A method and apparatus for power supply distribution

Abstract

This application discloses a power supply allocation method and apparatus, relating to the field of power technology. The method includes: extracting boundary parameters from an acquired guidance text; determining the selection probability of a candidate settlement value per unit of electricity based on a probability density function of the cleared settlement value per unit of electricity; determining the expected value of the actual settlement value per unit of electricity based on the selection probability; constructing a life-cycle power allocation planning model including an objective function and constraints; the decision variables of the model include the allocation ratio of guaranteed supply electricity and various non-guaranteed supply electricity; the objective function is used to maximize the expected value of the average settlement value per unit of electricity over the entire life-cycle based on the selection probability of the candidate settlement value per unit of electricity and the expected value of the actual settlement value per unit of electricity; the boundary parameters are used to provide parameter constraint ranges for the model; and solving the model to obtain the target allocation ratio of guaranteed supply electricity and various non-guaranteed supply electricity.

Description

Technical Field

[0001] This application relates to the field of power technology, and in particular to a power supply and distribution method and apparatus. Background Technology

[0002] In the electricity market, the service cycle of an electricity supply project is usually very long, with a full life cycle of 20 to 25 years. During this period, electricity supply is achieved through the cooperation of various electricity supply methods (i.e., multiple electricity supply dimensions). Throughout the life cycle of an electricity supply project, the electricity supply mechanism and market environment will continue to change, and the electricity supply allocation strategy (i.e., how the proportion of each electricity supply method is allocated) needs to be adjusted accordingly.

[0003] However, when formulating power supply allocation strategies, traditional methods are prone to the "curse of dimensionality" due to the long time span and the involvement of multiple stages of strategy adjustments. This makes it difficult to determine a suitable power supply allocation strategy, and an unsuitable power supply allocation strategy cannot adapt to the dual fluctuations of the mechanism and the market, making it difficult to ensure a stable power supply. Summary of the Invention

[0004] This application provides a power supply distribution method and apparatus to solve or at least partially solve the defects or deficiencies in related technologies.

[0005] In a first aspect, this application provides a power supply distribution method, the power supply distribution method comprising: Obtain the guidance text for the power supply project and extract boundary parameters from the guidance text; The probability of a candidate settlement value per unit of electricity is determined based on the probability density function of the cleared settlement value per unit of electricity; the probability density function of the cleared settlement value per unit of electricity follows a normal distribution. Based on the selection probability of the candidate settlement value per unit of electricity, the expected value of the actual settlement value per unit of electricity is determined; Based on the boundary parameters, the selection probability of the candidate settlement value per unit of electricity, and the expected value of the actual settlement value per unit of electricity, a life-cycle power allocation planning model including an objective function and constraints is constructed. The decision variables of the life-cycle settlement index planning model include: the allocation ratio of guaranteed supply electricity and the allocation ratio of various non-guaranteed supply electricity. The objective function is used to maximize the expected value of the average settlement value per unit of electricity throughout the life-cycle of the power supply project, based on the selection probability of the candidate settlement value per unit of electricity and the expected value of the actual settlement value per unit of electricity. The life-cycle of the power supply project includes a guaranteed supply stage and a non-guaranteed supply stage, where the non-guaranteed supply stage supplies the various non-guaranteed supply electricity. The constraints include constraints for the guaranteed supply stage and the non-guaranteed supply stage, respectively. The boundary parameters provide the parameter constraint range for the life-cycle power allocation planning model. Solve the full life cycle power allocation planning model to obtain the target allocation ratio of the power supply guaranteed by the mechanism and the target allocation ratio of the power supply guaranteed by various non-mechanism methods.

[0006] Secondly, this application provides a power supply distribution device, the power supply distribution device comprising: The parameter extraction module is used to obtain the guidance text of the power supply project and extract boundary parameters from the guidance text. The probability determination module is used to determine the selection probability of a candidate settlement value per unit of electricity based on the probability density function of the clearing settlement value per unit of electricity; the probability density function of the clearing settlement value per unit of electricity follows a normal distribution. The expectation determination module is used to determine the expected value of the actual settlement value per unit of electricity based on the selection probability of the candidate settlement value per unit of electricity. The model building module is used to construct a life-cycle power allocation planning model, including an objective function and constraints, based on the boundary parameters, the selection probability of the candidate settlement value per unit of electricity, and the expected value of the actual settlement value per unit of electricity. The decision variables of the life-cycle settlement index planning model include: the allocation ratio of guaranteed supply electricity and the allocation ratio of various non-guaranteed supply electricity. The objective function is used to maximize the expected value of the average settlement value per unit of electricity throughout the life-cycle of the power supply project, based on the selection probability of the candidate settlement value per unit of electricity and the expected value of the actual settlement value per unit of electricity. The life-cycle of the power supply project includes a guaranteed supply stage and a non-guaranteed supply stage, where the non-guaranteed supply stage supplies the various non-guaranteed supply electricity. The constraints include constraints for the guaranteed supply stage and the non-guaranteed supply stage, respectively. The boundary parameters provide the parameter constraint range for the life-cycle power allocation planning model. The model solving module is used to solve the full life cycle power allocation planning model to obtain the target allocation ratio of the power supply guaranteed by the mechanism and the target allocation ratio of the power supply guaranteed by various non-mechanism.

