CN115207947B

CN115207947B - Power grid node energy storage configuration method and device, computer equipment and storage medium

Info

Publication number: CN115207947B
Application number: CN202210689838.0A
Authority: CN
Inventors: 郭子暄; 刘平; 宫大千; 辜炜德; 黄豫; 李震; 高啸天; 覃芸; 郑可昕
Original assignee: Energy Development Research Institute of China Southern Power Grid Co Ltd
Current assignee: Energy Development Research Institute of China Southern Power Grid Co Ltd
Priority date: 2022-06-17
Filing date: 2022-06-17
Publication date: 2023-04-07
Anticipated expiration: 2042-06-17
Also published as: CN115207947A

Abstract

The application relates to a power grid node energy storage configuration method, a power grid node energy storage configuration device, a computer device, a storage medium and a computer program product. The method comprises the following steps: determining a target independent storage value of the target area based on the maximum load bearing capacity of the target area; acquiring the number of power supplies in a target area within a preset time period and power cost information of the power supplies in each area; calculating to obtain a first node electricity price of each power grid node based on the number of power supplies in the target area and power supply cost information of the power supplies in each area; determining a second node electricity price of each power grid node through the first node electricity price of each power grid node; and acquiring a power grid node energy storage configuration set based on the target independent energy storage value, the first node electricity price of each power grid node and the second node electricity price of each power grid node, wherein the power grid node energy storage configuration set comprises the maximum electric quantity energy storage value of each power grid node. The method can improve the reliability of the obtained power grid node energy storage configuration set.

Description

Power grid node energy storage configuration method and device, computer equipment and storage medium

Technical Field

The present application relates to the field of power energy storage technologies, and in particular, to a power grid node energy storage configuration method and apparatus, a computer device, and a storage medium.

Background

With the continuous development of domestic energy storage technology, the scale of power grid energy storage is increasingly large, the traditional fossil energy construction process is gradually slowed down, and with the continuous growth of national economy, the power supply situation of a central city is more and more tense. Therefore, for urban areas with dense users, independent energy storage at the power grid side can be used as an effective way for relieving local power supply areas, so that the independent energy storage gradually occupies a more important position in various energy storage application scenes, the urban energy storage construction is greatly limited by land utilization rate and construction cost, the regional power grid operation condition is considered, and how to provide power grid node energy storage configuration with high reliability and a planning layout scheme is a main problem for large-range regional energy storage planning of the current city.

At present, the coupling degree of the power generation power and the load characteristic of a power supply in a certain time range of renewable energy sources can be analyzed to aim at solving the problems of inverse peak regulation and local sending difficulty, and the configuration scale of the energy storage of the power grid nodes is obtained. However, the actual situation of the grid network frame in the urban area with dense users is complex, so that the reliability of the configuration of the grid node energy storage is low. Therefore, how to ensure the reliability of the configuration and distribution of the energy storage of the grid nodes is an urgent problem to be solved.

Disclosure of Invention

In view of the foregoing, it is necessary to provide a power grid node energy storage configuration method, apparatus, computer device, computer readable storage medium, and computer program product, which can improve reliability of power grid node energy storage configuration.

In a first aspect, the application provides a power grid node energy storage configuration method. The method comprises the following steps:

determining a target independent storage value of a target area based on the maximum load bearing capacity of the target area, wherein the target area comprises a plurality of power grid nodes;

acquiring the number of power supplies in a target area within a preset time period and power cost information of the power supplies in each area;

calculating to obtain a first node electricity price of each power grid node based on the number of power supplies in the target area and the power cost information of the power supplies in each area;

determining a second node electricity price of each power grid node through the first node electricity price of each power grid node, wherein the second node electricity price is a node electricity price in a non-blocking state in a preset time period, and the non-blocking state is that the node load of each power grid node is smaller than a blocking threshold value;

and acquiring a power grid node energy storage configuration set based on the target independent energy storage value, the first node electricity price of each power grid node and the second node electricity price of each power grid node, wherein the power grid node energy storage configuration set comprises the maximum electric quantity energy storage value of each power grid node.

In a second aspect, the application further provides a power grid node energy storage configuration device. The device comprises:

the determination module is used for determining a target independent storage value of a target area based on the maximum load bearing capacity of the target area, and the target area comprises a plurality of power grid nodes;

the acquisition module is used for acquiring the number of power supplies in a target area within a preset time period and power cost information of each power supply in the area;

the calculation module is used for calculating and obtaining the electricity price of the first node of each power grid node based on the number of power supplies in the target area and the power cost information of the power supplies in each area;

the determining module is further used for determining a second node electricity price of each power grid node through the first node electricity price of each power grid node, wherein the second node electricity price is a node electricity price in a non-blocking state within a preset time period, and the non-blocking state is that the node load of each power grid node is smaller than a blocking threshold value;

the obtaining module is further configured to obtain a power grid node energy storage configuration set based on the target independent energy storage value, the first node electricity price of each power grid node, and the second node electricity price of each power grid node, where the power grid node energy storage configuration set includes the maximum electric quantity energy storage value of each power grid node.

In a third aspect, the application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the following steps when executing the computer program:

acquiring the number of power supplies in a target area within a preset time period and power supply cost information of each power supply in the target area;

calculating to obtain a first node electricity price of each power grid node based on the number of power supplies in the target area and power supply cost information of the power supplies in each area;

In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:

determining a target independent storage value of a target area based on the maximum bearing load of the target area, wherein the target area comprises a plurality of power grid nodes;

and acquiring a power grid node energy storage configuration set based on the target independent energy storage value, the first node electricity price of each power grid node and the second node electricity price of each power grid node, wherein the power grid node energy storage configuration set comprises the maximum value of the electric quantity energy storage of each power grid node.

In a fifth aspect, the present application further provides a computer program product. The computer program product comprising a computer program which when executed by a processor performs the steps of:

The power grid node energy storage configuration method, the device, the computer equipment, the storage medium and the computer program product are characterized in that firstly, a target independent energy storage value of a target area is determined based on the maximum load bearing capacity of the target area, the target area comprises a plurality of power grid nodes, then the number of power supplies in the target area in a preset time period and power supply cost information of the power supplies in each area are obtained, then, a first node electricity price of each power grid node is obtained through calculation based on the number of the power supplies in the target area and the power supply cost information of the power supplies in each area, a second node electricity price of each power grid node is determined through the first node electricity price of each power grid node, the second node electricity price is a node electricity price in a non-blocking state in the preset time period, the non-blocking state is that the node load of the power grid node is smaller than a blocking threshold value, and finally, a power grid node energy storage configuration set is obtained based on the target independent energy storage value, the first node electricity price of each power grid node and the second node electricity price of each power grid node, and the power price of each power grid node, and the power storage configuration set of the power grid nodes includes the maximum electric quantity of the power storage of each power grid node. By the method, because the node in the non-blocking state is stable in electricity price and the power grid nodes can normally and stably supply power, the electricity price of each power grid node can be balanced by considering the electricity price when energy storage configuration is carried out, and the load level of a target area can be considered through the target independent energy storage value determined by the maximum load bearing load. Therefore, the reliability of the obtained power grid node energy storage configuration set is improved.

Drawings

FIG. 1A is a schematic diagram of a power grid configuration of a 500kV power supply block in one embodiment;

FIG. 1B is a schematic diagram of a power grid structure of a 500kV power supply area in another embodiment;

FIG. 1C is a schematic diagram of a power grid structure of a 500kV power supply area in yet another embodiment;

fig. 2 is a schematic flow chart of a power grid node energy storage configuration method in an embodiment;

fig. 3 is a schematic flow chart illustrating a step of acquiring a power grid node energy storage configuration set in one embodiment;

fig. 4 is a schematic flow chart of a power grid node energy storage configuration method in another embodiment;

fig. 5 is a schematic flow chart illustrating a step of obtaining a power grid node energy storage configuration set in another embodiment;

FIG. 6 is a flowchart illustrating the step of obtaining a target independent energy storage value according to an embodiment;

FIG. 7 is a schematic flowchart illustrating a step of obtaining a target independent energy storage value according to another embodiment;

FIG. 8 is a flowchart illustrating the step of determining a target energy storage value based on a second load curve according to one embodiment;

FIG. 9 is a flowchart illustrating the second node electricity price step of determining each grid node in one embodiment;

fig. 10 is an overall flow diagram of a power grid node energy storage configuration method in one embodiment;

fig. 11 is a block diagram of a configuration device for grid node energy storage according to an embodiment;

FIG. 12 is a diagram illustrating an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

The power grid node energy storage configuration method provided by the embodiment of the application is particularly applied to a 500 kilovolt (kV) power supply area power grid structure. Specifically, a schematic diagram of a 500kV power supply district power grid structure is shown in fig. 1A to 1C, where fig. 1A to 1C include a 500kV substation 102 and a 220kV substation 104, and fig. 1A to 1C all use the 500kV substation as a superior power supply and include a power grid structure of a plurality of 220kV substations. The 500kV power supply zone power grid structure specifically comprises but is not limited to a chain structure, a ring network shaped like a Chinese character 'ri', a ring network shaped like a Chinese character 'kou', a double 500kV power supply zone manual connection ring network and the like.

