A control method and platform for a highway distributed energy storage system

Abstract

The present invention relates to the technical field of energy storage management, and specifically discloses a control method and platform for a highway distributed energy storage system. The method includes collecting battery status parameters and outputting them as BMS feedback information in combination with battery balancing judgment results; a target EMS collects and analyzes BMS feedback information to determine key charge and discharge strategies for battery packs, and executes the strategies when feasible; a strategy optimization mode in which strategy safety degradation and a system joint compensation mechanism operate in coordination is adopted to optimize and protect infeasible key charge and discharge strategies; the target EMS collects and analyzes PCS collected data to determine a dynamic anti-backflow control strategy and execute it; environmental safety monitoring is performed on the system, and an abnormal response is performed based on the monitoring status, thereby ensuring that the high-speed distributed energy storage system can flexibly adjust the charge and discharge behavior, effectively preventing current from flowing back into the power grid, improving the system's intelligent control level and operating efficiency, and providing strong support for the energy supply and stable operation of highways.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage management, and in particular to a control method and platform for a highway distributed energy storage system. Background Art

[0002] In recent years, with the continued growth of highway traffic and the widespread adoption of new energy vehicles, energy demand for various facilities along highways has increased significantly. Distributed energy storage systems, as an effective means of energy storage and management, can meet highway energy needs. However, the complex nature of highways and their fluctuating energy demands present unique challenges in operating distributed energy storage systems. Failure to effectively manage and control these systems can shorten battery life, reduce system efficiency, and even lead to safety incidents.

[0003] Therefore, the present invention provides a control method and platform for a highway distributed energy storage system, which can effectively ensure that the high-speed distributed energy storage system can flexibly adjust its charging and discharging behavior, effectively prevent current from flowing back into the power grid, and improve the system's intelligent control level and operating efficiency. Summary of the Invention

[0004] The present invention provides a control method and platform for a distributed energy storage system on a highway, which is used to collect battery status parameters and output them as BMS feedback information in combination with battery balancing judgment results; the target EMS collects and analyzes BMS feedback information to determine the key charge and discharge strategies of the battery pack and executes them when the strategies are feasible; a strategy optimization mode in which strategy safety degradation and a system joint compensation mechanism operate in coordination is adopted to optimize and protect infeasible key charge and discharge strategies; the target EMS collects and analyzes PCS collected data to determine a dynamic anti-backflow control strategy and execute it; the system is monitored for environmental safety and, based on the monitoring status, responds to abnormalities, thereby ensuring that the high-speed distributed energy storage system can flexibly adjust its charge and discharge behavior, effectively preventing current from flowing back into the power grid, improving the system's intelligent control level and operating efficiency, and providing strong support for the energy supply and stable operation of highways.

[0005] The present invention provides a control method for a highway distributed energy storage system, comprising:

[0006] Step 1: Collect battery status parameters in real time and output them as BMS feedback information in combination with the equalization judgment results of the battery equalization status;

[0007] Step 2: The target EMS collects and analyzes BMS feedback information to determine the key charge and discharge strategies for each battery pack and executes them when feasible.

[0008] Step 3: Adopt a strategy optimization model that combines strategy safety degradation with a system joint compensation mechanism to optimize and protect infeasible key charging and discharging strategies.

[0009] Step 4: The target EMS collects and analyzes the data collected by the PCS, determines the dynamic anti-backflow control strategy and executes it to achieve dynamic anti-backflow control;

[0010] Step 5: Conduct environmental safety monitoring of the current distributed energy storage system and make targeted abnormal responses based on the abnormal safety monitoring status.

[0011] Preferably, real-time collection of battery status parameters and output of the BMS feedback information in combination with the equalization judgment result of the battery equalization status include:

[0012] Use pre-installed data acquisition equipment to collect battery status parameters of each battery pack in the current distributed energy storage system and transmit them to the target BMS;

[0013] The target BMS analyzes and calculates the battery status parameters of the battery pack to obtain battery balancing judgment parameters;

[0014] The balancing judgment result is obtained by comparing the battery balancing judgment parameter of the current battery pack with the corresponding preset balancing judgment threshold;

[0015] If the balancing judgment result of the battery balancing judgment parameter is unbalanced, the corresponding battery group will be marked as an unbalanced battery group;

[0016] Obtain and use the algorithm adaptation factor of the unbalanced battery pack as the algorithm matching condition to match the corresponding preset balancing algorithm;

[0017] The battery status parameters, balancing judgment results, and preset balancing algorithms of unbalanced battery packs of each battery pack in the current distributed energy storage system are transmitted to the target EMS as BMS feedback information.

[0018] Preferably, the target EMS collects and analyzes BMS feedback information to determine key charge and discharge strategies for each battery pack and executes them when feasible, including:

[0019] The target EMS determines a pre-balancing strategy for the unbalanced battery group according to a preset balancing algorithm for the unbalanced battery group in the BMS feedback information;

[0020] By comparing the battery state parameters of the battery pack with corresponding set state thresholds, a state comparison result is obtained;

[0021] Determine the key charge and discharge strategy of the current battery pack based on the status comparison results;

[0022] Input the battery state parameters of the battery pack into a pre-established charge and discharge capacity prediction model to output the predicted charge and discharge performance of the battery pack under different battery operating conditions;

[0023] The predicted charge and discharge performance of each battery pack corresponding to the battery operating condition that is most similar to the operating condition in the preset time period is regarded as the reference charge and discharge performance;

[0024] For unbalanced battery packs, the corresponding reference charge and discharge performance and pre-balancing strategy are used as feasibility evaluation indicators to evaluate the feasibility of the key charge and discharge strategy. If the feasibility evaluation result shows that the strategy is feasible, the key charge and discharge strategy is executed to protect the current unbalanced battery pack while executing the pre-balancing strategy.

[0025] For battery packs other than unbalanced battery packs, the corresponding reference charge and discharge performance is used as a feasibility evaluation indicator to evaluate the feasibility of the key charge and discharge strategy. If the feasibility evaluation result shows that the strategy is feasible, the key charge and discharge strategy is executed to perform charge and discharge protection on the current battery pack.

[0026] Preferably, a strategy optimization mode in which strategy safety degradation and system joint compensation mechanism operate in coordination is adopted to optimize and protect unfeasible key charging and discharging strategies, including:

[0027] Mark the key charging and discharging strategies whose feasibility evaluation results show that the strategies are not feasible as strategies to be adjusted;

[0028] According to the evaluation indicators that determine that the strategy to be adjusted is infeasible, the corresponding strategy degradation rules are matched;

[0029] Based on all obtained policy downgrade rules, the policy to be adjusted is adjusted for security downgrade to obtain the downgraded policy.

[0030] Execute the post-degradation strategy adapted to the battery pack to which it belongs and perform corresponding charge and discharge protection;

[0031] When the downgraded strategy is not compatible with the corresponding battery pack, the system linkage compensation mechanism is activated to provide compensation support.

[0032] Preferably, the system linkage compensation mechanism is activated to perform compensation analysis, including:

[0033] Marking a degraded strategy that is not compatible with the battery group to which it belongs as a compensation analysis strategy, and marking the battery group to which the compensation analysis strategy belongs as a compensation analysis battery group;

[0034] Obtain the reasons for the incompatibility between the compensation analysis battery pack and the corresponding compensation analysis strategy, and then determine a single compensation target based on the reasons for the incompatibility;

[0035] The real-time battery status data of all adjacent linked battery groups corresponding to the current compensation analysis battery group and the single compensation target are input into a pre-established adjacent linked compensation model to obtain an adjacent linked compensation result;

[0036] According to the neighboring linkage compensation result, if a neighboring linkage compensation scheme exists, the current distributed energy storage system executes the neighboring linkage compensation scheme and provides strategic support for the current compensation analysis battery group;

[0037] If there is no adjacent linkage compensation scheme, the current compensation analysis battery group is marked as a deep linkage battery group, and the corresponding compensation analysis strategy is marked as a deep linkage strategy;

[0038] By integrating the deep linkage battery group and deep linkage strategy into the pre-established compensation estimation model, the estimated compensation target of the current distributed energy storage system is output;

[0039] Obtain the pre-configured system linkage list of the current distributed energy storage system, and prioritize each linkage energy storage system in the pre-configured system linkage list by comprehensively considering system distance, system linkage delay, and short-term and long-term charging and discharging effects to obtain a system optimization score;

[0040] Sort each linked energy storage system in the preset system linkage list from largest to smallest according to the system optimization score to obtain a linkage system optimization sequence;

[0041] Input the real-time system operation data, linkage system optimization sequence and estimated compensation target of each linkage energy storage system in the preset system linkage list into the pre-established system linkage compensation model to obtain the system linkage compensation result;

[0042] Based on the system linkage compensation result, if a system linkage compensation plan exists, the system linkage compensation plan is executed to provide strategic support for the current distributed energy storage system;

[0043] If there is no system linkage compensation plan, the preset hierarchical protection mechanism will be activated.

