vehicle) to discharge during its operation. The interval between adjacent collection points can be 30 seconds or 60 seconds. The difference between the current collection point's charge and the previous collection point's charge can be obtained and divided by the interval time to get the corresponding discharge rate. The unit of the discharge rate is kW.

[0024] The system determines whether the discharge rate at each sampling point falls within a preset rate range. The maximum value of the rate range can be the discharge rate when the motor in the energy storage device outputs maximum power, and the minimum value can be the discharge rate when the energy storage device travels at a constant speed. By judging the discharge rate at each sampling point, the usage status at each sampling point is determined. If the discharge rate at the sampling point is within the rate range, the energy storage device is considered to be in normal operation, and the usage status at the sampling point is determined to be "in use." If the discharge rate at the sampling point is not within the rate range, the usage status at the sampling point is determined to be "not in use."

[0025] Peak-valley electricity periods include multiple time slots, such as: Time slot 1 is 0:00-7:59, corresponding to off-peak electricity price; Time slot 2 is 8:00-9:59, corresponding to flat electricity price; Time slot 3 is 10:00-10:59, corresponding to peak electricity price; Time slot 4 is 11:00-11:59, corresponding to peak electricity price; Time slot 5 is 12:00-13:59, corresponding to flat electricity price; Time slot 6 is 14:00-14:59, corresponding to peak electricity price; Time slot 7 is 15:00-16:59, corresponding to peak electricity price; Time slot 8 is 17:00-18:59, corresponding to peak electricity price; Time slot 9 is 19:00-23:59, corresponding to flat electricity price.

[0026] The usage status of the collection points corresponding to each time period in the peak and valley electricity period is statistically analyzed to obtain the corresponding collection statistics. The proportion and trend of the collection points in use in each time period are obtained as the corresponding collection statistics.

[0027] In a more specific embodiment, the step of statistically analyzing the usage status of each time period corresponding to the collection time point within the peak-valley electricity period to obtain corresponding collection statistics includes: statistically analyzing the usage duration of each time period corresponding to the usage status within the peak-valley electricity period each day to obtain the usage duration percentage of each time period; obtaining the average usage duration percentage of each time period for each day within a week to obtain the average percentage of each time period; performing trend analysis on the usage duration percentage of each time period for each day within a week to obtain usage trend information of each time period; and combining the average percentage of each time period and the usage trend information as the corresponding collection statistics.

[0028] Specifically, the usage time of each time period during the peak and off-peak electricity hours of each day can be statistically analyzed. That is, the total usage time of each time period on each day is calculated as the corresponding usage time. The ratio between the usage time of each time period and the total duration of the time period is calculated to obtain the usage time percentage of each time period on each day.

[0029] Each time period corresponds to a usage time percentage for each day, thus a time period contains multiple usage time percentages. Further calculations are made to average the usage time percentages for each time period within a single week (considering the difference between weekdays and weekends, from Monday to Sunday), yielding the average percentage for each time period. For example, if a day contains 9 time periods and a week contains 7 days, then the average percentage for a total of 63 time periods corresponding to a single week can be obtained.

[0030] Trend analysis is performed on the percentage of usage time for each time slot each day within a single week to obtain usage trend information for each time slot. This usage trend information can be used to reflect the changing trend of usage time. Specifically, the percentage of usage time for each day and time slot within the last two weeks is calculated and averaged to obtain the recent average percentage. The recent average percentage of usage time for each time slot within the week is subtracted from the average percentage of the corresponding time slot to obtain the percentage difference. This yields 63 percentage differences for each time slot within the week. The ratio of the percentage difference for each time slot to the average percentage of the corresponding time slot is used as the usage trend information for each time slot within the week, resulting in 63 usage trend information. If the usage trend information for a certain time slot is positive, it indicates that the probability of use during that time slot is increasing; if the usage trend information for a certain time slot is negative, it indicates that the probability of use during that time slot is decreasing. The magnitude of the increase or decrease is related to the value. The average percentage of each time slot and the usage trend information are combined to obtain the corresponding collected statistical information.