In an embodiment, as shown in fig. 2, a power grid node energy storage configuration method is provided, and this embodiment is illustrated by applying the method to a server, it is to be understood that the method may also be applied to a terminal, and may also be applied to a system including the terminal and the server, and is implemented by interaction between the terminal and the server. The terminal can be but not limited to various personal computers, notebook computers, smart phones, tablet computers and internet of things equipment, and the internet of things equipment can be smart speakers, smart televisions, smart air conditioners, smart vehicle-mounted equipment and the like. The server may be implemented as a stand-alone server or as a server cluster of multiple servers. The method specifically comprises the following steps:

step 202, determining a target independent storage value of a target area based on the maximum load of the target area, wherein the target area comprises a plurality of grid nodes.

Before determining the target independent energy storage value, the server needs to investigate the overall load level of the target area, specifically, the energy storage construction condition of the target area and the specific power grid structure of the target area need to be investigated, and the server can determine the maximum load bearing capacity of the target area according to the investigation result. For example, target area a is an area with open mountainous areas and target area B is an area with dense urban areas, then the maximum load bearing of target area a may be greater than the maximum load bearing of target area B.

Based on the target area, the server calculates based on the maximum load of the target area to determine the target independent storage value of the target area. Specifically, the target area includes a plurality of grid nodes, e.g., target area a includes grid node A1, grid node A2, and grid node A3, and target area B includes grid node B1, grid node B2, grid node B3, and grid node B4.

Step 204, acquiring the number of power supplies in the target area within a preset time period, and power supply cost information of each power supply in the target area.

The server acquires the number of the power supplies in the target area within a preset time period and power cost information of the power supplies in each area. Specifically, the preset time period may be one year, one half year or one quarter, and the power cost information specifically includes marginal cost information and original cost information. The number of power supplies in the region needs to be determined according to actual conditions such as the actual area of the target region and the actual power utilization condition, and the power supply cost information needs to be determined based on the actual pricing condition of the power supply provider.

And step 206, calculating to obtain the first node electricity price of each power grid node based on the number of the power supplies in the target area and the power supply cost information of each power supply in the area.

Specifically, the server needs to acquire a node peak load of each power grid node in a peak load state, and then determines a first node electricity price of each power grid node based on a power supply quote of a power supply in each region, a specific power grid structure and the node peak load of each power grid node in the peak load state.

And the power supply quote for each intra-zone power supply is determined based on the intra-zone power supply quantity for the target area and the power supply cost information for each intra-zone power supply. And under the condition that the number of the power supplies in the target area is equal to 1 and the number of the power supplies in the target area is greater than 1, the server adopts different calculation methods to quote the power supplies of the power supplies in each area. In practical application, when only one intra-area power supply exists in a target area, the intra-area power supply is an area monopolizing power supply in the target area, and monopolizing of the intra-area power supply is considered, at the moment, when power supply price quotation of the intra-area power supply is calculated, on the basis of considering the price quotation level of power supply cost information, a monopolizing floating coefficient is also considered, and marginal cost information in the power supply cost information is adopted during specific calculation. Second, when the number of intra-zone power supplies of the target area is greater than 1, the power generated by the power supply of each intra-zone power supply is more focused at this time.

Based on this, the power supply quote of the in-zone power supply is calculated as formula (1):

wherein bid _mar-in Power supply quote, bid, indicating in-district power supply _mar-main Marginal cost information, count, in power cost information representing power supplies within a region _G Denotes the number of in-zone power supplies of the target area, and Cost (G) denotes the in-zone power supplyG represents the power generated by the power supply in the region, κ represents the monopolistic float coefficient, and κ in this embodiment is specifically 20%.

And 208, determining a second node electricity price of each power grid node through the first node electricity price of each power grid node, wherein the second node electricity price is a node electricity price in a non-blocking state within a preset time period, and the non-blocking state is that the node load of each power grid node is smaller than a blocking threshold value.

The server further calculates based on the first node electricity prices for each grid node to determine second node electricity prices for each grid node. Specifically, the second node electricity price is a node electricity price in a non-blocking state within a preset time period, and the non-blocking state is that a node load of the power grid node is smaller than a blocking threshold value.

Because the second node electricity price is the node electricity price in the non-blocking state within the preset time period, if the calculated first node electricity price is reached, each power grid node in the target area is in the non-blocking state, and at the moment, the first node electricity price can be directly determined as the second node electricity price. Secondly, if the calculated first node electricity price is in a blocking state in the target area, namely node loads of the grid nodes are all larger than or equal to a blocking threshold value, the node loads of the grid nodes in the blocking state need to be adjusted, the first node electricity price is updated and calculated once each time the adjustment is carried out until the adjusted node loads of the grid nodes are smaller than the blocking threshold value, and the first node electricity price updated and calculated last time is determined as a second node electricity price.

Step 210, acquiring a power grid node energy storage configuration set based on the target independent energy storage value, the first node electricity price of each power grid node and the second node electricity price of each power grid node, wherein the power grid node energy storage configuration set comprises the maximum electric quantity energy storage value of each power grid node.

The server calculates based on the target independent energy storage value, the first node electricity price of each power grid node and the second node electricity price of each power grid node to obtain the maximum energy storage value of each power grid node, and then obtains a power grid node energy storage configuration set comprising the maximum energy storage value of each power grid node.

It should be understood that, in practical application, the server may also perform investigation on the load level of each power grid node, specifically, the energy storage construction condition of each power grid node needs to be investigated, and the server may determine the maximum load bearing capacity of each power grid node according to the investigation result. Therefore, if the calculated maximum value of the electric quantity energy storage of the power grid node is greater than the maximum load bearing load of the power grid node, the maximum value of the electric quantity energy storage of the power grid node is updated to be the maximum load bearing load of the power grid node.

Further, the server can calculate the maximum power energy storage value of each grid node based on the maximum electric energy storage value of each grid node. The server specifically calculates a product of the maximum electric energy storage value of each power grid node and an independent energy storage preset charging and discharging multiplying factor, so as to obtain the maximum power energy storage value of each power grid node, which is specifically as in a formula (2):

Ep _e，i ＝Eq _e，i *C； (2)

wherein, ep _e，i Representing the maximum value of the power storage of the grid node, eq _e，i The maximum value of the electric quantity energy storage of the power grid node is represented, the C represents the independent energy storage preset charging and discharging multiplying power, and the independent energy storage preset charging and discharging multiplying power is set to be 0.5 in the embodiment.

Based on this, the grid node energy storage configuration set obtained by the server may include an electric quantity energy storage maximum value of each grid node, and a power energy storage maximum value of each grid node. The method is specifically shown in formula (3):

C _e ＝{(Ep _e1 ，Eq _e1 )，(Ep _e2 ，Eq _e2 )，(Ep _e3 ，Eq _e3 )，...，(Ep _en ，Eq _en )}； (3)

wherein, C _e Representing a grid node energy storage configuration set, ep _e1 Representing the maximum value of the energy stored in the first grid node, eq _e1 Representing the maximum energy storage capacity of the first grid node, and so on, ep _en Representing power storage of the nth grid nodeMaximum value, eq _en And the maximum value of the electric quantity energy storage of the nth power grid node is represented, and n represents the number of the power grid nodes in the target area.

In the above power grid node energy storage configuration method, because the node power price in the non-blocking state is relatively stable and indicates that the power grid node can normally and stably supply power, the power price of each power grid node can be balanced by considering the power price when energy storage configuration is performed, and the load level of the target area can be considered by considering the target independent energy storage value determined by the maximum load bearing capacity. Therefore, the reliability of the obtained power grid node energy storage configuration set is improved.

