Multi-package energy storage game robust optimization configuration method

Abstract

The invention provides a multi-package energy storage game robust optimization configuration method, and relates to the technical field of power system optimization configuration and power energy storage, in the method, three shared energy storage service packages provided for a second user to select by a first user are constructed. Establishing an upper-layer shared energy storage model by taking the first user income maximization as a target, and establishing a lower-layer deterministic model corresponding to each second user by taking each second user income maximization as a target; the uncertainty of new energy output is considered, a first user is used as a dominator, a plurality of second users are used as followers, and a multi-package energy storage game robust optimization configuration model is established. And solving the multi-package energy storage game robust optimization configuration model, and determining an optimization configuration strategy for the first user and the target second user. The invention aims to improve the energy storage service demand quantity of the target second user, reduce the total internet surfing deviation quantity of the target second user, improve the consumption level of new energy and improve the income of the target second user.

Description

Technical Field

[0001] The present invention relates to the field of power system optimization configuration and power energy storage technology, and in particular to a multi-package energy storage game robust optimization configuration method. Background Art

[0002] In the rapid construction of modern power grids, energy storage can effectively improve the grid-connected consumption rate of new energy, so it is expected to become a strong support for the stable operation of the power system. However, shared energy storage is still facing problems such as inflexible trading mode and lack of basis for energy storage configuration. Therefore, conducting research on the optimal configuration of shared energy storage has an important impact on realizing the grid-connected consumption of new energy, optimizing the economic efficiency of grid operation, and ensuring the rationality of energy storage configuration.

[0003] At present, the research on the optimal configuration of shared energy storage mainly focuses on the robust optimization configuration of multi-package energy storage game. The robust optimization configuration of multi-package energy storage game is a method that introduces the concept of package and adopts master-slave game and distributed robust optimization methods in the new energy shared energy storage system to achieve the optimal configuration of energy storage resources and maximize economic benefits. The advantage of the robust optimization configuration of multi-package energy storage game is that it can well describe the interaction and optimal strategy between trading entities. In addition, as a new type of energy storage system based on the sharing economy, shared energy storage has a certain role in improving the economy and feasibility of the power grid.

[0004] However, the multi-package energy storage game robust optimization configuration method is difficult to achieve its economic benefits when resources are excessively idle. Summary of the invention

[0005] The present invention provides a multi-package energy storage game robust optimization configuration method, which effectively reduces the problem of excessively high costs caused by self-built energy storage facilities in new energy stations, while increasing the demand for energy storage services in new energy stations, reducing the total grid-connected deviation of new energy stations, improving the level of new energy consumption, and increasing the profits of new energy stations.

[0006] The technical solution of the present invention to solve the above technical problems is as follows:

[0007] In a first aspect, the present invention provides a multi-package energy storage game robust optimization configuration method, in which:

[0008] Construct a shared energy storage service package provided by a first user to at least one second user. Wherein, when the first user provides shared energy storage services to the target second user, the first user charges the target second user a service fee based on the shared energy storage service package; the target second user is any second user among the at least one second user. The shared energy storage service package includes a first package, a second package and a third package. The first package is determined based on the charge and discharge power purchased by the target second user. The second package is determined based on the shared energy storage capacity leased by the target second user. The third package is determined based on the time when the target second user leases the shared energy storage.

[0009] With the goal of maximizing the first user's profit, an upper-level shared energy storage model corresponding to the first user is established based on the energy storage investment, construction and operation constraints, energy storage power constraints, energy storage capacity constraints and energy storage supply and demand balance constraints corresponding to the first user.

[0010] With the goal of maximizing the benefit of the target second user, a lower-level deterministic model corresponding to the target second user is established based on the investment, construction and operation constraints, energy storage capacity constraints, energy storage power constraints and actual output constraints corresponding to the target second user.

[0011] The uncertainty parameters of renewable energy output are obtained, and a multi-package energy storage game robust optimization configuration model is established based on the shared energy storage service package, the upper-layer shared energy storage model, the lower-layer deterministic model corresponding to the target second user, and the uncertainty parameters of renewable energy output.

[0012] Based on the multi-package energy storage game robust optimization configuration model, the optimization configuration strategy for the first user and the target second user is determined. The optimization configuration strategy includes the pricing strategy and energy storage configuration strategy of the first user, as well as the package selection strategy, self-built energy storage strategy and energy storage service demand strategy of the second user.

[0013] Based on the above technical solution, the present invention can also be improved as follows.

[0014] Furthermore, the first user provides a shared energy storage service to the target second user based on the shared energy storage system, wherein the shared energy storage capacity includes the shared energy storage energy capacity and the shared energy storage power capacity.

[0015] The service fee for the first package is:

[0016]

[0017] in, represents the service fee corresponding to the first package; d represents a typical day; O d It represents the sum of the days represented by the typical day d; represents the unit power cost of charging the shared energy storage system at time t on a typical day d when the target second user selects the first package; represents the unit power cost of discharging to the shared energy storage system at time t on a typical day d when the target second user selects the first package; represents the power charged to the shared energy storage system at time t on a typical day d when the target second user selects the first package; represents the power discharged to the shared energy storage system at time t on a typical day d when the target second user selects the first package; L is a constant real number; represents the charging power service demand of the target second user to the shared energy storage system at time t on a typical day d; represents the target second user's discharge power service demand to the shared energy storage system at time t on a typical day d; when the target second user selects the first package, The value of is 1, and The value of is 0; when the target second user selects the second package, The value of is 1, and The value of is 0; when the second target user chooses the third package, The value of is 1, and The values ​​of are all 0;

[0018] The service fee for the second package is:

[0019]

[0020]

[0021] in, Indicates the service fee corresponding to the second package; represents the unit energy capacity cost of leasing the shared energy storage system at time t on a typical day d when the target second user selects the second package; represents the unit power capacity cost of leasing the shared energy storage system at time t on a typical day d when the target second user selects the second package; represents the shared energy storage capacity rented on a typical day d when the target second user selects the second package; Indicates the shared energy storage power capacity rented on a typical day when the target second user selects the second package; represents the power charged to the shared energy storage system at time t on a typical day d when the target second user selects the second package; represents the power discharged to the shared energy storage system at time t on a typical day d when the target second user selects the second package; η C represents the maximum charging efficiency of the shared energy storage system; η D represents the maximum discharge efficiency of the shared energy storage system; Indicates the shared energy storage power capacity rented at the preset initial time on a typical day d when the target second user selects the second package; Indicates the shared energy storage power capacity rented at the preset end time of a typical day d when the target second user selects the second package.

[0022] The service fee for the third package is:

[0023]

[0024] in, Indicates the service fee corresponding to the third package; It indicates the unit time cost of leasing shared energy storage on a typical day when the target second user chooses the third package; when the target second user chooses the third package, The value of is 1; when the target second user selects the first package or the second package, The value of is 0; represents the power charged to the shared energy storage system at time t on a typical day d when the target second user selects the third package; represents the power discharged to the shared energy storage system at time t on a typical day d when the target second user selects the third package; represents the time during which the target second user continuously uses the shared energy storage before and at time t on a typical day d; Indicates the shortest continuous usage time of the energy storage service when the target second user selects the third package.

[0025] Furthermore, an initial upper-layer shared energy storage model corresponding to the first user is established. Based on the energy storage investment and operation constraints, energy storage power constraints, energy storage capacity constraints, and energy storage supply and demand balance constraints corresponding to the first user, the initial upper-layer shared energy storage model is constrained to obtain an upper-layer shared energy storage model.

