Industrial park user side energy storage configuration method and device

Abstract

The invention discloses an industrial park user side energy storage configuration method and device which are used for achieving cooperative configuration of energy storage impact load suppression and peak-valley difference arbitrage and achieving optimal economical efficiency. The method comprises the following steps: taking the minimum annual cost of an industrial user as an optimization target, taking an electric quantity configuration interval and a power configuration interval of energy storage configuration as constraint conditions, and adopting the annual investment cost of energy storage, the annual operation cost of the industrial user and the annual operation and maintenance cost of the energy storage to construct an upper-layer planning model; the minimum annual operating cost of an industrial user is used as an optimization target, and energy storage charging and discharging power limitation, energy storage charge state constraint, power distribution network power flow constraint and voltage fluctuation constraint are used as constraint conditions. Constructing a lower-layer scheduling model by adopting the annual electricity purchase cost of the industrial users, the energy storage peak-valley difference benefit income, the energy storage battery degradation cost and the electric quantity management cost reduction income; and solving the upper-layer planning model and the lower-layer scheduling model to obtain the optimal electric quantity and the optimal power.

Description

Technical Field

[0001] The present invention relates to the field of energy storage technology, and in particular to a method and device for configuring user-side energy storage in an industrial park. Background Art

[0002] As a vital component of the modern economy, industrial parks host a significant amount of production activities and energy consumption. With the integration of a high proportion of renewable energy and changes in production methods, the power demand patterns in industrial parks are becoming increasingly complex and diverse. Industrial parks are experiencing an increasing number of high-power, frequently started and stopped, and rapidly fluctuating surge loads. These surge loads can cause large voltage fluctuations in the distribution network, potentially exceeding the lower voltage limit, severely impacting the normal operation of precision equipment within the industrial park. Therefore, industrial users with surge loads must take appropriate measures to address the voltage fluctuations caused by these surge loads. Otherwise, the power grid will penalize users with surge loads, such as charging power adjustment fees.

[0003] Currently, industrial users typically install reactive power compensation devices to adjust the reactive power distribution of distribution networks to maintain system voltage stability. However, the core function of reactive power compensation devices is to regulate reactive power, stabilizing voltage by altering the distribution of inductive or capacitive reactive power in the grid. When surge loads cause a significant gap in active power in the grid, reactive power compensation cannot directly compensate for this missing energy. Consequently, the grid voltage may still drop significantly due to insufficient active power, impacting the power quality of the distribution network. Furthermore, surge loads often occur instantaneously, requiring compensation measures to respond quickly. The slow response speed makes it difficult for reactive power compensation devices to keep pace with rapid load changes.

[0004] Furthermore, industrial parks implement a two-part electricity pricing system. This means that users pay a basic electricity fee in addition to the kilowatt-hour fee. This fee is primarily determined by the maximum power consumption of the transformer. For high-load industrial users with impact loads, the impact of impact loads not only affects the power quality of the distribution network, but also significantly increases capacity management costs for users with high power consumption. Furthermore, due to their high power consumption and significant peak-to-valley variations, industrial users have a need to exploit the peak-to-valley arbitrage to reduce their electricity costs.

[0005] Industrial users within industrial parks with impact loads need to mitigate the impact of these impacts on the distribution network while also reducing electricity costs through energy storage. Conventional energy storage configurations typically require one to two times the power of the energy storage. To ensure that energy storage can mitigate impact loads, the power of the energy storage must be higher, resulting in a higher power consumption and making it unsuitable for this scenario. Summary of the Invention

[0006] The present invention provides a user-side energy storage configuration method and device for an industrial park, which is used to solve the technical problem of how to balance the high power demand of impact loads and the high power demand of peak-valley arbitrage, realize the coordinated configuration of energy storage to suppress impact loads and peak-valley arbitrage, and achieve optimal economic efficiency.

[0007] The present invention provides a method for configuring user-side energy storage in an industrial park, comprising:

[0008] Taking the minimization of industrial user annual costs as the optimization goal, and the energy storage configuration's energy capacity and power configuration ranges as constraints, the upper-level planning model is constructed using the annual energy storage investment cost, the industrial user's annual operating expenses, and the energy storage's annual operation and maintenance costs.

