Intelligent scheduling method of flywheel energy storage system

Abstract

The invention relates to the field of energy storage system scheduling, in particular to an intelligent scheduling method for a flywheel energy storage system, which comprises the following steps: periodically acquiring the number of task execution equipment in a target management area and the equipment task conflict degree to determine the equipment execution state of the target management area; according to the equipment execution state of the target management area, determining a setting strategy of a key area, the setting strategy comprising determining the key area according to the distribution state of the target task point and the task completion degree, and determining the key area according to the task association coefficient of the key node and the related task conflict degree; according to the key area proportion and the key area change coefficient, whether energy storage transfer is carried out on the corresponding charging area is determined; and determining the number of flywheel energy storage nodes for executing energy storage transfer according to the key area proportion, and determining a target transfer node set according to the rotating speed coefficient of each flywheel energy storage node, thereby improving the power grid stability of the target management area.

Description

Technical Field

[0001] The present invention relates to the field of energy storage system scheduling, and in particular to an intelligent scheduling method for a flywheel energy storage system. Background Art

[0002] With the rise of new energy technologies, the proportion of new energy work vehicles in different work scenarios has gradually increased. Therefore, charging devices need to be arranged in the work area to ensure the continuous operation of each work vehicle. However, in the actual operation process, the increase in power supply demand in a certain period of time is likely to cause fluctuations in the power grid load. Therefore, the existing technology often dispatches the flywheel energy storage system to ensure the frequency stability of the power grid. Among them, for large operation areas, the route arrangement of each work vehicle affects the power supply demand of different charging areas. Therefore, how to effectively predict the fluctuation of power supply demand in different areas according to the route arrangement of the work vehicles in the actual operation scenario, and pre-dispatch the flywheel energy storage system to further ensure the stability of the power grid is a problem that needs to be urgently solved by technical personnel in this field.

[0003] Patent publication number CN106532814A discloses a flywheel energy storage electric vehicle charging station system, including a charging system, a power distribution system, a power storage system, an auxiliary power system, a central control system and a self-protection system. The AC distribution cabinet is connected to the power grid, the auxiliary power system and at least two flywheel energy storage systems respectively. Each flywheel energy storage system is connected to a DC / DC converter and then to a DC distribution cabinet. The DC distribution cabinet is connected to at least two charging devices. The central control system is connected to an energy storage system controller and an equipment controller. The equipment controller is respectively connected to the energy storage system controller, the DC distribution cabinet and each charging device. The energy storage system controller is respectively connected to each flywheel energy storage system and the DC / DC converter. Patent publication number CN114123413A discloses a charging method, charging device and AGV system for an AGV transport vehicle, the method comprising: determining a target AGV transport vehicle, the target AGV transport vehicle being one of the AGV transport vehicles that have not performed a task; determining a target charging amount based on at least a first power consumption and a second power consumption, the first power consumption being the power required for the target AGV transport vehicle to move from a first predetermined position to a second predetermined position, the second power consumption being the average power consumed by the target AGV transport vehicle to perform a task, the first predetermined position being the position of the center of the map, and the second predetermined position being the position of the charging pile; and controlling the target AGV transport vehicle to charge according to the target charging amount. However, the above scheme has the following problems: in the charging scenario of AGV transport vehicles, especially in large-scale scenarios such as smart ports, although a flywheel energy storage system can be used to adjust the output power when the power supply demand changes to ensure the stability of the power grid, the unstable power consumption during the actual use of the vehicle and the large degree of environmental impact on the power demand are not taken into account, resulting in the failure to timely schedule the flywheel energy storage system, which in turn leads to poor stability of the power grid. Summary of the invention

[0004] To this end, the present invention provides an intelligent scheduling method for a flywheel energy storage system to overcome the problem in the prior art that the fluctuation of power supply demand in different charging areas cannot be effectively predicted according to the route arrangement of each working vehicle in the actual scenario, resulting in the failure to timely schedule the flywheel energy storage system, which in turn leads to poor stability of the power grid.

