Energy storage coordination control method, system and equipment

Abstract

The invention discloses an energy storage coordination control method, system and equipment. Through receiving node state data of a corresponding energy storage node sent by each agent, each agent collects the node state data in real time and periodically sends the node state data; determining a first residual available capacity of the distributed energy storage system according to the state data of each node; and determining a first load distribution value of each energy storage node according to the first residual available capacity in combination with the predicted energy storage load demand, so as to carry out load distribution according to the first load distribution value. According to the method, by periodically obtaining the node state data of the energy storage nodes, the latest state of each energy storage node can be updated and mastered in time, meanwhile, by combining with reasonable prediction of the energy storage load demand quantity, optimization of load distribution of each energy storage node under specific conditions is achieved, the energy utilization efficiency and economic benefits are improved, and the method is suitable for large-scale popularization and application. And stable power supply can still be ensured when the load demand fluctuates, and the power supply reliability and flexibility of the distributed energy storage system are enhanced.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to an energy storage coordinated control method, system and device. Background Art

[0002] With the rapid development of renewable energy, distributed energy storage systems are playing an increasingly important role in power systems. These systems can effectively alleviate the imbalance between electricity supply and demand and improve the stability and reliability of the power grid.

[0003] However, in traditional distributed energy storage systems, the load distribution method is mostly a static configuration method. This method cannot adaptively adjust the load distribution amount of each energy storage node according to real-time status data, which may cause some energy storage nodes to be overloaded or idle. The capacity of the energy storage equipment cannot be fully utilized, resulting in low energy utilization efficiency. When the load demand fluctuates, the static configuration method cannot guarantee the stability and safety of power supply. Summary of the invention

[0004] The present invention provides a method, system and device for coordinated energy storage control to solve the problem that traditional energy storage systems cannot adaptively adjust load distribution when load demand fluctuates, resulting in reduced system performance, reduced energy utilization efficiency, and even affecting power supply stability and safety.

[0005] In a first aspect, an embodiment of the present invention provides an energy storage coordinated control method, which is applied to an energy storage coordinated control system. The energy storage coordinated control system includes a control terminal and at least one intelligent agent, and the intelligent agent is installed on each energy storage node of a distributed energy storage system. The method is executed by the control terminal, and the method includes:

[0006] Receiving node status data of corresponding energy storage nodes sent by each of the intelligent agents, each of the intelligent agents collects the node status data in real time and sends it periodically;

[0007] Determining a first remaining available capacity of the distributed energy storage system according to each of the node status data;

[0008] According to the first remaining available capacity and in combination with the predicted energy storage load demand, a first load distribution value of each energy storage node is determined so as to perform load distribution according to the first load distribution value.

[0009] In a second aspect, an embodiment of the present invention provides an energy storage coordination control system, the system comprising: a control terminal and at least one intelligent agent, the intelligent agent being installed on each energy storage node of a distributed energy storage system,

[0010] The control terminal comprises:

[0011] A data receiving module, used to receive node status data of the corresponding energy storage node sent by each of the intelligent agents, and each of the intelligent agents collects the node status data in real time and sends it periodically;

[0012] A capacity determination module, configured to determine a first remaining available capacity of the distributed energy storage system according to each of the node status data;

[0013] The load determination module is used to determine a first load distribution value of each of the energy storage nodes according to the first remaining available capacity in combination with the predicted energy storage load demand, so as to perform load distribution according to the first load distribution value.

[0014] In a third aspect, an embodiment of the present invention provides an electronic device, serving as a control terminal and / or an intelligent agent in the energy storage coordinated control system, the electronic device comprising:

[0015] at least one processor;

[0016] and a memory communicatively coupled to the at least one processor;

[0017] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the energy storage coordinated control method described in any embodiment of the present invention.

[0018] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the energy storage coordination control method described in any embodiment of the present invention when executed.

[0019] The technical solution of the embodiment of the present invention receives the node status data of the corresponding energy storage node sent by each intelligent agent, and each intelligent agent collects the node status data in real time and sends it periodically; according to each node status data, the first remaining available capacity of the distributed energy storage system is determined; according to the first remaining available capacity, combined with the predicted energy storage load demand, the first load distribution value of each energy storage node is determined to distribute the load according to the first load distribution value. This method can timely update and grasp the latest status of each energy storage node by periodically acquiring the node status data of the energy storage node, and at the same time, combined with the reasonable prediction of the energy storage load demand, it realizes the optimization of the load distribution of each energy storage node under specific circumstances, improves the energy utilization efficiency and economic benefits, and ensures stable power supply when the load demand fluctuates, thereby enhancing the power supply reliability and flexibility of the distributed energy storage system.