[0044] Preferably, the target EMS collects and analyzes the PCS data, determines and executes a dynamic anti-backflow control strategy, and implements dynamic anti-backflow control, including:

[0045] The target EMS receives the PCS collected data from the PCS, extracts the evaluation basis, and obtains the countercurrent evaluation basis;

[0046] According to the type of basis for the backflow assessment, the corresponding backflow judgment method is matched to obtain the backflow judgment result;

[0047] The backflow assessment basis with the backflow judgment result of possible backflow is marked as reference backflow basis;

[0048] If there is no reference reverse flow basis at present, it is determined that the energy storage system does not have reverse flow;

[0049] If there is currently a reference countercurrent basis, all reference countercurrent bases are summarized to obtain a comprehensive countercurrent basis;

[0050] Compare the comprehensive backflow basis with the set backflow judgment rule to determine the actual backflow judgment result of the current distributed energy storage system;

[0051] When the actual backflow judgment result is backflow, the comprehensive backflow basis is used as a screening condition to determine the dynamic anti-backflow control strategy and execute it to achieve dynamic anti-backflow control.

[0052] Preferably, the current distributed energy storage system is subjected to environmental safety monitoring, and targeted abnormal responses are made based on the abnormal safety monitoring conditions, including:

[0053] Use pre-installed environmental data acquisition equipment to monitor the current environmental conditions of the distributed energy storage system in real time and obtain system environmental data;

[0054] Compare system environment data with preset environment safety thresholds, and mark system environment data that exceeds the preset environment safety thresholds as abnormal environment data;

[0055] Determine the type of environmental safety anomaly based on the abnormal environmental data, and collect all abnormal environmental data of the same environmental safety anomaly type to obtain an anomaly type-data set;

[0056] By analyzing the difference between the system environment data and the preset environmental safety threshold, the environmental anomaly coefficient is obtained;

[0057] The environmental anomaly coefficients of all abnormal environmental data in the anomaly type-dataset are summed up and calculated, and output as the comprehensive environmental anomaly coefficient of the corresponding environmental safety anomaly type of the current anomaly type-dataset;

[0058] Determine the safety anomaly level of the environmental safety anomaly type based on the comprehensive environmental anomaly coefficient;

[0059] The environmental security exception type and the corresponding security exception level are used as matching conditions, and the corresponding exception handling strategy is matched to perform targeted exception responses.

[0060] The present invention provides a control platform for a highway distributed energy storage system, comprising:

[0061] Data acquisition module: used to collect battery status parameters in real time and output them as BMS feedback information in combination with the equalization judgment results of the battery equalization status;

[0062] Charge and discharge protection module: used by the target EMS to collect and analyze BMS feedback information, determine the key charge and discharge strategies for each battery pack, and execute them when feasible;

[0063] Strategy Optimization Module: This module is used to optimize and protect key charging and discharging strategies that are not feasible by adopting a strategy optimization mode that coordinates strategy safety degradation with a system joint compensation mechanism.

[0064] Anti-backflow control module: used by the target EMS to collect and analyze PCS data, determine dynamic anti-backflow control strategies and execute them to achieve dynamic anti-backflow control;

[0065] Abnormal response module: used to monitor the environmental safety of the current distributed energy storage system and make targeted abnormal responses based on the abnormal safety monitoring status.

[0066] Compared with the prior art, the beneficial effects of the present invention are as follows: by collecting battery status parameters and combining them with battery balancing judgment results as BMS feedback information output; the target EMS collects and analyzes BMS feedback information to determine the key charge and discharge strategy of the battery pack, and executes it when the strategy is feasible; a strategy optimization mode in which strategy safety degradation and system joint compensation mechanism operate in coordination is adopted to optimize and protect the infeasible key charge and discharge strategies; the target EMS collects and analyzes PCS collected data to determine the dynamic anti-backflow control strategy and execute it; the system is monitored for environmental safety, and an abnormal response is made according to the monitoring status, which can ensure that the high-speed distributed energy storage system can flexibly adjust the charge and discharge behavior, effectively prevent the current from flowing back to the power grid, improve the intelligent control level and operation efficiency of the system, and provide strong support for the energy supply and stable operation of the highway.

[0067] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in this application document.

[0068] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0070] Figure 1 This is a flow chart of a control method for a highway distributed energy storage system according to an embodiment of the present invention;

[0071] Figure 2Schematic diagram of the technical architecture of a highway distributed energy storage system in an embodiment of the present invention;

[0072] Figure 3 Schematic diagram of a control platform for a highway distributed energy storage system in an embodiment of the present invention. DETAILED DESCRIPTION

[0073] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention. Embodiment 1:

[0074] The present invention provides a control method for a highway distributed energy storage system, referring to Figure 1 ,include:

[0075] Step 1: Collect battery status parameters in real time and output them as BMS feedback information in combination with the equalization judgment results of the battery equalization status;

[0076] Step 2: The target EMS collects and analyzes BMS feedback information to determine the key charge and discharge strategies for each battery pack and executes them when feasible.

[0077] Step 3: Adopt a strategy optimization model that combines strategy safety degradation with a system joint compensation mechanism to optimize and protect infeasible key charging and discharging strategies.

[0078] Step 4: The target EMS collects and analyzes the data collected by the PCS, determines the dynamic anti-backflow control strategy and executes it to achieve dynamic anti-backflow control;

[0079] Step 5: Conduct environmental safety monitoring of the current distributed energy storage system and make targeted abnormal responses based on the abnormal safety monitoring status.

[0080] In this embodiment, the highway distributed energy storage system refers to an energy storage system that is deployed in a highway scenario, consists of multiple energy storage units (such as battery packs) distributed in a dispersed manner, and is connected and managed through a distributed architecture. It is used to store and release electrical energy to meet various power needs of the highway, such as tunnel lighting, service area power supply, electric vehicle charging, etc.

[0081] In this embodiment, the battery status parameters are used to reflect the working status and performance of the battery, including single cell voltage, total battery pack voltage, charge and discharge current, battery temperature, remaining capacity (SOC), state of health (SOH), etc. The target BMS refers to the battery management system in the current distributed energy storage system, which is responsible for real-time collection of battery status parameters, analysis and judgment of the battery status, and control of the battery charge and discharge process, etc.

[0082] In this embodiment, the balancing judgment results include battery pack balancing and battery pack imbalance. The BMS feedback information includes the battery status parameters of each battery pack in the current distributed energy storage system (such as single cell voltage, battery pack total voltage, charge and discharge current, battery temperature, etc.), the balancing judgment result (battery pack balance or battery pack imbalance), and the preset balancing algorithm. The target EMS refers to the energy management system in the current distributed energy storage system, which is responsible for the coordinated operation of the entire energy storage system with the power grid or other energy systems.

[0083] In this embodiment, PCS collected data refers to various data collected by the energy storage converter (PCS), mainly including current data of the network point (including the magnitude and direction of the current), PCS input and output voltage values, PSC input and output current values, and PCS output power data, etc.

[0084] In this embodiment, for example, there is a technical architecture of a highway distributed energy storage system, such as Figure 2 As shown, it specifically includes: battery units (i.e., battery packs, using lithium iron phosphate batteries, single cells 314Ah, each unit 16 cells in series, storage capacity 1004.8wh), battery management system BMS (including BMU sub-control unit, BCU main control unit and BAU main control unit, among which, BMU sub-control unit: each battery unit integrates a BMU sub-control unit, collects the voltage and temperature of the single cell, and uploads it to the BCU; at the same time, it receives the fan start and stop instructions issued by the BCU; among which, the BCU main control unit: collects the total voltage on the battery side, the total voltage on the PCS side, the charge and discharge current, estimates the SOC, etc.; controls the main positive, main negative, and pre-charge contactors to be closed or disconnected; receives battery data from the BMU through CAN; exchanges information with the BAU through CAN; battery protection logic judgment; among which, the BAU main control unit: collects the working position status of each switch and the position status of the rotary switch; exchanges information with the BCU through CAN; uploads battery information through CAN communication with the PCS; controls the PCS through 485 communication with the PCS Working mode, controlling PCS operation through time strategy; uploading data information with LCD via 485 and receiving LCD setting information; communicating with metering meter via 485 to read meter data; exchanging data with data terminal via 232 and receiving background time synchronization information) and energy management system EMS (battery management BMS master control unit BAU integrated design, setting charging and discharging strategy through touch screen display unit, the strategy is sent to master control unit BAU / EMS, the master control unit executes according to the strategy and sends corresponding instructions to PCS).

[0085] The beneficial effects of the above technical solution are: by collecting battery status parameters and combining them with battery balancing judgment results as BMS feedback information output; the target EMS collects and analyzes BMS feedback information to determine the key charging and discharging strategies of the battery pack, and executes them when the strategy is feasible; a strategy optimization mode that cooperates with strategy safety degradation and system joint compensation mechanism is adopted to optimize and protect infeasible key charging and discharging strategies; the target EMS collects and analyzes PCS collected data to determine the dynamic anti-backflow control strategy and execute it; the system is monitored for environmental safety, and abnormal responses are made according to the monitoring conditions, which can ensure that the high-speed distributed energy storage system can flexibly adjust the charging and discharging behavior, effectively prevent the current from flowing back to the power grid, improve the system's intelligent control level and operating efficiency, and provide strong support for the energy supply and stable operation of the highway. Example 2:

[0086] The present invention provides a control method for a highway distributed energy storage system, which collects battery status parameters in real time and outputs the battery status parameters as BMS feedback information in combination with the battery balance judgment result, including:

[0087] Use pre-installed data acquisition equipment to collect battery status parameters of each battery pack in the current distributed energy storage system and transmit them to the target BMS;

[0088] The target BMS analyzes and calculates the battery status parameters of the battery pack to obtain battery balancing judgment parameters;

[0089] The balancing judgment result is obtained by comparing the battery balancing judgment parameter of the current battery pack with the corresponding preset balancing judgment threshold;

[0090] If the balancing judgment result of the battery balancing judgment parameter is unbalanced, the corresponding battery group will be marked as an unbalanced battery group;

[0091] Obtain and use the algorithm adaptation factor of the unbalanced battery pack as the algorithm matching condition to match the corresponding preset balancing algorithm;

[0092] The battery status parameters, balancing judgment results, and preset balancing algorithms of unbalanced battery packs of each battery pack in the current distributed energy storage system are transmitted to the target EMS as BMS feedback information.

