Layered regulation and control method and device for power grid containing multi-element heterogeneous resources for light storage

Abstract

The invention provides a hierarchical regulation and control method and device for a power grid containing multi-element heterogeneous resources for optical storage, and the method comprises the steps: dividing a target region into a plurality of sub-regions based on the historical data of the multi-element heterogeneous resources for optical storage of the target region, and obtaining a multi-level regulation and control architecture; according to the current regulation and control requirement and the multi-level regulation and control framework, the region regulation and control problem of the target region is divided into a plurality of sub-regulation and control problems of the target level; wherein the sub-regulation problem of the target level comprises a sub-region regulation problem of the sub-region or a transformer region regulation problem of the transformer region; based on a multi-level regulation and control framework, adopting an improved alternating direction multiplier method to solve a plurality of sub-regulation and control problems of the target level in real time, and obtaining a pre-regulation and control scheme of the multi-element heterogeneous resources for optical storage of the target level in a single time section; and according to the pre-regulation scheme, regulating and controlling the multi-element heterogeneous resources for optical storage of the target level. According to the method, a multi-level regulation and control framework is constructed by considering spatial-temporal correlation aggregation of multi-element heterogeneous resources for optical storage, and the regional regulation and control problem is solved in real time by adopting an improved alternating direction multiplier method, so that the accurate regulation and control requirement of a power grid can be met, and the effect of error regulation and control is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid regulation, and in particular to a method and device for hierarchical regulation of a power grid containing multiple heterogeneous resources including photovoltaic storage. Background Art

[0002] Photovoltaic power generation, as an important component of clean energy, is experiencing rapid development. Distributed photovoltaic power generation is regarded as a key force in optimizing energy structure, ensuring energy security and improving ecological environment due to its advantages of being green, clean, cheap and ready for use.

[0003] However, the large-scale grid connection of low-voltage distributed photovoltaics also brings a series of technical challenges, including voltage over-limit, island operation, reverse overload, etc. In addition, the power grid has changed from a traditional single source-load to a source-load interaction, and the distribution subject has become more complex, requiring more accurate and efficient control strategies to ensure the stable and reliable operation of the power grid.

[0004] Most of the existing pre-control technologies are based on linear aggregation models, ignoring the nonlinear characteristics in complex scenarios, resulting in large aggregation errors and poor pre-control effects. At the same time, the optimization solution time based on the centralized control framework is long and cannot meet the real-time control needs of the power grid.

[0005] Therefore, there is an urgent need for a pre-control technology that can accurately predict distributed photovoltaic output, take into account the coordinated control of distributed energy, and realize real-time rolling optimization, so as to effectively improve the peak-shaving capacity of the power system. Summary of the invention

[0006] The present invention provides a method and device for hierarchical control of a power grid containing multiple heterogeneous resources of photovoltaic storage, so as to overcome the defects of the existing power grid pre-control technology that lacks the means for coordinated control of photovoltaic storage in complex scenarios, cannot meet the needs of precise control of the power grid, and has poor control effect, so as to meet the real-time solution needs of the optimization problem of hierarchical control of the aggregation of multiple heterogeneous resources of photovoltaic storage.

[0007] On the one hand, the present invention provides a method for hierarchical control of a power grid containing photovoltaic and storage multi-heterogeneous resources, comprising: based on historical data of photovoltaic and storage multi-heterogeneous resources in the target area, dividing the target area into multiple sub-areas to obtain a multi-level control architecture; wherein the sub-areas include one or more substations; according to current control needs and the multi-level control architecture, splitting the regional control problem of the target area into multiple sub-control problems of the target level; wherein the sub-control problems of the target level include sub-regional control problems of sub-areas or substation control problems of substations; based on the multi-level control architecture, using an improved alternating direction multiplier method to solve the multiple sub-control problems of the target level in real time, and obtaining a pre-control scheme for the photovoltaic and storage multi-heterogeneous resources of the target level at a single time section; according to the pre-control scheme, controlling the photovoltaic and storage multi-heterogeneous resources of the target level.

[0008] Furthermore, the historical data of multi - heterogeneous resources for optical storage includes the geographical spatial distribution data of the sub - regions, the historical output data of distributed photovoltaics, the configured capacity and maximum power of energy storage, the historical data of user loads, and the adjustable potential data of demand response.

[0009] Furthermore, based on the historical data of multi - heterogeneous resources for optical storage in the target area, the target area is divided into multiple sub - regions, including: generating a similarity matrix of the sub - regions according to the historical data of multi - heterogeneous resources for optical storage in the target area; initializing and updating the attraction and attribution of each sub - region in the target area; summing up the attraction and attribution of each sub - region to obtain a summation value; determining multiple target sub - regions as clustering centers according to the summation values of each sub - region in the target area; obtaining multiple clusters according to the similarity matrix of the sub - regions and the multiple target sub - regions; and the clusters correspond to the sub - regions one by one.

[0010] Furthermore, according to the current regulation requirements and the multi - level regulation framework, the regional regulation problem of the target area is split into multiple sub - regulation problems at the target level, including: calculating the index - bearing capacity of multi - heterogeneous resources for optical storage in the target level for the current regulation requirements according to the multi - level regulation framework; the index - bearing capacity includes one or a combination of peak - shaving index - bearing capacity, valley - filling index - bearing capacity, and photovoltaic accommodation index - bearing capacity; calculating the index requirements of multiple target levels with the index - bearing capacity as the weight to split the regional regulation problem of the target area into multiple sub - regulation problems belonging to the target level.

[0011] Furthermore, based on the multi - level regulation framework, the improved alternating direction method of multipliers is used to solve the multiple sub - regulation problems at the target level in real - time, including: S311, initializing the number of iterations and the area number; S312, using the column - sum constraint generation algorithm to solve the sub - regulation problem corresponding to the initial area number according to the initial regulation value corresponding to the initial area number; S313, when the initial area number is greater than any interconnected area number, updating the corresponding multiplier by the current area of the initial area number and transmitting the solution result to the interconnected area; S314, comparing the initial area number with the maximum area number; S315, when the initial area number is not greater than the maximum area number, updating the initial area number and executing steps S312 - S314; S316, when the initial area number is greater than the maximum area number but the regulation error is greater than or equal to the given error, updating the number of iterations and initializing the area number and executing steps S312 - S314; S317, when the initial area number is greater than the maximum area number and the regulation error is less than the given error, ending the iteration and outputting the pre - regulation plan of the multi - heterogeneous resources for optical storage at the target level at a single time section.

