A scheduling method for hybrid energy storage system considering actual grid regulation requirements

Abstract

The application provides a hybrid energy storage system scheduling method considering actual regulation and control requirements of a power grid, and relates to the technical field of energy storage power supply systems. Through comprehensive analysis of data parameters, an energy storage scheduling scheme suitable for energy requirements of the power grid is formed, so that the energy storage scheduling scheme for the energy storage system is more matched with the power demand of the power grid, the efficient use of the energy of the energy storage system is improved, and the energy is saved to a certain extent. In addition, through recording of the energy storage scheduling scheme, the subsequent energy storage scheduling scheme can be referenced after the new energy storage system is connected to the grid or part of the energy storage system is off-grid, and a new scheme suitable for the current energy storage scheduling can be quickly formed, the adaptability of the energy storage system to the change of the energy storage scheduling is enhanced, an efficient energy storage scheduling scheme is formed, the efficient use of energy is further improved, the energy is saved, and the technical problem of high energy loss in the energy storage power supply process in the prior art is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy storage power supply systems, in particular to a hybrid energy storage system scheduling method considering actual grid regulation requirements. BACKGROUND

[0002] The technical application of energy storage systems runs through all links of power generation, power transmission, power distribution and power consumption of the power system. Proper access of energy storage systems to power dispatching can improve the grid environment, improve the stability and reliability of the power system, and at the same time timely relieve the demand for electric energy of the grid. At present, there are various energy storage scheduling methods for energy storage systems, mainly according to the demand of the grid for power consumption to arrange reasonably. For example, for the energy scheduling of a hybrid energy storage system of multiple types set in a power supply area, the usual way is to arrange the power transmission of each energy storage system through demand power analysis. However, the type and process level of energy storage directly affect the charging and discharging efficiency of energy storage, that is, the loss of energy storage charging and discharging; the scheduling strategy of energy storage directly affects the cost-effectiveness, life cycle and other indicators of energy storage, and also affects the tie line plan of the grid, line loss, carbon emission and cost of power generation, and power price and load power cost.

[0003] Therefore, the prior art has the technical problem of high electric energy loss in the energy storage power supply process. SUMMARY

[0004] The purpose of the present application is to provide a hybrid energy storage system scheduling method considering actual grid regulation requirements to alleviate the technical problem of high electric energy loss in the energy storage power supply process of the prior art.

[0005] In a first aspect, the embodiments of the present application provide a hybrid energy storage system scheduling method considering actual grid regulation requirements, applied to a hybrid energy storage system corresponding to a preset power supply area, the hybrid energy storage system comprising a power-type energy storage system and an energy-type energy storage system; the method comprises:

[0006] obtaining energy storage scheduling data and performance parameters corresponding to the hybrid energy storage system;

[0007] determining an energy storage priority scheduling mode based on the energy storage scheduling data and the performance parameters;

[0008] determining a first energy storage scheduling scheme through the energy storage priority scheduling mode, and performing energy storage scheduling on the hybrid energy storage system through the first energy storage scheduling scheme;

[0009] determining first periodic energy storage scheduling data based on the first energy storage scheduling scheme;

[0010] optimizing a second energy storage scheduling scheme based on the first periodic energy storage scheduling data.

[0011] In a possible implementation, the energy storage scheduling data includes any one or more of the following:

[0012] power consumption demand information, power consumption demand power data, increased discharge power during a power consumption peak period, increased charge power during a power consumption valley period;

[0013] The performance parameters include any one or more of the following:

[0014] energy storage capacity of the hybrid energy storage system, economy and life cycle data of the hybrid energy storage system, charge and discharge performance parameters of the hybrid energy storage system, and power parameters of the hybrid energy storage system.

[0015] In a possible implementation, the step of determining an energy storage priority scheduling mode based on the energy storage scheduling data and the performance parameters includes:

[0016] allocating an overall energy scheduling amount based on the power consumption demand information, the energy storage capacity of the hybrid energy storage system, and the economy and life cycle data of the hybrid energy storage system;

[0017] performing an energy output change amount analysis based on the power consumption demand power data to obtain an energy output change analysis result;

[0018] determining the energy storage priority scheduling mode based on the increased discharge power during the power consumption peak period, the increased charge power during the power consumption valley period, the charge and discharge performance parameters of the hybrid energy storage system, the power parameters of the hybrid energy storage system, and the energy output change analysis result.

[0019] In a possible implementation, the power consumption demand information includes a total power consumption demand amount, and the step of allocating an overall energy scheduling amount based on the power consumption demand information, the energy storage capacity of the hybrid energy storage system, and the economy and life cycle data of the hybrid energy storage system includes:

[0020] establishing an economic benefit calculation model based on the total power consumption demand amount, the energy storage capacity of the hybrid energy storage system, and the economy and life cycle data of the hybrid energy storage system;

[0021] determining, according to the economic benefit calculation model, a type and a quantity of energy storage systems that need to be scheduled in the hybrid energy storage system.

[0022] In a possible implementation, the power output change analysis result includes power consumption demand change data during the scheduling period; and the step of determining the energy storage priority scheduling mode based on the increased discharging power during the power consumption peak period, the increased charging power during the power consumption valley period, the charging and discharging performance parameters of the hybrid energy storage system, the power parameters of the hybrid energy storage system, and the power output change analysis result includes:

[0023] determining the scheduling priority of the hybrid energy storage system based on the power consumption demand change data, the charging and discharging performance parameters of the hybrid energy storage system, and the power parameters of the hybrid energy storage system;

[0024] determining the type and quantity of the hybrid energy storage system that needs to be increased in scheduling in the hybrid energy storage system based on the increased discharging power during the power consumption peak period;

[0025] determining the type and quantity of the hybrid energy storage system that needs to be reduced in scheduling in the hybrid energy storage system based on the increased charging power during the power consumption valley period.

[0026] In a possible implementation, the step of determining the first periodic energy storage scheduling data based on the first energy storage scheduling scheme includes:

[0027] determining a first energy storage scheduling period based on the power consumption rule of the preset power supply area;

[0028] recording the actual scheduling power of the hybrid energy storage system varying with the scheduling time in the first energy storage scheduling period to obtain the first periodic energy storage scheduling data.

[0029] In a possible implementation, the hybrid energy storage system further includes a newly connected energy-type energy storage system and an off-grid backup energy storage system; the preset power supply area further includes a shared energy storage system that is not included in the hybrid energy storage system; and the step of optimizing the second energy storage scheduling scheme based on the first periodic energy storage scheduling data includes:

[0030] obtaining demand power varying with the scheduling time in the preset power supply area;

[0031] respectively calculating the matching degrees of the hybrid energy storage system, the energy-type energy storage system, the backup energy storage system, and the shared energy storage system relative to the demand power, and determining a target energy storage system with the highest matching degree;

[0032] adding the target energy storage system to the scheduling range of the hybrid energy storage system, or replacing at least one energy storage system in the hybrid energy storage system with the target energy storage system, to complete the optimization of the second energy storage scheduling scheme.