[0093] In this embodiment, the preset data acquisition device refers to various pre-set sensor devices for collecting battery status parameters, such as temperature sensors and current sensors; a battery pack refers to a combination of multiple single cells connected in series or parallel, used to store and release electrical energy. In highway energy storage systems, the battery pack is a core component; battery status parameters are used to reflect the operating status and performance of the battery, including single cell voltage, battery pack total voltage, charge and discharge current, battery temperature, remaining capacity (SOC), state of health (SOH), etc.; the target BMS refers to the battery management system within the current distributed energy storage system, which is responsible for real-time collection of battery status parameters, analysis and judgment of the battery status, and control of the battery charge and discharge process, etc.

[0094] In this embodiment, the cell balancing judgment parameters are pre-specified parameters used to measure the degree of battery pack balance, such as the voltage difference, remaining capacity (SOC) difference, and internal resistance difference between single cells. The preset balancing judgment threshold is a standard pre-determined based on the performance requirements and actual operating data of the battery pack, used to determine whether the cell balancing judgment parameters are in a balanced state, such as the voltage difference threshold between single cells. The balancing judgment results include balanced and unbalanced results. An unbalanced battery pack refers to a battery pack whose cell balancing judgment parameters do not meet the corresponding preset balancing judgment threshold requirements.

[0095] In this embodiment, the algorithm adaptation factor includes the battery pack size and battery pack characteristics (including battery type (such as lithium-ion battery, lead-acid battery), battery pack connection method (such as series connection, parallel connection) and connection number (such as series number, parallel number)); the preset balancing algorithm refers to the algorithm used to balance each single battery in the battery pack, such as the passive balancing algorithm (such as resistance energy consumption balancing) and the active balancing algorithm, which are obtained by matching from the preset balancing algorithm library using the algorithm adaptation factor as the matching condition; the preset balancing algorithm library refers to a collection of multiple balancing algorithms pre-stored, and the balancing algorithms included can be used for balancing battery packs of different types, different connection methods and different sizes.

[0096] In this embodiment, the BMS feedback information includes the battery status parameters of each battery pack in the current distributed energy storage system (such as single cell voltage, total battery pack voltage, charge and discharge current, battery temperature, etc.), the balancing judgment result (battery pack balanced or battery pack unbalanced), and the preset balancing algorithm; the target EMS refers to the energy management system in the current distributed energy storage system, which is responsible for the coordinated operation of the entire energy storage system with the power grid or other energy systems.

[0097] The beneficial effects of the above technical solution are: by collecting battery status parameters in real time and making equalization judgments, it is possible to promptly discover imbalance problems within the battery pack, and by matching the corresponding equalization algorithm, it is possible to more accurately equalize the battery pack, thereby reducing unnecessary energy loss; transmitting BMS feedback information such as battery status parameters, equalization judgment results and preset equalization algorithms to the target EMS helps the energy management system to fully understand the operating status of the energy storage system and provide effective data basis for subsequent system control. Example 3:

[0098] The present invention provides a control method for a highway distributed energy storage system. The target EMS collects and analyzes BMS feedback information to determine the key charge and discharge strategies for each battery pack and executes them when feasible, including:

[0099] The target EMS determines a pre-balancing strategy for the unbalanced battery group according to a preset balancing algorithm for the unbalanced battery group in the BMS feedback information;

[0100] By comparing the battery state parameters of the battery pack with corresponding set state thresholds, a state comparison result is obtained;

[0101] Determine the key charge and discharge strategy of the current battery pack based on the status comparison results;

[0102] Input the battery state parameters of the battery pack into a pre-established charge and discharge capacity prediction model to output the predicted charge and discharge performance of the battery pack under different battery operating conditions;

[0103] The predicted charge and discharge performance of each battery pack corresponding to the battery operating condition that is most similar to the operating condition in the preset time period is regarded as the reference charge and discharge performance;

[0104] For unbalanced battery packs, the corresponding reference charge and discharge performance and pre-balancing strategy are used as feasibility evaluation indicators to evaluate the feasibility of the key charge and discharge strategy. If the feasibility evaluation result shows that the strategy is feasible, the key charge and discharge strategy is executed to protect the current unbalanced battery pack while executing the pre-balancing strategy.

[0105] For battery packs other than unbalanced battery packs, the corresponding reference charge and discharge performance is used as a feasibility evaluation indicator to evaluate the feasibility of the key charge and discharge strategy. If the feasibility evaluation result shows that the strategy is feasible, the key charge and discharge strategy is executed to perform charge and discharge protection on the current battery pack.

[0106] In this embodiment, the target EMS is the energy management system within the current distributed energy storage system, which is responsible for the coordinated operation of the entire energy storage system with the power grid or other energy systems. Specifically, it refers to formulating and executing corresponding control strategies by collecting, analyzing and processing various information.

[0107] In this embodiment, the pre-balancing strategy refers to a strategy for balancing an unbalanced battery pack determined based on a preset balancing algorithm for the unbalanced battery pack in the BMS feedback information (such as a passive balancing algorithm (strategy determination steps: setting a balancing start threshold, determining a balancing current, formulating a balancing time, and generating a pre-balancing strategy), or an active balancing algorithm (strategy determination steps: determining a balancing trigger condition, calculating an energy transfer amount, selecting a balancing topology and control method, and generating a pre-balancing strategy)). The strategy aims to achieve consistency in parameters such as the voltage and remaining capacity (SOC) of each single cell in the battery pack through a specific control method, thereby improving the overall performance and safety of the battery pack.

[0108] In this embodiment, for example, the preset balancing algorithm for the unbalanced battery pack 1 is a passive balancing algorithm. The rated voltage of the unbalanced battery pack 1 is 48V, and it is composed of 16 single cells connected in series. The rated voltage of each single cell is 3V. When the single cell voltage exceeds 3.1V, passive balancing is started, and the balancing current is 50-100mA. When the single cell voltage difference is 0.1V, balancing is required for 1-2 hours.

[0109] At this time, the pre-balancing strategy of the unbalanced battery pack 1 is to discharge a single cell in the battery pack with a balancing current of 80mA when the voltage exceeds 3.1V, and the balancing time is 1.5 hours, until the voltage difference between the single cell and the other single cells is less than 0.05V.

[0110] In this embodiment, the set state threshold refers to a pre-set standard value or range used to determine whether the battery pack state is normal; the state comparison result refers to the result obtained by comparing the battery state parameters of the battery pack with the corresponding set state threshold (usually expressed by the degree of parameter difference between the battery state parameters and the corresponding set state threshold), which is used to determine whether the battery pack is in a normal working state, for example, whether abnormal conditions such as overcharging, over-discharging, and excessive temperature occur; the key charge and discharge strategy is the charge and discharge strategy of the current battery pack determined by the target EMS based on the state comparison result, specifically obtained by comprehensively considering the type of battery pack abnormality determined by the state comparison result (such as overcharging, over-discharging, and excessive temperature) and historical charge and discharge strategy data.

[0111] In this embodiment, for example, there is a status comparison result of battery pack 1: the voltage of a single cell exceeds 3.6V, and the total voltage of the battery pack exceeds 48V;

[0112] Strategy determination: The target EMS determines that the battery pack is in an overcharged state; the key charge and discharge strategy is to stop charging and start discharging to reduce the battery pack voltage; specific operation: set the charging current to 0A, start the discharge mode at the same time, and set the discharge current to 10A until the single cell voltage drops below 3.5V and the total battery pack voltage drops below 47V.

[0113] In this embodiment, the charge and discharge capacity prediction model is a pre-established model for predicting the charge and discharge performance of a battery pack under different battery operating conditions. The specific establishment steps are: first, historical data of the battery pack under different operating conditions are collected, and characteristic parameters that have a greater impact on the charge and discharge performance (for example, the battery's voltage, current, temperature, SOC, etc.) are selected from the collected data as input variables of the model; the neural network is trained using the acquired historical data and characteristic parameters, with the characteristic parameters as input and the corresponding charge and discharge performance data as output.

[0114] In this embodiment, predicting charge and discharge performance refers to inputting the battery state parameters of the battery pack into the charge and discharge capacity prediction model, and the model outputs the predicted results of the charge and discharge performance of the battery pack under different battery operating conditions, such as charging speed, discharge power, charge and discharge efficiency, etc.; battery operating conditions refer to the various working conditions and states of the battery pack during operation, such as ambient temperature and load characteristics.