[0012] Further, according to the pre-regulation scheme, the multi-source heterogeneous resources of photovoltaics, energy storage, and utilization at the regulated target level are regulated. After that, it further includes: real-time monitoring of the latest status data of the multi-source heterogeneous resources of photovoltaics, energy storage, and utilization at the target level; real-time evaluation of the pre-regulation effect of the pre-regulation scheme; modification of the pre-regulation scheme according to the latest status data and the pre-regulation effect; and regulation of the multi-source heterogeneous resources of photovoltaics, energy storage, and utilization at the target level according to the modified pre-regulation scheme.

[0013] In a second aspect, the present invention further provides a power grid hierarchical regulation device including multi-source heterogeneous resources of photovoltaics, energy storage, and utilization, comprising: a target area division module for dividing a target area into multiple sub-areas based on historical data of the multi-source heterogeneous resources of photovoltaics, energy storage, and utilization in the target area, obtaining a multi-level regulation architecture; wherein, the sub-areas include one or more distribution areas; a regional regulation problem division module for splitting the regional regulation problem of the target area into multiple sub-regulation problems at the target level according to the current regulation requirements and the multi-level regulation architecture; wherein, the sub-regulation problems at the target level include sub-area regulation problems of the sub-areas or distribution area regulation problems of the distribution areas; a sub-regulation problem solving module for, based on the multi-level regulation architecture, using an improved alternating direction method of multipliers to solve the multiple sub-regulation problems at the target level in real time, obtaining a pre-regulation scheme for the multi-source heterogeneous resources of photovoltaics, energy storage, and utilization at the target level at a single time section; and a power grid hierarchical regulation module for regulating the multi-source heterogeneous resources of photovoltaics, energy storage, and utilization at the target level according to the pre-regulation scheme.

[0014] In a third aspect, the present invention further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the power grid hierarchical regulation method including multi-source heterogeneous resources of photovoltaics, energy storage, and utilization as described in any one of the above.

[0015] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the power grid hierarchical regulation method including multi-source heterogeneous resources of photovoltaics, energy storage, and utilization as described in any one of the above.

[0016] In a fifth aspect, the present invention further provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the power grid hierarchical regulation method including multi-source heterogeneous resources of photovoltaics, energy storage, and utilization as described in any one of the above.

[0017] The grid hierarchical regulation method with multiple heterogeneous resources of photovoltaic, energy storage and load provided by the present invention divides the target area into multiple sub-areas based on the historical data of multiple heterogeneous resources of photovoltaic, energy storage and load in the target area, and obtains a multi-level regulation framework; wherein, the sub-area includes one or more distribution transformers; according to the current regulation requirements and the multi-level regulation framework, the regional regulation problem of the target area is split into multiple sub-regulation problems at the target level; wherein, the sub-regulation problems at the target level include the sub-area regulation problems of the sub-areas or the distribution transformer regulation problems of the distribution transformers; based on the multi-level regulation framework, the improved alternating direction method of multipliers is used to solve the multiple sub-regulation problems at the target level in real time, and a pre-regulation plan for the multiple heterogeneous resources of photovoltaic, energy storage and load at the target level at a single time section is obtained; according to the pre-regulation plan, the multiple heterogeneous resources of photovoltaic, energy storage and load at the target level are regulated. By considering the spatio-temporal correlation aggregation of multiple heterogeneous resources of photovoltaic, energy storage and load to construct a multi-level regulation framework and using the improved alternating direction method of multipliers to solve the regional regulation problem in real time, this method can meet the accurate regulation requirements of the power grid and achieve the effect of error regulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1 It is a schematic flow chart of the grid hierarchical regulation method with multiple heterogeneous resources of photovoltaic, energy storage and load provided by the embodiments of the present invention.

[0020] Figure 2 It is a schematic algorithm flow chart of the improved alternating direction method of multipliers provided by the embodiments of the present invention.

[0021] Figure 3 It is a schematic structural diagram of the grid hierarchical regulation device with multiple heterogeneous resources of photovoltaic, energy storage and load provided by the embodiments of the present invention.

[0022] Figure 4 It is a schematic physical structure diagram of the electronic device provided by the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] In order to make the objectives, technical solutions and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention with reference to the drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0024] It should be noted that vigorously promoting the application of photovoltaic power generation is of great strategic significance for optimizing the energy structure, ensuring energy security, improving the ecological environment, and transforming the urban and rural energy use patterns. Distributed photovoltaic power generation has characteristics such as green and clean, low cost, and immediate power generation and use, and can better support the integrated development of multiple scenarios of photovoltaic power generation.

[0025] However, problems such as voltage over-limit, island operation, reverse overload, in-situ consumption, and impact on peak regulation caused by large-scale grid connection of low-voltage distributed photovoltaics are becoming increasingly prominent. After large-scale access of distributed photovoltaics, the power grid has changed from a traditional single source-load to a source-load interaction, the distribution main body is more complex and diverse, the energy flow direction is more diverse, and there are many constraints in improving the system regulation ability.

[0026] In addition to distributed photovoltaic resources in the regulation area, there are also diverse heterogeneous resources such as distributed energy storage, electric vehicles, industrial and commercial loads, and residential loads. Currently, there is a lack of collaborative regulation means for photovoltaics, energy storage, and load in complex scenarios, and the technical means for low-voltage distributed photovoltaics to participate in regional power grid peak regulation are not perfect, unable to meet the accurate regulation requirements of the power grid. Existing research only focuses on linear aggregation, and the mechanism of aggregation error generation is not clear, resulting in poor pre-regulation effect after aggregation. In addition, the current pre-regulation strategies are all based on a centralized regulation framework, with a long optimization solution time, and the decomposition of the regulation plan instructions is not optimized and executed in real-time and continuously, directly leading to the regulation effect not meeting the expectations.