[0020] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 A flow chart of an energy storage coordinated control method provided by an embodiment of the present invention;

[0023] Figure 2 A schematic diagram of the structure of a control terminal in an energy storage coordinated control system provided by an embodiment of the present invention;

[0024] Figure 3 A schematic diagram of the structure of an electronic device that can be used to implement an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] It should be noted that traditional distributed energy storage systems often use static configuration to distribute loads. This method cannot adaptively adjust the load distribution according to real-time status data, causing some energy storage nodes to be overloaded or idle, resulting in low energy utilization efficiency and failure to fully utilize the capacity of energy storage equipment. When load demand fluctuates, the static configuration method cannot guarantee the stability and safety of power supply.

[0028] Based on this, an embodiment of the present invention provides an energy storage coordination control method, which is applied to an energy storage coordination control system. The energy storage coordination control system includes a control terminal and at least one intelligent agent, and the intelligent agent is installed on each energy storage node of a distributed energy storage system.

[0029] Among them, the control terminal can be understood as a physical device or software system used to receive data from each intelligent agent, analyze and make decisions on the received data, and then issue control instructions. The intelligent agent can be understood as a small control unit deployed on each energy storage node of the distributed energy storage system, which is used to monitor and manage the status and behavior of the energy storage node to which the intelligent agent belongs, such as health detection, temperature control, etc. The intelligent agent can be a hardware device or a software program. The distributed energy storage system can be understood as a network system composed of multiple energy storage nodes. The energy storage nodes are scattered in different locations of the power grid. Each energy storage node can independently store and release energy to meet local power demand or support the stability of the entire power grid.

[0030] Figure 1 A flow chart of a method for coordinated energy storage control provided in an embodiment of the present invention. The embodiment of the present invention can be applied to scenarios for coordinating load distribution of energy storage nodes in a distributed energy storage system. The method can be executed by a control terminal in an energy storage coordinated control system. The control terminal can be implemented in the form of software and / or hardware, and optionally, can be implemented by an electronic device, which is preferably a mobile terminal, a desktop computer, a laptop computer, a server, etc.

[0031] like Figure 1 As shown, the energy storage coordinated control method provided by the embodiment of the present invention may specifically include:

[0032] S101, receiving node status data of corresponding energy storage nodes sent by each intelligent agent, and each intelligent agent collects node status data in real time and sends it periodically.

[0033] Among them, node status data can be understood as the real-time status information of the energy storage node, such as power level, health status, charging and discharging status, as well as real-time temperature, current and voltage information.

[0034] In this embodiment, each intelligent agent installed on each energy storage node of the distributed energy storage system collects the node status data of the corresponding energy storage node in real time, and periodically (i.e., regularly) sends the collected node status data to the control terminal, and the control terminal receives the node status data of the corresponding energy storage node sent by each intelligent agent.

[0035] S102: Determine a first remaining available capacity of the distributed energy storage system according to status data of each node.

[0036] The first remaining available capacity may be understood as the remaining available energy storage capacity of the entire distributed energy storage system calculated by the control terminal after receiving the node status data.

[0037] In this embodiment, the total capacity that can be provided by the entire distributed energy storage system and the capacity that has been allocated or used can be obtained based on the status data of each node, thereby determining the first remaining available capacity of the distributed energy storage system. The remaining available capacity of each energy storage node can also be determined by calculating the total capacity of each energy storage node and the capacity that has been allocated or used, and the first remaining available capacity of the distributed energy storage system is obtained by accumulating the remaining available capacity of each energy storage node.

[0038] S103: Determine a first load distribution value for each energy storage node based on the first remaining available capacity and the predicted energy storage load demand, so as to perform load distribution according to the first load distribution value.

[0039] The energy storage load demand can be understood as the power demand that the energy storage system needs to provide in a specific time period. The first load distribution value can be understood as the energy storage load demand that each energy storage node needs to bear in a future period of time.

[0040] In this embodiment, based on the first remaining available capacity and the predicted energy storage load demand, as well as information such as the load that each node can bear, a first load distribution value assigned to each energy storage node is determined, and load distribution is performed for each energy storage node according to the first load distribution value.

[0041] An energy storage coordination control method provided by an embodiment of the present invention receives node status data of corresponding energy storage nodes sent by each intelligent agent, and each intelligent agent collects node status data in real time and sends it periodically; determines the first remaining available capacity of the distributed energy storage system according to the node status data; determines the first load distribution value of each energy storage node according to the first remaining available capacity, combined with the predicted energy storage load demand, so as to distribute the load according to the first load distribution value. This method can timely update and grasp the latest status of each energy storage node by periodically acquiring the node status data of the energy storage node, and at the same time, combined with the reasonable prediction of the energy storage load demand, realizes the optimization of the load distribution of each energy storage node under specific circumstances, improves the energy utilization efficiency and economic benefits, and ensures stable power supply when the load demand fluctuates, thereby enhancing the power supply reliability and flexibility of the distributed energy storage system.

[0042] As a first optional embodiment of this embodiment, based on the above embodiment, the node status data may be concretized to include:

[0043] The first current capacity, current load, charge and discharge power, voltage, current, temperature and internal impedance data of the energy storage node.