[0005] To achieve the above object, the present invention provides an intelligent scheduling method for a flywheel energy storage system, comprising:

[0006] Periodically obtain the number of task execution devices and device task conflict degree in the target management area to determine the device execution status in the target management area;

[0007] Determine the setting strategy of the key area according to the equipment execution status of the target management area, the setting strategy includes determining the key area according to the distribution status of the target task points and the task completion degree, and determining the key area according to the task correlation coefficient of the key node and the conflict degree of related tasks;

[0008] Determine whether to mobilize energy storage for the corresponding charging area based on the proportion of key areas and the key area change coefficient;

[0009] The number of flywheel energy storage nodes that perform energy storage mobilization is determined according to the proportion of key areas, and the target mobilization node set is determined according to the speed coefficient of each flywheel energy storage node.

[0010] Further, the device execution state of the target management area is determined according to the number of task execution devices in the target management area and the device task conflict degree;

[0011] If the number of task execution devices in the target management area is less than or equal to the preset number of task execution devices and the device-task conflict degree is less than or equal to the preset task conflict degree, then the device execution state is determined to be the first preset device execution state;

[0012] If the number of task execution devices in the target management area is greater than the preset number of task execution devices or the device-task conflict degree is greater than the preset task conflict degree, the device execution state is determined to be the second preset device execution state.

[0013] Furthermore, the setting strategy of the key area is determined according to the device execution status of the target management area, including:

[0014] If the target management area is in the first preset device execution state, the key area is determined according to the distribution state of the target task points and the task completion degree;

[0015] If the target management area is in the second preset device execution state, the key area is determined according to the task association coefficient of the key node and the conflict degree of the related tasks.

[0016] Further, the distribution state of the target task points is determined according to the number of target task points in the preset distribution area;

[0017] If the number of target task points in a preset distribution area of ​​a target task point is greater than the preset number of target task points, the target task point is determined to be in a dense state;

[0018] The target task point is the end point of the task route of each task execution device in the target management area at the current moment.

[0019] Furthermore, the completion difference values ​​of each dense area are tested;

[0020] The completion difference value of any dense area is determined according to the task completion degree of the task execution equipment corresponding to each target task point in the dense area, and the dense area with a completion difference value less than the preset completion difference value in the target management area is recorded as a key area;

[0021] The dense task points are target task points in a dense state;

[0022] The dense area is a set of preset distribution areas of at least two dense task points, and any dense task point in the dense area has overlapping task points.

[0023] Furthermore, when determining the key area according to the task correlation coefficient of the key node and the conflict degree of the related tasks, the task routes of each task execution device in the target management area at the current moment are obtained, and the route nodes whose number of related task routes is greater than the preset number of related task routes are recorded as key nodes;

[0024] For any route node, the task route passing through the route node is recorded as the relevant task route;

[0025] For any key node, the task execution devices corresponding to each task route passing through the key node are recorded as the associated devices of the key node, and the task association coefficient of the key node is the number of its associated devices.

[0026] Furthermore, the key length of the corresponding key node is set according to the task correlation coefficient of each key node and the conflict degree of the relevant tasks;

[0027] The conflict degree of related tasks of any key node is determined according to the proportion of overlapping lines of its related task lines and the reference interval distance;

[0028] The critical length is positively correlated with the task association coefficient and the related task conflict degree respectively.

[0029] Furthermore, if the relevant key parameter of a key node is greater than the preset relevant key parameter, the key length of the key node is increased and adjusted according to the number of relevant key nodes;

[0030] The increase in the key length is positively correlated with the number of relevant key nodes.

[0031] Furthermore, if the critical area ratio of a charging area is greater than the preset critical area ratio or the critical area variation coefficient is greater than the preset critical area variation coefficient, energy storage mobilization is performed for the charging area, and the number of flywheel energy storage nodes for performing energy storage mobilization is determined according to the critical area ratio;

[0032] The number of flywheel energy storage nodes is positively correlated with the proportion of key areas.

