Cooperative configuration processing method and device for power distribution network

Abstract

The specification provides a power distribution network collaborative configuration processing method and device. First, the network information of the target power distribution network, the associated information of the power grid company subject, and the associated information of the user side aggregator subject are acquired and constructed into a multi-subject planning model about the double-layer structure of the target power distribution network; wherein the multi-subject planning model at least includes: a first model layer and a second model layer, the first model layer is deployed with a flexible interconnection device configuration scheme planning model about the target power distribution network, and a user side resource configuration scheme planning model, the second model layer is deployed with a power grid company subject operation model, and a user side aggregator subject operation model; then according to the above multi-subject planning model, the matching target flexible interconnection device configuration scheme and target user side resource configuration scheme about the target power distribution network are determined by collaborative solving. Thus, it can be well adapted to the complex low-voltage area, and the precise configuration of the target power distribution network can be efficiently realized.

Description

Technical Field

[0001] This manual belongs to the field of power grid dispatching and planning technology, and in particular relates to the collaborative configuration processing methods and devices for distribution networks. Background Technology

[0002] With the advancement and development of low-carbon emission reduction efforts, distributed generation (DG) and new loads are beginning to be connected to the distribution network in large numbers, making the distribution network (especially the distribution network in low-voltage areas) relatively more complex. It is necessary to consider and take into account more and more complex situations and factors, which makes it difficult to efficiently and accurately realize the relevant configuration planning of the distribution network based on existing methods.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This specification provides a method and apparatus for collaborative configuration processing of distribution networks, which can be well adapted to low-voltage distribution areas with complex conditions and efficiently achieve accurate configuration of the target distribution network.

[0005] This specification provides a method for coordinated configuration processing of power distribution networks, including: Obtain network information of the target distribution network, associated information of the power grid company, and associated information of the user-side aggregator; wherein, the target distribution network belongs to a low-voltage distribution area; Based on the network information of the target distribution network, the association information of the power grid company, and the association information of the user-side aggregator, a multi-agent planning model for the two-layer structure of the target distribution network is constructed. The multi-agent planning model includes at least a first model layer and a second model layer. The first model layer deploys a planning model for the flexible interconnection device configuration scheme of the target distribution network and a planning model for the user-side resource configuration scheme. The second model layer deploys an operation model for the power grid company and an operation model for the user-side aggregator. The power grid company is the leader of the model, and the user-side aggregator is the follower of the model. According to the preset transformation rules, the transformed multi-agent programming model is obtained by transforming the follower-related models in the multi-agent programming model into corresponding equilibrium constraints. Based on the transformed multi-agent planning model, a collaborative solution is performed to determine the matching target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network.

[0006] In one embodiment, constructing a multi-agent planning model for the two-layer structure of the target distribution network based on the network information of the target distribution network, the association information of the power grid company entity, and the association information of the user-side aggregator entity includes: Based on the network information of the target distribution network, the correlation information of the power grid company, and the correlation information of the user-side aggregator, a multi-agent planning model framework based on a game-theoretic interaction model is constructed; and the power grid company is set as the leader of the model, and the user-side aggregator is set as the follower of the model. In the first model layer of the multi-agent planning model framework, a flexible interconnection device configuration scheme planning model is constructed by constructing a first objective function and a first constraint condition for the flexible interconnection device; simultaneously, a user-side resource allocation scheme planning model is constructed by constructing a second objective function and a second constraint condition for the user-side resource demand; wherein, the first objective function includes at least: a planning cost item for the flexible interconnection device, a maintenance cost item for the flexible interconnection device, and a carbon emission cost item for the power grid company entity based on the flexible interconnection device; In the second model layer of the multi-agent planning model framework, a power grid company operation model is constructed by establishing a third objective function and a third constraint condition for the operation of the power grid company. Simultaneously, a user-side aggregator operation model is constructed by establishing a fourth objective function and a fourth constraint condition for the operation of the user-side aggregator.

[0007] In one embodiment, the first objective function is constructed according to the following formula:

[0008] in, The value of the first objective function. For the planning cost item of flexible interconnect devices, For maintenance costs of flexible interconnect devices, For the carbon emission cost item of the main body of the power grid company based on flexible interconnection devices, d For the discount rate, y For the service life of flexible interconnect devices, The price per unit capacity of flexible interconnect devices, For installation on the node i The capacity of flexible interconnect devices, i Number the nodes in the target distribution network. N The total number of nodes equipped with flexible interconnect devices. This represents the annual operating and maintenance cost coefficient for flexible interconnect devices, etc. For carbon trading prices, For the number m The number of days included in a quarter. T The number of carbon emission moments per day, where m is the quarter number. For the upper-level power grid t The average carbon intensity coefficient at any given time. For the main body of the power grid companyt The power purchased from the upper-level power grid at all times.

[0009] In one embodiment, the first constraint is constructed as follows: Based on the network information of the target distribution network, construct the low-voltage distribution area power constraint term and the low-voltage flexible interconnection device installation location constraint term for the target distribution network; Based on the interaction relationships between flexible interconnect devices at different installation locations, construct corresponding low-voltage flexible interconnect device constraint terms; Based on the attribute parameters of the flexible interconnection device, construct the power loss constraint term of the flexible interconnection device, the capacity constraint term of the low-voltage flexible interconnection device, and the active power and reactive power constraint terms of the low-voltage flexible interconnection device respectively. By combining the low-voltage distribution area power constraint, the low-voltage flexible interconnection device installation location constraint, the low-voltage flexible interconnection device constraint, the flexible interconnection device power loss constraint, the low-voltage flexible interconnection device capacity constraint, and the low-voltage flexible interconnection device active power and reactive power constraint, the first constraint condition is constructed.

[0010] In one embodiment, constructing the installation location constraints for the low-voltage flexible interconnection device of the target distribution network based on the network information of the target distribution network includes: The installation location constraints for low-voltage flexible interconnect devices are constructed according to the following formula:

[0011] in, For the target distribution network i Indicator information indicating whether the node is equipped with a flexible interconnect device. The set of nodes in the target distribution network suitable for installing flexible interconnection devices. This represents the upper limit on the number of flexible interconnection devices to be installed in the target distribution network.

[0012] In one embodiment, constructing the low-voltage distribution area power constraint term for the target distribution network based on the network information of the target distribution network includes: Construct the low-voltage distribution area power constraint terms according to the following formula:

[0013] in, For the target distribution network i node t The active power injected at all times, For the target distribution network i node t The reactive power injected at all times For flexible interconnect devices located in iConverter at the node t Constant input / output active power For flexible interconnect devices located in i Converter at the node t Constant input / output reactive power Let be the active power of the energy storage system at node i at time t during discharge / charge. For the target distribution network i node t Active load at any given time For the target distribution network i node t Reactive load at all times This refers to the rated capacity of the transformer.

[0014] In one embodiment, the second objective function is constructed according to the following formula:

[0015] in, The value of the second objective function. The indication information is either 0 or 1, used to indicate whether the power grid company has selected node users in the target distribution network. i Demand-side resources S For the set of nodes in the target distribution network, The unit capacity cost of demand-side resources. For node users i Reserved response capacity.

[0016] In one embodiment, the user-side aggregator also integrates a distributed power operator, and correspondingly, the fourth objective function is constructed according to the following formula:

[0017] in, The revenue generated from electricity sales by the user-side aggregator to the power grid company. The cost of electricity purchased by the user-side aggregator from the power grid company. The cost per unit power for charging source-side energy storage. Let m be the charging power of the source-side energy storage at time t in the quarter numbered m. The cost per unit power of source-side energy storage discharge. Let be the discharge power of the source-side energy storage at time t in quarter numbered m. For a set of user nodes containing distributed power sources, This represents the unit electricity price at which the power grid company purchases electricity from the user-side aggregator at time t within quarter m. This represents the amount of electricity purchased by the power grid company from the user-side aggregator at time t in quarter number m. A set of user nodes with demand response capabilities. k This represents a user comfort function in response to load shifting. Let m be the net load power of the user at time t in quarter m. This represents the unit electricity price that the power grid company sells to nodal users at time t within quarter numbered m. This represents the amount of electricity sold by the power grid company to the node user numbered i at time t within a quarter numbered m. T The total number of moments in a day.

[0018] In one embodiment, after jointly solving for the matching target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network based on the transformed multi-agent planning model, the method further includes: Based on the target flexible interconnection device configuration scheme, a matching target location point is determined in the target distribution network; and a flexible interconnection device with a matching capacity is installed at the target location point. Based on the target user-side resource configuration scheme, identify the matching target node users in the target distribution network; and set the reserved response capacity matching the target node users.

