A method and system for managing and optimizing commercial energy storage systems

Abstract

This invention provides a management optimization method and system for industrial and commercial energy storage systems, comprising: real-time acquisition of business load demand information and the state of charge of the industrial and commercial energy storage system based on sensors, and determination of the charging and discharging nodes of the industrial and commercial energy storage system in combination with the performance parameters of each energy storage component in the system; control of charging and discharging of each energy storage component based on the charging and discharging nodes, and real-time monitoring and health status analysis of the operating parameters of each energy storage component; identification of faulty components in the industrial and commercial energy storage system based on the health status analysis results, and operation and maintenance management of the faulty components. This ensures the operational reliability of the industrial and commercial energy storage system, improves the management effect of the system, and ensures the maximum energy utilization rate of the system.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a management optimization method and system for industrial and commercial energy storage systems. Background Technology

[0002] Currently, with the continuous development of power technology, the demand for electricity and the requirements for management in daily life are increasing. Industrial and commercial energy storage systems can play an important role in demand response and improving power quality. Therefore, effective management of industrial and commercial energy storage systems is particularly important.

[0003] However, the charging and discharging strategies of traditional industrial and commercial energy storage systems are not flexible enough. They cannot be dynamically adjusted according to real-time electricity prices, load demand, and the status of the energy storage system itself. The management strategies for industrial and commercial energy storage systems are relatively simple and cannot maximize the utilization of energy in industrial and commercial energy storage systems. Moreover, when conducting charging and discharging management, it is not possible to monitor and control the charging and discharging process of energy storage components in detail based on the performance parameters of the energy storage components. Furthermore, the existing energy storage management system does not monitor the health status of energy storage equipment accurately enough, resulting in untimely equipment maintenance and greatly reducing the management effectiveness of industrial and commercial energy storage systems.

[0004] Therefore, in order to overcome the above-mentioned defects, the present invention provides a management optimization method and system for industrial and commercial energy storage systems. Summary of the Invention

[0005] This invention provides a management optimization method and system for industrial and commercial energy storage systems. By collecting business load demand information and the state of charge (SOC) of the industrial and commercial energy storage system, and combining this with the performance parameters of the energy storage components, the system accurately and effectively determines the charging and discharging nodes of the system. This enables charging and discharging control of the energy storage components based on these nodes, ensuring dynamic adjustments based on load demand and the system's own state. Furthermore, during the charging and discharging control process, real-time monitoring and health status analysis of each energy storage component facilitates timely and effective identification of faulty components and timely maintenance management. This ensures the operational reliability of the industrial and commercial energy storage system, improves management effectiveness, and maximizes energy utilization within the system.

[0006] This invention provides a management optimization method for industrial and commercial energy storage systems, comprising:

[0007] Step 1: Based on real-time acquisition of business load demand information and the state of charge of industrial and commercial energy storage systems by sensors, and combined with the performance parameters of each energy storage component in the industrial and commercial energy storage system, determine the charging and discharging nodes of the industrial and commercial energy storage system.

[0008] Step 2: Based on the charging and discharging nodes, perform charging and discharging control on each energy storage component, and monitor and analyze the operating parameters and health status of each energy storage component in real time.

[0009] Step 3: Based on the health status analysis results, identify the faulty components in the industrial and commercial energy storage system and carry out operation and maintenance management of the faulty components.

[0010] Preferably, in a management optimization method for industrial and commercial energy storage systems, step 1 involves real-time acquisition of business load demand information and the state of charge of the industrial and commercial energy storage system based on sensors, including:

[0011] The power grid line distribution structure is obtained, and the first business sensor and the first set of key acquisition points corresponding to the business data are determined based on the line distribution structure and monitoring objectives.

[0012] At the same time, the monitoring projects for industrial and commercial energy storage systems are identified, and the corresponding second business sensors and second key data acquisition point set are determined based on the project attributes of the monitoring projects.

[0013] Based on the first set of key acquisition points and the second set of key acquisition points, deployment guidance is provided for the first service sensor and the second service sensor respectively, and service parameters are adapted for the first service sensor and the second service sensor based on the deployment guidance results.

[0014] Based on the results of business parameter adaptation, the power grid and energy storage system are monitored in real time to obtain the corresponding business load demand information and charge status.

[0015] Preferably, a management optimization method for industrial and commercial energy storage systems obtains corresponding business load demand information and state of charge, including:

[0016] Based on the working time series of the sensor, the timestamps corresponding to the business load demand and the state of charge are determined, and the business load demand and the state of charge at different times are distinguished based on the timestamps.

[0017] A time tag is generated for each moment based on the timestamp, and the time tag is used to associate and mark the business load demand and charge status at different moments according to the differentiation results.

[0018] Based on the association tagging results, the business load demand and charge status at different times are distinguished and cached.

[0019] Preferably, in a management optimization method for industrial and commercial energy storage systems, step 1 involves determining the charging and discharging nodes of the industrial and commercial energy storage system based on the performance parameters of each energy storage component, including:

[0020] The structure of the industrial and commercial energy storage system is traversed to determine the structure of the energy storage components in the industrial and commercial energy storage system, and the performance parameters of each energy storage component are extracted based on the structure of the energy storage components.

[0021] The performance parameters are analyzed to determine the charge and discharge efficiency curves of each energy storage component, and the charge and discharge characteristics of each energy storage component are determined based on the charge and discharge efficiency curves.