In the process of obtaining the energy storage configuration set of the power grid nodes, active power in a preset time period is also considered to obtain specific load capacity of each power grid node, so that specific energy storage distribution is performed based on the specific load capacity of each power grid node. Based on this, in one embodiment, as shown in fig. 3, the grid node energy storage configuration method further includes:

step 302, obtaining active power of each power grid node in a preset time period.

The server obtains the active power of each power grid node in a preset time period. Specifically, the active power is an average value of integral of instantaneous power emitted or consumed by the load within a preset time period, and therefore, the server needs to obtain the instantaneous power emitted or consumed by each grid node within the preset time period, and then calculates an average value of integral of instantaneous power of each grid node within the preset time period to obtain the active power of each grid node within the preset time period.

And 304, calculating to obtain the load offset weight of each power grid node based on the active power of each power grid node in a preset time period.

The server calculates the active power of each power grid node in a preset time period to obtain a load offset weight of each power grid node, wherein the load offset weight is used for representing the occupied load weight of the power grid node in a target area in the preset time period, namely the load offset weight can represent the specific load capacity of the power grid node. Specifically, the server performs the aforementioned calculation by equation (4):

wherein, γ _load，i Representing load offset weights, p, of grid nodes _i The active power of the power grid nodes in a preset time period is represented, and n represents the number of the power grid nodes in the target area.

Step 210, obtaining a power grid node energy storage configuration set based on the target independent energy storage value, the first node electricity price of each power grid node, the second node electricity price of each power grid node, and the active power of each power grid node in the preset time period, including:

step 220, determining a cost offset weight of each power grid node based on the first node electricity price of each power grid node, the second node electricity price of each power grid node and the active power of each power grid node in a preset time period.

And the server calculates the first node electricity price of each power grid node, the second node electricity price of each power grid node and the active power of each power grid node in the preset time period to obtain the cost offset weight of each power grid node, wherein the cost offset weight is used for representing the node electricity price of the time period when the load is in peak load and the influence of the node electricity price in a non-blocking state on the load of each power grid node. Specifically, the server performs the aforementioned calculation by equation (5):

wherein, γ _nodal，i Indicating load offset weights, LMP, of grid nodes _i Second node electricity price, LMP, representing a grid node ₀ Representing the first node electricity price, p, of a grid node _i And the active power of the power grid nodes in a preset time period is represented, and n represents the number of the power grid nodes in the target area.

And step 230, acquiring a power grid node energy storage configuration set based on the target independent energy storage value, the cost offset weight of each power grid node and the load offset weight of each power grid node.

The server calculates based on the target independent energy storage value, the cost offset weight of each power grid node and the load offset weight of each power grid node to obtain the maximum energy storage value of each power grid node, and then obtains a power grid node energy storage configuration set comprising the maximum energy storage value of each power grid node. Similar to step 210, the server may further calculate a maximum power storage value of each grid node based on the maximum electric energy storage value of each grid node. The server specifically calculates a product of the maximum electric energy storage value of each power grid node and the preset independent energy storage charge-discharge multiplying factor, so as to obtain the maximum power energy storage value of each power grid node, which is specifically the formula (2), and is not described herein again. Based on this, the grid node energy storage configuration set obtained by the server may include an electric quantity energy storage maximum value of each grid node, and a power energy storage maximum value of each grid node.

In this embodiment, in the process of obtaining the energy storage configuration set of the power grid nodes, active power within a preset time period needs to be considered to obtain the specific load capacity of each power grid node. Secondly, the cost offset weight is obtained through calculation, and the load influence of the node electricity price of the time period when the load is in the peak load state and the node electricity price in the non-blocking state on each power grid node is also considered. Therefore, based on the specific load capacity of each power grid node and the load influence of the node electricity prices in different load bearing periods on each power grid node, the obtained power grid node energy storage configuration set can be relevant to practical application, and the reliability of energy storage distribution is further improved.

In one embodiment, as shown in fig. 4, the grid node energy storage configuration method further includes:

step 402, acquiring a maximum node load rate of each power grid node in a preset time period.

The server may obtain a maximum node load rate of each power grid node in a preset time period, where the maximum node load rate is used to represent a maximum load borne by the power grid node in the preset time period.

Step 230, obtaining a power grid node energy storage configuration set based on the target independent energy storage value, the cost offset weight of each power grid node, and the load offset weight of each power grid node, including:

and 240, acquiring a power grid node energy storage configuration set based on the target independent energy storage value, the cost offset weight of each power grid node, the load offset weight of each power grid node and the maximum node load rate of each power grid node in a preset time period.

The server obtains the maximum electric quantity energy storage value of each power grid node based on the target independent energy storage value, the cost offset weight of each power grid node, the load offset weight of each power grid node and the maximum node load rate of each power grid node in a preset time period, and then obtains a power grid node energy storage configuration set comprising the maximum electric quantity energy storage value of each power grid node.

Similar to step 210, the server may further calculate a maximum power storage value of each grid node based on the maximum power storage value of each grid node. The server specifically calculates a product of the maximum electric energy storage value of each power grid node and the preset independent energy storage charge-discharge multiplying factor, so as to obtain the maximum power energy storage value of each power grid node, specifically according to the formula (2), which is not described herein again. Based on this, the grid node energy storage configuration set obtained by the server may include an electric quantity energy storage maximum value of each grid node, and a power energy storage maximum value of each grid node.

In this embodiment, in the process of obtaining the energy storage configuration set of the power grid nodes, the maximum node load rate of each power grid node in the preset time period is further considered, and whether the maximum load of the power grid node is exceeded in the preset time period can be known through the maximum node load rate, so that the real load state of each power grid node can be obtained, and the reliability of energy storage distribution is further improved.

The server can know whether the power grid node exceeds the maximum load within a preset time period or not through the maximum node load rate of each power grid node within the preset time period, so that different energy storage configuration modes are required for different real load states of the power grid nodes. In one embodiment, as shown in fig. 5, step 240, obtaining a grid node energy storage configuration set based on the target independent energy storage value, the cost offset weight of each grid node, the load offset weight of each grid node, and the maximum node load rate of each grid node in a preset time period includes:

after acquiring the maximum node load rate of each power grid node in a preset time period, the server first determines whether the maximum node load rate of the power grid node in the preset time period is smaller than a preset light load threshold, if so, executes step 250, and if not, executes step 260. In this embodiment, the predetermined light load threshold is specifically 30%.

In step 250, if the maximum node load rate of the power grid node in the preset time period is smaller than a preset light load threshold, it is determined that the power grid node is a non-energy storage power grid node, and the maximum energy storage value of the non-energy storage power grid node is an electric quantity fixed value.

If the maximum node load rate of the power grid node in the preset time period is smaller than the preset light load threshold, it is indicated that the maximum load of the power grid node is not exceeded in the preset time period, and the load rate is low, so that the real load state of the power grid node can be known to be a low load, therefore, the situation that the power grid node is overloaded in the subsequent time period is determined to be low, the server determines that the power grid node is a non-energy storage power grid node, and the maximum energy storage value of the power grid node is an electric quantity fixed value. In this embodiment, the electric quantity fixed value is 0, that is, the server does not perform electric quantity energy storage distribution on the non-energy storage power grid node.

And step 260, if the maximum node load rate of the power grid node in the preset time period is greater than or equal to the preset light load threshold value, determining that the power grid node is an energy storage power grid node.

If the maximum node load rate of the power grid node in the preset time period is greater than or equal to the preset light load threshold, it is indicated that the load rate of the power grid node in the preset time period is higher, so that the real load state of the power grid node can be known to be higher load, and the server determines that the power grid node is an energy storage power grid node, that is, the server needs to further perform energy storage distribution on the electric quantity by the energy storage power grid node.

And 270, calculating to obtain the energy storage configuration weight of each energy storage power grid node based on the cost offset weight of each energy storage power grid node and the load offset weight of each energy storage power grid node.

And the server calculates the cost offset weight of each energy storage power grid node and the load offset weight of each energy storage power grid node to obtain the energy storage configuration weight of each energy storage power grid node. Specifically, the formula (6):

wherein, γ _i Representing energy storage configuration weight, gamma, of an energy storage grid node _load，i Representing cost offset weights, γ, of energy storage grid nodes _nodal，i Representing a load offset weight, ρ, of an energy storage grid node _load Representing a first predetermined weight, p _nodal A second preset weight representing a grid node.