[0115] In this embodiment, the preset time period refers to a pre-set time interval used to screen the battery operating condition with the highest similarity to the operating condition within the time period (using a specific similarity calculation method (such as Euclidean distance, cosine similarity, etc.) to compare different battery operating conditions with the operating conditions within the preset time period to obtain a similarity value). The operating condition similarity refers to a similarity value obtained by using a specific similarity calculation method (such as Euclidean distance, cosine similarity, etc.) to compare different battery operating conditions with the operating conditions within the preset time period.

[0116] In this embodiment, the reference charge and discharge performance refers to the predicted charge and discharge performance of the battery pack corresponding to the battery operating condition that is most similar to the operating condition in the preset time period; the feasible evaluation index refers to the specific index or condition used to evaluate whether the key charge and discharge strategy is feasible. For unbalanced battery packs, the feasible evaluation index refers to the reference charge and discharge performance and the pre-balancing strategy. For battery packs other than unbalanced battery packs, the feasible evaluation index refers to the reference charge and discharge performance. By judging whether the key charge and discharge strategy meets these feasible evaluation indicators, it can be determined whether the strategy is feasible.

[0117] In this embodiment, for example, if there is an unbalanced battery pack 2, the corresponding pre-balancing strategy is to discharge the single cells with higher voltages at a discharge current of 5A for 1 hour. The reference charge and discharge performance is that during normal charge and discharge, the battery pack voltage fluctuation range is within ±0.5V, and the charge and discharge efficiency can reach over 90%. The key charge and discharge strategy is to reduce the charging current to 80% of the normal current.

[0118] Feasibility assessment: Using the target EMS's internal simulation tool (software or algorithm module used to simulate battery pack operating conditions and assess strategy feasibility) to simulate the execution of key charge and discharge strategies and pre-balancing strategies, it is predicted that during the subsequent operation of unbalanced battery pack 2, the voltage fluctuation range can be controlled within ±0.4V, and the charge and discharge efficiency is expected to reach 92%. The pre-balancing strategy can also effectively improve the unbalanced state of unbalanced battery pack 2, reducing the single-cell voltage difference from the original 0.3V to within 0.1V.

[0119] Evaluation results: Since the simulation results meet the reference charge and discharge performance (voltage fluctuation range and charge and discharge efficiency requirements) and the pre-balancing strategy can effectively improve the unbalanced state, the key charge and discharge strategy for unbalanced battery group 2 is determined to be feasible. The target EMS will execute this strategy to provide charge and discharge protection for the current unbalanced battery group 2 while executing the pre-balancing strategy.

[0120] The beneficial effects of the above technical solution are: by comparing the battery status parameters with the set thresholds to determine the key charge and discharge strategy, it helps to avoid battery damage; for unbalanced battery packs, while executing the key charge and discharge strategy protection, the pre-balancing strategy is executed, which can improve the unbalanced state of the single cells in the battery pack and further improve the safety and stability of the system; by considering the different situations of unbalanced battery packs and other battery packs, different feasible evaluation indicators are used for strategy evaluation, which can ensure the effectiveness and reliability of the charge and discharge strategy. Embodiment 4:

[0121] The present invention provides a control method for a highway distributed energy storage system. The method adopts a strategy optimization mode in which strategy safety degradation and a system joint compensation mechanism operate in coordination, and optimizes and protects unfeasible key charging and discharging strategies. The method includes:

[0122] Mark the key charging and discharging strategies whose feasibility evaluation results show that the strategies are not feasible as strategies to be adjusted;

[0123] According to the evaluation indicators that determine that the strategy to be adjusted is infeasible, the corresponding strategy degradation rules are matched;

[0124] Based on all obtained policy downgrade rules, the policy to be adjusted is adjusted for security downgrade to obtain the downgraded policy.

[0125] Execute the post-degradation strategy adapted to the battery pack to which it belongs and perform corresponding charge and discharge protection;

[0126] When the downgraded strategy is not compatible with the corresponding battery pack, the system linkage compensation mechanism is activated to provide compensation support.

[0127] In this embodiment, the strategy to be adjusted refers to the key charge and discharge strategy that is not feasible; the evaluation index content refers to the corresponding content of the specific index for determining that the key charge and discharge strategy is not feasible. For example, if the key charge and discharge strategy of the unbalanced battery group 3 does not meet the reference charge and discharge performance and does not conflict with the pre-balancing strategy, then the corresponding evaluation index content refers to the specific content of the reference charge and discharge performance of the unbalanced battery group 3; for example, if the key charge and discharge strategy of the unbalanced battery group 4 does not meet the reference charge and discharge performance and conflicts with the pre-balancing strategy, then the corresponding evaluation index content refers to the reference charge and discharge performance of the unbalanced battery group 4 and the specific content of the pre-balancing strategy.

[0128] In this embodiment, the policy degradation rule refers to a rule for adjusting the policy to be adjusted that is adapted to the evaluation index content, and is intended to adjust an originally infeasible policy to a relatively safe and feasible policy. For example, the key charge and discharge policy of battery pack 2 requires charging a single cell, while the corresponding pre-balancing policy requires discharging the same single cell to improve the imbalanced state. In this case, the key charge and discharge policy of battery pack 2 is regarded as policy 1 to be adjusted, and the evaluation index content is the corresponding pre-balancing policy, that is, requiring the current single cell to be discharged. The policy degradation rule is to adjust the charge and discharge sequence, first executing the discharge operation in the pre-balancing policy, and then executing the charge operation in the key charge and discharge policy after the imbalanced state of battery pack 2 has been improved to a certain extent.

[0129] For example, the key charge and discharge strategy of battery group 3 causes the charge and discharge efficiency of battery group 3 to reach 75% under specific operating condition 1, while the corresponding reference charge and discharge performance is that the charge and discharge efficiency of battery group 3 under specific operating condition 1 should reach more than 85%; at this time, the key charge and discharge strategy of battery group 3 is regarded as strategy 2 to be adjusted, and the evaluation index content is the corresponding reference charge and discharge performance, that is, the charge and discharge efficiency of battery group 3 under specific operating condition 1 should reach more than 85%; the strategy degradation rule is to reduce the charging current set by the key charge and discharge strategy of battery group 3 by 20%.

[0130] In this embodiment, the downgraded strategy refers to the strategy obtained after the adjustment strategy is safely downgraded by using all the obtained strategy downgrade rules; the specific steps of judging whether the downgraded strategy is compatible with the battery pack to which it belongs are as follows: first, the various parameters set in the downgraded strategy (such as charging current, discharging current, charging and discharging time, etc.) are compared with the real-time status parameters of the battery pack to obtain the parameter comparison results of the battery pack; then, based on the design parameters and safety standards of the battery pack, combined with the parameter comparison results, it is evaluated whether the downgraded strategy will cause safety problems such as overcharging, over-discharging, and over-temperature in the battery pack during execution (for example, checking whether the charging current is within the charging current range allowed by the battery pack, whether the discharge current will cause over-discharging of the battery pack, and whether the charging and discharging time is consistent with the current SOC of the battery pack). state matching, etc.), to obtain a safety assessment result; then, by analyzing whether the charge and discharge efficiency under the degraded strategy meets the system operation requirements, a performance evaluation result is obtained (the charge and discharge efficiency is calculated by utilizing the actual charge and discharge data of the battery pack collected during the simulation execution of the degraded strategy, and compared with the preset operation efficiency standard of the system. If the calculated charge and discharge efficiency reaches or exceeds the preset operation efficiency standard of the system, it is determined that the charge and discharge efficiency under the degraded strategy meets the system operation requirements; otherwise, it is determined that it does not meet the requirements); finally, considering the safety assessment results and the performance evaluation results comprehensively, if the degraded strategy can meet the safety operation requirements of the battery pack, and the charge and discharge efficiency of the battery pack under the degraded strategy meets the system operation requirements, then it is determined that the current degraded strategy is adapted to the battery pack; otherwise, it is determined to be incompatible.

[0131] In this embodiment, the system linkage compensation mechanism refers to a mechanism for coordinated control and compensation support of the highway distributed energy storage system by considering the status and capabilities of other battery packs in the current distributed energy storage system or other linked energy storage systems.