[0022] The charging and discharging characteristics are matched with the applicable business scenarios, and the parameter ranges of each energy storage component are divided under different applicable business scenarios based on the matching results. The parameter range division results are used as the first node analysis indicator.

[0023] At the same time, the historical database is accessed to retrieve real-time electricity price data in the power grid for multiple time periods, and the peak and off-peak electricity price time intervals are determined based on the target values ​​of the real-time electricity price data.

[0024] The peak electricity price period and the off-peak electricity price period are used as the second node analysis indicators;

[0025] Based on business load demand information, the state of charge of industrial and commercial energy storage systems, and the first and second node analysis indicators, the charging and discharging time nodes and corresponding charging and discharging power of industrial and commercial energy storage systems under different business application scenarios are determined.

[0026] The charging and discharging nodes of industrial and commercial energy storage systems are obtained based on the charging and discharging time nodes and charging and discharging power.

[0027] Preferably, in a management optimization method for industrial and commercial energy storage systems, step 2 involves controlling the charging and discharging of each energy storage component based on charging and discharging nodes, including:

[0028] The obtained charging and discharging nodes are used to determine the state of charge of the industrial and commercial energy storage system in real time when the power grid needs to perform a discharge operation.

[0029] The discharge power of the industrial and commercial energy storage system is corrected in real time based on the real-time determined state of charge and grid load demand, and the discharge task is allocated to each energy storage component in the industrial and commercial energy storage system based on the real-time correction results and the determined charging and discharging nodes.

[0030] Based on the discharge task allocation results, coordinated discharge control is performed on each energy storage component.

[0031] Simultaneously, based on the results of coordinated discharge control, the relative magnitude relationship between the real-time state of charge and the preset lower limit in the industrial and commercial energy storage system is determined, and the discharge process of the industrial and commercial energy storage system is stopped when the real-time state of charge is less than the preset lower limit.

[0032] Based on the stopping results, the optimal charging time for the industrial and commercial energy storage system is determined according to the charging and discharging nodes, and slow charging control is implemented for the industrial and commercial energy storage system when the optimal charging time has not been reached at the current time.

[0033] When the charging time is reached, the slow charging control is terminated, and the current charging power is adjusted based on the charging power range that the industrial and commercial energy storage system can accept. Based on the adjustment result, the industrial and commercial energy storage system is subjected to fast charging control.

[0034] Preferably, in a management optimization method for industrial and commercial energy storage systems, step 2 involves real-time monitoring and health status analysis of the operating parameters of each energy storage component, including:

[0035] A distributed monitoring mechanism is constructed based on the structure of each energy storage component in the industrial and commercial energy storage system. The charging and discharging process of each energy storage component is monitored in real time based on the distributed monitoring mechanism to obtain the corresponding operating parameters.

[0036] Meanwhile, based on the configuration parameters of each energy storage component, the status monitoring items and corresponding safe operation thresholds are determined, and a health status assessment model is constructed based on the status monitoring items and safe operation thresholds.

[0037] The monitored operating parameters are analyzed based on the health status assessment model to obtain the operating status of each energy storage component. The operating status is then compared with the corresponding safe operating threshold to obtain the health status of each energy storage component.

[0038] Preferably, in a management optimization method for industrial and commercial energy storage systems, step 3 involves identifying faulty components in the industrial and commercial energy storage system based on health status analysis results, and then performing operation and maintenance management on these faulty components, including:

[0039] The obtained health status analysis results are obtained and read to identify energy storage components with abnormal health status in industrial and commercial energy storage systems, and these components are identified as faulty components.

[0040] Based on the health status analysis results, the fault type and fault level of the faulty component are determined, and the target operation and maintenance management strategy is matched from the preset operation and maintenance management strategy library based on the fault type and fault level.

[0041] The faulty components are managed based on the target operation and maintenance management strategy, and the status of the faulty components is re-inspected after the operation and maintenance management is completed.

[0042] When the status re-inspection results of the faulty component meet the normal operating standards, the operation and maintenance management is deemed qualified.

[0043] Preferably, a management optimization method for industrial and commercial energy storage systems determines that the operation and maintenance management is qualified when the status re-inspection results of the faulty component meet the normal operating standards, including:

[0044] The operation and maintenance management of industrial and commercial energy storage components is monitored throughout the entire process, and a dynamic registration form is built based on the full process monitoring.

[0045] When industrial and commercial energy storage components are subject to operation and maintenance management, the operation and maintenance management data for each operation and maintenance management session will be sequentially registered in the dynamic registration table.

[0046] The operation and maintenance management display table is obtained based on the order and level results, and then sent to the management terminal for visual viewing and management based on the viewing requirements of the management terminal.

[0047] This invention provides a management and optimization system for industrial and commercial energy storage systems, comprising:

[0048] The charge / discharge node determination module is used to determine the charge / discharge nodes of the industrial and commercial energy storage system based on real-time data collection of business load demand information and the state of charge of the industrial and commercial energy storage system, combined with the performance parameters of each energy storage component in the industrial and commercial energy storage system.

[0049] The charge and discharge management module is used to control the charge and discharge of each energy storage component based on the charge and discharge nodes, and to monitor the operating parameters and health status of each energy storage component in real time.

[0050] The operation and maintenance management module is used to identify faulty components in industrial and commercial energy storage systems based on health status analysis results, and to perform operation and maintenance management on these faulty components.