[0033] Further, if a charging area needs to perform energy storage mobilization and the number of flywheel energy storage nodes that have completed the energy storage mobilization is determined, the target mobilization node set is determined according to the speed coefficient of each flywheel energy storage node;

[0034] The set rotation speed coefficient of the target mobilization node set is greater than the preset set rotation speed coefficient.

[0035] Compared with the prior art, the beneficial effect of the present invention lies in that, in the technical solution of the present invention, a targeted key area setting strategy is determined according to the equipment execution status of the target management area, and the key areas within the target management area are obtained to effectively estimate the fluctuation of the power supply demand of the target key areas, and determine whether to mobilize energy storage for the corresponding charging areas according to the proportion of the key areas and the key area variation coefficient, and timely schedule the flywheel energy storage system. The present invention improves the stability of the power grid maintained by the flywheel energy storage system.

[0036] Furthermore, the present invention determines the equipment execution status of the target management area based on the number of task execution devices and the equipment task conflict degree in the target management area. The number of task execution devices and the equipment task conflict degree can effectively characterize the number and concentration of operating equipment running in the target management area, thereby determining the equipment execution status, and determining the setting strategy of the key area according to different equipment execution states, thereby improving the accuracy of the determined key areas.

[0037] Furthermore, in the present invention, when the target management area is in the first preset equipment execution state, that is, the number of operating equipment operating in the target management area is small and the probability of concentrated distribution of the operating equipment during operation is low, the dense area in the target management area where the completion difference value is less than the preset completion difference value is recorded as a key area. At this time, more task execution equipment is concentrated in the determined key area, so the possibility of an increase in the charging demand of the determined key area is greater. The present invention improves the accuracy of the determined key area.

[0038] Furthermore, in the present invention, when the target management area is in the second preset equipment execution state, that is, the number of operating equipment operating in the target management area is large or the probability of concentrated distribution of operating equipment during operation is high, since the task execution equipment is more likely to be congested when traveling near the key node, it is necessary to adjust the task routes of some task execution equipment, which leads to the possibility of concentration of task execution equipment in the vicinity of the key node. The radius length of the corresponding key area is set according to the task correlation coefficient of each key node and the related task conflict degree, so as to determine the key area that is more in line with the actual target management area.

[0039] Furthermore, it is determined whether to mobilize energy storage for the corresponding charging area based on the proportion of key areas and the key area change coefficient. The change in power supply demand in the charging area is estimated based on the proportion of key areas and the key area change coefficient. When the proportion of key areas is large or the change in key areas is large, energy storage is mobilized for the charging area. The flywheel energy storage system is used to modulate the grid frequency to avoid grid frequency fluctuations caused by changes in power supply demand, thereby avoiding damage to various power equipment and ensuring grid stability in the target management area. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A schematic diagram of an intelligent scheduling method for a flywheel energy storage system according to the present invention;

[0041] Figure 2 A flowchart of the present invention for determining the device execution state of the target management area according to the number of task execution devices in the target management area and the device task conflict degree;

[0042] Figure 3 A flowchart of the present invention for determining a setting strategy for a key area according to the device execution status of a target management area;

[0043] Figure 4 The present invention is a flow chart for determining whether to mobilize energy storage for a corresponding charging area according to the proportion of the key area and the key area variation coefficient. DETAILED DESCRIPTION

[0044] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0045] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0046] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0047] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0048] See also Figures 1 to 4 As shown, the present invention provides an intelligent scheduling method for a flywheel energy storage system, comprising:

[0049] Periodically obtain the number of task execution devices and device task conflict degree in the target management area to determine the device execution status in the target management area;

[0050] Determine the setting strategy of the key area according to the equipment execution status of the target management area, the setting strategy includes determining the key area according to the distribution status of the target task points and the task completion degree, and determining the key area according to the task correlation coefficient of the key node and the conflict degree of related tasks;

[0051] Determine whether to mobilize energy storage for the corresponding charging area based on the proportion of key areas and the key area change coefficient;

[0052] The number of flywheel energy storage nodes that perform energy storage mobilization is determined according to the proportion of key areas, and the target mobilization node set is determined according to the speed coefficient of each flywheel energy storage node.

