Intelligent energy storage management method and system for EMS (energy management system) and readable storage medium

Abstract

The invention discloses an intelligent EMS energy storage management method and system and a readable storage medium, and the method comprises the steps: carrying out the discharge management based on an energy storage machine, and adaptively adjusting the discharge power during the discharge; operation data of different energy storage batteries are obtained for charging management, and balance management is carried out in combination with the discharging requirement during charging management; in the charging and discharging scheduling management process, health management is carried out by combining a single energy storage machine and an overall energy storage machine; and recording an energy storage machine operation log in a preset period, and performing intelligent energy storage prediction to dynamically adjust a management mechanism. According to the invention, under the control and management of the EMS, charging and discharging management and health management can be carried out on the energy storage machine, energy flow can be effectively scheduled, and the service life of equipment can be prolonged by continuously and dynamically optimizing and adjusting management measures, and at the same time, an intelligent scheduling and distribution target can be realized.

Description

Technical Field

[0001] The present invention relates to the field of electric energy management technology, and more specifically, to an EMS energy intelligent storage management method, system and readable storage medium. Background Art

[0002] EMS (Energy Management System) is an intelligent management system used to optimize energy utilization, improve system efficiency, reduce energy consumption, and minimize energy costs.

[0003] At present, in the process of using EMS to manage energy storage machines, as the application deepens, it also faces a series of problems and challenges, such as how to make more reasonable arrangements during charging and discharging management, and how to adjust power during safety monitoring and protection, etc., all measures need to be further optimized. Summary of the invention

[0004] The purpose of the present invention is to provide an EMS energy intelligent energy storage management method, system and readable storage medium, which can perform charging and discharging management and health management of energy storage machines under the control and management of EMS, effectively dispatch energy flow, and achieve intelligent dispatching and allocation goals while extending equipment life by continuously and dynamically optimizing and adjusting management measures.

[0005] A first aspect of the present invention provides an EMS energy intelligent storage management method, comprising the following steps: Discharge management based on energy storage machine, in which the discharge power is adaptively adjusted during discharge; Obtain the operating data of different energy storage batteries for charging management, where charging management is combined with discharge demand for balanced management; In the process of charge and discharge scheduling management, health management is carried out by combining individual energy storage machines and overall energy storage machines; The operation log of the energy storage machine is recorded at a preset period, and intelligent energy storage prediction is performed to dynamically adjust the management mechanism.

[0006] In this solution, the discharge management based on the energy storage machine, wherein the discharge power is adaptively adjusted during discharge, specifically includes: A charging load capacity value is obtained based on user demand, wherein the user demand includes single-user demand and / or multi-user demand, and adaptive discharge power adjustment is performed based on the load capacity value, wherein: Adjusting power based on single user demand, wherein the charging power value of a single user is obtained to perform a discharge power response of the single energy storage machine; Adjusting power based on multi-user demand, wherein the type and operation period of the multi-user demand are obtained to adjust the power response of the overall energy storage machine; Multi-objective optimization adjustment, when adjusting the power response to multiple user needs, the target power of a single energy storage machine is adjusted based on the real-time power of the overall energy storage machine.

[0007] In this solution, the operation data of different energy storage batteries are obtained for charging management, specifically including: The energy storage device is charged and managed based on a preset time period, wherein the preset time period includes a first time period and a second time period, wherein: Performing charging management on the energy storage machine based on the first time period, where the first time period includes a low-peak electricity price time period; The energy storage machine is charged and managed based on the second time period, where the second time period includes a daytime experience time period.

[0008] In this solution, charging management is combined with discharge demand for balanced management, including: When the energy storage devices are charged and discharged in parallel, balanced management is performed based on the current time period and the user's needs, wherein: In the first time period, the single energy storage machine with the largest battery capacity in the overall energy storage machine is discharged based on the single-user demand response; the demand quantity value and the demand power value are identified based on the multi-user demand, and the overall energy storage machine is arranged in positive order of power, and the energy storage machine after the order is matched based on the demand quantity value and the demand power value is discharged; In the second time period, based on the single-user demand response, the single energy storage machine with the smallest battery capacity in the overall energy storage machine is discharged; based on the multi-user demand, the demand quantity value and the demand power value are identified, and the overall energy storage machine is arranged in reverse order of power, and the energy storage machine that is matched and sorted based on the demand quantity value and the demand power value is discharged.

[0009] In this solution, during the charge and discharge scheduling management process, health management is carried out in combination with individual energy storage machines and overall energy storage machines, specifically including: Monitor the real-time temperature and output voltage of a single energy storage machine, and perform intelligent control and adjustment based on the real-time temperature to complete the health management of the single energy storage machine; Health management is performed based on the total output power of the overall energy storage machine combined with the output voltage of a single energy storage machine, wherein the output voltage of a single energy storage machine is reasonably configured in combination with the total output power to complete the health management of the overall energy storage machine, and the configuration method includes vehicle model configuration and / or battery type configuration.