[0009] Taking the minimization of industrial users' annual operating expenses as the optimization goal, and taking energy storage charging and discharging power limits, energy storage charge state constraints, distribution network flow constraints, and voltage fluctuation constraints as constraints, the lower-level scheduling model is constructed using the industrial users' annual electricity purchase costs, energy storage peak-valley profit margins, energy storage battery degradation costs, and electricity management fee reduction benefits.

[0010] Solve the upper-level planning model and the lower-level scheduling model to obtain optimal electricity and optimal power.

[0011] Optionally, the upper-level planning model is:

[0012]

[0013] in, Annual fee for industrial users; is the annual investment cost of energy storage; Annual operating expenses for industrial users; The annual operation and maintenance cost of energy storage.

[0014] Optionally, the annual energy storage investment cost calculation formula is:

[0015]

[0016] in, The installation cost per unit of energy storage; is the unit power installation cost of energy storage; is the discount rate; For the entire life cycle of energy storage; is the energy storage power; is the energy storage capacity.

[0017] Optionally, the calculation formula for the annual operation and maintenance cost of the energy storage is:

[0018]

[0019] in, The operation and maintenance cost of the energy storage unit charging and discharging power; is the operation and maintenance cost per unit of energy storage; y is the year of energy storage operation; The power allocated for energy storage; The amount of electricity configured for energy storage.

[0020] Optionally, the lower-layer scheduling model is:

[0021]

[0022] in, Annual operating expenses for industrial users; The annual electricity purchase cost for industrial users; To earn arbitrage profits from energy storage peak-valley differences; Degradation cost of energy storage batteries; Cut revenue for electricity management costs.

[0023] Optionally, the calculation formula for the annual electricity purchase cost of the industrial user is:

[0024]

[0025] in, is the typical number of days in a year; is the time-of-use electricity price at time t; is the total load power of industrial users; is the discharge power of the energy storage system; The unit time interval.

[0026] Optionally, the energy storage peak-valley arbitrage profit calculation formula is:

[0027]

[0028] Where i is the year of energy storage operation; is the charging power of the energy storage system, is the inflation rate.

[0029] Optionally, the calculation formula for the energy storage battery degradation cost is:

[0030]

[0031] in, The unit cost of battery installation; The degradation factor is a quantitative indicator of the degree to which the life of the energy storage battery is reduced due to the charging and discharging process of the energy storage; , β, are the parameters calculated using the curve fitting method; K is the parameter of the energy storage battery, which is 3.446; and is the state of charge of the energy storage during period t and its change.

[0032] Optionally, the calculation formula for the power management fee reduction benefit is:

[0033]

[0034] in, is the number of operating months in a year; The maximum load demand value before the user installs energy storage; is the basic electricity price; The maximum load demand value after the user installs energy storage.

[0035] The present invention also provides an industrial park user-side energy storage configuration device, comprising:

[0036] The upper-level planning model construction module is used to minimize the annual cost of industrial users as the optimization goal, with the energy storage configuration's energy capacity and power configuration ranges as constraints, and uses the annual energy storage investment cost, the annual operating expenses of industrial users, and the annual operation and maintenance costs of energy storage to construct the upper-level planning model;

[0037] The lower-level dispatch model construction module is used to minimize the annual operating expenses of industrial users as the optimization goal, with energy storage charging and discharging power limits, energy storage charge state constraints, distribution network flow constraints, and voltage fluctuation constraints as constraints. The lower-level dispatch model is constructed using the annual electricity purchase cost of industrial users, the peak-valley profit of energy storage, the degradation cost of energy storage batteries, and the reduction in electricity management expenses.

[0038] The solution module is used to solve the upper-level planning model and the lower-level scheduling model to obtain the optimal amount of electricity and the optimal power.