[0027] Considering this, the present invention proposes a hierarchical regulation method for a power grid containing diverse heterogeneous resources of photovoltaics, energy storage, and load. Specifically, Figure 1 FIG. shows a schematic flowchart of the hierarchical regulation method for a power grid containing diverse heterogeneous resources of photovoltaics, energy storage, and load provided by an embodiment of the present invention.

[0028] As Figure 1 shown, the method includes steps S110-S140, and the following will describe steps S110-S140 and related steps in detail.

[0029] S110, based on the historical data of diverse heterogeneous resources of photovoltaics, energy storage, and load in the target area, divide the target area into multiple sub-areas to obtain a multi-level regulation architecture; wherein, the sub-areas include one or more distribution areas.

[0030] It is easy to understand that in this embodiment, based on the spatio-temporal correlation of diverse heterogeneous resources of photovoltaics, energy storage, and load in the target area, the near-neighbor propagation clustering algorithm is used to divide the target area into multiple sub-areas, and each sub-area includes one or more distribution areas, so that a multi-level regulation architecture of target area - sub-area, sub-area - distribution area, and distribution area - distribution area can be obtained.

[0031] Among them, the multi - heterogeneous resources for photovoltaic and energy storage include, but are not limited to, distributed photovoltaic resources, distributed energy storage resources, and other renewable resources, such as wind power, biomass energy, geothermal energy, ocean energy, etc. The power grid system containing multi - heterogeneous resources for photovoltaic and energy storage will be cleaner, more flexible, and more efficient.

[0032] The historical data of the multi - heterogeneous resources for photovoltaic and energy storage in this embodiment include, but are not limited to, the geographical spatial distribution data of n substations in the target area, the historical output data of distributed photovoltaics, the configured capacity and maximum power of energy storage, the historical user load data, and the adjustable potential data of demand response. Among them, the target area and the number n of substations in the target area are determined according to the actual situation and are not specifically limited here.

[0033] The geographical spatial distribution data of the substation includes the location information of the substation (such as longitude and latitude), the boundary range, the location of the transformer, etc. The historical output data of distributed photovoltaics include the electricity generated by each distributed photovoltaic at different time points. The configured capacity of energy storage is used to describe the storage capacity of the energy storage system, and the maximum configured power of energy storage is used to describe the maximum charge - discharge power that the energy storage system can provide. The historical electricity load data reflects the electricity consumption of users at different times. The adjustable potential data of demand response represents the ability of users or specific devices to reduce or transfer their electricity consumption when receiving incentives.

[0034] The Affinity Propagation (AP) clustering algorithm is a clustering method based on message passing. Through the information exchange between nodes (such as the multi - heterogeneous resources for photovoltaic and energy storage in this embodiment), each node has the opportunity to become the "example" or "representative" of other nodes, so as to determine the optimal number of clustering centers and achieve clustering.

[0035] On the basis of dividing the target area into multiple sub - areas according to the historical data of the multi - heterogeneous resources for photovoltaic and energy storage in the target area in step S110 to obtain a multi - level control architecture, further, step S120 is executed.

[0036] S120, according to the current control requirements and the multi - level control architecture, split the area control problem of the target area into multiple sub - control problems at the target level; among them, the sub - control problems at the target level include the sub - area control problems of sub - areas or the sub - station control problems of substations.

[0037] It is easy to understand that the target area is the area to be regulated by the power grid, and the corresponding one is the area control problem (that is, the control target). After dividing the target area into multiple sub - areas, in order to respond to the control instructions more efficiently, correspondingly, it is also necessary to split the area control problem of the target area into multiple sub - control problems at the target level.

[0038] Specifically, in the case of clarifying the current regulation requirements, the regional regulation problem of the target area can be determined. Then, according to the index bearing capacity of different regions (this region can be a sub-region or a substation area) in the target hierarchy, the regional regulation problem can be split to obtain multiple sub-regulation problems at the target hierarchy.

[0039] Among them, the multi-level regulation framework from large to small is the target area - sub-region level, the sub-region - substation area level, and the substation area - substation area level. When conducting power grid regulation, one or more levels among the target area - sub-region level, the sub-region - substation area level, and the substation area - substation area level can be selected as the target level according to actual needs, so as to split the regional regulation problem into sub-regulation problems at the target level and solve the sub-regulation problems at the target level.

[0040] In a specific embodiment, the target level is the target area - sub-region level. In this case, the regional regulation problem needs to be split into multiple sub-region regulation problems of the sub-regions.

[0041] In another specific embodiment, when the target level is the sub-region - substation area level or the substation area - substation area level, in this case, first, the regional regulation problem needs to be split into multiple sub-region regulation problems of the sub-regions, and then the sub-region regulation problems of the sub-regions need to be further split into multiple substation area regulation problems of the substation areas.

[0042] Based on splitting the regional regulation problem of the target area into multiple sub-regulation problems at the target level according to the current regulation requirements and the multi-level regulation architecture in step S120, further, step S130 is executed.

[0043] S130, based on the multi-level regulation architecture, use the improved alternating direction method of multipliers to solve multiple sub-regulation problems at the target level in real time, and obtain the pre-regulation scheme of the multi-source heterogeneous resources of optical storage and utilization at a single time section at the target level.

[0044] It is easy to understand that in the case of knowing the multi-level regulation architecture and multiple sub-regulation problems at the target level, the improved alternating direction method of multipliers can be used to solve multiple sub-regulation problems at the target level one by one, and finally obtain the pre-regulation scheme of the multi-source heterogeneous resources of optical storage and utilization at a single time section at the target level.

[0045] The improved alternating direction method of multipliers in this embodiment introduces a column sum constraint generation algorithm to improve the performance of the traditional alternating direction method of multipliers. Specifically, each sub-regulation problem is solved by the column sum constraint generation algorithm and iteratively updated by the traditional alternating direction method of multipliers to gradually approach the optimal solution.

