Policy elastic boundary-based cross-border power transaction scheme generation method and system

Abstract

The invention discloses a cross-border power transaction scheme generation method and system based on a policy elastic boundary, relates to the technical field of multi-objective optimization and the field of power transaction, and mainly aims to improve the problem that the policy quantification capability of an existing optimization method is insufficient. And the feasibility of the generated optimal transaction scheme is reduced due to the fact that the generated optimal transaction scheme does not conform to the elastic interval actually executed by the policy. According to the method, policy terms are deconstructed through a Huyd model to construct a single-party policy boundary matrix, namely an elastic interval participating in calculation, so that quantization of fuzzy policy terms is realized, the elastic interval completely conforming to actual policy execution is ensured, and the feasibility of an optimal transaction scheme is improved; furthermore, through the Pareto optimal concept, the transaction fairness of the generated cross-border power transaction scheme is ensured, so that the scheme is more easily accepted by two transaction parties, and the transaction achievement rate is improved.

Description

Technical Field

[0001] This application relates to the fields of multi-objective optimization technology and power trading, and in particular to a method and system for generating cross-border power trading schemes based on policy flexibility boundaries. Background Technology

[0002] Cross-border electricity trading is a core pathway to optimizing resource allocation and achieving regional carbon neutrality goals within the context of global energy transition. It not only addresses the problem of uneven energy distribution but also holds significant strategic importance in promoting the widespread adoption of clean energy. This field lies at the intersection of power system technology, market economics, and international trade policy. Its core challenge lies in generating feasible trading solutions that simultaneously satisfy the multiple interests of both parties within the complex and diverse policy frameworks of different countries.

[0003] Currently, most existing optimization methods focus on the techno-economic level. Specifically, based on precisely quantifiable physical and economic parameters such as power generation costs, transmission losses, grid congestion, and renewable energy volatility, they construct single-objective optimization models with the goal of minimizing costs. When considering policy factors, relevant policy provisions are usually transformed into constraints and incorporated into the model, and the techno-economic optimal solution is sought within the explicit and static constraints.

[0004] However, since policies are actually flexible and descriptive terms rather than explicit and static constraints, existing optimization methods lack the ability to quantify policies. Consequently, the generated optimal trading solutions often fail to meet the flexibility range of actual policy implementation, thus reducing their feasibility. Summary of the Invention

[0005] In view of this, this application provides a method and system for generating cross-border power trading schemes based on policy flexibility boundaries. The main purpose is to improve the problem that the optimal trading schemes generated by existing optimization methods often have reduced feasibility because they do not conform to the flexibility range of actual policy implementation.

[0006] According to one aspect of this application, a method for generating cross-border power trading schemes based on policy flexibility boundaries is provided, comprising: For each party involved in cross-border power transactions, obtain the policy tools for cross-border power transactions, and based on the Hud model, decompose the policy tools into authoritative tools and wealth tools, and transform the policy terms in the policy tools into parameter ranges corresponding to the authoritative tools and the wealth tools; Based on the authoritative tool and its corresponding parameter range, and the wealth tool and its corresponding parameter range, a unilateral policy boundary matrix is ​​constructed, wherein the unilateral policy boundary matrix is ​​used to characterize the constraints of the feasible domain of decision variables. Based on the interests of both parties in cross-border power transactions, a bilateral multi-objective optimization function set is constructed. Based on the unilateral policy boundary matrix and business constraints, a multi-objective optimization algorithm is used to collaboratively optimize the bilateral multi-objective optimization function set to obtain the Pareto front. The Pareto front contains multiple cross-border power transaction schemes to be verified. Each of the proposed cross-border power trading schemes to be verified is tested for feasibility and Pareto optimality, and the verified cross-border power trading scheme is taken as the Pareto optimal cross-border power trading scheme.

[0007] Preferably, the policy tools are broken down into authority tools and wealth tools based on the Hud model, including: Based on the Hud model, the authoritative instrument is deconstructed into policy elements representing market access rules, and the wealth instrument is deconstructed into policy elements representing network access fee ranges and value-added tax rates.

[0008] Preferably, the construction of a unilateral policy boundary matrix based on the authoritative tool and its corresponding parameter range, and the wealth tool and its corresponding parameter range, includes: The market access rules and their corresponding parameter ranges are quantified into constraints on the set of entities allowed to participate in cross-border power transactions; The range of grid access fees and the corresponding parameter ranges are quantified into a range constraint on the value of grid transmission cost; The value-added tax rate and its corresponding parameter range are quantified into a range constraint for the tax rate of electricity products. Based on the constraints of the set of entities allowed to participate in cross-border electricity transactions, the range of values ​​for grid transmission costs, and the range of values ​​for electricity commodity tax rates, a unilateral policy boundary matrix is ​​constructed.

[0009] Preferably, the construction of a bilateral multi-objective optimization function set based on the interests of both parties in a cross-border power transaction includes: To understand the interests of both parties in a cross-border power transaction, including the seller's economic objectives, asset efficiency objectives, stability objectives, the buyer's economic objectives, energy security objectives, and green and low-carbon objectives. Based on the seller's economic objectives, the seller's asset efficiency objectives, the seller's stability objectives, the buyer's economic objectives, the buyer's energy security objectives, and the buyer's green and low-carbon objectives, a bilateral multi-objective optimization function set is constructed, expressed as the following formula. , in, Indicates the seller's economic objective. Indicates the unit price in cross-border electricity transactions. This indicates the total electricity sold. This indicates the VAT rate for cross-border electricity transactions. This indicates the seller's asset efficiency objective. Indicates the seller's stability objective. This indicates the amount of electricity sold by the seller under a long-term contract to the buyer. Indicates the buyer's economic objectives. This indicates the buyer's energy security objectives. This indicates the buyer's green and low-carbon goals. This indicates the amount of electricity sold by the seller to the buyer under a short-term contract.

[0010] Preferably, the step of using a multi-objective optimization algorithm to collaboratively optimize the bilateral multi-objective optimization function set based on the unilateral policy boundary matrix and business constraints to obtain the Pareto front includes: Based on the unilateral policy boundary matrix and the business constraints, an initial population is randomly generated, wherein the initial population contains multiple initial cross-border power trading schemes. For each initial cross-border power trading scheme, calculate the bilateral multi-objective function value set corresponding to the initial cross-border power trading scheme, and based on each bilateral multi-objective function value set, determine the dominance relationship between any two initial cross-border power trading schemes, and based on the dominance relationship, perform non-dominance ranking on each initial cross-border power trading scheme to determine the priority level of each initial cross-border power trading scheme; Within the same priority level, calculate the congestion distance in the bilateral multi-objective function space for each initial cross-border power trading scheme; Based on a selection strategy that prioritizes priority and uses congestion distance as a secondary factor, parent cross-border power trading schemes are selected from the initial population. Cross-border power trading schemes are then subjected to cross-trading and mutation operations to generate offspring cross-border power trading schemes. The offspring cross-border power trading schemes satisfy the unilateral policy boundary matrix and the business constraints. All the parent generation cross-border power trading schemes and all the offspring generation cross-border power trading schemes are merged to obtain the next generation population; The priority level of cross-border power trading schemes in the next generation population is re-determined and congestion distance is calculated to select the parent cross-border power trading schemes of the next generation population. Crossover and mutation operations are then performed on the parent cross-border power trading schemes of the next generation population to obtain the offspring cross-border power trading schemes of the next generation population. All parent cross-border power trading schemes and all offspring cross-border power trading schemes of the next generation population are merged to obtain the next generation population. This process is repeated until a preset iteration termination condition is met. The set of cross-border power trading schemes with the highest priority level in the final generation population is taken as the Pareto front.