[0010] In this solution, the energy storage machine operation log is recorded at a preset period, and intelligent energy storage prediction is performed to dynamically adjust the management mechanism, including: Record the daily charging and discharging scheduling data and health management data of the energy storage device to obtain a daily log; Based on the period, data landing point mapping is performed on the daily log to obtain periodic regularity data of the current period management mechanism; Intelligent energy storage prediction is performed based on the periodic regular data to dynamically adjust the management mechanism of the next cycle.

[0011] The second aspect of the present invention further provides an EMS energy intelligent storage management system, comprising a memory and a processor, wherein the memory comprises an EMS energy intelligent storage management method program, and when the EMS energy intelligent storage management method program is executed by the processor, the following steps are implemented: Discharge management based on energy storage machine, in which the discharge power is adaptively adjusted during discharge; Obtain the operating data of different energy storage batteries for charging management, where charging management is combined with discharge demand for balanced management; In the process of charge and discharge scheduling management, health management is carried out by combining individual energy storage machines and overall energy storage machines; The operation log of the energy storage machine is recorded at a preset period, and intelligent energy storage prediction is performed to dynamically adjust the management mechanism.

[0012] In this solution, the discharge management based on the energy storage machine, wherein the discharge power is adaptively adjusted during discharge, specifically includes: A charging load capacity value is obtained based on user demand, wherein the user demand includes single-user demand and / or multi-user demand, and adaptive discharge power adjustment is performed based on the load capacity value, wherein: Adjusting power based on single user demand, wherein the charging power value of a single user is obtained to perform a discharge power response of the single energy storage machine; Adjusting power based on multi-user demand, wherein the type and operation period of the multi-user demand are obtained to adjust the power response of the overall energy storage machine; Multi-objective optimization adjustment, when adjusting the power response to multiple user needs, the target power of a single energy storage machine is adjusted based on the real-time power of the overall energy storage machine.

[0013] In this solution, the operation data of different energy storage batteries are obtained for charging management, specifically including: The energy storage device is charged and managed based on a preset time period, wherein the preset time period includes a first time period and a second time period, wherein: Performing charging management on the energy storage machine based on the first time period, where the first time period includes a low-peak electricity price time period; The energy storage machine is charged and managed based on the second time period, where the second time period includes a daytime experience time period.

[0014] In this solution, charging management is combined with discharge demand for balanced management, including: When the energy storage devices are charged and discharged in parallel, balanced management is performed based on the current time period and the user's needs, wherein: In the first time period, the single energy storage machine with the largest battery capacity in the overall energy storage machine is discharged based on the single-user demand response; the demand quantity value and the demand power value are identified based on the multi-user demand, and the overall energy storage machine is arranged in positive order of power, and the energy storage machine after the order is matched based on the demand quantity value and the demand power value is discharged; In the second time period, based on the single-user demand response, the single energy storage machine with the smallest battery capacity in the overall energy storage machine is discharged; based on the multi-user demand, the demand quantity value and the demand power value are identified, and the overall energy storage machine is arranged in reverse order of power, and the energy storage machine that is matched and sorted based on the demand quantity value and the demand power value is discharged.

[0015] In this solution, during the charge and discharge scheduling management process, health management is carried out in combination with individual energy storage machines and overall energy storage machines, specifically including: Monitor the real-time temperature and output voltage of a single energy storage machine, and perform intelligent control and adjustment based on the real-time temperature to complete the health management of the single energy storage machine; Health management is performed based on the total output power of the overall energy storage machine combined with the output voltage of a single energy storage machine, wherein the output voltage of a single energy storage machine is reasonably configured in combination with the total output power to complete the health management of the overall energy storage machine, and the configuration method includes vehicle model configuration and / or battery type configuration.

[0016] In this solution, the energy storage machine operation log is recorded at a preset period, and intelligent energy storage prediction is performed to dynamically adjust the management mechanism, including: Record the daily charging and discharging scheduling data and health management data of the energy storage device to obtain a daily log; Based on the period, data landing point mapping is performed on the daily log to obtain periodic regularity data of the current period management mechanism; Intelligent energy storage prediction is performed based on the periodic regular data to dynamically adjust the management mechanism of the next cycle.

[0017] The third aspect of the present invention provides a computer-readable storage medium, which includes an EMS energy intelligent energy storage management method program of a machine. When the EMS energy intelligent energy storage management method program is executed by a processor, the steps of an EMS energy intelligent energy storage management method as described in any one of the above items are implemented.