[0019] This specification also provides a collaborative configuration processing device for a distribution network, including: The acquisition module is used to acquire network information of the target distribution network, the associated information of the power grid company, and the associated information of the user-side aggregator; wherein the target distribution network belongs to a low-voltage distribution area. A construction module is used to construct a multi-agent planning model for the two-layer structure of the target distribution network based on the network information of the target distribution network, the association information of the power grid company, and the association information of the user-side aggregator. The multi-agent planning model includes at least a first model layer and a second model layer. The first model layer deploys a planning model for the flexible interconnection device configuration scheme of the target distribution network and a planning model for the user-side resource configuration scheme. The second model layer deploys an operation model for the power grid company and an operation model for the user-side aggregator. The power grid company is the leader of the model, and the user-side aggregator is the follower. The transformation module is used to transform the follower-related models in the multi-agent programming model into corresponding equilibrium constraints according to preset transformation rules, so as to obtain the transformed multi-agent programming model. The determination module is used to collaboratively solve the transformed multi-agent planning model to determine the matching target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network.

[0020] Based on the distribution network collaborative configuration processing method and apparatus provided in this specification, the network information of the target distribution network, the association information of the power grid company entity, and the association information of the user-side aggregator entity are first obtained. Then, based on the network information of the target distribution network, the association information of the power grid company entity, and the association information of the user-side aggregator entity, a multi-agent planning model for the two-layer structure of the target distribution network is constructed. The multi-agent planning model includes at least a first model layer and a second model layer. The first model layer deploys a flexible interconnection device configuration scheme planning model and a user-side resource configuration scheme planning model for the target distribution network. The second model layer deploys a power grid company entity operation model and a user-side aggregator entity operation model. The power grid company entity is the leader of the model, and the user-side aggregator entity is the follower of the model. According to a preset transformation rule, the multi-agent planning model is obtained by transforming the models related to the followers in the multi-agent planning model into corresponding equilibrium constraints. Based on the transformed multi-agent planning model, joint solutions are performed to determine the matching target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network. This allows for better adaptation to complex low-voltage distribution areas, effectively integrating the different situations and needs of both the power grid company and the user-side aggregator. It also helps to determine a target flexible device configuration scheme and a target user-side resource configuration scheme that can take into account the interests of all parties, achieve good results, and are mutually compatible, thus efficiently realizing the precise configuration of the target distribution network. Attached Figure Description

[0021] To more clearly illustrate the embodiments of this specification, the accompanying drawings used in the embodiments will be briefly introduced below. The drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating a method for collaborative configuration processing of a power distribution network provided in one embodiment of this specification. Figure 2 This is a schematic diagram of one embodiment of the collaborative configuration processing method for power distribution networks provided in this specification, applied in a scenario example. Figure 3 This is a schematic diagram of one embodiment of the collaborative configuration processing method for power distribution networks provided in this specification, applied in a scenario example. Figure 4This is a schematic diagram of the structural composition of a server provided in one embodiment of this specification; Figure 5 This is a schematic diagram of the structural composition of a distribution network collaborative configuration processing device provided in one embodiment of this specification; Figure 6 This is a schematic diagram of one embodiment of the collaborative configuration processing method for power distribution networks provided in this specification, applied in a scenario example. Figure 7 This is a schematic diagram of one embodiment of the collaborative configuration processing method for power distribution networks provided in the embodiments of this specification, applied in a scenario example. Detailed Implementation

[0023] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0024] It should be noted that the information and data related to users involved in the embodiments of this specification are all information and data authorized by the user or fully authorized by the relevant parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of the relevant data all comply with relevant laws, regulations, and standards, and necessary confidentiality measures have been taken. They do not violate public order and good morals, and corresponding operation entry points are provided for users or relevant parties to choose to authorize or refuse.

[0025] It should also be noted that in the embodiments of this specification, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0026] See Figure 1 As shown in the embodiments of this specification, a collaborative configuration processing method for a power distribution network is provided, wherein the method is specifically applied to the server side. In specific implementation, the method may include the following: S101: Obtain network information of the target distribution network, association information of the power grid company, and association information of the user-side aggregator; wherein, the target distribution network belongs to a low-voltage distribution area; S102: Based on the network information of the target distribution network, the association information of the power grid company, and the association information of the user-side aggregator, a multi-agent planning model for the two-layer structure of the target distribution network is constructed; wherein, the multi-agent planning model includes at least: a first model layer and a second model layer, the first model layer deploying a planning model for the flexible interconnection device configuration scheme of the target distribution network and a planning model for the user-side resource configuration scheme, the second model layer deploying a power grid company operation model and a user-side aggregator operation model; the power grid company is the leader of the model, and the user-side aggregator is the follower of the model; S103: According to the preset transformation rules, the transformed multi-agent programming model is obtained by transforming the follower-related models in the multi-agent programming model into corresponding equilibrium constraints. S104: Based on the transformed multi-agent planning model, perform collaborative solving to determine the matching target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network.

[0027] Specifically, the aforementioned target distribution network can be understood as a network comprising multiple low-voltage distribution areas to be configured. These low-voltage distribution areas can be further understood as low-voltage regions in the power system supplied to users by distribution transformers.

[0028] It should be noted that the aforementioned low-voltage distribution areas often connect to a large number of different types of users, resulting in a relatively large and complex distribution network structure. Furthermore, the significant differences in electricity demand and usage patterns among different types of users (including industrial, commercial, and residential users) further complicate grid configuration. Additionally, meeting carbon conservation and emission reduction requirements necessitates consideration of carbon emission costs, further increasing the difficulty of grid configuration.

[0029] To address the aforementioned problems and their root causes, this application proposes a game-theoretic interaction model to construct a two-layer multi-agent planning model for the target distribution network. In the first model layer (or configuration layer) of this multi-agent planning model, a flexible interconnection device configuration scheme planning model and a user-side resource configuration scheme planning model for the target distribution network are constructed and deployed. In the second model layer (or operation layer), a power grid company entity operation model and a user-side aggregator entity operation model are constructed and deployed. Simultaneously, the power grid company entity is designated as the leader of the model, and the user-side aggregators entity as followers. Based on this multi-agent planning model, with the power grid company entity playing a dominant role in the target distribution network as the leader and the user-side entities as followers, the model comprehensively considers the situations and needs of the power grid company entity and the user-side aggregators entity, as well as their mutual influence relationships, to collaboratively solve the problem. This allows for the determination of a target flexible interconnection device configuration scheme and a target user-side resource configuration scheme that effectively balances the interests of all parties and is mutually compatible, thereby efficiently and accurately achieving the configuration planning of the target distribution network.

[0030] The aforementioned target distribution network can be equipped with corresponding flexible interconnection devices.

[0031] The aforementioned flexible interconnection device can be understood as a power electronic device based on flexible DC transmission technology. It is mainly used for interconnection of multiple low-voltage distribution substations in the distribution network. It realizes functions such as power mutual assistance, dynamic capacity expansion and rapid fault transfer between substations through the DC bus. Its core principle is to use bidirectional back-to-back AC / DC converters or DC links for "soft" connection, thereby realizing precise power flow control and electrical decoupling.

[0032] Specifically, the aforementioned flexible interconnection device may include a flexible tie switch (SOP). The flexible tie switch (SOP) can be understood as a new type of intelligent power electronic device installed in the location of a traditional tie switch. It belongs to the intelligent soft switch type and can replace the traditional tie switch to achieve flexible closed-loop operation of the distribution network. This device specifically adopts a back-to-back voltage source converter structure, consisting of two symmetrical three-phase voltage source PWM converters connected through a DC capacitor, and has functions such as real-time adjustment of active / reactive power between feeders and providing reactive power support voltage.

[0033] In practical implementation, flexible interconnection devices can be introduced and used in the target distribution network to achieve flexible interconnection of multiple adjacent low-voltage distribution areas. By constructing an interconnection system with flexible interconnection devices as the core in the target distribution network, a closed-loop structure that enables bidirectional, flexible, and controllable power transfer can be formed. Based on this structure, the power transmission barriers between traditional distribution areas can be broken, significantly enhancing the system's regulation capability and operational flexibility.

[0034] The aforementioned power grid companies are specifically responsible for managing and operating the target distribution network, and for planning the location and capacity of flexible interconnection devices in the target distribution network.

[0035] Specifically, the aforementioned power grid company can be understood as an integration platform for various elements, primarily responsible for the planning and operation of the target distribution network, as well as the internal optimization and coordination of the distribution market. Under the premise of ensuring the safe and reliable operation of the system, the power grid company profits by earning the price difference between purchasing and selling electricity between the upstream power grid and user-side aggregators.

[0036] The aforementioned user-side aggregator directly connects to the user side and is responsible for configuring the relevant resources required by the user. To enable more realistic planning, the aforementioned user-side aggregator can also integrate distributed generation (DG) operators.

[0037] Specifically, the aforementioned user-side aggregators can generate revenue by purchasing and selling electricity from the power grid company, aiming to maximize profits. In order to increase the amount of electricity sold and avoid passive power curtailment, they can also configure energy storage according to the relevant requirements of the power grid company, thus possessing a certain degree of regulation capability. Furthermore, they can also have a certain degree of demand response capability based on the electricity consumption habits of users.

[0038] The network information of the target distribution network may specifically include: network structure parameters of the target distribution network (e.g., the topology of the target distribution network, the number and location of nodes in the target distribution network, and the number and location of nodes suitable for installing flexible interconnection devices, etc.), operating parameters of each node in the target distribution network, attribute parameters of transformers in the target distribution network (e.g., rated capacity of transformers, etc.), etc.