[0011] Preferably, the step of verifying the feasibility and Pareto optimality of each of the proposed cross-border power trading schemes to be verified, and taking the verified cross-border power trading scheme as the Pareto optimal cross-border power trading scheme, includes: For each cross-border power trading scheme to be verified, verify whether the cross-border power trading scheme to be verified meets the unilateral policy boundary matrix and the business constraints, and obtain the feasibility verification result of the cross-border power trading scheme to be verified. For each decision variable in the cross-border power trading scheme to be verified, the decision variable is adjusted to increase the benefit of one party, resulting in an adjusted cross-border power trading scheme. It is then determined whether the adjusted cross-border power trading scheme satisfies the reduction of the benefit of the other party, thus obtaining the Pareto optimality verification result of the cross-border power trading scheme to be verified. If both the feasibility verification result and the Pareto optimality verification result are satisfied, then the cross-border power trading scheme to be verified is taken as the Pareto optimal cross-border power trading scheme.

[0012] Preferably, the business constraints include non-negative constraints on the amount of electricity traded, upper limits on the amount of imported electricity, constraints on the proportion of electricity under long-term contracts, constraints on the complementary proportion of electricity spot market, constraints on the trading price range, and constraints on the value-added tax rate range. According to another aspect of this application, a cross-border power trading scheme generation system based on policy flexibility boundaries is provided, comprising: The policy tool deconstruction module is used to obtain the policy tools for cross-border power transactions for each party involved in the transaction. Based on the Hud model, the policy tools are decomposed into authoritative tools and wealth tools, and the policy clauses in the policy tools are transformed into parameter ranges corresponding to the authoritative tools and the wealth tools. The unilateral policy boundary matrix construction module is used to construct a unilateral policy boundary matrix based on the authoritative tool and its corresponding parameter range, the wealth tool and its corresponding parameter range, wherein the unilateral policy boundary matrix is ​​used to characterize the constraints of the feasible domain of decision variables; The Pareto front generation module is used to construct a bilateral multi-objective optimization function set based on the interests of both parties in a cross-border power transaction, and to perform collaborative optimization of the bilateral multi-objective optimization function set using a multi-objective optimization algorithm based on the unilateral policy boundary matrix and business constraints to obtain the Pareto front. The Pareto front contains multiple cross-border power transaction schemes to be verified. The Pareto optimal cross-border power trading scheme generation module is used to verify the feasibility and Pareto optimality of each of the cross-border power trading schemes to be verified, and to take the verified cross-border power trading schemes as Pareto optimal cross-border power trading schemes.

[0013] Preferably, the policy tool deconstruction module is used for: Based on the Hud model, the authoritative instrument is deconstructed into policy elements representing market access rules, and the wealth instrument is deconstructed into policy elements representing network access fee ranges and value-added tax rates.

[0014] Preferably, the unilateral policy boundary matrix construction module is used for: The market access rules and their corresponding parameter ranges are quantified into constraints on the set of entities allowed to participate in cross-border power transactions; The range of grid access fees and the corresponding parameter ranges are quantified into a range constraint on the value of grid transmission cost; The value-added tax rate and its corresponding parameter range are quantified into a range constraint for the tax rate of electricity products. Based on the constraints of the set of entities allowed to participate in cross-border electricity transactions, the range of values ​​for grid transmission costs, and the range of values ​​for electricity commodity tax rates, a unilateral policy boundary matrix is ​​constructed.

[0015] Preferably, the Pareto front generation module includes a bilateral multi-objective optimization function set construction unit, used for: To understand the interests of both parties in a cross-border power transaction, including the seller's economic objectives, asset efficiency objectives, stability objectives, the buyer's economic objectives, energy security objectives, and green and low-carbon objectives. Based on the seller's economic objectives, the seller's asset efficiency objectives, the seller's stability objectives, the buyer's economic objectives, the buyer's energy security objectives, and the buyer's green and low-carbon objectives, a bilateral multi-objective optimization function set is constructed, expressed as the following formula. , in, Indicates the seller's economic objective. Indicates the unit price in cross-border electricity transactions. This indicates the total electricity sold. This indicates the VAT rate for cross-border electricity transactions. This indicates the seller's asset efficiency objective. Indicates the seller's stability objective. This indicates the amount of electricity sold by the seller under a long-term contract to the buyer. Indicates the buyer's economic objectives. This indicates the buyer's energy security objectives. This indicates the buyer's green and low-carbon goals. This indicates the amount of electricity sold by the seller to the buyer under a short-term contract.

[0016] Preferably, the Pareto front generation module includes a Pareto front generation unit, used for: Based on the unilateral policy boundary matrix and the business constraints, an initial population is randomly generated, wherein the initial population contains multiple initial cross-border power trading schemes. For each initial cross-border power trading scheme, calculate the bilateral multi-objective function value set corresponding to the initial cross-border power trading scheme, and based on each bilateral multi-objective function value set, determine the dominance relationship between any two initial cross-border power trading schemes, and based on the dominance relationship, perform non-dominance ranking on each initial cross-border power trading scheme to determine the priority level of each initial cross-border power trading scheme; Within the same priority level, calculate the congestion distance in the bilateral multi-objective function space for each initial cross-border power trading scheme; Based on a selection strategy that prioritizes priority and uses congestion distance as a secondary factor, parent cross-border power trading schemes are selected from the initial population. Cross-border power trading schemes are then subjected to cross-trading and mutation operations to generate offspring cross-border power trading schemes. The offspring cross-border power trading schemes satisfy the unilateral policy boundary matrix and the business constraints. All the parent generation cross-border power trading schemes and all the offspring generation cross-border power trading schemes are merged to obtain the next generation population; The priority level of cross-border power trading schemes in the next generation population is re-determined and congestion distance is calculated to select the parent cross-border power trading schemes of the next generation population. Crossover and mutation operations are then performed on the parent cross-border power trading schemes of the next generation population to obtain the offspring cross-border power trading schemes of the next generation population. All parent cross-border power trading schemes and all offspring cross-border power trading schemes of the next generation population are merged to obtain the next generation population. This process is repeated until a preset iteration termination condition is met. The set of cross-border power trading schemes with the highest priority level in the final generation population is taken as the Pareto front.

[0017] Preferably, the Pareto optimal cross-border electricity trading scheme generation module is used for: For each cross-border power trading scheme to be verified, verify whether the cross-border power trading scheme to be verified meets the unilateral policy boundary matrix and the business constraints, and obtain the feasibility verification result of the cross-border power trading scheme to be verified. For each decision variable in the cross-border power trading scheme to be verified, the decision variable is adjusted to increase the benefit of one party, resulting in an adjusted cross-border power trading scheme. It is then determined whether the adjusted cross-border power trading scheme satisfies the reduction of the benefit of the other party, thus obtaining the Pareto optimality verification result of the cross-border power trading scheme to be verified. If both the feasibility verification result and the Pareto optimality verification result are satisfied, then the cross-border power trading scheme to be verified is taken as the Pareto optimal cross-border power trading scheme.

