CN116957635A - Electricity price acquisition method, device, electronic equipment and storage medium - Google Patents

Abstract

The disclosure provides a method, a device, electronic equipment and a storage medium for acquiring electric power price, wherein the method comprises the following steps: acquiring electricity consumption data of a supply node to be predicted and a use node; acquiring a target transaction path for transmitting power from a supply node to a using node based on power consumption data, and a first declaration price; calculating a conversion parameter based on the target transaction path, and determining a second declaration price of the supply node based on the conversion parameter and the first declaration price; a target power transmission price is determined based on the first declared price and the second declared price. The target transmission price is generated through the first declaration price of the target transaction path and the use node which are predicted to be generated, the conversion parameter is calculated, the second declaration price is determined based on the calculated conversion parameter, and the target transmission price is generated through the first declaration price and the second declaration price, so that more accurate transmission price is formulated from three dimensions of the supply node, the use node and the transaction path of the supply node and the use node, and accurate data is provided for follow-up power price formulation, bidding and other works.

Description

Electricity price acquisition method, device, electronic equipment and storage medium

Technical field

The present disclosure relates to the technical field of electricity price prediction, and in particular, to an electricity price acquisition method, device, electronic equipment and storage medium.

Background technique

Inter-provincial power spot trading is an important component of my country's multi-level unified power market system and an important measure to implement the national energy strategy and promote the power market reform. The continuous growth and development of inter-provincial power spot trading is of great significance to achieving the goals of ensuring power supply and low-carbon transformation during the construction of new power systems. Inter-provincial electricity spot transactions are closely related to the electricity supply and demand in each region. With global climate change, the supply and demand change trend is more difficult to judge, and the development trend of inter-provincial spot prices is difficult to predict. For example, during the peak summer period in 2022, due to persistent high temperatures Affected by multiple factors such as increased electricity demand and tight power supply, inter-provincial spot prices have risen. This has led to a more complex market environment, intensified the difficulty of transactions for market entities, and raised transaction thresholds.

Contents of the invention

The present disclosure aims to solve one of the technical problems in the related art, at least to a certain extent.

To this end, one object of the present disclosure is to propose a method for obtaining electricity prices.

The second object of the present disclosure is to provide an electric power price acquisition device.

The third object of the present disclosure is to provide an electronic device.

A fourth object of the present disclosure is to provide a non-transitory computer-readable storage medium.

A fifth object of the present disclosure is to provide a computer program product.

In order to achieve the above purpose, the first embodiment of the present disclosure proposes a method for obtaining electricity prices, which includes: obtaining the electricity consumption data of the supply nodes and usage nodes to be predicted; and obtaining the electricity price of the supply nodes to all the supply nodes based on the electricity consumption data. The target transaction path of the power transmission using the node, and the first declared price of the using node; calculate the conversion parameter based on the target transaction path, and determine the supply node based on the conversion parameter and the first declared price. The second declared price; determine the target transmission price based on the first declared price and the second declared price.

According to an embodiment of the present disclosure, calculating the conversion parameters based on the target transaction path includes: obtaining a target intermediate conversion variable; and determining the conversion parameters based on the target transaction path.

According to an embodiment of the present disclosure, determining the conversion parameters based on the target transaction path includes: obtaining multiple cross-region channels of the target transaction path and the transmission grid loss rate corresponding to each segment of the cross-region channel; converting 1 Subtract the transmission network loss rate to obtain the effective power transmission rate of each section of the cross-region channel; multiply the effective power transmission rates of all cross-region channels to calculate and obtain the conversion parameter.

According to an embodiment of the present disclosure, obtaining the target intermediate conversion variable includes: for any cross-region channel, obtaining the sub-conversion parameter and the power transmission price of the cross-region channel; Multiply to obtain the sub-intermediate conversion variables; add all sub-intermediate conversion variables to obtain the target intermediate conversion variable.

According to an embodiment of the present disclosure, obtaining the sub-conversion parameters of the cross-region channel includes: calculating the sub-effective power transmission rate from the supply node to the cross-region channel; The sub-effective power transmission rates of the channel are multiplied to calculate the sub-conversion parameters of the cross-region channel.

According to an embodiment of the present disclosure, calculating the second declaration price based on the conversion parameter, the target intermediate conversion variable and the first declaration price includes: combining the first declaration price and the conversion price The parameters are multiplied, and the product is subtracted from the target intermediate conversion variable to calculate and obtain the second declared price.