[0033] In a possible implementation, the step of respectively calculating the matching degrees of the hybrid energy storage system, the newly grid-connected energy type energy storage system, the backup energy storage system and the shared energy storage system with respect to the demand power, and determining the target energy storage system with the highest matching degree, comprises:

[0034] obtaining actual scheduling power of the hybrid energy storage system varying with scheduling time;

[0035] obtaining performance parameters, economy and life cycle data and rated energy of the newly grid-connected energy type energy storage system, and obtaining first economic scheduling power based on the performance parameters, economy and life cycle data and rated energy of the newly grid-connected energy type energy storage system;

[0036] obtaining performance parameters, economy and life cycle data and rated energy of the backup energy storage system, and obtaining second economic scheduling power based on the performance parameters, economy and life cycle data and rated energy of the backup energy storage system;

[0037] obtaining performance parameters, economy and life cycle data and rated energy of the shared energy storage system, and obtaining third economic scheduling power based on the performance parameters, economy and life cycle data and rated energy of the shared energy storage system;

[0038] respectively calculating the matching degrees of the actual scheduling power, the first economic scheduling power, the second economic scheduling power and the third economic scheduling power with respect to the demand power, and determining the target energy storage system with the highest matching degree.

[0039] In a second aspect, the embodiments of the present application provide a hybrid energy storage system scheduling device considering actual regulation and control requirements of a power grid, applied to a hybrid energy storage system corresponding to a preset power supply area, wherein the hybrid energy storage system comprises a hybrid energy storage system; and the device comprises:

[0040] an obtaining module, configured to obtain energy storage scheduling data and performance parameters corresponding to the hybrid energy storage system;

[0041] a first determining module, configured to determine an energy storage priority scheduling mode based on the energy storage scheduling data and the performance parameters;

[0042] a scheduling module, configured to determine a first energy storage scheduling scheme through the energy storage priority scheduling mode, and perform energy storage scheduling on the hybrid energy storage system through the first energy storage scheduling scheme;

[0043] a second determining module, configured to determine first periodic energy storage scheduling data based on the first energy storage scheduling scheme;

[0044] an optimization module, configured to optimize a second energy storage scheduling scheme based on the first periodic energy storage scheduling data.

[0045] In a third aspect, an electronic device is provided, which includes a memory and a processor. The memory stores a computer program executable on the processor. The processor implements the steps of the method in the first aspect when executing the computer program.

[0046] The embodiments of the present application have the following beneficial effects:

[0047] The embodiments of the present application provide a hybrid energy storage system scheduling method considering actual grid regulation requirements. First, energy storage scheduling data and performance parameters of the hybrid energy storage system are obtained. Then, based on the energy storage scheduling data and the performance parameters, a priority energy storage scheduling mode is determined. Thus, a first energy storage scheduling scheme is determined based on the priority energy storage scheduling mode, and the hybrid energy storage system is scheduled based on the first energy storage scheduling scheme. Then, first periodic energy storage scheduling data is determined based on the first energy storage scheduling scheme. Further, a second energy storage scheduling scheme is optimized based on the first periodic energy storage scheduling data. In this scheme, the hybrid energy storage system first obtains energy storage scheduling data of a preset power supply area and performance parameters of each energy storage system in the hybrid energy storage system corresponding to the preset power supply area. The two are combined and analyzed to form a priority energy storage scheduling mode. Then, a first energy storage scheduling scheme is determined based on the priority energy storage scheduling mode, so that the hybrid energy storage system is scheduled based on the first energy storage scheduling scheme. The hybrid energy storage system can also record data corresponding to the first energy storage scheduling scheme and form first periodic energy storage scheduling data based on the data. Further, the second energy storage scheduling scheme developed subsequently is optimized based on the first periodic energy storage scheduling data. By comprehensively analyzing data parameters, an energy storage scheduling scheme suitable for grid energy requirements is formed, so that the energy storage scheduling scheme for the energy storage system is more matched with the power demand of the grid, the efficient use of energy of the energy storage system is improved, and energy is saved to some extent. In addition, by recording the energy storage scheduling scheme, the subsequent energy storage scheduling scheme can be referenced after the new energy storage system is connected to the grid or part of the energy storage system is disconnected from the grid, and a new energy storage scheduling scheme suitable for the current energy storage can be quickly formed, the adaptability of the energy storage system to changes in energy storage scheduling is enhanced, an efficient energy storage scheduling scheme is formed, the efficient use of energy is further improved, and energy is saved. The technical problem of high energy loss in the process of energy storage power supply in the prior art is solved. BRIEF DESCRIPTION OF DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the specific embodiments of the present application or the prior art, the drawings needed to be used in the description of the specific embodiments or the prior art will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0049] Figure 1 A flowchart of a hybrid energy storage system scheduling method considering actual grid regulation requirements provided for an embodiment of the present application;

[0050] Figure 2 A flowchart of another hybrid energy storage system scheduling method considering actual grid regulation requirements provided for an embodiment of the present application;

[0051] Figure 3 A flowchart of a method for determining energy storage priority scheduling provided for an embodiment of the present application;

[0052] Figure 4 A flowchart of a method for allocating total energy scheduling quantities provided for an embodiment of the present application;

[0053] Figure 5 A flowchart of another method for determining energy storage priority scheduling provided for an embodiment of the present application;

[0054] Figure 6 A flowchart of a method for determining first periodic energy storage scheduling data provided for an embodiment of the present application;

[0055] Figure 7 A flowchart of a method for optimizing a second energy storage scheduling scheme provided for an embodiment of the present application;

[0056] Figure 8 A flowchart of another method for optimizing a second energy storage scheduling scheme provided for an embodiment of the present application;

[0057] Figure 9 A structural diagram of a hybrid energy storage system scheduling device considering actual grid regulation requirements provided for an embodiment of the present application;

[0058] Figure 10 A structural diagram of an electronic device provided for an embodiment of the present application. DETAILED DESCRIPTION

[0059] In order to make the purposes, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions of the present application will be described in detail below with the aid of drawings. Obviously, the described embodiments are only some but not all of the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts should fall within the scope of the present application.

[0060] The terms “comprising” and “having” and any variations thereof mentioned in the embodiments of the present application are intended to cover the inclusions not exclusively. For example, a process, method, system, product, or device comprising a series of steps or units is not limited to the listed steps or units, but can optionally further comprise other steps or units not listed, or can optionally further comprise other steps or units inherent to the process, method, product, or device.

[0061] The most important role of the energy storage system is to store electric energy and output when needed, effectively solving the imbalance of electric power in time and space. At present, the types of energy storage systems are various, which can be generally classified into mechanical energy storage systems, electromagnetic energy storage systems, and electrochemical energy storage systems. The mechanical energy storage systems are further classified into pumped storage energy storage systems, compressed air energy storage systems, and flywheel energy storage systems. The electromagnetic energy storage systems are further classified into superconducting energy storage systems and supercapacitors. The electrochemical energy storage systems are further classified into lead-acid battery energy storage systems, flow battery energy storage systems, and lithium ion battery energy storage systems. Different types of energy storage systems have different performances and application scenarios, and can be designed and adjusted according to needs.