Specifically, the first preset weight is used for adjusting the cost offset weight of each energy storage grid node, and the second preset weight is used for adjusting the load offset weight of each energy storage grid node. An example of the values of the first preset weight and the second preset weight is shown in table 1.

TABLE 1

Situation(s)	ρ _load	ρ _nodal
			Other cases	1	1
Heavy overload of local power grid node is serious	2-3.5	1
			Local power grid node line blockage is severe	1	2-3.5

As shown in table 1, under the condition that the local grid node is heavily overloaded, the value range of the first preset weight is 2 to 3.5, and the value of the second preset weight is 1. In this embodiment, the heavy overload of the local power grid node is serious, specifically, the maximum node load rate of the power grid node existing in the target area over 50% in the preset time period is greater than or equal to 80%.

Under the condition that local power grid node lines are seriously blocked, the value of the first preset weight is 1, and the value range of the second preset weight is 2-3.5. In this embodiment, the serious local grid node line blockage is specifically that the marginal electricity price of more than 50% of the grid nodes in the target area within the preset time period exceeds the weighted average value of the marginal electricity prices of each grid node in the target area within the preset time period.

Under other conditions, that is, under the conditions that the local grid node is not heavily overloaded, the local grid node is not severely blocked, the local grid node is not heavily overloaded, and the local grid node is not severely blocked, the value of the first preset weight is 1, and the value of the second preset weight is 1.

It should be understood that the adjustment and determination of the values of the first preset weight and the second preset weight need to be flexibly determined based on the actual situation of the target area, and the example in table 1 should not be construed as a limitation of the present solution.

For further understanding of the foregoing steps 250 and 270, please refer to equation (7):

wherein, γ _i Representing the energy storage configuration weight, gamma, of the grid node _load，i Representing cost offset weights, γ, of energy storage grid nodes _nodal，i Representing a load offset weight, p, of an energy storage grid node _load Representing a first predetermined weight, p _nodal Second predetermined weight, η, representing a grid node _i Representing the maximum node load rate, η, of the grid node within a preset time period ₀ Indicating a preset light load threshold.

And step 280, calculating to obtain the maximum electric quantity energy storage value of each energy storage power grid node based on the target independent energy storage value and the energy storage configuration weight of each energy storage power grid node.

The server can determine the cost offset weight of each energy storage grid node through step 270, and further, the server calculates the target independent energy storage value and the energy storage configuration weight of each energy storage grid node to obtain the maximum energy storage value of the electric quantity of each energy storage grid node. Specifically, the formula (8):

wherein, eq _e，i Represents the maximum value of the stored energy of the electric quantity of the nodes of the energy storage power grid, gamma _i Representing energy storage configuration weight, eq, of an energy storage grid node _sum Representing the target independent storage value.

And 290, generating a power grid node energy storage configuration set according to the electric quantity energy storage maximum value of each power grid node, wherein the power grid node energy storage configuration set specifically comprises the electric quantity energy storage maximum value of each non-energy storage power grid node and the electric quantity energy storage maximum value of each energy storage power grid node.

The server may obtain the maximum electric energy storage value of each non-energy storage grid node through the foregoing step 250, and may obtain the maximum electric energy storage value of each energy storage grid node through the foregoing steps 260 to 280, where each non-energy storage grid node and each energy storage grid node constitute a plurality of grid nodes in the target area. That is, the server may obtain the maximum electric energy storage value of each grid node through the foregoing steps 250 to 280, thereby generating a grid node energy storage configuration set, where the grid node energy storage configuration set specifically includes the maximum electric energy storage value of each non-energy storage grid node and the maximum electric energy storage value of each energy storage grid node.

In this embodiment, the fact that the maximum node load rate of the power grid node is smaller than the preset light load threshold indicates that the power grid node does not exceed the maximum load within the preset time period, and the load rate is low, so that it can be known that the real load state of the power grid node is a low load, and therefore, electric quantity energy storage distribution is not performed on non-energy storage power grid nodes, and waste of energy storage distribution is avoided.

In one embodiment, as shown in fig. 6, the preset time period includes a plurality of preset time periods. The power grid node energy storage configuration method further comprises the following steps:

step 602, a first load curve of the target area is obtained, wherein the first load curve comprises loads in each preset time period.

Specifically, the preset time period includes a plurality of preset time periods. For example, if the preset time period is 1 year, the preset time period may be 1 hour, so that 8760 preset time periods (hours) are specifically included in the preset time period (1 year). Based on the load curve, the server can also obtain the load of the target area in each preset time period, and a first load curve is formed through the load in each preset time period.

And step 604, acquiring the charging power of each power grid node in each preset time period.

The server acquires the charging power of each power grid node in each preset time period, and specifically, if the power supply power of a certain preset time period is a positive number, it indicates that the power grid node is charging in the preset time period, and conversely, if the power supply power of a certain preset time period is a negative number, it indicates that the power grid node is discharging in the preset time period.

Step 606, the first load curve is adjusted based on the charging power of each grid node in each preset time period to obtain a second load curve.

And the server adjusts the first load curve based on the charging power of each power grid node in each preset time period to obtain a second load curve. Specifically, the first load curve includes the load of the target area in each preset time period, based on which, the server calculates the difference between the load of the target area in one preset time period and the charging power of each grid node in one preset time period, so as to obtain the adjusted load in the preset time period, and performs the above calculation on each preset time period, so as to obtain the adjusted load in each preset time period, and obtain the second load curve through the adjusted load in each preset time period.

For understanding, the way for the server to calculate the adjusted load within a preset time period is specifically as in formula (9):

where Load' (t) represents the adjusted Load in the t-th preset time period, load (t) represents the Load of the target region in the t-th preset time period, and ch _c，i (t) represents the charging power of the ith grid node in the tth preset time period, and n represents the number of grid nodes in the target area.

Step 202, determining a target independent storage value of the target area based on the maximum load of the target area, including:

and step 212, determining a target storage value based on the maximum load-bearing load of the target area and the second load curve.

The server determines a target storage value based on the maximum load-bearing load of the target area and the second load curve.

In this embodiment, the load of the target area in each preset time period is adjusted by the charging power of each grid node in each preset time period, and the influence of the charging and discharging behavior in each preset time period on the load is considered, so that the obtained second load curve better conforms to the actual load level, and the authenticity and reliability of the scheme are further improved.

In practical application, it may also be considered that the target area includes a user node that needs to perform independent energy storage, for example, a plurality of large industrial plants exist in the target area, each industrial plant has an independent energy storage requirement, at this time, the industrial plant is set as one user node, and the energy storage requirement of the user node needs to be considered when performing energy storage allocation. Based on this, the following describes how to obtain the second load curve when there is a demand for energy storage in the user node. In one embodiment, as shown in fig. 7, the grid node energy storage configuration method further includes:

step 702, obtaining a user node energy storage configuration set, where the user node energy storage configuration set includes an electric quantity energy storage planning maximum value of each user node.

The server firstly obtains an energy storage configuration plan of each user node through research, and the energy storage configuration plan comprises an electric quantity energy storage plan and a power energy storage plan. Based on the above, the server determines a user node energy storage configuration set based on the energy storage configuration plans of the user nodes, wherein the user node energy storage configuration set comprises an electric quantity energy storage plan maximum value and a power energy storage plan maximum value of each user node. Specifically, the formula (10):

C _c ＝{(Ep _c1 ，Eq _c1 )，(Ep _c2 ，Eq _c2 )，(Ep _c3 ，Eq _c3 )，...，(Ep _cn ，Eq _cn )}； (10)

wherein, C _c Representing a set of user node energy storage configurations, ep _c1 Representing the maximum value of the power storage plan, eq, of the first user node _c1 ) Represents the maximum value of the energy storage plan of the first user node, and so on, ep _cn Represents the maximum value of the power storage planning, eq, of the nth user node _cn And the maximum value of the electric quantity energy storage planning of the nth user node is represented, and n represents the number of the user nodes in the target area.

Step 704, simulating based on the user node energy storage configuration set to obtain a simulated load curve, where the simulated load curve includes simulated loads in each preset time period.

And the server simulates the load of each user node in each preset time period based on the user node energy storage configuration set to obtain the simulated load in each preset time period, and a simulated load curve is generated.