According to an embodiment of the present disclosure, obtaining the first declared price of the usage node based on the power usage data includes: obtaining all historical power transmission prices of the usage node in the power usage data; based on the historical power transmission price Determine the first declared price.

In order to achieve the above purpose, the second embodiment of the present disclosure proposes an electricity price acquisition device, which includes: an acquisition module, used to acquire the power consumption data of supply nodes and usage nodes to be predicted and the power spot transaction model; a calling module, using Input the electricity consumption data into the electric power spot trading model to obtain the target transaction path and the first declaration price of the usage node; a determination module is used to determine the target transaction path and the first declaration price based on the target transaction path and the first declaration price. Price, determine the second declaration price of the supply node; and a formulation module, used to determine a target transaction strategy based on the first declaration price and the second declaration price.

To achieve the above object, a third embodiment of the present disclosure provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores information that can be used by the Instructions executed by at least one processor, the instructions being executed by the at least one processor, to implement the electricity price obtaining method as described in the embodiment of the first aspect of the present disclosure.

In order to achieve the above object, the fourth embodiment of the present disclosure provides a non-transient computer-readable storage medium storing computer instructions, wherein the computer instructions are used to implement the electric power as described in the first embodiment of the present disclosure. Price acquisition method.

In order to achieve the above object, the fifth embodiment of the present disclosure provides a computer program product, including a computer program. When executed by a processor, the computer program is used to implement the electricity price as described in the first embodiment of the present disclosure. Get method.

Thus, by predicting the target transaction path and the first declared price of the usage node, the conversion parameter is calculated, the second declaration price of the usage node is determined based on the calculated conversion parameter, and the target power transmission is generated by the first declaration price and the second declaration price. Price, in this way, a more accurate transmission price can be formulated from the three dimensions of supply node, user node and the transaction path between the two, and accurate data can be provided for subsequent power price setting, bidding and other work.

Description of the drawings

Figure 1 is a schematic diagram of an electricity price obtaining method according to an embodiment of the present disclosure;

Figure 2 is a schematic diagram of another electricity price acquisition method according to an embodiment of the present disclosure;

Figure 3 is a schematic diagram of an electricity price acquisition device according to an embodiment of the present disclosure;

Figure 4 is a schematic diagram of an electronic device according to an embodiment of the present disclosure.

Detailed ways

Embodiments of the present disclosure are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present disclosure and are not to be construed as limitations of the present disclosure.

Figure 1 is a schematic diagram of an exemplary implementation of an electricity price acquisition method proposed by the present disclosure. As shown in Figure 1, the electricity price acquisition method includes the following steps:

S101. Obtain the power consumption data of the supply node and the usage node to be predicted.

The electricity price acquisition method in the embodiment of the present application can be applied in the scenario of electricity spot trading or quotation. The execution subject of the electricity price acquisition in the embodiment of the present application can be the electricity price acquisition device in the embodiment of the present application. The electricity price acquisition device can Set on electronic device.

It should be noted that the supply node is the location of the power supply source, and the node can be the province where the power supply source is located. The use node is the location that needs to be powered, and the node can be the province that needs to be powered.

In the embodiment of the present disclosure, the power consumption data of the supply node and the usage node may include multiple types, and there is no limitation here. The specific limitation may be based on actual design needs. For example, it can include information such as historical transaction prices, forecast time, bidding space, new energy output, temperature, wind speed, electricity prices between buyers and sellers, and so on.

It should be noted that the electricity consumption data can be extracted by obtaining the data disclosed by the trading center, or it can be obtained through historical transaction records. There are no restrictions here.

S102: Obtain the target transaction path of power transmission from the supply node to the user node based on the power consumption data, and the first declared price of the user node.

In the embodiment of the present disclosure, there may be multiple methods for determining the first declared price of the usage node based on electrical data, and there is no limitation here. For example, the first declared price can be determined based on the historical house purchase price in the electricity data; the first declared price can also be obtained by inputting the electricity data into the node price generation model.

In the embodiment of the present disclosure, there may be multiple transaction paths from the supply node to the user node, and the target transaction path is the optimal path that meets the conditions among all current paths. This condition can be of many kinds and is not limited here. For example, it can be a transaction path that passes through all set locations, it can be a transaction path with the shortest distance, or it can be a transaction path with the lowest power loss.