[0062] The technical application of the energy storage system also runs through each link of power generation, power transmission, power distribution, and power consumption of the power system, and truly plays the roles of peak load shifting, efficient system frequency modulation, and increasing power supply reliability. Therefore, the appropriate access of the energy storage system to power dispatching can improve the power grid environment, improve the stability and reliability of the power system, and timely relieve the demand of the power grid for electric energy. By incorporating renewable energy into the power generation range of the power grid through the energy storage system, coordinating with other power generation equipment, and reasonably arranging power generation, the energy storage system can effectively reduce the loss and waste of electric energy, and achieve excellent environmental protection and energy saving effects.

[0063] At present, the energy scheduling method of energy storage system is various, mainly according to the demand of power grid for electricity to arrange reasonably. For the energy scheduling of mixed energy storage system with multiple types in the range, the usual way is to arrange the power transmission of each energy storage system through the analysis of demand power, without reasonably considering the relationship between different types of energy storage system and demand power information. This way is difficult to improve the utilization of energy while considering the economic benefit, and due to the need of energy scheduling, the power of energy storage system in the regional range will fluctuate in the short term, how to incorporate the new energy storage system or exclude part of the mixed energy storage system after the energy storage system according to the demand of power is the acute problem of mixed energy storage system in energy scheduling, which is related to the efficient use of energy and the conservation of resources, and closely related to the livelihood of the people.

[0064] Therefore, due to the technical problem of high power loss in the process of energy storage power supply in the prior art, it is necessary to design a collaborative scheduling method of mixed energy storage system, which can realize efficient energy scheduling of mixed energy storage system formed by incorporating new or excluding part of energy storage system in time while closely combining with power demand information.

[0065] Based on this, the embodiment of the present application provides a mixed energy storage system scheduling method considering the actual regulation and control demand of power grid, which can alleviate the technical problem of high power loss in the process of energy storage power supply in the prior art.

[0066] The embodiments of the present application will be further introduced below in combination with the drawings.

[0067] Figure 1 A flowchart of a mixed energy storage system scheduling method considering the actual regulation and control demand of power grid is provided for the embodiments of the present application, the method can be applied to the mixed energy storage system corresponding to the preset power supply area, and the mixed energy storage system includes power type energy storage system and energy type energy storage system. As shown in the figure, Figure 1 The method includes:

[0068] Step S110, obtaining energy storage scheduling data and performance parameters corresponding to the mixed energy storage system.

[0069] Exemplarily, as Figure 2As shown, the hybrid energy storage system can include a plurality of power-type energy storage systems and a plurality of energy-type energy storage systems. The hybrid energy storage system can first acquire energy storage scheduling data and performance parameters corresponding to the hybrid energy storage system. The hybrid energy storage system can determine the energy storage scheduling data by analyzing load data of a power grid in a preset power supply area. The energy storage scheduling data is the basis for energy storage scheduling and is technical reference data for forming a scheduling scheme. In the embodiments of the present application, the selection of the energy storage scheduling data needs to include as much important information as possible, including electricity demand information, electricity demand power data, increased discharge power during electricity peak period, and increased charging power during electricity valley period. The more aspects considered and the more parameters involved in the selection of the energy storage scheduling data, the more suitable the energy scheduling scheme developed based on the energy storage scheduling data is for the current energy demand, the more efficient the energy scheduling is, and the higher the utilization rate of energy is. The performance parameters of the energy storage system are indispensable when developing the energy storage scheduling scheme. The performance parameters of the hybrid energy storage system include, but are not limited to, the energy storage capacity, economy and life cycle data, charging and discharging performance parameters, and power parameters of each power-type energy storage system and energy-type energy storage system in the hybrid energy storage system. Different types of energy storage systems have their own performance characteristics, and when collecting the performance parameters of each energy storage system, these differences are considered as much as possible to achieve efficient use of energy of different types of energy storage systems.

[0070] Step S120, determining an energy storage priority scheduling mode based on the energy storage scheduling data and the performance parameters.

[0071] As shown in the example, Figure 2 As shown in the example, the main purpose of energy division is to analyze and arrange the acquired parameter data to form reference data for developing an energy storage scheduling scheme. Specifically, the total energy scheduling amount can be divided according to the electricity demand information, the energy storage capacity of each energy storage system, and the economy and life cycle data of each energy storage system; the change amount of energy output can be analyzed according to the electricity demand power data to form an energy output change analysis result; the energy storage priority scheduling mode of the hybrid energy storage system can be determined according to the increased discharge power during the electricity peak period, the increased charging power during the electricity valley period, the charging and discharging performance parameters of each energy storage system, the power parameters of each energy storage system, and the energy output change analysis result.

[0072] Step S130, determining a first energy storage scheduling scheme through the energy storage priority scheduling mode and performing energy storage scheduling on the hybrid energy storage system through the first energy storage scheduling scheme.

[0073] As shown in the example, Figure 2As shown in the figure, once the energy storage priority scheduling method is established, it provides a specific direction and technical foundation for the development of the first energy storage scheduling plan. When determining the first energy storage scheduling plan based on the energy storage priority scheduling method, it is necessary to consider actual scheduling conditions, such as the operability of the scheduling and the actual amount of electricity to be dispatched, and convert the theoretical design data parameters into a feasible engineering solution. Scheduling energy storage according to the first energy storage scheduling plan verifies its feasibility and provides a reference and basis for future energy storage scheduling.

[0074] Step S140: determining first periodic energy storage scheduling data based on the first energy storage scheduling scheme.

[0075] For example, the power grid's demand for electric energy remains basically unchanged or changes regularly within each cycle. Therefore, for the electric energy scheduling plan, an efficient and fast way is to utilize the periodicity of the power grid's electricity consumption and optimize it according to historical scheduling plans. In an embodiment of the present application, the first energy storage scheduling cycle can be determined based on the power grid's electricity consumption pattern; during the first energy storage scheduling cycle, the actual scheduling power of each energy storage system involved in the first energy storage scheduling plan as it changes with the scheduling time is recorded to form the first periodic energy storage scheduling data. The optimization involves changes in the energy storage system, and it is necessary to use historical scheduling plan data to adjust the changed energy storage system to conform to the current energy storage scheduling situation, so as to ensure that the energy storage scheduling of the hybrid energy storage system is adapted to the current energy demand.

[0076] It should be noted that the data on energy storage scheduling is rich and highly referenceable. When formulating scheduling plans in actual applications, parameters can be expanded and supplemented to a certain extent based on the actual project, further optimizing the process and content of the subsequent second energy storage scheduling plan.

[0077] Step S150: Optimizing the second energy storage scheduling scheme based on the first periodic energy storage scheduling data.