[0007] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application provides a power supply allocation method and apparatus. Based on boundary parameters extracted from the guidance text of power supply projects, the probability of selection of candidate settlement values ​​per unit of electricity, and the expected value of actual settlement values ​​per unit of electricity, a full life-cycle power allocation planning model is constructed. Under the constraints of different stages in the full life cycle, the expected value of the average settlement value per unit of electricity in the full life cycle is maximized by solving the objective function, thereby obtaining a suitable power supply allocation strategy. The power supply strategy determined by the power supply project based on the settlement value characteristics per unit of electricity in the full life cycle can achieve the rational allocation of diversified power supply methods, balance the advantages and disadvantages of different power supply methods, enable the allocation of each power supply method to adapt to the dual fluctuations of the mechanism and the market, improve the stability of the power supply system, and ensure a stable power supply. Attached Figure Description

[0008] Figure 1 A schematic flowchart illustrating a power supply distribution method according to an embodiment of this application; Figure 2 A functional module diagram of a power supply distribution device provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0009] The present application will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0010] In one exemplary embodiment, such as Figure 1 As shown, a power supply distribution method is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. The terminal is not limited to desktop computers or laptops, and the server can be a standalone server, a server cluster, or a cloud server.

[0011] In the embodiments of this application, such as Figure 1 As shown, the power supply distribution method includes steps 101 to 105. Wherein: Step 101: Obtain the guidance text for the power supply project and extract the boundary parameters from the guidance text.

[0012] The guidance text for a power supply project may include relevant descriptions and restrictions for the power supply project. After obtaining the guidance text for the power supply project, the boundary parameters of the power supply project can be extracted from the guidance text.

[0013] Optionally, the method for extracting boundary parameters from the guidance text may include: extracting boundary parameters from the guidance text using the BERT-BiLSTM-CRF model.

[0014] Optionally, the boundary parameters may include the following: the upper limit of the allocation ratio of the supplied electricity guaranteed by the mechanism. The mechanism guarantees the implementation period of electricity supply. Annual upper limit for the entire life cycle of a power supply project And the upper limit of the candidate settlement value per unit of electricity. and lower limit value .

[0015] Among these requirements, power supply projects need to include a portion of electricity supplied through guaranteed supply mechanisms, known as guaranteed supply electricity (also called guaranteed supply volume). Guaranteed supply electricity is the portion of electricity in a power supply project that is guaranteed according to policies or rules. This is the core electricity volume that the project prioritizes for consumption, and settlement for this portion can be made according to the agreed-upon guaranteed electricity price. Additionally, power supply projects also need to include a portion of electricity supplied through non-guaranteed supply mechanisms, known as non-guaranteed supply volume. There can be various non-guaranteed supply methods. By coordinating guaranteed supply and non-guaranteed supply methods in a reasonable allocation ratio, power supply can be achieved, adapting to electricity market fluctuations and ensuring a stable power supply.

[0016] Each power supply method must account for a certain proportion of the total electricity supplied under each power supply method within the entire power supply project. This proportion is the allocation ratio for each power supply method. Specifically, the proportion of electricity supplied under the mechanism-guaranteed supply method within the entire power supply project is the allocation ratio for the mechanism-guaranteed supply electricity. This allocation ratio is limited to no more than [a certain percentage]. .

[0017] For the portion of electricity supplied through mechanisms that guarantee supply, the implementation period needs to be restricted. The mechanism-guaranteed supply method can only be adopted within the implementation period, and settlement will be made at the mechanism electricity price. The duration of the electricity supplied under the mechanism-guaranteed supply method is limited to not exceeding the implementation period. .

[0018] The entire lifecycle of a power supply project comprises two phases: the first phase is the guaranteed supply phase, and the second phase is the non-guaranteed supply phase. The guaranteed supply phase covers the electricity supplied through guaranteed supply methods, while the non-guaranteed supply phase covers the supply of various non-guaranteed supply electricity through a combination of different non-guaranteed supply methods. The entire lifecycle of a power supply project is limited to an annual upper limit. .

[0019] The candidate settlement value per unit of electricity is a core indicator for determining the electricity supply allocation strategy (i.e., the proportion by which all supply methods are allocated). It characterizes the possible values ​​for the settlement value per unit of electricity, and the set of all candidate settlement values ​​per unit of electricity constitutes the set of possible values ​​for the settlement value per unit of electricity. In this embodiment, a suitable electricity supply allocation strategy can be found by quantifying the selection probability of each candidate settlement value per unit of electricity. The upper limit of the candidate settlement value per unit of electricity... and lower limit value The set of selectable values ​​for the unit electricity billing value is limited.

[0020] Step 102: Determine the selection probability of the candidate settlement value per unit of electricity based on the probability density function of the clearing settlement value per unit of electricity; the probability density function of the clearing settlement value per unit of electricity follows a normal distribution.

[0021] The unit electricity clearing settlement value refers to the final unit electricity settlement value that satisfies all market rules and physical constraints in the electricity market, formed through factors such as market supply and demand, bidding mechanisms, and grid operation constraints. Optionally, in the embodiments of this application, the unit electricity clearing settlement value can be a unified marginal unit electricity clearing settlement value, that is, the unit electricity clearing settlement value can adopt a unified marginal clearing mechanism.

[0022] In this embodiment of the application, the clearing settlement value per unit of electricity can be obtained by fitting historical clearing settlement value data per unit of electricity. probability density function , Follows a normal distribution ,in, Clearing settlement value per unit of electricity The mean, Clearing settlement value per unit of electricity The variance.

[0023] Then, settlement can be based on the unit electricity clearing value. probability density function Determine the candidate settlement value per unit of electricity probability of selection The selection criteria are based on preset rules or experience, and are specific to the candidate settlement values ​​per unit of electricity. One of the selection criteria is that if the candidate settlement value per unit of electricity meets the selection criterion, the candidate is selected; if it does not meet the selection criterion, the candidate is not selected. The lower the candidate settlement value per unit of electricity, the higher the probability of selection.

[0024] In this embodiment of the application, the selection probability of the candidate settlement value per unit of electricity can be determined by the following formula (8) based on the probability density function of the clearing settlement value per unit of electricity. Formula (8); in, This represents the candidate settlement value per unit of electricity. This indicates the probability of a candidate settlement value per unit of electricity being selected. This represents the clearing settlement value per unit of electricity. The probability density function representing the clearing settlement value per unit of electricity. This indicates the upper limit of the settlement value per unit of electricity.