[0018] Preferably, the business constraints include non-negative constraints on the amount of electricity traded, upper limits on the amount of imported electricity, constraints on the proportion of electricity under long-term contracts, constraints on the complementary proportion of electricity spot market, constraints on the trading price range, and constraints on the value-added tax rate range. According to another aspect of this application, a storage medium is provided, wherein at least one executable instruction is stored therein, the executable instruction causing a processor to perform an operation corresponding to the above-described method for generating cross-border power trading schemes based on policy flexibility boundaries.

[0019] According to another aspect of this application, a terminal is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus; The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the above-described method for generating cross-border power trading schemes based on policy flexibility boundaries.

[0020] By employing the above technical solutions, the technical solutions provided in the embodiments of this application have at least the following advantages: This application provides a method and system for generating cross-border power trading schemes based on policy flexibility boundaries. First, for each party involved in a cross-border power transaction, the policy tools for cross-border power trading are obtained. Based on the Hude model, these policy tools are decomposed into authority tools and wealth tools, and the policy clauses within these tools are transformed into parameter ranges corresponding to the authority tools and wealth tools. Second, based on the authority tools and their corresponding parameter ranges, and the wealth tools and their corresponding parameter ranges, a unilateral policy boundary matrix is ​​constructed. This unilateral policy boundary matrix is ​​used to characterize the constraints of the feasible region of decision variables. Third, based on the interests of both parties in the cross-border power transaction, a bilateral multi-objective optimization function set is constructed. Based on the unilateral policy boundary matrix and business constraints, a multi-objective optimization algorithm is used to collaboratively optimize the bilateral multi-objective optimization function set to obtain a Pareto front. The Pareto front contains multiple cross-border power trading schemes to be verified. Finally, the feasibility and Pareto optimality of each of the unverified cross-border power trading schemes are verified, and the verified scheme is taken as the Pareto optimal cross-border power trading scheme. Compared with existing technologies, the embodiments of this application deconstruct policy terms using the Hude model to construct a unilateral policy boundary matrix, which is the elastic range that can participate in the calculation. This achieves the quantification of ambiguous policy terms and ensures that the elastic range fully conforms to the actual implementation of the policy, thereby improving the feasibility of the optimal trading scheme. Furthermore, by using the concept of Pareto optimality, the fairness of the generated cross-border power trading scheme is ensured, making the scheme more acceptable to both parties to the transaction and improving the transaction completion rate.

[0021] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0022] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 This paper presents a flowchart illustrating a method for generating cross-border power trading schemes based on policy flexibility boundaries, as provided in an embodiment of this application. Figure 2 This paper illustrates a flowchart of another method for generating cross-border power trading schemes based on policy flexibility boundaries, as provided in an embodiment of this application. Figure 3This paper illustrates a block diagram of a cross-border power trading scheme generation system based on policy flexibility boundaries, as provided in an embodiment of this application. Figure 4 A schematic diagram of the structure of a terminal provided in an embodiment of this application is shown. Detailed Implementation

[0023] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0024] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0025] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the scope of this application and its application or use.

[0026] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0027] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0028] The embodiments of this application can be applied to computer systems / servers that can operate with a wide range of other general-purpose or special-purpose computing system environments or configurations. Examples of well-known computing systems, environments, and / or configurations suitable for use with computer systems / servers include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems, etc.

[0029] Computer systems / servers can be described in the general context of computer system executable instructions (such as program modules) executed by the computer system. Typically, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in distributed cloud computing environments, where tasks are performed by remote processing devices linked through a communication network. In distributed cloud computing environments, program modules can reside on local or remote computing system storage media, including storage devices.

[0030] This application provides a method for generating cross-border power trading schemes based on policy flexibility boundaries, such as... Figure 1 As shown, the method includes: 101. For each party involved in cross-border power transactions, obtain the policy tools for cross-border power transactions. Based on the Hud model, break down the policy tools into authoritative tools and wealth tools, and transform the policy clauses in the policy tools into parameter ranges corresponding to the authoritative tools and wealth tools.

[0031] Among these, authoritative tools are embodied in the licensing, prohibition, and standard setting of transaction entities, behaviors, and qualifications; wealth tools are embodied in various fees, taxes, and subsidies. In this embodiment of the application, the current execution end can be the generation module of the cross-border power trading scheme.

[0032] 102. Construct a unilateral policy boundary matrix based on authoritative tools and their corresponding parameter ranges, and wealth tools and their corresponding parameter ranges.

[0033] The unilateral policy boundary matrix is ​​used to characterize the constraints of the feasible domain of decision variables; the authority instrument and its corresponding parameter range are used to construct subject eligibility constraints; and the wealth instrument and its corresponding parameter range are used to construct the range constraints of power grid transmission costs and the range constraints of electricity commodity tax rates. In this embodiment, the unilateral policy boundary matrix can ensure from the source that the generated cross-border electricity trading scheme conforms to the flexibility range of actual policy implementation, thereby improving the feasibility of the scheme.

[0034] 103. Based on the interests of both parties in cross-border power transactions, a bilateral multi-objective optimization function set is constructed. Based on the unilateral policy boundary matrix and business constraints, a multi-objective optimization algorithm is used to perform collaborative optimization on the bilateral multi-objective optimization function set to obtain the Pareto front.

[0035] The objectives of cross-border power transactions include the interests of both parties, such as maximizing the seller's total revenue, maximizing the seller's electricity sales volume, maximizing the seller's long-term contract electricity volume ratio, minimizing the buyer's electricity purchase cost, minimizing the buyer's imported electricity volume, and maximizing the buyer's short-term contract electricity volume ratio. The bilateral multi-objective optimization function set must encompass all the interests of both parties. The Pareto front includes multiple unverified cross-border power transaction schemes, each representing different trade-offs. Business constraints include constraints on the non-negativity of transaction volume, the upper limit of imported electricity volume, the proportion of long-term contract electricity volume, the complementarity of electricity spot market share, the transaction price range, and the VAT rate range. For example... .

[0036] 104. Conduct feasibility and Pareto optimality verifications on each cross-border power trading scheme to be verified, and take the verified cross-border power trading scheme as the Pareto optimal cross-border power trading scheme.

[0037] Among them, the feasibility verification is used to verify whether the scheme in the Pareto front in step 103 of the embodiment satisfies the unilateral policy boundary matrix constraint and business constraint; the Pareto optimality verification is used to verify whether the scheme in the Pareto front in step 103 of the embodiment satisfies "it is impossible to increase the target value of the other party without reducing the target value of either party".

[0038] It is understandable that there may be multiple Pareto optimal cross-border electricity trading schemes, and each Pareto optimal cross-border electricity trading scheme has a different trade-off.

[0039] Compared with existing technologies, the embodiments of this application deconstruct policy terms using the Hude model to construct a unilateral policy boundary matrix, which is the elastic range that can participate in the calculation. This achieves the quantification of ambiguous policy terms and ensures that the elastic range fully conforms to the actual implementation of the policy, thereby improving the feasibility of the optimal trading scheme. Furthermore, by using the concept of Pareto optimality, the fairness of the generated cross-border power trading scheme is ensured, making the scheme more acceptable to both parties to the transaction and improving the transaction completion rate.

