Scheduling optimization method and device for cooperation of independent energy storage and power grid

Abstract

The invention relates to the technical field of power grid dispatching, in particular to an independent energy storage and power grid collaborative dispatching optimization method and device.The method comprises the steps that a power grid coverage area is divided into a plurality of power grid unit areas, and each power grid unit area comprises at least one power energy storage device; a unique unit area identifier is set for each power grid unit area; obtaining a power supply and demand state vector of each power grid unit area, wherein the power supply and demand state vector comprises an electrical load gap index and a corresponding unit area identifier; and inputting all the power supply and demand state vectors into a preset power cooperative scheduling space for optimization processing, obtaining an optimal cooperative scheduling scheme in the power grid coverage area, and performing scheduling processing based on the optimal cooperative scheduling scheme. Power grid load fluctuation and energy storage state change can be quickly responded, power grid operation cost is reduced, and power supply quality and service level are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of composite materials, and in particular to a method and device for optimizing the coordinated dispatching of independent energy storage and power grid. Background Art

[0002] With the rapid development of renewable energy, the proportion of intermittent energy such as wind and solar energy continues to increase, and the load volatility and uncertainty of the power grid have increased significantly. In order to meet this challenge, independent energy storage systems have received extensive attention and development. Independent energy storage systems can smooth load fluctuations and improve the flexibility and stability of the power system by storing excess electricity and releasing it when needed.

[0003] However, in practical applications, how to effectively integrate independent energy storage systems into the existing power grid and ensure the coordinated operation between the two to achieve the goal of optimizing resource allocation and improving economic benefits is still an urgent problem to be solved. The current dispatching methods often lack the refined management of regional power load characteristics and energy storage status, making it difficult to fully tap the potential of energy storage equipment, resulting in low efficiency and high costs of grid operation, and even affecting the quality of power supply and service level.

[0004] Therefore, there is an urgent need to provide a scheduling optimization method and device for coordinated independent energy storage and power grid to solve the above technical problems. Summary of the invention

[0005] The embodiments of the present invention provide a method and device for optimizing the coordinated dispatch of independent energy storage and power grid, which can quickly respond to grid load fluctuations and changes in energy storage status, reduce grid operation costs, and improve power supply quality and service levels.

[0006] In a first aspect, an embodiment of the present invention provides a dispatch optimization method for coordinated independent energy storage and power grid, the method comprising: Divide the grid coverage area into a number of grid unit areas, each grid unit area includes at least one power energy storage device, and set a unique unit area identifier for each grid unit area; Acquire a power supply and demand state vector of each of the power grid unit areas, wherein the power supply and demand state vector includes a power load gap index and a corresponding unit area identifier; All power supply and demand state vectors are input into a preset power coordinated dispatching space for optimization processing, an optimal coordinated dispatching scheme within the power grid coverage area is obtained, and dispatching processing is performed based on the optimal coordinated dispatching scheme.

[0007] In a second aspect, an embodiment of the present invention further provides a dispatch optimization device for coordinated independent energy storage and power grid, the device comprising: A grid unit division module, used to divide the grid coverage area into a plurality of grid unit areas, each grid unit area includes at least one power energy storage device, and a unique unit area identifier is set for each grid unit area; A power supply and demand state acquisition module, used to acquire a power supply and demand state vector of each power grid unit area, wherein the power supply and demand state vector includes a power load gap index and a corresponding unit area identifier; The coordinated dispatch optimization module is used to input all power supply and demand state vectors into the preset power coordinated dispatch space for optimization processing to obtain the optimal coordinated dispatch solution within the power grid coverage area; The scheduling processing execution module is used to perform actual scheduling processing based on the optimal collaborative scheduling solution.

[0008] In a third aspect, an embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the method of any embodiment of the present invention is implemented.

[0009] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to execute a method according to any embodiment of the present invention.