[0039] The related information of the aforementioned power grid company entity may specifically include: cost information of the power grid company entity installing flexible interconnection devices, cost information of the power grid company entity maintaining flexible interconnection devices, carbon emission information of the power grid company entity, and interaction information between the power grid company entity and the superior power grid, etc.

[0040] The associated information of the aforementioned user-side aggregator entity may specifically include: user attribute parameters of the node users covered by the user-side aggregator entity (e.g., user's electricity consumption type, user's electricity consumption prediction characteristics, etc.), interaction information between the user-side aggregator entity and the power grid company entity (e.g., the electricity purchase cost of the user-side aggregator entity from the power grid company entity), charging and discharging power information involved by the user-side aggregator entity, etc.

[0041] The aforementioned multi-agent programming model can be understood as a two-tiered multi-agent programming model based on a game theory model. For details, please refer to [reference needed]. Figure 2 As shown.

[0042] Specifically, the aforementioned game theory model can be a Stackelberg model, which can be a type of output leadership model. Based on this model, the dependencies and influences between the power grid company (the main entity in the distribution network) and the user-side aggregator (the main entity in the user-side aggregator) when making decisions regarding the configuration of flexible interconnection devices can be analyzed using a leader-follower paradigm. This allows for full interaction between the two parties during the solution process, ultimately determining a suitable target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network that simultaneously considers the interests and needs of all parties.

[0043] In practice, after obtaining the network information of the target distribution network, the associated information of the power grid company, and the associated information of the user-side aggregator, the above data information can be cleaned and normalized to obtain the network information of the target distribution network, the associated information of the power grid company, and the associated information of the user-side aggregator that meet the requirements. Then, based on the above data information, the corresponding parameter information can be extracted as model parameters for constructing a multi-agent planning model. Based on the above model parameters and combined with the modeling rules of the corresponding game interaction model, a multi-agent planning model for the two-layer structure of the target distribution network can be constructed.

[0044] In practical implementation, considering that in interactive activities surrounding the target distribution network, the user-side aggregator, as a follower, is more influenced by the leader, the power grid company, its behavior can be altered. Therefore, based on preset transformation rules, the follower-related models in the multi-agent programming model can be transformed into corresponding equilibrium constraints. This simplifies the original complex two-layer model into a single-layer, solvable optimization model, resulting in the transformed multi-agent programming model. Specifically, the preset transformation rules can be model transformation rules based on KKT conditions.

[0045] The aforementioned Kuhn-Tucker (KKT) conditions can be understood as necessary conditions for determining a point in a nonlinear programming problem as an extreme point, and also sufficient conditions when the programming problem is convex. These conditions require that the objective function and constraint functions be continuously differentiable. A system of equations is constructed by introducing nonnegative multipliers, including complementary relaxation conditions, and the multipliers are nonzero only when the constraints are in effect. When the objective function is convex, the inequality constraints are convex, and the equality constraints are affine functions, the feasible point satisfying these conditions is the global minimum. The aforementioned KKT conditions include primal feasibility, dual feasibility, complementary relaxation conditions, and gradient conditions.

[0046] In practice, according to the preset transformation rules, the minimum value problem in the original follower-related model is transformed into a maximum value problem by introducing dual variables through the use of KKT conditions. A Lagrangian function is constructed to make the running model of the follower (user-side aggregator) in the lower layer (i.e., the second model layer) equivalent to the equilibrium constraint of the upper layer (i.e., the first model layer), thus obtaining the transformed multi-agent programming model.

[0047] For the transformed multi-agent programming model, nonlinear constraints are handled using polyhedral linearization techniques, and bilinear terms are processed to eliminate partial linearity, further transforming it into a MILP (Mixed Integer Linear Programming) problem. Then, a corresponding solver (e.g., the CPLEX solver) is used for specific solution, thereby achieving efficient and accurate collaborative solution, and determining the matching target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network.

[0048] Based on the above embodiments, by constructing and solving a multi-agent planning model for the two-layer structure of the target distribution network, the different situations and needs of the power grid company and the user-side aggregator can be effectively considered. In this way, the target flexible device configuration scheme and the target user-side resource configuration scheme that can take into account the interests of all parties and achieve better results can be determined simultaneously, so as to efficiently realize the accurate configuration of the target distribution network.

[0049] In some embodiments, see Figure 3 As shown, the construction of a multi-agent planning model for the two-layer structure of the target distribution network, based on the network information of the target distribution network, the association information of the power grid company, and the association information of the user-side aggregator, can specifically include the following: S1: Based on the network information of the target distribution network, the association information of the power grid company, and the association information of the user-side aggregator, construct a multi-agent planning model framework based on a game-theoretic interaction model; and set the power grid company as the leader of the model and the user-side aggregator as the follower of the model. S2: In the first model layer of the multi-agent planning model framework, a flexible interconnection device configuration scheme planning model is constructed by constructing a first objective function and a first constraint condition for the flexible interconnection device; simultaneously, a user-side resource allocation scheme planning model is constructed by constructing a second objective function and a second constraint condition for the user-side resource demand; wherein, the first objective function includes at least: a planning cost item for the flexible interconnection device, a maintenance cost item for the flexible interconnection device, and a carbon emission cost item for the power grid company entity based on the flexible interconnection device; S3: In the second model layer of the multi-agent planning model framework, a power grid company main operation model is constructed by constructing a third objective function and a third constraint condition for the main operation of the power grid company; at the same time, a user-side aggregator main operation model is constructed by constructing a fourth objective function and a fourth constraint condition for the main operation of the user-side aggregator.

[0050] Based on the above embodiments, the network information of the target distribution network, the associated information of the power grid company, and the associated information of the user-side aggregator can be fully utilized to construct a multi-entity planning model that is suitable for low-voltage distribution areas with complex situations and has good results.

[0051] In some embodiments, the first objective function can be specifically constructed according to the following formula:

[0052] in, The value of the first objective function. For the planning cost item of flexible interconnect devices, For maintenance costs of flexible interconnect devices, For the carbon emission cost item of the main body of the power grid company based on flexible interconnection devices, d For the discount rate, y For the service life of flexible interconnect devices, The price per unit capacity of flexible interconnect devices, For installation on the node i The capacity of flexible interconnect devices, i Number the nodes in the target distribution network. N The total number of nodes equipped with flexible interconnect devices. This represents the annual operating and maintenance cost coefficient for flexible interconnect devices, etc. For carbon trading prices, For the number m The number of days included in a quarter. T The number of carbon emission moments per day, where m is the quarter number. For the upper-level power grid t The average carbon intensity coefficient at any given time. For the main body of the power grid company t The power purchased from the upper-level power grid at all times.

[0053] The aforementioned carbon emission information (including the number of carbon emission moments per day, average carbon emission intensity coefficient, and carbon trading price) can be determined as follows: Obtain carbon emission experimental test records from a sample distribution network similar to the target distribution network, along with relevant experimental test environment information; obtain weather information, user electricity consumption information, and geographical location information of the low-voltage distribution area to which the target distribution network belongs as background environment information; analyze and learn from the carbon emission experimental test records of the sample distribution network to determine the initial carbon emission information; then, based on the experimental test environment information, determine the statistical results of the test environment characteristic distribution through data statistics; based on the background environment information of the target distribution network, determine the statistical results of the background environment characteristic distribution of the target distribution network through data statistics; based on the statistical results of the test environment characteristic distribution and the statistical results of the background environment characteristic distribution of the target distribution network, determine the corresponding fitting mapping relationship through data fitting; and adjust and correct the initial carbon emission information according to this fitting mapping relationship to obtain the required carbon emission information for the target distribution network.

[0054] Based on the above embodiments, the specific scenarios faced by the target distribution network can be fully considered, and the characteristics of the flexible interconnection device and the specific requirements for carbon emissions can be combined to accurately construct the first objective function for the flexible interconnection device.

[0055] In some embodiments, the first constraint condition can be specifically constructed in the following manner: S1: Based on the network information of the target distribution network, construct the low-voltage distribution area power constraint term and the low-voltage flexible interconnection device installation location constraint term for the target distribution network; S2: Based on the interaction between flexible interconnect devices at different installation locations, construct corresponding low-voltage flexible interconnect device constraint terms; S3: Obtain and construct power loss constraints for flexible interconnection devices, capacity constraints for low-voltage flexible interconnection devices, and active and reactive power constraints for low-voltage flexible interconnection devices based on the attribute parameters of the flexible interconnection devices. S4: By combining the low-voltage distribution area power constraint, the low-voltage flexible interconnection device installation location constraint, the low-voltage flexible interconnection device constraint, the flexible interconnection device power loss constraint, the low-voltage flexible interconnection device capacity constraint, and the low-voltage flexible interconnection device active power and reactive power constraint, the first constraint condition is constructed.

[0056] Based on the above embodiments, the working characteristics of the flexible interconnection device and the operating characteristics of the low-voltage distribution area can be comprehensively considered to accurately construct a more comprehensive and effective first constraint condition for the flexible interconnection device.