[0025] Formula (8) above indicates the candidate settlement value for a unit of electricity. The probability of selection is the cumulative probability that is less than or equal to the clearing settlement value per unit of electricity, and the candidate settlement value per unit of electricity. The lower the value, the greater the probability of it being below the clearing settlement value per unit of electricity; candidate settlement value per unit of electricity. The higher the probability of being selected.

[0026] Step 103: Determine the expected value of the actual settlement value per unit of electricity based on the selection probability of the candidate settlement value per unit of electricity.

[0027] Under a unified marginal clearing mechanism, if the candidate settlement value per unit of electricity If selected, the actual settlement value per unit of electricity is not... Instead, it is the clearing settlement value per unit of electricity. Therefore, in this embodiment of the application, the expected value of the actual settlement value per unit of electricity can be determined by the following formula (9) based on the selection probability of the candidate settlement value per unit of electricity. Formula (9); in, This represents the actual settlement value per unit of electricity. This indicates that you have been selected. This represents the expected value of the actual settlement value per unit of electricity. This represents the clearing settlement value per unit of electricity. The probability density function representing the clearing settlement value per unit of electricity. This indicates the upper limit of the settlement value per unit of electricity. This represents the candidate settlement value per unit of electricity. This represents the probability of a candidate settlement value per unit of electricity being selected.

[0028] Formula (9) above shows the candidate settlement value per unit of electricity. This serves only as an entry threshold; the actual settlement value per unit of electricity depends on the clearing settlement value per unit of electricity.

[0029] Step 104: Based on boundary parameters, the probability of selection of candidate settlement values ​​per unit of electricity, and the expected value of actual settlement values ​​per unit of electricity, a life-cycle electricity allocation planning model including an objective function and constraints is constructed. The decision variables of the life-cycle settlement index planning model include: the allocation ratio of electricity supplied under guaranteed mechanisms and the allocation ratio of various non-guaranteed electricity supplies. The objective function is used to maximize the expected value of the average settlement value per unit of electricity throughout the life-cycle of the electricity supply project, based on the probability of selection of candidate settlement values ​​per unit of electricity and the expected value of actual settlement values ​​per unit of electricity. The life-cycle of the electricity supply project includes a guaranteed supply stage and a non-guaranteed supply stage. The non-guaranteed supply stage is used to supply various non-guaranteed electricity supplies. The constraints include constraints for the guaranteed supply stage and the non-guaranteed supply stage respectively. Boundary parameters are used to provide the parameter constraint range for the life-cycle electricity allocation planning model.

[0030] In this step, the settlement can be based on boundary parameters and candidate settlement values ​​per unit of electricity. probability of selection Expected value of actual settlement value per unit of electricity A full life-cycle power allocation planning model is constructed. This model comprehensively considers the characteristics of different stages throughout the entire life cycle of a power supply project (including the stage of guaranteed supply through mechanisms and the stage of non-guaranteed supply through mechanisms), thereby realizing the allocation planning of power supply methods throughout the entire life cycle of the power supply project.

[0031] The decision variables in a full life-cycle electricity allocation planning model can include: the allocation ratio of guaranteed supply electricity and the allocation ratio of various non-guaranteed supply electricity (i.e., the allocation ratio of each type of non-guaranteed supply electricity). The full life-cycle of an electricity supply project includes a guaranteed supply phase and a non-guaranteed supply phase. The guaranteed supply phase is used to supply both guaranteed supply electricity and various non-guaranteed supply electricity, while the non-guaranteed supply phase is used to supply various non-guaranteed supply electricity. In other words, in the guaranteed supply phase, guaranteed supply electricity and various non-guaranteed supply electricity are combined to achieve electricity supply; in the non-guaranteed supply phase, guaranteed supply electricity is no longer used, and only various non-guaranteed supply electricity are combined to achieve electricity supply.

[0032] Optionally, the various non-mechanism-guaranteed electricity supply may include at least two of the following: electricity supplied by agreement for a certain period (i.e., the portion of electricity settled at an agreed unit electricity settlement value within a certain period), electricity supplied in real time on the spot market (i.e., the portion of electricity settled according to the real-time settlement value of unit electricity in the market), and electricity supplied through green electricity (i.e., the portion of electricity supplied through green electricity).

[0033] In one alternative implementation, when multiple non-mechanism-guaranteed power supply methods include time-bound contractual power supply, spot real-time power supply, and green electricity supply, the power supply allocation strategy for the entire lifecycle of a power supply project can be defined as an allocation ratio encompassing four dimensions: Mechanism to guarantee electricity supply (in the annual In this embodiment of the application, the mechanism ensures that the electricity supply is within the annual allocation ratio. The allocation ratio, also known as the annual The mechanism guarantees the allocation ratio of supplied electricity. The allocation ratios for electricity supplied through other methods can also be described here. This decision variable is controlled by the bidding results and exit decisions. If a power supply project is won and not withdrawn or reduced, the mechanism-guaranteed allocation ratio for the first year will be the preset ratio. (One of the boundary parameters), namely Furthermore, the annual allocation ratio of guaranteed electricity supply cannot be higher than the previous year's allocation ratio.

[0034] The allocation ratio of electricity supply is agreed upon within a specified period.

[0035] The allocation ratio of real-time spot electricity supply.

[0036] The proportion of electricity supplied by green electricity.

[0037] Define the year Distribution ratio vector .

[0038] The objective function of the life-cycle power allocation planning model is used to calculate the candidate settlement value per unit of electricity. probability of selection Expected value of actual settlement value per unit of electricity To maximize the expected value of the average settlement value per unit of electricity throughout the entire lifecycle of a power supply project. .