[0026] Furthermore, the initial upper-level shared energy storage model includes:

[0027] F ses =F ses,new +F ses,grid -F ses,inv -F ses,pun ;

[0028]

[0029] Among them, F ses represents the total revenue of the first user; F ses,new F represents the service fee charged by the first user for providing shared energy storage service to the target second user; ses,grid represents the revenue of the first user from selling electricity to the target second user; F ses,inv represents the investment and construction cost of the shared energy storage system by the first user; Fses,pun represents the over-limit penalty cost of the shared energy storage system; θ sell represents the unit power cost of the first user selling electricity to the target second user; θ buy Indicates the unit power cost of the first user's electricity purchase; represents the power sold by the first user to the target second user at time t on a typical day d; represents the power purchased by the first user at time t on a typical day d; s represents the shared energy storage system; represents the annual construction cost of the shared energy storage system by the first user; if the shared energy storage system is already constructed, then c s The value of is 1; if the shared energy storage system is not yet built, then c s The value of θ is 0; pun represents the unit penalty cost when the power of the shared energy storage system exceeds the limit; represents the charging power penalty term of the shared energy storage system at time t on a typical day d; represents the discharge power penalty term of the shared energy storage system at time t on a typical day d.

[0030] Furthermore, the energy storage investment and operation constraints corresponding to the first user include:

[0031]

[0032] Among them, if the shared energy storage system is in a charging state at time t on a typical day d, then The value of is 1, The value of is 0; if the shared energy storage system is in a discharging state at time t on a typical day d, then The value of is 0, The value of is 1;

[0033] The energy storage power constraints corresponding to the first user include:

[0034]

[0035] in, represents the total charging power of the shared energy storage system at time t on a typical day d; represents the total discharge power of the shared energy storage system at time t on a typical day d; represents the charging power of the shared energy storage system to the target second user at time t on a typical day d; represents the discharge power of the shared energy storage system to the target second user at time t on a typical day d; Indicates the minimum value of the charging power of the shared energy storage system; Indicates the maximum value of the charging power of the shared energy storage system; Indicates the minimum value of the discharge power of the shared energy storage system; Indicates the maximum discharge power of the shared energy storage system.

[0036] The energy storage capacity constraints corresponding to the first user include:

[0037]

[0038]

[0039] Among them, E sdt represents the total shared energy storage capacity of the shared energy storage system at time t on a typical day d; represents the remaining shared energy storage capacity of the shared energy storage system at time t on a typical day d; represents the shared energy storage capacity leased by the target second user from the first user at time t on a typical day d based on the second package; represents the shared energy storage capacity that the target second user leases from the first user based on the second package at the preset initial time on a typical day d; represents the shared energy storage capacity that the target second user leases from the first user based on the second package at the preset end time of the typical day d; represents the total shared energy storage capacity of the shared energy storage system leased through the second package on a typical day d; Indicates the maximum value of the shared energy storage capacity of the shared energy storage system; represents the minimum value of the shared energy storage capacity of the shared energy storage system; represents the remaining shared energy storage capacity of the shared energy storage system at the preset initial time on a typical day d; represents the remaining shared energy storage capacity of the shared energy storage system at the preset end time of a typical day d;

[0040] The energy storage supply and demand balance constraints corresponding to the first user include:

[0041]

[0042] in, represents the charging power constant value reported to the shared energy storage system at time t on a typical day d when the target second user selects the first package; represents the discharge power constant value reported to the shared energy storage system at time t on a typical day d when the target second user selects the first package;

[0043] represents the charging power constant value reported to the shared energy storage system at time t on a typical day d when the target second user selects the second package; represents the discharge power constant value reported to the shared energy storage system at time t on a typical day d when the target second user selects the second package; represents the charging power constant value reported to the shared energy storage system at time t on a typical day d when the target second user selects the third package; represents the discharge power constant value reported to the shared energy storage system at time t on a typical day d when the target second user selects the third package; It represents the constant value of the shared energy storage capacity leased from the first user on a typical day d when the target second user selects the second package.

[0044] Furthermore, an initial lower-level deterministic model corresponding to the target second user is established. Based on the investment and operation constraints, energy storage capacity constraints, energy storage power constraints, and actual output constraints corresponding to the target second user, the initial lower-level deterministic model is constrained to obtain the lower-level deterministic model corresponding to the target second user.

[0045] Furthermore, the initial lower-layer deterministic model corresponding to the target second user includes:

[0046]

[0047] α ndt ,β ndt ≥0;

[0048]

[0049] in, represents the total revenue of the target second user; Indicates the Internet access income of the target second user; represents the Internet access deviation penalty cost paid by the target second user; Indicates the investment and construction cost of the target second user's self-built energy storage; represents the service fee paid by the target second user to the first user; Indicates the unit electricity selling price of the target second user; represents the Internet access power of the target second user at time t on a typical day d; P ndt represents the actual output parameter of the target second user at time t on a typical day d; represents the charging power of the target second user to the target second user's self-built energy storage at time t on a typical day d; represents the discharge power of the target second user's self-built energy storage to the target second user at time t on a typical day d; α ndt The first alternative decision variable representing the target second user's Internet access power deviation; β ndt The second alternative decision variable representing the target second user's Internet access power deviation; α ndt and β ndt Always a positive number; The unit price representing the target second user's online deviation penalty; represents the power reported by the target second user to the shared energy storage system at time t on a typical day d; k represents the self-built energy storage of the target second user; represents the annual investment cost of the target second user for the self-built energy storage of the target second user; if the self-built energy storage of the target second user is in the investment state, then c k,n The value of is 1; if the self-built energy storage of the second target user is not yet built, then c k,n The value of is 0; represents the charging power of the target second user to the self-built energy storage of the target second user at time t on a typical day d; It represents the discharge power of the target second user to the self-built energy storage of the target second user at time t on a typical day d.

[0050] Furthermore, the investment, construction and operation constraints corresponding to the target second user include:

[0051]

[0052] Among them, if the self-built energy storage of the target second user is in a charging state at time t on a typical day d, The value of is 1, The value of is 0; if the self-built energy storage of the second target user is in the discharging state at time t on the typical day d, The value of is 0, The value of is 1;

[0053] The energy storage capacity constraints corresponding to the target second user include:

[0054]

[0055] E k,nd0 =E k,ndT ;

[0056] Among them, E k,ndt represents the total shared energy storage capacity of the target second user's self-built energy storage at time t on a typical day d; Indicates the charging efficiency of the self-built energy storage of the target second user; Indicates the discharge efficiency of the self-built energy storage of the target second user; represents the charging power of the self-built energy storage of the second target user at time t on a typical day d; represents the discharge power of the self-built energy storage of the second target user at time t on a typical day d; represents the minimum value of the shared energy storage capacity of the self-built energy storage of the target second user; Indicates the maximum value of the shared energy storage capacity of the self-built energy storage of the target second user; E k,nd0 E represents the shared energy storage capacity of the target second user's self-built energy storage at the preset initial time of a typical day d; k,ndTRepresents the shared energy storage capacity of the target second user’s self-built energy storage at the preset end time of a typical day d.

[0057] The energy storage power constraints corresponding to the target second user include:

[0058]

[0059] in, Indicates the minimum value of the charging power of the self-built energy storage of the target second user; Indicates the maximum value of the charging power of the self-built energy storage of the target second user; Indicates the minimum value of the discharge power of the self-built energy storage of the target second user; Indicates the maximum discharge power of the self-built energy storage of the target second user.

[0060] The actual output constraints corresponding to the target second user include:

[0061]

[0062] Where κ represents the maximum power fluctuation percentage of the self-built energy storage of the target second user; Represents the installed capacity of the self-built energy storage of the target second user.

[0063] Furthermore, the uncertainty parameters of renewable energy output include:

[0064]

[0065] in, Ψ represents the maximum deviation of the target second user's new energy output from the predicted value at time t on a typical day d; t Represents the uncertainty parameter at time t.

[0066] The multi-package energy storage game robust optimization configuration model includes:

[0067]

[0068] Wherein, w represents a human-controllable variable. The human-controllable variable includes a state parameter used to characterize the investment and construction state of the shared energy storage system, and a state parameter used to characterize the investment and construction state of the self-built energy storage of the target second user; u represents an uncontrollable variable, which includes the uncertainty parameter of the output of new energy; represents the optimization configuration strategy; G(w,u) represents the constraints of the multi-package energy storage game robust optimization configuration model; W represents the strategy set of controllable variables; U represents the strategy set of uncontrollable variables.