[0018] The present invention discloses an EMS energy intelligent storage management method, system and readable storage medium, which can perform charging and discharging management and health management of energy storage machines under the control and management of EMS, can effectively dispatch energy flow, and can extend the life of equipment while achieving intelligent dispatching and allocation goals by continuously and dynamically optimizing and adjusting management measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A flow chart of an EMS energy intelligent storage management method of the present invention is shown; Figure 2 A block diagram of an EMS energy intelligent storage management system of the present invention is shown. DETAILED DESCRIPTION

[0020] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0021] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0022] Figure 1 A flow chart of an EMS energy intelligent storage management method of the present application is shown.

[0023] like Figure 1 As shown, the present application discloses an EMS energy intelligent storage management method, comprising the following steps: S102, performing discharge management based on the energy storage machine, wherein the discharge power is adaptively adjusted during discharge; S104, obtaining operation data of different energy storage batteries to perform charging management, wherein charging management is performed in combination with discharge demand for balanced management; S106, during the charge and discharge scheduling management process, health management is performed in combination with a single energy storage machine and the overall energy storage machine; S108, recording the energy storage machine operation log at a preset period, performing intelligent energy storage prediction to dynamically adjust the management mechanism.

[0024] It should be noted that, in this embodiment, the energy management system (EMS) is used to manage the energy storage machine (such as the battery energy storage system), which can optimize the energy charging and discharging control, extend the battery life, improve the economy and efficiency of the system, and improve the energy utilization rate in many scenarios. In this embodiment, two management mechanisms are mainly described, one is the charging and discharging management, and the other is the health management. Specifically, the discharge management is based on the energy storage machine, wherein the discharge power is adaptively adjusted during discharge, and when the operating data of different energy storage batteries are obtained for charging management, it is necessary to carry out balanced management in combination with the specific discharge requirements for intelligent deployment; at the same time, in the process of charging and discharging scheduling management, the health management is carried out in combination with the single energy storage machine and the overall energy storage machine, so that the entire operating system is in a safe and stable working state, the energy storage machine operation log is recorded at a preset period, and intelligent energy storage prediction is carried out to dynamically adjust the management mechanism.

[0025] According to an embodiment of the present invention, the energy storage machine-based discharge management, wherein the discharge power is adaptively adjusted during discharge, specifically includes: A charging load capacity value is obtained based on user demand, wherein the user demand includes single-user demand and / or multi-user demand, and adaptive discharge power adjustment is performed based on the load capacity value, wherein: Adjusting power based on single user demand, wherein the charging power value of a single user is obtained to perform a discharge power response of the single energy storage machine; Adjusting power based on multi-user demand, wherein the type and operation period of the multi-user demand are obtained to adjust the power response of the overall energy storage machine; Multi-objective optimization adjustment, when adjusting the power response to multiple user needs, the target power of a single energy storage machine is adjusted based on the real-time power of the overall energy storage machine.

[0026] It should be noted that, in this embodiment, how to perform discharge management is specifically described, and three adjustment measures are given, one of which is to adjust power based on the needs of a single user, the second is to adjust power based on the needs of multiple users, and the third is multi-objective optimization adjustment. Specifically, the power is adjusted based on the needs of a single user, wherein the charging power value of a single user is obtained to perform the discharge power response of the single energy storage machine so that the charging demand of the single user meets the corresponding power value; at the same time, the power is adjusted based on the needs of multiple users, wherein the types and operating periods of the needs of multiple users are obtained to adjust the power response of the overall energy storage machine, wherein the charging needs of different users are used to adjust the power response of the energy storage machine. Adjust the power response of the overall energy storage machine in different time periods. Specifically, the power response of the overall energy storage machine is obtained based on the comprehensive charging needs of users during the daytime and nighttime periods to meet the electricity demand in different time periods, and multi-objective optimization adjustment. When adjusting the power response to multi-user needs, the target power of a single energy storage machine is adjusted based on the real-time power of the overall energy storage machine. Since the total input power of the overall energy storage machine is constant, it is necessary to perform statistics based on the discharge objects (vehicles) connected to the single energy storage machine in real time in multi-user applications based on multi-objective optimization adjustment, and perform average regulation or differential regulation on the overall energy storage machine.

[0027] According to an embodiment of the present invention, the acquisition of operating data of different energy storage batteries for charging management specifically includes: The energy storage device is charged and managed based on a preset time period, wherein the preset time period includes a first time period and a second time period, wherein: Performing charging management on the energy storage machine based on the first time period, where the first time period includes a low-peak electricity price time period; The energy storage machine is charged and managed based on the second time period, where the second time period includes a daytime experience time period.

[0028] It should be noted that, in this embodiment, the first time period is night time, and the second time period is day time. When the energy storage machine is charged and managed, the energy storage machine is charged and managed based on the first time period, and the first time period includes a low-peak electricity price time period, so that charging is performed when the electricity price is low, reducing the storage cost, and discharging is performed during the peak electricity consumption during the day; the energy storage machine is charged and managed based on the second time period, and the second time period includes a daytime experience time period, wherein the daytime experience time period is a time period with low electricity demand during the non-low-peak period during the day and a low-peak electricity price period during the day, and the daytime discharge demand is met by charging during the low-peak electricity price and charging when the demand is low.