[0031] S130, the converter obtains storage action allocation information corresponding to the collected statistical information according to the preset storage allocation strategy and the peak and valley electricity periods, and sends it to the smart meter.

[0032] Furthermore, based on the storage and distribution allocation strategy, storage and distribution action allocation information that matches the aforementioned peak and valley electricity periods and collected statistical information is obtained. This storage and distribution action allocation information can allocate energy storage and discharge actions for a future period of time, and the obtained storage and distribution action allocation information is sent to the smart meter.

[0033] In a more specific embodiment, step S130 includes the following sub-steps: determining whether the average proportion and usage trend information of the low-price time period in the peak-valley electricity period meet the judgment rules in the energy storage and distribution strategy; if the low-price time period meets the judgment rules, determining the low-price time period as the energy storage operation time period; filtering the time period between two adjacent energy storage operation time periods according to the filtering rules in the energy storage and distribution strategy to determine one of the time periods as the discharge operation time period; and combining the energy storage operation time period and the discharge operation time period to obtain the corresponding energy storage and distribution operation allocation information.

[0034] Based on peak and off-peak electricity hours, time periods within a week are sequentially combined, and the lowest-priced time periods within the combined time period information are further identified. These lowest-priced time periods may include off-peak electricity price periods and flat-peak electricity price periods. The average proportion and usage trend information of these lowest-priced time periods are then assessed to determine if they meet the judgment rules in the energy storage allocation strategy. This judgment requires obtaining the lowest-priced time periods for each day of the week for separate assessment. Specifically, it can be determined whether the average proportion of the lowest-priced time periods does not exceed the proportion threshold in the judgment rules, and whether the usage trend information of these lowest-priced time periods does not exceed the trend threshold in the judgment rules. If the average proportion of the lowest-priced time periods does not exceed the proportion threshold, and the usage trend information does not exceed the trend threshold, then the lowest-priced time period is determined to be an energy storage operation period. If the average proportion of the lowest-priced time periods exceeds the proportion threshold, or the usage trend information exceeds the trend threshold, then the lowest-priced time period is determined not to be an energy storage operation period.

[0035] Alternatively, the trend coefficient can be calculated using the trend coefficient calculation formula in the judgment rules to obtain the average proportion of the low-price period and the trend coefficient corresponding to the trend information used, and then it can be determined whether the trend coefficient does not exceed the trend coefficient threshold in the judgment rules. For example, the trend coefficient calculation formula could be: Where B is the average proportion of a certain low-price period, q is the usage trend information of that low-price period, r is the trend parameter (which can be set to the natural logarithm base), and Q is the calculated trend coefficient. If the trend coefficient of a low-price period does not exceed the trend coefficient threshold, then the low-price period is determined to be a period for energy storage operations; if the trend coefficient of a low-price period exceeds the trend coefficient threshold, then the low-price period is determined not to be a period for energy storage operations.

[0036] During the judgment process using the judgment rules, if two or more adjacent low-price time periods all meet the judgment rules, the electricity prices of the two or more adjacent low-price time periods are compared, and the lowest-priced time period is selected as the energy storage action period. If there are multiple low-price time periods with the lowest electricity prices among the two or more adjacent low-price time periods, the earlier low-price time period is selected as the energy storage action period. If a low-price time period is not the energy storage action period, then that low-price time period is determined to be the power supply guarantee period.

[0037] Furthermore, the trend coefficient threshold is determined based on the recent average usage duration percentage of energy storage devices and corresponding usage trend information. This allows for dynamic adjustment of the trend coefficient threshold based on users' recent usage of energy storage devices, enabling more accurate acquisition of low-price periods. Specifically, the usage duration percentage of energy storage devices in recent periods (e.g., within the last two weeks) is obtained and averaged as the average usage duration percentage. The average usage duration percentage of the collected statistics is then obtained as the overall average percentage. Subtracting the overall average percentage from the average usage duration percentage yields the percentage difference. The ratio of the percentage difference to the overall average percentage is used as the recent usage trend information of the energy storage devices. The trend threshold calculation formula is as follows: Calculate and set the trend threshold accordingly, where B is the average proportion of recent usage time of energy storage devices, q is the recent usage trend information of energy storage devices, r is the trend parameter, which can be set to the natural logarithm base, t is the adjustment coefficient, such as t=0.4; Q' is the calculated trend threshold.