[0039] In an alternative implementation, the objective function may include the following formula (7): Formula (7); in, ; This represents the average settlement value per unit of electricity generated throughout the entire lifecycle of a power supply project. This represents the expected value of the average settlement value per unit of electricity over the entire lifecycle of a power supply project. This represents the annual upper limit for the entire lifecycle of a power supply project. This refers to any year in the entire lifecycle of a power supply project. Indicates the year The total calculated value of electricity consumption. Indicates the year The expected value of the total calculated value of electricity consumption. Indicates the year Internet usage power consumption This represents the candidate settlement value per unit of electricity. This indicates the probability of a candidate settlement value per unit of electricity being selected. This indicates the candidate settlement value per unit of electricity in the annual case of selection. The total calculated value of electricity consumption, This indicates the annual settlement value per unit of electricity when not selected. The total calculated value of electricity consumption. Optionally, It can be set to 0, or compared to These are very small or extremely small values.

[0040] The constraints of the full life-cycle electricity allocation planning model include: first-stage constraints for the mechanism-guaranteed supply stage, and second-stage constraints for the non-mechanism-guaranteed supply stage.

[0041] The first stage constraints include the following formulas (1), (2), and (3): Formula (1); Formula (2); Formula (3).

[0042] in, This refers to any year in the entire lifecycle of a power supply project. The mechanism indicates that the electricity supply will be guaranteed within the annual target range. The allocation ratio The mechanism indicates that the electricity supply will be guaranteed within the annual target range. The allocation ratio This indicates the upper limit of the allocation ratio of electricity supply guaranteed by the mechanism. This represents the first of several non-mechanism-based power supply guarantees. Non-mechanism-based guarantee of electricity supply in the annual The allocation ratio This indicates the year of exit from the supply guarantee phase of the mechanism. This represents the annual upper limit for the entire lifecycle of a power supply project.

[0043] In the stage of ensuring supply through mechanisms ( ),year Distribution ratio vector It exhibits the following dual-track characteristics: The annual allocation ratio of guaranteed power supply cannot exceed that of the previous year. Furthermore, provided that a power supply project has been won and not withdrawn or reduced, the annual allocation ratio of guaranteed power supply cannot exceed [a certain percentage]. ; The sum of the allocation ratio of electricity supplied by the mechanism and the allocation ratio of electricity supplied by various non-mechanism guarantees is 100%.

[0044] Accordingly, in the stage of ensuring supply through mechanisms, the formula (7) The following formula (7-1) can be satisfied: Formula (7-1).

[0045] The second-stage constraints include the following formulas (4), (5), and (6): Formula (4); Formula (5); Formula (6).

[0046] In the non-mechanism-guaranteed supply stage ( The allocation ratio of electricity supplied by the mechanism is reduced to zero, and the mechanism-guaranteed supply method is no longer used. The total allocation ratio of various non-mechanism-guaranteed electricity supplies is 100%.

[0047] Accordingly, in the non-mechanism-guaranteed supply stage, in formula (7) The following formula (7-2) can be satisfied: Formula (7-2).

[0048] in, ; The mechanism indicates that the electricity supply will be guaranteed within the annual target range. The allocation ratio This represents the actual settlement value per unit of electricity. This indicates that you have been selected. This represents the expected value of the actual settlement value per unit of electricity. This represents the weighted average settlement value per unit of electricity during the non-mechanism-guaranteed supply phase. This represents the first of several non-mechanism-based power supply guarantees. Non-mechanism-based guarantee of electricity supply in the annual The allocation ratio This represents the first of several non-mechanism-based power supply guarantees. Non-mechanism-based guarantee of electricity supply in the annual The predicted value of the average settlement value per unit of electricity.

[0049] Optionally, It can be based on the first The historical settlement value (i.e., historical data) of the unit electricity volume of the non-mechanism-guaranteed supply method is used to predict the first... Non-mechanism-based guarantee of electricity supply in the annual The average settlement value per unit of electricity (i.e., the predicted value). For example, ,in, It can predict the annual electricity supply volume based on the historical settlement value of the unit electricity volume under the term-based supply agreement method. Average settlement value per unit of electricity; This can be used to predict the real-time spot supply volume in the annual period based on the historical settlement value of unit electricity volume (referring only to the historical settlement value of unit electricity volume of the power type used in the spot market). Average settlement value per unit of electricity; It can predict the annual green electricity supply volume based on the historical settlement value of the unit electricity volume according to the green electricity supply method. The average settlement value per unit of electricity.

[0050] The boundary parameters extracted in step 101 are used to provide parameter constraints for the full life-cycle power allocation planning model. Specifically, this can include forming constraint conditions and limiting the traversal range (or value range) of parameters during the objective function solution process. For example, a mechanism can be used to guarantee an upper limit on the allocation ratio of supplied electricity. This forms one of the constraints represented by formula (1); the mechanism can guarantee the execution period of the electricity supply. Determine the year of exit from the mechanism. The lower bound of the traversal range is It can be based on the annual upper limit of the entire life cycle of the power supply project. Determine the year The upper limit of the traversal range is It can be based on the upper limit of the candidate settlement value per unit of electricity. and lower limit Determine the candidate settlement value per unit of electricity The upper and lower bounds of the traversal range are respectively and .

[0051] Step 105: Solve the full life cycle power allocation planning model to obtain the target allocation ratio of power supply guaranteed by mechanisms and the target allocation ratio of power supply without mechanisms.

[0052] In this step, the power supply allocation strategy can be obtained by solving the full life cycle power allocation planning model, that is, how to allocate each type of supply method for each year of the full life cycle of the power supply project.

