Method and system for identifying market power of boring power generation enterprise based on game theory

Abstract

The invention, which relates to the technical field of the power market, discloses a method and system for identifying the market power of an boring power generation enterprise based on a game theory, comprising the following steps: collecting current power market data, constructing a power generation enterprise bidding networking strategy model, and making an actual quotation curve; according to the current electricity market data, constructing an abuse market power behavior identification index system; based on the actual quotation curve and the abuse market power behavior identification index system, calculating a reference quotation of the power market subject, and performing a behavior test and a price influence test; and determining whether the power generation enterprise market power level is in a normal range based on the behavior test and the price influence test. According to the method, behaviors and strategies of boring power generation enterprises in the market can be simulated and analyzed more accurately through the game theory model, a behavior test and a price influence test are fused, a supervisor is helped to supervise the market power condition of each power generation enterprise by establishing an evaluation system in the abuse market, and fair competition of the market is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of power market, and in particular to a method and system for identifying the market power of oligopolistic power generation enterprises based on game theory. Background Art

[0002] In today's world, the transformation of energy structure and the deepening reform of the power market have become a global trend. The market's competition mechanism, trading rules and regulatory system are facing major challenges and opportunities. Especially in the power market, as key participants in the market, the rational use of market power and effective supervision of power generation companies are particularly critical.

[0004] Abuse of market power refers to market participants taking advantage of their dominant position in the market to influence market prices and transactions through improper means, thereby obtaining excess profits. In the electricity market, power generation companies may influence electricity transaction prices and market supply and demand balance by manipulating bids, restricting supply, and other means, thereby damaging the interests of other market participants and consumers.

[0005] Although existing studies have focused on the issue of market power in the electricity market, existing methods mostly rely on qualitative analysis and empirical judgment, lacking scientific, systematic, and quantitative identification methods. In addition, with the surge in the amount of electricity market data, traditional analysis methods are unable to cope with the complexity and variability in the big data environment.

[0006] As a theoretical tool for studying the interactive behaviors between individuals with conflicting interests, game theory has been widely used in the study of the power market. By constructing a game model between power generation companies, we can simulate and analyze the strategic choices and behavioral responses of market participants under different market mechanisms, providing theoretical support for market supervision and policy making.

[0007] In view of the particularity of the power market and the complexity of market power abuse, it is urgent to develop a scientific and efficient market power identification method to achieve real-time monitoring and early warning of the market behavior of power generation companies. At the same time, the method should be able to adapt to the big data environment of the power market and have good generalization ability and practicality. Summary of the invention

[0008] In view of the above-mentioned problems, the present invention is proposed.

[0009] Therefore, the technical problem solved by the present invention is to effectively identify and supervise the abuse of market power by power generation enterprises in the power market by constructing a bidding strategy model for power generation enterprises and an identification index system for abuse of market power.

[0010] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for identifying the market power of oligopolistic power generation enterprises based on game theory, comprising:

[0011] As a preferred solution of the method for identifying market power of oligopolistic power generation enterprises based on game theory of the present invention, it includes collecting current electricity market data, building a bidding strategy model for power generation enterprises, and making an actual quotation curve; building an abuse of market power behavior identification index system based on current electricity market data; calculating the reference quotations of power market entities based on the actual quotation curve and the abuse of market power behavior identification index system, and conducting behavior tests and price impact tests; and judging whether the market power level of the power generation enterprise is within a normal range based on the behavior test and the price impact test.

[0012] As a preferred solution of the method for identifying the market power of oligopolistic power generation enterprises based on game theory of the present invention, the formula for constructing the power generation enterprise bidding strategy model is as follows:

[0013] π i (p i ,p j )=(p i -c)D i (p i ,p j )

[0014] Among them, π i (p i ,p j ) represents the profit of power generation enterprises, p i represents the market price of power generation enterprise i, p j represents the market price of its competitor j, D i (p i ,p j ) represents the market demand function, c represents the marginal cost of each power generation enterprise to produce electricity commodities; the market demand function D i (p i ,p j ) is as follows:

[0015]

[0016] Among them, D i (p i ,p j ) represents the market demand function, p i represents the market price of power generation enterprise i, p j represents the market price of its competitor j, n represents the number of power generation companies, p n represents the market quotation of power generation enterprise n, i represents power generation enterprise i, and j represents power generation enterprise j; the formula for maximizing the profit of power generation enterprise i is as follows:

[0017]

[0018] Among them, π i represents the maximum profit of power generation enterprise i, p i represents the market quotation of power generation enterprise i, c represents the marginal cost of each power generation enterprise to produce electricity commodities, D i (p i ) represents the market demand function.