[0044] Among them, the first current capacity can be understood as the amount of electric energy currently stored in each energy storage node, which is used to evaluate the remaining available capacity and availability of each energy storage node. The current load can be understood as the amount of electric power currently provided by each energy storage node, which is used to help understand the immediate working status and energy flow of each energy storage node.

[0045] The above technical solution of this embodiment ensures the safe, reliable and efficient operation of the distributed energy storage system by continuously monitoring and analyzing the above key parameters in the node status data, and provides strong support for fault diagnosis, performance evaluation and optimized management of the distributed energy storage system.

[0046] As a second optional embodiment of this embodiment, based on the above embodiment, the first remaining available capacity of the distributed energy storage system can be determined according to the node status data, which can be concretized into the following steps:

[0047] a1) receiving energy storage availability status information fed back by each of the intelligent agents relative to the energy storage node, and determining a first available mark value of each of the energy storage nodes.

[0048] Among them, the energy storage available status information can be understood as information used to reflect whether the energy storage node is currently in an available state, and can include two state information: the energy storage node is available and the energy storage node is unavailable. The first available mark value can be understood as the mark value used to indicate the availability or health status of each energy storage node marked by the control terminal for each energy storage node based on the received energy storage available status information, so as to determine whether the energy storage node can participate in the current operation of the distributed energy storage system or power grid.

[0049] In this embodiment, each intelligent agent determines the energy storage available status information of each energy storage node based on the node status data of each energy storage node collected in real time, and sends the energy storage available status information to the control terminal. The control terminal receives the energy storage available status information fed back by each intelligent agent relative to the energy storage node, and marks the first available tag value for the corresponding energy storage node according to each energy storage available status information. The first available tag value can be 0 or 1. A value of 0 indicates that the energy storage node is unavailable, and a value of 1 indicates that the energy storage node is available.

[0050] Exemplarily, if the energy storage availability status information fed back by a certain intelligent agent relative to the energy storage node received by the control terminal indicates that the energy storage node is available, then the first available mark value marked for the energy storage node is 1; if the energy storage availability status information fed back by a certain intelligent agent relative to the energy storage node received by the control terminal indicates that the energy storage node is unavailable, then the first available mark value marked for the energy storage node is 0.

[0051] b1) determining a first remaining available capacity of the distributed energy storage system according to each of the first available mark values ​​and a first current capacity in each of the node status data.

[0052] In this embodiment, whether the corresponding energy storage node is available can be judged according to the first available mark value. If available, the first current capacity contained in the node status data of the energy storage node is determined, and the first current capacities corresponding to all available energy storage nodes are accumulated to determine the first remaining available capacity of the distributed energy storage system.

[0053] In this embodiment, the first available mark value of each energy storage node and the first current capacity in the corresponding node status data may be multiplied and added together to determine the first remaining available capacity of the distributed energy storage system. The specific formula may be expressed as:

[0054]

[0055] Among them, C total is the first remaining available capacity, N is the total number of energy storage nodes, C i For the i The first current capacity in the node status data corresponding to the energy storage node, Hi is the first available mark value of the i-th energy storage node.

[0056] The above technical solution of this embodiment summarizes the first available capacity of each energy storage node based on the availability of each energy storage node, thereby accurately determining the first remaining available capacity of the distributed energy storage system, thereby improving the reliability and effectiveness of subsequent coordinated control of the distributed energy storage system.

[0057] As one implementation manner, this optional embodiment may further specify the first load distribution value of each energy storage node according to the first remaining available capacity in combination with the predicted energy storage load demand as follows:

[0058] a2) Obtaining the energy storage load demand predicted by the distributed energy storage system through the historical load data of each energy storage node using a time series analysis method.

[0059] In this embodiment, a time series analysis method is used to analyze the historical load data of each energy storage node, so as to predict the energy storage load demand that the distributed energy storage system may need to bear at a specific moment in the future.

[0060] b2) For each energy storage node, determine a first capacity ratio of the energy storage node, and determine the product of the first capacity ratio and the energy storage load demand as the first load distribution value of the energy storage node, wherein the first capacity ratio is a first quotient of a first product of the first available mark value and the first current capacity and the first remaining available capacity.

[0061] The first capacity ratio may be understood as the ratio of the first current capacity actually available to each energy storage node to the first remaining available capacity of the distributed energy storage system.

[0062] In this embodiment, the corresponding first load distribution value is determined for each energy storage node, firstly, the first product value of the first available mark value and the first current capacity is obtained, then the first quotient value between the first product value and the first remaining available capacity is obtained, and the first quotient value is determined as the first capacity ratio, and then the product value of the first capacity ratio and the energy storage load demand is obtained, and the product value is determined as the first load distribution value of the energy storage node. For better understanding, the formula for determining the first load distribution value can be expressed as:

[0063]

[0064] Among them, L i is the first load distribution value of the i-th energy storage node, and R(t) is the predicted energy storage load demand at time t.