[0069] Furthermore, based on the particle swarm optimization algorithm, the robust optimization configuration model of multi-package energy storage game is solved to determine the optimization configuration strategy for the first user and the target second user.

[0070] The beneficial effects of the present invention are:

[0071] (1) When the shared energy storage investor invests in shared energy storage, it can effectively reduce the high cost problem caused by self-built energy storage facilities at new energy stations. While increasing the demand for energy storage services at new energy stations, it can also reduce the total grid-connected deviation of new energy stations, thereby improving the level of new energy consumption and significantly increasing the profits of new energy stations.

[0072] (2) It enables new energy stations to choose packages that better meet their own energy storage service needs, thereby increasing their enthusiasm for using energy storage services. The game model is used to ensure that shared energy storage investors can optimize planning and operation indicators under various possible circumstances, which is conducive to a more reasonable configuration of energy storage facilities.

[0073] In a second aspect, the present invention provides a multi-package energy storage game robust optimization configuration system, which can execute any of the methods described in the first aspect above.

[0074] In a third aspect, the present invention provides an electronic device, comprising: a memory, one or more processors; the memory and the processor are coupled; wherein the memory stores computer program code, the computer program code comprises computer instructions, and when the computer instructions are executed by the processor, the electronic device executes a multi-package energy storage game robust optimization configuration method as described in any one of the first aspects above.

[0075] In a fourth aspect, a computer-readable storage medium is provided, comprising computer instructions. When the computer instructions are executed on an electronic device, the electronic device executes a multi-package energy storage game robust optimization configuration method as described in any one of the first aspects above.

[0076] In a fifth aspect, a computer program product is provided. When the computer program product is run on a computer, the computer is enabled to execute a multi-package energy storage game robust optimization configuration method as described in any one of the first aspects above.

[0077] It can be understood that the beneficial effects that can be achieved by the system of the second aspect, the electronic device described in the third aspect, the computer-readable storage medium described in the fourth aspect, and the computer program product described in the fifth aspect provided above can refer to the beneficial effects in the first aspect and any possible design method thereof, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1The optimized configuration mode diagram of the second user of the shared energy storage target provided by the present invention;

[0079] Figure 2 A flowchart of the multi-package energy storage game robust optimization configuration method provided by the present invention;

[0080] Figure 3 A schematic diagram of a flow chart for solving a model provided by the present invention;

[0081] Figure 4 The typical daily effort curves of three second users provided by the present invention;

[0082] Figure 5 The use of shared energy storage in Case 2 provided by the present invention;

[0083] FIG6( a ) is a diagram showing the revenue iteration of the second user 1 in case 3 provided by the present invention;

[0084] FIG6( b ) is a diagram showing the revenue iteration of the second user 2 in case 3 provided by the present invention;

[0085] FIG6( c ) is a diagram showing the revenue iteration of the second user 3 in case 3 provided by the present invention;

[0086] Figure 7 It is a comparison diagram of the total power demand of Case 3 and Case 4 of the present invention;

[0087] FIG8( a) is a diagram of the shared energy storage usage strategy of the second user 1 in Case 4 and Case 5 provided by the present invention;

[0088] FIG8( b ) is a diagram of a strategy for using the shared energy storage by the second user 2 in Case 4 and Case 5 provided by the present invention;

[0089] FIG8( c ) is a diagram showing a strategy for using the shared energy storage by the second user 3 in Case 4 and Case 5 provided by the present invention. DETAILED DESCRIPTION

[0090] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application. Among them, in the description of the present application, unless otherwise specified, " / " indicates that the objects associated before and after are in an "or" relationship, for example, A / B can represent A or B; "and / or" in the present application is only a description of the association relationship of the associated objects, indicating that there can be three relationships, for example, A and / or B, which can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. And, in the description of the present application, unless otherwise specified, "multiple" refers to two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple. In addition, in order to facilitate the clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, the words "first", "second" and the like are used to distinguish between the same items or similar items with substantially the same functions and effects. Those skilled in the art will understand that the words "first", "second" and the like do not limit the quantity and execution order, and the words "first", "second" and the like do not necessarily limit the differences. At the same time, in the embodiments of the present application, the words "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or design.

[0091] The optimal configuration mode of new energy shared energy storage based on game theory is shown in the figure Figure 1As shown, the participants in the game are the shared energy storage investor (also referred to as the first user in this application) and each new energy station (also referred to as the second user in the embodiment of this application). Each new energy station reports its energy storage service demand to the shared energy storage investor. The shared energy storage investor provides optional packages (for example, the first package, the second package and the third package in this application) and the service fees corresponding to each package based on the reported demand. The new energy station readjusts its own energy storage service demand based on the package and service fee. If the shared energy storage service is priced too high at a certain moment, the new energy station will reduce the use of energy storage services at that moment in combination with its own reality and the goal of maximizing benefits to reduce the excessively high energy storage service costs; if the shared energy storage service is priced lower at a certain moment, the new energy station will appropriately increase the use of energy storage services at that moment according to its own situation. The new energy station adjusts its own needs and proposes a new energy storage service usage strategy. The shared energy storage investor will readjust the price according to the new energy storage service needs of the new energy station to maximize its own interests. When new energy stations use shared energy storage services less, the service price should be appropriately lowered to encourage new energy stations to actively use shared energy storage services. When new energy stations use the services more, the price should be appropriately increased to obtain more profits.

[0092] In addition, the energy storage service demand of new energy sites will also affect the investment and construction of shared energy storage. Through repeated optimization strategies by both parties, until the shared energy storage investors and new energy sites reach the maximum profit under this model, the current shared energy storage service usage strategy, pricing strategy and energy storage investment and construction strategy are all the optimal solutions that can be obtained by the model of the present invention.

[0093] The multi-package energy storage game robust optimization configuration method provided by the present invention is different from the traditional scenario in which multiple new energy stations each use energy storage equipment separately. Based on robust optimization technology, the present invention considers the uncertainty of new energy output, proposes that multiple independent new energy stations jointly use energy storage equipment provided by a third-party shared energy storage investor, and combines game theory to construct a game robust optimization configuration method to optimize the energy storage configuration.

[0094] See also Figure 2 The multi-package energy storage game robust optimization configuration method provided by the present invention specifically includes the following steps:

[0095] S201: Construct a shared energy storage service package provided by a first user to at least one second user.

[0096] Wherein, when the first user provides the shared energy storage service to the target second user, the service fee is charged to the target second user based on the shared energy storage service package. The target second user is any second user among the at least one second user. The shared energy storage service package includes a first package, a second package and a third package. The first package is determined based on the charge and discharge power purchased by the target second user. The second package is determined based on the shared energy storage capacity leased by the target second user. The third package is determined based on the time when the target second user leases the shared energy storage.

[0097] In some embodiments, the first user provides a shared energy storage service to a target second user based on a shared energy storage system, wherein the shared energy storage capacity includes a shared energy storage energy capacity and a shared energy storage power capacity.

[0098] The service fee for the first package is:

[0099]

[0100] in, represents the service fee corresponding to the first package; d represents a typical day; O d It represents the sum of the days represented by the typical day d; represents the unit power cost of charging the shared energy storage system at time t on a typical day d when the target second user selects the first package; represents the unit power cost of discharging to the shared energy storage system at time t on a typical day d when the target second user selects the first package; represents the power charged to the shared energy storage system at time t on a typical day d when the target second user selects the first package; represents the power discharged to the shared energy storage system at time t on a typical day d when the target second user selects the first package; L is a constant real number; represents the charging power service demand of the target second user to the shared energy storage system at time t on a typical day d; represents the target second user's discharge power service demand to the shared energy storage system at time t on a typical day d; when the target second user selects the first package, The value of is 1, and The value of is 0; when the target second user selects the second package, The value of is 1, and The value of is 0; when the second target user chooses the third package, The value of is 1, and The values ​​of are all 0;

[0101] The service fee for the second package is:

[0102]

[0103] in, Indicates the service fee corresponding to the second package; represents the unit energy capacity fee of leasing the shared energy storage system at time t on a typical day d when the target second user selects the second package; represents the unit power capacity fee of leasing the shared energy storage system at time t on a typical day d when the target second user selects the second package; represents the shared energy storage capacity rented on a typical day d when the target second user selects the second package; Indicates the shared energy storage power capacity rented on a typical day when the target second user selects the second package; represents the power charged to the shared energy storage system at time t on a typical day d when the target second user selects the second package; represents the power discharged to the shared energy storage system at time t on a typical day d when the target second user selects the second package; η C represents the maximum charging efficiency of the shared energy storage system; η D represents the maximum discharge efficiency of the shared energy storage system; Indicates the shared energy storage power capacity rented at the preset initial time on a typical day d when the target second user selects the second package; Indicates the shared energy storage power capacity rented at the preset end time of a typical day d when the target second user selects the second package.