[0053] In one alternative implementation, the life-cycle power allocation planning model can be solved in the following manner, including inner and outer loops, specifically: In the inner loop, a fixed unit of electricity is used as the candidate settlement value. And mechanisms to ensure the exit of the supply phase in the annual Combination ( , In the case of ), determine each year in the entire life cycle of the power supply project. The weighted average settlement value per unit of electricity during the non-mechanism-guaranteed supply phase is thus achieved. The largest mechanism guarantees the candidate allocation ratio of supplied electricity. and various non-mechanism-based guaranteed power supply candidate allocation ratios ; In the outer loop, iterate through the candidate settlement values ​​for unit electricity. And mechanisms to ensure the exit of the supply phase in the annual Each combination determines the expected value of the average settlement value per unit of electricity over the entire lifecycle of the power supply project from the candidate allocation ratios for guaranteed power supply. The biggest mechanism guarantees the target allocation ratio of electricity supply. And, from the candidate allocation ratios of each non-mechanism-guaranteed power supply, determine the expected value of the average settlement value per unit of power over the entire life cycle of the power supply project. The maximum target allocation ratio for each type of non-mechanism-guaranteed power supply .

[0054] The inner loop can be fixed. and Each year, the allocation ratio of electricity supply guaranteed by the optimization mechanism and the allocation ratio of electricity supply guaranteed by various non-mechanism methods are optimized to ensure that the annual... maximize.

[0055] The outer loop iterates through each type ( , The combination of ) in which, The traversal range is [ , ], The traversal range is [ For each type ( , Combinations of ) to iterate through the years In each year, the inner loop is called, causing the inner loop to return the value that makes that year's result... The largest and Then summarize each combination ( , In all years And calculate each combination ( , ) corresponding For each type ( , After the combination traversal is completed, select the one that makes The largest combination ( , Among them, variables Can decide Whether it is effective, variables Can decide When to return to zero, therefore, find out... The largest combination ( , ), then we can find the result in the inner loop from [ Within the year The largest and And find out in ( Within the year The largest and .

[0056] For example, the annual upper limit for the entire lifecycle of a power supply project. The upper limit of the allocation ratio of electricity supply guaranteed by the mechanism for 25 years. The mechanism guarantees the implementation period of electricity supply. The probability density function of the 10-year, unit electricity clearing settlement value follows a normal distribution. In this case, the exit year for the mechanism-guaranteed supply phase can be determined through the above solution process. =8, that is, from the first year to the end of the eighth year, the power supply can be provided by a combination of mechanism-guaranteed supply and various non-mechanism-guaranteed supply methods (including time-bound supply, spot real-time supply and green electricity supply). After the end of the eighth year, the mechanism-guaranteed supply method can be phased out, and only various non-mechanism-guaranteed supply methods (including time-bound supply, spot real-time supply and green electricity supply) can be used to provide power supply.

[0057] The final power supply allocation strategy is as follows: Years 1-8 (Supply Guarantee Phase, also known as the Mechanism Operation Period): Implementation 70% of the guaranteed electricity supply will be allocated through a mechanism-based system, while the remaining 30% will be allocated according to a pre-agreed timeframe. =20%, Spot real-time supply electricity allocation ratio =10%.

[0058] Years 9-25 (Non-mechanism-guaranteed supply phase, also known as the full marketization period): The proportion of electricity allocated for mechanism-guaranteed supply is reduced to zero, and the proportion of electricity allocated for green electricity supply is implemented. The power supply allocation ratio shall be agreed upon within the specified time limit. =30%, Spot real-time supply power allocation ratio =10%.

[0059] Formulating a power supply allocation strategy is a typical high-dimensional nonlinear dynamic programming problem. Traditional methods are prone to convergence due to the "curse of dimensionality" when dealing with such planning problems with long time spans and multiple stages of adjustment, making it difficult to determine a suitable power supply allocation strategy. The power supply allocation method provided in this application constructs a full life-cycle power allocation planning model based on boundary parameters extracted from the guidance text of power supply projects, the probability of selection of candidate settlement values ​​per unit of electricity, and the expected value of actual settlement values ​​per unit of electricity. Under the constraints of different stages in the full life cycle, the objective function is solved to maximize the expected value of the average settlement value per unit of electricity throughout the entire life cycle, thereby obtaining a suitable power supply allocation strategy. The power supply strategy determined based on the settlement value characteristics of the unit of electricity throughout the full life cycle of the power supply project in this application can achieve a reasonable allocation of diversified power supply methods, balance the advantages and disadvantages of different power supply methods, and enable the allocation of each power supply method to adapt to the dual fluctuations of the mechanism and the market, thereby improving the stability of the power supply system and ensuring a stable power supply.

[0060] In some embodiments of this application, when solving the full lifecycle power allocation planning model, the instantaneous power allocation ratio of various power supply methods can be optimized through an inner loop, and the exit node can be achieved through an outer loop that traverses the entire lifecycle. With key operators This decouples computational efficiency and solution space in large-span periodic multidimensional coupled optimization. This decoupling ensures the search for the global optimal solution while significantly reducing the solution complexity of the model, thus solving the problem of balancing solution efficiency and solution quality in large-span periodic multidimensional coupled optimization.

[0061] Traditional methods often employ deterministic unit electricity settlement values ​​to solve for optimal strategies, failing to objectively characterize the stochastic characteristics under the specific rule of "uniform marginal clearing." This means the specific unit electricity settlement value only determines whether a project is selected; the final unit electricity settlement value used in a power supply project is the cleared settlement value, not the selected settlement value. Under this rule, the unit electricity settlement value and the actual settlement price (i.e., the cleared settlement value) are not linearly equal but exhibit complex conditional probabilistic coupling. In some embodiments of this application, by constructing a probability density function for the cleared settlement value, the nonlinear impact of the specific unit electricity settlement value on the selection probability and the expected actual settlement price is quantified. This improvement addresses the technical shortcomings of traditional methods in highly stochastic market environments and significantly enhances the physical confidence of power market behavior prediction.