[0057] In some embodiments, constructing the installation location constraints for the low-voltage flexible interconnection device of the target distribution network based on the network information of the target distribution network may specifically include: The installation location constraints for low-voltage flexible interconnect devices are constructed according to the following formula:

[0058] in, For the target distribution network i Indicator information indicating whether the node is equipped with a flexible interconnect device. The set of nodes in the target distribution network suitable for installing flexible interconnection devices. This represents the upper limit on the number of flexible interconnection devices to be installed in the target distribution network.

[0059] Specifically, when This indicates that a flexible interconnection device is installed at node i in the target distribution network, when This indicates that node i in the target distribution network does not have a flexible interconnection device installed.

[0060] In some embodiments, constructing a low-voltage distribution area power constraint term for the target distribution network based on the network information of the target distribution network may specifically include: Construct the low-voltage distribution area power constraint terms according to the following formula:

[0061] in, For the target distribution network i node t The active power injected at all times, For the target distribution network i node t The reactive power injected at all times For flexible interconnect devices located in i Converter at the node t Constant input / output active power For flexible interconnect devices located in i Converter at the node t Constant input / output reactive power Let be the active power of the energy storage system at node i at time t during discharge / charge. For the target distribution network i node t Active load at any given time For the target distribution network i node t Reactive load at all times This refers to the rated capacity of the transformer.

[0062] In some embodiments, the corresponding low-voltage flexible interconnect device constraint terms can be constructed according to the following formula:

[0063] in, For flexible interconnect devices located in i Converter at the node t Constant input / output active power For flexible interconnect devices located in i Converter at the node t There is always power loss. For flexible interconnect devices located in j Converter at the node t Constant input / output active power For flexible interconnect devices located in j Converter at the node t There is always power loss.

[0064] In some embodiments, the power loss constraint term of the flexible interconnect device can be constructed according to the following formula:

[0065] in, This represents the power loss factor of the flexible interconnect device.

[0066] In some embodiments, the capacity constraint term of the low-voltage flexible interconnect device can be constructed according to the following formula:

[0067] in, For flexible interconnect devices located in i The rated capacity of the VSC at the node, For flexible interconnect devices located in j The rated capacity of the VSC at the node, where VSC is a voltage source converter.

[0068] In some embodiments, the active and reactive power constraints of the low-voltage flexible interconnect device can be constructed according to the following formula:

[0069] in, This represents the upper limit of the active power output for flexible interconnect devices. This refers to the upper limit of reactive power operation for the flexible interconnection device. The specific upper limits of active power and reactive power operation for the flexible interconnection device can be determined through prior experimental testing of the device.

[0070] In some embodiments, the second objective function is constructed according to the following formula:

[0071] in, The value of the second objective function. The indication information is either 0 or 1, used to indicate whether the power grid company has selected node users in the target distribution network. i Demand-side resources S For the set of nodes in the target distribution network, The unit capacity cost of demand-side resources. For node users i Reserved response capacity.

[0072] Specifically, when When the value is 1, it indicates that the power grid company has selected the demand-side resources for user i at node i in the target distribution network; conversely, when... When the value is 0, it indicates that the power grid company has not selected the demand-side resources of node user i in the target distribution network.

[0073] Based on the above embodiments, the specific scenarios faced by user-side aggregators can be fully considered, and a second objective function with better performance regarding user-side resource requirements can be accurately constructed.

[0074] In some embodiments, the second constraint can be constructed as follows:

[0075] in, For node users t Actual response power at any time The deviation range of the node user's response. For the main body of the power grid company t Power scheduling at any given time. The specific deviation range of the above-mentioned node user response can be determined by statistical learning from a large amount of historical node user response power data, combined with the user type of the node user.

[0076] It should be noted that the power grid company mainly manages the demand-side resources of users through demand response (DR), so the response characteristics of demand-side resources are closely related to the demand response mode.

[0077] The aforementioned incentive-based demand-side response (DR) specifically refers to user behavior that changes the inherent electricity consumption patterns of node users under the influence of the power grid company's incentive mechanism, thereby reducing or shifting electricity load during a certain period. It is often used in demand-side resource planning problems. However, due to the uncertainty of user response willingness, the response results of demand-side resources may deviate from the main dispatch plan of the power grid company.

[0078] Therefore, this is where the node user response power is measured. Dispatch is considered to be carried out by the power grid company. Using this as the primary reference, and taking into account specific user types, a matching response method is adopted, fluctuating within a certain proportion range.

[0079] It is important to emphasize that different types of node users exhibit significantly different load response characteristics due to their varying electricity consumption patterns. Specifically, industrial users' industrial loads primarily consist of assembly line operations with fixed processes, and their response mode is mainly load shifting; commercial users' commercial loads mainly consist of temperature control and lighting loads, and their response mode is mainly load reduction; residential users' residential loads mainly consist of household appliance loads, and their response mode is mainly load reduction. In other words, industrial users' response mode is load shifting (or load that can be shifted), while residential and commercial users' response mode is load reduction (or load that can be reduced).

[0080] Specifically, different response models can be built for different types of node users, such as load shifting and load reduction in demand-side resources.

[0081] In practical implementation, for industrial users, the load shifting response model can be constructed according to the following formula:

[0082] in, Let be the active power of the load shifted at time t in the kth stage; M represents the load transfer duration, where M is the total process time for the load transfer. The unit electricity subsidy for load shifting, This is a subsidy for the total electricity consumption of shiftable loads within the dispatch cycle. For markets with a scheduling cycle, such as 1 hour.

[0083] For residential or commercial users, the load reduction response model can be constructed using the following formula:

[0084] in, The active power of the load is reduced at time t. The set of operating times of the target distribution network. To reduce the total load during the scheduling cycle, To reduce the unit electricity subsidy for load reduction, To reduce the total electricity subsidy for load during the dispatch cycle.

[0085] In practice, a matching response model can be selected based on the user type of the node user to determine the deviation range of the node user's response and set a second constraint. Simultaneously, the second objective function can be adjusted for adaptability by selecting a matching response model based on the user type of the node user.

[0086] In some embodiments, the third objective function can be constructed as follows:

[0087] Where x is the decision variable vector of the power grid company (corresponding to the configuration scheme of the flexible interconnection device), and the electricity trading price of a typical day in each quarter of the year is selected as the electricity trading price for each quarter. For the number m The number of days included in a quarter. T The number of time intervals in a day; N The number of node users (including load users and distributed power operators). For the main body of the power grid company in the quarter numbered m t The unit price of electricity sold to node users at any given time. For the main body of the power grid company in the quarter numbered m t Time to number i The amount of electricity sold by the node users. For the main body of the power grid company in the quarter numbered m t The unit price of electricity purchased from the superior power grid at all times. For the main body of the power grid company in the quarter numbered m t The amount of electricity purchased from the upper-level power grid at all times. For the main body of the power grid company in the quarter numbered m t The price per unit of electricity sold to the higher-level power grid at all times. This represents the amount of electricity sold by the power grid company to its superior power grid at time t within the quarter numbered m. This represents the unit electricity price at which the power grid company purchases electricity from the user-side aggregator at time t within quarter m. This represents the amount of electricity purchased by the power grid company from the user-side aggregator at time t in quarter number m. Let be the total planning cost of the power grid company, corresponding to the value of the first objective function. , , These are, respectively, user node sets containing distributed power sources, user node sets with demand response capabilities, and user node sets without demand response capabilities.

[0088] In some embodiments, the third constraint can be constructed as follows: Electricity price constraints: .

[0089] Power balance constraints of power grid companies: .

[0090] Distribution network power flow constraints: For nodes j and branch roads ij of t At any given time, the following constraints apply, among which It represents the number of hours in each day of the year.

[0091] .

[0092] .

[0093] Branch voltage constraints: .

[0094] Node voltage constraints: .

[0095] Branch capacity constraints: .

[0096] In some embodiments, the user-side aggregator entity also integrates a distributed power operator, and correspondingly, the fourth objective function can be constructed according to the following formula:

[0097] in, The revenue generated from electricity sales by the user-side aggregator to the power grid company. The cost of electricity purchased by the user-side aggregator from the power grid company. The cost per unit power for charging source-side energy storage. Let m be the charging power of the source-side energy storage at time t in the quarter numbered m. The cost per unit power of source-side energy storage discharge. Let be the discharge power of the source-side energy storage at time t in quarter numbered m. For a set of user nodes containing distributed power sources, This represents the unit electricity price at which the power grid company purchases electricity from the user-side aggregator at time t within quarter m. This represents the amount of electricity purchased by the power grid company from the user-side aggregator at time t in quarter number m. A set of user nodes with demand response capabilities. k This represents a user comfort function in response to load shifting. Let m be the net load power of the user at time t in quarter m. This represents the unit electricity price that the power grid company sells to nodal users at time t within quarter numbered m. This represents the amount of electricity sold by the power grid company to the node user numbered i at time t within a quarter numbered m. T The total number of moments in a day.

[0098] In specific implementation, the above It can be expressed as follows:

[0099] in, Let m be the load power to the user at node i at time t in quarter m. The distributed power generation capacity at time t in quarter m is the power generated by the distributed power source to node i.