[0104] The service fee for the third package is:

[0105]

[0106] in, Indicates the service fee corresponding to the third package; It indicates the unit time cost of leasing shared energy storage on a typical day when the target second user chooses the third package; when the target second user chooses the third package, The value of is 1; when the target second user selects the first package or the second package, The value of is 0; represents the power charged to the shared energy storage system at time t on a typical day d when the target second user selects the third package; represents the power discharged to the shared energy storage system at time t on a typical day d when the target second user selects the third package; represents the time during which the target second user continuously uses the shared energy storage before and at time t on a typical day d; Indicates the shortest continuous usage time of the energy storage service when the target second user selects the third package.

[0107] S202: With the goal of maximizing the first user's profit, an upper-level shared energy storage model corresponding to the first user is established based on the energy storage investment, construction and operation constraints, energy storage power constraints, energy storage capacity constraints and energy storage supply and demand balance constraints corresponding to the first user.

[0108] In some embodiments, an initial upper-layer shared energy storage model corresponding to the first user is established. Based on the energy storage investment and operation constraints, energy storage power constraints, energy storage capacity constraints, and energy storage supply and demand balance constraints corresponding to the first user, the initial upper-layer shared energy storage model is constrained to obtain the upper-layer shared energy storage model.

[0109] In some embodiments, without considering the life loss and maintenance cost of the shared energy storage equipment, the initial upper-layer shared energy storage model includes:

[0110] F ses =F ses,new +F ses,grid -F ses,inv -F ses,pun ;

[0111]

[0112]

[0113] Among them, F ses represents the total revenue of the first user; F ses,new F represents the service fee charged by the first user for providing shared energy storage service to the target second user; ses,grid represents the revenue of the first user from selling electricity to the target second user; F ses,inv represents the investment and construction cost of the shared energy storage system by the first user; F ses,pun represents the over-limit penalty cost of the shared energy storage system; θ sell represents the unit power cost of the first user selling electricity to the target second user; θ buy Indicates the unit power cost of the first user's electricity purchase; represents the power sold by the first user to the target second user at time t on a typical day d; represents the power purchased by the first user at time t on a typical day d; s represents the shared energy storage system; represents the annual construction cost of the shared energy storage system by the first user; if the shared energy storage system is already constructed, then c s The value of is 1; if the shared energy storage system is not yet built, then c s The value of θ is 0; pun represents the unit penalty cost when the power of the shared energy storage system exceeds the limit; represents the charging power penalty term of the shared energy storage system at time t on a typical day d; represents the discharge power penalty term of the shared energy storage system at time t on a typical day d.

[0114] In some embodiments, the energy storage investment and operation constraints corresponding to the first user include:

[0115]

[0116] Among them, if the shared energy storage system is in a charging state at time t on a typical day d, then The value of is 1, The value of is 0; if the shared energy storage system is in a discharging state at time t on a typical day d, then The value of is 0, The value of is 1;

[0117] The energy storage power constraints corresponding to the first user include:

[0118]

[0119]

[0120] in, represents the total charging power of the shared energy storage system at time t on a typical day d; represents the total discharge power of the shared energy storage system at time t on a typical day d; represents the charging power of the shared energy storage system to the target second user at time t on a typical day d; represents the discharge power of the shared energy storage system to the target second user at time t on a typical day d; Indicates the minimum value of the charging power of the shared energy storage system; Indicates the maximum value of the charging power of the shared energy storage system; Indicates the minimum value of the discharge power of the shared energy storage system; Indicates the maximum discharge power of the shared energy storage system.

[0121] The energy storage capacity constraints corresponding to the first user include:

[0122]

[0123] Among them, E sdt represents the total shared energy storage capacity of the shared energy storage system at time t on a typical day d; represents the remaining shared energy storage capacity of the shared energy storage system at time t on a typical day d; represents the shared energy storage capacity leased by the target second user from the first user at time t on a typical day d based on the second package; represents the shared energy storage capacity that the target second user leases from the first user based on the second package at the preset initial time on a typical day d; represents the shared energy storage capacity that the target second user leases from the first user based on the second package at the preset end time of the typical day d; represents the total shared energy storage capacity of the shared energy storage system leased through the second package on a typical day d; Indicates the maximum value of the shared energy storage capacity of the shared energy storage system; represents the minimum value of the shared energy storage capacity of the shared energy storage system; represents the remaining shared energy storage capacity of the shared energy storage system at the preset initial time on a typical day d; represents the remaining shared energy storage capacity of the shared energy storage system at the preset end time of a typical day d;

[0124] The energy storage supply and demand balance constraints corresponding to the first user include:

[0125]

[0126]

[0127] in, represents the charging power constant value reported to the shared energy storage system at time t on a typical day d when the target second user selects the first package; represents the discharge power constant value reported to the shared energy storage system at time t on a typical day d when the target second user selects the first package;

[0128] represents the charging power constant value reported to the shared energy storage system at time t on a typical day d when the target second user selects the second package; represents the discharge power constant value reported to the shared energy storage system at time t on a typical day d when the target second user selects the second package; represents the charging power constant value reported to the shared energy storage system at time t on a typical day d when the target second user selects the third package; represents the discharge power constant value reported to the shared energy storage system at time t on a typical day d when the target second user selects the third package; It represents the constant value of the shared energy storage capacity leased from the first user on a typical day d when the target second user selects the second package.

[0129] S203: With the goal of maximizing the benefit of the target second user, a lower-level deterministic model corresponding to the target second user is established based on the investment, construction and operation constraints, energy storage capacity constraints, energy storage power constraints and actual output constraints corresponding to the target second user.

[0130] In some embodiments, an initial lower-layer deterministic model corresponding to the target second user is established. Based on the investment and operation constraints, energy storage capacity constraints, energy storage power constraints, and actual output constraints corresponding to the target second user, the initial lower-layer deterministic model is constrained to obtain the lower-layer deterministic model corresponding to the target second user.

[0131] In some embodiments, the initial lower-layer deterministic model corresponding to the target second user includes:

[0132]

[0133] α ndt ,β ndt ≥0;

[0134]

[0135] in, represents the total revenue of the target second user; Indicates the Internet access income of the target second user; represents the Internet access deviation penalty cost paid by the target second user; Indicates the investment and construction cost of the target second user's self-built energy storage; represents the service fee paid by the target second user to the first user; Indicates the unit electricity selling price of the target second user; represents the Internet access power of the target second user at time t on a typical day d; P ndt represents the actual output parameter of the target second user at time t on a typical day d; represents the charging power of the target second user to the target second user's self-built energy storage at time t on a typical day d; represents the discharge power of the target second user's self-built energy storage to the target second user at time t on a typical day d; α ndt The first alternative decision variable representing the target second user's Internet access power deviation; β ndt The second alternative decision variable representing the target second user's Internet access power deviation; α ndt and β ndt Always a positive number; The unit price representing the target second user's online deviation penalty; represents the power reported by the target second user to the shared energy storage system at time t on a typical day d; k represents the self-built energy storage of the target second user; represents the annual investment cost of the target second user for the self-built energy storage of the target second user; if the self-built energy storage of the target second user is in the investment state, then c k,n The value of is 1; if the self-built energy storage of the second target user is not yet built, then c k,n The value of is 0; represents the charging power of the target second user to the self-built energy storage of the target second user at time t on a typical day d; It represents the discharge power of the target second user to the self-built energy storage of the target second user at time t on a typical day d.