[0065] The above technical solution of this embodiment adopts the time series analysis method to predict the future energy storage load demand, and then determines the first load distribution value of each energy storage node according to the availability of each energy storage node, the first current capacity and the predicted energy storage load demand, thereby realizing flexible and reasonable adjustment of the first load distribution value of each energy storage node, improving energy utilization efficiency, and at the same time improving the stability, reliability and safety of power supply when load demand fluctuates, so as to give full play to the capacity of the distributed energy storage system.

[0066] As a third optional embodiment of this embodiment, based on the above embodiment, it also includes:

[0067] a3) Upon receiving energy storage node fault information sent by the target intelligent agent, the energy storage node corresponding to the energy storage node fault information is determined as a faulty node, and the power grid is controlled to disconnect from the faulty node, wherein the energy storage node fault information is generated and sent when the target intelligent agent confirms that the energy storage node to which it belongs is a faulty node.

[0068] In this embodiment, the target intelligent agent can be understood as an intelligent agent that confirms that the energy storage node to which it belongs is a faulty node. When the target intelligent agent confirms that the energy storage node to which it belongs has a fault, it generates and sends energy storage node fault information to the control terminal, wherein the energy storage node fault information may include node status data, operation information, health status and / or parameter information of the energy storage node confirmed to have a fault. When the control terminal receives the energy storage node fault information sent by the target intelligent agent, it determines the corresponding energy storage node as a faulty node according to the energy storage node fault information, controls the power grid to disconnect from the faulty node, and sets the first available mark value of the faulty node to the energy storage node being unavailable, i.e., 0.

[0069] b3) Acquire the current target load of the faulty node, and determine a second remaining available capacity of the distributed energy storage system after excluding the faulty node.

[0070] The current target load can be understood as the load borne by the faulty node before the fault occurs. The second remaining available capacity can be understood as the remaining available energy storage capacity value in the distributed energy storage system after disconnecting the faulty node.

[0071] In this embodiment, the current target load of the faulty node can be obtained from the received energy storage node fault information, and the second remaining available capacity of the distributed energy storage system after the faulty node is re-determined, that is, the second remaining available capacity can be obtained by subtracting the current capacity of the faulty node from the first remaining available capacity, or the second remaining available capacity can be obtained by calculating according to the formula provided in b1). It can be understood that the calculation method for calculating the second remaining available capacity can be the same as the calculation method provided in b1).

[0072] c3) allocating the current target load to the other energy storage nodes according to the second remaining available capacity and the node status data of the other energy storage nodes except the faulty node.

[0073] In this embodiment, based on the second remaining available capacity and the node status data of other energy storage nodes except the faulty node, the current target load of the faulty node is reasonably distributed to other available energy storage nodes according to certain rules, such as giving priority to nodes with larger current capacity and allocating capacity according to a certain ratio, or uniformly allocating capacity to each available energy storage node according to a certain ratio.

[0074] The above technical scheme of this embodiment determines that the corresponding energy storage node is a faulty node when receiving the energy storage node fault information sent by the target intelligent body, and controls the power grid to disconnect from the faulty node. At the same time, according to the second remaining available capacity and the node status data of other energy storage nodes except the faulty node, the current target load is distributed to the other energy storage nodes, thereby ensuring that the distributed energy storage system can respond quickly and isolate the faulty node quickly when the energy storage node fails, and reasonably distribute the current target load on the faulty node, effectively preventing cascading failures caused by the failure of a single energy storage node, so that the distributed energy storage system can still maintain stable and reliable operation when a single point failure occurs, thereby ensuring the stability and operation efficiency of the power grid.

[0075] As one implementation method, this optional embodiment may further specify the following content in which the current target load allocation value is allocated to the other energy storage nodes according to the second remaining available capacity and the node status data of the other energy storage nodes except the faulty node:

[0076] a4) For each other energy storage node except the faulty node, obtain a second current capacity from the corresponding node status data, and determine a second available mark value of the other energy storage node.

[0077] The second current capacity can be understood as the amount of electric energy currently stored in each other energy storage node except the node that is currently faulty. The second available mark value can be understood as the mark value used to indicate the availability of each energy storage node when the faulty node is marked by the control terminal to determine whether the energy storage node can participate in the current operation of the distributed energy storage system or power grid.

[0078] In this embodiment, for each other energy storage node except the currently determined faulty node, the second current capacity is obtained from the corresponding node status data of each energy storage node, and the second available mark value of each other energy storage node is determined.

[0079] b4) Determine a second capacity ratio of the other energy storage nodes according to the second current capacity, the second available mark value and the second remaining available capacity.

[0080] The second capacity ratio may be understood as the ratio of the second current capacity actually available to each energy storage node to the second remaining available capacity of the distributed energy storage system.

[0081] In this embodiment, the second current capacity of each energy storage node is multiplied by the second available mark value to obtain a product value to determine the actually available second current capacity of each energy storage node, that is, if the second available mark value is 1 (that is, the energy storage node has not failed and is available), the actually available second current capacity is the second current capacity of the energy storage node, and if the second available mark value is 0 (that is, the energy storage node has failed and is unavailable), the actually available second current capacity is 0. Then, each of the product values ​​is divided by the second remaining available capacity to obtain the second capacity ratio of each other energy storage node.