[0053] The application scenario of the present invention is a large port. The area in the port where the task execution equipment can pass or charge is recorded as the target management area, and the target management area is divided into several charging areas. The number of charging devices in each charging area obtained by division is the same. The operating equipment in the present invention is a movable device for performing port operation tasks, and each operating equipment uses electric energy to provide operating power. The types of operating equipment include but are not limited to: electric-driven mobile cranes, tractors and automatic guided vehicles. The port operation tasks performed by the operating equipment in the present invention include but are not limited to: cargo loading and unloading, cargo stacking, cargo transfer and personnel transfer. There are several driving routes in the target management area for the operating equipment to travel, and the positions where the driving routes intersect are recorded as route nodes; multiple flywheel energy storage nodes are connected in parallel to form a flywheel energy storage array system, and each flywheel energy storage unit operates in a coordinated manner. When the grid frequency fluctuates, the flywheel energy storage array system can immediately adjust its output or input power to stabilize the grid frequency;

[0054] The present invention applies a cyclic management cycle, and the duration of the management cycle can be determined by the user. The higher the user's requirements for the grid stability of the target management area, the shorter the duration of the management cycle. A management cycle duration is provided, and the management cycle is 30 minutes. At the end of each management cycle, the number of task execution devices and the device task conflict degree in the target management area at that moment are obtained to determine the device execution status. The setting strategy of the key area is determined based on the device execution status to determine the key area in the target management area, so as to further determine whether to mobilize energy storage for each charging area;

[0055] Several historical management records are applied in the present invention, and any historical management record records the number of task execution devices, task conflict degree, number of related task routes, node distance, related key parameters, key area proportion and key area variation coefficient in at least one management record for the target management area, and each historical management record corresponds to a qualified mark, which records whether the power grid stability requirements for the target management area meet user needs.

[0056] Specifically, the device execution status of the target management area is determined according to the number of task execution devices in the target management area and the device task conflict degree;

[0057] If the number of task execution devices in the target management area is less than or equal to the preset number of task execution devices and the device-task conflict degree is less than or equal to the preset task conflict degree, then the device execution state is determined to be the first preset device execution state;

[0058] If the number of task execution devices in the target management area is greater than the preset number of task execution devices or the device-task conflict degree is greater than the preset task conflict degree, the device execution state is determined to be the second preset device execution state.

[0059] Among them, at the end moment of any management cycle, the task execution equipment and the task routes of each task execution equipment in the target management area at that moment are obtained. The task execution equipment is the operating equipment that is executing any port operation task at that moment. When any task execution equipment obtains the port operation task it needs to perform, it also obtains the driving route it needs to pass through in the process of completing the port operation task, and the set of driving routes that need to be passed is recorded as the task route of the task execution equipment. The equipment task conflict degree is determined according to the task routes of each task execution equipment obtained at that moment. The equipment task conflict degree = the sum of the lengths of the overlapping routes in the detected task routes / the sum of the lengths of the detected task routes. If there are at least two task routes that need to pass through the same part of the driving route, the part of the driving route is recorded as an overlapping route;

[0060] The user can determine the values ​​of the number of preset task execution devices and the preset task conflict degree according to the actual working scenario. For example, the user can set them according to historical monitoring records. The higher the user's requirements for the grid stability of the target management area, the smaller the value of the number of preset task execution devices and the smaller the value of the preset task conflict degree. A method for determining the value of the number of preset task execution devices is provided, and the historical management records of the target management area in the first preset device execution state are recorded as state reference records, and the maximum value of the number of task execution devices in the target management area obtained from each detection in the state reference records that meet the user's requirements for the grid stability of the target management area is recorded as the preset task execution device number. A method for determining the value of the preset task conflict degree is provided, and the maximum value of the task conflict degree of the target management area obtained from each detection in the state reference records that meet the user's requirements for the grid stability of the target management area is recorded as the preset task conflict degree.