[0040] This application provides another method for generating cross-border power trading schemes based on policy flexibility boundaries, such as... Figure 2 As shown, the method includes: 201. Construct a unilateral policy boundary matrix.

[0041] Accordingly, step 201 of the embodiment specifically includes: for each party involved in the cross-border power transaction, obtaining the policy tools for cross-border power transactions; based on the Hude model, deconstructing the authoritative tool into policy elements representing market access rules, and deconstructing the wealth tool into policy elements representing grid access fee ranges and VAT rates; and converting the policy clauses in the policy tools into parameter ranges corresponding to the authoritative tool and the wealth tool; quantifying the market access rules and their corresponding parameter ranges into constraints on the set of entities allowed to participate in cross-border power transactions; quantifying the grid access fee range and its corresponding parameter ranges into constraints on the range of grid transmission costs; quantifying the VAT rate and its corresponding parameter range into constraints on the range of electricity commodity tax rates; and constructing a unilateral policy boundary matrix based on the constraints on the set of entities allowed to participate in cross-border power transactions, the constraints on the range of grid transmission costs, and the constraints on the range of electricity commodity tax rates.

[0042] In this embodiment, for each party involved in a cross-border power transaction, the relevant laws, regulations, bilateral agreements, and other policy documents are first collected. Then, based on the Hude model, the policy tools are deconstructed, that is, policy clauses are summarized and deconstructed into authoritative tools and wealth tools. Authoritative tools refer to policy elements representing market access rules, which may include entities permitted to participate in cross-border power transactions, such as power generation companies, trading companies, and distribution companies. Wealth tools refer to policy elements representing grid access fees and VAT rates. Grid access fees refer to the fees paid for using the other country's grid infrastructure for power transmission, and VAT is a tax levied on power commodity transactions. Furthermore, descriptive and flexible policy clauses are transformed into quantitative parameter ranges that can be directly processed by the mathematical model. Specifically, for market access rules, policy interpretation can transform them into explicit constraints on the set of entities permitted to participate in cross-border power transactions; for grid access fees, the range of grid transmission costs can be extracted from the policy clauses; and for VAT rates, the range of VAT rates applicable to cross-border power transactions can be extracted from the policy clauses. Finally, the quantified parameters are systematically integrated to construct a policy boundary matrix for a single trading party.

[0043] 202. Based on the interests of both parties in cross-border power transactions, construct a bilateral multi-objective optimization function set.

[0044] Accordingly, step 202 of the embodiment specifically includes: obtaining the interests of both parties in the cross-border power transaction, wherein the interests of both parties include the seller's economic objectives, seller's asset efficiency objectives, seller's stability objectives, buyer's economic objectives, buyer's energy security objectives, and buyer's green and low-carbon objectives; based on the seller's economic objectives, seller's asset efficiency objectives, seller's stability objectives, buyer's economic objectives, buyer's energy security objectives, and buyer's green and low-carbon objectives, constructing a bilateral multi-objective optimization function set, expressed as the following formula. , in, This indicates the seller's economic objective, namely, maximizing total revenue after deducting value-added tax. This indicates the unit price for cross-border electricity transactions (unit: USD / MWh). , Indicates total electricity sales That is, the total electricity purchased by the buyer, and , Indicates the value-added tax rate for cross-border electricity transactions , This indicates the seller's asset efficiency objective, namely, maximizing total electricity sales. This indicates the seller's stability objective, namely, maximizing the proportion of long-term contracts. This indicates the amount of electricity sold by the seller under a long-term contract to the buyer. This indicates the buyer's economic objective, namely, minimizing the total cost of electricity purchase and conversely maximizing it. This indicates the buyer's energy security objective, namely, minimizing imports. This indicates the buyer's green and low-carbon objective, namely, maximizing the proportion of spot trading. This indicates the amount of electricity sold by the seller to the buyer under a short-term contract (unit: megawatt-hours). .

[0045] It should be noted that, due to the conflict between objectives, there is no single "unique optimal solution" that is best for all objectives. Instead, there is a set of "optimal compromise solutions," which is the Pareto optimal frontier. Therefore, in order to satisfy the mathematical consistency of Pareto optimization, the buyer's "minimization objective" is transformed into a "maximization objective" through a negative transformation, ultimately determining a system of six objective functions for the bilateral multi-objective system.

[0046] 203. Based on the unilateral policy boundary matrix and business constraints, a multi-objective optimization algorithm is used to perform collaborative optimization on the bilateral multi-objective optimization function set to obtain the Pareto front.

[0047] Accordingly, step 203 of the embodiment specifically includes: randomly generating an initial population based on the unilateral policy boundary matrix and business constraints, wherein the initial population contains multiple initial cross-border power trading schemes; for each initial cross-border power trading scheme, calculating the bilateral multi-objective function value set corresponding to the initial cross-border power trading scheme, and determining the dominance relationship between any two initial cross-border power trading schemes based on each bilateral multi-objective function value set, and performing non-dominated ranking of each initial cross-border power trading scheme based on the dominance relationship to determine the priority level of each initial cross-border power trading scheme; within the same priority level, calculating the congestion distance in the bilateral multi-objective function space of each initial cross-border power trading scheme; and selecting parent cross-border power trading schemes from the initial population according to the selection strategy of prioritizing priority level and using congestion distance as a secondary factor, and performing crossover and mutation on each parent cross-border power trading scheme. The process involves generating offspring cross-border power trading schemes, where each scheme satisfies the unilateral policy boundary matrix and business constraints. All parent and offspring cross-border power trading schemes are merged to obtain the next generation population. Priority ranking and congestion distance calculations are then performed on the cross-border power trading schemes in the next generation population to select the parent schemes. Crossover and mutation operations are then performed on the parent schemes to obtain offspring cross-border power trading schemes. Finally, all parent and offspring cross-border power trading schemes in the next generation population are merged to obtain the next generation population. This process is repeated until a preset iteration termination condition is met. The set of cross-border power trading schemes with the highest priority in the final generation population is taken as the Pareto front.

[0048] The Pareto front is represented by the following formula. , Indicates the initial population. Values ​​can be retrieved Each initial cross-border power trading scheme All constraints are satisfied, and a solution is generated within the feasible region of the decision variables through uniform random sampling: , , , , Representing an interval uniform distribution on and These correspond to the upper limits for the proportion of long-term contracts and the upper limits for the proportion of spot goods, respectively.