In one possible implementation manner, the electrical data is input into the electricity spot trading model to obtain the target trading path. The electricity spot trading model is trained in advance and stored in the storage space of the electronic device to facilitate retrieval and use when needed. This electricity spot trading model is used to predict the buyer's declared price in a specific area in the future time period.

First, a trading network graph is constructed through the power spot trading model, in which each supply node and usage node are used as nodes in the graph. The edges connecting the nodes are the transaction paths. The nodes are divided based on information such as power transmission price, network loss rate, channel capacity, and voltage level. The features of the node are aggregated with the features of its neighbor nodes to obtain a new feature representation of the node. Process irregular graph structure data by constructing local first-order approximation calculations of spectral domain graph convolution, learn the embedding representation of nodes and edges, and capture the structure and relationship between nodes:

in, Is the input of the l-th layer network;/> ,n is the picture/> The number of nodes in; each node is represented by a d-dimensional eigenvector; A is the adjacency matrix of the undirected graph;/> ;/> is the n-order identity matrix;/> is the degree matrix of the undirected graph,/> ;/> is the parameter to be trained; h is the output dimension;/> is the corresponding activation function Relu.

After selecting the sending province and the receiving province, and defining the number of channels J and the output result K, the first K target transaction path combinations with the number of channels no higher than J are automatically output through the graph neural network and displayed on the map. In addition to automatically outputting the target transaction path, you can also directly use a single variable such as transmission price to sort the transaction path combinations (such as the top K transaction path combinations from the lowest to the highest transmission price and the number of channels is not higher than J), as shown The content includes the sending end, receiving end, transaction path, transmission price, total network loss, transaction path composition, channel market space information used to view the market space change trend of the channel, maintenance days, maintenance time, channel limit and other monthly maintenance Plan, transmission capacity, maximum transmission capacity, available capacity, used capacity and other channel transmission capacity information.

It should be noted that the first declaration price is the optimal quotation of the using node or the predicted quotation combined with historical transaction data.

S103. Calculate the conversion parameters based on the target transaction path, and determine the second declaration price of the supply node based on the conversion parameters and the first declaration price.

It should be noted that the historical transaction path from the supply node to the user node may include cross-regional channels, inter-provincial tie lines or regional shared power grids. During the transmission process, there may be factors such as power loss and power transmission costs. Parameters are used to describe these parameters that affect the cost of electricity. It should be noted that the larger the conversion parameter, the higher the transportation cost, and the higher the second declaration price that affects the supply node.

In the embodiment of the present disclosure, there are many methods for calculating the conversion parameters after obtaining the target transaction path, and there is no limitation here.

Optionally, the second declaration price of the supply node can be obtained by inputting the target transaction path into the conversion parameter generation model. The conversion parameter generation model is trained in advance and stored in the storage space of the electronic device to facilitate retrieval and use when needed.

Optionally, the target transaction path can also be processed through preset processing conditions to obtain the conversion parameters. The processing conditions can be multiple, and there are no limitations here. For example, the processing conditions can be to obtain the conversion parameters by determining the electrical loss on the target transaction path.

S104: Determine the target transmission price based on the first declared price and the second declared price.

It should be noted that the target transmission price is the electric energy price that best meets user needs under the current target transaction path. The user requirements may include a variety of requirements. For example, the user requirements may include profit margins, loss rates, etc., which may be specifically limited based on actual design needs.

In the embodiment of the present disclosure, based on the first declared price and the second declared price, there may be multiple methods for determining the target transmission price, which are not limited here.

Optionally, the target transmission price can be determined by setting weight parameters for the first declared price and the second declared price respectively, and allocating the proportions of the first declared price and the second declared price in the target transmission price based on the weight parameters. It should be noted that this weight parameter can be set according to actual design needs, and there is no limitation here.

Optionally, the target transmission price can also be obtained by inputting the first declared price and the second declared price into the transmission price generation model. The transmission price generation model is trained in advance and stored in the storage space of the electronic device to facilitate retrieval and use when needed.