[0132] The beneficial effects of the above technical solution are: by safely downgrading infeasible key charging and discharging strategies and judging whether the downgraded strategies are compatible with the battery pack, it is possible to avoid damage to the battery pack caused by directly executing infeasible strategies, and ensure that the execution of downgraded strategies will not cause new safety hazards; when the downgraded strategy is incompatible with the battery pack, the system linkage compensation mechanism is activated, which can ensure that the system can maintain a relatively stable operating state under various circumstances, which helps to improve the safety of distributed energy storage systems on highways. Example 5:

[0133] The present invention provides a control method for a highway distributed energy storage system, which starts a system linkage compensation mechanism to perform compensation analysis, including:

[0134] Marking a degraded strategy that is not compatible with the battery group to which it belongs as a compensation analysis strategy, and marking the battery group to which the compensation analysis strategy belongs as a compensation analysis battery group;

[0135] Obtain the reasons for the incompatibility between the compensation analysis battery pack and the corresponding compensation analysis strategy, and then determine a single compensation target based on the reasons for the incompatibility;

[0136] The real-time battery status data of all adjacent linked battery groups corresponding to the current compensation analysis battery group and the single compensation target are input into a pre-established adjacent linked compensation model to obtain an adjacent linked compensation result;

[0137] According to the neighboring linkage compensation result, if a neighboring linkage compensation scheme exists, the current distributed energy storage system executes the neighboring linkage compensation scheme and provides strategic support for the current compensation analysis battery group;

[0138] If there is no adjacent linkage compensation scheme, the current compensation analysis battery group is marked as a deep linkage battery group, and the corresponding compensation analysis strategy is marked as a deep linkage strategy;

[0139] By integrating the deep linkage battery group and deep linkage strategy into the pre-established compensation estimation model, the estimated compensation target of the current distributed energy storage system is output;

[0140] Obtain the pre-configured system linkage list of the current distributed energy storage system, and prioritize each linkage energy storage system in the pre-configured system linkage list by comprehensively considering system distance, system linkage delay, and short-term and long-term charging and discharging effects to obtain a system optimization score;

[0141] Sort each linked energy storage system in the preset system linkage list from largest to smallest according to the system optimization score to obtain a linkage system optimization sequence;

[0142] Input the real-time system operation data, linkage system optimization sequence and estimated compensation target of each linkage energy storage system in the preset system linkage list into the pre-established system linkage compensation model to obtain the system linkage compensation result;

[0143] Based on the system linkage compensation result, if a system linkage compensation plan exists, the system linkage compensation plan is executed to provide strategic support for the current distributed energy storage system;

[0144] If there is no system linkage compensation plan, the preset hierarchical protection mechanism will be activated.

[0145] In this embodiment, the compensation analysis strategy refers to a degraded strategy that is incompatible with the battery pack to which it belongs, that is, a degraded strategy that cannot meet the safe operation requirements or charge and discharge efficiency requirements of the battery pack is marked as a compensation analysis strategy; the compensation analysis battery pack refers to the battery pack corresponding to the compensation analysis strategy; the incompatibility reason refers to the specific reason that causes the incompatibility between the degraded strategy and the battery pack, such as the battery pack state parameter exceeding the range set by the degraded strategy, the charge and discharge efficiency under the degraded strategy not meeting the system operation requirements, etc.; the single compensation target refers to the target that needs to be achieved in order to enable the compensation analysis strategy to adapt to the compensation analysis battery pack, which is matched from the preset adaptation-compensation table using the incompatibility reason as a screening condition, such as adjusting the charging current, discharging current or charging and discharging time; wherein the preset adaptation-compensation table is a pre-set data table that stores the mapping relationship between various incompatibility reasons and corresponding compensation targets. For example, when the incompatibility reason is "the battery pack temperature is too high and exceeds the temperature range set by the degraded strategy", the corresponding single compensation target is to shorten the operating time of the battery pack in the current charge and discharge stage and reduce the charge and discharge power to restore the battery pack temperature to a normal range as soon as possible.

[0146] In this embodiment, the adjacent linkage battery group refers to a battery group that is spatially adjacent to the compensation analysis battery group and can provide strategic support to the compensation analysis battery group through linkage control; the adjacent linkage compensation model can comprehensively consider the status and capabilities of the adjacent battery groups and provide a reasonable compensation plan, specifically: first, collect data on battery groups adjacent to each other in different spatial positions under various operating conditions, including status parameters such as battery group voltage, current, temperature, and remaining power, as well as the charging and discharging strategies and actual effects of linkage control between these battery groups; then, use a neural network algorithm to train and learn these data, so that the model can automatically analyze and output a reasonable compensation plan based on the input adjacent battery group status data and a single compensation target.

[0147] In this embodiment, the neighboring linkage compensation result refers to the result output by the model after the real-time battery pack status data of the neighboring linkage battery pack and a single compensation target are input into the neighboring linkage compensation model, including two types of results: no plan and with a neighboring linkage compensation plan; the neighboring linkage compensation plan refers to a specific plan determined based on the neighboring linkage compensation result, which can be actually implemented and provides strategic support for the compensation analysis battery pack.

[0148] In this embodiment, for example, a highway section 1 has a service area and a tunnel, both of which rely on highway distributed energy storage system 1 for power supply. Highway distributed energy storage system 1 is composed of multiple battery packs distributed in different locations and connected and managed via a distributed architecture. Battery pack A is responsible for powering some electrical equipment in the service area, battery pack B is responsible for powering the tunnel lighting system, and battery pack C is a backup battery pack.

[0149] During one operation, battery pack A rapidly degraded due to long-term high-load power supply to the service area. The corresponding degraded charge and discharge strategy was deemed infeasible and was marked as compensation analysis battery pack 1.

[0150] The corresponding single compensation objective for the strategy after the degradation of compensation analysis battery pack 1 is: quickly replenish the power of compensation analysis battery pack 1 without causing overcharging. The adjacent linkage battery packs of compensation analysis battery pack 1 are battery packs B and battery pack C. Battery pack B currently has a remaining charge of 50% and is currently supplying power to the tunnel lighting system, but the tunnel lighting demand is relatively stable, leaving sufficient power allocation space. Battery pack C is a backup battery pack with a remaining charge of 70% and is not yet in use.

[0151] At this time, after the single compensation target of the compensation analysis battery group 1 and the real-time battery group status data of battery groups B and C (including remaining power, charge and discharge current, voltage, etc.) are input into the adjacent linkage compensation model, the adjacent linkage compensation result of the compensation analysis battery group 1 is obtained as "battery group B reduces the power supply to the tunnel lighting by 15% and allocates this power to battery group A for charging; battery group C can directly output a charging current of 15A to battery group A"; the adjacent linkage compensation plan of the compensation analysis battery group 1 is "battery group B reduces the power supply to the tunnel lighting by 15%, and at the same time, battery group C charges battery group A with a charging current of 15A."

[0152] In this embodiment, the deep linkage battery group refers to a compensation analysis battery group for which there is no adjacent linkage compensation scheme; the deep linkage strategy refers to a compensation analysis strategy corresponding to the deep linkage battery group, that is, the strategy requires a wider range of linkage energy storage systems for compensation support when executed.

[0153] In this embodiment, the compensation estimation model refers to a model used to output the estimated compensation target of the current distributed energy storage system based on the deep linkage battery pack and the deep linkage strategy. The specific establishment steps are: first, collect historical data of different battery packs and charge and discharge strategies in different operating scenarios, including various state parameters of the battery pack, the specific content of the charge and discharge strategy, and the actual operating effect of the system after the implementation of the strategy; then, use data analysis technology and machine learning algorithms (such as decision tree algorithm or support vector machine algorithm) to mine and analyze these data to construct a model that can output the estimated compensation target; the estimated compensation target refers to the deep linkage After the battery pack and deep linkage strategy are input into the compensation estimation model, the estimated compensation target output by the model provides a reference basis for subsequent system linkage compensation. For example, after inputting a deep linkage battery pack (such as battery pack D, with a remaining power of 20% and a maximum charging and discharging power of 50kW) and a deep linkage strategy (such as increasing the charging power of battery pack D to 60kW within the next hour) into the compensation estimation model, the estimated compensation target output by the model may be "In the next hour, an additional 10kW of charging power will need to be allocated from other linked energy storage systems to ensure that battery pack D can be charged safely and efficiently according to the deep linkage strategy."

[0154] In this embodiment, the preset system linkage list is a pre-set list of various linked energy storage systems that may participate in the linkage compensation of the current distributed energy storage system, providing optional support objects for the system linkage compensation; the system preference score is used to evaluate the support priority of each linked energy storage system; the linkage system preference sequence refers to the sequence obtained by sorting the linked energy storage systems in the preset system linkage list from large to small according to the system preference score, clarifying the support priority order of each linked energy storage system; the real-time system operation data refers to the real-time operation data of each linked energy storage system in the preset system linkage list, including battery status, charge and discharge status, system load, etc.

[0155] In this embodiment, by comprehensively considering system distance, system linkage delay, and short-term and long-term charging and discharging effects, each linked energy storage system in the preset system linkage list is prioritized and analyzed to obtain a system priority score, including:

[0156] Assign corresponding distance attenuation weights based on the physical distance between the current distributed energy storage system and each corresponding linked energy storage system;

[0157] Obtain historical linkage data of each linked energy storage system within a preset time period for the current distributed energy storage system, and extract historical linkage delay from the historical linkage data;

[0158] Calculate the average historical linkage delay of each interconnected energy storage system for the current distributed energy storage system;

[0159] A short-term and long-term dual verification mechanism is used to evaluate the self-charging and discharging efficiency of each linked energy storage system, resulting in corresponding short-term and long-term performance evaluation coefficients.

[0160] If the short-term performance evaluation coefficient of a linked energy storage system within a set short time period is lower than a set short-term performance threshold, or the long-term performance evaluation coefficient within a set long time period is lower than a set long-term performance threshold, the charge-discharge effect evaluation value of the current linked energy storage system is adjusted downward using the set short-term performance threshold or the set long-term performance threshold;

[0161] The distance attenuation weight, average historical linkage delay, and charge-discharge effect evaluation value are combined to calculate the characterization optimization coefficient, which is then normalized to obtain the system optimization coefficient.