[0051] Preferably, a commercial and industrial energy storage system management and optimization system, including a charge / discharge node determination module, comprises:

[0052] Sensor and location determination unit, used for:

[0053] The power grid line distribution structure is obtained, and the first business sensor and the first set of key acquisition points corresponding to the business data are determined based on the line distribution structure and monitoring objectives.

[0054] At the same time, the monitoring projects for industrial and commercial energy storage systems are identified, and the corresponding second business sensors and second key data acquisition point set are determined based on the project attributes of the monitoring projects.

[0055] Monitoring unit, used for:

[0056] Based on the first set of key acquisition points and the second set of key acquisition points, deployment guidance is provided for the first service sensor and the second service sensor respectively, and service parameters are adapted for the first service sensor and the second service sensor based on the deployment guidance results.

[0057] Based on the results of business parameter adaptation, the power grid and energy storage system are monitored in real time to obtain the corresponding business load demand information and charge status.

[0058] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0059] By collecting business load demand information and the state of charge of industrial and commercial energy storage systems, and combining this with the performance parameters of energy storage components, the charging and discharging nodes of industrial and commercial energy storage systems can be accurately and effectively determined. This enables charging and discharging control of energy storage components based on these nodes, ensuring dynamic adjustments based on load demand and the system's own state. Furthermore, during the charging and discharging control process, real-time monitoring and health status analysis of each energy storage component facilitates the timely and effective identification of faulty components and enables timely operation and maintenance management. This ensures the operational reliability of industrial and commercial energy storage systems, improves management effectiveness, and guarantees maximum energy utilization within these systems.

[0060] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in this application.

[0061] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0062] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0063] Figure 1 This is a flowchart of a management optimization method for industrial and commercial energy storage systems according to an embodiment of the present invention;

[0064] Figure 2 This is a flowchart of step 2 in a management optimization method for industrial and commercial energy storage systems according to Embodiment 6 of the present invention;

[0065] Figure 3 This is a structural diagram of a commercial and industrial energy storage system management optimization system according to an embodiment of the present invention. Detailed Implementation

[0066] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0067] Example 1:

[0068] This embodiment provides a management optimization method for industrial and commercial energy storage systems, such as... Figure 1 As shown, it includes:

[0069] Step 1: Based on real-time acquisition of business load demand information and the state of charge of industrial and commercial energy storage systems by sensors, and combined with the performance parameters of each energy storage component in the industrial and commercial energy storage system, determine the charging and discharging nodes of the industrial and commercial energy storage system.

[0070] Step 2: Based on the charging and discharging nodes, perform charging and discharging control on each energy storage component, and monitor and analyze the operating parameters and health status of each energy storage component in real time.

[0071] Step 3: Based on the health status analysis results, identify the faulty components in the industrial and commercial energy storage system and carry out operation and maintenance management of the faulty components.

[0072] In this embodiment, the service load demand information refers to the current load situation in the power grid, that is, the required power demand.

[0073] In this embodiment, the state of charge refers to the percentage of the current electricity in the industrial and commercial energy storage system relative to the rated electricity, such as a current state of charge of 50%.

[0074] In this embodiment, the performance parameters refer to the charge and discharge efficiencies of different energy storage components included in the industrial and commercial energy storage system. For example, lithium-ion batteries have the characteristics of high energy density and high charge and discharge efficiency, and are suitable for rapid response to load demand for charging and discharging in a short period of time. Lead-acid batteries have lower cost and better safety, and can be used for long-term energy storage needs.

[0075] In this embodiment, the charge / discharge node refers to the time point at which the industrial and commercial energy storage system performs charging and discharging, as well as the corresponding charging and discharging power.

[0076] In this embodiment, health status analysis refers to monitoring and analyzing the voltage, current, and temperature of each energy storage component, with the aim of timely detecting any abnormal components in the energy storage components.

[0077] In this embodiment, the faulty component refers to a component in the energy storage module whose operating state does not meet the preset requirements.

[0078] In this embodiment, operation and maintenance management refers to operations such as repairing or replacing faulty components.

[0079] The beneficial effects of the above technical solution are as follows: By collecting business load demand information and the state of charge of the industrial and commercial energy storage system, and combining the performance parameters of the energy storage components, the charging and discharging nodes of the industrial and commercial energy storage system can be accurately and effectively determined. This enables the charging and discharging control of the energy storage components based on the charging and discharging nodes, ensuring dynamic adjustment according to load demand and the state of the energy storage system itself. Secondly, during the charging and discharging control process, real-time monitoring and health status analysis of each energy storage component are performed, facilitating the timely and effective identification of faulty components and enabling timely operation and maintenance management. This ensures the operational reliability of the industrial and commercial energy storage system, improves the management effect of the industrial and commercial energy storage system, and ensures the maximum energy utilization rate of the industrial and commercial energy storage system.

[0080] Example 2:

[0081] Based on Example 1, this example provides a management optimization method for industrial and commercial energy storage systems. Step 1 involves real-time acquisition of business load demand information and the state of charge of the industrial and commercial energy storage system using sensors, including:

[0082] The power grid line distribution structure is obtained, and the first business sensor and the first set of key acquisition points corresponding to the business data are determined based on the line distribution structure and monitoring objectives.