In the embodiment of the present disclosure, the power consumption data of the supply node and the usage node to be predicted are first obtained, and then the target transaction path of power transmission from the supply node to the usage node and the first declared price of the usage node are obtained based on the power usage data, and then based on The target transaction path calculates the conversion parameters, and determines the second declaration price of the supply node based on the conversion parameters and the first declaration price. Finally, the target transmission price is determined based on the first declaration price and the second declaration price. Thus, by predicting the target transaction path and the first declared price of the usage node, the conversion parameter is calculated, the second declaration price of the usage node is determined based on the calculated conversion parameter, and the target power transmission is generated by the first declaration price and the second declaration price. Price, in this way, a more accurate transmission price can be formulated from the three dimensions of supply node, user node and the transaction path between the two, and accurate data can be provided for subsequent power price setting, bidding and other work.

In the embodiment of the present disclosure, to obtain the first declared price of the usage node based on the power consumption data, all historical power transmission prices of the usage node in the power usage data may be first obtained, and then the first declared price may be determined based on the historical power transmission price.

In an embodiment of the present disclosure, after obtaining the target transaction path, the entire network transaction channel and transaction path can also be determined based on channel information such as channel name, power transmission price, network loss rate, channel capacity, voltage level, and number of channels. A presentation that combines two modules. Among them, the whole network transaction channel uses different color blocks in the map to display the Northeast Power Grid, North China Power Grid, Northwest Power Grid, East China Power Grid, and Central China Power Grid. After selecting the color block, the number of channels, channel name, transmission price, network loss rate, channel capacity, Channel information such as voltage level. In this way, the prediction results can be displayed to users more clearly and concretely, improving the user experience.

In the above embodiment, the calculation of conversion parameters based on the target transaction path can be further explained through Figure 2. The method includes:

S201: Obtain the target intermediate conversion variable.

In the embodiment of the present disclosure, the intermediate conversion variable is used to represent the loss of electricity during transportation based on the target transaction path.

It should be noted that the historical transaction path from the supply node to the user node may include cross-regional channels, inter-provincial tie lines or regional shared power grids. The transmission loss and electricity price of each cross-regional channel may be different. Therefore, it needs to be based on Each cross-region channel is analyzed separately to determine the target intermediate conversion variable.

In the embodiment of the present disclosure, the cross-region channel sub-conversion parameters and power transmission prices can be obtained for any cross-region channel, and then the transmission price and sub-conversion parameters are multiplied to obtain the sub-intermediate conversion variables, and finally all sub-intermediate conversion variables are obtained. The conversion variables are added to obtain the target intermediate conversion variable.

It should be noted that to obtain the cross-region channel sub-conversion parameters, you can first calculate the sub-effective power transmission rate from the supply node to the inter-region channel, and then multiply the sub-effective power transmission rates from all supply nodes to the inter-region channel to calculate and obtain the cross-region channel. Area channel sub-conversion parameter.

In the embodiment of the present disclosure, the target intermediate conversion variable can be calculated through the following formula:

in, is the target intermediate conversion variable, N is the total number of cross-region channels,/> is the sub-effective power transmission rate of the cross-region channel labeled r,/> is the power transmission price of the cross-region channel, and m is the serial number of the cross-region channel that currently needs to be calculated.

S202: Determine the conversion parameters based on the target transaction path.

In the embodiment of the present disclosure, multiple cross-region channels of the target transaction path and the transmission network loss rate corresponding to each cross-region channel can be first obtained, and then the transmission network loss rate is subtracted from 1 to obtain the effective transmission network loss rate of each cross-region channel. Transmission rate, and finally multiply the effective transmission rates of all cross-region channels to calculate the conversion parameters.

In the embodiment of the present disclosure, the conversion parameter can be calculated through the following formula:

in, is the conversion parameter, N is the total number of cross-region channels, m is the serial number of the cross-region channel that currently needs to be calculated,/> The sub-effective power transmission rate of the cross-region channel labeled m.

In the embodiment of the present disclosure, the target intermediate conversion variable is first obtained, and then the conversion parameters are determined based on the target transaction path. Therefore, by dividing the target transaction path into multiple cross-region channels and analyzing them separately, more accurate conversion parameters can be obtained and the accuracy of the data can be improved.

In the embodiment of the present disclosure, to determine the target transmission price based on the first declared price and the second declared price, the first declared price and the conversion parameter may be multiplied first, and the product may be subtracted from the target intermediate conversion variable to obtain Calculate and obtain the second declared price.

The second declaration price can be calculated by the following formula.

in, is the target intermediate conversion variable,/> is the conversion parameter,/> is the first declared price of the buyer node in period t,/> is the second declared price of the buyer node in period t.