[0082] c4) determining the product value of the second capacity ratio and the current target load as the second load distribution value of the other energy storage nodes, so as to perform load distribution according to the second load distribution value.

[0083] The second load distribution value may be understood as the new load that each of the other energy storage nodes needs to bear, and is used to share the current target load originally borne by the faulty node.

[0084] In this embodiment, the product of the second capacity ratio of each other energy storage node and the current target load is determined as the second load distribution value corresponding to the other energy storage nodes, and the load of each other energy storage node is distributed according to the determined second load distribution value.

[0085] The above technical scheme of this embodiment determines the second load distribution value of each other energy storage node according to the second current capacity and the second available mark value of each other energy storage node except the faulty node, and combines the second remaining available capacity and the current target load, so as to distribute the load according to the second load distribution value, thereby ensuring that the distributed energy storage system can respond and take measures in a timely manner when facing a single point failure, so that the current target load borne by the faulty node is evenly distributed among the healthy energy storage nodes, avoiding overload or no load of a single energy storage node, thereby improving the utilization efficiency of the second remaining available capacity, realizing the stable operation of the distributed energy storage system, and reducing the impact of single point failures on the stability of the power grid.

[0086] As another implementation manner, this optional embodiment may further specify the step of the target intelligent agent confirming that the energy storage node to which it belongs is a faulty node as follows:

[0087] a5) The target intelligent agent sends fault collaborative verification information to the adjacent intelligent agents of the adjacent energy storage nodes.

[0088] Among them, the fault collaborative verification information can be understood as information containing various monitoring data monitored by the target intelligent agent through the sensor array during the process of monitoring the energy storage node to which it belongs, and is used to provide fault information to adjacent intelligent agents so that the adjacent intelligent agents can assist in confirming whether the target intelligent agent has a fault.

[0089] In this embodiment, normal ranges and fault thresholds are set in advance for key parameters of each energy storage node (such as voltage, current, temperature, and internal impedance data) based on historical data and equipment specifications. When the target intelligent agent detects that the energy storage node to which it belongs may have a fault, that is, when the key parameters collected in real time exceed the set fault threshold, fault collaborative verification information is immediately generated and sent to the adjacent intelligent agent.

[0090] b5) Each of the adjacent intelligent agents performs fault verification on the energy storage node to which the target intelligent agent belongs according to the fault collaborative verification information.

[0091] In this embodiment, after receiving the fault collaborative verification information, each of the adjacent intelligent agents of the target intelligent agent uses the monitoring data obtained by monitoring its own energy storage node to compare with the monitoring data of the energy storage node to which the target intelligent agent belongs contained in the fault collaborative verification information. If the monitoring data of the energy storage node to which the target intelligent agent belongs has obvious abnormalities, the fault verification result of the energy storage node to which the target intelligent agent belongs is confirmed to be a fault state, and the fault verification result is fed back to the target intelligent agent after the fault verification is completed.

[0092] c5) The target intelligent agent confirms the fault of the energy storage node to which it belongs based on the fault verification results fed back by each of the adjacent intelligent agents.

[0093] In this embodiment, the target agent receives the fault verification results fed back by each of the adjacent agents and confirms the fault of the energy storage node to which it belongs. If more than a certain proportion of the adjacent agents in the received fault verification results feed back a fault state, it is determined that the fault state of the energy storage node to which it belongs is established, and the energy storage node fault information is sent to the control terminal.

[0094] The above technical scheme of this embodiment coordinates fault verification through multiple adjacent intelligent agents, and confirms the fault of the energy storage node according to the fault verification results fed back by each adjacent intelligent agent. Even if the detection result of a certain intelligent agent is inaccurate or interfered with, the verification results of other intelligent agents can provide additional verification, thereby reducing the false positives and missed positives of the target intelligent agent's faults and enhancing the robustness and reliability of the entire distributed energy storage system.

[0095] As a third implementation manner, this optional embodiment also includes:

[0096] a6) Upon receiving the fault recovery information fed back by the target intelligent agent relative to the fault node to which it belongs, the fault node corresponding to the fault recovery information is determined as the recovery node, and the power grid is controlled to reconnect with the recovery node, wherein the fault recovery information is generated by the target intelligent agent monitoring the node key parameters of the fault node to which it belongs in real time, and when it is determined that the node key parameters remain within the set range for a set period of time.

[0097] Among them, the fault recovery information can be understood as information used to inform the control terminal that the faulty node has resumed normal working status. The fault recovery information may include key node parameters collected by the target intelligent agent, and the key node parameters may include current, voltage, temperature and internal impedance data.

[0098] It should be noted that the target intelligent body of the faulty node will monitor and verify the key node parameters of the faulty node in real time, and send the verification results to the control terminal.