[0049] In this embodiment, firstly, based on the unilateral policy boundary matrix and business constraints, a population containing N initial trading schemes is randomly generated. Each initial trading scheme is defined by a set of decision variables including the trading price, long-term contract electricity volume, short-term contract electricity volume, and VAT rate. Further, the six objective function values ​​corresponding to each initial cross-border power trading scheme are calculated, i.e., a bilateral multi-objective function value set. Any two initial cross-border power trading schemes A and B are compared. If scheme A is no worse than scheme B in all six objectives (i.e., for both the seller's and buyer's objectives, the value of A is greater than or equal to the value of B, and is strictly better in at least one objective), then A is determined to dominate B. If an initial cross-border power trading scheme is not dominated by any other initial cross-border power trading scheme in the population, then that initial cross-border power trading scheme is determined as a non-dominated solution. All non-dominated solutions are selected and determined as the first priority level. Subsequently, these first-priority initial cross-border power trading schemes are temporarily removed. New non-dominated solutions are found among the remaining initial cross-border power trading schemes and determined as the second priority level. This process is repeated until the priority level of all initial cross-border power trading schemes has been determined. Specifically, for all objective functions… Not inferior to : There exists at least one objective function. Strictly superior to : , making Then it can be called Dominate , recorded as If no scheme exists in the population Dominate ,but For non-dominated solutions, the ordering is based on dominance relations, where the initial population... For each solution, calculate the number of solutions that dominate it. and the set of dominant schemes. Let the sorting levels be determined again. All The solution is classified into the first level (non-dominated solution set). ),right Each of the schemes traverse its dominated set For each make ,make Classified as the second level Based on the sorting process, this process is repeated until all solutions are classified. ,in This represents the optimal solution set (non-dominated solutions). Furthermore, to avoid the algorithm converging to a local point on the Pareto front and to ensure that the final solutions are widely distributed in the objective space, covering different trade-offs, within each priority level, for each objective function, all initial cross-border power trading schemes within that level are sorted in ascending order of their function values. For a given initial cross-border power trading scheme, its normalized distance to the function values ​​of its two adjacent initial cross-border power trading schemes on each objective function is calculated, and these distances are summed to obtain the crowding distance of that initial cross-border power trading scheme. The larger the crowding distance, the sparser the surrounding area of ​​the initial cross-border power trading scheme, and the greater its contribution to maintaining population diversity. Therefore, it should be protected in subsequent selections. Specifically, for each priority level... The scheme in the middle, according to each objective function Sort, to obtain a sorted subset. ,in, for The number of solutions in the solution, defining the solution In the target The crowded distance above, that is: , In this design, the congestion level of the boundary scheme is set to infinity to avoid being eliminated. This allows us to find the intra-level extremum of the objective function. Furthermore, based on a selection strategy that prioritizes priority level and secondarily considers crowding distance—that is, prioritizing schemes with higher priority levels, and when priority levels are the same, prioritizing schemes with larger crowding distances—we select excellent initial cross-border electricity trading schemes from the current population as parent schemes. Specifically, based on a binary preference selection of "non-dominance level + crowding degree," we generate the parent set. Among them, priority selection, etc. For options with lower congestion levels, if the levels are the same, choose the congestion level. For larger-scale solutions, calculate the probability of selection based on different levels of solutions: , The probability is selected according to the roulette wheel betting method. A set of parent schemes. Further, parent cross-border power trading schemes are randomly paired. For each paired scheme, their decision variables are mixed in a certain proportion to generate two child cross-border power trading schemes. A small-scale random perturbation is applied to a decision variable of each child scheme to obtain the child cross-border power trading scheme. It should be noted that the child cross-border power trading schemes must be re-verified to ensure they satisfy the unilateral policy boundary matrix and business constraints. If not, they must be adjusted or discarded to ensure that evolution always occurs within the feasible policy and business space. Specifically, based on the parent schemes, schemes randomly paired from the parent set... and Generate offspring and ,Right now: , in, As a crossover factor, the generated offspring must satisfy the constraints of the lower-level structure in the two-level optimization structure. If the generated offspring cannot be constrained, it should be discarded and regenerated. Specifically, for the parent scheme... Add a Gaussian perturbation to each decision variable to generate a mutation scheme. ,Right now: , in, For variable asynchronous length, It follows a standard normal distribution, and after mutation, it needs to be truncated to the feasible region of the decision variable, i.e.: like Then let ;like Then let ; like Then let ;like Then let ; like Then let ;like Then let ; like Then let ;like Then let .

[0050] Furthermore, the parent population and the newly generated offspring population through crossover and mutation are merged to form a larger temporary population. This merged population undergoes a new non-dominated ranking and crowding calculation. Then, based on the ranking rank and crowding, N optimal schemes, the same number as the initial population, are selected to form the next generation population. This process of population generation continues until a preset iteration termination condition is met: when evolution reaches a preset maximum number of generations, or when the change in the first priority rank across multiple generations is minimal, iteration stops. The set of cross-border electricity trading schemes with the highest priority rank in the final generation population is taken as the Pareto front. Specifically, based on the processes of selection, mutation, and crossover, the N legal schemes generated through crossover and mutation constitute the offspring population. The offspring population and the t-th generation parent population then merged into a single population. Among them, the newly formed merged population Repeat the non-dominated sorting and crowding calculation process, and select according to "rank priority + crowding priority". The plan consists of several parts. Generation population Based on continuous population updates and iterations, when the number of iterations... Reaching the preset threshold Or the optimal rank of a population for five consecutive generations. The variance of the crowding level, i.e.: When the iteration reaches convergence and stability, it terminates. Specifically, after the iteration terminates, the final population... The first level This is the Pareto optimal frontier, i.e.: , Among them, each of the cutting-edge solutions Each corresponds to a set of feasible trading plans. Both satisfy the condition that "it is impossible to increase the target value of the other party without decreasing the target value of either party".

[0051] 204. Conduct feasibility and Pareto optimality verifications on each cross-border power trading scheme to be verified, and take the verified cross-border power trading scheme as the Pareto optimal cross-border power trading scheme.

[0052] Accordingly, step 204 of the embodiment specifically includes: for each cross-border power trading scheme to be verified, verifying whether the cross-border power trading scheme to be verified satisfies the unilateral policy boundary matrix and business constraints, and obtaining the feasibility verification result of the cross-border power trading scheme to be verified; for each decision variable in the cross-border power trading scheme to be verified, adjusting the decision variable to improve the unilateral interest, obtaining the adjusted cross-border power trading scheme, and determining whether the adjusted cross-border power trading scheme satisfies the reduction of the other party's interest, and obtaining the Pareto optimality verification result of the cross-border power trading scheme to be verified; if both the feasibility verification result and the Pareto optimality verification result are satisfied, then the cross-border power trading scheme to be verified is taken as the Pareto optimal cross-border power trading scheme.

[0053] An example, the cross-border power trading scheme to be verified, is as follows: , This includes verifying whether the constraints are met, namely: , Based on the decision variables that satisfy the constraints, calculate the objective function, i.e.: , in, This indicates the seller's actual profit after deducting the 8% value-added tax. This indicates that the seller's total electricity sales volume is 6000 megawatt-hours. This indicates that long-term contracts account for 0.6%. This represents the buyer's total cost, including 8% VAT. This indicates that the buyer's total electricity imports amounted to 6000 megawatt-hours. This indicates that the spot market accounts for 0.4%. Based on the calculation results of the objective function, Pareto optimality is verified.

[0054] Specifically, based on the calculation results, Pareto optimality is verified from two aspects: increasing the seller's revenue and reducing the buyer's cost. Among them, increasing the seller's revenue ( ),Right now: Seller's after-tax income: , Seller's after-tax income growth rate: , Buyer's total cost including tax: , Buyer's total cost including tax increase: , Buyer's after-tax unit cost: , Specifically, it increases the seller's profits, resulting in a higher after-tax income compared to before. However, this increased the buyer's total cost including tax compared to before. And this increases the buyer's after-tax unit cost to It has exceeded This means that importing electricity from the seller no longer has a price advantage, and the solution is not the optimal one.