[0010] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention realizes accurate grasp of the power supply and demand status by refining the grid area division, and the unique identification of each grid unit area ensures the traceability of data and the refinement of management; at the same time, the introduction of a preset power collaborative dispatching space for optimization processing can comprehensively consider the actual situation of each grid unit area, tap the maximum potential of energy storage equipment, and formulate the optimal collaborative dispatching plan; the optimal collaborative dispatching plan not only improves the flexibility and stability of grid operation, but also effectively reduces operating costs and avoids waste of resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0012] Figure 1 It is a flow chart of a dispatch optimization method for independent energy storage and power grid coordination provided by an embodiment of the present invention; Figure 2 is a hardware architecture diagram of an electronic device provided by an embodiment of the present invention; Figure 3It is a structural diagram of a dispatching optimization device for coordinated independent energy storage and power grid provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0013] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0014] Please refer to Figure 1 The embodiment of the present invention provides a dispatch optimization method for independent energy storage and power grid coordination, the method comprising: Step 100: Divide the grid coverage area into a plurality of grid unit areas, each grid unit area includes at least one power storage device, and set a unique unit area identifier for each grid unit area; Step 200: Obtain a power supply and demand state vector of each of the power grid unit areas, wherein the power supply and demand state vector includes a power load gap index and a corresponding unit area identifier; Step 300: input all power supply and demand state vectors into a preset power coordinated dispatching space for optimization processing, obtain the optimal coordinated dispatching scheme within the power grid coverage area, and perform dispatching processing based on the optimal coordinated dispatching scheme.

[0015] In this embodiment, by subdividing the grid coverage area into multiple grid unit areas and setting a unique identifier for each area, more refined management of the power system is achieved; by obtaining the power supply and demand state vector of each unit area, including the power load gap index and the corresponding unit area identifier, the difference between power demand and supply in each area can be accurately evaluated; by simultaneously inputting all power supply and demand state vectors into the preset power collaborative dispatching space for optimization processing, the optimal collaborative dispatching scheme is determined; not only the power load characteristics between different regions are taken into account, but also the potential of energy storage equipment in smoothing load fluctuations is fully explored; by optimizing the charging and discharging strategy of the energy storage equipment, the peak-to-valley difference in the operation of the power grid can be effectively reduced, and the flexibility and stability of the system can be improved; at the same time, the data-driven decision-making process helps to improve resource allocation efficiency, reduce operating costs, and ensure that the power supply quality and service level are not affected.

[0016] It should be noted that in order to better manage and optimize the allocation of power resources, the entire grid coverage area needs to be reasonably divided to form a number of relatively independent but interconnected grid unit areas; the basis for the division includes geographical factors (such as topography, urban distribution, etc.), power load characteristics (such as load density, load volatility, etc.), power network structure (such as substation distribution, transmission line direction, etc.) and energy storage equipment distribution and capacity and other factors; the goal of the division is to make the power supply and demand in each grid unit area relatively balanced, while facilitating the access and scheduling of independent energy storage systems; for example, the use of technologies such as geographic information systems (GIS) for precise division ensures the accuracy and rationality of the division.

[0017] In each grid unit area, at least one power energy storage device is configured according to the power supply and demand characteristics and energy storage requirements of the area. The division of the grid unit area takes into account the distribution factors of the energy storage device, making the access and scheduling of the independent energy storage system more convenient; the type, capacity and location of the energy storage device and other parameters should be optimized according to the actual situation to ensure that it can effectively smooth load fluctuations and improve the stability and flexibility of the power system; a unique unit area identifier is set for each grid unit area, and the unit area identifier is used to characterize the relative position coordinates of the grid unit area in the grid coverage area. By setting a unique unit area identifier for each grid unit area, each area can be easily identified and located, which facilitates the subsequent power supply and demand status monitoring and coordinated scheduling, and helps to reduce the complexity and cost of power resource management; the data format of the unit area identifier can be numbers, letters, or a combination of numbers and letters; through the unit area identifier, each grid unit area can be easily identified and located, which facilitates the subsequent power supply and demand status monitoring and coordinated scheduling.

[0018] In one embodiment of the present invention, a method for obtaining a power supply and demand state vector of each of the power grid unit areas includes: Step 210: Collect grid load data and energy storage device status data in each grid unit area; the grid load data includes the real-time power load, historical load curve, load forecast data, etc. of each grid unit area, reflecting the power demand characteristics of the area; the energy storage device status data includes the current energy storage capacity, charging and discharging power, charging and discharging efficiency, remaining capacity (SOC), health status (SOH), etc. of the energy storage device, reflecting the operating status and regulation capability of the energy storage device; by deploying smart meters and energy storage device status monitoring sensors in each grid unit area, the grid load data and energy storage device status data are collected in real time; through the Internet of Things (IoT) technology, the collected data is transmitted to the central data processing platform to ensure the real-time and integrity of the data.