Specifically, the server specifically simulates the load of each user node in each preset time period based on a "two-charging and two-discharging" policy, which is: the customer node charging time periods are 03-05 and 30-13, respectively, and the customer node discharging time periods are grid peak load time periods, 10-00 and 18-00, respectively, and the discharge amount per day is about 16 ten thousand kilowatt-hours, and the charge amount is about 21.3 ten thousand kilowatt-hours. It should be understood that, in practical applications, the simulation may also be performed according to other charging and discharging strategies, and is not limited herein.

Step 706, a first load curve of the target area is obtained, and the first load curve includes the load in each preset time period.

The server obtains the first load curve of the target area based on a similar manner in step 602, which is not described herein again.

And 708, obtaining a third load curve based on the first load curve and the simulated load curve.

The server obtains a third load curve based on the first load curve and the simulated load curve. Specifically, since the first load curve includes the load in each preset time period, and the simulated load curve includes the simulated load in each preset time period, the server subtracts the difference between the simulated loads in each preset time period and the required energy storage load in each preset time period from the load in each preset time period, thereby obtaining the third load curve, that is, the third load curve includes the required energy storage load in each preset time period.

And step 710, acquiring the charging power of each power grid node in each preset time period.

The server obtains the charging power of each grid node in each preset time period based on a similar manner of step 604, which is not described herein again.

And 712, adjusting the third load curve based on the charging power of each grid node in each preset time period to obtain a second load curve.

The server adjusts the third load curve based on the charging power of each grid node in each preset time period based on a similar manner of step 606 to obtain a second load curve, which is not described herein again.

step 222, determining a target storage value based on the maximum load-bearing load of the target area and the second load curve.

In this embodiment, the energy storage requirements of the user nodes are considered during energy storage allocation to obtain the energy storage load required in each preset time period, so that it is ensured that all nodes with energy storage requirements in the target area can perform energy storage allocation, and the reliability of energy storage allocation is ensured. The load of the target area in each preset time period is adjusted through the charging power of each power grid node in each preset time period, and the influence of the charging and discharging behaviors in each preset time period on the load is considered, so that the obtained second load curve is more consistent with the actual load level. Therefore, the authenticity and reliability of the scheme can be further improved through the processing.

In one embodiment, as shown in fig. 8, determining the target storage value based on the maximum load-bearing load of the target area and the second load curve includes:

and step 802, determining the maximum real load of the target area in a preset time period based on the second load curve.

Because the second load curve includes the adjusted loads in each preset time period, based on this, the server sorts the adjusted loads in each preset time period in turn from large to small, and determines the highest sorted load in the adjusted loads in each preset time period as the maximum real load of the target area.

And step 804, calculating a difference value between the maximum load bearing capacity of the target area and the maximum real load of the target area to obtain a target peak clipping value of the target area.

And the server calculates the difference between the maximum load bearing load of the target area and the maximum real load of the target area, wherein the difference is the target peak clipping value of the target area. For example, if the maximum load of the target area is 2600 Megawatts (MW) and the maximum real load of the target area is 2891MW, which are determined according to the requirements of the scheduling on safety and stability margin, the difference between the maximum load and the maximum real load is 261MW (2891 MW-2600 MW), which is the target peak value of the target area.

At step 806, an initial storage value for the target region is determined from the target clipping value and an initial time period is recorded.

The server determines the initial storage value of the target area through the target peak clipping value and records the initial time period. Specifically, the aforementioned initial period is specifically 1 hour. Next, the server determines the initial stored energy value of the target area by equation (11):

Eq _sum，0 ＝0.8p _curt ； (11)

wherein，Eq _sum，0 Representing the initial stored value, p, of the target area _curt Representing the target clipping value.

And 808, determining an energy storage action based on the area simulation load obtained by the initial energy storage value simulation, and generating the area simulation load obtained after the energy storage action is performed.

Further, the server needs to simulate the initial energy storage value obtained in step 806 to obtain a regional simulated load, and determine whether the regional simulated load is greater than a maximum load limit, if yes, the server needs to determine whether a discharge space exists, and if not, the server determines that the energy storage function is not to store energy. And otherwise, if so, the server determines the energy storage activity as energy storage discharge.

And secondly, if the area simulation load is less than or equal to the load maximum limit value, the server also needs to judge whether a charging space exists, and if not, the server determines that the energy storage is not used for storing energy. And otherwise, if so, the server determines the energy storage function as energy storage charging.

Further, the server needs to determine whether the area simulation load obtained after the energy storage operation is greater than the maximum load limit, if yes, the server performs step 810, otherwise, the server needs to determine whether the initial time period or the updated initial time period is greater than the minimum time period, if yes, the server performs step 814, and if not, the server performs step 812.

Step 810, if the area simulation load obtained after the energy storage action is greater than the load maximum limit value, updating the initial storage value based on the target clipping peak value, and obtaining the area simulation load based on the updated initial storage value.

And under the condition that the area simulation load obtained after the energy storage action is greater than the load maximum limit value, updating the initial storage value by the server based on the target peak clipping value, simulating to obtain the area simulation load based on the updated initial storage value, executing the area simulation load obtained by simulating based on the initial storage value to determine the energy storage action and generate the area simulation load obtained after the energy storage action by the server again in the step 808, and specifically, the description is omitted here.

Specifically, the server updates the initial stored value by equation (12):

Eq _sum，0 ′＝Eq _sum，0 +θ·p _curt ； (12)

wherein, eq _sum，0 Representing the initial stored energy value, eq, of the target area _sum，0 ' represents the updated initial stored energy value, p _curt Represents the target clipping value, θ represents the preset coefficient, and the specific value range of θ in this embodiment is 2% to 5%.

In step 812, if the area simulated load obtained after the energy storage operation is less than or equal to the maximum load limit and the initial time period is less than or equal to the minimum time period, the initial time period is updated, and the area simulated load is obtained based on the initial energy storage value simulation.

And under the condition that the area simulation load obtained after the energy storage action is less than or equal to the maximum load limit value and the initial time period is less than or equal to the minimum time period, the server updates the initial time period. Specifically, the aforementioned minimum period of time is 8760 hours. Secondly, the server adds a preset duration on the basis of the initial time period, and the preset duration is equal to the time length of the initial time period, for example, the initial time period is 1 hour, and then the initial time period with the update thickness is 2 hours. Based on this, the server executes the region simulation load obtained in step 808 again, determines the energy storage action based on the region simulation load obtained by the initial energy storage value simulation, and generates the region simulation load obtained after the energy storage action, which is not described herein again in detail.

In step 814, if the area simulated load obtained after the energy storage action is performed is less than or equal to the maximum load limit and the updated initial value or initial time period is greater than the minimum time period, the initial energy storage value obtained by the last update is determined as the target energy storage value.

And under the condition that the area simulation load obtained after the energy storage action is less than or equal to the maximum load limit and the initial time period is greater than the minimum time period, the simulation in the minimum time period is completed, the area simulation load in each preset time period is less than or equal to the maximum load limit, and the initial energy storage value obtained by the last updating is determined as the target energy storage value.

In this embodiment, the determined target clipping value of the target area may reflect a load to be adjusted in the target area, a simulation cycle is performed based on the load, and the initial storage value is adjusted based on the target clipping value, so as to ensure that the initial storage value obtained by the last update is output after the load adjustment of the target clipping value is completed, and thus the determined target storage value can meet the discharge energy storage requirement of each power grid node when the load is high, thereby ensuring the reliability of the energy storage configuration.

In one embodiment, as shown in fig. 9, step 208, determining the second node electricity prices for each grid node from the first node electricity prices for each grid node includes:

step 218, if the grid node is in the peak-load time period and in the non-blocking state, determining the grid node as a first grid node, and determining a first node electricity price of the first grid node as a second node electricity price of the first grid node.

In the time period when the power grid node is in the peak load state and in the non-blocking state, the server determines the power grid node as a first power grid node, and directly determines the first node electricity price of the first power grid node as a second node electricity price of the first power grid node.

In step 228, if the grid node is in the peak load time period and in the blocking state, the grid node is determined as a second grid node, and the reactive power of each second grid node in the preset time period is obtained.

In the time period when the power grid node is in the peak load state and in the blocking state, the server needs to adjust the power grid node in the blocking state, and calculates the electricity price of the second node when the power grid node is adjusted to be in the non-blocking state. Based on the method, the server determines the grid nodes which are in the peak load time period and in the blocking state as second grid nodes, and obtains the reactive power of each second grid node in a preset time period.