[0062] It should be noted that the settlement items and settlement units for various settlement values ​​in this application embodiment depend on the specific settlement method agreed upon in the power supply project, and this application embodiment does not impose specific limitations on this.

[0063] Based on the same inventive concept, this application also provides a power supply distribution device for implementing the power supply distribution method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more power supply distribution device embodiments provided below can be found in the limitations of the power supply distribution method described above, and will not be repeated here.

[0064] In one exemplary embodiment, such as Figure 2 As shown, a power supply distribution device is provided, which includes: The parameter extraction module is used to obtain the guidance text of the power supply project and extract boundary parameters from the guidance text. The probability determination module is used to determine the selection probability of a candidate settlement value per unit of electricity based on the probability density function of the clearing settlement value per unit of electricity; the probability density function of the clearing settlement value per unit of electricity follows a normal distribution. The expectation determination module is used to determine the expected value of the actual settlement value per unit of electricity based on the selection probability of the candidate settlement value per unit of electricity. The model building module is used to construct a life-cycle power allocation planning model, including an objective function and constraints, based on the boundary parameters, the selection probability of the candidate settlement value per unit of electricity, and the expected value of the actual settlement value per unit of electricity. The decision variables of the life-cycle settlement index planning model include: the allocation ratio of guaranteed supply electricity and the allocation ratio of various non-guaranteed supply electricity. The objective function is used to maximize the expected value of the average settlement value per unit of electricity throughout the life-cycle of the power supply project, based on the selection probability of the candidate settlement value per unit of electricity and the expected value of the actual settlement value per unit of electricity. The life-cycle of the power supply project includes a guaranteed supply stage and a non-guaranteed supply stage, where the non-guaranteed supply stage supplies the various non-guaranteed supply electricity. The constraints include constraints for the guaranteed supply stage and the non-guaranteed supply stage, respectively. The boundary parameters provide the parameter constraint range for the life-cycle power allocation planning model. The model solving module is used to solve the full life cycle power allocation planning model to obtain the target allocation ratio of the power supply guaranteed by the mechanism and the target allocation ratio of the power supply guaranteed by various non-mechanism.

[0065] Optionally, the constraints include: a first-stage constraint for the mechanism-guaranteed supply stage, and a second-stage constraint for the non-mechanism-guaranteed supply stage. The constraints of the first stage include the following formulas (1), (2), and (3): Formula (1); Formula (2); Formula (3); The second stage constraints include the following formulas (4), (5), and (6): Formula (4); Formula (5); Formula (6); in, This refers to any year in the entire lifecycle of the power supply project. This indicates that the mechanism guarantees the supply of electricity within the annual range. The allocation ratio This indicates that the mechanism guarantees the supply of electricity within the annual range. The allocation ratio This indicates the upper limit of the allocation ratio of the supplied electricity guaranteed by the mechanism. This indicates the first of the various non-mechanism-based power supply guarantees. Non-mechanism-based guarantee of electricity supply in the annual The allocation ratio This indicates the year in which the mechanism guarantees the exit from the supply phase. This represents the annual upper limit of the entire life cycle of the power supply project.

[0066] Optionally, the objective function includes the following formula (7): Formula (7); in, ; This represents the average settlement value per unit of electricity consumption over the entire lifecycle of the power supply project. This represents the expected value of the average settlement value per unit of electricity over the entire lifecycle of the power supply project. This represents the annual upper limit for the entire lifecycle of the power supply project. This refers to any year in the entire lifecycle of the power supply project. Indicates the year The total calculated value of electricity consumption, Indicates the year The expected value of the total calculated value of electricity consumption. Indicates the year Internet usage power consumption This represents the candidate settlement value per unit of electricity. This indicates the probability of the candidate settlement value per unit of electricity being selected. This indicates the annual settlement value per unit of electricity under the selected condition. The total calculated value of electricity consumption, This indicates the annual settlement value per unit of electricity when it is not selected. The total calculated value of the electricity consumption.

[0067] Optionally, during the supply guarantee phase of the mechanism, in formula (7) It satisfies the following formula (7-1): Formula (7-1); In the non-mechanism-guaranteed supply phase, in formula (7) It satisfies the following formula (7-2): Formula (7-2); in, ; This indicates that the mechanism guarantees the supply of electricity within the annual range. The allocation ratio This represents the actual settlement value per unit of electricity. This indicates that you have been selected. This represents the expected value of the actual settlement value per unit of electricity. This represents the weighted average settlement value per unit of electricity during the non-mechanism-guaranteed supply phase. This indicates the first of the various non-mechanism-based power supply guarantees. Non-mechanism-based guarantee of electricity supply in the annual The allocation ratio This indicates the first of the various non-mechanism-based power supply guarantees. Non-mechanism-based guarantee of electricity supply in the annual The predicted value of the average settlement value per unit of electricity.

[0068] Optionally, solving the full life-cycle power allocation planning model to obtain the target allocation ratio of the power supply guaranteed by the mechanism and the target allocation ratio of the power supply guaranteed by various non-mechanism methods includes: In the inner loop, with a fixed combination of the candidate settlement value per unit of electricity and the exit year of the mechanism-guaranteed supply phase, the candidate allocation ratio of the mechanism-guaranteed supply electricity that maximizes the weighted average settlement value per unit of electricity in the non-mechanism-guaranteed supply phase, as well as the candidate allocation ratio of the various non-mechanism-guaranteed supply electricity, are determined for each year in the entire life cycle of the power supply project. In the outer loop, it iterates through each combination of the candidate settlement value per unit of electricity and the exit year of the mechanism-guaranteed supply phase, determines the target allocation ratio of the mechanism-guaranteed supply electricity that maximizes the expected value of the average settlement value per unit of electricity throughout the entire life cycle of the power supply project from the candidate allocation ratios of the mechanism-guaranteed supply electricity, and determines the target allocation ratio of each non-mechanism-guaranteed supply electricity that maximizes the expected value of the average settlement value per unit of electricity throughout the entire life cycle of the power supply project from each candidate allocation ratio of non-mechanism-guaranteed supply electricity.