[0019] Step 220: for each grid unit area, the collected grid load data and energy storage device status data are respectively input into the pre-trained power demand analysis model and energy storage device status assessment model, and the power load demand index and energy storage device supply index are output; the power load demand index is used to characterize the difference between the power load that the grid can provide for the grid unit area and the power load consumed by the grid unit area; the power load demand index output by the power demand analysis model can accurately characterize the difference between the power supply capacity of the grid and the power load of the unit area, which is helpful to clarify whether the power supply of each area is sufficient; the supply index output by the energy storage device status assessment model can reflect the regulation capacity of the energy storage device, and provide a quantitative basis for evaluating the extent to which it can support power supply; The input of the power demand analysis model is the power grid load data, including real-time power load, historical load curve and load forecast data, and the output is the power load demand index, which is used to characterize the difference between the power load that the power grid can provide to the power grid unit area and the power load consumed by the area; by analyzing the power demand characteristics of the power grid unit area, the power load changes in the future period are predicted; the difference between the power supply capacity of the power grid and the power load is calculated to generate the power load demand index. When the power load demand index is positive, it means that the power supply is sufficient, and when it is negative, it means that the power supply is insufficient; The input of the energy storage device status assessment model is the energy storage device status data, including the current energy storage capacity, charging and discharging power, charging and discharging efficiency, remaining capacity (SOC), etc.; the output is the energy storage device supply index, which is used to characterize the power regulation capability of the energy storage device in the current state; the energy storage device status assessment model is used to assess the available capacity and charging and discharging capability of the energy storage device, and determine the maximum power support it can provide; combined with the operating status of the energy storage device, the energy storage device supply index is generated; the higher the energy storage device supply index, the stronger the regulation capability of the energy storage device.

[0020] Step 230: Calculate the power load gap index of each grid unit area based on the power load demand index and energy storage equipment supply index output in step S220; the calculation formula is: Electricity load gap index = electricity load demand index − energy storage equipment supply index; The electricity load gap index is used to characterize the electricity supply and demand gap in the current state of the grid unit area: when the electricity load gap index is positive, it means that there is a power supply gap in the area and electricity needs to be allocated from the grid or other areas; when the electricity load gap index is negative, it means that the power supply in the area is sufficient and the energy storage equipment can release excess electricity to support other areas; the gap calculation helps to identify which areas need additional power support and which areas can release excess electricity, thereby achieving the optimal allocation of resources and improving the operating efficiency of the entire power system.

[0021] Step 240: Combine the calculated power load gap index with the unit area identifier of the grid unit area to create a comprehensive description of the power supply and demand state, which not only retains the spatial information but also includes the dynamic change characteristics in the time dimension; the formed power supply and demand state vector is a multidimensional array, in which each element represents the power supply and demand state of a certain grid unit area at a specific time point; In terms of data structure, arrays, structures and other methods can be used to achieve this heterogeneous combination; for example, in programming, a structure can be defined, which contains two member variables: a unit area identifier (such as a string or integer code) and an electricity load gap index (a floating point number or integer); if an array is used, the unit area identifier and the electricity load gap index can be stored in the array in a certain order, such as [unit area identifier 1, electricity load gap index 1, unit area identifier 2, electricity load gap index 2,...], which is convenient for identification and processing in the subsequent power coordinated dispatching process; The power supply and demand state vector after heterogeneous combination is convenient for identification and processing in the subsequent power coordinated dispatch process; when it is necessary to query, analyze or make dispatch decisions on the power supply and demand situation in a specific area, the corresponding power load gap index can be quickly located through the unit area identifier, so as to take corresponding measures; for example, when the power grid covers a large area, the power generation plan or the charging and discharging strategy of the energy storage equipment can be adjusted in a targeted manner according to the power supply and demand state vectors in different regions.

[0022] By collecting multiple types of data on grid load and energy storage equipment status, the regional power supply and demand situation can be fully reflected; the use of power demand analysis models and energy storage equipment status assessment models can effectively predict power load changes, evaluate energy storage regulation capabilities, and scientifically derive supply and demand indexes; the calculation of the power load gap index intuitively presents the regional power supply and demand gap, making it easier to determine the direction of power allocation; the gap index is combined with the unit area identifier to form a multidimensional array. This heterogeneous combination method not only retains spatial information but also reflects temporal dynamic changes, which facilitates query, analysis and decision-making in subsequent power coordinated dispatching. It can timely adjust power generation plans and energy storage equipment charging and discharging strategies according to the conditions of different regions, improve the overall operation efficiency of the power grid, resource utilization and ensure power supply stability.