In the embodiment of the present disclosure, the optimal trading strategy is determined based on the first declaration price and the second declaration price, and the sales price of the supply node can also be obtained, and then the predicted quotation is adjusted based on the sales price and the second declaration price, and the formulation Optimal trading strategy.

It should be noted that the optimal trading strategy can also be formulated with reference to the preset limiting conditions. There can be a variety of preset limiting conditions, and there are no limitations here. For example, limiting conditions may include rate of return, preferred routes, etc.

Corresponding to the electricity price obtaining methods provided by the above embodiments, one embodiment of the present disclosure also provides an electric power price obtaining device. Corresponding to the electricity price acquisition method, the above implementation of the electricity price acquisition method is also applicable to the electricity price acquisition device provided by the embodiments of the present disclosure, and will not be described in detail in the following embodiments.

Figure 3 is a schematic diagram of an electricity price acquisition device proposed by the present disclosure. As shown in Figure 3, the electricity price acquisition device 300 includes: an acquisition module 310, a calling module 320, a determination module 330 and a formulation module 340.

Among them, the acquisition module 310 is used to acquire the power consumption data of supply nodes and usage nodes to be predicted.

The calling module 320 is used to obtain the target transaction path of power transmission from the supply node to the using node based on the power consumption data, and the first declared price of the using node.

The determination module 330 is configured to calculate the conversion parameter based on the target transaction path, and determine the second declaration price of the supply node based on the conversion parameter and the first declaration price.

The formulating module 340 is configured to determine the target transmission price based on the first declared price and the second declared price.

In the embodiment of the present disclosure, the determination module 330 is also used to: obtain the target intermediate conversion variable; and determine the conversion parameters based on the target transaction path.

In the embodiment of the present disclosure, the determination module 330 is also used to: obtain multiple cross-region channels of the target transaction path and the transmission network loss rate corresponding to each cross-region channel; subtract the transmission network loss rate from 1 to obtain each segment. The effective power transmission rate of cross-region channels; multiply the effective power transmission rates of all cross-region channels to calculate the conversion parameters.

In the embodiment of the present disclosure, the determination module 330 is also used to: for any cross-region channel, obtain the sub-conversion parameter and the power transmission price of the cross-region channel; multiply the transmission price and the sub-conversion parameter to obtain the sub-intermediate conversion variable; Add all child intermediate conversion variables to obtain the target intermediate conversion variable.

In the embodiment of the present disclosure, the determination module 330 is also used to: calculate the sub-effective power transmission rate from the supply node to the inter-region channel; and multiply the sub-effective power transmission rates from all supply nodes to the inter-region channel to calculate and obtain the inter-region channel. Channel sub-conversion parameters.

In the embodiment of the present disclosure, the determination module 330 is also used to multiply the first declared price and the conversion parameter, and subtract the product from the target intermediate conversion variable to calculate and obtain the second declared price.

In the embodiment of the present disclosure, the formulation module 340 is also used to: obtain all historical power transmission prices of the nodes used in the power consumption data; and determine the first declared price based on the historical power transmission prices.

Thus, by predicting the target transaction path and the first declared price of the usage node, the conversion parameter is calculated, the second declaration price of the usage node is determined based on the calculated conversion parameter, and the target power transmission is generated by the first declaration price and the second declaration price. Price, in this way, a more accurate transmission price can be formulated from the three dimensions of supply node, user node and the transaction path between the two, and accurate data can be provided for subsequent power price setting, bidding and other work.

In order to implement the above embodiments, an embodiment of the present disclosure also proposes an electronic device 400. As shown in Figure 4, the electronic device 400 includes: a processor 401 and a memory 402 communicatively connected to the processor. The memory 402 stores information that can be used by at least one The instructions executed by the processor are executed by at least one processor 401 to implement the electricity price obtaining method according to the embodiment of the first aspect of the present disclosure.

In order to implement the above embodiments, embodiments of the present disclosure also provide a non-transient computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to implement the electricity price acquisition method as in the first embodiment of the present disclosure.

In order to implement the above embodiments, embodiments of the present disclosure also provide a computer program product, which includes a computer program. When the computer program is executed by a processor, the computer program implements the electricity price obtaining method according to the embodiment of the first aspect of the present disclosure.