[0100] Based on the above embodiments, the specific scenarios faced by user-side aggregators can be fully considered, and a more comprehensive and accurate fourth objective function adapted to complex low-voltage distribution areas can be accurately constructed.

[0101] In some embodiments, the fourth constraint described above includes at least the source-side energy storage operation constraint.

[0102] The aforementioned source-side energy storage operation constraints mainly include: charging and discharging power limit constraints, energy storage state constraints, scheduling cycle capacity balance constraints, and power balance constraints. Correspondingly, the fourth constraint can be constructed according to the following formula:

[0103] in, The maximum charging power for energy storage on the source side; The maximum discharge power of the energy stored on the source side. Let m be the amount of energy stored at time t in quarter m. The charging efficiency of source-side energy storage. The discharge efficiency of energy storage on the source side. For a unit of time period; The minimum amount of electricity allowed for energy storage. The maximum allowable amount of energy storage. This refers to the power generation capacity of distributed power sources in the user-side aggregator.

[0104] Furthermore, the fourth constraint mentioned above can also include response capacity constraints and load transfer constraints, which can be constructed according to the following formula:

[0105] In the above formula, the first formula means that the load adjustment capacity does not exceed the response capacity, the second formula means that the basic load cannot be reduced or the upper limit cannot be exceeded, and the third formula means that the total load after the transfer is guaranteed to be no less than the user's original demand.

[0106] Furthermore, the fourth constraint can also include a piecewise linearization constraint term generated by piecewise linearization of the comfort function involved in the fourth objective function, as shown below: .

[0107] In some embodiments, after jointly solving for the matching target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network based on the transformed multi-agent planning model, the method may further include the following: S1: Based on the target flexible interconnection device configuration scheme, determine the matching target location point in the target distribution network; and install a flexible interconnection device with matching capacity at the target location point; S2: Based on the target user-side resource configuration scheme, identify the matching target node user in the target distribution network; and set the reserved response capacity matching the target node user.

[0108] Based on the above embodiments, the configuration of the corresponding flexible interconnection devices and the resource configuration of the node users can be carried out simultaneously according to the target flexible interconnection device configuration scheme and the target user-side resource configuration scheme, thereby achieving efficient and accurate configuration for the target distribution network.

[0109] As can be seen from the above, the collaborative configuration processing method for distribution networks provided in the embodiments of this specification first obtains the network information of the target distribution network, the association information of the power grid company entity, and the association information of the user-side aggregator entity; then, based on the network information of the target distribution network, the association information of the power grid company entity, and the association information of the user-side aggregator entity, a multi-agent planning model for the two-layer structure of the target distribution network is constructed; wherein, the multi-agent planning model includes at least: a first model layer and a second model layer, the first model layer deploys a flexible interconnection device configuration scheme planning model and a user-side resource configuration scheme planning model for the target distribution network, and the second model layer deploys a power grid company entity operation model and a user-side aggregator entity operation model; the power grid company entity is the leader of the model, and the user-side aggregator entity is the follower of the model; according to the preset transformation rules, the multi-agent planning model is obtained by transforming the models related to the followers in the multi-agent planning model into corresponding equilibrium constraints; based on the transformed multi-agent planning model, joint solution is performed to determine the matching target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network. This allows it to be well adapted to low-voltage distribution areas with complex conditions, effectively integrate the different situations and needs of the power grid company and the user-side aggregator, and determine the target flexible device configuration scheme and the target user-side resource configuration scheme that can take into account the interests of all parties and achieve good results, so as to efficiently realize the precise configuration of the target distribution network.

[0110] This specification provides an embodiment of a server, see below. Figure 4 As shown. The server includes a network communication port 401, a processor 402, and a memory 403. These structures are connected by internal cables so that they can perform specific data interaction.

[0111] Specifically, the network communication port 401 can be used to obtain network information of the target distribution network, the associated information of the power grid company, and the associated information of the user-side aggregator; wherein the target distribution network belongs to a low-voltage distribution area.

[0112] The processor 402 is specifically used to construct a multi-agent planning model for a two-layer structure of the target distribution network based on network information of the target distribution network, association information of the power grid company, and association information of the user-side aggregator. The multi-agent planning model includes at least a first model layer and a second model layer. The first model layer deploys a flexible interconnection device configuration scheme planning model and a user-side resource configuration scheme planning model for the target distribution network. The second model layer deploys a power grid company operation model and a user-side aggregator operation model. The power grid company is the leader of the model, and the user-side aggregator is the follower. According to preset transformation rules, the multi-agent planning model is transformed by converting the models related to the followers in the multi-agent planning model into corresponding equilibrium constraints to obtain a transformed multi-agent planning model. Based on the transformed multi-agent planning model, collaborative solving is performed to determine the matching target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network.

[0113] The memory 403 can be used to store the corresponding instruction program and related intermediate data.

[0114] Based on the above method, the relevant structural performance of the server can be effectively utilized to improve the data processing speed of electronic devices and efficiently realize the coordinated processing of the power distribution network.

[0115] In this embodiment, the network communication port 401 can be a virtual port bound to different communication protocols, thereby enabling the sending or receiving of different data. For example, the network communication port can be a port responsible for web data communication, a port responsible for FTP data communication, or a port responsible for email data communication. Furthermore, the network communication port can also be a physical communication interface or communication chip. For example, it can be a wireless mobile network communication chip, such as GSM or CDMA; it can also be a Wi-Fi chip; or it can be a Bluetooth chip.

[0116] In this embodiment, the processor 402 can be implemented in any suitable manner. For example, the processor can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers, etc. This specification is not limiting.

[0117] In this embodiment, the memory 403 may include multiple layers. In a digital system, anything that can store binary data can be a memory. In an integrated circuit, a circuit with storage function but no physical form is also called a memory, such as RAM, FIFO, etc. In a system, a storage device with a physical form is also called a memory, such as a memory stick, TF card, etc.

[0118] This specification also provides a computer-readable storage medium based on the above-described collaborative configuration processing method for distribution networks. The computer-readable storage medium stores computer program instructions, which, when executed, implement the following: acquiring network information of the target distribution network, association information of the power grid company entity, and association information of the user-side aggregator entity; wherein the target distribution network belongs to a low-voltage distribution area; and constructing a multi-agent planning model of a two-layer structure for the target distribution network based on the network information of the target distribution network, the association information of the power grid company entity, and the association information of the user-side aggregator entity; wherein the multi-agent planning model includes at least: a first model layer and a second model layer, the first model layer... The first model layer deploys a planning model for the flexible interconnection device configuration scheme of the target distribution network and a planning model for the user-side resource configuration scheme. The second model layer deploys a main operation model of the power grid company and a main operation model of the user-side aggregator. The power grid company is the leader of the model, and the user-side aggregator is the follower of the model. According to the preset transformation rules, the multi-agent planning model is obtained by transforming the models related to the followers in the multi-agent planning model into corresponding equilibrium constraints. Based on the transformed multi-agent planning model, collaborative solution is performed to determine the matching target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network.

[0119] In this embodiment, the storage medium includes, but is not limited to, Random Access Memory (RAM), Read-Only Memory (ROM), Cache, Hard Disk Drive (HDD), or Memory Card. The memory can be used to store computer program instructions. The network communication unit can be an interface configured according to standards specified in the communication protocol for network connection communication.

[0120] In this embodiment, the specific functions and effects implemented by the program instructions stored in the computer-readable storage medium can be explained in comparison with other embodiments, and will not be repeated here.

[0121] This specification also provides a computer program product, comprising at least a computer program, which, when executed by a processor, implements the following method steps: acquiring network information of a target distribution network, association information of a power grid company, and association information of a user-side aggregator; wherein the target distribution network belongs to a low-voltage distribution area; and constructing a multi-agent planning model of a two-layer structure for the target distribution network based on the network information of the target distribution network, the association information of the power grid company, and the association information of the user-side aggregator; wherein the multi-agent planning model includes at least a first model layer and a second model layer, the first model layer being deployed with information about the target distribution network. The system comprises a flexible interconnection device configuration scheme planning model and a user-side resource configuration scheme planning model. The second model layer deploys a power grid company main operation model and a user-side aggregator main operation model. The power grid company is the leader of the model, and the user-side aggregator is the follower of the model. According to a preset transformation rule, the multi-agent planning model is transformed into a corresponding equilibrium constraint by transforming the models related to the followers in the multi-agent planning model. Based on the transformed multi-agent planning model, collaborative solution is performed to determine the matching target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network.

[0122] See Figure 5 As shown in the embodiments of this specification, a collaborative configuration processing device for a power distribution network is also provided. This device may specifically include the following structural modules: The acquisition module 501 can be specifically used to acquire network information of the target distribution network, the associated information of the power grid company, and the associated information of the user-side aggregator; wherein, the target distribution network belongs to a low-voltage distribution area; The construction module 502 is used to construct a multi-agent planning model for the two-layer structure of the target distribution network based on the network information of the target distribution network, the association information of the power grid company, and the association information of the user-side aggregator. Specifically, the multi-agent planning model includes at least a first model layer and a second model layer. The first model layer deploys a planning model for the flexible interconnection device configuration scheme of the target distribution network and a planning model for the user-side resource configuration scheme. The second model layer deploys an operation model of the power grid company and an operation model of the user-side aggregator. The power grid company is the leader of the model, and the user-side aggregator is the follower of the model. The transformation module 503 can be used to transform the follower-related models in the multi-agent programming model into corresponding equilibrium constraints according to preset transformation rules, so as to obtain the transformed multi-agent programming model. Module 504 is specifically used to perform collaborative solving based on the transformed multi-agent planning model to determine the matching target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network.