[0046] Among them, the alternating direction multiplier method combines the advantages of the Lagrange multiplier method and the splitting method, and is particularly suitable for large-scale data processing in a distributed computing environment. This method solves complex optimization problems by decomposing them into a series of simpler sub-problems and can effectively handle constraint conditions.

[0047] The core idea of the column and constraint generation algorithm is to gradually build the model instead of adding all variables and constraints to the initial model at once, which can significantly reduce the computational burden. Column generation is mainly used to handle optimization problems with a large number of potential variables; constraint generation is applicable to problems with a large number of potential constraint conditions.

[0048] After obtaining the pre-regulation plan by using the improved alternating direction multiplier method to solve multiple sub-regulation problems of the target level in real time based on the multi-level regulation architecture in step S130, further, step S140 is executed.

[0049] S140, according to the pre-regulation plan, regulate the multiple heterogeneous optical storage and utilization resources of the target level.

[0050] It is easy to understand that the pre-regulation plan of the multiple heterogeneous optical storage and utilization resources of the target level at a single time section is sent to the control systems of each sub-region or each sub-station area for execution, and the actual operation situation is continuously monitored and compared with the expected effect. If a large deviation is found, the regulation parameters are adjusted in time or the optimization solution is re-optimized. In addition, the performance of the entire power grid system should be evaluated regularly, potential improvement points should be identified, and the pre-regulation plan should be updated to adapt to the new environment and technological development.

[0051] In this embodiment, based on the historical data of the multiple heterogeneous optical storage and utilization resources of the target area, the target area is divided into multiple sub-regions to obtain a multi-level regulation architecture; among them, the sub-region includes one or more sub-station areas; according to the current regulation requirements and the multi-level regulation architecture, the regional regulation problem of the target area is split into multiple sub-regulation problems of the target level; among them, the sub-regulation problems of the target level include the sub-region regulation problems of the sub-region or the sub-station area regulation problems of the sub-station area; based on the multi-level regulation architecture, the improved alternating direction multiplier method is used to solve multiple sub-regulation problems of the target level in real time to obtain the pre-regulation plan of the multiple heterogeneous optical storage and utilization resources of the target level at a single time section; according to the pre-regulation plan, the multiple heterogeneous optical storage and utilization resources of the target level are regulated. This method can meet the precise regulation requirements of the power grid and achieve the effect of error regulation by considering the spatio-temporal correlation aggregation of the multiple heterogeneous optical storage and utilization resources to construct a multi-level regulation architecture and using the improved alternating direction multiplier method to solve the regional regulation problem in real time.

[0052] On the basis of the above embodiments, further, the process of dividing the target area will be described in detail below.

[0053] Based on the historical data of the multi - heterogeneous resources of photovoltaic, energy storage and load in the target area, the target area is divided into multiple sub - areas, including: generating a similarity matrix of distribution transformers according to the historical data of the multi - heterogeneous resources of photovoltaic, energy storage and load in the target area; initializing and updating the attraction and belonging degree of each distribution transformer in the target area; summing up the attraction and belonging degree of each distribution transformer to obtain a summation value; determining multiple target distribution transformers as clustering centers according to the summation values of each distribution transformer in the target area; obtaining multiple clusters based on the similarity matrix of distribution transformers and the multiple target distribution transformers; and there is a one - to - one correspondence between the clusters and the sub - areas.

[0054] It is easy to understand that considering the spatio - temporal correlation of the multi - heterogeneous resources of photovoltaic, energy storage and load, a similarity matrix S of distribution transformers can be generated according to the historical data of the multi - heterogeneous resources of photovoltaic, energy storage and load in the target area, and the Euclidean distance can be used as the similarity metric. Among them, the similarity matrix of distribution transformers is as shown in the following formula (1).

[0055] (1)。

[0056] (2)。

[0057] In formulas (1)-(2), used to describe the similarity between distribution transformer and distribution transformer 、 respectively represent the historical output data of the distributed photovoltaic of distribution transformer 、distribution transformer , 、 respectively represent the historical load data of users of distribution transformer 、distribution transformer , 、 respectively represent the adjustable potential data of demand response of distribution transformer 、distribution transformer , 、 respectively represent the energy storage configuration capacity of distribution transformer 、distribution transformer , 、 respectively represent the maximum power of the energy storage configuration of distribution transformer 、distribution transformer , 、 respectively represent the geospatial distribution data of distribution transformer 、distribution transformer , represents the time period, represents the total number of time periods divided per day, Indicates the serial number of geospatial distribution data, 1 represents the normalized distance on the longitude, and 2 represents the normalized distance on the latitude.

[0058] It should be noted that to avoid the differential impact brought by the substation area scale, the data used to calculate the substation area similarity matrix (i.e., substation area geospatial distribution data, historical output data of distributed photovoltaics, energy storage configuration capacity and maximum power, historical user load data, and demand response adjustable potential data, etc.) are all data after normalization processing.

[0059] Subsequently, determine the attraction calculation formula and the membership calculation formula for each substation area in the target area, and initialize the membership of all substation areas to 0. Among them, the attraction calculation formula and the membership calculation formula can be seen in the following formula (3)-(3).

[0060] (3).

[0061] (4).

[0062] (5).

[0063] In formulas (3)-(5), represents the substation area to the candidate clustering center substation area 's attraction, which reflects the degree to which the substation area is suitable as the substation area clustering center, represents the substation area to the candidate clustering center substation area 's membership, which reflects the verification degree that the substation area selects the substation area as the clustering center considering other substation areas planned to use the substation area as the clustering center, represents the similarity between the substation area and the substation area , represents the node , represents the substation area to the candidate clustering center substation area 's attraction, represents the node , represents the substation area to the candidate clustering center substation area 's membership.