And 238, adjusting the node load of each second power grid node based on the reactive power of each second power grid node in the preset time period and the active power of each second power grid node in the preset time period, and calculating the adjusted node electricity price of each second power grid node after the node load is adjusted.

Since the server can obtain the active power of each grid node in the preset time period in step 302, the active power of each second grid node in the preset time period can be obtained by screening from the active power of each grid node in the preset time period. Based on the above, the server adjusts the node load of each second grid node based on the reactive power of each second grid node in the preset time period and the active power of each second grid node in the preset time period.

Specifically, the active power is adjusted first based on the reactive power of each second grid node in a preset time period and the active power of each second grid node in the preset time period, and then the adjusted active power determines the adjusted node load of each second grid node. Specifically, the active power is adjusted as in formula (13):

wherein, P _i ' denotes the active power of the adjusted second grid node in a predetermined time period, p _i Representing the active power of the second grid node during a predetermined time period, q _i The reactive power of the second grid node in a preset time period is represented, σ represents a compensation coefficient, and the specific value of the compensation coefficient in this embodiment is 10%.

Further, the server determines the adjusted node electricity price of each second grid node through the adjusted node load of each second grid node, the power supply quotation of each power supply in each region and the specific grid structure. The power supply quotation for the particular grid configuration and local power supplies is described in step 206 and will not be described further herein.

Step 248, when the adjusted node load of each second grid node is smaller than the blocking threshold, determining the adjusted node electricity price obtained after the last adjustment as the second node electricity price of the second grid node.

And when the adjusted node load of each second power grid node is smaller than the blocking threshold, the server determines the electricity price of the adjusted node obtained after the last adjustment as the electricity price of the second node of the second power grid node. If the adjusted node load of the second grid node is still greater than or equal to the blocking threshold, the server continues to perform step 238 to adjust the node load of the second grid node until the adjusted node load is less than the blocking threshold.

In this embodiment, under the condition that the power grid node is in the peak-load time period and in the non-blocking state, the first node electricity price is directly determined as the second node electricity price, and the efficiency of determining the node electricity prices is improved on the basis of ensuring the node electricity prices. Secondly, in the time period when the power grid node is in the peak load state and in the non-blocking state, the load of the power grid node is adjusted to meet the power price calculation condition of the power price of the second node, and the reliability of the scheme is further improved.

In one embodiment, taking the user node needing to independently store energy in the target area as an example for detailed description, as shown in fig. 10,

step 1002, acquiring a user node energy storage configuration set.

And the server acquires a user node energy storage configuration set comprising the maximum value of the electric quantity energy storage planning of each user node.

And 1004, simulating based on the energy storage configuration set of the user node to obtain a simulated load curve.

Step 1006, a first load curve of the target area is obtained.

The server obtains the load of the target area in each preset time period, and a first load curve is formed through the load in each preset time period.

And 1008, obtaining a third load curve based on the first load curve and the simulated load curve.

And the server subtracts the difference between the simulated loads in each preset time period and the load required in each preset time period from the load in each preset time period, so as to obtain a third load curve, wherein the third load curve comprises the energy storage load required in each preset time period.

Step 1010, obtaining the charging power of each grid node in each preset time period.

The server obtains charging power of each power grid node in each preset time period, specifically, if the power supply power of a certain preset time period is a positive number, it indicates that the power grid node is being charged in the preset time period, and otherwise, if the power supply power of a certain preset time period is a negative number, it indicates that the power grid node is being discharged in the preset time period.

Step 1012, adjusting the third load curve based on the charging power of each grid node in each preset time period to obtain a second load curve.

The server calculates the difference between the load of the target area in a preset time period and the charging power of each power grid node in the preset time period, so that the adjusted load in the preset time period can be obtained, the above calculation is carried out on each preset time period, so that the adjusted load in each preset time period can be obtained, and a second load curve can be obtained through the adjusted load in each preset time period.

And 1014, determining the maximum real load of the target area in the preset time period based on the second load curve.

Step 1016, calculating a difference between the maximum load of the target area and the maximum real load of the target area to obtain a target clipping value of the target area.

And the server calculates the difference between the maximum load bearing load of the target area and the maximum real load of the target area, wherein the difference is the target peak clipping value of the target area.

An initial stored value for the target region is determined by the target clipping value and the initial time period is recorded, step 1018.

The server determines the initial storage value of the target area through the target peak clipping value and records the initial time period. Specifically, the aforementioned initial period of time is specifically 1 hour. The server determines the initial stored energy value of the target region, in particular by the aforementioned equation (11).

And 1020, determining an energy storage action based on the area simulation load obtained by the initial energy storage value simulation, and generating the area simulation load obtained after the energy storage action is performed.

The server also needs to simulate the initial energy storage value to obtain a regional simulation load, and judges whether the regional simulation load is larger than the maximum load limit value, if so, the server also needs to judge whether a discharge space exists, and if not, the server determines that the energy storage is not used for energy storage. And otherwise, if so, the server determines the energy storage activity as energy storage discharge.

Further, the server also needs to determine whether the area simulation load obtained after the energy storage operation is greater than the maximum load limit, if yes, the server performs step 1022, otherwise, the server also needs to determine whether the initial time period or the updated initial time period is greater than the minimum time period, if yes, the server performs step 1026, and if not, the server performs step 1024.

And step 1022, if the area simulation load obtained after the energy storage action is performed is greater than the maximum load value, updating the initial storage value based on the target clipping value, and obtaining the area simulation load based on the updated initial storage value.

And under the condition that the area simulation load obtained after the energy storage action is greater than the load maximum limit value, updating the initial storage value by the server based on the target peak clipping value, obtaining the area simulation load by simulating based on the updated initial storage value, then determining the energy storage action by the server again based on the area simulation load obtained by simulating based on the initial storage value, and generating the area simulation load obtained after the energy storage action, wherein details are not repeated herein.

And step 1024, if the area simulated load obtained after the energy storage action is less than or equal to the maximum load limit and the initial time period is less than or equal to the minimum time period, updating the initial time period and obtaining the area simulated load based on the initial energy storage value simulation again.

And under the condition that the area simulation load obtained after the energy storage action is less than or equal to the maximum load limit value and the initial time period is less than or equal to the minimum time period, the server updates the initial time period. Based on this, the server executes the step of determining the energy storage action based on the region simulation load obtained by the initial energy storage value simulation again, and generates the region simulation load obtained after the energy storage action, which is not described herein again in detail.

In step 1026, if the area simulated load obtained after the energy storage operation is performed is less than or equal to the maximum load limit value, and the updated initial value or initial time period is greater than the minimum time period, the initial energy storage value obtained by the last update is determined as the target energy storage value.

And under the condition that the area simulation load obtained after the energy storage action is less than or equal to the maximum load limit value and the initial time period is greater than the minimum time period, the simulation in the minimum time period is completed, the area simulation load in each preset time period is less than or equal to the maximum load limit value, and the initial energy storage value obtained by the last updating is determined as the target energy storage value.

Step 1028, determining a target independent storage value of the target area based on the maximum load of the target area, where the target area includes a plurality of grid nodes.

Before determining the target independent energy storage value, the server needs to investigate the overall load level of the target area, specifically needs to investigate the energy storage construction conditions of the target area and the specific power grid structure of the target area, and can determine the maximum load bearing capacity of the target area according to the investigation result.

Step 1030, acquiring the number of power supplies in the target area within a preset time period, and power cost information of the power supplies in each area.

And 1032, calculating to obtain the first node electricity price of each power grid node based on the number of the power supplies in the target area and the power supply cost information of each power supply in the area.

Step 1034, determining a second node electricity price of each power grid node through the first node electricity price of each power grid node.

The server further calculates based on the first node electricity prices for each grid node to determine second node electricity prices for each grid node. Specifically, the second node electricity price is the node electricity price in a non-blocking state within a preset time period, and the non-blocking state is that the node load of the power grid node is smaller than a blocking threshold value

Step 1036, obtaining a grid node energy storage configuration set based on the target independent energy storage value, the first node electricity price of each grid node, and the second node electricity price of each grid node.