[0061] Specifically, the setting strategy of the key area is determined according to the device execution status of the target management area, including:

[0062] If the target management area is in the first preset device execution state, the key area is determined according to the distribution state of the target task points and the task completion degree;

[0063] If the target management area is in the second preset device execution state, the key area is determined according to the task association coefficient of the key node and the conflict degree of the related tasks.

[0064] Among them, determining the key area according to the distribution status of the target task points and the task completion degree is recorded as the first setting strategy, and determining the key area according to the task correlation coefficient of the key node and the related task conflict degree is recorded as the second setting strategy.

[0065] Specifically, the distribution status of the target task points is determined according to the number of target task points in the preset distribution area;

[0066] If the number of target task points in a preset distribution area of ​​a target task point is greater than the preset number of target task points, the target task point is determined to be in a dense state;

[0067] The target task point is the end point of the task route of each task execution device in the target management area at the current moment.

[0068] Specifically, the completion difference values ​​of each dense area are tested;

[0069] The completion difference value of any dense area is determined according to the task completion degree of the task execution equipment corresponding to each target task point in the dense area, and the dense area with a completion difference value less than the preset completion difference value in the target management area is recorded as a key area;

[0070] The dense task points are target task points in a dense state;

[0071] The dense area is a set of preset distribution areas of at least two dense task points, and any dense task point in the dense area has overlapping task points.

[0072] When executing the first setting strategy, the distribution status of each target task point is obtained and the dense area is determined, and the completion difference value of each dense area is detected, and the dense area with a completion difference value less than the preset completion difference value in the target management area is recorded as a key area;

[0073] The distribution state includes a dense state and a discrete state. If the number of target task points in the preset distribution area of ​​a target task point is less than or equal to the preset number of target task points, the target task point is determined to be in a discrete state. When judging the distribution state of each target task point, the distribution length of the preset distribution area of ​​each target task point is positively correlated with the number of related equipment of the corresponding target task point. For a single target task point, its preset distribution area is a circular area with the target task point as the center and the distribution length as the radius. The value of the preset number of target task points can be determined by the user according to the actual working scenario. For example, the user can set it according to historical monitoring records. The higher the user's requirements for the grid stability of the target management area, the smaller the value of the preset number of target task points. A method for determining the value of the preset number of target task points is provided, which will meet the user's requirements for the grid stability of the target management area. The minimum value of the number of target task points in the preset distribution area of ​​each dense task point in the historical management records.

[0074] If a target task point exists in the preset distribution areas of two different dense task points, the target task point is recorded as an overlapping task point. For any dense area, m is the number of task execution devices corresponding to the target task point in the dense area, Dv is the task completion degree of the vth task execution device, D0 is the average of the task completion degrees of each task execution device, and for a single task execution device, the task completion degree = the length of the task route of the part that the task execution device has traveled / the length of the task route of the task execution device;

[0075] The value of the preset completion difference value can be determined by the user according to the actual working scenario. For example, the user can set it according to historical monitoring records. The higher the user's requirement for the grid stability of the target management area, the larger the value of the preset completion difference value. A method for determining the preset completion difference value is provided. The historical management records of the key areas determined according to the distribution status of the target task points and the task completion are recorded as completion reference records, and the average value of the completion difference values ​​of each key area in the completion reference records that meet the user's requirement for the grid stability of the target management area is recorded as the preset completion difference value.

[0076] Specifically, when determining the key area according to the task correlation coefficient of the key node and the conflict degree of the related tasks, the task routes of each task execution device in the target management area at the current moment are obtained, and the route nodes whose number of related task routes is greater than the preset number of related task routes are recorded as key nodes;

[0077] For any route node, the task route passing through the route node is recorded as the relevant task route;

[0078] For any key node, the task execution devices corresponding to each task route passing through the key node are recorded as the associated devices of the key node, and the task association coefficient of the key node is the number of its associated devices.