[0078] For example, Figure 2 As shown, energy storage scheduling is a massive undertaking involving numerous aspects. Simply selecting energy storage systems for scheduling requires considering the number and types of energy storage systems within the scope, such as newly connected energy storage systems and off-grid backup energy storage systems. This requires also considering both economic benefits and efficient energy utilization, ensuring efficient energy scheduling despite changing conditions. In this embodiment, the second energy storage scheduling plan developed subsequently can be optimized based on the first periodic energy storage scheduling data.

[0079] In the embodiments of the present application, the hybrid energy storage system first acquires energy storage scheduling data of a preset power supply area and performance parameters of each energy storage system in the hybrid energy storage system corresponding to the preset power supply area, analyzes the two to form an energy storage priority scheduling mode, then determines a first energy storage scheduling scheme according to the energy storage priority scheduling mode, and schedules the energy storage of the hybrid energy storage system through the first energy storage scheduling scheme; the hybrid energy storage system can also record data corresponding to the first energy storage scheduling scheme, form first periodic energy storage scheduling data according to the data, and then optimize a second energy storage scheduling scheme formulated subsequently according to the first periodic energy storage scheduling data. By comprehensively analyzing the data parameters, an energy storage scheduling scheme suitable for the energy demand of the power grid is formed, so that the energy storage scheduling scheme for the energy storage system is more matched with the power demand of the power grid, the efficient use of the energy of the energy storage system is improved, and the energy is saved to a certain extent. In addition, by recording the energy storage scheduling scheme, the subsequent energy storage scheduling scheme can be referenced after the new energy storage system is connected to the grid or part of the energy storage system is disconnected from the grid, and a new scheme suitable for the current energy storage scheduling can be quickly formed, the adaptability of the energy storage system to the change of the energy storage scheduling is enhanced, an efficient energy storage scheduling scheme is formed, the efficient use of energy is further improved, and energy is saved. The technical problem of high power loss in the energy storage power supply process in the prior art is solved.

[0080] The above steps are described in detail below.

[0081] In some embodiments, the energy storage scheduling data and the performance parameters can include multiple types. By including multiple data types, the hybrid energy storage system can more flexibly schedule multiple subordinate energy storage systems, and the scheduling can be more accurate and reasonable, which effectively reduces the power loss in the energy storage power supply process. As an example, the energy storage scheduling data includes any one or more of the following:

[0082] power demand information, power demand power data, increased discharge power during power peak period, and increased charge power during power valley period;

[0083] The performance parameters include any one or more of the following:

[0084] energy storage capacity of the hybrid energy storage system, economy and life cycle data of the hybrid energy storage system, charge and discharge performance parameters of the hybrid energy storage system, and power parameters of the hybrid energy storage system.

[0085] For example, Figure 3As shown, the energy storage scheduling data is the basis for energy scheduling, and is the technical reference data for forming the scheduling scheme. The selection of energy storage scheduling data needs to include as much information as possible, including electricity demand information, electricity demand power data, increased discharge power during electricity peak period, and increased charging power during electricity valley period. Among them, the electricity demand information can provide a total electricity demand as a basis for determining the demand electricity demand and matching the total electricity demand. At the same time, the electricity demand information also provides a reference basis for determining the preset power supply area range of the hybrid energy storage system and matching different types and quantities of energy storage systems. For electricity demand power data, it mainly provides the distribution form of demand power under the condition of total demand of power grid electricity. It can guide the selection of type and quantity of energy storage system in energy scheduling, and provide the basis for scheduling priority of these energy storage systems. For the increased discharge power during the electricity peak period, it mainly affects the selection and scheduling of energy storage system when the electricity demand increases in the scheduling scheme. Similarly, the increased charging power during the electricity valley period mainly provides the selection and scheduling of energy storage system when the electricity demand decreases in the scheduling scheme. The more aspects considered and the more parameters involved in the selection of energy demand data, the more suitable the energy scheduling scheme developed based on these energy demand data for the current energy demand, and the more efficient the energy scheduling, which improves the utilization rate of energy.

[0086] For the performance parameters of the hybrid energy storage system, they are indispensable when developing the energy storage scheduling scheme. Different types of power energy storage systems and energy energy storage systems in the hybrid energy storage system have their own performance characteristics. If the performance parameters of each energy storage system are collected as much as possible considering these differences, the efficient use of energy of different types of energy storage systems can be achieved. Therefore, the selection of performance parameters of each energy storage system includes but is not limited to the energy storage capacity of each energy storage system, the economy and life cycle data of each energy storage system, the discharge and charge performance parameters of each energy storage system, and the power parameters of each energy storage system. Among them, the energy storage capacity of the energy storage system provides the rated energy of the energy storage system. The economy and life cycle data of the energy storage system are the parameter data when the energy storage system reaches the best energy supply state considering its own situation, which is the basis for considering economic benefits when developing the energy storage scheduling scheme. The discharge and charge performance parameters of the energy storage system and the power parameters of the energy storage system are the basis for prioritizing and scheduling different types and quantities of energy storage systems according to the actual electricity demand when developing the energy storage scheduling scheme, and are also the basis for determining whether the energy scheduling scheme is more efficient in using electricity.

[0087] By including multiple types of energy storage scheduling data and performance parameters, the hybrid energy storage system can more flexibly schedule multiple energy storage systems, more accurately and reasonably schedule, and more effectively reduce power loss during energy storage power supply.

[0088] In some embodiments, the energy storage scheduling data and the performance parameters of the hybrid energy storage system can be combined for comprehensive processing to confirm the energy storage priority scheduling mode. By scientifically and efficiently confirming the energy storage priority scheduling mode, power loss during energy storage power supply can be effectively reduced. As an example, the above step S120 can specifically include the following steps:

[0089] Step a), based on the electricity demand information, the energy storage capacity of the hybrid energy storage system, and the economy and life cycle data of the hybrid energy storage system, the total energy scheduling amount is allocated.

[0090] Step b), based on the electricity demand power data, the energy output change amount is analyzed to obtain the energy output change analysis result.

[0091] Step c), based on the increased discharge power during the electricity peak period, the increased charge power during the electricity valley period, the charge and discharge performance parameters of the hybrid energy storage system, the power parameters of the hybrid energy storage system, and the energy output change analysis result, the energy storage priority scheduling mode is determined.

[0092] As shown in the example of Figure 3 The electricity demand information, the energy storage capacity of each energy storage system under the hybrid energy storage system, and the economy and life cycle data of each energy storage system under the hybrid energy storage system can be comprehensively processed to reasonably and effectively allocate the performance of the hybrid energy storage system according to the total energy scheduling amount of the electricity demand, and then the energy storage scheduling of the hybrid energy storage system is more matched to the actual electricity demand, achieving the purpose of efficient use of energy storage system power. Based on the electricity demand power data, the energy output change amount can be analyzed. The energy output change analysis is the basis for subsequent confirmation of the energy deployment mode of the hybrid energy storage system, which provides a basis for reasonably arranging different types and quantities of energy storage systems. Combined with the increased discharge power during the electricity peak period, the increased charge power during the electricity valley period, the charge and discharge performance parameters of each energy storage system under the hybrid energy storage system, and the power parameters of each energy storage system under the hybrid energy storage system, the energy scheduling of the hybrid energy storage system can be more specifically arranged and designed.