[0123] In some embodiments, when the above-mentioned construction module 502 is specifically implemented, a multi-agent planning model for the two-layer structure of the target distribution network can be constructed in the following manner based on the network information of the target distribution network, the association information of the power grid company entity, and the association information of the user-side aggregator entity: A multi-agent planning model framework based on a game-theoretic interaction model is constructed based on the network information of the target distribution network, the association information of the power grid company entity, and the association information of the user-side aggregator entity; the power grid company entity is set as the leader of the model, and the user-side aggregator entity is set as the follower of the model; in the first model layer of the multi-agent planning model framework, a flexible interconnection device is constructed by constructing a first objective function and a first constraint condition. A planning model for flexible interconnection device configuration schemes is constructed. Simultaneously, a user-side resource allocation scheme planning model is built by constructing a second objective function regarding user-side resource demand and a second constraint condition. The first objective function includes at least: a planning cost item for flexible interconnection devices, a maintenance cost item for flexible interconnection devices, and a carbon emission cost item for the power grid company entity based on flexible interconnection devices. In the second model layer of the multi-entity planning model framework, a power grid company entity operation model is constructed by constructing a third objective function regarding the operation of the power grid company entity and a third constraint condition. Simultaneously, a user-side aggregator entity operation model is constructed by constructing a fourth objective function regarding the operation of the user-side aggregator entity and a fourth constraint condition.

[0124] In some embodiments, when the above-described construction module 502 is specifically implemented, the first objective function can be constructed in the following manner:

[0125] in, The value of the first objective function. For the planning cost item of flexible interconnect devices, For maintenance costs of flexible interconnect devices, For the carbon emission cost item of the main body of the power grid company based on flexible interconnection devices, d For the discount rate, y For the service life of flexible interconnect devices, The price per unit capacity of flexible interconnect devices, For installation on the node i The capacity of flexible interconnect devices, i Number the nodes in the target distribution network. N The total number of nodes equipped with flexible interconnect devices. This represents the annual operating and maintenance cost coefficient for flexible interconnect devices, etc. For carbon trading prices, For the number m The number of days included in a quarter. T The number of carbon emission moments per day, where m is the quarter number. For the upper-level power grid t The average carbon intensity coefficient at any given time. For the main body of the power grid company t The power purchased from the upper-level power grid at all times.

[0126] In some embodiments, when the above-mentioned construction module 502 is specifically implemented, the first constraint condition can be constructed in the following manner: based on the network information of the target distribution network, construct a low-voltage distribution area power constraint term and a low-voltage flexible interconnection device installation location constraint term for the target distribution network; based on the relevant interaction relationship between flexible interconnection devices at different installation locations, construct corresponding low-voltage flexible interconnection device constraint terms; obtain and construct, based on the attribute parameters of the flexible interconnection device, a power loss constraint term for the flexible interconnection device, a capacity constraint term for the low-voltage flexible interconnection device, and active power and reactive power constraint terms for the low-voltage flexible interconnection device; combine the low-voltage distribution area power constraint term, the low-voltage flexible interconnection device installation location constraint term, the low-voltage flexible interconnection device constraint term, the power loss constraint term for the flexible interconnection device, the capacity constraint term for the low-voltage flexible interconnection device, and the active power and reactive power constraint terms for the low-voltage flexible interconnection device to construct the first constraint condition.

[0127] In some embodiments, when the above-described construction module 502 is specifically implemented, the installation position constraints of the low-voltage flexible interconnect device can be constructed in the following manner:

[0128] in, For the target distribution network i Indicator information indicating whether the node is equipped with a flexible interconnect device. The set of nodes in the target distribution network suitable for installing flexible interconnection devices. This represents the upper limit on the number of flexible interconnection devices to be installed in the target distribution network.

[0129] In some embodiments, when the above-described construction module 502 is specifically implemented, the low-voltage distribution area power constraint term can be constructed in the following manner:

[0130] in, For the target distribution network i node t The active power injected at all times, For the target distribution network i node t The reactive power injected at all times For flexible interconnect devices located in i Converter at the node t Constant input / output active power For flexible interconnect devices located in i Converter at the node t Constant input / output reactive power Let be the active power of the energy storage system at node i at time t during discharge / charge. For the target distribution network i node t Active load at any given time For the target distribution network i node t Reactive load at all times This refers to the rated capacity of the transformer.

[0131] In some embodiments, when the above-described construction module 502 is specifically implemented, the second objective function can be constructed in the following manner:

[0132] in, The value of the second objective function. The indication information is either 0 or 1, used to indicate whether the power grid company has selected node users in the target distribution network. i Demand-side resources S For the set of nodes in the target distribution network, The unit capacity cost of demand-side resources. For node users i Reserved response capacity.

[0133] In some embodiments, when the above-described construction module 502 is specifically implemented, the fourth objective function can be constructed in the following manner:

[0134] in, The revenue generated from electricity sales by the user-side aggregator to the power grid company. The cost of electricity purchased by the user-side aggregator from the power grid company. The cost per unit power for charging source-side energy storage. Let m be the charging power of the source-side energy storage at time t in the quarter numbered m. The cost per unit power of source-side energy storage discharge. Let be the discharge power of the source-side energy storage at time t in quarter numbered m. For a set of user nodes containing distributed power sources, This represents the unit electricity price at which the power grid company purchases electricity from the user-side aggregator at time t within quarter m. This represents the amount of electricity purchased by the power grid company from the user-side aggregator at time t in quarter number m. A set of user nodes with demand response capabilities. k This represents a user comfort function in response to load shifting. Let m be the net load power of the user at time t in quarter m. This represents the unit electricity price that the power grid company sells to nodal users at time t within quarter numbered m. This represents the amount of electricity sold by the power grid company to the node user numbered i at time t within a quarter numbered m. T The total number of moments in a day.

[0135] In some embodiments, after jointly solving for the matching target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network based on the transformed multi-agent planning model, the device can also be used in specific implementations to: determine the matching target location point in the target distribution network according to the target flexible interconnection device configuration scheme; install a flexible interconnection device with matching capacity at the target location point; determine the matching target node user in the target distribution network according to the target user-side resource configuration scheme; and set the reserved response capacity matching the target node user.

[0136] It should be noted that the units, devices, or modules described in the above embodiments can be implemented by computer chips or physical entities, or by products with certain functions. For ease of description, the above devices are described by dividing them into various modules according to their functions. Of course, in implementing this specification, the functions of each module can be implemented in one or more software and / or hardware, or the module that implements the same function can be implemented by a combination of multiple sub-modules or sub-units, etc. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection between the devices or units shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0137] As can be seen from the above, the collaborative configuration processing device for the distribution network provided in the embodiments of this specification can be well adapted to low-voltage distribution areas with complex conditions, effectively integrate the different situations and needs of the power grid company and the user-side aggregator, and determine the target flexible device configuration scheme and the target user-side resource configuration scheme that can take into account the interests of all parties and achieve good results, so as to efficiently realize the precise configuration of the target distribution network.

[0138] In a specific scenario example, the collaborative configuration processing method for distribution networks provided in this manual can be applied to achieve low-voltage distribution area flexible interconnection devices and demand-side resource low-carbon collaborative planning. For detailed implementation procedures, please refer to [the manual's documentation]. Figure 6 and Figure 2 As shown, it includes the following content.

[0139] In this scenario, the large-scale integration of distributed generation (DG) and new loads into the distribution network brings problems such as voltage exceeding limits, increased network losses, and difficulties in power flow control. Traditional distribution network regulation methods are limited, making it difficult to achieve flexible and continuous power flow control. Flexible interconnection devices (SOPs), as a type of flexible power electronic device, can improve the power flow control capability of the distribution network; however, the unit capacity cost of SOPs is relatively high, requiring reasonable configuration to maximize their benefits.

[0140] The following technical problems exist in current power distribution network planning and research: (1) Conflict of interests among multiple stakeholders: After the opening of the electricity market, the distribution network presents a multi-stakeholder interaction pattern involving power grid companies and user-side aggregators. The interests of these stakeholders are not aligned, making it difficult to achieve overall optimization. Existing planning methods often start from the interests of a single stakeholder and cannot reflect the actual situation of multi-stakeholder game in a market environment.

[0141] (2) Insufficient handling of uncertainty: Distributed power output and load demand have significant uncertainties, which existing planning methods do not adequately consider. In particular, there is uncertainty in user willingness in demand-side resource response, and traditional deterministic planning methods cannot accurately describe this elastic response characteristic.