[0038] The combined time period information includes the energy storage action time period determined above. The time period between two adjacent energy storage action time periods in the time period information is determined as the candidate time period. The candidate time period is then filtered according to the filtering rules in the energy storage and release allocation strategy to obtain the discharge action time period.

[0039] Specifically, the electricity price of candidate time periods between two energy storage operation periods can be obtained and sorted. For example, the candidate time points between time period 5 and time period 1 include time periods 6, 7, 8, and 9. First, the candidate time periods are sorted according to electricity price. Time period 7 has the highest price, followed by time periods 6 and 8, and then time period 9. Therefore, time period 7 ranks first and time period 9 ranks last. Then, time periods 6 and 8 are further sorted. Since time period 8 is later in the ranking, it ranks before time period 6. The final sorted result is time periods 7, 8, 6, and 9. The candidate time periods included in the sorted result are then retrieved and their selection criteria are checked. First, time period 7 is checked. If it does, time period 7 is determined to be a discharge operation time period; otherwise, the next candidate time period is retrieved and checked.

[0040] It can be determined whether the average proportion and usage trend information of the candidate time periods meet the screening rules in the storage and allocation strategy. Specifically, it can be determined whether the average proportion of the candidate time periods does not exceed the proportion threshold in the screening rules, and whether the usage trend information of the candidate time periods does not exceed the trend threshold in the screening rules. If the average proportion of the candidate time periods does not exceed the proportion threshold, and the usage trend information does not exceed the trend threshold, the candidate time period is determined to be a discharge operation time period. If the average proportion of the candidate time periods exceeds the proportion threshold, or the usage trend information exceeds the trend threshold, the candidate time period is determined not to be a discharge operation time period.

[0041] Alternatively, the screening coefficient for each candidate time period in the sorted results can be calculated using the screening coefficient calculation formula in the screening rules. For example, the screening coefficient calculation formula could be: Where S is the calculated screening coefficient, d0 is the electricity price of the current candidate time period, d1 is the electricity price of the energy storage action time period preceding the current candidate time period (d0 > d1), e is the natural logarithm base, p is the sequence number of the current candidate time period in the sorting results, B is the average proportion of the candidate time periods, q is the usage trend information of the candidate time period, and r is the trend parameter, which can be set to the natural logarithm base. The system checks whether the screening coefficient with the largest value among the candidate time periods in the sorting results is greater than the screening coefficient threshold set in the screening rules. If the largest screening coefficient is greater than the screening coefficient threshold, the candidate time period with the largest screening coefficient is determined as the discharge action time period; if the largest screening coefficient is not greater than the screening coefficient threshold, all candidate time periods are determined as power preservation time periods. The obtained energy storage action time periods and discharge action time periods are combined to obtain the corresponding energy storage and discharge action allocation information. During the power preservation time period, the battery power is retained, and no discharge operation is performed during the power preservation time period.

[0042] S140. If the energy storage time point corresponding to the energy storage action in the energy storage action allocation information is reached, the smart meter controls the energy storage port of the energy storage device to connect to the main line for energy storage.

[0043] It can determine whether the energy storage time point corresponding to the energy storage action in the energy storage action allocation information has been reached. The energy storage action time period corresponds to the energy storage action, and the energy storage time point corresponding to the energy storage action is also the start time point of the energy storage action time period. If the energy storage time point has been reached, the smart meter controls the energy storage device's energy storage port to connect to the main line for energy storage. At this time, the main line outputs three-phase AC power to the converter, which converts the three-phase AC power into DC power and outputs it to the energy storage device for energy storage.

[0044] In a more specific embodiment, step S140 includes the following sub-steps: acquiring environmental detection information detected at the current moment; and controlling the energy storage power output to the energy storage port according to the preset energy storage strategy, the energy storage action time period corresponding to the energy storage time point, and the environmental detection information.