[0083] At the same time, the monitoring projects for industrial and commercial energy storage systems are identified, and the corresponding second business sensors and second key data acquisition point set are determined based on the project attributes of the monitoring projects.

[0084] Based on the first set of key acquisition points and the second set of key acquisition points, deployment guidance is provided for the first service sensor and the second service sensor respectively, and service parameters are adapted for the first service sensor and the second service sensor based on the deployment guidance results.

[0085] Based on the results of business parameter adaptation, the power grid and energy storage system are monitored in real time to obtain the corresponding business load demand information and charge status.

[0086] In this embodiment, the line distribution structure refers to the specific details of the line distribution and structure in the power grid.

[0087] In this embodiment, the monitoring objective refers to the items that need to be monitored and the monitoring results that need to be achieved.

[0088] In this embodiment, the first business sensor refers to the sensor required for monitoring business data in the power grid.

[0089] In this embodiment, the first set of key acquisition points refers to the location where the first service sensor is deployed, that is, the effective monitoring point corresponding to when the first service sensor can perform the monitoring task.

[0090] In this embodiment, the monitoring project refers to the monitoring business when monitoring industrial and commercial energy storage systems, that is, the types of business that need to be monitored.

[0091] In this embodiment, project attributes refer to the project type of the monitored project and the specific characteristics of the monitored project.

[0092] In this embodiment, the second operational sensor refers to the sensor required to perform monitoring of industrial and commercial energy storage systems.

[0093] In this embodiment, the second set of key acquisition points refers to the effective locations where the second service sensor is deployed.

[0094] The beneficial effects of the above technical solution are: by identifying the sensors and corresponding key points required for monitoring the power grid and industrial and commercial energy storage systems, and then guiding the deployment of sensors based on the key points, the comprehensiveness and reliability of the final collected business load demand information and charge status are ensured.

[0095] Example 3:

[0096] Based on Example 2, this example provides a management optimization method for industrial and commercial energy storage systems, which obtains corresponding business load demand information and state of charge, including:

[0097] Based on the working time series of the sensor, the timestamps corresponding to the business load demand and the state of charge are determined, and the business load demand and the state of charge at different times are distinguished based on the timestamps.

[0098] A time tag is generated for each moment based on the timestamp, and the time tag is used to associate and mark the business load demand and charge status at different moments according to the differentiation results.

[0099] Based on the association tagging results, the business load demand and charge status at different times are distinguished and cached.

[0100] In this embodiment, the timestamp refers to the specific collection time information corresponding to the collected service load demand and charge status.

[0101] In this embodiment, the time tag is generated based on the timestamp and is a marker symbol used to distinguish the service load demand and charge status at different times.

[0102] In this embodiment, the association marker refers to associating the service load demand and charge status under the same timestamp, thereby facilitating the determination of the service load demand and charge status at the same moment.

[0103] The beneficial effects of the above technical solution are: by distinguishing and caching the service load demand and charge status collected at different times, it is easier to determine the charging and discharging control strategy at different times, so as to adjust the status in a timely manner according to the demand, and ensure the accuracy and reliability of charging and discharging management.

[0104] Example 4:

[0105] Based on Example 1, this example provides a management optimization method for industrial and commercial energy storage systems. Step 1 involves determining the charging and discharging nodes of the industrial and commercial energy storage system by combining the performance parameters of each energy storage component, including:

[0106] The structure of the industrial and commercial energy storage system is traversed to determine the structure of the energy storage components in the industrial and commercial energy storage system, and the performance parameters of each energy storage component are extracted based on the structure of the energy storage components.

[0107] The performance parameters are analyzed to determine the charge and discharge efficiency curves of each energy storage component, and the charge and discharge characteristics of each energy storage component are determined based on the charge and discharge efficiency curves.

[0108] The charging and discharging characteristics are matched with the applicable business scenarios, and the parameter ranges of each energy storage component are divided under different applicable business scenarios based on the matching results. The parameter range division results are used as the first node analysis indicator.

[0109] At the same time, the historical database is accessed to retrieve real-time electricity price data in the power grid for multiple time periods, and the peak and off-peak electricity price time intervals are determined based on the target values ​​of the real-time electricity price data.

[0110] The peak electricity price period and the off-peak electricity price period are used as the second node analysis indicators;

[0111] Based on business load demand information, the state of charge of industrial and commercial energy storage systems, and the first and second node analysis indicators, the charging and discharging time nodes and corresponding charging and discharging power of industrial and commercial energy storage systems under different business application scenarios are determined.

[0112] The charging and discharging nodes of industrial and commercial energy storage systems are obtained based on the charging and discharging time nodes and charging and discharging power.

[0113] In this embodiment, the energy storage component structure refers to the energy storage components included in an industrial and commercial energy storage system, such as batteries.

[0114] In this embodiment, performance parameters refer to parameters such as the charging and discharging efficiency and energy storage effect of each energy storage component during charging and discharging.

[0115] In this embodiment, charge and discharge characteristics refer to the charging and discharging speed of each energy storage component. For example, lithium batteries can provide rapid discharge in a short time to meet emergency response needs, while lead-acid batteries can provide stable power supply over a long period of time.

[0116] In this embodiment, the applicable business scenario refers to the type or scenario of power dispatch required by the current power grid.

[0117] In this embodiment, parameter range division refers to the division of charging and discharging power or energy release amount of each energy storage component under different business application scenarios.