[0079] Among them, when executing the second setting strategy, the key nodes are determined according to the number of relevant task routes, the task correlation coefficient of each key node and the relevant task conflict degree are obtained to determine the critical length of the corresponding key node, and the key area of ​​the corresponding key node is determined according to the critical length of each key node. For a single key node, its key area is a circular area formed with the key node as the center and the critical length of the key node as the radius;

[0080] The value of the preset number of related task routes can be determined by the user according to the actual working scenario. For example, the user can set it according to historical monitoring records. The higher the user's requirement for the power grid stability of the target management area, the smaller the value of the preset number of related task routes. A method for determining the value of the preset number of related task routes is provided. The historical management records of the key area of ​​the key node determined according to the task correlation coefficient and task overlap of the key node are recorded as relevant reference records. The minimum number of related task routes of each key node in the relevant reference records that meets the user's requirement for the power grid stability of the target management area is recorded as the value of the preset number of related task routes. A value of the preset related task route is provided, and the value of the preset related task route is 3.

[0081] Specifically, the key length of the corresponding key node is set according to the task correlation coefficient of each key node and the conflict degree of related tasks;

[0082] The conflict degree of related tasks of any key node is determined according to the proportion of overlapping lines of its related task lines and the reference interval distance;

[0083] The critical length is positively correlated with the task association coefficient and the related task conflict degree respectively.

[0084] Among them, for a single key node, the proportion of overlapping routes = the sum of the lengths of each overlapping route in the relevant task routes of the key node / the sum of the lengths of the relevant task routes of the key node, the reference interval distance is the average of the interval distances between the key node and each overlapping route, the shortest distance required for the key node to reach an overlapping route is recorded as the interval distance between the key node and the overlapping route, the relevant task conflict degree = ln (overlapping route proportion / reference interval distance), the task association coefficient and the sum of the relevant task conflict degree are positively correlated with the critical length corresponding to the key node.

[0085] Specifically, if the relevant key parameter of a key node is greater than the preset relevant key parameter, the key length of the key node is increased and adjusted according to the number of relevant key nodes;

[0086] The increase in the key length is positively correlated with the number of relevant key nodes.

[0087] Among them, for a single key node, the relevant key parameter is determined according to the number of relevant key nodes of the key node and the reference node distance, the relevant key parameter = ln (number of relevant key nodes / reference node distance), the reference node distance is the average value of the node distance between the key node and its relevant key nodes, if there is a relevant task route between the two key nodes and the node distance is less than the preset node distance, then the two key nodes are determined to be relevant key nodes to each other, and the length of the relevant task route between the two key nodes is recorded as the node distance, the value of the preset node distance can be determined by the user according to the actual working scenario, for example, the user can set it according to historical monitoring records, the higher the user's requirements for the grid stability of the target management area, the smaller the value of the preset node distance, and a method for determining the value of the preset node distance is provided, and the minimum value of the node distance between two nodes that are relevant key nodes in the historical management records that meet the user's requirements for the grid stability of the target management area is recorded as the preset node distance;

[0088] The values ​​of the preset relevant key parameters can be determined by the user according to the actual working scenario. For example, the user can set them according to historical monitoring records. The higher the user's requirements for the grid stability of the target management area, the smaller the values ​​of the preset relevant key parameters. A method for setting the values ​​of the preset relevant key parameters is provided, and the historical management records adjusted for the length of the key area are recorded as key parameter records, and the average values ​​of the relevant key parameters of each key node in the key parameter records that meet the user's requirements for the grid stability of the target management area are recorded as preset relevant key parameters.