[0093] The total energy scheduling amount is distributed based on the electricity demand information, the energy storage capacity of the hybrid energy storage system, and the economy and life cycle data of the hybrid energy storage system, the electricity output change amount is analyzed based on the electricity demand power data, the electricity output change analysis result is obtained, the energy storage priority scheduling mode is determined based on the increased discharge power in the electricity peak period, the increased charge power in the electricity valley period, the charge and discharge performance parameters of the hybrid energy storage system, the power parameters of the hybrid energy storage system, and the electricity output change analysis result. Overall, the electricity demand, the performance of the hybrid energy storage system, and the dynamic design of scheduling are comprehensively unified to form a close energy storage scheduling scheme development method, which is beneficial to efficient energy scheduling and to a certain extent, efficient use of energy.

[0094] Based on the above steps a), step b) and step c), in actual application, the total power generation of the power grid needs to be balanced with the total power consumption to meet the demand of the power grid for power consumption, while ensuring the stability of the operation of the power grid. The process of energy storage scheduling itself is also a process of generating economic benefits, so while developing a reasonable first energy storage scheduling scheme, the economic benefits generated by the process need to be considered, and the total energy scheduling amount is distributed according to the economic benefits, so as to realize efficient use of energy. As an example, the electricity demand information includes the total electricity demand; the above step a) can specifically include the following steps:

[0095] Step d), based on the total electricity demand, the energy storage capacity of the hybrid energy storage system, and the economy and life cycle data of the hybrid energy storage system, an economic benefit calculation model is established.

[0096] Step e), the type and quantity of the hybrid energy storage system that needs to be scheduled in the hybrid energy storage system are determined according to the economic benefit calculation model.

[0097] As shown in Figure 4 , the economy of energy storage scheduling can be analyzed as a target function, which can obtain higher economic benefits, and the first energy storage scheduling scheme accompanied by economic benefits is also optimized in the economic level. The economic benefits are related to the economy and life cycle data of each energy storage system under the hybrid energy storage system, and the energy storage capacity and electricity demand of each energy storage system are related. The economic benefits and electricity demand are unified in the two performance parameters of each energy storage system, a related target function relationship is established, and the type and quantity of each energy storage system involved in energy scheduling to obtain higher economic benefits can be obtained.

[0098] By first establishing an economic benefit calculation model based on the total electricity demand, the energy storage capacity of the hybrid energy storage system, and the economic benefit and life cycle data of the hybrid energy storage system, and then determining the type and quantity of the hybrid energy storage system that needs to be dispatched in the hybrid energy storage system according to the economic benefit calculation model, a reasonable first energy storage dispatching scheme is formulated while taking into account the economic benefit, the total energy dispatching amount is allocated according to the economic benefit, and efficient use of energy is achieved.

[0099] Based on the above steps a), step b) and step c), in actual application, although the total demand for electric energy is unchanged, the demand for electric energy is fluctuating within the time range of energy storage dispatching during the process of energy storage dispatching, therefore, it is necessary to reasonably prioritize and arrange the various energy storage systems determined for this energy storage dispatching according to such fluctuations, so as to achieve efficient use of energy. As an example, the electric energy output change analysis result includes power demand change data during the dispatching period; the above step c) can specifically include the following steps:

[0100] Step f), based on the power demand change data, the charging and discharging performance parameters of the hybrid energy storage system, and the power parameters of the hybrid energy storage system, the dispatching priority of the hybrid energy storage system is determined.

[0101] Step g), based on the increased discharging power during the power consumption peak period, the type and quantity of the hybrid energy storage system that needs to be increased in dispatching in the hybrid energy storage system are determined.

[0102] Step h), based on the increased charging power during the power consumption valley period, the type and quantity of the hybrid energy storage system that needs to be reduced in dispatching in the hybrid energy storage system are determined.

[0103] As an example, as shown in Figure 5 The power demand data is the basis for such priority allocation and arrangement, the change in the demand for electric energy is matched according to the performance parameters of each energy storage system, so as to determine the allocation priority of each energy storage system, especially when the increased discharging power during the power consumption peak period is increased, the type and quantity of each energy storage system that needs to be increased in dispatching are determined, and when the power consumption decreases during the power consumption valley, the type and quantity of each energy storage system that needs to be reduced in dispatching are determined, both of which relate to the stable operation of the power grid and the prominent role of the energy storage system in peak load shifting of the power grid.

[0104] The scheduling priority of the hybrid energy storage system is determined based on the power change data of the electricity demand, the charging and discharging performance parameters of the hybrid energy storage system, and the power parameters of the hybrid energy storage system. The type and quantity of the hybrid energy storage system that needs to be increased in scheduling are determined based on the increased discharging power during the electricity peak period. The type and quantity of the hybrid energy storage system that needs to be reduced in scheduling are determined based on the increased charging power during the electricity valley period. In the process of energy storage scheduling, reasonable priority allocation and arrangement of each energy storage system according to the fluctuation of the electricity demand are realized, and efficient use of energy is realized.

[0105] In some embodiments, the demand for electricity of the power grid is basically unchanged or regularly changed in each cycle, so that the efficient and fast way of scheduling scheme for electricity is to utilize the periodicity of power grid electricity and optimize the historical scheduling scheme, thereby effectively realizing efficient use of electricity. As an example, the above step S140 can specifically include the following steps:

[0106] Step i), determining a first energy storage scheduling cycle based on the electricity regularity of the preset power supply area.

[0107] Step j), recording the actual scheduling electricity of the hybrid energy storage system changing with the scheduling time in the first energy storage scheduling cycle to obtain first periodic energy storage scheduling data.

[0108] As an example, as shown in Figure 6 the first energy storage scheduling cycle can be determined according to the electricity regularity of the power grid of the preset power supply area; the actual scheduling electricity of each energy storage system involved in the first energy storage scheduling scheme changing with the scheduling time is recorded in the first energy storage scheduling cycle to form the first periodic energy storage scheduling data. The change of the energy storage system involved in the optimization needs to utilize the historical scheduling scheme data to adjust the changed energy storage system to adapt to the current energy storage scheduling situation, so as to ensure that the energy storage scheduling of the energy storage system adapts to the current energy demand.

[0109] By first determining the first energy storage scheduling cycle based on the electricity regularity of the preset power supply area, and then recording the actual scheduling electricity of the hybrid energy storage system changing with the scheduling time in the first energy storage scheduling cycle to obtain the first periodic energy storage scheduling data, the actual scheduling electricity of the hybrid energy storage system changing with the scheduling time in the first energy storage scheduling cycle can be realized, which is convenient for realizing the later optimization and reducing the electricity loss in the energy storage power supply process.