In the description of the present disclosure, it should be understood that the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", " "Back", "Left", "Right", "Vertical", "Horizontal", "Top", "Bottom", "Inside", "Outside", "Clockwise", "Counterclockwise", "Axis", The orientations or positional relationships indicated by "radial direction", "circumferential direction", etc. are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the present disclosure and simplifying the description, and do not indicate or imply the referred devices or elements. Must have a specific orientation, be constructed and operate in a specific orientation and therefore are not to be construed as limitations on the disclosure.

In addition, the terms “first” and “second” are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of indicated technical features. Therefore, features defined as "first" and "second" may explicitly or implicitly include one or more of these features. In the description of the present disclosure, "plurality" means two or more than two, unless otherwise expressly and specifically limited.

In the description of this specification, reference to the terms "one embodiment," "some embodiments," "an example," "specific examples," or "some examples" or the like means that specific features are described in connection with the embodiment or example. , structures, materials, or features are included in at least one embodiment or example of the present disclosure. In this specification, the schematic expressions of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the specific features, structures, materials or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, those skilled in the art may combine and combine different embodiments or examples and features of different embodiments or examples described in this specification unless they are inconsistent with each other.

Although the embodiments of the present disclosure have been shown and described above, it can be understood that the above-mentioned embodiments are illustrative and should not be construed as limitations to the present disclosure. Those of ordinary skill in the art can make modifications to the above-mentioned embodiments within the scope of the present disclosure. The embodiments are subject to changes, modifications, substitutions and variations.

Claims (10)

1. A power price acquisition method, characterized by comprising:

acquiring electricity consumption data of a supply node to be predicted and a use node;

acquiring a target transaction path of the power transmission from the supply node to the using node and a first declaration price of the using node based on the power consumption data;

calculating a conversion parameter based on the target transaction path, and determining a second declared price of the supply node based on the conversion parameter and the first declared price;

a target power transmission price is determined based on the first declared price and the second declared price.

2. The method of claim 1, wherein the calculating a conversion parameter based on the target transaction path comprises:

acquiring a target intermediate conversion variable;

a conversion parameter is determined based on the target transaction path.

3. The method of claim 2, wherein the determining a conversion parameter based on the target transaction path comprises:

acquiring a plurality of sections of cross-region channels of the target transaction path and a power transmission network loss rate corresponding to each section of cross-region channel;

subtracting the transmission network loss rate from 1 to obtain the effective transmission rate of each section of the cross-regional channel;

and multiplying the effective power transmission rates of all the cross-zone channels to calculate and obtain the conversion parameters.

4. A method according to claim 3, wherein the obtaining the target intermediate conversion variable comprises:

aiming at any cross-zone channel, acquiring sub-conversion parameters and power transmission prices of the cross-zone channel;

multiplying the power transmission price and the sub-conversion parameters to obtain sub-intermediate conversion variables;

all sub-intermediate conversion variables are added to obtain the target intermediate conversion variable.

5. The method of claim 4, wherein the obtaining the cross-zone channel sub-conversion parameter comprises:

calculating the sub-effective power transmission rate from the supply node to the trans-regional channel;

multiplying the sub-effective power transmission rates from all the supply nodes to the cross-zone channel to calculate and obtain the cross-zone channel sub-conversion parameters.

6. The method of any of claims 2-5, wherein the determining a second declared price for the supply node based on the conversion parameter and the first declared price comprises:

multiplying the first declaration price and the conversion parameter, and subtracting the product from a target intermediate conversion variable to calculate and obtain the second declaration price.

7. The method of claim 1, wherein obtaining a first declared price for the usage node based on the electricity usage data comprises:

acquiring all historical power transmission prices of the using nodes in the power consumption data;

the first declared price is determined based on the historical transmission price.

8. An electric power price acquisition device, characterized by comprising:

the acquisition module is used for acquiring electricity utilization data of the supply node and the use node to be predicted;

the calling module is used for acquiring a target transaction path of the power transmission from the supply node to the using node based on the power consumption data and a first declaration price of the using node;

a determining module configured to calculate a conversion parameter based on the target transaction path, and determine a second declaration price of the supply node based on the conversion parameter and the first declaration price;

and the formulating module is used for determining a target power transmission price based on the first declaration price and the second declaration price.

9. An electronic device, comprising a memory and a processor;

wherein the processor runs a program corresponding to executable program code stored in the memory by reading the executable program code for implementing the method according to any one of claims 1-7.

10. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of any one of claims 1-7.