[0039] From the above technical solutions, it can be seen that the present invention has the following advantages: the present invention takes the minimum annual cost of industrial users as the optimization goal, takes the energy storage configuration power configuration interval and power configuration interval as the constraint conditions, and uses the annual investment cost of energy storage, the annual operating cost of industrial users and the annual operation and maintenance cost of energy storage to construct the upper-level planning model; takes the minimum annual operating cost of industrial users as the optimization goal, takes the energy storage charging and discharging power limit, energy storage charge state constraint, distribution network flow constraint and voltage fluctuation constraint as the constraint conditions, and uses the annual electricity purchase cost of industrial users, energy storage peak-valley difference profit, energy storage battery degradation cost and electricity management fee reduction profit to construct the lower-level scheduling model; solves the upper-level planning model and the lower-level scheduling model to obtain the optimal electricity and optimal power. It balances the high power demand of impact load and the high electricity demand of peak-valley difference arbitrage, thereby realizing the coordinated configuration of energy storage to suppress impact load and peak-valley difference arbitrage, and achieving optimal economic efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0041] Figure 1 A flowchart of a method for configuring user-side energy storage in an industrial park according to an embodiment of the present invention;

[0042] Figure 2 This is the load curve of a user in an industrial park with impact load;

[0043] Figure 3 This is a structural block diagram of a user-side energy storage configuration device for an industrial park provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0044] The embodiments of the present invention provide a method and device for configuring user-side energy storage in an industrial park, which are used to solve the technical problem of how to balance the high power demand of impact loads and the high electricity demand of peak-valley arbitrage, realize the coordinated configuration of energy storage to suppress impact loads and peak-valley arbitrage, and achieve optimal economic efficiency.

[0045] In order to make the purpose, features, and advantages of the present invention more obvious and easy to understand, 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 embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0046] See also Figure 1 , Figure 1 A flowchart of the steps of a method for configuring user-side energy storage in an industrial park provided by an embodiment of the present invention.

[0047] The present invention provides a method for configuring user-side energy storage in an industrial park, which may include the following steps:

[0048] Step 101: Taking minimizing the annual cost for industrial users as the optimization objective, using the energy storage configuration's energy capacity and power configuration ranges as constraints, and constructing an upper-level planning model using the annual investment cost of energy storage, the annual operating cost for industrial users, and the annual operation and maintenance cost of energy storage;

[0049] In this embodiment of the present invention, the overall concept of energy storage capacity allocation is to first determine the minimum energy storage capacity required to buffer shock loads, using this as a foundational guarantee. Then, based on the economic benefits of peak-valley arbitrage, the energy storage capacity is gradually expanded for peak-valley arbitrage. Because suppressing shock loads requires a higher output power of the energy storage, the energy storage power is configured based on the minimum power required to suppress the shock loads.

[0050] Therefore, the present invention is implemented by establishing a planning model for user-side energy storage configuration. First, the optimization goal is to minimize the annual cost for industrial users, and the capacity range and power range of the energy storage configuration are used as constraints. The upper-level planning model is constructed using the annual investment cost of energy storage, the annual operating cost of industrial users, and the annual operation and maintenance cost of energy storage.

[0051] The objective function of the upper-level planning model is:

[0052]

[0053] in, Annual fee for industrial users; is the annual investment cost of energy storage; Annual operating expenses for industrial users; The annual operation and maintenance cost of energy storage.

[0054] The formula for calculating the annual investment cost of energy storage is:

[0055]

[0056] in, The installation cost per unit of energy storage; is the unit power installation cost of energy storage; is the discount rate; For the entire life cycle of energy storage; is the energy storage power; is the energy storage capacity.

[0057] The calculation formula for the annual operation and maintenance cost of energy storage is:

[0058]

[0059] in, The operation and maintenance cost of the energy storage unit charging and discharging power; is the operation and maintenance cost per unit of energy storage; y is the year of energy storage operation; Allocate power for energy storage; Allocate power for energy storage.

[0060] Considering the impact load characteristics, it is necessary to constrain the capacity and power of the energy storage configuration.

[0061] Based on the load curves of large users in the park and the role of energy storage in suppressing impact loads and peak-valley arbitrage, the energy storage configuration's electricity configuration range (closed range) and power configuration range (closed range) can be obtained. Figure 2 The red part is the power curve of the impact load, and the blue part is the power curve of other loads of the industrial user. Energy storage can participate in peak-valley arbitrage to reduce the user's electricity purchase cost in the middle of the two impact loads. t1 and t2, t3 and t5 are respectively Figure 2 The time when the two impact loads occur and end, t4 is the time when the power of the impact load reaches the maximum, P s,max It is the maximum load demand value before the user installs energy storage, that is, the maximum power of the user load including impact load.