[0023] In one embodiment of the present invention, the power supply and demand state vectors of all power grid unit areas are optimized through a preset power coordinated dispatching space to generate an optimal coordinated dispatching scheme, and the power grid and energy storage system are dispatched and executed based on the scheme. The specific implementation is as follows: Step 310, classify all the power supply and demand state vectors to obtain a set of load surplus unit areas and a set of load deficit unit areas; the classification principle is that the power supply and demand state vectors with a positive power load gap index are divided into a set of load deficit unit areas; the power supply and demand state vectors with a negative power load gap index are divided into a set of load surplus unit areas; by classifying all power supply and demand state vectors, the power grid unit areas are clearly divided into two categories: load surplus and load deficit; this method helps to accurately identify which areas have excess or insufficient power, thereby providing a clear direction for subsequent scheduling decisions; classification processing makes resource allocation more targeted, avoids waste caused by blind adjustments, and improves the operating efficiency of the entire power system.

[0024] Step 320, arrange each grid unit area in the load surplus unit area set in ascending order according to the corresponding electricity load gap index to obtain a load surplus unit area sequence; and mark the grid unit areas in the load surplus unit area sequence from the first surplus unit area to the nth surplus unit area in sequence; by arranging the load surplus unit areas in ascending order according to the electricity load gap index, preferentially dispatching areas with smaller power surpluses to ensure reasonable allocation and efficient utilization of power resources; the sorting process enables the resources in the power surplus areas to be maximized, avoids waste of resources, and reduces the additional load pressure on the power grid; through sorting, the optimization algorithm can quickly locate the best matching object, reduce calculation time, and improve the efficiency of generating scheduling plans.

[0025] Step 330: using the unit area identifier, determine whether the power load gap index corresponding to the power grid unit area closest to the first surplus unit area in the load deficit unit area set is greater than the power load gap index of the first surplus unit area, and update the load deficit unit area set and the load surplus unit area set according to the determination result; If it is greater than, the power load gap index corresponding to the grid unit area closest to the first surplus unit area is modified to the sum of the two, and the remaining power supply capacity is retained to provide support for subsequent matching; and the first surplus unit area is deleted from the load surplus unit area set, and the rankings of the remaining surplus unit areas are increased in sequence (that is, the original second surplus unit area is promoted to the first surplus unit area, the original third surplus unit area is promoted to the second surplus unit area, and so on), ensuring that the resources of the power surplus area can be maximized and avoid waste of resources; by dynamically updating the set, the number of load deficit and load surplus unit areas is gradually reduced, simplifying the complexity of the scheduling problem; If it is less than, the power load gap index corresponding to the first surplus unit area is modified to the sum of the two, and the load surplus unit area set is re-arranged in ascending order to obtain the latest load surplus unit area sequence to ensure the dynamic adaptability of the dispatching process; and the grid unit area closest to the first surplus unit area is deleted from the load deficit unit area set to accurately eliminate the power supply gap and improve the dispatching efficiency; the load surplus unit area set is re-ordered to ensure that the area with smaller power surplus is dispatched first and optimize the allocation order of power resources; If they are equal, then the grid unit area closest to the first surplus unit area is deleted from the load deficit unit area set, and the first surplus unit area is deleted from the load surplus unit area set. The remaining surplus unit areas are ranked in ascending order. By deleting the load deficit and load surplus unit areas at the same time, the scale of the scheduling problem is gradually reduced and the scheduling efficiency is improved. By judging the relationship between the electricity load gap index of the load-deficit unit area and the load-surplus unit area, accurate matching of supply and demand can be achieved to ensure the rational allocation of power resources; the set of load-deficit unit areas and the set of load-surplus unit areas are dynamically updated according to the matching results to ensure the real-time and flexibility of the scheduling process; by modifying the electricity load gap index and re-sorting it, a more balanced distribution of power resources is ensured to avoid imbalance in power supply and demand in local areas.