[0118] In this embodiment, the first node analysis index refers to the result obtained after dividing the parameter range of each energy storage component, including the energy charging and discharging amount of each energy storage component and the corresponding charging and discharging time, etc.

[0119] In this embodiment, real-time electricity price data refers to the electricity price of the power grid at different times, which is related to the amount of electricity and the time of use, and the electricity price rules are fixed.

[0120] In this embodiment, the second node analysis indicator refers to the peak electricity price period and the off-peak electricity price period.

[0121] The beneficial effects of the above technical solution are as follows: By performing a structural traversal of the industrial and commercial energy storage system, the performance parameters of each energy storage component can be determined, thereby determining the charging and discharging characteristics of each energy storage component, providing data support for determining the charging and discharging nodes. Secondly, by matching the charging and discharging characteristics with the applicable business scenarios, the charging and discharging efficiency under different applicable business scenarios can be determined. At the same time, considering the peak and off-peak electricity price periods, the charging and discharging nodes of the industrial and commercial energy storage system can be accurately and effectively determined, providing convenience and guarantee for the subsequent charging and discharging management of the industrial and commercial energy storage system.

[0122] Example 5:

[0123] Based on Example 1, this example provides a management optimization method for industrial and commercial energy storage systems. In step 2, charging and discharging control of each energy storage component is performed based on the charging and discharging nodes, including:

[0124] The obtained charging and discharging nodes are used to determine the state of charge of the industrial and commercial energy storage system in real time when the power grid needs to perform a discharge operation.

[0125] The discharge power of the industrial and commercial energy storage system is corrected in real time based on the real-time determined state of charge and grid load demand, and the discharge task is allocated to each energy storage component in the industrial and commercial energy storage system based on the real-time correction results and the determined charging and discharging nodes.

[0126] Based on the discharge task allocation results, coordinated discharge control is performed on each energy storage component.

[0127] Simultaneously, based on the results of coordinated discharge control, the relative magnitude relationship between the real-time state of charge and the preset lower limit in the industrial and commercial energy storage system is determined, and the discharge process of the industrial and commercial energy storage system is stopped when the real-time state of charge is less than the preset lower limit.

[0128] Based on the stopping results, the optimal charging time for the industrial and commercial energy storage system is determined according to the charging and discharging nodes, and slow charging control is implemented for the industrial and commercial energy storage system when the optimal charging time has not been reached at the current time.

[0129] When the charging time is reached, the slow charging control is terminated, and the current charging power is adjusted based on the charging power range that the industrial and commercial energy storage system can accept. Based on the adjustment result, the industrial and commercial energy storage system is subjected to fast charging control.

[0130] In this embodiment, the discharge task allocation refers to the discharge sequence of each energy storage component and the discharge amount of each energy storage component.

[0131] In this embodiment, coordinated discharge control refers to coordinated control of the discharge operation of each energy storage component. That is, when performing a discharge operation, the energy storage component with higher energy storage can discharge first, and then when the average level is reached, the energy storage components can discharge simultaneously.

[0132] In this embodiment, the preset lower limit value is set in advance and is used to characterize the minimum amount of electrical energy that the industrial and commercial energy storage system needs to retain.

[0133] In this embodiment, determining the optimal charging time for the industrial and commercial energy storage system based on the stopping result and the charging / discharging node refers to the period of low electricity prices in the power grid system.

[0134] In this embodiment, slow charging control refers to controlling a small amount of electrical energy in the industrial and commercial energy storage system and limiting the charging power when the optimal charging time has not yet been reached.

[0135] In this embodiment, the chargeable power range refers to the range of charging power values ​​that the industrial and commercial energy storage system can withstand.

[0136] In this embodiment, adjusting the current charging power based on the charging power range of the commercial and industrial energy storage system means adjusting the charging power of the commercial and industrial energy storage system to the maximum within the charging power range.

[0137] The beneficial effects of the above technical solution are: by controlling the charging and discharging of each energy storage component in the industrial and commercial energy storage system according to the obtained charging and discharging nodes, the reliability of the control of the industrial and commercial energy storage system during the discharging and charging stages is ensured, and the charging and discharging efficiency of the industrial and commercial energy storage system is also ensured.

[0138] Example 6:

[0139] Based on Example 1, this example provides a management optimization method for industrial and commercial energy storage systems, such as... Figure 2 As shown, in step 2, the operating parameters and health status analysis of each energy storage component are performed in real time, including:

[0140] Step 201: Based on the structure of each energy storage component in the industrial and commercial energy storage system, construct a distributed monitoring mechanism, and monitor the charging and discharging process of each energy storage component in real time based on the distributed monitoring mechanism to obtain the corresponding operating parameters;

[0141] Step 202: Simultaneously, based on the configuration parameters of each energy storage component, determine the status monitoring items and corresponding safe operation thresholds, and construct a health status assessment model based on the status monitoring items and safe operation thresholds;

[0142] Step 203: Analyze the monitored operating parameters based on the health status assessment model to obtain the operating status of each energy storage component, and compare the operating status with the corresponding safe operating threshold to obtain the health status of each energy storage component.

[0143] In this embodiment, the distributed monitoring mechanism refers to a scheme that monitors each energy storage component simultaneously, and the monitoring of each energy storage component does not affect the other.

[0144] In this embodiment, the configuration parameters refer to the device status parameters of each energy storage component, including the voltage and current values ​​that each energy storage component can withstand.