[0136] In some embodiments, the investment and operation constraints corresponding to the target second user include:

[0137]

[0138] Among them, if the self-built energy storage of the target second user is in a charging state at time t on a typical day d, The value of is 1, The value of is 0; if the self-built energy storage of the second target user is in the discharging state at time t on the typical day d, The value of is 0, The value of is 1;

[0139] The energy storage capacity constraints corresponding to the target second user include:

[0140]

[0141] E k,nd0 =E k,ndT ;

[0142] Among them, E k,ndt represents the total shared energy storage capacity of the target second user's self-built energy storage at time t on a typical day d; Indicates the charging efficiency of the self-built energy storage of the target second user; Indicates the discharge efficiency of the self-built energy storage of the target second user; represents the charging power of the self-built energy storage of the second target user at time t on a typical day d; represents the discharge power of the self-built energy storage of the second target user at time t on a typical day d; represents the minimum value of the shared energy storage capacity of the self-built energy storage of the target second user; Indicates the maximum value of the shared energy storage capacity of the self-built energy storage of the target second user; E k,nd0 E represents the shared energy storage capacity of the target second user's self-built energy storage at the preset initial time of a typical day d; k,ndT Represents the shared energy storage capacity of the target second user’s self-built energy storage at the preset end time of a typical day d.

[0143] The energy storage power constraints corresponding to the target second user include:

[0144]

[0145] in, Indicates the minimum value of the charging power of the self-built energy storage of the target second user; Indicates the maximum value of the charging power of the self-built energy storage of the target second user; Indicates the minimum value of the discharge power of the self-built energy storage of the target second user; Indicates the maximum discharge power of the self-built energy storage of the target second user.

[0146] The actual output constraints corresponding to the target second user include:

[0147]

[0148] Where κ represents the maximum power fluctuation percentage of the self-built energy storage of the target second user; Represents the installed capacity of the self-built energy storage of the target second user.

[0149] S204: Obtain uncertainty parameters of renewable energy output, and establish a multi-package energy storage game robust optimization configuration model based on the shared energy storage service package, the upper shared energy storage model, the lower deterministic model corresponding to the target second user, and the uncertainty parameters of renewable energy output.

[0150] It should be noted that the selection of "uncertainty parameters of new energy output" is the key to robust optimization of uncertainty problems. The characteristic of the uncertainty parameters of cardinality new energy output adopted in the present invention is that it controls the relative value of the uncertainty parameter offset and can more accurately measure the fluctuation of the parameters.

[0151] In some embodiments, the uncertainty parameters of the new energy output include:

[0152]

[0153] in, Ψ represents the maximum deviation of the target second user's new energy output from the predicted value at time t on a typical day d; t Represents the uncertainty parameter at time t.

[0154] The present invention adopts a multi-package energy storage game robust optimization configuration model to deal with the uncertainty of new energy output. The multi-package energy storage game robust optimization configuration model can be understood as the uncertainty of new energy output trying to worsen the planning and operation indicators of the target second user and shared energy storage, while the decision maker tries to give a strategy to optimize the planning and operation indicators under various possible circumstances. The multi-package energy storage game robust optimization configuration model includes:

[0155]

[0156] Wherein, w represents a human-controllable variable. The human-controllable variable includes a state parameter used to characterize the investment and construction state of the shared energy storage system, and a state parameter used to characterize the investment and construction state of the self-built energy storage of the target second user; u represents an uncontrollable variable, which includes the uncertainty parameter of the output of new energy; represents the optimization configuration strategy; G(w,u) represents the constraints of the multi-package energy storage game robust optimization configuration model; W represents the strategy set of controllable variables; U represents the strategy set of uncontrollable variables.

[0157] S205: Based on the multi-package energy storage game robust optimization configuration model, determine the optimization configuration strategy for the first user and the target second user.

[0158] Among them, the optimization configuration strategy includes the pricing strategy and energy storage configuration strategy of the first user, as well as the package selection strategy, self-built energy storage strategy and energy storage service demand strategy of the second user.

[0159] In some embodiments, a multi-package energy storage game robust optimization configuration model can be solved based on optimization software and a particle swarm optimization algorithm to determine an optimization configuration strategy for a first user and a target second user.

[0160] The solution of the present invention can be solved by combining the mature optimization software GUROBI with the particle swarm optimization algorithm to solve the multi-package energy storage game robust optimization configuration model established in step S204 under MATLAB2018B. The specific solution process is:

[0161] (1) Setting basic parameters: input known parameters in the model, set relevant parameters such as the number of particles, inertia weight, and the maximum number of iterations R in PSO (Particle Swarm Optimization);

[0162] The input parameters include: grid time-of-use electricity price data, target second user output data, agent-built shared energy storage system data, target second user self-built energy storage data, and model-related price data.

[0163] (2) Initializing package prices: Using PSO to initialize the prices of the three packages provided by the first user;

[0164] (3) Solve the lower-level target second user model: Based on the price settings of the three packages of the current first user, solve the energy storage service requirements, package selection strategies, and self-built energy storage strategies of each target second user for shared energy storage, and obtain the highest benefit of each target second user;

[0165] (4) Solve the upper-level shared energy storage model: calculate the total revenue of the current first user, update the optimal solution, and use PSO to update the current optimal price strategy;

[0166] (5) Iterate until output: Determine whether the current number of iterations has reached the maximum number of iterations R. If not, repeat steps (3) to (4) until the maximum number of iterations is reached. At this time, the pricing strategy and energy storage configuration strategy of the first user, the energy storage service requirements of the target second user, the package selection strategy, and the self-built energy storage strategy are output.

[0167] Exemplarily, the present invention adopts a method combining mature optimization software with a particle swarm optimization algorithm and follows the following Figure 3 The solution process shown is used to solve the model of the present invention.

[0168] The second user output data of the present invention includes the output data of three different second users in the northwest region every hour in a typical day. Figure 4 The output curves of the second user N1 (this embodiment of the present application may also be referred to as the second user 1), the second user N2 (this embodiment of the present application may also be referred to as the second user 2), and the second user N3 (this embodiment of the present application may also be referred to as the second user 3) in the northwest region of China with a total installed capacity of 100MW, 100MW, and 150MW respectively in 24 time periods within a typical day, the grid-connected price of new energy output refers to the grid-connected electricity price in the region, which is set to 259.5 yuan / (MW·h), the output deviation penalty coefficient is set to 519 yuan / (MW·h), and the time-of-use electricity price setting of the power grid refers to the setting of the development and reform commission of the region on optimizing the peak and valley time-of-use electricity price mechanism.

[0169] The grid time-of-use electricity price data includes the time and unit price data of valley electricity price, peak electricity price and general electricity price. Table 1 and Table 2 show the grid time-of-use electricity price parameter settings and the model related price data parameter settings respectively. The related price data include the upper and lower limits of the charging pricing of the first user for the second user, the upper and lower limits of the discharge pricing of the first user for the second user, the upper and lower limits of the unit pricing of different packages, the penalty price for the online deviation of different second users, the electricity selling price of the second user, and the purchase and sale price of electricity from the first user to the grid. The model price related parameter settings in Table 2 are set in accordance with the "Ningxia Power Auxiliary Market Operation Rules" issued by the Northwest Regulatory Bureau of the National Energy Administration and the Ningxia Hui Autonomous Region Development and Reform Commission.

[0170] Table 1

[0171]

[0172] Table 2

[0173]

[0174] in, They respectively represent the minimum and maximum unit power charges for discharging to the shared energy storage in the first package within a typical day d; They represent the minimum and maximum unit power charges for charging shared energy storage in the first package on a typical day d respectively; They represent the minimum and maximum values ​​of the unit energy capacity fee for leasing shared energy storage in the second package within a typical day d; They represent the minimum and maximum values ​​of the unit power capacity fee for leasing shared energy storage in the second package within a typical day d; They respectively represent the minimum and maximum unit time cost of leasing shared energy storage in the third package within a typical day.