[0162] The calculation formula for characterizing the optimization coefficient is as follows:

[0163] ;

[0164] Where, It is expressed as the characterization optimization coefficient of the linkage energy storage system for the current distributed energy storage system; Represented as the physical distance between the current distributed energy storage system and the interconnected energy storage system; It represents the distance attenuation weight of the interconnected energy storage system for the current distributed energy storage system; e represents the base of the natural logarithm, which is 2.7; It is expressed as the weight of the influence of the physical distance between systems on the calculation of the characterization preference coefficient; It is represented as the maximum linkage delay among the average historical linkage delays of all the linkage energy storage systems for the current distributed energy storage system; It is expressed as the minimum linkage delay among the average historical linkage delays of all the linkage energy storage systems for the current distributed energy storage system; It is represented as the average linkage delay among the average historical linkage delays of all the linked energy storage systems for the current distributed energy storage system; It is represented as the average historical linkage delay of the linkage energy storage system for the current distributed energy storage system; It is represented by the influence weight of linkage delay on the calculation characterization optimization coefficient; p is represented by the charging and discharging effect evaluation value of the linkage energy storage system for the current distributed energy storage system; It is expressed as the weight of the influence of the system charging and discharging effect on the calculation characterization optimization coefficient; 、 and The value range of is (0, 1), which is obtained by solving the matrix constructed after pairwise comparison and scoring using the hierarchical analysis method.

[0165] In this embodiment, linkage refers to the mutual cooperation between energy storage systems. Specifically, when a battery pack in a high-speed distributed energy storage system cannot meet its own operating needs due to various reasons (such as strategy mismatch, insufficient power, etc.), other adjacent linked battery packs or linked energy storage systems in a pre-set system linkage list will adjust their own charging and discharging strategies, power allocation, etc. to provide strategic support to the battery pack, jointly achieving stable operation of the highway distributed energy storage system and efficient energy management.

[0166] In this embodiment, physical distance refers to the actual spatial distance between the current distributed energy storage system and each corresponding linked energy storage system. The distance weight is a weight coefficient assigned based on the physical distance in combination with an exponential function, which is used to reflect the degree of influence of distance on the resource scheduling effect between systems. The historical linkage data records the relevant data of each linked energy storage system's linkage (resource scheduling) with the current distributed energy storage system within a preset time period, including linkage time, linkage duration, linkage power, linkage delay, etc.

[0167] In this embodiment, the historical linkage delay refers to the time difference between each linked energy storage system receiving a linkage instruction and actually starting to execute the linkage operation during the historical linkage process. It is an important indicator for evaluating the response speed of the linked energy storage system. The average historical linkage delay refers to the result obtained by averaging all historical linkage delays of the linked energy storage systems within a preset time period.

[0168] In this embodiment, the short-term and long-term dual verification mechanism refers to considering the charging and discharging performance of the linked energy storage system within a set short time period (such as a few minutes to a few hours) and a set long time period (such as a few days to a few weeks) to comprehensively evaluate the performance of the energy storage system; the self-charging and discharging efficiency refers to the charging and discharging efficiency of the linked energy storage system itself.

[0169] In this embodiment, the short-term performance evaluation coefficient is obtained by calculating the average ratio of the historical charge and discharge efficiency of the linked energy storage system at each historical moment within a set short time period to the corresponding set charge and discharge efficiency; the long-term performance evaluation coefficient is obtained by calculating the average ratio of the historical charge and discharge efficiency of the linked energy storage system at each historical moment within a set long time period to the corresponding set charge and discharge efficiency; the short-term performance threshold is a pre-set important criterion for judging whether the short-term charge and discharge performance of the linked energy storage system meets the standard, such as 0.9; the long-term performance threshold is a pre-set important criterion for judging whether the long-term charge and discharge performance of the linked energy storage system meets the standard, such as 0.85.

[0170] In this embodiment, the system linkage compensation model first collects the real-time system operation data of each linkage energy storage system corresponding to the current distributed energy storage system under different operating conditions (including information such as the charging and discharging power of the energy storage system, the remaining power, the energy storage capacity, and the distance from the compensation analysis battery group); then, a set of reasonable evaluation indicators and weight systems are formulated based on the system distance, the system linkage delay, and the short-term and long-term charging and discharging effect factors; then, using these data and evaluation indicators, a genetic algorithm is used to train and establish a system linkage compensation model, so that the model can output the optimal system linkage compensation plan based on the input real-time system operation data, the linkage system preferred sequence and the estimated compensation target; the system linkage compensation result refers to the result output by the model after the real-time system operation data, the linkage system preferred sequence and the estimated compensation target are input into the system linkage compensation model, including two types of results: no plan and a system linkage compensation plan; the system A linkage compensation scheme refers to a specific plan used to strategically support the current distributed energy storage system. For example, after inputting real-time system operating data (e.g., energy storage system E has a remaining charge of 60% and a charge / discharge power of 30kW; energy storage system F has a remaining charge of 50% and a charge / discharge power of 25kW), the linkage system optimization sequence (energy storage system E has a optimization score of 0.8, and energy storage system F has a optimization score of 0.7), and the estimated compensation target (an additional 15kW of charging power is required) into the system linkage compensation model, the model's output system linkage compensation scheme might be "activate energy storage system E and increase its charge / discharge power to 40kW, of which 15kW is used to strategically support the current distributed energy storage system to meet the estimated compensation target." A preset hierarchical protection mechanism is a pre-set protection mechanism that is activated when the system linkage compensation scheme is not feasible. This includes measures such as reducing the system load and disconnecting some battery packs.

[0171] The beneficial effect of the above technical solution is that when the downgraded strategy is not compatible with the battery pack to which it belongs, a multi-level system linkage compensation solution can be quickly activated for strategic support, which can effectively improve the ability of the distributed energy storage system to cope with various complex situations, ensure that the system can fully utilize the surrounding linked energy storage resources, realize the optimal allocation of resources, improve the charging and discharging efficiency of the distributed energy storage system, and reduce operating costs. Example 6:

[0172] The present invention provides a control method for a highway distributed energy storage system. The target EMS collects and analyzes data collected by the PCS to determine and execute a dynamic anti-backflow control strategy to achieve dynamic anti-backflow control, including:

[0173] The target EMS receives the PCS collected data from the PCS, extracts the evaluation basis, and obtains the countercurrent evaluation basis;

[0174] According to the type of basis for the backflow assessment, the corresponding backflow judgment method is matched to obtain the backflow judgment result;

[0175] The backflow assessment basis with the backflow judgment result of possible backflow is marked as reference backflow basis;

[0176] If there is no reference reverse flow basis at present, it is determined that the energy storage system does not have reverse flow;

[0177] If there is currently a reference countercurrent basis, all reference countercurrent bases are summarized to obtain a comprehensive countercurrent basis;

[0178] Compare the comprehensive backflow basis with the set backflow judgment rule to determine the actual backflow judgment result of the current distributed energy storage system;

[0179] When the actual backflow judgment result is backflow, the comprehensive backflow basis is used as a screening condition to determine the dynamic anti-backflow control strategy and execute it to achieve dynamic anti-backflow control.

[0180] In this embodiment, PCS collected data refers to various data collected by the energy storage converter (PCS), mainly including the current data of the network point (including the magnitude and direction of the current), the PCS input and output voltage values, the PSC input and output current values, and the PCS output power data, etc.; the reverse flow assessment indicators include the current direction (comparing the actual direction of the current with the preset grid-connected direction. When the current direction is opposite to the preset direction, there may be a reverse flow), the power flow direction (determining whether there is a reverse flow trend by comparing the output power of the energy storage system and the input power of the grid), and the reverse flow power ratio (the ratio of the reverse flow power to the total output power), etc., which are used to assess whether there is a reverse flow risk in the energy storage system.

[0181] In this embodiment, the reverse flow assessment basis is extracted from the PCS collected data, including the current direction (actual current direction, preset grid connection direction), power flow direction (output power of the energy storage system, input power of the grid), and reverse flow power ratio (ratio of reverse flow power to total output power), etc.

[0182] In this embodiment, the basis type refers to the category to which the reverse flow assessment basis belongs, such as power basis (output power of the energy storage system, input power of the grid), current basis (actual direction of current, preset grid connection direction), and reverse flow risk basis (reverse flow power ratio). Different basis types may correspond to different reverse flow judgment methods; the reverse flow judgment method refers to the specific method used to judge whether the energy storage system may have reverse flow based on the reverse flow assessment basis of different basis types. For example, for the power basis, a power threshold can be set. When the output power of the energy storage system is greater than the input power of the grid, and the difference exceeds the threshold, it is judged as "possible reverse flow"; for the current basis, the actual direction of the current is directly compared with the preset direction. When the current direction is opposite to the preset direction, it is judged as "possible reverse flow"; for the reverse flow risk basis, a threshold for the reverse flow power ratio is set. When the reverse flow power ratio exceeds the threshold, it is judged as "possible reverse flow".

[0183] In this embodiment, the reverse flow judgment result refers to the result obtained after judging the reverse flow assessment basis through the reverse flow judgment method, which is divided into two cases: "possible reverse flow" and "impossible reverse flow"; among them, when the basis type of the reverse flow assessment basis is current-based, the actual direction of the current is compared with the preset grid-connected direction. When the current direction is opposite to the preset direction, the reverse flow judgment result is possible reverse flow; when the basis type of the reverse flow assessment basis is power-based, the output power of the energy storage system and the input power of the grid are compared to determine whether there is a reverse flow trend; when the basis type of the reverse flow assessment basis is reverse flow risk, the reverse flow power ratio (the ratio of reverse flow power to total output power) is compared with a preset reverse flow power ratio threshold. If the threshold is exceeded, the reverse flow judgment result is possible reverse flow.