[0145] In this embodiment, the condition monitoring project refers to the business type of monitoring each energy storage component.

[0146] The beneficial effects of the above technical solution are: by constructing a distributed monitoring mechanism, real-time monitoring of each energy storage component in the industrial and commercial energy storage system can be achieved, thereby determining the operating parameters of each energy storage component, which facilitates health status analysis based on the operating parameters, and ensures the reliability of monitoring the operating status of the industrial and commercial energy storage system.

[0147] Example 7:

[0148] Based on Example 1, this example provides a management optimization method for industrial and commercial energy storage systems. In step 3, faulty components in the industrial and commercial energy storage system are identified based on health status analysis results, and operation and maintenance management of the faulty components is performed, including:

[0149] The obtained health status analysis results are obtained and read to identify energy storage components with abnormal health status in industrial and commercial energy storage systems, and these components are identified as faulty components.

[0150] Based on the health status analysis results, the fault type and fault level of the faulty component are determined, and the target operation and maintenance management strategy is matched from the preset operation and maintenance management strategy library based on the fault type and fault level.

[0151] The faulty components are managed based on the target operation and maintenance management strategy, and the status of the faulty components is re-inspected after the operation and maintenance management is completed.

[0152] When the status re-inspection results of the faulty component meet the normal operating standards, the operation and maintenance management is deemed qualified.

[0153] In this embodiment, an energy storage component with abnormal health status refers to an energy storage component that exhibits abnormal voltage or leakage.

[0154] In this embodiment, the preset operation management strategy library is pre-built and used to store operation management strategies corresponding to various fault types and fault levels.

[0155] In this embodiment, the target operation and maintenance management strategy refers to a solution applicable to resolving the current fault type and fault level.

[0156] In this embodiment, the normal operating standard is set in advance, that is, the operating state of the energy storage component when there are no abnormalities.

[0157] The beneficial effects of the above technical solution are as follows: by identifying faulty components in the industrial and commercial energy storage system based on the health status analysis results, and determining the fault type and fault level of the faulty components, the target operation and maintenance management strategy for the faulty components can be determined based on the fault type and fault level. Finally, the operation and maintenance management of the faulty components can be carried out according to the target operation and maintenance management strategy, and the faulty components can be re-inspected after the operation and maintenance management is completed, thus ensuring the reliability of the operation and maintenance management of the industrial and commercial energy storage system.

[0158] Example 8:

[0159] Based on Example 7, this example provides a management optimization method for industrial and commercial energy storage systems. When the status re-inspection results of a faulty component meet the normal operating standards, the operation and maintenance management is deemed qualified, including:

[0160] The operation and maintenance management of industrial and commercial energy storage components is monitored throughout the entire process, and a dynamic registration form is built based on the full process monitoring.

[0161] When industrial and commercial energy storage components are subject to operation and maintenance management, the operation and maintenance management data for each operation and maintenance management session will be sequentially registered in the dynamic registration table.

[0162] The operation and maintenance management display table is obtained based on the order and level results, and then sent to the management terminal for visual viewing and management based on the viewing requirements of the management terminal.

[0163] The beneficial effects of the above technical solution are: by monitoring the entire process of operation and maintenance, an operation and maintenance management exhibition table for industrial and commercial energy storage systems can be constructed based on the monitoring results. The obtained operation and maintenance management exhibition table can be fed back and visualized for management terminal viewing needs, making it convenient for users to understand the operation status of industrial and commercial energy storage systems in a timely manner.

[0164] Example 9:

[0165] This embodiment provides a management optimization system for industrial and commercial energy storage systems, such as... Figure 3 As shown, it includes:

[0166] The charge / discharge node determination module is used to determine the charge / discharge nodes of the industrial and commercial energy storage system based on real-time data collection of business load demand information and the state of charge of the industrial and commercial energy storage system, combined with the performance parameters of each energy storage component in the industrial and commercial energy storage system.

[0167] The charge and discharge management module is used to control the charge and discharge of each energy storage component based on the charge and discharge nodes, and to monitor the operating parameters and health status of each energy storage component in real time.

[0168] The operation and maintenance management module is used to identify faulty components in industrial and commercial energy storage systems based on health status analysis results, and to perform operation and maintenance management on these faulty components.

[0169] The beneficial effects of the above technical solution are as follows: By collecting business load demand information and the state of charge of the industrial and commercial energy storage system, and combining the performance parameters of the energy storage components, the charging and discharging nodes of the industrial and commercial energy storage system can be accurately and effectively determined. This enables the charging and discharging control of the energy storage components based on the charging and discharging nodes, ensuring dynamic adjustment according to load demand and the state of the energy storage system itself. Secondly, during the charging and discharging control process, real-time monitoring and health status analysis of each energy storage component are performed, facilitating the timely and effective identification of faulty components and enabling timely operation and maintenance management. This ensures the operational reliability of the industrial and commercial energy storage system, improves the management effect of the industrial and commercial energy storage system, and ensures the maximum energy utilization rate of the industrial and commercial energy storage system.

[0170] Example 10:

[0171] Based on Example 9, this example provides a management optimization system for industrial and commercial energy storage systems, characterized in that the charge / discharge node determination module includes:

[0172] Sensor and location determination unit, used for:

[0173] The power grid line distribution structure is obtained, and the first business sensor and the first set of key acquisition points corresponding to the business data are determined based on the line distribution structure and monitoring objectives.