[0110] In some embodiments, the mixed energy storage system includes multiple types of energy storage systems, and the preset power supply area also includes shared energy storage systems that are not included in the mixed energy storage system. By including these energy storages together and considering them in the scheduling, the scheduling of the mixed energy storage system can be more flexible. As an example, the mixed energy storage system also includes newly connected energy type energy storage systems and off-grid backup energy storage systems, and the preset power supply area also includes shared energy storage systems that are not included in the mixed energy storage system. The above step S150 can specifically include the following steps:

[0111] Step k), obtaining the demand power of the preset power supply area varying with the scheduling time.

[0112] Step l), calculating the matching degree of the mixed energy storage system, the newly connected energy type energy storage system, the backup energy storage system, and the shared energy storage system with respect to the demand power, respectively, and determining the target energy storage system with the highest matching degree.

[0113] Step m), adding the target energy storage system to the scheduling range of the mixed energy storage system, or replacing at least one energy storage system in the mixed energy storage system with the target energy storage system, to complete the optimization of the second energy scheduling scheme.

[0114] As shown in the example of Figure 7 When there is a newly connected energy type energy storage system in the preset power supply area, i.e., in the energy scheduling range, if it is directly included in the energy storage scheduling range, on the one hand, it is difficult to achieve efficient and economic use of the energy storage system without matching analysis of the energy storage system and the energy demand, which may reduce the efficiency of energy scheduling and further reduce the energy utilization rate and waste energy. On the other hand, increasing the amount of scheduling energy in a system that has already achieved balance between scheduling energy and demand energy may cause imbalance between energy scheduling and demand, thereby affecting the stability of the power grid. For subsequent energy deployment schemes, if the off-grid energy storage system is excluded from the preset power supply area, the shared energy storage system that is not included in the preset power supply area and can be selected needs to be considered, and the efficiency of energy deployment needs to be improved.

[0115] Therefore, the existing mixed energy storage system, newly connected energy type energy storage system, off-grid backup energy storage system, and shared energy storage system that is not included in the mixed energy storage system need to be considered together, the matching degree of each of the four with respect to the actual demand power is calculated, and the target energy storage system with the highest matching degree is selected, so as to optimize the next cycle energy scheduling scheme. It should be noted that the existing mixed energy storage system can include multiple power type energy storage systems and multiple energy type energy storage systems, and therefore the matching degree of each energy storage system in the existing mixed energy storage system can be calculated. As an example,Figure 8 If only the power-type energy storage system exists in the existing hybrid energy storage system, and the matching degree of the power-type energy storage system is the highest after calculation, the scheme does not need to be changed; if the energy-type energy storage system newly connected to the grid has the highest matching degree, it can be used to replace one or more energy storage systems in the existing hybrid energy storage system; if the standby energy storage system off the grid has the highest matching degree, it can be included in the hybrid energy storage system for continuous use, or it can be used to replace one or more energy storage systems in the existing hybrid energy storage system; if the shared energy storage system not included has the highest matching degree, it can also be included in the hybrid energy storage system for continuous use, or it can be used to replace one or more energy storage systems in the existing hybrid energy storage system.

[0116] By including multiple energy storage systems in the dispatch consideration range and comparing the matching degrees, the dispatch of the hybrid energy storage system can be more flexible, the energy storage dispatch scheme of the next period can be more perfect, and the utilization rate of energy can be improved.

[0117] Based on the above steps k), step l) and step m), the comparison of multiple energy storage systems can be realized in a more scientific way, so that the most reasonable energy storage dispatch scheme can be provided for the hybrid energy storage system, and the energy storage dispatch scheme for the energy storage system can be more matched with the power grid demand, and the efficient use of energy of the energy storage system can be improved. As an example, the above step l) can specifically include the following steps:

[0118] Step n), obtaining the actual dispatch power of the hybrid energy storage system changing with the dispatch time.

[0119] Step o), obtaining the performance parameters, economy and life cycle data, and rated energy of the energy-type energy storage system newly connected to the grid, and based on the performance parameters, economy and life cycle data, and rated energy of the energy-type energy storage system, obtaining the first economic dispatch power.

[0120] Step p), obtaining the performance parameters, economy and life cycle data, and rated energy of the standby energy storage system, and based on the performance parameters, economy and life cycle data, and rated energy of the standby energy storage system, obtaining the second economic dispatch power.

[0121] Step q), obtaining the performance parameters, economy and life cycle data, and rated energy of the shared energy storage system, and based on the performance parameters, economy and life cycle data, and rated energy of the shared energy storage system, obtaining the third economic dispatch power.

[0122] Step r), respectively calculating the matching degrees of the actual dispatch power, the first economic dispatch power, the second economic dispatch power, and the third economic dispatch power relative to the demand power, and determining the target energy storage system with the highest matching degree.

[0123] For example, for the existing hybrid energy storage system, the actual scheduling power on the previous cycle varying with the scheduling time can be directly used as the comparison data, and for other energy storage systems, the corresponding economic scheduling power can be calculated through the performance parameters, economy and life cycle data, and rated energy of various energy storage systems. By comparing the power of the four energy storage systems with the actual demand power, the target energy storage system with the highest matching degree can be determined.

[0124] Figure 9 A structure diagram of a hybrid energy storage system scheduling device 900 considering the actual regulation and control demand of the power grid is provided for the embodiments of the present application. The device can be applied to the hybrid energy storage system corresponding to the preset power supply area, and the hybrid energy storage system includes a power-type energy storage system and an energy-type energy storage system. As shown in the figure, the device includes: Figure 9 The acquisition module 901 is configured to acquire energy storage scheduling data and performance parameters corresponding to the hybrid energy storage system.

[0125] The first determination module 902 is configured to determine an energy storage priority scheduling mode based on the energy storage scheduling data and the performance parameters.

[0126] The scheduling module 903 is configured to determine a first energy storage scheduling scheme through the energy storage priority scheduling mode, and to perform energy storage scheduling on the hybrid energy storage system through the first energy storage scheduling scheme.

[0127] The second determination module 904 is configured to determine first periodic energy storage scheduling data based on the first energy storage scheduling scheme.

[0128] The optimization module 905 is configured to optimize a second energy storage scheduling scheme based on the first periodic energy storage scheduling data.

[0129] In some embodiments, the energy storage scheduling data includes any one or more of the following:

[0130] power demand information, power demand power data, increased discharge power during power demand peak period, and increased charge power during power demand valley period;

[0131] The performance parameters include any one or more of the following:

[0132] energy storage capacity of the hybrid energy storage system, economy and life cycle data of the hybrid energy storage system, charge and discharge performance parameters of the hybrid energy storage system, and power parameters of the hybrid energy storage system.