[0055] Among them, reducing the buyer's costs ( ),Right now: Buyer's cost including tax: , Buyer's cost savings including tax: , Seller's after-tax income: , The decrease in the seller's after-tax income: , Seller's after-tax unit price: , Specifically, it reduces the buyer's costs, lowering the buyer's cost compared to the previous cost including tax. However, this directly harms the seller's after-tax income. And make the seller's after-tax unit price lower than This results in the seller's profit margin being far below the profit threshold, meaning that exporting electricity to the buyer can no longer meet the seller's acceptable profit requirements, and the solution is not optimal.

[0056] Based on the verification process, it is proven that the solution is a Pareto optimal solution, and the scheme is a Pareto optimal cross-border electricity trading scheme.

[0057] This application provides a method for generating cross-border power trading schemes based on policy flexibility boundaries. First, for each party involved in the cross-border power transaction, the policy instruments for cross-border power trading are obtained. Based on the Hude model, these policy instruments are decomposed into authority instruments and wealth instruments, and the policy clauses within these instruments are transformed into parameter ranges corresponding to the authority and wealth instruments. Second, based on the authority instruments and their corresponding parameter ranges, and the wealth instruments and their corresponding parameter ranges, a unilateral policy boundary matrix is ​​constructed. This unilateral policy boundary matrix is ​​used to characterize the constraints of the feasible region of decision variables. Third, based on the interests of both parties in the cross-border power transaction, a bilateral multi-objective optimization function set is constructed. Based on the unilateral policy boundary matrix and business constraints, a multi-objective optimization algorithm is used to collaboratively optimize the bilateral multi-objective optimization function set to obtain a Pareto front. The Pareto front contains multiple cross-border power trading schemes to be verified. Finally, the feasibility and Pareto optimality of each of the unverified cross-border power trading schemes are verified, and the verified scheme is taken as the Pareto optimal cross-border power trading scheme. Compared with existing technologies, the embodiments of this application deconstruct policy terms using the Hude model to construct a unilateral policy boundary matrix, which is the elastic range that can participate in the calculation. This achieves the quantification of ambiguous policy terms and ensures that the elastic range fully conforms to the actual implementation of the policy, thereby improving the feasibility of the optimal trading scheme. Furthermore, by using the concept of Pareto optimality, the fairness of the generated cross-border power trading scheme is ensured, making the scheme more acceptable to both parties to the transaction and improving the transaction completion rate.

[0058] Furthermore, as a response to the above Figure 1 The implementation of the method shown in this application provides a cross-border power trading scheme generation system based on policy flexibility boundaries, such as... Figure 3 As shown, the system includes: Policy tool deconstruction module 31, unilateral policy boundary matrix construction module 32, Pareto frontier generation module 33, Pareto optimal cross-border power trading scheme generation module 34; The policy tool deconstruction module 31 is used to obtain the policy tools for cross-border power transactions for each party involved in the cross-border power transaction, and to decompose the policy tools into authoritative tools and wealth tools based on the Hud model, and to convert the policy terms in the policy tools into parameter ranges corresponding to the authoritative tools and the wealth tools. The unilateral policy boundary matrix construction module 32 is used to construct a unilateral policy boundary matrix based on the authoritative tool and its corresponding parameter range, the wealth tool and its corresponding parameter range, wherein the unilateral policy boundary matrix is ​​used to characterize the constraints of the feasible domain of the decision variables; The Pareto front generation module 33 is used to construct a bilateral multi-objective optimization function group based on the interests of both parties in a cross-border power transaction, and to perform collaborative optimization of the bilateral multi-objective optimization function group using a multi-objective optimization algorithm based on the unilateral policy boundary matrix and business constraints to obtain the Pareto front, wherein the Pareto front contains multiple cross-border power transaction schemes to be verified. The Pareto optimal cross-border power trading scheme generation module 34 is used to verify the feasibility and Pareto optimality of each of the cross-border power trading schemes to be verified, and to take the verified cross-border power trading scheme as the Pareto optimal cross-border power trading scheme.

[0059] In specific application scenarios, the policy tool deconstruction module is used for: Based on the Hud model, the authoritative instrument is deconstructed into policy elements representing market access rules, and the wealth instrument is deconstructed into policy elements representing network access fee ranges and value-added tax rates.

[0060] In specific application scenarios, the unilateral policy boundary matrix construction module is used for: The market access rules and their corresponding parameter ranges are quantified into constraints on the set of entities allowed to participate in cross-border power transactions; The range of grid access fees and the corresponding parameter ranges are quantified into a range constraint on the value of grid transmission cost; The value-added tax rate and its corresponding parameter range are quantified into a range constraint for the tax rate of electricity products. Based on the constraints of the set of entities allowed to participate in cross-border electricity transactions, the range of values ​​for grid transmission costs, and the range of values ​​for electricity commodity tax rates, a unilateral policy boundary matrix is ​​constructed.

[0061] In specific application scenarios, the Pareto front generation module includes a bilateral multi-objective optimization function group construction unit, used for: To understand the interests of both parties in a cross-border power transaction, including the seller's economic objectives, asset efficiency objectives, stability objectives, the buyer's economic objectives, energy security objectives, and green and low-carbon objectives. Based on the seller's economic objectives, the seller's asset efficiency objectives, the seller's stability objectives, the buyer's economic objectives, the buyer's energy security objectives, and the buyer's green and low-carbon objectives, a bilateral multi-objective optimization function set is constructed, expressed as the following formula. , in, Indicates the seller's economic objective. Indicates the unit price in cross-border electricity transactions. This indicates the total electricity sold. This indicates the VAT rate for cross-border electricity transactions. This indicates the seller's asset efficiency objective. Indicates the seller's stability objective. This indicates the amount of electricity sold by the seller under a long-term contract to the buyer. Indicates the buyer's economic objectives. This indicates the buyer's energy security objectives. This indicates the buyer's green and low-carbon goals. This indicates the amount of electricity sold by the seller to the buyer under a short-term contract.

[0062] In specific application scenarios, the Pareto front generation module includes a Pareto front generation unit, used for: Based on the unilateral policy boundary matrix and the business constraints, an initial population is randomly generated, wherein the initial population contains multiple initial cross-border power trading schemes. For each initial cross-border power trading scheme, calculate the bilateral multi-objective function value set corresponding to the initial cross-border power trading scheme, and based on each bilateral multi-objective function value set, determine the dominance relationship between any two initial cross-border power trading schemes, and based on the dominance relationship, perform non-dominance ranking on each initial cross-border power trading scheme to determine the priority level of each initial cross-border power trading scheme; Within the same priority level, calculate the congestion distance in the bilateral multi-objective function space for each initial cross-border power trading scheme; Based on a selection strategy that prioritizes priority and uses congestion distance as a secondary factor, parent cross-border power trading schemes are selected from the initial population. Cross-border power trading schemes are then subjected to cross-trading and mutation operations to generate offspring cross-border power trading schemes. The offspring cross-border power trading schemes satisfy the unilateral policy boundary matrix and the business constraints. All the parent generation cross-border power trading schemes and all the offspring generation cross-border power trading schemes are merged to obtain the next generation population; The priority level of cross-border power trading schemes in the next generation population is re-determined and congestion distance is calculated to select the parent cross-border power trading schemes of the next generation population. Crossover and mutation operations are then performed on the parent cross-border power trading schemes of the next generation population to obtain the offspring cross-border power trading schemes of the next generation population. All parent cross-border power trading schemes and all offspring cross-border power trading schemes of the next generation population are merged to obtain the next generation population. This process is repeated until a preset iteration termination condition is met. The set of cross-border power trading schemes with the highest priority level in the final generation population is taken as the Pareto front.