[0029] According to an embodiment of the present invention, charging management is combined with discharging demand to perform balanced management, specifically including: When the energy storage devices are charged and discharged in parallel, balanced management is performed based on the current time period and the user's needs, wherein: In the first time period, the single energy storage machine with the largest battery capacity in the overall energy storage machine is discharged based on the single-user demand response; the demand quantity value and the demand power value are identified based on the multi-user demand, and the overall energy storage machine is arranged in positive order of power, and the energy storage machine after the order is matched based on the demand quantity value and the demand power value is discharged; In the second time period, based on the single-user demand response, the single energy storage machine with the smallest battery capacity in the overall energy storage machine is discharged; based on the multi-user demand, the demand quantity value and the demand power value are identified, and the overall energy storage machine is arranged in reverse order of power, and the energy storage machine that is matched and sorted based on the demand quantity value and the demand power value is discharged.

[0030] It should be noted that in this embodiment, the energy storage system is charged and discharged at the same time, which is usually called "bidirectional charging and discharging" or parallel charging and discharging. In the first time period, when the energy storage machine is charged and discharged in parallel, the single energy storage machine with the largest battery capacity in the overall energy storage machine is discharged based on the single user demand response. At this time, the battery capacity of the energy storage machine is charged at a low price and can be used for commercial discharge to gain more profits. Based on the multi-user demand identification of the demand quantity value and the demand power value, it is necessary to arrange the overall energy storage machine in positive order of power, and the order is matched based on the demand quantity value and the demand power value. The energy storage machines after discharge are prioritized in combination with the required power value. The energy storage machines in positive order are screened based on the required quantity value, and the energy storage machines are matched according to the required power value. For example, the required quantity value is 5, and the corresponding required power values ​​are "58%, 73%, 64%, 80%, 92%" respectively. Therefore, the energy storage machines arranged in positive order according to the power are A1, A2, A3, A4 and A5. Correspondingly, A1 is paired with 92%, A2 is paired with 80%, A3 is paired with 73%, A4 is paired with 64%, and A5 is paired with 58%.

[0031] According to an embodiment of the present invention, in the process of charge and discharge scheduling management, health management is performed in combination with a single energy storage machine and an overall energy storage machine, specifically including: Monitor the real-time temperature and output voltage of a single energy storage machine, and perform intelligent control and adjustment based on the real-time temperature to complete the health management of the single energy storage machine; Health management is performed based on the total output power of the overall energy storage machine combined with the output voltage of a single energy storage machine, wherein the output voltage of a single energy storage machine is reasonably configured in combination with the total output power to complete the health management of the overall energy storage machine, and the configuration method includes vehicle model configuration and / or battery type configuration.

[0032] It should be noted that, in this embodiment, when performing health management, temperature and voltage can be managed, wherein, specifically, the real-time temperature and output voltage of a single energy storage machine are monitored, so that intelligent control adjustment is performed based on the real-time temperature to complete the health management of the single energy storage machine, and the temperature of the energy storage machine is prevented from being too high or too low; at the same time, health management is performed based on the total output power of the overall energy storage machine combined with the output voltage of the single energy storage machine, wherein the output voltage of the single energy storage machine is reasonably configured in combination with the total output power to complete the overall energy storage machine health management, and the configuration method includes vehicle type configuration and / or battery type configuration. Specifically, the above embodiment illustrates that when power adjustment is performed, average regulation or differential regulation is included, wherein power regulation is to regulate with output voltage, and when average regulation is performed, the average output voltage is obtained in combination with the current battery type, so that in the case of full demand, average regulation is used to ensure that each demand is met; and for differential regulation, the voltage requirement corresponding to each vehicle is obtained in combination with the vehicle type configuration, and different voltage requirements are configured based on different vehicles to better cope with the charging needs of vehicles from different manufacturers.

[0033] According to an embodiment of the present invention, the operation log of the energy storage machine is recorded at a preset period, and intelligent energy storage prediction is performed to dynamically adjust the management mechanism, which specifically includes: Record the daily charging and discharging scheduling data and health management data of the energy storage device to obtain a daily log; Based on the period, data landing point mapping is performed on the daily log to obtain periodic regularity data of the current period management mechanism; Intelligent energy storage prediction is performed based on the periodic regular data to dynamically adjust the management mechanism of the next cycle.

[0034] It should be noted that, in this embodiment, 24 hours is used as the recording time of the daily log, and 7 days from Tuesday to Monday is used as the preset cycle to record the daily log. The charging and discharging data and health management data of different dates and different time periods on the date are combined to map the data landing points on the time axis to obtain the periodic regularity data of the current 7-day cycle management mechanism, so as to perform intelligent energy storage prediction based on the periodic regularity data to dynamically adjust the management mechanism of the next cycle, which is mainly reflected in the power adjustment in different time periods and the selection of the energy storage machine charging period.