[0133] In some embodiments, the first determination module 902 is specifically configured to:

[0134]

[0135] ​based on the electricity demand information, the energy storage capacity of the hybrid energy storage system, and the economy and life cycle data of the hybrid energy storage system, to perform total electricity scheduling quantity distribution;

[0136] based on the electricity demand power data, to perform electricity output change quantity analysis, and obtain an electricity output change analysis result;

[0137] based on the increased discharge power during the electricity peak period, the increased charge power during the electricity valley period, the charge and discharge performance parameters of the hybrid energy storage system, the power parameters of the hybrid energy storage system, and the electricity output change analysis result, to determine the energy storage priority scheduling mode.

[0138] In some embodiments, the electricity demand information includes a total electricity demand quantity; the first determination module 902 is specifically configured to:

[0139] based on the total electricity demand quantity, the energy storage capacity of the hybrid energy storage system, and the economy and life cycle data of the hybrid energy storage system, to establish an economic benefit calculation model;

[0140] determine the type and quantity of the energy storage system in the hybrid energy storage system that needs to be scheduled according to the economic benefit calculation model.

[0141] In some embodiments, the electricity output change analysis result includes electricity demand power change data during the scheduling period; the first determination module 902 is specifically configured to:

[0142] based on the electricity demand power change data, the charge and discharge performance parameters of the hybrid energy storage system, and the power parameters of the hybrid energy storage system, to determine the scheduling priority of the hybrid energy storage system;

[0143] based on the increased discharge power during the electricity peak period, to determine the type and quantity of the energy storage system in the hybrid energy storage system that needs to be increased in scheduling;

[0144] based on the increased charge power during the electricity valley period, to determine the type and quantity of the energy storage system in the hybrid energy storage system that needs to be reduced in scheduling.

[0145] In some embodiments, the second determination module 904 is specifically configured to:

[0146] based on the electricity usage law of the preset power supply area, to determine a first energy storage scheduling period;

[0147] record the actual scheduling electricity quantity of the hybrid energy storage system with respect to the scheduling time within the first energy storage scheduling period, and obtain first periodic energy storage scheduling data.

[0148] In some embodiments, the hybrid energy storage system further includes a newly grid-connected energy type energy storage system and an off-grid backup energy storage system; the preset power supply area further includes a shared energy storage system that is not included in the hybrid energy storage system; the optimization module 905 is specifically configured to:

[0149] obtaining the demand power of the preset power supply area varying with the scheduling time;

[0150] respectively calculating the matching degrees of the hybrid energy storage system, the newly grid-connected energy type energy storage system, the backup energy storage system and the shared energy storage system with respect to the demand power, and determining a target energy storage system with the highest matching degree;

[0151] adding the target energy storage system to the scheduling range of the hybrid energy storage system, or replacing at least one energy storage system in the hybrid energy storage system with the target energy storage system, to complete the optimization of the second energy storage scheduling scheme.

[0152] In some embodiments, the optimization module 905 is specifically configured to:

[0153] obtaining the actual scheduling power of the hybrid energy storage system varying with the scheduling time;

[0154] obtaining the performance parameters, economy and life cycle data and rated energy of the newly grid-connected energy type energy storage system, and obtaining a first economic scheduling power based on the performance parameters, economy and life cycle data and rated energy of the newly grid-connected energy type energy storage system;

[0155] obtaining the performance parameters, economy and life cycle data and rated energy of the backup energy storage system, and obtaining a second economic scheduling power based on the performance parameters, economy and life cycle data and rated energy of the backup energy storage system;

[0156] obtaining the performance parameters, economy and life cycle data and rated energy of the shared energy storage system, and obtaining a third economic scheduling power based on the performance parameters, economy and life cycle data and rated energy of the shared energy storage system;

[0157] respectively calculating the matching degrees of the actual scheduling power, the first economic scheduling power, the second economic scheduling power and the third economic scheduling power with respect to the demand power, and determining a target energy storage system with the highest matching degree.

[0158] The apparatus provided by the embodiments of the present application has the same implementation principle and technical effects as the foregoing method embodiments, and for brevity of description, the parts not mentioned in the system embodiment part can be referred to the corresponding contents in the foregoing method embodiments.

[0159] The electronic device provided by the embodiments of the present application, specifically, comprises a processor and a storage device; the storage device stores a computer program, and the computer program performs the method of any one of the above embodiments when executed by the processor.

[0160] Figure 10A structural schematic diagram of an electronic device provided by the embodiment of the present application is provided, and the electronic device comprises a processor 1001, a memory 1002, a bus 1003 and a communication interface 1004, the processor 1001, the communication interface 1004 and the memory 1002 are connected through the bus 1003; the processor 1001 is used for executing an executable module stored in the memory 1002, for example, a computer program.

[0161] The memory 1002 can contain a high-speed random access memory (RAM, Random Access Memory) and can also include a non-volatile memory (Non-volatile Memory), for example, at least one disk memory. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 1004 (which can be wired or wireless), and the Internet, a wide area network, a local area network, a metropolitan area network, etc. can be used.

[0162] The bus 1003 can be an ISA bus, a PCI bus or an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 10 Only one bidirectional arrow is used in the above figure, but it does not mean that there is only one bus or only one type of bus.

[0163] The memory 1002 is used for storing a program, and the processor 1001 executes the program after receiving an execution instruction. The method executed by the device defined by the flow process disclosed in any of the above embodiments of the present application can be applied to the processor 1001 or realized by the processor 1001.

[0164] The processor 1001 can be an integrated circuit chip having a signal processing capability. In the implementation process, each step of the above method can be completed by the integrated logic circuit or the instruction in the form of software in the processor 1001. The processor 1001 described above can be a general processor, including a central processing unit (CPU), a network processor (NP), etc.; can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component. Each method, step and logic block diagram disclosed in the embodiments of the present application can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as a hardware code processor for execution, or a combination of hardware and software modules in the code processor for execution. The software module can be located in a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium in the art. The storage medium is located in the memory 1002, and the processor 1001 reads the information in the memory 1002, and combines the hardware to complete the steps of the above method.

[0165] The computer program product of the readable storage medium provided by the embodiments of the present application comprises a computer readable storage medium storing program codes, and the instructions included in the program codes can be used to execute the method in the foregoing method embodiments. For specific implementation, please refer to the foregoing method embodiments, which will not be described here.