[0063] In specific application scenarios, the Pareto optimal cross-border electricity trading scheme generation module is used for: For each cross-border power trading scheme to be verified, verify whether the cross-border power trading scheme to be verified meets the unilateral policy boundary matrix and the business constraints, and obtain the feasibility verification result of the cross-border power trading scheme to be verified. For each decision variable in the cross-border power trading scheme to be verified, the decision variable is adjusted to increase the benefit of one party, resulting in an adjusted cross-border power trading scheme. It is then determined whether the adjusted cross-border power trading scheme satisfies the reduction of the benefit of the other party, thus obtaining the Pareto optimality verification result of the cross-border power trading scheme to be verified. If both the feasibility verification result and the Pareto optimality verification result are satisfied, then the cross-border power trading scheme to be verified is taken as the Pareto optimal cross-border power trading scheme.

[0064] In specific application scenarios, the business constraints include non-negative constraints on the amount of electricity traded, upper limits on the amount of imported electricity, constraints on the proportion of electricity under long-term contracts, constraints on the complementary proportion of electricity spot market, constraints on the trading price range, and constraints on the value-added tax rate range. This application provides a cross-border power trading scheme generation system based on policy flexibility boundaries. First, for each party involved in the cross-border power transaction, the policy instruments for cross-border power trading are obtained. Based on the Hude model, these policy instruments are decomposed into authority instruments and wealth instruments, and the policy clauses within these instruments are transformed into parameter ranges corresponding to the authority and wealth instruments. Second, based on the authority instruments and their corresponding parameter ranges, and the wealth instruments and their corresponding parameter ranges, a unilateral policy boundary matrix is ​​constructed. This unilateral policy boundary matrix is ​​used to characterize the constraints of the feasible region of decision variables. Third, based on the interests of both parties in the cross-border power transaction, a bilateral multi-objective optimization function set is constructed. Based on the unilateral policy boundary matrix and business constraints, a multi-objective optimization algorithm is used to collaboratively optimize the bilateral multi-objective optimization function set to obtain a Pareto front. The Pareto front contains multiple cross-border power trading schemes to be verified. Finally, the feasibility and Pareto optimality of each of the unverified cross-border power trading schemes are verified, and the verified scheme is taken as the Pareto optimal cross-border power trading scheme. Compared with existing technologies, the embodiments of this application deconstruct policy terms using the Hude model to construct a unilateral policy boundary matrix, which is the elastic range that can participate in the calculation. This achieves the quantification of ambiguous policy terms and ensures that the elastic range fully conforms to the actual implementation of the policy, thereby improving the feasibility of the optimal trading scheme. Furthermore, by using the concept of Pareto optimality, the fairness of the generated cross-border power trading scheme is ensured, making the scheme more acceptable to both parties to the transaction and improving the transaction completion rate.

[0065] According to one embodiment of this application, a storage medium is provided, the storage medium storing at least one executable instruction, which can execute the method for generating cross-border power trading schemes based on policy flexibility boundaries in any of the above method embodiments.

[0066] Based on this understanding, the technical solution of this application can be embodied in the form of a software product. The software product can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, or portable hard drive), and includes several instructions to cause a computer device (such as a personal computer, server, or network device) to execute the methods described in the various implementation scenarios of this application.

[0067] Figure 4 The diagram shows a structural schematic of a terminal according to one embodiment of the present application. The specific embodiments of the present application do not limit the specific implementation of the terminal.

[0068] like Figure 4As shown, the terminal may include: a processor 402, a communications interface 404, a memory 406, and a communications bus 408.

[0069] The processor 402, communication interface 404, and memory 406 communicate with each other via communication bus 408.

[0070] Communication interface 404 is used to communicate with other network elements such as clients or other servers.

[0071] The processor 402 is used to execute program 410, specifically to execute the relevant steps in the above-described embodiment of the method for generating cross-border power trading schemes based on policy flexibility boundaries.

[0072] Specifically, program 410 may include program code that includes computer operation instructions.

[0073] Processor 402 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application. The computer device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or they may be processors of different types, such as one or more CPUs and one or more ASICs.

[0074] Memory 406 is used to store program 410. Memory 406 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0075] Specifically, program 410 can be used to cause processor 402 to perform the following operations: For each party involved in cross-border power transactions, obtain the policy tools for cross-border power transactions, and based on the Hud model, decompose the policy tools into authoritative tools and wealth tools, and transform the policy terms in the policy tools into parameter ranges corresponding to the authoritative tools and the wealth tools; Based on the authoritative tool and its corresponding parameter range, and the wealth tool and its corresponding parameter range, a unilateral policy boundary matrix is ​​constructed, wherein the unilateral policy boundary matrix is ​​used to characterize the constraints of the feasible domain of decision variables. Based on the interests of both parties in cross-border power transactions, a bilateral multi-objective optimization function set is constructed. Based on the unilateral policy boundary matrix and business constraints, a multi-objective optimization algorithm is used to collaboratively optimize the bilateral multi-objective optimization function set to obtain the Pareto front. The Pareto front contains multiple cross-border power transaction schemes to be verified. Each of the proposed cross-border power trading schemes to be verified is tested for feasibility and Pareto optimality, and the verified cross-border power trading scheme is taken as the Pareto optimal cross-border power trading scheme.

[0076] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the physical device used in the aforementioned method for generating cross-border power trading schemes based on policy flexibility boundaries, supporting the operation of information processing programs and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software in the information processing physical device.

[0077] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0078] The methods and systems of this application may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of this application are not limited to the order specifically described above, unless otherwise specifically stated. Furthermore, in some embodiments, this application may also be implemented as a program recorded on a recording medium, the program including machine-readable instructions for implementing the methods according to this application. Thus, this application also covers recording media storing programs for performing the methods according to this application.

[0079] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing systems. They can be centralized on a single computing system or distributed across a network of multiple computing systems. Optionally, they can be implemented using program code executable by a computing system, thereby storing them in a storage system for execution by the computing system. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0080] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for generating cross-border power trading schemes based on policy flexibility boundaries, characterized in that, include: For each party involved in cross-border power transactions, obtain the policy tools for cross-border power transactions, and based on the Hud model, decompose the policy tools into authoritative tools and wealth tools, and transform the policy terms in the policy tools into parameter ranges corresponding to the authoritative tools and the wealth tools; Based on the authoritative tool and its corresponding parameter range, and the wealth tool and its corresponding parameter range, a unilateral policy boundary matrix is ​​constructed, wherein the unilateral policy boundary matrix is ​​used to characterize the constraints of the feasible domain of decision variables. Based on the interests of both parties in cross-border power transactions, a bilateral multi-objective optimization function set is constructed. Based on the unilateral policy boundary matrix and business constraints, a multi-objective optimization algorithm is used to collaboratively optimize the bilateral multi-objective optimization function set to obtain the Pareto front. The Pareto front contains multiple cross-border power transaction schemes to be verified. Each of the proposed cross-border power trading schemes to be verified is tested for feasibility and Pareto optimality, and the verified cross-border power trading scheme is taken as the Pareto optimal cross-border power trading scheme.