[0174] At the same time, the monitoring projects for industrial and commercial energy storage systems are identified, and the corresponding second business sensors and second key data acquisition point set are determined based on the project attributes of the monitoring projects.

[0175] Monitoring unit, used for:

[0176] Based on the first set of key acquisition points and the second set of key acquisition points, deployment guidance is provided for the first service sensor and the second service sensor respectively, and service parameters are adapted for the first service sensor and the second service sensor based on the deployment guidance results.

[0177] Based on the results of business parameter adaptation, the power grid and energy storage system are monitored in real time to obtain the corresponding business load demand information and charge status.

[0178] The beneficial effects of the above technical solution are: by identifying the sensors and corresponding key points required for monitoring the power grid and industrial and commercial energy storage systems, and then guiding the deployment of sensors based on the key points, the comprehensiveness and reliability of the final collected business load demand information and charge status are ensured.

[0179] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A management optimization method for industrial and commercial energy storage systems, characterized in that, include: Step 1: Based on real-time acquisition of business load demand information and the state of charge of industrial and commercial energy storage systems by sensors, and combined with the performance parameters of each energy storage component in the industrial and commercial energy storage system, determine the charging and discharging nodes of the industrial and commercial energy storage system. Step 2: Perform charge and discharge control on each energy storage component based on the charge and discharge nodes, and monitor and analyze the operating parameters and health status of each energy storage component in real time. Step 3: Based on the health status analysis results, identify the faulty components in the industrial and commercial energy storage system and carry out operation and maintenance management of the faulty components; In step 1, the charging and discharging nodes of the industrial and commercial energy storage system are determined based on the performance parameters of each energy storage component, including: The structure of the industrial and commercial energy storage system is traversed to determine the structure of the energy storage components in the system, and the performance parameters of each energy storage component are extracted based on the structure of the energy storage components. The performance parameters are analyzed to determine the charge and discharge efficiency curves of each energy storage component, and the charge and discharge characteristics of each energy storage component are determined based on the charge and discharge efficiency curves. The charging and discharging characteristics are matched with the applicable business scenarios, and the parameter ranges of each energy storage component are divided under different applicable business scenarios based on the matching results. The parameter range division results are used as the first node analysis indicator. At the same time, the historical database is accessed to retrieve real-time electricity price data in the power grid for multiple time periods, and the peak and off-peak electricity price time intervals are determined based on the target values ​​of the real-time electricity price data. The peak electricity price period and the off-peak electricity price period are used as the second node analysis indicators; Based on business load demand information, the state of charge of industrial and commercial energy storage systems, and the first and second node analysis indicators, the charging and discharging time nodes and corresponding charging and discharging power of industrial and commercial energy storage systems under different business application scenarios are determined. The charging and discharging nodes of industrial and commercial energy storage systems are obtained based on the charging and discharging time nodes and charging and discharging power.

2. The management optimization method for industrial and commercial energy storage systems according to claim 1, characterized in that, In step 1, real-time data collection of business load demand information and the state of charge of industrial and commercial energy storage systems is performed based on sensors, including: The power grid line distribution structure is obtained, and the first business sensor and the first set of key acquisition points corresponding to the business data are determined based on the line distribution structure and monitoring objectives. At the same time, the monitoring projects for industrial and commercial energy storage systems are identified, and the corresponding second business sensors and second key data acquisition point set are determined based on the project attributes of the monitoring projects. Based on the first set of key acquisition points and the second set of key acquisition points, deployment guidance is provided for the first service sensor and the second service sensor respectively, and service parameters are adapted for the first service sensor and the second service sensor based on the deployment guidance results. Based on the results of business parameter adaptation, the power grid and energy storage system are monitored in real time to obtain the corresponding business load demand information and charge status.

3. The management optimization method for industrial and commercial energy storage systems according to claim 2, characterized in that, Obtain the corresponding business load demand information and charge status, including: Based on the working time series of the sensor, the timestamps corresponding to the service load demand and the state of charge are determined, and the service load demand and the state of charge at different times are distinguished based on the timestamps. A time tag is generated for each moment based on the timestamp, and the time tag is used to associate and mark the business load demand and charge status at different moments according to the differentiation results. Based on the association tagging results, the business load demand and charge status at different times are distinguished and cached.

4. The management optimization method for industrial and commercial energy storage systems according to claim 1, characterized in that, In step 2, charge and discharge control of each energy storage component is performed based on the charge and discharge nodes, including: The obtained charging and discharging nodes are used to determine the state of charge of the industrial and commercial energy storage system in real time when the power grid needs to perform a discharge operation. The discharge power of the industrial and commercial energy storage system is corrected in real time based on the real-time determined state of charge and grid load demand, and the discharge task is allocated to each energy storage component in the industrial and commercial energy storage system based on the real-time correction results and the determined charging and discharging nodes. Based on the discharge task allocation results, coordinated discharge control is performed on each energy storage component. Simultaneously, based on the results of coordinated discharge control, the relative magnitude relationship between the real-time state of charge and the preset lower limit in the industrial and commercial energy storage system is determined, and the discharge process of the industrial and commercial energy storage system is stopped when the real-time state of charge is less than the preset lower limit. Based on the stopping results, the optimal charging time for the industrial and commercial energy storage system is determined according to the charging and discharging nodes, and slow charging control is implemented for the industrial and commercial energy storage system when the optimal charging time has not been reached at the current time. When the charging time is reached, the slow charging control is terminated, and the current charging power is adjusted based on the charging power range that the industrial and commercial energy storage system can accept. Based on the adjustment result, the industrial and commercial energy storage system is subjected to fast charging control.