[0026] Step 340, repeat the judgment process in step 330 until the grid unit areas in the load surplus unit area set and / or the load deficit unit area set are cleared; through the iterative matching process, the power supply and demand gap in the grid coverage area is gradually eliminated to ensure the global balance of power supply and demand; the repeated matching process can maximize the use of power resources in the load surplus area, reduce the power gap in the load deficit area, and improve the overall operation efficiency of the grid; the iterative matching process can respond to changes in the grid load and energy storage status in real time to ensure the dynamic adaptability and robustness of the scheduling plan.

[0027] Step 350: Based on the zeroing process, at least two grid unit areas participating in the addition are respectively taken as objects of mutual collaborative scheduling, and an optimal collaborative scheduling plan within the grid coverage area is generated; based on the at least two grid unit areas participating in the addition in the zeroing process as objects of mutual collaborative scheduling, resource complementarity between different areas is achieved, a synergistic effect is formed, and the stability and reliability of the overall power system are improved; the generated optimal collaborative scheduling plan not only guides specific scheduling operations, but also provides a scientific decision-making basis for the management, helping it to better plan future development directions; corresponding early warning information is generated according to different situations (such as power load deficit, power storage load surplus or power self-sufficiency), so that relevant departments can prepare response measures in advance to further ensure the quality of power supply and service level.

[0028] More specifically, in response to the load surplus unit area set being cleared first, at least two grid unit areas participating in the addition are respectively used as mutual coordinated dispatch objects, an optimal coordinated dispatch plan within the grid coverage area is generated, and early warning information of power load deficit in the grid coverage area is generated and displayed, so that grid managers can know in advance the possible power supply shortage; it is conducive to taking measures in time, such as increasing power generation power, adjusting the discharge strategy of energy storage equipment, or carrying out power allocation between regions, so as to ensure the stable operation of the grid; In response to the load-deficient unit area set being cleared first, at least two grid unit areas participating in the addition are respectively taken as objects of mutual coordinated dispatching, an optimal coordinated dispatching scheme within the grid coverage area is generated, and early warning information of the surplus of power storage load in the grid coverage area is generated and displayed; grid managers can make reasonable plans for energy storage equipment based on this information, for example, adjust the charging strategy of energy storage equipment or consider other forms of utilization of excess electric energy, such as participating in electricity market transactions, etc., to improve the overall economic benefits of the grid; In response to the load-deficit unit area set and the load-surplus unit area set being cleared at the same time, at least two grid unit areas participating in the addition are respectively used as mutual collaborative scheduling objects, an optimal collaborative scheduling plan within the grid coverage area is generated, and information on electricity self-sufficiency in the grid coverage area is generated and displayed; this allows grid managers to intuitively understand the overall operating status of the grid, helps to enhance the transparency of grid operation, and is of great significance for daily management, planning, and response to emergencies of the grid.

[0029] By judging the order of clearing different sets, it is possible to flexibly respond to changes in the supply and demand status of the power grid and ensure the real-time and effectiveness of the dispatch plan; generating corresponding early warning information or self-sufficient information based on the clearing situation helps dispatchers to understand the power grid status in a timely manner, take targeted measures, and improve the transparency and controllability of power grid operation; this process realizes the refined management and coordinated dispatch of the supply and demand status of the power grid, which helps to optimize resource allocation and improve the overall performance and economic benefits of the power grid.

[0030] In this embodiment, accurate power allocation between load-deficit unit areas and load-surplus unit areas is achieved through classification, sorting and matching processing, and resource allocation is optimized; through iterative matching and zeroing processes, the optimal coordinated scheduling plan is quickly generated to improve scheduling efficiency; early warning information is generated based on the zeroing situation to provide real-time decision support for power grid operation and improve power supply quality and stability; the power supply and demand status of each grid unit area is comprehensively considered to achieve global power supply and demand balance in the grid coverage area and reduce operating costs.

[0031] like Figure 2 , Figure 3 As shown, the embodiment of the present invention provides a dispatch optimization device for independent energy storage and power grid coordination. The device embodiment can be implemented by software, or by hardware or a combination of software and hardware. From the hardware level, Figure 2 As shown, it is a hardware architecture diagram of an electronic device where an independent energy storage and grid-coordinated dispatch optimization device provided by an embodiment of the present invention is located, except Figure 2 In addition to the processor, memory, network interface, and non-volatile memory shown, the electronic device in the embodiment may also include other hardware, such as a forwarding chip responsible for processing messages, etc. Taking software implementation as an example, Figure 3 As shown, as a device in a logical sense, the CPU of the electronic device in which it is located reads the corresponding computer program in the non-volatile memory into the internal memory and runs it.