2. The method according to claim 1, characterized in that, The policy tools, based on the Hud model, are broken down into authority tools and wealth tools, including: Based on the Hud model, the authoritative instrument is deconstructed into policy elements representing market access rules, and the wealth instrument is deconstructed into policy elements representing network access fee ranges and value-added tax rates.

3. The method according to claim 2, characterized in that, The construction of a unilateral policy boundary matrix based on the authoritative tool and its corresponding parameter range, and the wealth tool and its corresponding parameter range, includes: The market access rules and their corresponding parameter ranges are quantified into constraints on the set of entities allowed to participate in cross-border power transactions; The range of grid access fees and the corresponding parameter ranges are quantified into a range constraint on the value of grid transmission cost; The value-added tax rate and its corresponding parameter range are quantified into a range constraint for the tax rate of electricity products. Based on the constraints of the set of entities allowed to participate in cross-border electricity transactions, the range of values ​​for grid transmission costs, and the range of values ​​for electricity commodity tax rates, a unilateral policy boundary matrix is ​​constructed.

4. The method according to claim 1, characterized in that, Based on the interests of both parties in cross-border power transactions, a bilateral multi-objective optimization function set is constructed, including: To understand the interests of both parties in a cross-border power transaction, including the seller's economic objectives, asset efficiency objectives, stability objectives, the buyer's economic objectives, energy security objectives, and green and low-carbon objectives. Based on the seller's economic objectives, the seller's asset efficiency objectives, the seller's stability objectives, the buyer's economic objectives, the buyer's energy security objectives, and the buyer's green and low-carbon objectives, a bilateral multi-objective optimization function set is constructed, expressed as the following formula. ， in, Indicates the seller's economic objective. Indicates the unit price in cross-border electricity transactions. This indicates the total electricity sold. This indicates the VAT rate for cross-border electricity transactions. This indicates the seller's asset efficiency objective. Indicates the seller's stability objective. This indicates the amount of electricity sold by the seller under a long-term contract to the buyer. Indicates the buyer's economic objectives. This indicates the buyer's energy security objectives. This indicates the buyer's green and low-carbon goals. This indicates the amount of electricity sold by the seller to the buyer under a short-term contract.

5. The method according to claim 1, characterized in that, Based on the unilateral policy boundary matrix and business constraints, a multi-objective optimization algorithm is used to collaboratively optimize the bilateral multi-objective optimization function set to obtain the Pareto front, including: Based on the unilateral policy boundary matrix and the business constraints, an initial population is randomly generated, wherein the initial population contains multiple initial cross-border power trading schemes. For each initial cross-border power trading scheme, calculate the bilateral multi-objective function value set corresponding to the initial cross-border power trading scheme, and based on each bilateral multi-objective function value set, determine the dominance relationship between any two initial cross-border power trading schemes, and based on the dominance relationship, perform non-dominance ranking on each initial cross-border power trading scheme to determine the priority level of each initial cross-border power trading scheme; Within the same priority level, calculate the congestion distance in the bilateral multi-objective function space for each initial cross-border power trading scheme; Based on a selection strategy that prioritizes priority and uses congestion distance as a secondary factor, parent cross-border power trading schemes are selected from the initial population. Cross-border power trading schemes are then subjected to cross-trading and mutation operations to generate offspring cross-border power trading schemes. The offspring cross-border power trading schemes satisfy the unilateral policy boundary matrix and the business constraints. All the parent generation cross-border power trading schemes and all the offspring generation cross-border power trading schemes are merged to obtain the next generation population; The priority level of cross-border power trading schemes in the next generation population is re-determined and congestion distance is calculated to select the parent cross-border power trading schemes of the next generation population. Crossover and mutation operations are then performed on the parent cross-border power trading schemes of the next generation population to obtain the offspring cross-border power trading schemes of the next generation population. All parent cross-border power trading schemes and all offspring cross-border power trading schemes of the next generation population are merged to obtain the next generation population. This process is repeated until a preset iteration termination condition is met. The set of cross-border power trading schemes with the highest priority level in the final generation population is taken as the Pareto front.

6. The method according to claim 1, characterized in that, The process of verifying the feasibility and Pareto optimality of each of the proposed cross-border power trading schemes, and designating the verified schemes as Pareto optimal schemes, includes: For each cross-border power trading scheme to be verified, verify whether the cross-border power trading scheme to be verified meets the unilateral policy boundary matrix and the business constraints, and obtain the feasibility verification result of the cross-border power trading scheme to be verified. For each decision variable in the cross-border power trading scheme to be verified, the decision variable is adjusted to increase the benefit of one party, resulting in an adjusted cross-border power trading scheme. It is then determined whether the adjusted cross-border power trading scheme satisfies the reduction of the benefit of the other party, thus obtaining the Pareto optimality verification result of the cross-border power trading scheme to be verified. If both the feasibility verification result and the Pareto optimality verification result are satisfied, then the cross-border power trading scheme to be verified is taken as the Pareto optimal cross-border power trading scheme.

7. The method according to claim 1, characterized in that, The business constraints include non-negative constraints on the amount of electricity traded, upper limits on the amount of imported electricity, constraints on the proportion of electricity under long-term contracts, constraints on the complementary proportion of electricity spot market, constraints on the trading price range, and constraints on the value-added tax rate range.

8. A cross-border power trading scheme generation system based on policy flexibility boundaries, characterized in that, include: The policy tool deconstruction module is used to obtain the policy tools for cross-border power transactions for each party involved in the transaction. Based on the Hud model, the policy tools are decomposed into authoritative tools and wealth tools, and the policy clauses in the policy tools are transformed into parameter ranges corresponding to the authoritative tools and the wealth tools. The unilateral policy boundary matrix construction module is used to construct a unilateral policy boundary matrix based on the authoritative tool and its corresponding parameter range, the wealth tool and its corresponding parameter range, wherein the unilateral policy boundary matrix is ​​used to characterize the constraints of the feasible domain of decision variables; The Pareto front generation module is used to construct a bilateral multi-objective optimization function set based on the interests of both parties in a cross-border power transaction, and to perform collaborative optimization of the bilateral multi-objective optimization function set using a multi-objective optimization algorithm based on the unilateral policy boundary matrix and business constraints to obtain the Pareto front. The Pareto front contains multiple cross-border power transaction schemes to be verified. The Pareto optimal cross-border power trading scheme generation module is used to verify the feasibility and Pareto optimality of each of the cross-border power trading schemes to be verified, and to take the verified cross-border power trading schemes as Pareto optimal cross-border power trading schemes.

9. A storage medium storing at least one executable instruction, characterized in that, The executable instructions cause the processor to perform the operations corresponding to the method for generating cross-border power trading schemes based on policy flexibility boundaries as described in any one of claims 1-7.

10. A terminal, comprising: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, characterized in that the executable instruction causes the processor to perform the operation corresponding to the method for generating cross-border power trading schemes based on policy flexibility boundaries as described in any one of claims 1-7.

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