[0062] To suppress shock load demand, the energy storage configuration should be greater than the power consumed by the longest and highest peak shock load that occurs in a single day, that is:

[0063]

[0064] Among them, S is the energy storage configuration capacity; S 1,max The power consumed by the impact load with the longest impact time and the highest peak value in a day; P load It is the power of the impact load of industrial users; 1 / 60 is the conversion ratio between minutes and hours.

[0065] To meet the peak-valley arbitrage demand, energy storage should be smaller than the difference between the energy released by peak electricity prices and the energy absorbed by valley electricity prices, that is:

[0066]

[0067] Energy storage is discharged when a shock load occurs to mitigate the impact of the shock load. On the one hand, after the shock load ends, the energy storage is in a charging state. In order to ensure that the energy storage has enough power to cope with the shock load, the power of the energy storage needs to be limited; on the other hand, the power of the energy storage configuration should not be greater than the maximum power of the shock load. That is:

[0068]

[0069] Where P is the energy storage configuration power, The maximum load demand value after the user installs energy storage.

[0070] Step 102: Taking the minimization of the annual operating expenses of industrial users as the optimization objective, and using energy storage charging and discharging power limits, energy storage state of charge constraints, distribution network flow constraints, and voltage fluctuation constraints as constraints, a lower-level scheduling model is constructed using the annual electricity purchase cost of industrial users, energy storage peak-valley profit, energy storage battery degradation costs, and power management fee reduction benefits.

[0071] In the embodiment of the present invention, the impact load is characterized by frequent action, which requires frequent charging and discharging of the energy storage device. Energy storage has a decay effect, that is, the charging and discharging process will reduce the life of the energy storage battery, and the cost of charging and discharging losses during the energy storage operation needs to be considered. In order to improve the utilization rate of the energy storage system and reduce the user's electricity costs, energy storage is used for peak-valley arbitrage during non-impact load periods, that is, energy storage is discharged when electricity prices are high and energy storage is charged when electricity prices are low. For the lower-level scheduling model, the optimization goal is to minimize the annual operating costs of industrial users, that is:

[0072]

[0073] in, Annual operating expenses for industrial users; The annual electricity purchase cost for industrial users; To earn arbitrage profits from energy storage peak-valley differences; Degradation cost of energy storage batteries; Cut revenue for electricity management costs.

[0074] In order to achieve different sampling periods for different working modes of energy storage throughout the entire dispatch cycle, the entire day is divided into two parts: the time when impact load occurs and the time when non-impact load occurs. During the time when impact load occurs, that is, T1, the sampling interval is set to 1s; during the time when non-impact load occurs, that is, T2, the sampling interval is set to 15 minutes, as shown below:

[0075]

[0076] The annual electricity purchase cost calculation formula for industrial users is:

[0077]

[0078] in, is the typical number of days in a year; is the time-of-use electricity price at time t; is the total load power of industrial users; is the discharge power of the energy storage system; The unit time interval.

[0079] The formula for calculating the energy storage peak-valley arbitrage profit is:

[0080]

[0081] Where i is the year of energy storage operation; is the charging power of the energy storage system, Inflation rate

[0082] The calculation formula for the degradation cost of energy storage batteries is:

[0083]

[0084] in, The unit cost of battery installation; The degradation factor is a quantitative indicator of the degree to which the life of the energy storage battery is reduced due to the charging and discharging process of the energy storage; , β, are the parameters calculated using the curve fitting method; K is the parameter of the energy storage battery, which is 3.446; and is the state of charge of the energy storage during period t and its change.

[0085] The calculation formula for the benefits of reducing electricity management costs is:

[0086]

[0087] in, is the number of operating months in a year; The maximum load demand value before the user installs energy storage, that is, the maximum power of the user load including impact load; is the basic electricity price; The maximum load demand value after the user installs energy storage.

[0088] The constraints of the lower-level scheduling model include energy storage charging and discharging power limits, energy storage state of charge constraints, distribution network flow constraints, and voltage fluctuation constraints.

[0089] The energy storage charging and discharging power limits are:

[0090]

[0091] in, 、P c,t are the discharge power and charging power of the energy storage device during period t; B dc,t 、 Bc,t are 0 and 1 variables respectively.