[0089] Specifically, if the critical area ratio of a charging area is greater than the preset critical area ratio or the critical area variation coefficient is greater than the preset critical area variation coefficient, energy storage mobilization is performed for the charging area, and the number of flywheel energy storage nodes for performing energy storage mobilization is determined according to the critical area ratio;

[0090] The number of flywheel energy storage nodes is positively correlated with the proportion of key areas.

[0091] Among them, for a single charging area, the critical area proportion = the sum of the areas of the critical areas in the charging area / the area of ​​the charging area, the critical area change coefficient is negatively correlated with the overlapping area of ​​the critical area determined at the end time of the current management cycle and the key area determined at the end time of the previous management cycle, and the overlapping area is the area of ​​the partial area in the target management area that is determined as the critical area twice. The values ​​of the preset critical area proportion and the preset critical area change coefficient can be determined by the user according to the actual working scenario. For example, the user can set them according to the historical monitoring records. The higher the user's requirements for the grid stability of the target management area, the smaller the value of the preset critical area proportion and the smaller the value of the preset critical area change coefficient. A method for determining the preset critical area proportion is provided, and the minimum value of the critical area proportion of each charging area for energy storage mobilization in the historical management records that meet the user's requirements for the grid stability of the target management area is recorded as the preset critical area proportion. A method for determining the preset critical area change coefficient is provided, and the minimum value of the critical area change coefficient of each charging area for energy storage mobilization in the historical management records that meet the user's requirements for the grid stability of the target management area is recorded as the preset critical area change coefficient.

[0092] Specifically, if a charging area needs to perform energy storage mobilization and the number of flywheel energy storage nodes that have completed the energy storage mobilization is determined, the target mobilization node set is determined according to the speed coefficient of each flywheel energy storage node;

[0093] The set rotation speed coefficient of the target mobilization node set is greater than the preset set rotation speed coefficient.

[0094] Among them, for a charging area that needs to be mobilized for energy storage, the power supply demand of the charging area is monitored in real time. When the power supply demand of the charging area changes, the output or input power of each flywheel energy storage node in the target mobilization node set is adjusted to ensure the stability of the power grid frequency. For a single flywheel energy storage node, the flywheel angular velocity at the current moment, as well as the maximum flywheel angular velocity and the minimum flywheel angular velocity of the flywheel energy storage node are detected. The maximum flywheel angular velocity is the maximum value of the flywheel angular velocity reached during the historical operation of the flywheel energy storage node, and the minimum flywheel angular velocity is the minimum value of the flywheel angular velocity reached during the historical operation of the flywheel energy storage node. The speed coefficient = (flywheel angular velocity at the current moment - minimum flywheel angular velocity) × (flywheel angular velocity at the current moment + minimum flywheel angular velocity) / (maximum flywheel angular velocity + minimum flywheel angular velocity) × (maximum flywheel angular velocity - minimum flywheel angular velocity). The number of flywheel energy storage nodes in the determined target mobilization node set is the same as the number of flywheel energy storage nodes that have completed the energy storage mobilization. n is the number of flywheel energy storage nodes in the target mobilization node set, mi is the flywheel angular velocity of the i-th flywheel energy storage node at the current moment, li is the minimum flywheel angular velocity of the i-th flywheel energy storage node, fi is the maximum flywheel angular velocity of the i-th flywheel energy storage node, and a preset set speed coefficient value is provided, and the preset set speed coefficient value is 0.2.

[0095] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0096] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An intelligent scheduling method for a flywheel energy storage system, characterized in that: include: Periodically obtain the number of task execution devices and device task conflict degree in the target management area to determine the device execution status in the target management area; Determine the setting strategy of the key area according to the equipment execution status of the target management area, the setting strategy includes determining the key area according to the distribution status of the target task points and the task completion degree, and determining the key area according to the task correlation coefficient of the key node and the conflict degree of related tasks; Determine whether to mobilize energy storage for the corresponding charging area based on the proportion of key areas and the key area change coefficient; The number of flywheel energy storage nodes that perform energy storage mobilization is determined according to the proportion of key areas, and the target mobilization node set is determined according to the speed coefficient of each flywheel energy storage node.