The server calculates based on the target independent energy storage value, the first node electricity price of each power grid node and the second node electricity price of each power grid node to obtain the maximum energy storage value of each power grid node, and then obtains a power grid node energy storage configuration set comprising the maximum energy storage value of each power grid node. Further, the server can calculate the maximum power energy storage value of each grid node based on the maximum electric energy storage value of each grid node.

It should be understood that the detailed description of each step in fig. 10 is described in detail in the foregoing embodiment, and thus, the detailed description is omitted here.

It should be understood that, although the steps in the flowcharts related to the embodiments as described above are sequentially displayed as indicated by arrows, the steps are not necessarily performed sequentially as indicated by the arrows. The steps are not limited to being performed in the exact order illustrated and, unless explicitly stated herein, may be performed in other orders. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be rotated or alternated with other steps or at least a part of the steps or stages in other steps.

Based on the same inventive concept, the embodiment of the application also provides a power grid node energy storage configuration device for realizing the power grid node energy storage configuration method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the method, so that specific limitations in one or more embodiments of the power grid node energy storage configuration device provided below can be referred to the limitations on the power grid node energy storage configuration method in the foregoing, and details are not described herein again.

In one embodiment, as shown in fig. 11, there is provided a grid node energy storage configuration apparatus, including: a determination module 1102, an acquisition module 1104, and a calculation module 1106, wherein:

a determining module 1102, configured to determine a target independent storage value of a target area based on a maximum load of the target area, where the target area includes multiple grid nodes;

an obtaining module 1104, configured to obtain the number of power supplies in a target area within a preset time period, and power cost information of each power supply in the target area;

a calculating module 1106, configured to calculate, based on the number of power supplies in a target area and power cost information of each power supply in the area, a first node electricity price of each grid node;

the determining module 1102 is further configured to determine a second node electricity price of each power grid node according to the first node electricity price of each power grid node, where the second node electricity price is a node electricity price in a non-blocking state within a preset time period, and the non-blocking state is a state where a node load of the power grid node is smaller than a blocking threshold;

the obtaining module 1104 is further configured to obtain a power grid node energy storage configuration set based on the target independent energy storage value, the first node electricity price of each power grid node, and the second node electricity price of each power grid node, where the power grid node energy storage configuration set includes a maximum electric quantity energy storage value of each power grid node.

In an embodiment, the obtaining module 1104 is further configured to obtain active power of each grid node within a preset time period;

the calculating module 1106 is further configured to calculate a load offset weight of each power grid node based on the active power of each power grid node in a preset time period;

the obtaining module 1104 is specifically configured to:

determining a cost offset weight of each power grid node based on a first node electricity price of each power grid node, a second node electricity price of each power grid node and active power of each power grid node in a preset time period;

and acquiring a power grid node energy storage configuration set based on the target independent energy storage value, the cost offset weight of each power grid node and the load offset weight of each power grid node.

In an embodiment, the obtaining module 1104 is further configured to obtain a maximum node load rate of each grid node within a preset time period;

the obtaining module 1104 is specifically configured to obtain an energy storage configuration set of the power grid nodes based on the target independent energy storage value, the cost offset weight of each power grid node, the load offset weight of each power grid node, and the maximum node load rate of each power grid node in a preset time period.

In an embodiment, the obtaining module 1104 is specifically configured to:

if the maximum node load rate of the power grid node in a preset time period is smaller than a preset light load threshold value, determining that the power grid node is a non-energy-storage power grid node, and the maximum energy storage value of the non-energy-storage power grid node is an electric quantity fixed value;

if the maximum node load rate of the power grid node in a preset time period is greater than or equal to a preset light load threshold value, determining that the power grid node is an energy storage power grid node;

calculating to obtain an energy storage configuration weight of each energy storage power grid node based on the cost offset weight of each energy storage power grid node and the load offset weight of each energy storage power grid node;

calculating to obtain the electric quantity energy storage maximum value of each energy storage power grid node based on the target independent energy storage value and the energy storage configuration weight of each energy storage power grid node;

and generating a power grid node energy storage configuration set through the electric quantity energy storage maximum value of each power grid node, wherein the power grid node energy storage configuration set specifically comprises the electric quantity energy storage maximum value of each non-energy storage power grid node and the electric quantity energy storage maximum value of each energy storage power grid node.

In one embodiment, the preset time period comprises a plurality of preset time periods;

the obtaining module 1104 is further configured to obtain a first load curve of the target area, where the first load curve includes a load in each preset time period; acquiring the charging power of each power grid node in each preset time period; adjusting the first load curve based on the charging power of each power grid node in each preset time period to obtain a second load curve;

the determining module 1102 is specifically configured to determine a target storage value based on the maximum load-bearing load of the target area and the second load curve.

In an embodiment, the obtaining module 1104 is further configured to obtain a user node energy storage configuration set, where the user node energy storage configuration set includes an electric quantity energy storage planning maximum value of each user node; simulating based on the user node energy storage configuration set to obtain a simulated load curve, wherein the simulated load curve comprises simulated loads in each preset time period; acquiring a first load curve of the target area, wherein the first load curve comprises the load in each preset time period; obtaining a third load curve based on the first load curve and the simulated load curve; acquiring the charging power of each power grid node in each preset time period; adjusting the third load curve based on the charging power of each power grid node in each preset time period to obtain a second load curve;

the determining module 1102 is specifically configured to determine the target storage value based on the maximum load-bearing load of the target area and the second load curve.

In an embodiment, the determining module 1102 is specifically configured to:

determining the maximum real load of the target area in a preset time period based on the second load curve;

calculating the difference between the maximum load bearing load of the target area and the maximum real load of the target area to obtain a target peak clipping value of the target area;

determining an initial storage value of the target area through the target peak clipping value, and recording an initial time period;

determining an energy storage action based on the region simulation load obtained by the initial energy storage value simulation, and generating a region simulation load obtained after the energy storage action is performed;

if the area simulation load obtained after the energy storage action is greater than the load maximum limit value, updating the initial storage value based on the target peak clipping value, and simulating to obtain the area simulation load based on the updated initial storage value;

if the area simulation load obtained after the energy storage action is less than or equal to the maximum load limit value and the initial time period is less than or equal to the minimum time period, updating the initial time period and obtaining the area simulation load based on the initial energy storage value simulation;

and if the area simulation load obtained after the energy storage action is performed is less than or equal to the maximum load limit value and the updated initial value or initial time period is greater than the minimum time period, determining the initial energy storage value obtained by the last updating as the target energy storage value.

In one embodiment, the determining module 1102 is specifically configured to:

if the power grid node is in the peak-load time period and is in the non-blocking state, determining the power grid node as a first power grid node, and determining the first node electricity price of the first power grid node as a second node electricity price of the first power grid node;

if the power grid node is in the peak load time period and in the blocking state, determining the power grid node as a second power grid node, and acquiring the reactive power of each second power grid node in a preset time period;

adjusting the node load of each second power grid node based on the reactive power of each second power grid node in a preset time period and the active power of each second power grid node in the preset time period, and calculating the adjusted node electricity price of each second power grid node after the node load is adjusted;

and when the adjusted node load of each second power grid node is smaller than the blocking threshold, determining the electricity price of the adjusted node obtained after the last adjustment as the electricity price of the second node of the second power grid node.

All or part of each module in the power grid node energy storage configuration device can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent of a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 12. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operating system and the computer program to run on the non-volatile storage medium. The database of the computer equipment is used for storing data such as the number of power supplies in each region of a target region, power cost information of the power supplies in each region, active power of each power grid node in a preset time period, and maximum node load rate of each power grid node in the preset time period. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a grid node energy storage configuration method.

It will be appreciated by those skilled in the art that the configuration shown in fig. 12 is a block diagram of only a portion of the configuration associated with the present application, and is not intended to limit the computing device to which the present application may be applied, and that a particular computing device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is further provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method embodiments when executing the computer program.

In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.