[0142] (3) Lack of collaborative optimization: Most existing studies consider the configuration of flexible interconnection devices or the planning of demand-side resources separately, lacking an overall scheme for the collaborative configuration of flexible interconnection devices and demand-side resources, thus failing to achieve functional complementarity and maximize the benefits of the two resources.

[0143] (4) Low solution efficiency: The planning problem of flexible interconnection device usually uses heuristic algorithms to determine the location capacity combination. For large-scale power distribution systems, as the number of candidate location capacity combinations increases, the solution speed and optimization efficiency of heuristic algorithms will decrease significantly, and the global optimality of the solution result is difficult to guarantee.

[0144] To address the aforementioned technical issues, there is an urgent need for a configuration method that can comprehensively consider multi-stakeholder game theory, uncertainty handling, and collaborative optimization in order to improve the economy and reliability of power distribution network planning.

[0145] This scenario example proposes a low-carbon collaborative planning method for flexible interconnection devices in low-voltage distribution areas and demand-side resources. Through a multi-agent interaction framework, it achieves coordinated and optimized configuration of flexible interconnection devices (Soft Open Point, SOP) and user demand-side resources (DSR), improving the economic efficiency of the distribution network and its capacity for renewable energy absorption. See also... Figure 6 As shown, the specific steps may include the following.

[0146] Step 1: Establish a multi-entity interactive game model for the distribution network in a market environment (e.g., a multi-entity planning model). This model takes the power grid company that manages the distribution network equipped with flexible interconnection devices (e.g., the power grid company entity) as the leader and the user-side aggregators that include distributed power sources and demand-side resources (e.g., the user-side aggregators entity) as the followers, forming a typical master-slave game structure. Step 2: Construct a two-layer model for the collaborative allocation of low-voltage distribution area flexible interconnection devices and demand-side resources, embedding multi-agent game interaction. At the planning layer, with the goal of minimizing the distribution company's annual comprehensive cost and considering carbon emission costs, decide on the location and capacity allocation scheme of the power grid company's low-voltage flexible interconnection devices and the demand-side resource allocation scheme of the user-side aggregator. The demand-side resource allocation scheme includes introducing 0-1 decision variables to determine whether to select demand-side resources for users of specific distribution network nodes, and determining the corresponding reserved response capacity flexible interconnection devices. Step 3: Employ mathematical optimization techniques to transform and efficiently solve the complex two-layer game model. This includes: using KKT conditions to convert the runtime game model into equivalent planning layer constraints; combining polyhedral linearization techniques to transform the nonlinear model into a mixed-integer linear programming (MILP) model; and using the CPLEX solver for efficient solution.

[0147] In specific implementation of step 1, a non-cooperative Stackelberg game model is constructed between the power grid company and the user-side aggregator to simulate the interaction of various stakeholders in a market environment, including: 1) The multi-stakeholder game framework for the distribution network is as follows: This application considers a multi-stakeholder game-theoretic framework that includes two main stakeholders: the power grid company and the user-side aggregator. The functions and interests of each stakeholder are described below: The power grid company is the main integration platform for all elements, primarily responsible for the planning and operation of the distribution network, as well as the internal optimization and coordination of the distribution market. Under the premise of ensuring the safe and reliable operation of the system, the power grid company profits by earning the price difference between purchasing and selling electricity between the upstream power grid and user-side aggregators.

[0148] User-side aggregators can first generate revenue by purchasing and selling electricity from the grid, aiming to maximize profits. In order to increase the amount of electricity sold and avoid passive power curtailment, they can also configure energy storage according to the relevant requirements of the grid, thus possessing a certain degree of regulation capability. Secondly, based on people's consumption habits, they can also have a certain degree of demand response capability.

[0149] 2) Considering the multi-party game theory of flexible interconnected devices and the collaborative allocation of demand-side resources, specifically: The planning of flexible interconnection devices falls within the business scope of the power grid operator. By configuring and utilizing flexible interconnection devices, the power grid operator addresses voltage and current over-limit issues caused by power exchange during source-grid-load interaction in a market environment, and promotes economic operation.

[0150] Demand-side resource planning falls under the business scope of user-side aggregators. By aggregating demand-side resources, user-side aggregators form an extremely rapid and flexible adjustment capability, which can coordinate the electricity consumption adjustments of massive numbers of users, providing valuable support to the power grid, effectively replacing some traditional generation-side adjustment resources, and enhancing the grid's resilience in the face of emergencies.

[0151] Therefore, this application establishes a power grid company decision-making model that includes flexible interconnection device planning and trading strategies, with the objective of maximizing the main entity's average annual revenue, and using the configuration and operation of flexible interconnection devices, the electricity trading price with user-side aggregators, and the electricity trading volume with the upper-level power grid as decision variables. A user-side aggregator decision-making model that includes demand-side resource planning is also established, with the objective of minimizing the total planning and operating costs of user-side aggregators, and using the configuration and operation of demand-side resources and the electricity trading volume with the power grid company as decision variables.

[0152] An optimal operation model is established for user-side aggregators after receiving electricity trading prices from the power grid company. The model aims to maximize operational profits and uses the electricity trading volume between user-side aggregators and the power grid entity as the decision variable.

[0153] The aforementioned model is essentially a non-cooperative game structure, where the leader is the power grid entity and the followers are the user-side aggregators. Through the interaction among these market participants, a game equilibrium is reached, leading to the power grid entity's flexible interconnection device planning scheme under market conditions, as well as the power trading strategy between the power grid entity and the user-side aggregators.

[0154] In specific implementation of step 3, the follower model is equivalent to the equilibrium constraint in the leader model using KKT conditions, thereby converting the two-layer interactive game model into a single-layer optimization model and solving it. This includes the transformation of the multi-agent game model, specifically including the following:

[0155] In this scenario, the proposed multi-agent game model is a leader-follower game model, with a leader being the power grid company. As the leader, its objective is higher than the decision objectives of the other two layers. For a two-layer model, it's not feasible to solve each layer independently. This application proposes using the Kuhn-Tak method for solution. The specific solution process first uses KKT conditions to equivalently transform the problem to be solved in the lower-layer model. In other words, it applies a single-layer nonlinear programming problem with multiple constraints to equivalently replace the original two-layer programming problem. KKT conditions are used to replace the strategy space of the lower-layer followers, while the upper-layer leader solves its own planning problem when considering the optimal decision of the lower-layer model.

[0156] (a) Dual transformation

[0157] To solve this problem, we introduce a dual variable, transforming the min problem into a max problem, i.e., finding the dual problem of the min problem. The process is as follows: .

[0158] (b) KKT transformation

[0159] The KKT conditions for the user-side aggregator model are:

[0160] in, .

[0161] in, For Lagrange functions, Let Lagrange multiplier vectors be the set of inequalities. Constrain the left-hand side of all equations. The left side of the inequality is the part. This is a vector set of independent variables, including the transaction price between the grid company and the user-side aggregators, and the transmission power between multiple user-side aggregators and the grid company. The above KKT conditions are then incorporated into the upper-level model, transforming it into a single-layer model.

[0162] (c) Treatment of bilinear terms

[0163] The power grid model company contains bilinear terms. and Therefore, a dual problem is used to transform the objective function, thereby eliminating the bilinear terms in the objective function.

[0164]

[0165] in, Since it is a nonlinear term, linearization using the Big M method yields:

[0166] in, It is a vector composed of a series of binary variables.

[0167] In practical applications, Figure 7 The actual power distribution system in a certain region is shown as an example. The system network structure and node load types are as follows. The power distribution company can select up to 5 nodes as flexible interconnection devices, and the maximum number of load nodes for demand-side resources is 30.

[0168] To illustrate the effectiveness of joint planning of demand-side resources and soft switching, the following schemes are compared and analyzed: Scheme 1, considering only demand-side resources; Scheme 2, considering only flexible interconnect devices; and Scheme 3, comprehensively considering both demand-side resources and flexible interconnect devices.

[0169] The results of the power grid company's investment costs, the location and capacity determination of flexible interconnection devices, and the demand-side resource allocation schemes for each scheme are shown in Tables 1, 2, and 3, respectively.

[0170] Table 1. Investment Costs of Power Grid Companies for Each Planning Scheme

[0171] Table 2. Site selection and capacity determination results for flexible interconnect devices

[0172] Table 3 Demand-Side Resource Planning Results

[0173] The above scenario examples verify the effectiveness of the collaborative configuration processing method for distribution networks provided in this manual. It ensures that the resulting flexible interconnection device and demand-side resource collaborative configuration scheme take into account both the market environment and the benefits of the power grid company, supporting the safe and economical operation of the distribution network under market conditions.

[0174] While this specification provides the steps of operation for the methods described in the embodiments or flowcharts, more or fewer steps may be included based on conventional or non-inventive means. The order of steps listed in the embodiments is merely one possible order of execution among many steps and does not represent the only possible order. In actual device or client product execution, the methods shown in the embodiments or drawings may be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment, or even a distributed data processing environment). The terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, product, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, product, or apparatus. Without further limitations, the presence of other identical or equivalent elements in a process, method, product, or apparatus that includes said elements is not excluded. The terms "first," "second," etc., are used to denote names and do not indicate any particular order.