[0035] It is worth mentioning that the method also includes renewable energy management. In the second time period, when the output voltage of a single energy storage machine is reasonably configured for multiple users in combination with the total output power, renewable energy is used for auxiliary configuration.

[0036] It should be noted that in this embodiment, due to the multi-user power control, this application proposes two methods, one is average control, and the second is differential control. Then, since the output power of the power grid is constant, the differential control method may be turbulent. During the second time period, renewable energy is needed for auxiliary configuration. The power gap can be made up by supplying power to renewable energy. Accordingly, the renewable energy includes photovoltaic energy.

[0037] It is worth mentioning that the method also includes integrated management of photovoltaic energy, specifically including: In the second time period, when charging and discharging different energy storage batteries are managed, integrated management is performed based on the photovoltaic power source, including coordinating the relationship between the current photovoltaic power source and the charging load and coordinating the relationship between the current photovoltaic power source and the energy storage battery.

[0038] It should be noted that, in this embodiment, in the traditional method, the photovoltaic power source directly charges the energy storage battery, and then the energy storage battery discharges the energy. In this embodiment, in the second time period, especially during the low-peak electricity price period, the photovoltaic power source can be used to discharge the load while the energy storage battery of the energy storage machine can be used to discharge the load. The corresponding discharge ratio can be determined based on the current demand quantity value. When the demand quantity value is greater than or equal to the quantity value of the energy storage machine, the ratio is 1:1, and when the demand quantity value is less than the quantity value of the energy storage machine, the ratio is 2:1.

[0039] Figure 2 A block diagram of an EMS energy intelligent storage management system of the present invention is shown.

[0040] like Figure 2 As shown, the present invention discloses an EMS energy intelligent storage management system, including a memory and a processor, wherein the memory includes an EMS energy intelligent storage management method program, and when the EMS energy intelligent storage management method program is executed by the processor, the following steps are implemented: Discharge management based on energy storage machine, in which the discharge power is adaptively adjusted during discharge; Obtain the operating data of different energy storage batteries for charging management, where charging management is combined with discharge demand for balanced management; In the process of charge and discharge scheduling management, health management is carried out by combining individual energy storage machines and overall energy storage machines; The operation log of the energy storage machine is recorded at a preset period, and intelligent energy storage prediction is performed to dynamically adjust the management mechanism.

[0041] It should be noted that, in this embodiment, the energy management system (EMS) is used to manage the energy storage machine (such as the battery energy storage system), which can optimize the energy charging and discharging control, extend the battery life, improve the economy and efficiency of the system, and improve the energy utilization rate in many scenarios. In this embodiment, two management mechanisms are mainly described, one is the charging and discharging management, and the other is the health management. Specifically, the discharge management is based on the energy storage machine, wherein the discharge power is adaptively adjusted during discharge, and when the operating data of different energy storage batteries are obtained for charging management, it is necessary to carry out balanced management in combination with the specific discharge requirements for intelligent deployment; at the same time, in the process of charging and discharging scheduling management, the health management is carried out in combination with the single energy storage machine and the overall energy storage machine, so that the entire operating system is in a safe and stable working state, the energy storage machine operation log is recorded at a preset period, and intelligent energy storage prediction is carried out to dynamically adjust the management mechanism.

[0042] According to an embodiment of the present invention, the energy storage machine-based discharge management, wherein the discharge power is adaptively adjusted during discharge, specifically includes: A charging load capacity value is obtained based on user demand, wherein the user demand includes single-user demand and / or multi-user demand, and adaptive discharge power adjustment is performed based on the load capacity value, wherein: Adjusting power based on single user demand, wherein the charging power value of a single user is obtained to perform a discharge power response of the single energy storage machine; Adjusting power based on multi-user demand, wherein the type and operation period of the multi-user demand are obtained to adjust the power response of the overall energy storage machine; Multi-objective optimization adjustment, when adjusting the power response to multiple user needs, the target power of a single energy storage machine is adjusted based on the real-time power of the overall energy storage machine.

[0043] It should be noted that, in this embodiment, how to perform discharge management is specifically described, and three adjustment measures are given, one of which is to adjust power based on the needs of a single user, the second is to adjust power based on the needs of multiple users, and the third is multi-objective optimization adjustment. Specifically, the power is adjusted based on the needs of a single user, wherein the charging power value of a single user is obtained to perform the discharge power response of the single energy storage machine so that the charging demand of the single user meets the corresponding power value; at the same time, the power is adjusted based on the needs of multiple users, wherein the types and operating periods of the needs of multiple users are obtained to adjust the power response of the overall energy storage machine, wherein the charging needs of different users are used to adjust the power response of the energy storage machine. Adjust the power response of the overall energy storage machine in different time periods. Specifically, the power response of the overall energy storage machine is obtained based on the comprehensive charging needs of users during the daytime and nighttime periods to meet the electricity demand in different time periods, and multi-objective optimization adjustment. When adjusting the power response to multi-user needs, the target power of a single energy storage machine is adjusted based on the real-time power of the overall energy storage machine. Since the total input power of the overall energy storage machine is constant, it is necessary to perform statistics based on the discharge objects (vehicles) connected to the single energy storage machine in real time in multi-user applications based on multi-objective optimization adjustment, and perform average regulation or differential regulation on the overall energy storage machine.