[0064] Furthermore, the attraction of the station area is updated given the attribution of each station area, and the attribution of the station area is updated given the attraction of each station area. Then the attraction and attribution of each station area are summed, and if the sum value obtained is greater than the set value (for example, 0), the station area is updated as the cluster center. If the cluster center remains unchanged after multiple iterations or the number of iterations reaches a preset number of iterations, the iteration is terminated. In this way, multiple target stations can be determined as cluster centers.

[0065] Next, multiple clusters are obtained based on the similarity between other sub-areas that are not cluster centers and the target sub-area that is the cluster center. These multiple clusters correspond one-to-one to multiple sub-areas, that is, each cluster represents a sub-area, thereby achieving the purpose of dividing the target area into multiple sub-areas.

[0066] Subsequently, based on the clustering results, different substations are divided into their corresponding sub-regions, thus obtaining a multi-level regulatory framework consisting of target area-sub-region-substation.

[0067] In this embodiment, by generating a substation similarity matrix based on the historical data of the multi-heterogeneous resources of the target area, the attraction and belonging of each substation in the target area are initialized and updated, and then the attraction and belonging of each substation are summed, and multiple target substations as cluster centers are determined according to the summed values ​​of each substation in the target area, and then multiple clusters corresponding to the sub-areas are obtained according to the substation similarity matrix and the multiple target substations, so as to obtain a multi-level control framework. Therefore, based on the multi-level control framework, the improved alternating direction multiplier method is used to solve multiple sub-control problems of the target level in real time, and the pre-control scheme of the multi-heterogeneous resources of the target level for the photovoltaic storage in a single time section is obtained; according to the pre-control scheme, the multi-heterogeneous resources of the target level for the photovoltaic storage are regulated. This method constructs a multi-level control framework by considering the spatiotemporal correlation aggregation of the multi-heterogeneous resources of the photovoltaic storage, and uses the improved alternating direction multiplier method to solve the regional control problem in real time, which can meet the precise control needs of the power grid and achieve the effect of error control.

[0068] On the basis of the above-mentioned embodiments, the division process of the regional regulation problem will be further described in detail below.

[0069] According to the current regulation requirements and multi-level regulation framework, the regional regulation problem of the target area is split into multiple sub-regulation problems at the target level, including: calculating, according to the multi-level regulation framework, the index bearing capacity of the diversified heterogeneous resources of optical storage and utilization within the target level for the current regulation requirements; the index bearing capacity includes one or a combination of multiple items such as peak shaving index bearing capacity, frequency modulation index bearing capacity, and photovoltaic accommodation index bearing capacity; calculating the index requirements of multiple target levels with the index bearing capacity as the weight, so as to split the regional regulation problem of the target area into multiple sub-regulation problems belonging to the target level.

[0070] It is easy to understand that, according to the multi-level regulation framework, the index bearing capacity of the diversified heterogeneous resources of optical storage and utilization within the target level for the current regulation requirements can be calculated. Among them, the current regulation requirements include, but are not limited to, one or a combination of multiple index requirements such as power supply-demand balance, improvement of power quality, energy conservation and emission reduction, peak shaving, frequency modulation, and maximization of photovoltaic accommodation in normal scenarios and special scenarios.

[0071] The normal scenario refers to the normal operation state of the power grid without the influence of extreme weather and major social events, including the load changes on typical days such as weekdays, weekends, and holidays. Special scenarios include extreme weather events and emergencies. Extreme weather events such as the peak electricity consumption caused by high temperatures in summer, the increased heating load due to severe cold in winter, the damage of power grid facilities or the sudden change of distributed energy output caused by typhoons and heavy rains, and emergencies such as power grid failures and large-scale accidents leading to partial or large-area power outages, which require emergency allocation of resources for rapid restoration.

[0072] For the case where the current regulation requirements include peak shaving indicators, the peak shaving index bearing capacity of each area (sub-area or substation area) at the target level, including the upward adjustment ability and the downward adjustment ability, can be determined according to the total energy storage capacity, energy storage charge-discharge power, and demand response adjustable potential of the target level (sub-area or substation area).

[0073] For the case where the current regulation requirements include frequency modulation indicators, the frequency modulation index bearing capacity of each area (sub-area or substation area) at the target level, including frequency modulation speed, frequency modulation accuracy, response time, and duration, etc., can be determined according to the total energy storage charge-discharge power and demand response adjustable potential of the target level (sub-area or substation area).

[0074] For the case where the current regulation requirements include the maximization of photovoltaic accommodation indicators, the photovoltaic accommodation index bearing capacity of each area (sub-area or substation area) at the target level, including the maximum surplus power generation and utilization ratio of photovoltaic , photovoltaic accommodation ratio etc. The maximum surplus power generation and utilization ratio of photovoltaic , photovoltaic accommodation ratio The calculation formula can be seen in the following formulas (6)-(7).

[0075] (6).

[0076] (7).

[0077] In formulas (6)-(7), and represent the load power and the maximum load power within the measurement period at time respectively, represents the output power of the distributed photovoltaic at time ; represents the electricity consumption, represents the photovoltaic power generation.

[0078] After calculating the index bearing capacity of the multi-source heterogeneous resources of optical storage and utilization for the current regulation demand within the target level, the index requirements that each region (sub-region or substation area) of the target level needs to bear are calculated with the index bearing capacity as the weight. Thus, the regional regulation problem of the target area can be split into multiple sub-regulation problems belonging to the target level.

[0079] In this embodiment, according to the multi-level regulation architecture, the index bearing capacity of the multi-source heterogeneous resources of optical storage and utilization for the current regulation demand within the target level is calculated, and then, with the index bearing capacity as the weight, the index requirements of multiple target levels are calculated to split the regional regulation problem of the target area into multiple sub-regulation problems belonging to the target level. Furthermore, based on the multi-level regulation architecture, the improved alternating direction multiplier method is used to solve the multiple sub-regulation problems of the target level in real time, and a pre-regulation scheme of the multi-source heterogeneous resources of optical storage and utilization at a single time section of the target level is obtained; according to the pre-regulation scheme, the multi-source heterogeneous resources of optical storage and utilization at the target level are regulated. This method constructs a multi-level regulation architecture by considering the spatio-temporal correlation aggregation of the multi-source heterogeneous resources of optical storage and utilization, and uses the improved alternating direction multiplier method to solve the regional regulation problem in real time, which can meet the accurate regulation demand of the power grid and achieve the effect of error regulation.