[0184] In this embodiment, the reference reverse flow basis refers to the reverse flow assessment basis when the reverse flow judgment result is "possible reverse flow"; the comprehensive reverse flow basis refers to a comprehensive judgment basis formed by summarizing all reference reverse flow bases; the set reverse flow judgment rule refers to a pre-set standard for judging whether the distributed energy storage system is actually reverse flow, for example, the current direction is opposite to the preset grid-connected direction, the output power of the energy storage system is greater than the input power of the grid, and the power difference exceeds the corresponding set threshold, and the reverse flow power ratio exceeds the corresponding set ratio threshold, then it is determined that there is a reverse flow; the actual reverse flow judgment result refers to the final judgment result obtained after comparing the comprehensive reverse flow basis with the set reverse flow judgment rule, clarifying whether the energy storage system is actually reverse flow; the dynamic anti-reverse flow control strategy refers to when it is determined that the energy storage system is actually reverse flow, the control strategy determined according to the comprehensive reverse flow basis is used to prevent the further occurrence or expansion of the reverse flow, such as reducing the output power of the PCS.

[0185] The beneficial effects of the above technical solution are: through real-time monitoring and analysis of PCS collected data, the basis for backflow assessment is obtained, and the backflow is accurately judged according to different backflow assessment bases and set backflow judgment rules. The corresponding dynamic anti-backflow control strategy is adopted to prevent the further occurrence or expansion of backflow, thereby ensuring the safe and stable operation of the energy storage system. Example 7:

[0186] The present invention provides a control method for a highway distributed energy storage system, which performs environmental safety monitoring on the current distributed energy storage system and performs targeted abnormal response based on the abnormal safety monitoring status, including:

[0187] Use pre-installed environmental data acquisition equipment to monitor the current environmental conditions of the distributed energy storage system in real time and obtain system environmental data;

[0188] Compare system environment data with preset environment safety thresholds, and mark system environment data that exceeds the preset environment safety thresholds as abnormal environment data;

[0189] Determine the type of environmental safety anomaly based on the abnormal environmental data, and collect all abnormal environmental data of the same environmental safety anomaly type to obtain an anomaly type-data set;

[0190] By analyzing the difference between the system environment data and the preset environmental safety threshold, the environmental anomaly coefficient is obtained;

[0191] The environmental anomaly coefficients of all abnormal environmental data in the anomaly type-dataset are summed up and calculated, and output as the comprehensive environmental anomaly coefficient of the corresponding environmental safety anomaly type of the current anomaly type-dataset;

[0192] Determine the safety anomaly level of the environmental safety anomaly type based on the comprehensive environmental anomaly coefficient;

[0193] The environmental security exception type and the corresponding security exception level are used as matching conditions, and the corresponding exception handling strategy is matched to perform targeted exception responses.

[0194] In this embodiment, the preset environmental data acquisition equipment refers to various sensors and monitoring devices pre-installed inside and around the distributed energy storage system, which are used to collect various data related to the system environment in real time. For example, smoke sensors, combustible gas sensors, temperature and humidity sensors, etc. are evenly distributed in the battery compartment; wind speed sensors, rain sensors, etc. are set around the energy storage system; system environmental data refers to a series of data obtained by real-time monitoring by the preset environmental data acquisition equipment, reflecting the environmental status of the distributed energy storage system, including environmental parameters such as temperature, humidity, and smoke concentration that affect the normal operation of the energy storage system; the preset environmental safety threshold is a series of critical values pre-set according to the design requirements of the distributed energy storage system and relevant safety standards for judging whether the environment is safe. When the system environmental data exceeds the corresponding threshold, it means that the environment may pose a threat to the safe operation of the energy storage system and needs to be processed accordingly; abnormal environmental data refers to system environmental data that exceeds the preset environmental safety threshold.

[0195] In this embodiment, the environmental safety anomaly type refers to the specific environmental safety problem category determined based on the monitored abnormal environmental data. The specific steps are to first extract the abnormal data characteristics of the abnormal environmental data (such as specific numerical values) and substitute them into the set judgment rules; then check one by one whether the conditions of a set judgment rule are met; finally, the abnormal type corresponding to the satisfied set judgment rule is output as the environmental safety anomaly type; wherein the set judgment rule is a series of judgment rules set based on historical data and relevant safety standards. For example, set judgment rule 1: if the smoke concentration increases (exceeds the set threshold A) and the temperature rises abnormally (the temperature value exceeds the set threshold B), it is judged that there is a fire hazard; set judgment rule 2: if only combustible gas leakage is detected (combustible gas concentration exceeds the set threshold C), and other parameters (such as temperature, smoke concentration, etc.) are within the normal range, it is judged to be a combustible gas leakage event.

[0196] In this embodiment, the abnormal type-data set is a data set formed by combining all abnormal environment data that are determined to be of the same environmental safety abnormality type; the environmental abnormality coefficient refers to the difference value of the system environmental data minus the corresponding preset environmental safety threshold, divided by the ratio of the corresponding preset environmental safety threshold, which is used to measure the severity of the environmental abnormality. The greater the difference, the higher the environmental abnormality coefficient; the comprehensive environmental abnormality coefficient is a value obtained by directly summing up the environmental abnormality coefficients of all abnormal environment data in the abnormal type-data set, which is used to comprehensively reflect the overall severity of the current environmental safety abnormality type; the safety abnormality level is obtained by screening from the set environmental safety abnormality level mapping table with the comprehensive environmental abnormality coefficient as the matching condition, wherein the set environmental safety abnormality level mapping table is composed of the comprehensive environmental abnormality coefficient value range and the corresponding safety abnormality level. The safety anomaly levels include minor anomalies, general anomalies, and severe anomalies. Different levels correspond to different degrees of urgency and abnormal response measures. The abnormality handling strategy refers to a set of pre-established response measures or operating procedures for different environmental safety anomaly types and safety anomaly levels. For example, when the environmental safety anomaly type is the presence of a fire hazard and the safety anomaly level is minor, the abnormality handling strategy is to start the ventilation equipment in the energy storage system to accelerate air circulation and reduce smoke concentration and temperature. If the safety anomaly level is severe, the abnormality handling strategy is to quickly cut off the main power supply of the energy storage system to prevent further spread of the fire, start the fire-fighting system, such as the sprinkler system or gas fire-extinguishing system (select the appropriate fire-fighting method according to the characteristics of the energy storage system), and immediately evacuate all personnel around the energy storage system and notify the fire department to rush to the scene for rescue.

[0197] The beneficial effects of the above technical solution are: by real-time monitoring of the system environmental conditions, potential safety hazards in the environment can be discovered in a timely manner, and by analyzing abnormal environmental data, the type of environmental safety anomaly and the degree of anomaly can be determined and quantified, which helps to accurately locate and classify abnormal situations, and provide a strong basis for the subsequent formulation of targeted processing strategies, thereby improving the efficiency and accuracy of abnormality processing, and thus helping to ensure the stability of highway power supply. Example 8:

[0198] The present invention provides a control platform for a highway distributed energy storage system. Figure 3 ,include:

[0199] Data acquisition module: used to collect battery status parameters in real time and output them as BMS feedback information in combination with the equalization judgment results of the battery equalization status;

[0200] Charge and discharge protection module: used by the target EMS to collect and analyze BMS feedback information, determine the key charge and discharge strategies for each battery pack, and execute them when feasible;

[0201] Strategy Optimization Module: This module is used to optimize and protect key charging and discharging strategies that are not feasible by adopting a strategy optimization mode that coordinates strategy safety degradation with a system joint compensation mechanism.

[0202] Anti-backflow control module: used by the target EMS to collect and analyze PCS data, determine dynamic anti-backflow control strategies and execute them to achieve dynamic anti-backflow control;

[0203] Abnormal response module: used to monitor the environmental safety of the current distributed energy storage system and make targeted abnormal responses based on the abnormal safety monitoring status.

[0204] The beneficial effects of the above technical solution are: by collecting battery status parameters and combining them with battery balancing judgment results as BMS feedback information output; the target EMS collects and analyzes BMS feedback information to determine the key charging and discharging strategies of the battery pack, and executes them when the strategy is feasible; a strategy optimization mode that cooperates with strategy safety degradation and system joint compensation mechanism is adopted to optimize and protect infeasible key charging and discharging strategies; the target EMS collects and analyzes PCS collected data to determine the dynamic anti-backflow control strategy and execute it; the system is monitored for environmental safety, and abnormal responses are made according to the monitoring conditions, which can ensure that the high-speed distributed energy storage system can flexibly adjust the charging and discharging behavior, effectively prevent the current from flowing back to the power grid, improve the system's intelligent control level and operating efficiency, and provide strong support for the energy supply and stable operation of the highway.