[0099] In this embodiment, when the key node parameters of the faulty node monitored by the target agent in real time within a period of time are all within the preset key normal range of the node after verification, the target agent will generate fault recovery information and send it to the control terminal. When the control terminal receives the fault recovery information fed back by the target agent relative to the faulty node, the faulty node corresponding to the fault recovery information is determined as a recovery node, and the power grid is controlled to reconnect to the recovery node, and the available mark value of the recovery node is set to 1, indicating that the recovery node is available.

[0100] b6) Determine a third remaining available capacity of the distributed energy storage system after adding the recovery node.

[0101] The third remaining available capacity may be understood as the total remaining available energy storage capacity of the distributed energy storage system determined after taking into account the available capacity of the recovery node.

[0102] In this embodiment, the third remaining available capacity can be obtained by adding the remaining available capacity of the distributed energy storage system before controlling access to the recovery node to the available capacity of the recovery node, or by accumulating the product of the current available capacity of each energy storage node and the corresponding available mark value.

[0103] c6) determining a third load distribution value of each energy storage node according to the third remaining available capacity and in combination with node status data of each energy storage node in the distributed energy storage system, so as to perform load distribution according to the third load distribution value.

[0104] Among them, the third load distribution value can be understood as the distribution amount that each energy storage node needs to bear in the future period after the predicted energy storage load demand is redistributed to each energy storage node including the recovery node after accessing the recovery node.

[0105] In this embodiment, the actual available capacity of each energy storage node is determined based on the product value of the available mark value of each energy storage node and the current capacity in the node status data, and then the ratio of the actual available capacity of each energy storage node to the total remaining available capacity of the distributed energy storage system is calculated to determine the allocation ratio of each energy storage node, and then the product value of each ratio and the energy storage load demand is obtained, and each product value is determined as the third load distribution value of each energy storage node, and load distribution is performed according to the third load distribution value.

[0106] The above technical solution of this embodiment determines the fault node corresponding to the fault recovery information as the recovery node when the fault recovery information is received, and controls the power grid to reconnect with the recovery node. At the same time, according to the third remaining available capacity combined with the node status data of each energy storage node, the third load distribution value of each energy storage node is determined, so as to ensure that the distributed energy storage system automatically connects to the power grid after the energy storage node fails and recovers, and re-allocates the energy storage load demand to each energy storage node, so that the distributed energy storage system can respond to the failure and recovery of the node more flexibly, thereby improving the overall safety, reliability and efficiency of the distributed energy storage system, and then maintaining the stable operation of the power grid.

[0107] Figure 2 The schematic diagram of the structure of a control terminal in an energy storage coordination control system provided by an embodiment of the present invention includes a control terminal and at least one intelligent agent, and the intelligent agent is installed on each energy storage node of a distributed energy storage system. Figure 2 As shown, the control terminal includes: a data receiving module 21, a capacity determination module 22 and a load determination module 23, wherein:

[0108] The data receiving module 21 is used to receive the node status data of the corresponding energy storage node sent by each of the intelligent agents. Each of the intelligent agents collects the node status data in real time and sends it periodically. The node status data includes: the first current capacity, current load, charge and discharge power, voltage, current, temperature and internal impedance data of the energy storage node;

[0109] A capacity determination module 22, configured to determine a first remaining available capacity of the distributed energy storage system according to each of the node status data;

[0110] The load determination module 23 is used to determine a first load distribution value of each of the energy storage nodes according to the first remaining available capacity and the predicted energy storage load demand, so as to perform load distribution according to the first load distribution value.

[0111] An energy storage coordination control system provided by an embodiment of the present invention receives node status data of corresponding energy storage nodes sent by each intelligent agent, and each intelligent agent collects node status data in real time and sends it periodically; determines the first remaining available capacity of the distributed energy storage system according to the node status data; determines the first load distribution value of each energy storage node according to the first remaining available capacity, combined with the predicted energy storage load demand, so as to distribute the load according to the first load distribution value. This method can timely update and grasp the latest status of each energy storage node by periodically acquiring the node status data of the energy storage node, and at the same time, combined with the reasonable prediction of the energy storage load demand, realizes the optimization of the load distribution of each energy storage node under specific circumstances, improves the energy utilization efficiency and economic benefits, and ensures stable power supply when the load demand fluctuates, thereby enhancing the power supply reliability and flexibility of the distributed energy storage system.

[0112] Furthermore, the capacity determination module 22 may be specifically used for:

[0113] Receiving energy storage availability status information fed back by each of the intelligent agents relative to the energy storage node, and determining a first available mark value of each of the energy storage nodes;

[0114] A first remaining available capacity of the distributed energy storage system is determined according to each of the first available mark values ​​and the first current capacity in each of the node status data.

[0115] Furthermore, the load determination module 23 may be specifically used for:

[0116] Obtaining the energy storage load demand predicted by the distributed energy storage system based on the historical load data of each energy storage node using a time series analysis method;

[0117] For each energy storage node, determine a first capacity ratio of the energy storage node, and determine a product value of the first capacity ratio and the energy storage load demand as a first load distribution value of the energy storage node;

[0118] The first capacity ratio is a first quotient of a first product of the first available mark value and the first current capacity and the first remaining available capacity.