[0044] According to an embodiment of the present invention, the acquisition of operating data of different energy storage batteries for charging management specifically includes: The energy storage device is charged and managed based on a preset time period, wherein the preset time period includes a first time period and a second time period, wherein: Performing charging management on the energy storage machine based on the first time period, where the first time period includes a low-peak electricity price time period; The energy storage machine is charged and managed based on the second time period, where the second time period includes a daytime experience time period.

[0045] It should be noted that, in this embodiment, the first time period is night time, and the second time period is day time. When the energy storage machine is charged and managed, the energy storage machine is charged and managed based on the first time period, and the first time period includes a low-peak electricity price time period, so that charging is performed when the electricity price is low, reducing the storage cost, and discharging is performed during the peak electricity consumption during the day; the energy storage machine is charged and managed based on the second time period, and the second time period includes a daytime experience time period, wherein the daytime experience time period is a time period with low electricity demand during the non-low-peak period during the day and a low-peak electricity price period during the day, and the daytime discharge demand is met by charging during the low-peak electricity price and charging when the demand is low.

[0046] According to an embodiment of the present invention, charging management is combined with discharging demand to perform balanced management, specifically including: When the energy storage devices are charged and discharged in parallel, balanced management is performed based on the current time period and the user's needs, wherein: In the first time period, the single energy storage machine with the largest battery capacity in the overall energy storage machine is discharged based on the single-user demand response; the demand quantity value and the demand power value are identified based on the multi-user demand, and the overall energy storage machine is arranged in positive order of power, and the energy storage machine after the order is matched based on the demand quantity value and the demand power value is discharged; In the second time period, based on the single-user demand response, the single energy storage machine with the smallest battery capacity in the overall energy storage machine is discharged; based on the multi-user demand, the demand quantity value and the demand power value are identified, and the overall energy storage machine is arranged in reverse order of power, and the energy storage machine that is matched and sorted based on the demand quantity value and the demand power value is discharged.

[0047] It should be noted that in this embodiment, the energy storage system is charged and discharged at the same time, which is usually called "bidirectional charging and discharging" or parallel charging and discharging. In the first time period, when the energy storage machine is charged and discharged in parallel, the single energy storage machine with the largest battery capacity in the overall energy storage machine is discharged based on the single user demand response. At this time, the battery capacity of the energy storage machine is charged at a low price and can be used for commercial discharge to gain more profits. Based on the multi-user demand identification of the demand quantity value and the demand power value, it is necessary to arrange the overall energy storage machine in positive order of power, and the order is matched based on the demand quantity value and the demand power value. The energy storage machines after discharge are prioritized in combination with the required power value. The energy storage machines in positive order are screened based on the required quantity value, and the energy storage machines are matched according to the required power value. For example, the required quantity value is 5, and the corresponding required power values ​​are "58%, 73%, 64%, 80%, 92%" respectively. Therefore, the energy storage machines arranged in positive order according to the power are A1, A2, A3, A4 and A5. Correspondingly, A1 is paired with 92%, A2 is paired with 80%, A3 is paired with 73%, A4 is paired with 64%, and A5 is paired with 58%.

[0048] According to an embodiment of the present invention, in the process of charge and discharge scheduling management, health management is performed in combination with a single energy storage machine and an overall energy storage machine, specifically including: Monitor the real-time temperature and output voltage of a single energy storage machine, and perform intelligent control and adjustment based on the real-time temperature to complete the health management of the single energy storage machine; Health management is performed based on the total output power of the overall energy storage machine combined with the output voltage of a single energy storage machine, wherein the output voltage of a single energy storage machine is reasonably configured in combination with the total output power to complete the health management of the overall energy storage machine, and the configuration method includes vehicle model configuration and / or battery type configuration.

[0049] It should be noted that, in this embodiment, when performing health management, temperature and voltage can be managed, wherein, specifically, the real-time temperature and output voltage of a single energy storage machine are monitored, so that intelligent control adjustment is performed based on the real-time temperature to complete the health management of the single energy storage machine, and the temperature of the energy storage machine is prevented from being too high or too low; at the same time, health management is performed based on the total output power of the overall energy storage machine combined with the output voltage of the single energy storage machine, wherein the output voltage of the single energy storage machine is reasonably configured in combination with the total output power to complete the overall energy storage machine health management, and the configuration method includes vehicle type configuration and / or battery type configuration. Specifically, the above embodiment illustrates that when power adjustment is performed, average regulation or differential regulation is included, wherein power regulation is to regulate with output voltage, and when average regulation is performed, the average output voltage is obtained in combination with the current battery type, so that in the case of full demand, average regulation is used to ensure that each demand is met; and for differential regulation, the voltage requirement corresponding to each vehicle is obtained in combination with the vehicle type configuration, and different voltage requirements are configured based on different vehicles to better cope with the charging needs of vehicles from different manufacturers.