[0092] The energy storage state of charge constraint is:

[0093]

[0094] in, is the state of charge of the energy storage at time t-1; 、 are the energy conversion efficiency during energy storage charging and discharging, respectively.

[0095] Energy storage can be used for peak-valley arbitrage during the intervals between impact loads. To ensure that the energy storage has sufficient power to suppress the impact load, the charge state of the energy storage at the time of the impact load needs to be constrained, namely:

[0096]

[0097] in: is the moment when the impact load occurs.

[0098] To ensure the sustainability of energy storage operations, the energy storage must return to its initial capacity after one day of operation, namely:

[0099]

[0100] in, 、 They are the charge states of the energy storage at the beginning and end of each day respectively.

[0101] In order to ensure that the system fully utilizes energy storage without negatively impacting the operational stability and reliability of the power grid, the distribution network flow constraints also need to be considered. The formula is:

[0102]

[0103] in, 、 are the active power and reactive power injected into node i during period t, respectively; 、 、 are the conductance, susceptance and phase difference between nodes i and j respectively; 、 are the voltage amplitudes of nodes i and j at time period t respectively; and are the maximum and minimum voltage values ​​allowed for node i respectively; is the transmission power of branch ij during period t; is the transmission power limit of branch ij.

[0104] The voltage fluctuation constraint is:

[0105]

[0106] in, is the upper limit of voltage fluctuation rate; is the reference voltage.

[0107] Step 103: Solve the upper-level planning model and the lower-level scheduling model to obtain the optimal amount of electricity and the optimal power.

[0108] After constructing the two-layer planning model (including the upper-layer planning model and the lower-layer scheduling model) and the corresponding constraints, the two-layer planning model can be solved to obtain the optimal electricity and optimal power.

[0109] It should be noted that any conventional optimization method in the art may be used to solve the two-layer programming model, and the embodiment of the present invention does not impose any specific limitation on this.

[0110] The present invention uses the minimum annual cost for industrial users as the optimization goal, the energy storage configuration power configuration interval and power configuration interval as constraints, and uses the annual investment cost of energy storage, the annual operating cost of industrial users, and the annual operation and maintenance cost of energy storage to construct an upper-level planning model; uses the minimum annual operating cost for industrial users as the optimization goal, uses the energy storage charge and discharge power limit, energy storage charge state constraint, distribution network flow constraint, and voltage fluctuation constraint as constraints, and uses the annual electricity purchase cost of industrial users, energy storage peak-valley difference profit, energy storage battery degradation cost, and energy management fee reduction profit to construct a lower-level scheduling model; solves the upper-level planning model and the lower-level scheduling model to obtain the optimal power and optimal power. This balances the high power demand of impact loads and the high power demand of peak-valley difference arbitrage, thereby achieving a coordinated configuration of energy storage to suppress impact loads and peak-valley difference arbitrage, achieving optimal economic efficiency.

[0111] See also Figure 3 , Figure 3 This is a structural block diagram of a user-side energy storage configuration device for an industrial park provided by an embodiment of the present invention.

[0112] An embodiment of the present invention provides a user-side energy storage configuration device for an industrial park, comprising:

[0113] Upper-level planning model construction module 301 is used to construct an upper-level planning model with the annual cost of energy storage being minimized, the annual cost of industrial users being minimized, and the annual energy storage operation and maintenance cost being constrained by the energy storage configuration's energy capacity and power configuration ranges.

[0114] Lower-level dispatch model construction module 302 is used to optimize the annual operating expenses of industrial users by minimizing them, using energy storage charging and discharging power limits, energy storage state of charge constraints, distribution network power flow constraints, and voltage fluctuation constraints as constraints, and using the annual electricity purchase cost of industrial users, energy storage peak-valley profit margins, energy storage battery degradation costs, and electricity management fee reduction benefits to construct the lower-level dispatch model;

[0115] The solution module 303 is used to solve the upper-level planning model and the lower-level scheduling model to obtain the optimal amount of electricity and the optimal power.

[0116] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0117] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0118] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, apparatus, or computer program products. Thus, embodiments of the present invention may take the form of a fully hardware embodiment, a fully software embodiment, or an embodiment combining software and hardware. Furthermore, embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0119] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0120] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0121] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 a process or multiple processes and / or boxes Figure 1The steps for the function specified in one or more boxes.