In an embodiment, a computer program product is provided, comprising a computer program which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions of a computer program, which may be stored in a non-volatile computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include a Read-Only Memory (ROM), a magnetic tape, a floppy disk, a flash Memory, an optical Memory, a high-density embedded nonvolatile Memory, a resistive Random Access Memory (ReRAM), a Magnetic Random Access Memory (MRAM), a Ferroelectric Random Access Memory (FRAM), a Phase Change Memory (PCM), a graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), for example. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the various embodiments provided herein may be, without limitation, general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, or the like.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, and these are all within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A power grid node energy storage configuration method is characterized by comprising the following steps:

determining a target independent storage value of a target area based on the maximum load-bearing load of the target area and a second load curve, wherein the target area comprises a plurality of power grid nodes, and the target independent storage value is used for describing an independent storage value of each power grid node; wherein the second load curve is: the method comprises the steps that a first load curve is obtained after adjustment is carried out on the charging power of each power grid node in each preset time period, wherein the first load curve comprises loads in each preset time period; or, the second load curve is: a third load curve is obtained by adjusting the charging power of each power grid node in each preset time period, the third load curve is obtained based on the first load curve and a simulated load curve, the simulated load curve is obtained by simulating the maximum value of the electric quantity energy storage plan of each user node, and the preset time period belongs to a preset time period;

acquiring the number of power supplies in the target area within the preset time period and power supply cost information of each power supply in the target area;

calculating to obtain a first node electricity price of each power grid node based on the number of the power supplies in the target area and the power supply cost information of the power supplies in each area, wherein the first node electricity price is as follows: the corresponding power grid node is in the peak load time period and is in the node electricity price of the non-blocking state;

determining a second node electricity price of each power grid node through the first node electricity price of each power grid node, wherein the second node electricity price is as follows: the corresponding power grid node is in a node electricity price of a non-blocking state within the preset time period, wherein the non-blocking state is that the node load of the power grid node is smaller than a blocking threshold value;

calculating based on the first node electricity price of each power grid node, the second node electricity price of each power grid node and the active power of each power grid node in the preset time period, and determining a cost deviation weight of each power grid node, wherein the cost deviation weight is used for representing: the node electricity price of the time period when the load is in the peak load state and the node electricity price in the non-blocking state influence the load of each power grid node;

calculating based on the target independent energy storage value, the cost offset weight of each power grid node and the load offset weight of each power grid node to obtain a power grid node energy storage configuration set, wherein the power grid node energy storage configuration set comprises the maximum electric quantity energy storage value of each power grid node, and the load offset weight is used for representing the occupied load weight of the corresponding power grid node in the target area in the preset time period.

2. The method of claim 1, further comprising:

acquiring the maximum node load rate of each power grid node in the preset time period;

the obtaining the power grid node energy storage configuration set based on the target independent energy storage value, the cost offset weight of each power grid node, and the load offset weight of each power grid node includes:

and acquiring the energy storage configuration set of the power grid nodes based on the target independent energy storage value, the cost offset weight of each power grid node, the load offset weight of each power grid node and the maximum node load rate of each power grid node in the preset time period.

3. The method of claim 2, wherein obtaining the grid node energy storage configuration set based on the target independent energy storage value, the cost offset weight of each grid node, the load offset weight of each grid node, and the maximum node load rate of each grid node within the preset time period comprises:

if the maximum node load rate of the power grid node in the preset time period is smaller than a preset light load threshold value, determining that the power grid node is a non-energy-storage power grid node, and the maximum energy storage value of the non-energy-storage power grid node is an electric quantity fixed value;

if the maximum node load rate of the power grid node in the preset time period is greater than or equal to the preset light load threshold value, determining that the power grid node is an energy storage power grid node;

calculating to obtain the maximum electric quantity energy storage value of each energy storage power grid node based on the target independent energy storage value and the energy storage configuration weight of each energy storage power grid node;

4. The method of claim 1, wherein the determining the target independent storage value based on the maximum load bearing of the target region and the second load curve comprises:

determining a maximum real load of the target area within the preset time period based on the second load curve;

calculating a difference value between the maximum load bearing load of the target area and the maximum real load of the target area to obtain a target peak clipping value of the target area;

if the area simulation load obtained after the energy storage action is larger than the load maximum limit value, updating the initial storage value based on the target peak clipping value, and obtaining the area simulation load based on the updated initial storage value;

if the area simulation load obtained after the energy storage action is less than or equal to the load maximum limit value and the initial time period is less than or equal to the minimum time period, updating the initial time period and obtaining the area simulation load based on the initial energy storage value simulation;

and if the area simulation load obtained after the energy storage action is performed is less than or equal to the load maximum limit value and the updated initial value or the initial time period is greater than the minimum time period, determining the initial energy storage value obtained by the last updating as the target independent energy storage value.

5. The method of claim 1, wherein determining the second node electricity prices for each grid node from the first node electricity prices for each grid node comprises:

if the power grid node is in a peak load time period and is in a non-blocking state, determining the power grid node as a first power grid node, and determining the first node electricity price of the first power grid node as the second node electricity price of the first power grid node;

if the power grid node is in the time period of peak load and is in the blocking state, determining the power grid node as a second power grid node, and acquiring the reactive power of each second power grid node in the preset time period;

adjusting the node load of each second power grid node based on the reactive power of each second power grid node in the preset time period and the active power of each second power grid node in the preset time period, and calculating the adjusted node electricity price of each second power grid node after the node load is adjusted;

and when the adjusted node load of each second power grid node is smaller than the blocking threshold, determining the adjusted node electricity price obtained after the last adjustment as the second node electricity price of the second power grid node.

6. A grid node energy storage configuration apparatus, the apparatus comprising:

a determining module, configured to determine a target independent storage value of a target area based on a maximum load-bearing load of the target area and a second load curve, where the target area includes multiple grid nodes, and the target independent storage value is used to describe an independent storage value of each grid node; wherein the second load curve is: the method comprises the steps that a first load curve is obtained after adjustment is carried out on the charging power of each power grid node in each preset time period, wherein the first load curve comprises loads in each preset time period; or, the second load curve is: adjusting a third load curve according to the charging power of each power grid node in each preset time period, wherein the third load curve is obtained based on the first load curve and a simulated load curve, the simulated load curve is obtained by simulating the maximum value of the electric quantity energy storage plan of each user node, and the preset time period belongs to a preset time period;

the acquisition module is used for acquiring the number of the power supplies in the target area in the preset time period and the power cost information of the power supplies in each area;

a calculating module, configured to calculate, based on the number of power supplies in the target area and power cost information of the power supply in each area, a first node electricity price of each grid node, where the first node electricity price is: the corresponding power grid node is in the peak-load time period and is in the node electricity price in the non-blocking state;

the determining module is further configured to determine a second node electricity price of each power grid node through the first node electricity price of each power grid node, where the second node electricity price is: the corresponding power grid node is in a node electricity price of a non-blocking state in the preset time period, wherein the non-blocking state is that the node load of the power grid node is smaller than a blocking threshold value;

the obtaining module is further configured to calculate based on the first node electricity price of each power grid node, the second node electricity price of each power grid node, and the active power of each power grid node in the preset time period, and determine a cost offset weight of each power grid node, where the cost offset weight is used to represent: the node electricity price of the time period when the load is in the peak load state and the node electricity price in the non-blocking state influence the load of each power grid node; calculating based on the target independent energy storage value, the cost offset weight of each power grid node and the load offset weight of each power grid node to obtain a power grid node energy storage configuration set, wherein the power grid node energy storage configuration set comprises the maximum electric quantity energy storage value of each power grid node, and the load offset weight is used for representing the occupied load weight of the corresponding power grid node in the target area in the preset time period.

7. The apparatus according to claim 6, wherein the obtaining module is further configured to obtain a maximum node load rate of each grid node in the preset time period;

the obtaining module is specifically configured to obtain the power grid node energy storage configuration set based on the target independent energy storage value, the cost offset weight of each power grid node, the load offset weight of each power grid node, and the maximum node load rate of each power grid node in the preset time period.

8. The apparatus of claim 7, wherein the obtaining module is specifically configured to:

if the maximum node load rate of the power grid node in the preset time period is smaller than a preset light load threshold value, determining that the power grid node is a non-energy-storage power grid node, and the maximum value of the energy storage of the non-energy-storage power grid node is an electric quantity fixed value;

9. The apparatus of claim 6, wherein the determining module is specifically configured to:

calculating a difference value between the maximum load-bearing load of the target area and the maximum real load of the target area to obtain a target peak clipping value of the target area;

if the area simulation load obtained after the energy storage action is greater than the maximum load value, updating the initial storage value based on the target peak clipping value, and obtaining the area simulation load based on the updated initial storage value;

if the area simulation load obtained after the energy storage action is carried out is less than or equal to the maximum load limit value and the initial time period is less than or equal to the minimum time period, updating the initial time period and obtaining the area simulation load based on the initial energy storage value simulation;

10. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 5.