[0080] On the basis of the above embodiment, further, the real-time solution process of multiple sub-regulation problems will be described in detail below.

[0081] Based on the multi-level regulation architecture, the improved alternating direction multiplier method is used to solve the multiple sub-regulation problems of the target level in real time. Specifically, Figure 2 shows the schematic diagram of the algorithm flow of the improved alternating direction multiplier method provided by the embodiment of the present invention. As Figure 2 shown, the improved alternating direction multiplier method includes steps S311-S317.

[0082] S311. Initialize the number of iterations and the region number. Given the initial values of all variables and parameters, for example, initialize the number of iterations , and the initial region number .

[0083] S312. According to the initial control value corresponding to the initial region number, use the column sum constraint generation algorithm to solve the sub-control problem corresponding to the initial region number .

[0084] Among them, the initial control value can be calculated according to the control index, including energy storage charge and discharge, demand response, etc. The column sum constraint generation algorithm here is just a better way, and it can also be replaced by other robust optimization algorithms, which are not specifically limited here.

[0085] S313. When the initial region number is greater than any interconnection region number, update the corresponding multiplier from the current region of the initial region number and transmit the solution result to the interconnection region. The interconnection region described in this step refers to the region adjacent to the region where the sub-control problem in step S312 is located (i.e., the current region).

[0086] S314. Compare the initial region number with the maximum region number. The maximum region number here is the same as the number of sub-regions obtained by division.

[0087] S315. When the initial region number is not greater than the maximum region number, update the initial region number , and execute steps S312 - S314.

[0088] S316. When the initial region number is greater than the maximum region number, but the control error is greater than or equal to the given error, update the number of iterations and initialize the region number , and execute steps S312 - S314.

[0089] S317. When the initial region number is greater than the maximum region number, and the control error is less than the given error, end the iteration and output the pre-control scheme of the multi-source heterogeneous resources of optical storage and utilization at a single time section of the target level.

[0090] In this embodiment, based on the multi-level control architecture, the improved alternating direction multiplier method is used to solve multiple sub-control problems of the target level in real time, and the pre-control scheme of the multi-source heterogeneous resources of optical storage and utilization at a single time section of the target level is obtained; according to the pre-control scheme, the multi-source heterogeneous resources of optical storage and utilization at the target level are controlled. This method constructs a multi-level control architecture by considering the spatio-temporal correlation aggregation of the multi-source heterogeneous resources of optical storage and utilization, and uses the improved alternating direction multiplier method to solve the regional control problem in real time, which can meet the accurate control requirements of the power grid and achieve the effect of error control.

[0091] On the basis of the above embodiments, further, the update and optimization process of the pre-regulation scheme will be described in detail below.

[0092] According to the pre-regulation scheme, regulate the multi-source heterogeneous resources of photovoltaic energy storage and utilization at the target level of regulation. Subsequently, it also includes: real-time monitoring of the latest status data of the multi-source heterogeneous resources of photovoltaic energy storage and utilization at the target level; real-time evaluation of the pre-regulation effect of the pre-regulation scheme; correction of the pre-regulation scheme according to the latest status data and the pre-regulation effect; and regulation of the multi-source heterogeneous resources of photovoltaic energy storage and utilization at the target level according to the corrected pre-regulation scheme.

[0093] It is easy to understand that after implementing the pre-regulation scheme, the latest status data of the multi-source heterogeneous resources of photovoltaic energy storage and utilization at the target level can be monitored in real time through the deployed sensor devices, including the photovoltaic output of the substation area, load changes, and fluctuations of adjustable resources, etc., to ensure the accuracy of the data.

[0094] Among them, the latest status data includes but is not limited to the geographical spatial distribution data of the substation area, the output data of distributed photovoltaics, the configured capacity and maximum power of energy storage, user load data, and the adjustable potential data of demand response.

[0095] Subsequently, implement the evaluation of the pre-regulation effect of the pre-regulation scheme. Specifically, set a series of key indicators, such as power grid stability, renewable energy utilization rate, operating cost, etc., and regularly compare the pre-regulation effect with the key indicators to identify deviations and potential problems, so as to measure the pre-regulation effect of the pre-regulation scheme.

[0096] Immediately afterwards, according to the latest status data and the pre-regulation effect, re-divide the sub-regions, re-solve the corresponding sub-regulation problems, and timely correct the pre-regulation scheme.

[0097] Finally, according to the corrected pre-regulation scheme, quickly adjust the regulation instructions to regulate the multi-source heterogeneous resources of photovoltaic energy storage and utilization at the target level.

[0098] In this embodiment, the implementation of the pre-regulation scheme and the correction of the pre-regulation scheme form a periodic rolling closed loop, which can quickly adjust the regulation instructions to ensure that the regulation result can achieve the expected regulation effect and achieve the goal of error-free regulation.

[0099] It is worth mentioning that the grid hierarchical regulation method with optical storage and multiple heterogeneous resources provided by the embodiments of the present invention effectively overcomes the problem of low accuracy of regulation instruction response caused by large modeling errors of traditional linear aggregation algorithms and the lack of consideration of the spatio-temporal correlation of adjustable potential between substations. It can be based on a multi-level regulation architecture of target area - sub-area, sub-area - substation area, and substation area - substation area, and through an improved alternating direction multiplier method, solve multiple sub-regulation problems in real time. Considering the fluctuations of distributed photovoltaic power output, load, and adjustable potential within the substation area during the real-time operation process, based on the time-domain rolling mechanism, roll to solve and update the pre-regulation plan, and based on the real-time evaluation results of the pre-regulation plan, correct the pre-regulation plan to make the overall regulation power reach the planned target value and achieve the effect of error-free regulation.