[0175] Those skilled in the art will also know that, besides implementing the controller in the form of purely computer-readable program code, the same functions can be achieved by logically programming the method steps, making the controller take the form of logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers (PLCs), and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the devices within it used to implement various functions can also be considered structures within that hardware component. Alternatively, the devices used to implement various functions can be considered as both software modules implementing the method and structures within a hardware component.

[0176] This specification can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, classes, etc., that perform a specific task or implement a specific abstract data type. This specification can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer-readable storage media, including storage devices.

[0177] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this specification can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions of this specification can essentially be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, mobile terminal, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments of this specification.

[0178] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. This specification can be used in numerous general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable electronic devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices, etc.

[0179] Although this specification has been described by way of examples, those skilled in the art will recognize that many variations and modifications are possible without departing from the spirit of this specification, and it is intended that the appended claims cover such variations and modifications without departing from the spirit of this specification.

Claims

1. A method for coordinated configuration processing of a power distribution network, characterized in that, include: Obtain network information of the target distribution network, associated information of the power grid company, and associated information of the user-side aggregator; wherein the target distribution network belongs to a low-voltage distribution area; Based on the network information of the target distribution network, the association information of the power grid company, and the association information of the user-side aggregator, a multi-agent planning model for the two-layer structure of the target distribution network is constructed. The multi-agent planning model includes at least a first model layer and a second model layer. The first model layer deploys a planning model for the flexible interconnection device configuration scheme of the target distribution network and a planning model for the user-side resource configuration scheme. The second model layer deploys an operation model for the power grid company and an operation model for the user-side aggregator. The power grid company is the leader of the model, and the user-side aggregator is the follower of the model. According to the preset transformation rules, the transformed multi-agent programming model is obtained by transforming the follower-related models in the multi-agent programming model into corresponding equilibrium constraints. Based on the transformed multi-agent planning model, a collaborative solution is performed to determine the matching target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network.

2. The method according to claim 1, characterized in that, The process of constructing a multi-agent planning model for the two-layer structure of the target distribution network based on network information of the target distribution network, association information of the power grid company, and association information of the user-side aggregator includes: Based on the network information of the target distribution network, the correlation information of the power grid company, and the correlation information of the user-side aggregator, a multi-agent planning model framework based on a game-theoretic interaction model is constructed; and the power grid company is set as the leader of the model, and the user-side aggregator is set as the follower of the model. In the first model layer of the multi-agent planning model framework, a flexible interconnection device configuration scheme planning model is constructed by constructing a first objective function and a first constraint condition for the flexible interconnection device; simultaneously, a user-side resource allocation scheme planning model is constructed by constructing a second objective function and a second constraint condition for the user-side resource demand; wherein, the first objective function includes at least: a planning cost item for the flexible interconnection device, a maintenance cost item for the flexible interconnection device, and a carbon emission cost item for the power grid company entity based on the flexible interconnection device; In the second model layer of the multi-agent planning model framework, a power grid company operation model is constructed by establishing a third objective function and a third constraint condition for the operation of the power grid company. Simultaneously, a user-side aggregator operation model is constructed by establishing a fourth objective function and a fourth constraint condition for the operation of the user-side aggregator.

3. The method according to claim 2, characterized in that, The first objective function is constructed according to the following formula: in, The first objective function value, For the planning cost item of flexible interconnect devices, For maintenance costs of flexible interconnect devices, For the carbon emission cost item of the main body of the power grid company based on flexible interconnection devices, d For the discount rate, y For the service life of flexible interconnect devices, The price per unit capacity of flexible interconnect devices, For installation on the node i The capacity of flexible interconnect devices, i Number the nodes in the target distribution network. N The total number of nodes equipped with flexible interconnect devices. This refers to the annual operating and maintenance cost coefficient for flexible interconnect devices, etc. For carbon trading prices, For the number m The number of days included in a quarter. T The number of carbon emission moments per day, where m is the quarter number. For the upper-level power grid t The average carbon intensity coefficient at any given time. For the main body of the power grid company in the numbered m In the quarter t The power purchased from the upper-level power grid is constantly monitored.

4. The method according to claim 2, characterized in that, The first constraint is constructed as follows: Based on the network information of the target distribution network, construct the low-voltage distribution area power constraint term and the low-voltage flexible interconnection device installation location constraint term for the target distribution network; Based on the interaction relationships between flexible interconnect devices at different installation locations, construct corresponding low-voltage flexible interconnect device constraint terms; Based on the attribute parameters of the flexible interconnection device, construct the power loss constraint term of the flexible interconnection device, the capacity constraint term of the low-voltage flexible interconnection device, and the active power and reactive power constraint terms of the low-voltage flexible interconnection device respectively. By combining the low-voltage distribution area power constraint, the low-voltage flexible interconnection device installation location constraint, the low-voltage flexible interconnection device constraint, the flexible interconnection device power loss constraint, the low-voltage flexible interconnection device capacity constraint, and the low-voltage flexible interconnection device active power and reactive power constraint, the first constraint condition is constructed.

5. The method according to claim 4, characterized in that, The step of constructing installation location constraints for low-voltage flexible interconnection devices in the target distribution network based on network information includes: The installation location constraints for low-voltage flexible interconnect devices are constructed according to the following formula: in, For the target distribution network i Indicator information indicating whether the node is equipped with a flexible interconnect device. The set of nodes in the target distribution network suitable for installing flexible interconnection devices. This represents the upper limit on the number of flexible interconnection devices to be installed in the target distribution network.

6. The method according to claim 4, characterized in that, The step of constructing low-voltage distribution area power constraint terms for the target distribution network based on the network information of the target distribution network includes: Construct the low-voltage distribution area power constraint terms according to the following formula: in, For the target distribution network i node t The active power injected at all times, For the target distribution network i node t The reactive power injected at all times For flexible interconnect devices located in i Converter at the node t Constant input / output active power For flexible interconnect devices located in i Converter at the node t Constant input / output reactive power For energy storage systems located in i At the node t Active power for constant discharge / charge. For the target distribution network i node t Active load at any given time For the target distribution network i node t Reactive load at all times This refers to the rated capacity of the transformer.

7. The method according to claim 2, characterized in that, The second objective function is constructed according to the following formula: in, The value of the second objective function. The indication information is either 0 or 1, used to indicate whether the power grid company has selected node users in the target distribution network. i Demand-side resources S For the set of nodes in the target distribution network, The unit capacity cost of demand-side resources. For node users i Reserved response capacity.

8. The method according to claim 2, characterized in that, The user-side aggregator also integrates a distributed power operator; correspondingly, the fourth objective function is constructed according to the following formula: in, The revenue generated from electricity sales by the user-side aggregator to the power grid company. The cost of electricity purchased by the user-side aggregator from the power grid company. The cost per unit power for charging source-side energy storage. Let m be the charging power of the source-side energy storage at time t in the quarter numbered m. The cost per unit power of energy storage discharge on the source side. Let be the discharge power of the source-side energy storage at time t in quarter numbered m. For a set of user nodes containing distributed power sources, This represents the unit electricity price at which the power grid company purchases electricity from the user-side aggregator at time t within quarter m. This represents the amount of electricity purchased by the power grid company from the user-side aggregator at time t in quarter number m. For a set of user nodes with demand response capabilities, k This represents a user comfort function in response to load shifting. Let m be the net load power of the user at time t in quarter m. This represents the unit electricity price that the power grid company sells to nodal users at time t within quarter numbered m. This represents the amount of electricity sold by the power grid company to the node user numbered i at time t within a quarter numbered m. T The total number of moments in a day.

9. The method according to claim 1, characterized in that, After jointly solving for the matching target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network based on the transformed multi-agent planning model, the method further includes: Based on the target flexible interconnection device configuration scheme, a matching target location point is determined in the target distribution network; and a flexible interconnection device with a matching capacity is installed at the target location point. Based on the target user-side resource configuration scheme, identify the matching target node users in the target distribution network; and set the reserved response capacity matching the target node users.

10. A collaborative configuration processing device for a power distribution network, characterized in that, include: The acquisition module is used to acquire network information of the target distribution network, the associated information of the power grid company, and the associated information of the user-side aggregator; wherein the target distribution network belongs to a low-voltage distribution area. A construction module is used to construct a multi-agent planning model for the two-layer structure of the target distribution network based on the network information of the target distribution network, the association information of the power grid company, and the association information of the user-side aggregator. The multi-agent planning model includes at least a first model layer and a second model layer. The first model layer deploys a planning model for the flexible interconnection device configuration scheme of the target distribution network and a planning model for the user-side resource configuration scheme. The second model layer deploys an operation model for the power grid company and an operation model for the user-side aggregator. The power grid company is the leader of the model, and the user-side aggregator is the follower. The transformation module is used to transform the follower-related models in the multi-agent programming model into corresponding equilibrium constraints according to preset transformation rules, so as to obtain the transformed multi-agent programming model. The determination module is used to collaboratively solve the transformed multi-agent planning model to determine the matching target flexible interconnection device configuration scheme and target user-side resource configuration scheme for the target distribution network.

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