[0069] Optionally, determining the selection probability of a candidate settlement value per unit of electricity based on the probability density function of the clearing settlement value per unit of electricity includes: Based on the probability density function of the clearing settlement value per unit of electricity, the selection probability of the candidate settlement value per unit of electricity is determined by the following formula (8); Formula (8); in, This represents the candidate settlement value per unit of electricity. This indicates the probability of the candidate settlement value per unit of electricity being selected. This represents the clearing settlement value per unit of electricity. The probability density function representing the clearing settlement value per unit of electricity. This indicates the upper limit of the unit electricity clearing settlement value.

[0070] Optionally, determining the expected value of the actual settlement value per unit of electricity based on the selection probability of the candidate settlement value per unit of electricity includes: Based on the selection probability of the candidate settlement value per unit of electricity, the expected value of the actual settlement value per unit of electricity is determined by the following formula (9); Formula (9); in, This represents the actual settlement value per unit of electricity. This indicates that you have been selected. This represents the expected value of the actual settlement value per unit of electricity. This represents the clearing settlement value per unit of electricity. The probability density function representing the clearing settlement value per unit of electricity. This indicates the upper limit of the unit electricity clearing settlement value. This represents the candidate settlement value per unit of electricity. This indicates the probability of the candidate settlement value per unit of electricity being selected.

[0071] Optionally, the boundary parameters include: the upper limit of the allocation ratio of the supplied electricity guaranteed by the mechanism, the execution period of the supplied electricity guaranteed by the mechanism, the annual upper limit of the entire life cycle of the power supply project, and the upper and lower limits of the candidate settlement value per unit of electricity.

[0072] Optionally, the various non-mechanism-guaranteed power supply includes at least two of the following: power supply agreed upon within a specified period, real-time spot power supply, and green power supply.

[0073] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0074] The aforementioned computer device may be, for example, a server or a terminal, and its internal structure diagram may be as follows: Figure 3 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When executed by the processor, the computer program implements a power supply distribution method.

[0075] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0076] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0077] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0078] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0079] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. 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).

[0080] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0081] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0082] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for power supply and distribution, characterized in that, The power supply distribution method includes: Obtain the guidance text for the power supply project and extract boundary parameters from the guidance text; The probability of a candidate settlement value per unit of electricity is determined based on the probability density function of the cleared settlement value per unit of electricity; the probability density function of the cleared settlement value per unit of electricity follows a normal distribution. Based on the selection probability of the candidate settlement value per unit of electricity, the expected value of the actual settlement value per unit of electricity is determined; Based on the boundary parameters, the selection probability of the candidate settlement value per unit of electricity, and the expected value of the actual settlement value per unit of electricity, a life-cycle power allocation planning model including an objective function and constraints is constructed. The decision variables of the life-cycle settlement index planning model include: the allocation ratio of guaranteed supply electricity and the allocation ratio of various non-guaranteed supply electricity. The objective function is used to maximize the expected value of the average settlement value per unit of electricity throughout the life-cycle of the power supply project, based on the selection probability of the candidate settlement value per unit of electricity and the expected value of the actual settlement value per unit of electricity. The life-cycle of the power supply project includes a guaranteed supply stage and a non-guaranteed supply stage, where the non-guaranteed supply stage supplies the various non-guaranteed supply electricity. The constraints include constraints for the guaranteed supply stage and the non-guaranteed supply stage, respectively. The boundary parameters provide the parameter constraint range for the life-cycle power allocation planning model. Solve the full life cycle power allocation planning model to obtain the target allocation ratio of the power supply guaranteed by the mechanism and the target allocation ratio of the power supply guaranteed by various non-mechanism methods.

2. The power supply and distribution method according to claim 1, characterized in that, The constraints include: first-stage constraints for the mechanism-guaranteed supply phase, and second-stage constraints for the non-mechanism-guaranteed supply phase. The constraints of the first stage include the following formulas (1), (2), and (3): Official (1); Official (2); Official (3); The second stage constraints include the following formulas (4), (5), and (6): Official (4); Official (5); Official (6); in, This refers to any year in the entire lifecycle of the power supply project. This indicates that the mechanism guarantees the supply of electricity within the annual range. The allocation ratio This indicates that the mechanism guarantees the supply of electricity within the annual range. The allocation ratio This indicates the upper limit of the allocation ratio of the supplied electricity guaranteed by the mechanism. This indicates the first of the various non-mechanism-based power supply guarantees. Non-mechanism-based guarantee of electricity supply in the annual The allocation ratio This indicates the year in which the mechanism guarantees the exit from the supply phase. This represents the annual upper limit of the entire life cycle of the power supply project.

3. The power supply and distribution method according to claim 1, characterized in that, The objective function includes the following formula (7): Official (7); in, ; This represents the average settlement value per unit of electricity consumption over the entire lifecycle of the power supply project. This represents the expected value of the average settlement value per unit of electricity over the entire lifecycle of the power supply project. This represents the annual upper limit for the entire lifecycle of the power supply project. This refers to any year in the entire lifecycle of the power supply project. Indicates the year The total calculated value of electricity consumption, Indicates the year The expected value of the total calculated value of electricity consumption. Indicates the year Internet usage power consumption This represents the candidate settlement value per unit of electricity. This indicates the probability of the candidate settlement value per unit of electricity being selected. This indicates the annual settlement value per unit of electricity under the selected condition. The total calculated value of electricity consumption, This indicates the annual settlement value per unit of electricity when it is not selected. The total calculated value of the electricity consumption.