5. The management optimization method for industrial and commercial energy storage systems according to claim 1, characterized in that, In step 2, the operating parameters and health status analysis of each energy storage component are performed in real time, including: A distributed monitoring mechanism is constructed based on the structure of each energy storage component in the industrial and commercial energy storage system. The charging and discharging process of each energy storage component is monitored in real time based on the distributed monitoring mechanism to obtain the corresponding operating parameters. Meanwhile, based on the configuration parameters of each energy storage component, the status monitoring items and corresponding safe operation thresholds are determined, and a health status assessment model is constructed based on the status monitoring items and safe operation thresholds. The monitored operating parameters are analyzed based on the health status assessment model to obtain the operating status of each energy storage component. The operating status is then compared with the corresponding safe operating threshold to obtain the health status of each energy storage component.

6. The management optimization method for industrial and commercial energy storage systems according to claim 1, characterized in that, In step 3, based on the health status analysis results, faulty components in the industrial and commercial energy storage system are identified, and operation and maintenance management of these faulty components is carried out, including: The obtained health status analysis results are obtained and read to identify energy storage components with abnormal health status in industrial and commercial energy storage systems, and these components are identified as faulty components. Based on the health status analysis results, the fault type and fault level of the faulty component are determined, and the target operation and maintenance management strategy is matched from the preset operation and maintenance management strategy library based on the fault type and fault level. The faulty components are managed based on the target operation and maintenance management strategy, and the status of the faulty components is re-inspected after the operation and maintenance management is completed. When the status re-inspection results of the faulty component meet the normal operating standards, the operation and maintenance management is deemed qualified.

7. The management optimization method for industrial and commercial energy storage systems according to claim 6, characterized in that, When the status re-inspection results of the faulty component meet the normal operating standards, the operation and maintenance management is deemed qualified, including: The operation and maintenance management of industrial and commercial energy storage components is monitored throughout the entire process, and a dynamic registration form is built based on the full process monitoring. When industrial and commercial energy storage components are subject to operation and maintenance management, the operation and maintenance management data for each operation and maintenance management session will be sequentially registered in the dynamic registration table. The operation and maintenance management display table is obtained based on the order and level results, and then sent to the management terminal for visual viewing and management based on the viewing requirements of the management terminal.

8. A management and optimization system for industrial and commercial energy storage systems, characterized in that, include: The charge / discharge node determination module is used to determine the charge / discharge nodes of the industrial and commercial energy storage system based on real-time data collection of business load demand information and the state of charge of the industrial and commercial energy storage system, combined with the performance parameters of each energy storage component in the industrial and commercial energy storage system. The charge and discharge management module is used to control the charge and discharge of each energy storage component based on the charge and discharge nodes, and to monitor the operating parameters and health status of each energy storage component in real time. The operation and maintenance management module is used to identify faulty components in industrial and commercial energy storage systems based on health status analysis results, and to perform operation and maintenance management on the faulty components. The charge / discharge node determination module includes: The structure of the industrial and commercial energy storage system is traversed to determine the structure of the energy storage components in the system, and the performance parameters of each energy storage component are extracted based on the structure of the energy storage components. The performance parameters are analyzed to determine the charge and discharge efficiency curves of each energy storage component, and the charge and discharge characteristics of each energy storage component are determined based on the charge and discharge efficiency curves. The charging and discharging characteristics are matched with the applicable business scenarios, and the parameter ranges of each energy storage component are divided under different applicable business scenarios based on the matching results. The parameter range division results are used as the first node analysis indicator. At the same time, the historical database is accessed to retrieve real-time electricity price data in the power grid for multiple time periods, and the peak and off-peak electricity price time intervals are determined based on the target values ​​of the real-time electricity price data. The peak electricity price period and the off-peak electricity price period are used as the second node analysis indicators; Based on business load demand information, the state of charge of industrial and commercial energy storage systems, and the first and second node analysis indicators, the charging and discharging time nodes and corresponding charging and discharging power of industrial and commercial energy storage systems under different business application scenarios are determined. The charging and discharging nodes of industrial and commercial energy storage systems are obtained based on the charging and discharging time nodes and charging and discharging power.

9. The industrial and commercial energy storage system management optimization system according to claim 8, characterized in that, The charge / discharge node determination module includes: Sensor and location determination unit, used for: The power grid line distribution structure is obtained, and the first business sensor and the first set of key acquisition points corresponding to the business data are determined based on the line distribution structure and monitoring objectives. At the same time, the monitoring projects for industrial and commercial energy storage systems are identified, and the corresponding second business sensors and second key data acquisition point set are determined based on the project attributes of the monitoring projects. Monitoring unit, used for: Based on the first set of key acquisition points and the second set of key acquisition points, deployment guidance is provided for the first service sensor and the second service sensor respectively, and service parameters are adapted for the first service sensor and the second service sensor based on the deployment guidance results. Based on the results of business parameter adaptation, the power grid and energy storage system are monitored in real time to obtain the corresponding business load demand information and charge status.

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