[0166] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the part of the prior art that essentially contributes to the present application or the part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the embodiments of the present application. The aforementioned storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0167] Finally, it should be noted that the above embodiments are only specific implementations of the present application, which are used to illustrate the technical solutions of the present application, but not to limit them. The protection scope of the present application is not limited thereto. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily think of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed by the present application, or make equivalent replacements to some of the technical features. These modifications, changes or replacements do not cause the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A hybrid energy storage system scheduling method considering the actual control needs of the power grid, characterized in that: A hybrid energy storage system corresponding to a preset power supply area, wherein the hybrid energy storage system includes a power-type energy storage system and an energy-type energy storage system; the method includes: Obtaining energy storage scheduling data and performance parameters corresponding to the hybrid energy storage system; Determining an energy storage priority scheduling method based on the energy storage scheduling data and the performance parameters; Determining a first energy storage scheduling scheme by using the energy storage priority scheduling method, and performing energy storage scheduling on the hybrid energy storage system by using the first energy storage scheduling scheme; Determining first periodic energy storage scheduling data based on the first energy storage scheduling plan; Optimizing a second energy storage scheduling scheme based on the first periodic energy storage scheduling data; The hybrid energy storage system also includes a newly grid-connected energy storage system and an off-grid backup energy storage system; the preset power supply area also includes a shared energy storage system that is not included in the hybrid energy storage system; The step of optimizing the second energy storage scheduling scheme based on the first periodic energy storage scheduling data includes: Obtaining the power demand of the preset power supply area as it changes with the scheduling time; Calculating the matching degree of the hybrid energy storage system, the newly grid-connected energy storage system, the backup energy storage system, and the shared energy storage system relative to the required power, and determining the target energy storage system with the highest matching degree; The target energy storage system is added to the scheduling range of the hybrid energy storage system, or at least one energy storage system in the hybrid energy storage system is replaced with the target energy storage system to complete the optimization of the second energy storage scheduling scheme.

2. The method according to claim 1, characterized in that The energy storage scheduling data includes any one or more of the following: Electricity demand information, electricity demand power data, increased discharge power during peak periods, and increased charging power during off-peak periods; The performance parameters include any one or more of the following: The energy storage capacity of the hybrid energy storage system, the economic and life cycle data of the hybrid energy storage system, the charging and discharging performance parameters of the hybrid energy storage system, and the power parameters of the hybrid energy storage system.

3. The method according to claim 2, characterized in that The step of determining the energy storage priority scheduling method based on the energy storage scheduling data and the performance parameters includes: Allocate a total amount of electric energy based on the electricity demand information, the energy storage capacity of the hybrid energy storage system, and the economic performance and life cycle data of the hybrid energy storage system; Performing an analysis of the change in electric energy output based on the electric energy demand power data to obtain an analysis result of the change in electric energy output; The energy storage priority scheduling method is determined based on the increased discharge power during the peak electricity consumption period, the increased charging power during the valley electricity consumption period, the charging and discharging performance parameters of the hybrid energy storage system, the power parameters of the hybrid energy storage system, and the analysis results of the electric energy output changes.

4. The method according to claim 3, characterized in that The electricity demand information includes a total electricity demand; and the step of allocating a total electric energy dispatch amount based on the electricity demand information, the energy storage capacity of the hybrid energy storage system, and the economic performance and life cycle data of the hybrid energy storage system includes: Establishing an economic benefit calculation model based on the total electricity demand, the energy storage capacity of the hybrid energy storage system, and the economic performance and life cycle data of the hybrid energy storage system; The type and quantity of energy storage systems that need to be scheduled in the hybrid energy storage system are determined according to the economic benefit calculation model.

5. The method according to claim 3, characterized in that The electric energy output change analysis result includes power demand change data during the scheduling period; the step of determining the energy storage priority scheduling method based on the increased discharge power during the peak power consumption period, the increased charging power during the valley power consumption period, the charging and discharging performance parameters of the hybrid energy storage system, the power parameters of the hybrid energy storage system, and the electric energy output change analysis result includes: Determining a scheduling priority of the hybrid energy storage system based on the power change data of the electricity demand, the charging and discharging performance parameters of the hybrid energy storage system, and the power parameters of the hybrid energy storage system; Determining, based on the increased discharge power during the peak electricity consumption period, the type and number of the hybrid energy storage systems that need to be increased in scheduling in the hybrid energy storage system; Based on the increased charging power during the electricity consumption valley period, the type and number of the hybrid energy storage systems that need to reduce scheduling are determined.

6. The method according to claim 1, characterized in that The step of determining first periodic energy storage scheduling data based on the first energy storage scheduling scheme includes: Determining a first energy storage scheduling period based on the power consumption pattern of the preset power supply area; During the first energy storage scheduling period, actual dispatched power of the hybrid energy storage system that changes with scheduling time is recorded to obtain first periodic energy storage scheduling data.

7. The method according to claim 1, characterized in that The step of respectively calculating the matching degree of the hybrid energy storage system, the newly grid-connected energy-type energy storage system, the backup energy storage system, and the shared energy storage system relative to the required power, and determining the target energy storage system with the highest matching degree includes: Obtaining actual dispatched power of the hybrid energy storage system as it changes with dispatch time; Obtaining performance parameters, economic and life cycle data, and rated energy of the newly grid-connected energy-type energy storage system, and obtaining a first economically dispatched power based on the performance parameters, economic and life cycle data, and rated energy of the newly grid-connected energy-type energy storage system; Obtaining performance parameters, economic and life cycle data, and rated energy of the backup energy storage system, and obtaining a second economically dispatchable power based on the performance parameters, economic and life cycle data, and rated energy of the backup energy storage system; Obtaining performance parameters, economic and life cycle data, and rated energy of the shared energy storage system, and obtaining a third economic dispatch power based on the performance parameters, economic and life cycle data, and rated energy of the shared energy storage system; The matching degrees of the actual dispatched electricity, the first economic dispatched electricity, the second economic dispatched electricity, and the third economic dispatched electricity relative to the required electricity are calculated respectively, and a target energy storage system with the highest matching degree is determined.

8. A hybrid energy storage system scheduling device that takes into account the actual control needs of the power grid, characterized in that: A hybrid energy storage system corresponding to a preset power supply area, the hybrid energy storage system including a power-type energy storage system and an energy-type energy storage system; the device includes: An acquisition module, configured to acquire energy storage scheduling data and performance parameters corresponding to the hybrid energy storage system; A first determining module is configured to determine an energy storage priority scheduling mode based on the energy storage scheduling data and the performance parameters; a scheduling module, configured to determine a first energy storage scheduling scheme according to the energy storage priority scheduling method, and perform energy storage scheduling on the hybrid energy storage system according to the first energy storage scheduling scheme; a second determining module, configured to determine first periodic energy storage scheduling data based on the first energy storage scheduling scheme; an optimization module, configured to optimize a second energy storage scheduling scheme based on the first periodic energy storage scheduling data; The hybrid energy storage system also includes a newly grid-connected energy storage system and an off-grid backup energy storage system; the preset power supply area also includes a shared energy storage system that is not included in the hybrid energy storage system; The second determination module is further configured to: obtain the power demand of the preset power supply area as it changes with the scheduling time; respectively calculate the matching degree of the hybrid energy storage system, the newly grid-connected energy storage system, the backup energy storage system, and the shared energy storage system relative to the power demand, and determine the target energy storage system with the highest matching degree; add the target energy storage system to the scheduling range of the hybrid energy storage system, or replace at least one energy storage system in the hybrid energy storage system with the target energy storage system, thereby completing the optimization of the second energy storage scheduling scheme.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

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