4. The power supply and distribution method according to claim 3, characterized in that, During the supply guarantee phase of the mechanism, in formula (7) It satisfies the following formula (7-1): Official (7-1); In the non-mechanism-guaranteed supply phase, in formula (7) It satisfies the following formula (7-2): Official (7-2); in, ; This indicates that the mechanism guarantees the supply of electricity within the annual range. The allocation ratio This represents the actual settlement value per unit of electricity. This indicates that you have been selected. This represents the expected value of the actual settlement value per unit of electricity. This represents the weighted average settlement value per unit of electricity during the non-mechanism-guaranteed supply phase. This indicates the first of the various non-mechanism-based power supply guarantees. Non-mechanism-based guarantee of electricity supply in the annual The allocation ratio This indicates the first of the various non-mechanism-based power supply guarantees. Non-mechanism-based guarantee of electricity supply in the annual The predicted value of the average settlement value per unit of electricity.

5. The power supply and distribution method according to claim 1, characterized in that, Solving the full life-cycle power allocation planning model yields the target allocation ratio of the power supply guaranteed by the mechanism and the target allocation ratio of the various non-mechanism-guaranteed power supply, including: In the inner loop, with a fixed combination of the candidate settlement value per unit of electricity and the exit year of the mechanism-guaranteed supply phase, the candidate allocation ratio of the mechanism-guaranteed supply electricity that maximizes the weighted average settlement value per unit of electricity in the non-mechanism-guaranteed supply phase, as well as the candidate allocation ratio of the various non-mechanism-guaranteed supply electricity, are determined for each year in the entire life cycle of the power supply project. In the outer loop, it iterates through each combination of the candidate settlement value per unit of electricity and the exit year of the mechanism-guaranteed supply phase, determines the target allocation ratio of the mechanism-guaranteed supply electricity that maximizes the expected value of the average settlement value per unit of electricity throughout the entire life cycle of the power supply project from the candidate allocation ratios of the mechanism-guaranteed supply electricity, and determines the target allocation ratio of each non-mechanism-guaranteed supply electricity that maximizes the expected value of the average settlement value per unit of electricity throughout the entire life cycle of the power supply project from each candidate allocation ratio of non-mechanism-guaranteed supply electricity.

6. The power supply and distribution method according to claim 1, characterized in that, The determination of the selection probability of a candidate settlement value per unit of electricity based on the probability density function of the clearing settlement value per unit of electricity includes: Based on the probability density function of the clearing settlement value per unit of electricity, the selection probability of the candidate settlement value per unit of electricity is determined by the following formula (8); Official (8); in, This represents the candidate settlement value per unit of electricity. This indicates the probability of the candidate settlement value per unit of electricity being selected. This represents the clearing settlement value per unit of electricity. The probability density function representing the clearing settlement value per unit of electricity. This indicates the upper limit of the unit electricity clearing settlement value.

7. The power supply and distribution method according to claim 1, characterized in that, The determination of the expected value of the actual settlement value per unit of electricity based on the selection probability of the candidate settlement value per unit of electricity includes: Based on the selection probability of the candidate settlement value per unit of electricity, the expected value of the actual settlement value per unit of electricity is determined by the following formula (9); Official (9); in, This represents the actual settlement value per unit of electricity. This indicates that you have been selected. This represents the expected value of the actual settlement value per unit of electricity. This represents the clearing settlement value per unit of electricity. The probability density function representing the clearing settlement value per unit of electricity. This indicates the upper limit of the unit electricity clearing settlement value. This represents the candidate settlement value per unit of electricity. This indicates the probability of the candidate settlement value per unit of electricity being selected.

8. The power supply and distribution method according to claim 1, characterized in that, The boundary parameters include: the upper limit of the allocation ratio of the supplied electricity guaranteed by the mechanism, the execution period of the supplied electricity guaranteed by the mechanism, the annual upper limit of the entire life cycle of the power supply project, and the upper and lower limits of the candidate settlement value per unit of electricity.

9. The power supply and distribution method according to claim 1, characterized in that, The various non-mechanism-based guaranteed power supply includes at least two of the following: power supply agreed upon within a specified period, real-time spot power supply, and green electricity supply.

10. A power supply and distribution device, characterized in that, The power supply distribution device includes: The parameter extraction module is used to obtain the guidance text of the power supply project and extract boundary parameters from the guidance text. The probability determination module is used to determine the selection probability of a candidate settlement value per unit of electricity based on the probability density function of the clearing settlement value per unit of electricity; the probability density function of the clearing settlement value per unit of electricity follows a normal distribution. The expectation determination module is used to determine the expected value of the actual settlement value per unit of electricity based on the selection probability of the candidate settlement value per unit of electricity. The model building module is used to construct a life-cycle power allocation planning model, including an objective function and constraints, based on the boundary parameters, the selection probability of the candidate settlement value per unit of electricity, and the expected value of the actual settlement value per unit of electricity. The decision variables of the life-cycle settlement index planning model include: the allocation ratio of guaranteed supply electricity and the allocation ratio of various non-guaranteed supply electricity. The objective function is used to maximize the expected value of the average settlement value per unit of electricity throughout the life-cycle of the power supply project, based on the selection probability of the candidate settlement value per unit of electricity and the expected value of the actual settlement value per unit of electricity. The life-cycle of the power supply project includes a guaranteed supply stage and a non-guaranteed supply stage, where the non-guaranteed supply stage supplies the various non-guaranteed supply electricity. The constraints include constraints for the guaranteed supply stage and the non-guaranteed supply stage, respectively. The boundary parameters provide the parameter constraint range for the life-cycle power allocation planning model. The model solving module is used to solve the full life cycle power allocation planning model to obtain the target allocation ratio of the power supply guaranteed by the mechanism and the target allocation ratio of the power supply guaranteed by various non-mechanism.

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