[0045] Specifically, it can acquire environmental detection information at the current moment and control the energy storage power output to the energy storage port based on the energy storage strategy, the current energy storage operation time period, and the environmental detection information. The environmental detection information includes ambient temperature. The energy storage strategy is configured with multiple charging curves, each corresponding to a different strategy. Different charging curves require different charging times. The charging curves also contain the relationship between battery capacity and basic charging power; generally, the higher the battery capacity, the lower the basic charging power. Based on the duration of the current energy storage operation time period, a charging curve matching the duration of that time period can be obtained from the energy storage strategy as the target charging curve for application.

[0046] The energy storage strategy also includes a power calculation formula to determine the base charging power corresponding to the current battery capacity in the target charging curve. Based on this formula, the base charging power and environmental monitoring information are used to calculate the target power value, which is then used to control the energy storage power output to the energy storage port. Since energy storage devices generate a significant amount of heat during charging, overheating can be avoided by obtaining the target power value to ensure the energy storage power is adapted to the current ambient temperature. For example, the power calculation formula can be set as follows: Where t0 is the standard ambient temperature, for example, if t0 = 25℃, t max The maximum allowable temperature of the equipment, such as setting t max =100℃, t1 is the ambient temperature in the environmental monitoring information, lg is the logarithm with base 10, and ln is the natural logarithm. P0 is the base charging power corresponding to the current battery capacity in the target charging curve, and P' is the obtained target power value.

[0047] S150. If the discharge time point corresponding to the discharge action in the storage action allocation information is reached, the smart meter controls the discharge port of the energy storage device to connect to the main line for discharge according to the preset discharge strategy and the monitoring information of the main line.

[0048] It can be determined whether the discharge time point corresponding to the discharge action in the energy storage action allocation information has been reached. The discharge action time period corresponds to the discharge action, and the discharge time point corresponding to the discharge action is also the start time point of the discharge action time period. If the discharge time point is reached, the discharge port of the energy storage device is controlled to connect to the main line for discharge according to the discharge strategy and monitoring information. At this time, the discharge port of the energy storage device can be controlled to connect to the main line for discharge. The discharge port can be independent of the energy storage port, or the energy storage port can be directly used as the discharge port (e.g., a discharge control command can be sent to the energy storage device to adjust the energy storage device to discharge externally). At this time, the DC power output by the energy storage device is converted to AC power by the converter, and the AC power is then output to the main line.

[0049] In a more specific embodiment, step S150 includes the following sub-steps: obtaining the discharge power value corresponding to the monitoring information according to the discharge strategy; and controlling the time point and discharge power of the discharge port connecting to the main line according to the discharge power value.

[0050] Specifically, monitoring information of the main line can be obtained, including the voltage monitoring value of the main line. The higher the voltage monitoring value of the main line, the smaller the grid load; the lower the voltage monitoring value, the larger the grid load. Generally speaking, the voltage value of the main line is higher than 220V. When the grid load in the area is larger, it indicates that the power consumption connected to the grid in that area is larger. At this time, the voltage of the main line will drop and gradually approach 220V.

[0051] The discharge power value corresponding to the monitoring information can be obtained according to the discharge strategy, and the timing and power of the discharge port connecting to the main line for discharge can be controlled based on this discharge power value. Specifically, the discharge strategy includes a discharge configuration mode, for example, the discharge configuration mode could be: Where y is the adjustment coefficient of the three-phase power supply (e.g., the adjustment coefficient can be set to 3 based on experience), and P j Based on the discharge power, P f The calculated discharge power value is given by v0, which is the rated voltage of the power grid, and its value is 220V. c This refers to the voltage monitoring value in the monitoring information.

[0052] After obtaining the discharge power value, the discharge time can be calculated by dividing the battery's dischargeable capacity by the discharge power value. Based on this discharge time, the timing for connecting to the main line for discharge can be determined. For example, if the dischargeable capacity is 50 kW·h and the discharge power value is 300 kW (this discharge power is greater than the maximum value in the rate range), then the corresponding discharge time T is... f The duration is 10 minutes; the current discharge action time period is [T1, T2], if T2-T f If T1 ≥ T1, then the time point for discharge is determined to be T2-T. f If T2-Tf <If T1, then determine that the time point for discharging is T1. During this discharging process, if the time point T2 is reached and there is still remaining dischargeable capacity, then continue discharging in the next time period until the dischargeable capacity reaches zero.