[0205] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A control method for a highway distributed energy storage system, characterized in that: include: Step 1: Collect battery status parameters in real time and output them as BMS feedback information in combination with the equalization judgment results of the battery equalization status; Step 2: The target EMS collects and analyzes BMS feedback information to determine the key charge and discharge strategies for each battery pack and executes them when feasible. Step 3: Adopt a strategy optimization model that combines strategy safety degradation with a system joint compensation mechanism to optimize and protect infeasible key charging and discharging strategies. Step 4: The target EMS collects and analyzes the data collected by the PCS, determines the dynamic anti-backflow control strategy and executes it to achieve dynamic anti-backflow control; Step 5: Conduct environmental safety monitoring of the current distributed energy storage system and respond to any abnormalities based on the safety monitoring status. Among them, a strategy optimization model that coordinates strategy safety degradation with system joint compensation mechanism is adopted to optimize and protect unfeasible key charging and discharging strategies, including: Mark the key charging and discharging strategies whose feasibility evaluation results show that the strategies are not feasible as strategies to be adjusted; According to the evaluation indicators that determine that the strategy to be adjusted is infeasible, the corresponding strategy degradation rules are matched; Based on all obtained policy downgrade rules, the policy to be adjusted is adjusted for security downgrade to obtain the downgraded policy. Execute the post-degradation strategy adapted to the battery pack to which it belongs and perform corresponding charge and discharge protection; When the downgraded strategy is not compatible with the corresponding battery pack, the system linkage compensation mechanism is activated to provide compensation support.

2. The control method of a highway distributed energy storage system according to claim 1, characterized in that: Real-time collection of battery status parameters and combined with the equalization judgment results of the battery equalization status as BMS feedback information output, including: Use pre-installed data acquisition equipment to collect battery status parameters of each battery pack in the current distributed energy storage system and transmit them to the target BMS; The target BMS analyzes and calculates the battery status parameters of the battery pack to obtain battery balancing judgment parameters; The balancing judgment result is obtained by comparing the battery balancing judgment parameter of the current battery pack with the corresponding preset balancing judgment threshold; If the balancing judgment result of the battery balancing judgment parameter is unbalanced, the corresponding battery group will be marked as an unbalanced battery group; Obtain and use the algorithm adaptation factor of the unbalanced battery pack as the algorithm matching condition to match the corresponding preset balancing algorithm; The battery status parameters, balancing judgment results, and preset balancing algorithms of unbalanced battery packs of each battery pack in the current distributed energy storage system are transmitted to the target EMS as BMS feedback information.

3. The control method of a highway distributed energy storage system according to claim 1, characterized in that: The target EMS collects and analyzes BMS feedback information to determine the key charge and discharge strategies for each battery pack and executes them when feasible, including: The target EMS determines a pre-balancing strategy for the unbalanced battery group according to a preset balancing algorithm for the unbalanced battery group in the BMS feedback information; By comparing the battery state parameters of the battery pack with corresponding set state thresholds, a state comparison result is obtained; Determine the key charge and discharge strategy of the current battery pack based on the status comparison results; Input the battery state parameters of the battery pack into a pre-established charge and discharge capacity prediction model to output the predicted charge and discharge performance of the battery pack under different battery operating conditions; The predicted charge and discharge performance of each battery pack corresponding to the battery operating condition that is most similar to the operating condition in the preset time period is regarded as the reference charge and discharge performance; For unbalanced battery packs, the corresponding reference charge and discharge performance and pre-balancing strategy are used as feasibility evaluation indicators to evaluate the feasibility of the key charge and discharge strategy. If the feasibility evaluation result shows that the strategy is feasible, the key charge and discharge strategy is executed to protect the current unbalanced battery pack while executing the pre-balancing strategy. For battery packs other than unbalanced battery packs, the corresponding reference charge and discharge performance is used as a feasibility evaluation indicator to evaluate the feasibility of the key charge and discharge strategy. If the feasibility evaluation result shows that the strategy is feasible, the key charge and discharge strategy is executed to perform charge and discharge protection on the current battery pack.

4. The control method of a highway distributed energy storage system according to claim 1, characterized in that: Start the system linkage compensation mechanism to conduct compensation analysis, including: Marking a degraded strategy that is not compatible with the battery group to which it belongs as a compensation analysis strategy, and marking the battery group to which the compensation analysis strategy belongs as a compensation analysis battery group; Obtain the reasons for the incompatibility between the compensation analysis battery pack and the corresponding compensation analysis strategy, and then determine a single compensation target based on the reasons for the incompatibility; The real-time battery status data of all adjacent linked battery groups corresponding to the current compensation analysis battery group and the single compensation target are input into a pre-established adjacent linked compensation model to obtain an adjacent linked compensation result; According to the neighboring linkage compensation result, if a neighboring linkage compensation scheme exists, the current distributed energy storage system executes the neighboring linkage compensation scheme and provides strategic support for the current compensation analysis battery group; If there is no adjacent linkage compensation scheme, the current compensation analysis battery group is marked as a deep linkage battery group, and the corresponding compensation analysis strategy is marked as a deep linkage strategy; By integrating the deep linkage battery group and deep linkage strategy into the pre-established compensation estimation model, the estimated compensation target of the current distributed energy storage system is output; Obtain the pre-configured system linkage list of the current distributed energy storage system, and prioritize each linkage energy storage system in the pre-configured system linkage list by comprehensively considering system distance, system linkage delay, and short-term and long-term charging and discharging effects to obtain a system optimization score; Sort each linked energy storage system in the preset system linkage list from largest to smallest according to the system optimization score to obtain a linkage system optimization sequence; Input the real-time system operation data, linkage system optimization sequence and estimated compensation target of each linkage energy storage system in the preset system linkage list into the pre-established system linkage compensation model to obtain the system linkage compensation result; Based on the system linkage compensation result, if a system linkage compensation plan exists, the system linkage compensation plan is executed to provide strategic support for the current distributed energy storage system; If there is no system linkage compensation plan, the preset hierarchical protection mechanism will be activated.

5. The control method of a highway distributed energy storage system according to claim 1, characterized in that: The target EMS collects and analyzes data collected by the PCS to determine and execute dynamic anti-backflow control strategies to achieve dynamic anti-backflow control, including: The target EMS receives the PCS collected data from the PCS, extracts the evaluation basis, and obtains the countercurrent evaluation basis; According to the type of basis for the backflow assessment, the corresponding backflow judgment method is matched to obtain the backflow judgment result; The backflow assessment basis with the backflow judgment result of possible backflow is marked as reference backflow basis; If there is no reference reverse flow basis at present, it is determined that the energy storage system does not have reverse flow; If there is currently a reference countercurrent basis, all reference countercurrent bases are summarized to obtain a comprehensive countercurrent basis; Compare the comprehensive backflow basis with the set backflow judgment rule to determine the actual backflow judgment result of the current distributed energy storage system; When the actual backflow judgment result is backflow, the comprehensive backflow basis is used as a screening condition to determine the dynamic anti-backflow control strategy and execute it to achieve dynamic anti-backflow control.

6. The control method of a highway distributed energy storage system according to claim 1, characterized in that: Conduct environmental safety monitoring of the current distributed energy storage system and make targeted abnormal responses based on abnormal safety monitoring conditions, including: Use pre-installed environmental data acquisition equipment to monitor the current environmental conditions of the distributed energy storage system in real time and obtain system environmental data; Compare system environment data with preset environment safety thresholds, and mark system environment data that exceeds the preset environment safety thresholds as abnormal environment data; Determine the type of environmental safety anomaly based on the abnormal environmental data, and collect all abnormal environmental data of the same environmental safety anomaly type to obtain an anomaly type-data set; By analyzing the difference between the system environment data and the preset environmental safety threshold, the environmental anomaly coefficient is obtained; The environmental anomaly coefficients of all abnormal environmental data in the anomaly type-dataset are summed up and calculated, and output as the comprehensive environmental anomaly coefficient of the corresponding environmental safety anomaly type of the current anomaly type-dataset; Determine the safety anomaly level of the environmental safety anomaly type based on the comprehensive environmental anomaly coefficient; The environmental security exception type and the corresponding security exception level are used as matching conditions, and the corresponding exception handling strategy is matched to perform targeted exception responses.

7. A control platform for a highway distributed energy storage system, characterized in that: include: Data acquisition module: used to collect battery status parameters in real time and output them as BMS feedback information in combination with the equalization judgment results of the battery equalization status; Charge and discharge protection module: used by the target EMS to collect and analyze BMS feedback information, determine the key charge and discharge strategies for each battery pack, and execute them when feasible; Strategy Optimization Module: This module is used to optimize and protect key charging and discharging strategies that are not feasible by adopting a strategy optimization mode that coordinates strategy safety degradation with a system joint compensation mechanism. Anti-backflow control module: used by the target EMS to collect and analyze PCS data, determine dynamic anti-backflow control strategies and execute them to achieve dynamic anti-backflow control; Abnormal response module: used to monitor the environmental safety of the current distributed energy storage system and make targeted abnormal responses based on the abnormal safety monitoring status; Among them, the strategy optimization module includes: Mark the key charging and discharging strategies whose feasibility evaluation results show that the strategies are not feasible as strategies to be adjusted; According to the evaluation indicators that determine that the strategy to be adjusted is infeasible, the corresponding strategy degradation rules are matched; Based on all obtained policy downgrade rules, the policy to be adjusted is adjusted for security downgrade to obtain the downgraded policy. Execute the post-degradation strategy adapted to the battery pack to which it belongs and perform corresponding charge and discharge protection; When the downgraded strategy is not compatible with the corresponding battery pack, the system linkage compensation mechanism is activated to provide compensation support.

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