[0100] Corresponding to the grid hierarchical regulation method with optical storage and multiple heterogeneous resources described in the above embodiments, the present invention also proposes a grid hierarchical regulation device with optical storage and multiple heterogeneous resources.

[0101] Specifically, Figure 3 The structural schematic diagram of the grid hierarchical regulation device with optical storage and multiple heterogeneous resources provided by the embodiments of the present invention is shown.

[0102] As Figure 3 shown, the device includes: a target area division module 310, configured to divide the target area into multiple sub-areas based on the historical data of optical storage and multiple heterogeneous resources in the target area, to obtain a multi-level regulation architecture; wherein, the sub-area includes one or more substations; a regional regulation problem division module 320, configured to split the regional regulation problem of the target area into multiple sub-regulation problems at the target level according to the current regulation requirements and the multi-level regulation architecture; wherein, the sub-regulation problems at the target level include sub-regional regulation problems of the sub-area or substation area regulation problems of the substation area; a sub-regulation problem solving module 330, configured to based on the multi-level regulation architecture, use an improved alternating direction multiplier method to solve multiple sub-regulation problems at the target level in real time, to obtain a pre-regulation plan of optical storage and multiple heterogeneous resources at the target level at a single time section; a grid hierarchical regulation module 340, configured to regulate the optical storage and multiple heterogeneous resources at the target level according to the pre-regulation plan.

[0103] In this embodiment, the target area division module 310 divides the target area into multiple sub-areas based on the historical data of the multi-source heterogeneous resources of photovoltaic energy storage and power consumption in the target area, obtaining a multi-level control architecture; wherein, the sub-areas include one or more distribution areas; the area control problem division module 320 splits the area control problem of the target area into multiple sub-control problems at the target level according to the current control requirements and the multi-level control architecture; wherein, the sub-control problems at the target level include the sub-area control problems of the sub-areas or the distribution area control problems of the distribution areas; the sub-control problem solving module 330 performs real-time solution on the multiple sub-control problems at the target level based on the multi-level control architecture by using the improved alternating direction method of multipliers, obtaining a pre-control plan for the multi-source heterogeneous resources of photovoltaic energy storage and power consumption at the target level at a single time section; the power grid multi-level control module 340 controls the multi-source heterogeneous resources of photovoltaic energy storage and power consumption at the target level according to the pre-control plan. By considering the spatio-temporal correlation aggregation of the multi-source heterogeneous resources of photovoltaic energy storage and power consumption to construct a multi-level control architecture and using the improved alternating direction method of multipliers to perform real-time solution on the area control problem, this device can meet the accurate control requirements of the power grid and achieve the effect of error control.

[0104] It should be noted that the power grid hierarchical control device with multi-source heterogeneous resources of photovoltaic energy storage and power consumption provided in the embodiments of the present invention can be correspondingly referred to the power grid hierarchical control method with multi-source heterogeneous resources of photovoltaic energy storage and power consumption described in the above embodiments, and will not be elaborated here.

[0105] Figure 4 An entity structure diagram of an electronic device is exemplified, as Figure 4 shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430, and a communication bus 440. Among them, the processor 410, the communication interface 420, and the memory 430 complete mutual communication through the communication bus 440. The processor 410 can call the logical instructions in the memory 430 to execute the power grid hierarchical control method with multi-source heterogeneous resources of photovoltaic energy storage and power consumption. The method includes: dividing the target area into multiple sub-areas based on the historical data of the multi-source heterogeneous resources of photovoltaic energy storage and power consumption in the target area, obtaining a multi-level control architecture; wherein, the sub-areas include one or more distribution areas; splitting the area control problem of the target area into multiple sub-control problems at the target level according to the current control requirements and the multi-level control architecture; wherein, the sub-control problems at the target level include the sub-area control problems of the sub-areas or the distribution area control problems of the distribution areas; performing real-time solution on the multiple sub-control problems at the target level based on the multi-level control architecture by using the improved alternating direction method of multipliers, obtaining a pre-control plan for the multi-source heterogeneous resources of photovoltaic energy storage and power consumption at the target level at a single time section; controlling the multi-source heterogeneous resources of photovoltaic energy storage and power consumption at the target level according to the pre-control plan.

[0106] In addition, when the logical instructions in the above-mentioned memory 430 can be implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs.

[0107] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the grid hierarchical regulation method with optical storage and multi-heterogeneous resources provided by the above-mentioned various methods. The method includes: dividing a target area into multiple sub-areas based on the historical data of the optical storage and multi-heterogeneous resources in the target area to obtain a multi-level regulation architecture; wherein, the sub-area includes one or more distribution transformer areas; splitting the area regulation problem of the target area into multiple sub-regulation problems at the target level according to the current regulation requirements and the multi-level regulation architecture; wherein, the sub-regulation problems at the target level include sub-area regulation problems of the sub-areas or distribution transformer area regulation problems of the distribution transformer areas; based on the multi-level regulation architecture, using the improved alternating direction method of multipliers to solve the multiple sub-regulation problems at the target level in real time to obtain a pre-regulation plan for the optical storage and multi-heterogeneous resources at the target level at a single time section; regulating the optical storage and multi-heterogeneous resources at the target level according to the pre-regulation plan.

[0108] In another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is used to execute the hierarchical regulation method of the power grid with optical storage and multi-source heterogeneous resources provided by the above-mentioned various methods. The method includes: dividing the target area into multiple sub-areas based on the historical data of the optical storage and multi-source heterogeneous resources in the target area to obtain a multi-level regulation architecture; wherein, the sub-areas include one or more transformer substations; according to the current regulation requirements and the multi-level regulation architecture, splitting the area regulation problem of the target area into multiple sub-regulation problems at the target level; wherein, the sub-regulation problems at the target level include sub-area regulation problems of the sub-areas or transformer substation regulation problems of the transformer substations; based on the multi-level regulation architecture, using the improved alternating direction multiplier method to solve the multiple sub-regulation problems at the target level in real time to obtain a pre-regulation plan for the optical storage and multi-source heterogeneous resources at the target level at a single time section; according to the pre-regulation plan, regulating the optical storage and multi-source heterogeneous resources at the target level.