[0175] The second user's self-built energy storage data includes the upper and lower limits of the capacity of the self-built energy storage equipment, the upper and lower limits of the output, the charging and discharging efficiency, and the unit investment and construction cost of each type of self-built energy storage. The data of the shared energy storage system built on behalf of others includes the upper and lower limits of the capacity of the shared energy storage equipment, the upper and lower limits of the output, the charging and discharging efficiency, and the unit investment and construction cost of each type of shared energy storage. The parameter settings of the second user's self-built energy storage and the parameter settings of the shared energy storage system built on behalf of others are shown in Tables 3 and 4 respectively. The settings of the model-related parameters and related prices refer to the relevant domestic policies and actual conditions.

[0176] Table 3

[0177]

[0178] Table 4

[0179]

[0180] The present invention uses 5 examples as shown in Table 5 for comparative analysis. Case 1-2 does not consider game theory, and its shared energy storage service pricing is fixed pricing. Case 1-3 does not consider package selection, and its billing method is based on the first package in the package setting, that is, the power package billing method.

[0181] Table 5

[0182]

[0183] The total benefits of the second user and the first user in Case 1-5 are shown in Table 6.

[0184] Table 6

[0185]

[0186]

[0187] The income of the first user in Case 1-5 shows a steady upward trend, and the income of each second user in Case 1-4 also increases to varying degrees. Therefore, the investment and construction of shared energy storage is beneficial to both parties in increasing their income.

[0188] In case 1-5, the strategy of the second user building its own energy storage and the first user investing in shared energy storage is shown in Table 7.

[0189] Table 7

[0190]

[0191] In the case of shared energy storage participation, the second user tends to lease shared energy storage services to avoid the cost of building their own energy storage. In addition, due to the concentrated advantages of the first user's investment in energy storage facilities, the second user's energy storage service needs can be better met, which is conducive to promoting the consumption of new energy, reducing the second user's costs and increasing profits.

[0192] The solution results of case 1-2 are shown in Table 8. Case 2 considers the investment, construction and operation of shared energy storage on the basis of case 1. As shown in Table 8, compared with case 1, case 2 considers the participation of the first user, and the second user can choose to rent shared energy storage services to avoid the high investment and construction costs of self-built energy storage, which is also conducive to the consumption of new energy.

[0193] Table 8

[0194]

[0195] Depend on Figure 5 It can be seen that the peak of the shared energy storage discharge power occurs at time 4. The main reason is that the second user 3 encounters a large output fluctuation at time 4. In order to avoid the penalty cost of online deviation, the second user 3 chooses to use the shared energy storage service to discharge to it. At the same time, it can be seen from Table 1 that since time 5 is the valley electricity price, the shared energy storage adopts the strategy of buying electricity from the power grid to ensure the normal use of the energy storage service, ensuring a certain amount of its own electricity to cope with the subsequent use of the second user.

[0196] The first peak of the remaining power of shared energy storage occurs at 7 o'clock. This is because the second user has a higher charging power at this moment. In order to ensure the sustainability of subsequent new energy consumption, shared energy storage chooses to sell part of the power to the power grid at 8 and 9 o'clock when the electricity price is peak. At 11 and 12 o'clock, because this time interval still belongs to the peak electricity price time and the second user has no discharge power demand, shared energy storage chooses to sell all the power to the power grid for profit on the premise of ensuring the use needs of the second user, in order to reduce the idle rate and increase its own profits.

[0197] At 13:00 and 15:00, shared energy storage has a higher power purchase power. On the one hand, it is because the electricity price at this moment is normal and the cost of purchasing electricity is relatively low. Purchasing a certain amount of electricity at this moment can guarantee the subsequent usage needs of the second user. On the other hand, at 15:00, the second user has a higher discharge demand. In order to ensure its own remaining power, shared energy storage chooses to purchase electricity from the power grid to meet the needs of the second user.

[0198] At 19:00, 20:00, and 22:00, the shared energy storage system chooses to sell a portion of the electricity for profit, and the remaining electricity is used to meet the shared energy storage service needs of the second user. When the electricity price is at a low point at 24:00, the shared energy storage system purchases a certain amount of electricity from the grid to meet the energy storage needs of the second user the next day.

[0199] Depend on Figure 6(a)-Figure 6(c) It can be seen that after adopting the game pricing mechanism, the total revenue of the second users 1, 2, and 3 (also referred to as new energy stations 1, 2, and 3 in the embodiment of the present application) tends to converge after multiple iterations, and after convergence, the second users cannot obtain higher revenue by changing the operating strategy.

[0200] The package selection of the second user in Case 4-5 is shown in Table 9.

[0201] Table 9

[0202]

[0203] pass Figure 7 It can be seen that after formulating the package, the total power demand of the second user's shared energy storage service has increased at almost every moment. This is because the second user can choose a shared energy storage service that is more in line with its own fluctuations. Compared with Case 3, it can not only better meet its own energy storage needs, but also reduce the cost of the second user's shared energy storage service due to the personalization of the package, thereby increasing the second user's enthusiasm for using shared energy storage. Among them, the moments with the highest growth rate are moments 3 and 4. As shown in Table 9, this is because the second user 3 selected a time package within this time interval. Since the second user 3 has obvious fluctuations in the output of new energy in this time interval, in order to meet its own Internet access needs, it has put forward a higher demand for shared energy storage services.

[0204] Case 4, 5 Second user shared energy storage usage strategy Figure 8(a)-Figure 8(c)As shown. As shown in Figure 8(a), the energy storage service demand of the second user 1 in Case 4 is small and scattered, and there is a significant difference in demand. Therefore, the second user 1 selected the first package with the highest flexibility and purchased energy storage services at the 8th, 12th, and 15th moments with large fluctuations. As shown in Figure 8(b), the energy storage service demand of the second user 2 in Case 4 is evenly distributed at all times, and there is no significant difference in demand. Therefore, the second user selected the second package. After selecting this package, the second user 2 can obtain the right to use the leased energy storage during a longer demand moment and better plan its own operation strategy. As shown in Figure 8(c), the demand for energy storage services by the second user 3 in Case 4 is concentrated between the 3rd and 8th moments, and the demand is relatively high. This is because the second user 3 has too large output fluctuations in this time interval, so the third package that is more in line with its own needs is selected. Compared with the other two packages, after selecting this package, the second user 3 can use more energy storage services during the rental time to meet its own needs, which is more economical.

[0205] The specific total amount of grid-connected deviation and total amount of energy storage service demand are shown in Table 10. Under the influence of output uncertainty, the total amount of grid-connected deviation of the second user increased by 162.51 MW·h, which caused the second user to purchase more shared energy storage services to balance the output size. Therefore, the total demand for shared energy storage services of the second user in Case 5 increased from 262.81 MW·h in Case 4 to 733.42 MW·h.

[0206] Table 10

[0207]

[0208] In terms of package selection, as shown in Table 9, the second user 3 did not change its own energy storage service package selection strategy, but the package selections of the second users 1 and 2 were changed to the second package and 1 respectively. This is because the uncertainty of the output of new energy is taken into account. The fluctuation of the second user 1 is more frequent. From the charging and discharging power of case 5 in Figure 8 (a), it can be seen that the time when the second user 1 needs energy storage has increased; while the output fluctuation of the second user 2 has intensified. From the charging and discharging power of case 5 in Figure 8 (b), it can be seen that the energy storage demand of the second user 2, which was originally not much different, has become irregular and has a large difference due to fluctuations. Based on the above situation, at this time, the second package can better meet the usage needs of the second user 1 than the first package. Similarly, the first package can better meet the usage needs of the second user 2 under uncertainty. Therefore, in order to obtain higher profits, the second users 1 and 2 change their original package selection strategies and choose the second package and 1 respectively.