[0053] In a more specific embodiment, after step S150, it further includes: the smart meter detects and obtains power consumption detection information corresponding to each time period in the peak-valley electricity period within one billing cycle; the smart meter prices the power consumption detection information according to the pricing table corresponding to the peak-valley electricity period to obtain corresponding power consumption pricing information; the smart meter reports the power consumption detection information and the power consumption pricing information to the cloud.

[0054] Furthermore, the smart meter can detect power consumption detection information corresponding to each time period within one billing cycle. One billing cycle can be from 00:00 to 23:59. The smart meter can obtain the power consumption and discharge amount of each time period within this billing cycle to obtain power consumption detection information. Price the power consumption detection information according to the pricing table corresponding to the peak-valley electricity period, so as to obtain the electricity price and discharge income as power consumption pricing information. Report the power consumption detection information and the power consumption pricing information obtained within one billing cycle to the cloud to achieve data synchronization. The cloud is also the cloud server configured by the power grid operator.

[0055] In the intelligent charge-discharge control method based on a smart meter disclosed in the above embodiments, the method includes: if the converter detects the access of the energy storage device, it sends a collection request to obtain device collection information, statistically analyzes the device collection information, and combines it with the peak-valley electricity period to obtain charge-discharge action allocation information and send it to the smart meter. If the charge time point in the charge-discharge action allocation information is reached, the smart meter controls the energy storage device to charge. If the discharge time point is reached, the smart meter controls the energy storage device to discharge. The above intelligent charge-discharge control method based on a smart meter obtains device collection information, statistically analyzes it to allocate and obtain charge-discharge action allocation information, and intelligently controls charge and discharge through the smart meter. It can not only accurately match the user's usage requirements for the energy storage device, but also effectively relieve the operating pressure of the power grid under high load, and greatly improve the accuracy and control effect of charge-discharge control.

[0056] The embodiment of the present invention also provides an intelligent charge-discharge control system based on a smart meter. The intelligent charge-discharge control system based on a smart meter includes a smart meter and a converter electrically connected to the smart meter. The intelligent charge-discharge control system based on a smart meter is used to execute any embodiment of the foregoing intelligent charge-discharge control method based on a smart meter. Specifically, please refer to Figure 3 , Figure 3 which is a schematic block diagram of the intelligent charge-discharge control system based on a smart meter provided by the embodiment of the present invention.

[0057] like Figure 3 As shown, the smart energy storage and discharge control system 100 based on a smart meter includes a device information acquisition unit 110, an information acquisition and statistics unit 120, and an energy storage and discharge action allocation information acquisition unit 130 configured in the converter, as well as an energy storage control unit 140 and an energy discharge control unit 150 configured in the smart meter.

[0058] The device information acquisition unit 110 is used to send an acquisition request to the energy storage device if the energy storage device is detected to be connected, so as to obtain the device acquisition information fed back by the energy storage device according to the acquisition request.

[0059] The data acquisition and statistics unit 120 is used to collect data from the device based on preset peak and off-peak electricity periods to obtain corresponding data acquisition and statistics.

[0060] The storage and release action allocation information acquisition unit 130 is used to acquire storage and release action allocation information corresponding to the collected statistical information according to the preset storage and release allocation strategy and the peak and valley electricity time periods, and send it to the smart meter.

[0061] The energy storage control unit 140 is used to control the energy storage port of the energy storage device to connect to the main line for energy storage when the energy storage time point corresponding to the energy storage action in the energy storage action allocation information is reached.

[0062] The discharge control unit 150 is used to control the discharge port of the energy storage device to connect to the main line for discharge according to the preset discharge strategy and the monitoring information of the main line when the discharge time point corresponding to the discharge action in the storage action allocation information is reached.