2. The intelligent dispatching method of the flywheel energy storage system according to claim 1, characterized in that: Determine the device execution status of the target management area according to the number of task execution devices in the target management area and the device task conflict degree; If the number of task execution devices in the target management area is less than or equal to the preset number of task execution devices and the device-task conflict degree is less than or equal to the preset task conflict degree, then the device execution state is determined to be the first preset device execution state; If the number of task execution devices in the target management area is greater than the preset number of task execution devices or the device-task conflict degree is greater than the preset task conflict degree, the device execution state is determined to be the second preset device execution state.

3. The intelligent dispatching method of the flywheel energy storage system according to claim 2, characterized in that: Determine the setting strategy for key areas based on the device execution status of the target management area, including: If the target management area is in the first preset device execution state, the key area is determined according to the distribution state of the target task points and the task completion degree; If the target management area is in the second preset device execution state, the key area is determined according to the task association coefficient of the key node and the conflict degree of the related tasks.

4. The intelligent dispatching method of the flywheel energy storage system according to claim 3, characterized in that: The distribution state of the target task points is determined according to the number of target task points in the preset distribution area; If the number of target task points in a preset distribution area of ​​a target task point is greater than the preset number of target task points, the target task point is determined to be in a dense state; The target task point is the end point of the task route of each task execution device in the target management area at the current moment.

5. The intelligent dispatching method of the flywheel energy storage system according to claim 4, characterized in that: Test the completion difference values ​​of each dense area; The completion difference value of any dense area is determined according to the task completion degree of the task execution equipment corresponding to each target task point in the dense area, and the dense area with a completion difference value less than the preset completion difference value in the target management area is recorded as a key area; The dense task points are target task points in a dense state; The dense area is a set of preset distribution areas of at least two dense task points, and any dense task point in the dense area has overlapping task points.

6. The intelligent dispatching method of the flywheel energy storage system according to claim 3, characterized in that: When determining the key area according to the task correlation coefficient of the key node and the conflict degree of the related tasks, the task routes of each task execution device in the target management area at the current moment are obtained, and the route nodes whose number of related task routes is greater than the preset number of related task routes are recorded as key nodes; For any route node, the task route passing through the route node is recorded as the relevant task route; For any key node, the task execution devices corresponding to each task route passing through the key node are recorded as the associated devices of the key node, and the task association coefficient of the key node is the number of its associated devices.

7. The intelligent dispatching method of the flywheel energy storage system according to claim 6, characterized in that: The key length of the corresponding key node is set according to the task correlation coefficient of each key node and the conflict degree of related tasks; The conflict degree of related tasks of any key node is determined according to the proportion of overlapping lines of its related task lines and the reference interval distance; The critical length is positively correlated with the task association coefficient and the related task conflict degree respectively.

8. The intelligent dispatching method of the flywheel energy storage system according to claim 7, characterized in that: If the relevant key parameter of a key node is greater than the preset relevant key parameter, the key length of the key node is increased and adjusted according to the number of relevant key nodes; The increase in the key length is positively correlated with the number of relevant key nodes.

9. The intelligent dispatching method of the flywheel energy storage system according to claim 8, characterized in that: If the critical area ratio of a charging area is greater than the preset critical area ratio or the critical area variation coefficient is greater than the preset critical area variation coefficient, energy storage mobilization is performed for the charging area, and the number of flywheel energy storage nodes for performing energy storage mobilization is determined according to the critical area ratio; The number of flywheel energy storage nodes is positively correlated with the proportion of key areas.

10. The intelligent dispatching method of the flywheel energy storage system according to claim 9, characterized in that: If a charging area needs to perform energy storage mobilization and the number of flywheel energy storage nodes that have completed the energy storage mobilization is determined, the target mobilization node set is determined according to the speed coefficient of each flywheel energy storage node; The set rotation speed coefficient of the target mobilization node set is greater than the preset set rotation speed coefficient.

Images