[0209] The present invention aims at the problem of reasonable configuration of energy storage facilities after the access of new energy to the power system. The first user is used as the third-party investor of shared energy storage, and the second user is selected as the new energy station for analysis. By establishing a business interaction model of the master-slave game of upper and lower layers of new energy shared energy storage, the personalized packages are customized according to the different output characteristics of each second user, so as to improve the enthusiasm of the second user to use the shared energy storage service. The uncertainty of the output of new energy is considered in combination with the robust optimization method, which is more in line with the actual production and avoids unnecessary investment and construction. Finally, the actual second user output data in a certain area in northwest my country is used for case analysis, and the following conclusions are drawn:

[0210] When the first user invests in shared energy storage, it can effectively reduce the high cost problem caused by the second user's self-built energy storage facilities. While increasing the second user's demand for energy storage services, it also reduces the second user's total grid-connected deviation, improves the level of new energy consumption, and significantly increases the second user's profit.

[0211] Based on the formulation of multiple packages for energy storage services, the second user can choose a package that better meets their own energy storage service needs, which increases the second user's enthusiasm for using energy storage services; by adopting a master-slave game pricing mechanism, the first user can reasonably adjust the price according to the second user's usage strategy, which is conducive to a more reasonable configuration of energy storage facilities.

[0212] The robust optimization method takes into account the uncertainty of renewable energy output and selects appropriate parameters based on actual data to reduce the conservatism of the model, avoiding excessive robustness caused by output uncertainty, which would lead to unnecessary investment in energy storage, so as to ensure the profitability of the energy storage investor itself while meeting the needs of the target second user.

[0213] In some schemes, multiple embodiments of the present application can be combined, and the combined scheme can be implemented. Optionally, some operations in the process of each method embodiment are optionally combined, and / or the order of some operations is optionally changed. In addition, the execution order between the steps of each process is only exemplary and does not constitute a restriction on the execution order between the steps. There can also be other execution orders between the steps. It is not intended to indicate that the execution order is the only order in which these operations can be performed. A person of ordinary skill in the art will think of a variety of ways to reorder the operations described herein. In addition, it should be noted that the process details involved in a certain embodiment of this article are also applicable to other embodiments in a similar manner, or different embodiments can be used in combination.

[0214] In addition, some steps in the method embodiment may be equivalently replaced by other possible steps. Alternatively, some steps in the method embodiment may be optional and may be deleted in certain usage scenarios. Alternatively, other possible steps may be added to the method embodiment. Furthermore, the method embodiments may be implemented separately or in combination.

[0215] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the system can be divided into different functional modules to complete all or part of the functions described above.

[0216] In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

[0217] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0218] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium, including several instructions to enable a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0219] The above contents are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application shall be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A multi-package energy storage game robust optimization configuration method, characterized in that: include: Constructing a shared energy storage service package provided by a first user to at least one second user; When the first user provides the shared energy storage service to the target second user, the first user charges the target second user a service fee based on the shared energy storage service package; the target second user is any second user among the at least one second user; the shared energy storage service package includes a first package, a second package and a third package; the first package is determined based on the charge and discharge power purchased by the target second user; the second package is determined based on the shared energy storage capacity rented by the target second user; the third package is determined based on the time when the target second user rents the shared energy storage; Taking maximizing the benefit of the first user as the goal, an upper-layer shared energy storage model corresponding to the first user is established based on energy storage investment, construction and operation constraints, energy storage power constraints, energy storage capacity constraints and energy storage supply and demand balance constraints corresponding to the first user; Taking the maximization of the benefit of the target second user as the goal, based on the investment, construction and operation constraints, energy storage capacity constraints, energy storage power constraints and actual output constraints corresponding to the target second user, a lower-level deterministic model corresponding to the target second user is established; Obtain uncertainty parameters of the new energy output, and establish a multi-package energy storage game robust optimization configuration model based on the shared energy storage service package, the upper-layer shared energy storage model, the lower-layer deterministic model corresponding to the target second user, and the uncertainty parameters of the new energy output; Based on the multi-package energy storage game robust optimization configuration model, an optimization configuration strategy for the first user and the target second user is determined; the optimization configuration strategy includes the pricing strategy and energy storage configuration strategy of the first user, and the package selection strategy, self-built energy storage strategy and energy storage service demand strategy of the second user.

2. The method according to claim 1, characterized in that The first user provides a shared energy storage service to the target second user based on a shared energy storage system; the shared energy storage capacity includes a shared energy storage energy capacity and a shared energy storage power capacity; The service fee corresponding to the first package is: in, represents the service fee corresponding to the first package; d represents a typical day; O d represents the sum of the days represented by the typical day d; represents the unit power cost of charging the shared energy storage system at time t on the typical day d when the target second user selects the first package; represents the unit power cost of discharging to the shared energy storage system at time t on the typical day d when the target second user selects the first package; represents the power of charging the shared energy storage system at time t on the typical day d when the target second user selects the first package; represents the power discharged to the shared energy storage system at time t on the typical day d when the target second user selects the first package; L is a constant real number; represents the charging power service demand of the target second user to the shared energy storage system at time t on the typical day d; represents the discharge power service demand of the target second user to the shared energy storage system at time t on the typical day d; when the target second user selects the first package, The value of is 1, and The values ​​of are all 0; when the target second user selects the second package, The value of is 1, and The values ​​of are all 0; when the target second user selects the third package, The value of is 1, and The values ​​of are all 0; The service fee for the second package is: in, Indicates the service fee corresponding to the second package; represents the unit energy capacity fee for leasing the shared energy storage system at time t on the typical day d when the target second user selects the second package; represents the unit power capacity fee for leasing the shared energy storage system at time t on the typical day d when the target second user selects the second package; represents the shared energy storage capacity rented on the typical day when the target second user selects the second package; represents the shared energy storage power capacity rented on the typical day when the target second user selects the second package; represents the power of charging the shared energy storage system at time t on the typical day d when the target second user selects the second package; represents the power discharged to the shared energy storage system at time t on the typical day d when the target second user selects the second package; η C represents the maximum charging efficiency of the shared energy storage system; η D represents the maximum discharge efficiency of the shared energy storage system; represents the shared energy storage power capacity rented at the preset initial time on the typical day d when the target second user selects the second package; represents the shared energy storage power capacity rented at the preset end time of the typical day d when the target second user selects the second package; The service fee corresponding to the third package is: in, Indicates the service fee corresponding to the third package; represents the unit time fee for leasing the shared energy storage on the typical day when the target second user selects the third package; when the target second user selects the third package, The value of is 1; when the target second user selects the first package or the second package, The value of is 0; represents the power of charging the shared energy storage system at time t on the typical day d when the target second user selects the third package; represents the power discharged to the shared energy storage system at time t on the typical day d when the target second user selects the third package; represents the time during which the target second user continuously uses the shared energy storage before and at time t on the typical day d; Indicates the shortest continuous usage time of the energy storage service when the target second user selects the third package.

3. The method according to claim 2, characterized in that The establishing of an upper-layer shared energy storage model corresponding to the first user based on the energy storage investment and operation constraints, energy storage power constraints, energy storage capacity constraints, and energy storage supply and demand balance constraints corresponding to the first user includes: Establishing an initial upper-layer shared energy storage model corresponding to the first user; Based on the energy storage investment, construction and operation constraints, energy storage power constraints, energy storage capacity constraints and energy storage supply and demand balance constraints corresponding to the first user, the initial upper-level shared energy storage model is constrained to obtain the upper-level shared energy storage model.

4. The method according to claim 3, characterized in that The initial upper-layer shared energy storage model includes: F ses =F ses,new +F ses,grid -F ses,inv -F ses,pun ; Among them, F ses represents the total revenue of the first user; ses,new represents the service fee charged by the first user for providing the shared energy storage service to the target second user; F ses,grid represents the income of the first user from selling electricity to the target second user; F ses,inv represents the investment and construction cost of the shared energy storage system by the first user; F ses,pun represents the over-limit penalty cost of the shared energy storage system; θ sell represents the unit power cost of the first user selling electricity to the target second user; θ buy represents the unit power cost of the first user's electricity purchase; represents the power sold by the first user to the target second user at time t on the typical day d; represents the power purchased by the first user at time t on the typical day d; s represents the shared energy storage system; represents the annual construction cost of the shared energy storage system by the first user; if the shared energy storage system is in the construction state, then c s The value of is 1; if the shared energy storage system is not yet built, then c s The value of θ is 0; pun Indicates the unit penalty cost when the power of the shared energy storage system exceeds the limit; represents the charging power penalty term of the shared energy storage system at time t on the typical day d; represents the discharge power penalty term of the shared energy storage system at time t on the typical day d.