[0122] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they become aware of the basic creative concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0123] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0124] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or terminal device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or terminal device that includes the element.

[0125] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features thereof can be replaced by equivalents. 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 method for configuring user-side energy storage in an industrial park, characterized in that: include: Taking the minimization of industrial user annual costs as the optimization goal, and the energy storage configuration's energy capacity and power configuration ranges as constraints, the upper-level planning model is constructed using the annual energy storage investment cost, the industrial user's annual operating expenses, and the energy storage's annual operation and maintenance costs. Taking the minimization of industrial users' annual operating expenses as the optimization goal, and taking energy storage charging and discharging power limits, energy storage charge state constraints, distribution network flow constraints, and voltage fluctuation constraints as constraints, the lower-level scheduling model is constructed using the industrial users' annual electricity purchase costs, energy storage peak-valley profit margins, energy storage battery degradation costs, and electricity management fee reduction benefits. Solve the upper-level planning model and the lower-level scheduling model to obtain optimal electricity and optimal power.

2. The method according to claim 1, characterized in that The upper-level planning model is: in, Annual fee for industrial users; is the annual investment cost of energy storage; Annual operating expenses for industrial users; The annual operation and maintenance cost of energy storage.

3. The method according to claim 2, characterized in that The formula for calculating the annual investment cost of energy storage is: in, The installation cost per unit of energy storage; is the unit power installation cost of energy storage; is the discount rate; For the entire life cycle of energy storage; is the energy storage power; is the energy storage capacity.

4. The method according to claim 2, characterized in that The calculation formula for the annual operation and maintenance cost of energy storage is: in, The operation and maintenance cost of the energy storage unit charging and discharging power; is the operation and maintenance cost per unit of energy storage; y is the year of energy storage operation; The power allocated for energy storage; The amount of electricity configured for energy storage.

5. The method according to claim 1, characterized in that The lower-layer scheduling model is: in, Annual operating expenses for industrial users; The annual electricity purchase cost for industrial users; To earn arbitrage profits from energy storage peak-valley differences; Degradation cost of energy storage batteries; Cut revenue for electricity management costs.

6. The method according to claim 5, characterized in that The calculation formula for the annual electricity purchase cost of industrial users is: in, is the typical number of days in a year; is the time-of-use electricity price at time t; is the total load power of industrial users; is the discharge power of the energy storage system; The unit time interval.

7. The method according to claim 5, characterized in that The formula for calculating the energy storage peak-valley arbitrage profit is: Where i is the year of energy storage operation; is the charging power of the energy storage system, is the inflation rate.

8. The method according to claim 5, characterized in that The calculation formula for the energy storage battery degradation cost is: in, The unit cost of battery installation; The degradation factor is a quantitative indicator of the degree to which the life of the energy storage battery is reduced due to the charging and discharging process of the energy storage; , β, are the parameters calculated using the curve fitting method; K is the parameter of the energy storage battery, which is 3.446; and is the state of charge of the energy storage during period t and its change.

9. The method according to claim 5, characterized in that The calculation formula for the power management fee reduction benefit is: in, is the number of operating months in a year; The maximum load demand value before the user installs energy storage, that is, the maximum power of the user load including impact load; is the basic electricity price; The maximum load demand value after the user installs energy storage.

10. An industrial park user-side energy storage configuration device, characterized in that: include: The upper-level planning model construction module is used to minimize the annual cost of industrial users as the optimization goal, with the energy storage configuration's energy capacity and power configuration ranges as constraints, and uses the annual energy storage investment cost, the annual operating expenses of industrial users, and the annual operation and maintenance costs of energy storage to construct the upper-level planning model; The lower-level dispatch model construction module is used to minimize the annual operating expenses of industrial users as the optimization goal, with energy storage charging and discharging power limits, energy storage charge state constraints, distribution network flow constraints, and voltage fluctuation constraints as constraints. The lower-level dispatch model is constructed using the annual electricity purchase cost of industrial users, the peak-valley profit of energy storage, the degradation cost of energy storage batteries, and the reduction in electricity management expenses. The solution module is used to solve the upper-level planning model and the lower-level scheduling model to obtain the optimal amount of electricity and the optimal power.

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