[0119] Furthermore, the control terminal also includes a target load distribution module, which may specifically include:

[0120] A fault determination unit is used to, upon receiving the energy storage node fault information sent by the target intelligent agent, determine the energy storage node corresponding to the energy storage node fault information as a faulty node, and control the power grid to disconnect from the faulty node, wherein the energy storage node fault information is generated and sent when the target intelligent agent confirms that the energy storage node to which it belongs is a faulty node;

[0121] A remaining capacity value determining unit, configured to obtain a current target load of the faulty node and determine a second remaining available capacity of the distributed energy storage system after the faulty node;

[0122] A load distribution unit is used to distribute the current target load to the other energy storage nodes according to the second remaining available capacity and the node status data of the other energy storage nodes except the faulty node.

[0123] Furthermore, the load distribution unit may be specifically used for:

[0124] For each other energy storage node except the faulty node, obtain a second current capacity from the corresponding node status data, and determine a second available mark value of the other energy storage node;

[0125] Determine a second capacity ratio of the other energy storage nodes according to the second current capacity, the second available mark value and the second remaining available capacity;

[0126] The product value of the second capacity ratio and the current target load is determined as the second load distribution value of the other energy storage nodes, so as to perform load distribution according to the second load distribution value.

[0127] Furthermore, the agent also includes a fault node confirmation module, which can be specifically used for:

[0128] The target intelligent agent sends fault collaborative verification information to the adjacent intelligent agents of the adjacent energy storage nodes;

[0129] Each of the adjacent intelligent agents performs fault verification on the energy storage node to which the target intelligent agent belongs according to the fault collaborative verification information;

[0130] The target intelligent agent confirms the fault of the energy storage node to which it belongs according to the fault verification results fed back by each of the adjacent intelligent agents.

[0131] Furthermore, the control terminal also includes a recovery state load distribution module, which can be specifically used for:

[0132] When receiving the fault recovery information fed back by the target intelligent agent relative to the fault node, the fault node corresponding to the fault recovery information is determined as the recovery node, and the power grid is controlled to reconnect with the recovery node, wherein the fault recovery information is generated by the target intelligent agent monitoring the key node parameters of the fault node in real time and when it is determined that the key node parameters are continuously within the set range within the set time;

[0133] Determine a third remaining available capacity of the distributed energy storage system after adding the recovery node;

[0134] According to the third remaining available capacity and in combination with the node status data of each energy storage node in the distributed energy storage system, a third load distribution value of each energy storage node is determined, so as to perform load distribution according to the third load distribution value.

[0135] When receiving the fault recovery information fed back by the target intelligent agent relative to the fault node to which it belongs, the fault recovery information corresponding to the fault node is determined as the recovery node, and the power grid is controlled to reconnect with the recovery node, wherein the fault recovery information is generated by the target intelligent agent monitoring the key node parameters of the fault node to which it belongs in real time and when it is determined that the set time of the key node parameters is continuously within the set range;

[0136] Determine a third remaining available capacity of the distributed energy storage system after adding the recovery node;

[0137] According to the third remaining available capacity and in combination with the node status data of each energy storage node in the distributed energy storage system, a third load distribution value of each energy storage node is determined, so as to perform load distribution according to the third load distribution value.

[0138] An energy storage coordination control system provided by an embodiment of the present invention can execute an energy storage coordination control method provided by any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0139] Figure 3 A schematic diagram of the structure of an electronic device 30 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0140] like Figure 3As shown, the electronic device 30 includes at least one processor 31, and a memory connected to the at least one processor 31, such as a read-only memory (ROM) 32, a random access memory (RAM) 33, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 31 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 32 or the computer program loaded from the storage unit 38 to the random access memory (RAM) 33. In the RAM 33, various programs and data required for the operation of the electronic device 30 can also be stored. The processor 31, the ROM 32, and the RAM 33 are connected to each other through a bus 34. An input / output (I / O) interface 35 is also connected to the bus 34.

[0141] A number of components in the electronic device 30 are connected to the I / O interface 35, including: an input unit 36, such as a keyboard, a mouse, etc.; an output unit 37, such as various types of displays, speakers, etc.; a storage unit 38, such as a disk, an optical disk, etc.; and a communication unit 39, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 39 allows the electronic device 30 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0142] The processor 31 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 31 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 31 executes the various methods and processes described above, such as a storage coordination control method.

[0143] In some embodiments, a method for coordinated control of energy storage may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 38. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 30 via the ROM 32 and / or the communication unit 39. When the computer program is loaded into the RAM 33 and executed by the processor 31, one or more steps of the method for coordinated control of energy storage described above may be performed. Alternatively, in other embodiments, the processor 31 may be configured to perform a method for coordinated control of energy storage in any other appropriate manner (e.g., by means of firmware).