5. The method according to claim 4, characterized in that The energy storage investment and operation constraints corresponding to the first user include: If the shared energy storage system is in a charging state at time t on the typical day d, then The value of is 1, The value of is 0; if the shared energy storage system is in a discharging state at time t on the typical day d, then The value of is 0, The value of is 1; The energy storage power constraints corresponding to the first user include: in, represents the total charging power of the shared energy storage system at time t on the typical day d; represents the total discharge power of the shared energy storage system at time t on the typical day d; represents the charging power of the shared energy storage system to the target second user at time t on the typical day d; represents the discharge power of the shared energy storage system to the target second user at time t on the typical day d; Indicates the minimum value of the charging power of the shared energy storage system; Indicates the maximum value of the charging power of the shared energy storage system; represents the minimum value of the discharge power of the shared energy storage system; Indicates the maximum value of the discharge power of the shared energy storage system; The energy storage capacity constraints corresponding to the first user include: Among them, E sdt represents the total shared energy storage capacity of the shared energy storage system at time t on the typical day d; represents the remaining shared energy storage capacity of the shared energy storage system at time t on the typical day d; represents the shared energy storage capacity leased by the target second user from the first user at time t on the typical day d based on the second package; represents the shared energy storage capacity leased by the target second user from the first user based on the second package at the preset initial time on the typical day d; represents the shared energy storage capacity leased by the target second user from the first user based on the second package at the preset end time of the typical day d; represents the total shared energy storage capacity of the shared energy storage system leased through the second package on the typical day d; Indicates the maximum value of the shared energy storage capacity of the shared energy storage system; represents the minimum value of the shared energy storage capacity of the shared energy storage system; represents the remaining shared energy storage capacity of the shared energy storage system at the preset initial time on the typical day d; represents the remaining shared energy storage capacity of the shared energy storage system at the preset end time of the typical day d; The energy storage supply and demand balance constraints corresponding to the first user include: in, represents the charging power constant value reported to the shared energy storage system at time t on the typical day d when the target second user selects the first package; represents the discharge power constant value reported to the shared energy storage system at time t on the typical day d when the target second user selects the first package; represents the charging power constant value reported to the shared energy storage system at time t on the typical day d when the target second user selects the second package; represents the discharge power constant value reported to the shared energy storage system at time t on the typical day d when the target second user selects the second package; represents the charging power constant value reported to the shared energy storage system at time t on the typical day d when the target second user selects the third package; represents the discharge power constant value reported to the shared energy storage system at time t on the typical day d when the target second user selects the third package; It represents the set value of the shared energy storage capacity rented from the first user on the typical day when the target second user selects the second package.

6. The method according to claim 5, characterized in that The step of establishing a lower-layer deterministic model corresponding to the target second user based on the investment and operation constraints, energy storage capacity constraints, energy storage power constraints, and actual output constraints corresponding to the target second user includes: Establishing an initial lower-layer deterministic model corresponding to the target second user; Based on the investment, construction and operation constraints, energy storage capacity constraints, energy storage power constraints and actual output constraints corresponding to the target second user, the initial lower-level deterministic model is constrained to obtain the lower-level deterministic model corresponding to the target second user.

7. The method according to claim 6, characterized in that The initial lower layer deterministic model corresponding to the target second user includes: α ndt ,β ndt ≥0； in, represents the total revenue of the target second user; Indicates the Internet access income of the target second user; represents the Internet access deviation penalty cost paid by the target second user; Indicates the investment and construction cost of the self-built energy storage of the target second user; represents the service fee paid by the target second user to the first user; Indicates the unit electricity selling price of the target second user; represents the Internet access power of the target second user at time t on the typical day d; P ndt represents the actual output parameter of the target second user at time t on the typical day d; represents the charging power of the target second user to the target second user's self-built energy storage at time t on the typical day d; represents the discharge power of the target second user to the target second user's self-built energy storage at time t on the typical day d; α nd t represents the first alternative decision variable of the target second user's Internet access power deviation; β ndt A second alternative decision variable representing the target second user's Internet access power deviation; α ndt and β ndt Always a positive number; Indicates the unit price of the target second user's Internet access deviation penalty; represents the power reported by the target second user to the shared energy storage system at time t on the typical day d; k represents the self-built energy storage of the target second user; represents the annual investment cost of the target second user for the self-built energy storage of the target second user; if the self-built energy storage of the target second user is in the investment state, then c k,n The value of is 1; if the self-built energy storage of the target second user is not yet built, then c k,n The value of is 0; represents the charging power of the target second user to the self-built energy storage of the target second user at time t on the typical day d; It represents the discharge power of the target second user to the self-built energy storage of the target second user at time t on the typical day d.

8. The method according to claim 7, characterized in that The investment and operation constraints corresponding to the target second user include: If the self-built energy storage of the target second user is in a charging state at time t on the typical day d, The value of is 1, The value of is 0; if the self-built energy storage of the target second user is in a discharging state at time t on the typical day d, The value of is 0, The value of is 1; The energy storage capacity constraints corresponding to the target second user include: AND k,nd0 =And k,ndT ; Among them, E k,ndt Represents the total shared energy storage capacity of the self-built energy storage of the target second user at time t on the typical day d; Indicates the charging efficiency of the self-built energy storage of the target second user; Indicates the discharge efficiency of the self-built energy storage of the target second user; represents the charging power of the self-built energy storage of the target second user at time t on the typical day d; represents the discharge power of the self-built energy storage of the target second user at time t on the typical day d; represents the minimum value of the shared energy storage capacity of the self-built energy storage of the target second user; represents the maximum value of the shared energy storage capacity of the self-built energy storage of the target second user; E k,nd0 represents the shared energy storage capacity of the self-built energy storage of the target second user at the preset initial time of the typical day d; E k,ndT Represents the shared energy storage capacity of the self-built energy storage of the target second user at the preset end time of the typical day d; The energy storage power constraint corresponding to the target second user includes: in, Indicates the minimum value of the charging power of the self-built energy storage of the target second user; Indicates the maximum value of the charging power of the self-built energy storage of the target second user; represents the minimum value of the discharge power of the self-built energy storage of the target second user; Indicates the maximum value of the discharge power of the self-built energy storage of the target second user; The actual output constraints corresponding to the target second user include: Wherein, κ represents the maximum power fluctuation percentage of the self-built energy storage of the target second user; Represents the installed capacity of the self-built energy storage of the target second user.

9. The method according to claim 8, characterized in that The uncertainty parameters of the new energy output include: in, represents the maximum offset of the target second user's new energy output from the predicted value at time t on the typical day d; t represents the uncertainty parameter at time t; The multi-package energy storage game robust optimization configuration model includes: Wherein, w represents an artificially controllable variable; the artificially controllable variable includes a state parameter for characterizing the investment and construction state of the shared energy storage system, and a state parameter for characterizing the investment and construction state of the self-built energy storage of the target second user; u represents an uncontrollable variable, and the uncontrollable variable includes an uncertainty parameter of the new energy output; Represents the optimization configuration strategy; G(w,u) represents the constraints of the multi-package energy storage game robust optimization configuration model; W represents the strategy set of the controllable variables; U represents the strategy set of the uncontrollable variables.

10. The method according to claim 9, characterized in that The step of determining the optimization configuration strategy for the first user and the target second user based on the multi-package energy storage game robust optimization configuration model includes: The multi-package energy storage game robust optimization configuration model is solved based on the particle swarm optimization algorithm to determine the optimization configuration strategy for the first user and the target second user.

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