[0050] According to an embodiment of the present invention, the operation log of the energy storage machine is recorded at a preset period, and intelligent energy storage prediction is performed to dynamically adjust the management mechanism, which specifically includes: Record the daily charging and discharging scheduling data and health management data of the energy storage device to obtain a daily log; Based on the period, data landing point mapping is performed on the daily log to obtain periodic regularity data of the current period management mechanism; Intelligent energy storage prediction is performed based on the periodic regular data to dynamically adjust the management mechanism of the next cycle.

[0051] It should be noted that, in this embodiment, 24 hours is used as the recording time of the daily log, and 7 days from Tuesday to Monday is used as the preset cycle to record the daily log. The charging and discharging data and health management data of different dates and different time periods on the date are combined to map the data landing points on the time axis to obtain the periodic regularity data of the current 7-day cycle management mechanism, so as to perform intelligent energy storage prediction based on the periodic regularity data to dynamically adjust the management mechanism of the next cycle, which is mainly reflected in the power adjustment in different time periods and the selection of the energy storage machine charging period.

[0052] It is worth mentioning that the method also includes renewable energy management. In the second time period, when the output voltage of a single energy storage machine is reasonably configured for multiple users in combination with the total output power, renewable energy is used for auxiliary configuration.

[0053] It should be noted that in this embodiment, due to the multi-user power control, this application proposes two methods, one is average control, and the second is differential control. Then, since the output power of the power grid is constant, the differential control method may be turbulent. During the second time period, renewable energy is needed for auxiliary configuration. The power gap can be made up by supplying power to renewable energy. Accordingly, the renewable energy includes photovoltaic energy.

[0054] It is worth mentioning that the method also includes integrated management of photovoltaic energy, specifically including: In the second time period, when charging and discharging different energy storage batteries are managed, integrated management is performed based on the photovoltaic power source, including coordinating the relationship between the current photovoltaic power source and the charging load and coordinating the relationship between the current photovoltaic power source and the energy storage battery.

[0055] It should be noted that, in this embodiment, in the traditional method, the photovoltaic power source directly charges the energy storage battery, and then the energy storage battery discharges the energy. In this embodiment, in the second time period, especially during the low-peak electricity price period, the photovoltaic power source can be used to discharge the load while the energy storage battery of the energy storage machine can be used to discharge the load. The corresponding discharge ratio can be determined based on the current demand quantity value. When the demand quantity value is greater than or equal to the quantity value of the energy storage machine, the ratio is 1:1, and when the demand quantity value is less than the quantity value of the energy storage machine, the ratio is 2:1.

[0056] The third aspect of the present invention provides a computer-readable storage medium, which includes an EMS energy intelligent energy storage management method program. When the EMS energy intelligent energy storage management method program is executed by a processor, the steps of an EMS energy intelligent energy storage management method as described in any one of the above items are implemented.

[0057] The present invention discloses an EMS energy intelligent storage management method, system and readable storage medium, which can perform charging and discharging management and health management of energy storage machines under the control and management of EMS, can effectively dispatch energy flow, and can extend the life of equipment while achieving intelligent dispatching and allocation goals by continuously and dynamically optimizing and adjusting management measures.

[0058] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0059] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0060] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0061] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: a mobile storage device, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0062] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

Claims

1. An EMS energy intelligent storage management method, characterized in that: The following steps are involved: Discharge management based on energy storage machine, in which the discharge power is adaptively adjusted during discharge; Obtain the operating data of different energy storage batteries for charging management, where charging management is combined with discharge demand for balanced management; In the process of charge and discharge scheduling management, health management is carried out by combining individual energy storage machines and overall energy storage machines; The operation log of the energy storage machine is recorded at a preset period, and intelligent energy storage prediction is performed to dynamically adjust the management mechanism.

2. The EMS energy intelligent storage management method according to claim 1, characterized in that: The energy storage machine-based discharge management, wherein the discharge power is adaptively adjusted during discharge, specifically includes: A charging load capacity value is obtained based on user demand, wherein the user demand includes single-user demand and / or multi-user demand, and adaptive discharge power adjustment is performed based on the load capacity value, wherein: Adjusting power based on single user demand, wherein the charging power value of a single user is obtained to perform a discharge power response of the single energy storage machine; Adjusting power based on multi-user demand, wherein the type and operation period of the multi-user demand are obtained to adjust the power response of the overall energy storage machine; Multi-objective optimization adjustment, when adjusting the power response to multiple user needs, the target power of a single energy storage machine is adjusted based on the real-time power of the overall energy storage machine.