[0032] like Figure 3 As shown, the present invention provides a dispatching optimization device for independent energy storage and power grid coordination, comprising: A grid unit division module 400 is used to divide the grid coverage area into a plurality of grid unit areas, each grid unit area includes at least one power energy storage device, and a unique unit area identifier is set for each grid unit area; The power supply and demand state acquisition module 402 is used to acquire the power supply and demand state vector of each grid unit area, wherein the power supply and demand state vector includes a power load gap index and a corresponding unit area identifier; The coordinated dispatch optimization module 404 is used to input all power supply and demand state vectors into a preset power coordinated dispatch space for optimization processing to obtain the optimal coordinated dispatch solution within the power grid coverage area; The scheduling processing execution module 406 is used to perform actual scheduling processing based on the optimal collaborative scheduling solution.

[0033] In the embodiment of the present invention, the grid unit division module 400 can be used to execute step 100 in the above method embodiment, the power supply and demand state acquisition module 402 can be used to execute step 200 in the above method embodiment, and the collaborative scheduling optimization module and the scheduling processing execution module can be used to execute step 300 in the above method embodiment. Through the collaborative work of the above modules, the device can effectively integrate multiple independent energy storage systems into the existing power network, ensuring good collaborative operation between the two, thereby achieving the goal of optimizing resource allocation and improving economic benefits, not only improving the efficiency of power grid operation and reducing costs, but also enhancing power supply reliability and user experience.

[0034] It is understandable that the structure illustrated in the embodiment of the present invention does not constitute a specific limitation on a dispatch optimization device for an independent energy storage and a power grid. In other embodiments of the present invention, a dispatch optimization device for an independent energy storage and a power grid may include more or fewer components than shown in the figure, or combine certain components, or split certain components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0035] The information interaction, execution process and other contents between the modules in the above-mentioned device are based on the same concept as the embodiment of the method of the present invention. For the specific contents, please refer to the description in the embodiment of the method of the present invention, and no further description is given here.

[0036] An embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, a dispatch optimization method for coordinated independent energy storage and power grid in any embodiment of the present invention is implemented.

[0037] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the processor executes a method for optimizing the scheduling of independent energy storage and power grid collaboration in any embodiment of the present invention.

[0038] Specifically, a system or device equipped with a storage medium can be provided, on which software program code that implements the functions of any of the above-mentioned embodiments is stored, and a computer (or CPU or MPU) of the system or device can be enabled to read and execute the program code stored in the storage medium.

[0039] In this case, the program code itself read from the storage medium can realize the function of any one of the above-mentioned embodiments, and thus the program code and the storage medium storing the program code constitute a part of the present invention.

[0040] The storage medium embodiments for providing the program code include a floppy disk, a hard disk, a magneto-optical disk, an optical disk (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), a magnetic tape, a non-volatile memory card, and a ROM. Alternatively, the program code can be downloaded from a server computer via a communication network.

[0041] In addition, it should be clear that the functions of any of the above embodiments can be implemented not only by executing the program code read by the computer, but also by enabling an operating system operating on the computer to complete part or all of the actual operations based on instructions from the program code.

[0042] In addition, it can be understood that the program code read from the storage medium is written to a memory provided in an expansion board inserted into the computer or to a memory provided in an expansion module connected to the computer, and then based on the instructions of the program code, a CPU installed on the expansion board or expansion module is enabled to perform part or all of the actual operations, thereby realizing the functions of any of the above-mentioned embodiments.

[0043] It should be noted that, in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical factors in the process, method, article or device including the elements.

[0044] A person of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk, etc., various media that can store program codes.

[0045] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A dispatch optimization method for coordinated independent energy storage and power grid, characterized in that: The method comprises: Divide the grid coverage area into a number of grid unit areas, each grid unit area includes at least one power energy storage device, and set a unique unit area identifier for each grid unit area; Acquire a power supply and demand state vector of each of the power grid unit areas, wherein the power supply and demand state vector includes a power load gap index and a corresponding unit area identifier; All power supply and demand state vectors are input into a preset power coordinated dispatching space for optimization processing, an optimal coordinated dispatching scheme within the power grid coverage area is obtained, and dispatching processing is performed based on the optimal coordinated dispatching scheme.