[0063] In the smart energy storage and discharge control system based on smart meters provided in this embodiment of the invention, the aforementioned smart energy storage and discharge control method based on smart meters is applied. If the converter detects the access of an energy storage device, it sends a data acquisition request to obtain the device's data acquisition information. The acquired data is statistically analyzed and combined with peak and off-peak electricity periods to obtain energy storage and discharge action allocation information, which is then sent to the smart meter. If the energy storage time point in the energy storage and discharge action allocation information is reached, the smart meter controls the energy storage device to store energy; if the discharge time point is reached, the smart meter controls the energy storage device to discharge. This smart energy storage and discharge control method based on smart meters acquires and statistically analyzes the acquired data to allocate energy storage and discharge action allocation information, and intelligently controls energy storage and discharge through smart meters. This not only accurately matches the user's demand for energy storage devices but also effectively alleviates the operational pressure of high grid loads, significantly improving the accuracy and effectiveness of energy storage and discharge control.

[0064] The aforementioned intelligent energy storage and discharge control system based on smart meters can be implemented as a computer program, which can be used in various ways, such as... Figure 4It runs on the computer device shown.

[0065] Please see Figure 4 , Figure 4 This is a schematic block diagram of a computer device provided in an embodiment of the present invention. The computer device may be a converter or a smart meter for executing a smart energy storage and discharge control method based on a smart meter to control the energy storage and discharge of an energy storage device.

[0066] See Figure 4 The computer device 500 includes a processor 502, a memory, and a communication interface 505 connected via a communication bus 501. The memory may include a storage medium 503 and internal memory 504.

[0067] The storage medium 503 may store an operating system 5031 and a computer program 5032. When the computer program 5032 is executed, it enables the processor 502 to execute a smart storage and discharge control method based on a smart meter. The storage medium 503 may be a volatile storage medium or a non-volatile storage medium.

[0068] The processor 502 provides computing and control capabilities to support the operation of the entire computer device 500.

[0069] The internal memory 504 provides an environment for the operation of the computer program 5032 in the storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a smart storage and discharge control method based on a smart meter.

[0070] This communication interface 505 is used for network communication, such as providing data transmission. Those skilled in the art will understand that... Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the computer device 500 to which the present invention is applied. The specific computer device 500 may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0071] The processor 502 is used to run the computer program 5032 stored in the memory to implement the corresponding functions in the above-mentioned intelligent storage and discharge control method based on smart meters.

[0072] Those skilled in the art will understand that Figure 4The embodiments of the computer device shown do not constitute a limitation on the specific configuration of the computer device. In other embodiments, the computer device may include more or fewer components than illustrated, or combine certain components, or have different component arrangements. For example, in some embodiments, the computer device may include only memory and a processor. In such embodiments, the structure and function of the memory and processor are different from those shown. Figure 4 The embodiments shown are consistent and will not be repeated here.

[0073] It should be understood that, in this embodiment of the invention, the processor 502 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0074] In another embodiment of the invention, a computer-readable storage medium is provided. This computer-readable storage medium may be volatile or non-volatile. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps included in the above-described intelligent energy storage and discharge control method based on a smart meter.

[0075] Those skilled in the art will readily understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention.

[0076] In the embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Units with the same function may be grouped into one unit. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, or it may be an electrical, mechanical, or other form of connection.

[0077] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of the present invention, depending on actual needs.

[0078] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0079] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a computer-readable storage medium and includes several instructions to cause a computer device to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned computer-readable storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks.

[0080] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A smart energy storage and discharge control method based on a smart meter, characterized in that, The method is applied in an intelligent energy storage and discharge control system, which includes a smart meter and a converter electrically connected to the smart meter. The method includes: If the converter detects that an energy storage device is connected, it sends a data acquisition request to the energy storage device to obtain the device acquisition information fed back by the energy storage device according to the data acquisition request. The converter performs statistical analysis on the information collected by the device according to preset peak and off-peak electricity periods to obtain corresponding statistical information. The converter obtains storage action allocation information corresponding to the collected statistical information according to the preset storage allocation strategy and the peak and valley electricity periods, and sends it to the smart meter. If the energy storage time point corresponding to the energy storage action in the energy storage action allocation information is reached, the smart meter controls the energy storage port of the energy storage device to connect to the main line for energy storage. If the discharge time point corresponding to the discharge action in the storage action allocation information is reached, the smart meter controls the discharge port of the energy storage device to connect to the main line for discharge according to the preset discharge strategy and the monitoring information of the main line.