3. The EMS energy intelligent storage management method according to claim 2 is characterized in that: The obtaining of operating data of different energy storage batteries for charging management specifically includes: The energy storage device is charged and managed based on a preset time period, wherein the preset time period includes a first time period and a second time period, wherein: Performing charging management on the energy storage machine based on the first time period, where the first time period includes a low-peak electricity price time period; The energy storage machine is charged and managed based on the second time period, where the second time period includes a daytime experience time period.

4. The EMS energy intelligent storage management method according to claim 3 is characterized in that: When managing charging, balance management is performed in combination with discharge requirements, including: When the energy storage devices are charged and discharged in parallel, balanced management is performed based on the current time period and the user's needs, wherein: In the first time period, the single energy storage machine with the largest battery capacity in the overall energy storage machine is discharged based on the single-user demand response; the demand quantity value and the demand power value are identified based on the multi-user demand, and the overall energy storage machine is arranged in positive order of power, and the energy storage machine after the order is matched based on the demand quantity value and the demand power value is discharged; In the second time period, based on the single-user demand response, the single energy storage machine with the smallest battery capacity in the overall energy storage machine is discharged; based on the multi-user demand, the demand quantity value and the demand power value are identified, and the overall energy storage machine is arranged in reverse order of power, and the energy storage machine that is matched and sorted based on the demand quantity value and the demand power value is discharged.

5. The EMS energy intelligent storage management method according to claim 4 is characterized in that: In the process of charge and discharge scheduling management, health management is carried out in combination with individual energy storage devices and overall energy storage devices, including: Monitor the real-time temperature and output voltage of a single energy storage machine, and perform intelligent control and adjustment based on the real-time temperature to complete the health management of the single energy storage machine; Health management is performed based on the total output power of the overall energy storage machine combined with the output voltage of a single energy storage machine, wherein the output voltage of a single energy storage machine is reasonably configured in combination with the total output power to complete the health management of the overall energy storage machine, and the configuration method includes vehicle model configuration and / or battery type configuration.

6. The EMS energy intelligent storage management method according to claim 5, characterized in that: The energy storage machine operation log is recorded at a preset period, and intelligent energy storage prediction is performed to dynamically adjust the management mechanism, including: Record the daily charging and discharging scheduling data and health management data of the energy storage device to obtain a daily log; Based on the period, data landing point mapping is performed on the daily log to obtain periodic regularity data of the current period management mechanism; Intelligent energy storage prediction is performed based on the periodic regular data to dynamically adjust the management mechanism of the next cycle.

7. An EMS energy intelligent storage management system, characterized in that: The invention comprises a memory and a processor, wherein the memory comprises an EMS energy intelligent energy storage management method program, and when the EMS energy intelligent energy storage management method program is executed by the processor, the following steps are implemented: Discharge management based on energy storage machine, in which the discharge power is adaptively adjusted during discharge; Obtain the operating data of different energy storage batteries for charging management, where charging management is combined with discharge demand for balanced management; In the process of charge and discharge scheduling management, health management is carried out by combining individual energy storage machines and overall energy storage machines; The operation log of the energy storage machine is recorded at a preset period, and intelligent energy storage prediction is performed to dynamically adjust the management mechanism.

8. The EMS energy intelligent storage management system according to claim 7 is characterized in that: The energy storage machine-based discharge management, wherein the discharge power is adaptively adjusted during discharge, specifically includes: A charging load capacity value is obtained based on user demand, wherein the user demand includes single-user demand and / or multi-user demand, and adaptive discharge power adjustment is performed based on the load capacity value, wherein: Adjusting power based on single user demand, wherein the charging power value of a single user is obtained to perform a discharge power response of the single energy storage machine; Adjusting power based on multi-user demand, wherein the type and operation period of the multi-user demand are obtained to adjust the power response of the overall energy storage machine; Multi-objective optimization adjustment, when adjusting the power response to multiple user needs, the target power of a single energy storage machine is adjusted based on the real-time power of the overall energy storage machine.

9. The EMS energy intelligent storage management system according to claim 8 is characterized in that: The obtaining of operating data of different energy storage batteries for charging management specifically includes: The energy storage device is charged and managed based on a preset time period, wherein the preset time period includes a first time period and a second time period, wherein: Performing charging management on the energy storage machine based on the first time period, where the first time period includes a low-peak electricity price time period; The energy storage machine is charged and managed based on the second time period, where the second time period includes a daytime experience time period.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes an EMS energy intelligent energy storage management method program. When the EMS energy intelligent energy storage management method program is executed by a processor, the steps of an EMS energy intelligent energy storage management method as described in any one of claims 1 to 6 are implemented.

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