2. The dispatch optimization method for independent energy storage and power grid coordination according to claim 1, characterized in that: The unit area identifier is used to represent the relative position coordinates of the power grid unit area within the power grid coverage area.

3. The dispatch optimization method for coordinated independent energy storage and power grid according to claim 2, characterized in that: Obtaining the power supply and demand state vector of each of the grid unit areas, including: Collect grid load data and energy storage equipment status data in each grid unit area; For each grid unit area, the collected grid load data and energy storage device status data are respectively input into the pre-trained power demand analysis model and energy storage device status assessment model, and the power load demand index and energy storage device supply index are output; the power load demand index is used to characterize the difference between the power load that the grid can provide for the grid unit area and the power load consumed by the grid unit area; Based on the power load demand index and the energy storage device supply index, calculate the power load gap index of the grid unit area; The electricity load gap index is heterogeneously combined with the corresponding unit area identifier to obtain the power supply and demand state vector of the power grid unit area.

4. The dispatch optimization method for independent energy storage and power grid coordination according to claim 3, characterized in that: The method for optimizing the preset power coordinated dispatch space includes: Classifying all the power supply and demand state vectors to obtain a load surplus unit area set and a load deficit unit area set; Arrange the grid unit areas in the load surplus unit area set in ascending order according to the corresponding electricity load gap index to obtain a load surplus unit area sequence; and mark the grid unit areas in the load surplus unit area sequence from the first surplus unit area to the nth surplus unit area in sequence; Using the unit area identifier, determine whether the power load gap index corresponding to the power grid unit area closest to the first surplus unit area in the load deficit unit area set is greater than the power load gap index of the first surplus unit area, and update the load deficit unit area set and the load surplus unit area set according to the determination result; Repeat the determination process until the grid unit areas in the load surplus unit area set and / or the load deficit unit area set are cleared; Based on the zeroing process, at least two grid unit areas participating in the addition are respectively taken as mutual collaborative scheduling objects to generate an optimal collaborative scheduling plan within the grid coverage area.

5. The dispatch optimization method for independent energy storage and power grid coordination according to claim 4, characterized in that: The judgment process is as follows: If it is greater, the power load gap index corresponding to the grid unit area closest to the first surplus unit area is modified to the sum of the two; and the first surplus unit area is deleted from the load surplus unit area set, and the rankings of the remaining surplus unit areas are increased in sequence; If it is less than, the power load gap index corresponding to the first surplus unit area is modified to the sum of the two, and the load surplus unit area set is re-arranged in ascending order; and the grid unit area closest to the first surplus unit area is deleted from the load deficit unit area set; If they are equal, the grid unit area closest to the first surplus unit area is deleted from the load deficit unit area set, and the first surplus unit area is deleted from the load surplus unit area set, and the remaining surplus unit areas are ranked in ascending order.

6. The dispatch optimization method for coordinated independent energy storage and power grid according to claim 5, characterized in that: In response to the load surplus unit area set being cleared first, generating and displaying warning information of power load deficit in the area covered by the power grid; In response to the load-deficit unit area set being cleared first, generating and displaying warning information of the power storage load surplus in the area covered by the power grid; In response to the simultaneous clearing of the load-deficit unit area set and the load-surplus unit area set, information on electricity self-sufficiency in the area covered by the power grid is generated and displayed.

7. The dispatch optimization method for independent energy storage and power grid coordination according to claim 3, characterized in that: The grid load data includes real-time power load, historical load curve and load forecast data; the energy storage device status data includes current energy storage capacity, charge and discharge power, charge and discharge efficiency and remaining power.

8. A dispatch optimization device for coordinated independent energy storage and power grid, characterized in that: The device comprises: A grid unit division module, used to divide the grid coverage area into a plurality of grid unit areas, each grid unit area includes at least one power energy storage device, and a unique unit area identifier is set for each grid unit area; A power supply and demand state acquisition module, used to acquire a power supply and demand state vector of each power grid unit area, wherein the power supply and demand state vector includes a power load gap index and a corresponding unit area identifier; The coordinated dispatch optimization module is used to input all power supply and demand state vectors into the preset power coordinated dispatch space for optimization processing to obtain the optimal coordinated dispatch solution within the power grid coverage area; The scheduling processing execution module is used to perform actual scheduling processing based on the optimal collaborative scheduling solution.

9. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed in a computer, the computer is caused to execute the method according to any one of claims 1 to 7.

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