[0109] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative labor.

[0110] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the essence of the above technical solutions, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0111] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A hierarchical control method for a power grid containing multiple heterogeneous resources including photovoltaic storage, characterized in that: include: Based on the historical data of the multi-dimensional heterogeneous resources of the target area for photovoltaic storage, the target area is divided into multiple sub-areas to obtain a multi-level control architecture; wherein the sub-area includes one or more substations; According to the current regulation demand and the multi-level regulation framework, the regional regulation problem of the target area is divided into multiple sub-regulation problems at the target level; wherein the sub-regulation problems at the target level include sub-regional regulation problems of sub-areas or sub-area regulation problems of sub-areas; Based on the multi-level control architecture, an improved alternating direction multiplier method is used to solve multiple sub-control problems at the target level in real time, and a pre-control scheme for the target level's photovoltaic and storage multi-heterogeneous resources at a single time section is obtained; According to the pre-regulation scheme, the photovoltaic storage multi-heterogeneous resources at the target level are regulated.

2. The hierarchical control method for a power grid containing multiple heterogeneous resources including photovoltaic storage and utilization according to claim 1 is characterized in that: The historical data of multi-heterogeneous resources for photovoltaic storage include geographical spatial distribution data of substations, historical output data of distributed photovoltaics, energy storage configuration capacity and maximum power, historical data of user loads, and demand response adjustable potential data.

3. The hierarchical control method for a power grid containing multiple heterogeneous resources including photovoltaic storage and utilization according to claim 1 is characterized in that: The target area is divided into a plurality of sub-areas based on the historical data of the multi-dimensional heterogeneous resources for photovoltaic storage in the target area, including: Generate a similarity matrix of substations based on historical data of multi-dimensional heterogeneous resources of photovoltaic and storage in the target area; Initialize the attraction and belongingness of each area in the target area and update them; The attraction degree and belonging degree of each area are summed to obtain the sum value; According to the summed values ​​of each substation in the target area, multiple target substations are determined as cluster centers; According to the station area similarity matrix and multiple target stations, multiple clusters are obtained; the clusters correspond to the sub-areas one by one.

4. The hierarchical control method for a power grid containing multiple heterogeneous resources including photovoltaic storage and utilization according to claim 1, characterized in that: According to the current regulation requirements and the multi-level regulation architecture, the regional regulation problem of the target area is divided into multiple sub-regulation problems at the target level, including: According to the multi-level control framework, the index bearing capacity of the multi-heterogeneous resources of photovoltaic storage and use in the target level for the current control demand is calculated; the index bearing capacity includes one or more combinations of peak load bearing capacity, peak load bearing capacity and photovoltaic consumption bearing capacity; The indicator requirements of multiple target levels are calculated using the indicator bearing capacity as weight, so as to split the regional regulation problem of the target area into multiple sub-regulation problems belonging to the target level.

5. The hierarchical control method for a power grid containing multiple heterogeneous resources including photovoltaic storage and utilization according to claim 1, characterized in that: Based on the multi-level control framework, the improved alternating direction multiplier method is used to solve multiple sub-control problems at the target level in real time, including: S311, initializing the number of iterations and the region number; S312, according to the initial control value corresponding to the initial area number, using the column and constraint generation algorithm to solve the sub-control problem corresponding to the initial area number; S313, when the initial region number is greater than any interconnected region number, the current region of the initial region number updates the corresponding multiplier, and transmits the solution result to the interconnected region; S314, comparing the initial area number with the maximum area number; S315, when the initial area number is not greater than the maximum area number, updating the initial area number and executing steps S312-S314; S316, when the initial region number is greater than the maximum region number, but the control error is greater than or equal to the given error, update the number of iterations and initialize the region number, and execute steps S312-S314; S317, when the initial area number is greater than the maximum area number and the control error is less than a given error, the iteration is terminated, and a pre-control scheme for the target-level photovoltaic storage multi-heterogeneous resources in a single time section is output.

6. The hierarchical control method for a power grid containing multiple heterogeneous resources including photovoltaic storage and utilization according to claim 1, characterized in that: According to the pre-regulation scheme, the target level of the photovoltaic storage multi-source heterogeneous resources is regulated, and then the following is further included: Real-time monitoring of the latest status data of multiple heterogeneous resources for photovoltaic storage at the target level; Real-time evaluation of the pre-regulation effect of the pre-regulation scheme; According to the latest status data and the pre-control effect, modify the pre-control plan; According to the revised pre-regulation scheme, the photovoltaic storage and diversified heterogeneous resources at the target level are regulated.

7. A hierarchical control device for a power grid containing multiple heterogeneous resources including photovoltaic storage, characterized in that: include: The target area division module is used to divide the target area into multiple sub-areas based on the historical data of the multi-dimensional heterogeneous resources of the target area for photovoltaic storage, so as to obtain a multi-level control architecture; wherein the sub-area includes one or more substations; A regional control problem division module is used to divide the regional control problem of the target area into multiple sub-control problems of the target level according to the current control demand and the multi-level control architecture; wherein the sub-control problem of the target level includes the sub-regional control problem of the sub-region or the sub-station control problem of the sub-station; A sub-regulation problem solving module is used to solve multiple sub-regulation problems of the target level in real time based on the multi-level regulation architecture by using an improved alternating direction multiplier method to obtain a pre-regulation scheme for the target level's photovoltaic and storage multi-heterogeneous resources in a single time section; The grid hierarchical control module is used to control the photovoltaic and storage multi-heterogeneous resources at the target level according to the pre-control plan.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the method for hierarchical control of a power grid containing multiple heterogeneous resources including photovoltaic storage and utilization as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for hierarchical control of a power grid containing multiple heterogeneous resources including photovoltaic energy storage and utilization as described in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for hierarchical control of a power grid containing multiple heterogeneous resources including photovoltaic energy storage and utilization as described in any one of claims 1 to 6 is implemented.

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