[0144] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0145] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0146] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0147] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0148] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0149] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0150] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0151] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for coordinated energy storage control, characterized in that: Applied to an energy storage coordination control system, the energy storage coordination control system includes a control terminal and at least one intelligent agent, the intelligent agent is installed on each energy storage node of a distributed energy storage system, and the method is executed by the control terminal, including: Receiving node status data of corresponding energy storage nodes sent by each of the intelligent agents, each of the intelligent agents collects the node status data in real time and sends it periodically; Determining a first remaining available capacity of the distributed energy storage system according to each of the node status data; According to the first remaining available capacity and in combination with the predicted energy storage load demand, a first load distribution value of each energy storage node is determined so as to perform load distribution according to the first load distribution value.

2. The method according to claim 1, characterized in that: The node status data includes: a first current capacity, a current load, a charge and discharge power, a voltage, a current, a temperature and an internal impedance data of the energy storage node.

3. The method according to claim 1, characterized in that Determining the first remaining available capacity of the distributed energy storage system according to each of the node status data includes: Receiving energy storage availability status information fed back by each of the intelligent agents relative to the energy storage node, and determining a first available mark value of each of the energy storage nodes; A first remaining available capacity of the distributed energy storage system is determined according to each of the first available mark values ​​and the first current capacity in each of the node status data.

4. The method according to claim 3, characterized in that: The determining, according to the first remaining available capacity and in combination with the predicted energy storage load demand, a first load distribution value of each energy storage node comprises: Obtaining the energy storage load demand predicted by the distributed energy storage system based on the historical load data of each energy storage node using a time series analysis method; For each energy storage node, determine a first capacity ratio of the energy storage node, and determine a product value of the first capacity ratio and the energy storage load demand as a first load distribution value of the energy storage node; The first capacity ratio is a first quotient of a first product of the first available mark value and the first current capacity and the first remaining available capacity.

5. The method according to claim 1, characterized in that Also includes: When receiving energy storage node fault information sent by the target intelligent agent, the energy storage node corresponding to the energy storage node fault information is determined as a faulty node, and the power grid is controlled to disconnect from the faulty node, wherein the energy storage node fault information is generated and sent when the target intelligent agent confirms that the energy storage node is a faulty node; Acquire the current target load of the faulty node, and determine a second remaining available capacity of the distributed energy storage system excluding the faulty node; According to the second remaining available capacity and the node status data of other energy storage nodes except the faulty node, the current target load is distributed to the other energy storage nodes.

6. The method according to claim 5, characterized in that The allocating the current target load to the other energy storage nodes according to the second remaining available capacity and the node status data of the other energy storage nodes except the faulty node comprises: For each other energy storage node except the faulty node, obtain a second current capacity from the corresponding node status data, and determine a second available mark value of the other energy storage node; Determine a second capacity ratio of the other energy storage nodes according to the second current capacity, the second available mark value and the second remaining available capacity; The product value of the second capacity ratio and the current target load is determined as the second load distribution value of the other energy storage nodes, so as to perform load distribution according to the second load distribution value.

7. The method according to claim 5, characterized in that The step of the target intelligent agent confirming that the energy storage node to which it belongs is a faulty node comprises: The target intelligent agent sends fault collaborative verification information to the adjacent intelligent agents of the adjacent energy storage nodes; Each of the adjacent intelligent agents performs fault verification on the energy storage node to which the target intelligent agent belongs according to the fault collaborative verification information; The target intelligent agent confirms the fault of the energy storage node to which it belongs according to the fault verification results fed back by each of the adjacent intelligent agents.

8. The method according to claim 5, characterized in that Also includes: When receiving the fault recovery information fed back by the target intelligent agent relative to the fault node, the fault node corresponding to the fault recovery information is determined as the recovery node, and the power grid is controlled to reconnect with the recovery node, wherein the fault recovery information is generated by the target intelligent agent monitoring the key node parameters of the fault node in real time and when it is determined that the key node parameters are continuously within the set range within the set time; Determine a third remaining available capacity of the distributed energy storage system after adding the recovery node; According to the third remaining available capacity and in combination with the node status data of each energy storage node in the distributed energy storage system, a third load distribution value of each energy storage node is determined, so as to perform load distribution according to the third load distribution value.

9. An energy storage coordinated control system, characterized in that: include: A control terminal and at least one intelligent agent, wherein the intelligent agent is installed on each energy storage node of the distributed energy storage system, The control terminal comprises: A data receiving module, used to receive node status data of the corresponding energy storage node sent by each of the intelligent agents, and each of the intelligent agents collects the node status data in real time and sends it periodically; A capacity determination module, configured to determine a first remaining available capacity of the distributed energy storage system according to each of the node status data; The load determination module is used to determine a first load distribution value of each of the energy storage nodes according to the first remaining available capacity in combination with the predicted energy storage load demand, so as to perform load distribution according to the first load distribution value.

10. An electronic device, characterized in that: As a control terminal and / or intelligent agent in the energy storage coordinated control system according to claim 9, the electronic device includes: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the energy storage coordinated control method according to any one of claims 1 to 8.

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