2. The intelligent energy storage and discharge control method based on a smart meter according to claim 1, characterized in that, The step of statistically analyzing the information collected by the device based on preset peak and off-peak electricity periods to obtain corresponding statistical information includes: Determine the discharge rate at each acquisition point in the information collected by the device to obtain the usage status at each acquisition point; The usage status of the collection time points corresponding to each time period in the peak and valley electricity period is statistically analyzed to obtain the corresponding collection statistics.

3. The intelligent energy storage and discharge control method based on a smart meter according to claim 2, characterized in that, The usage status of the data collection points corresponding to each time period within the peak and off-peak electricity periods is statistically analyzed to obtain corresponding data collection statistics, including: The usage duration of each time period during the peak and off-peak electricity hours of each day is statistically analyzed to obtain the usage duration percentage of each time period. Obtain the average percentage of usage time for each time period on each day of the week, and get the average percentage for each time period; By performing trend analysis on the percentage of usage time in different time periods each day of a week, usage trend information for each time period can be obtained. The average percentage and usage trend information for each time period are combined to form the corresponding collected statistical information.

4. The intelligent energy storage and discharge control method based on a smart meter according to any one of claims 1-3, characterized in that, The step of obtaining storage and distribution action allocation information corresponding to the collected statistical information based on the preset storage and distribution allocation strategy and the peak and off-peak electricity periods includes: Determine whether the average proportion and usage trend information of the low-price time period in the peak-valley electricity period meet the judgment rules in the storage and allocation strategy; If the low-price period meets the judgment rule, the low-price period is determined as the energy storage operation period; The time period between two adjacent energy storage operation time periods is filtered according to the filtering rules in the energy storage and allocation strategy to determine one of the time periods as the discharge operation time period. By combining the energy storage action time period and the discharge action time period, the corresponding energy storage and discharge action allocation information is obtained.

5. The intelligent energy storage and discharge control method based on a smart meter according to claim 4, characterized in that, The step of controlling the discharge port of the energy storage device to connect to the main line for discharge according to the preset discharge strategy and the monitoring information of the main line includes: The discharge power value corresponding to the monitoring information is obtained according to the discharge strategy; The timing and discharge power of the discharge port being connected to the main line are controlled based on the discharge power value.

6. The intelligent energy storage and discharge control method based on a smart meter according to claim 5, characterized in that, The control of the energy storage device's energy storage port to connect to the main line for energy storage includes: Obtain environmental detection information at the current moment; The energy storage power output to the energy storage port is controlled according to the preset energy storage strategy, the energy storage action time period corresponding to the energy storage time point, and the environmental detection information.

7. The intelligent energy storage and discharge control method based on a smart meter according to claim 6, characterized in that, After controlling the discharge port of the energy storage device to connect to the main line for discharge according to the preset discharge strategy and the monitoring information of the main line, the method further includes: The smart meter detects and acquires electricity consumption information corresponding to each time period within the peak and off-peak electricity periods during a billing cycle. The smart meter calculates the electricity consumption information based on the pricing table corresponding to the peak and off-peak electricity periods, thereby obtaining the corresponding electricity consumption pricing information; The smart meter reports the electricity consumption detection information and the electricity pricing information to the cloud.

8. A smart energy storage and discharge control system based on a smart meter, characterized in that, The system is configured in an intelligent energy storage and discharge control system, which includes a smart meter and a converter electrically connected to the smart meter. The system is used to execute the intelligent energy storage and discharge control method based on the smart meter as described in any one of claims 1-7.

9. A computer device, characterized in that, The device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; When a processor executes a program stored in a memory, it implements the steps of the intelligent storage and discharge control method based on a smart meter as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the intelligent storage and discharge control method based on a smart meter as described in any one of claims 1-7.

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