[0019] As a preferred solution of the market power identification method of oligopolistic power generation enterprises based on game theory of the present invention, the actual bidding curve is prepared by calculating the actual bidding according to the maximized profit of the power generation enterprises, and drawing the actual bidding curve. The calculation formula is as follows:

[0020] Q=D i (p i ,p j )*π i

[0021] Among them, Q represents the actual quoted value, D i (p i ,p j ) represents the market demand function, π i represents the maximum profit of power generation enterprise i.

[0022] As a preferred solution of the market power identification method of oligopolistic power generation enterprises based on game theory of the present invention, the indicators in the market power abuse identification index system include the power generation enterprise quotation data, the declared electricity share of each section, the transaction electricity share of each section, the declaration success ratio of each section, whether it is a high price in this section, and the number of high quotations; the calculation formula of the power generation enterprise quotation data is as follows:

[0023]

[0024] Among them, x 1i Indicates the bid data of power generation enterprises; They represent the declared electricity price, declared electricity quantity and traded electricity quantity of the jth segment of the i-th power generation enterprise respectively; i represents the number of power generation enterprises, and n represents the number of quotation segments; the calculation formula for the declared electricity quantity share of each segment is as follows:

[0025] x 2i =(x 2i1 ,x 2i2 ,…,x 2in )

[0026]

[0027] Among them, x 2i Indicates that x 2ij represents the electricity share reported by the i-th enterprise in the j-th period, It represents the declared electricity price of the jth segment of the i-th power generation enterprise; the calculation formula of the transaction electricity share of each segment is as follows:

[0028] x 3i =(x 3i1 ,x 3i2 ,…,x 3in )

[0029]

[0030] Among them, x 3ij represents the transaction electricity share of the i-th enterprise in the j-th period, It represents the transaction volume of the i-th power generation enterprise in the j-th segment; the calculation formula for the successful application ratio of each segment is as follows:

[0031] x 4i =(x 4i1 ,x 4i2 ,…,x 4in )

[0032]

[0033] Among them, x 4ij It represents the success rate of the j-th segment declaration of the i-th enterprise; the calculation formula for judging whether it is the high price in this segment is as follows:

[0034] x 5i =(x 5i1 ,x 5i2 ,…,x 5in )

[0035]

[0036] Among them, x 5ij Indicates whether the i-th enterprise's quotation in the j-th segment is the highest price in this segment;

[0037] The calculation formula for the number of high quotations is as follows:

[0038]

[0039] Among them, x 6ij It indicates the number of high bids made by the i-th power generation enterprise in the j-th period.

[0040] As a preferred solution of the market power identification method of oligopolistic power generation enterprises based on game theory of the present invention, wherein: calculating the reference quotation of the power market subject includes calculating the quotation deviation, quotation volatility and quotation limit rate;

[0041]

[0042] As a preferred solution of the method for identifying market power of oligopolistic power generation enterprises based on game theory of the present invention, the behavioral test includes comparing the reference quotations of power market entities, including the calculated quotation deviation, quotation volatility and quotation limit rate, with the thresholds of various indicators in the power market to determine whether there are any abnormal market power situations.

[0043] As a preferred solution of the market power identification method of oligopolistic power generation enterprises based on game theory of the present invention, the price impact test includes comparing the market clearing price level of the actual quotation and the market clearing price level formed after replacing the quotation of the tested power generation entity with the reference quotation, and performing threshold determination; the price impact test factor is defined as:

[0044]

[0045] Among them, β price impact test factor, x represents the market price when the dispatching center uses the original quotation of the unit for clearing, called the original market price, y represents the market price when the dispatching center uses the benchmark quotation instead of the original quotation for clearing, called the alternative market price.

[0046] Another object of the present invention is to provide a market power identification system for oligopolistic power generation enterprises based on game theory, including: a model building module, which is used to collect current electricity market data, build a power generation enterprise bidding strategy model, and produce an actual quotation curve; an indicator system building module, which is used to build an abuse of market power behavior identification indicator system based on current electricity market data; a testing module, which is used to calculate the reference quotation of electricity market entities based on the actual quotation curve and the abuse of market power behavior identification indicator system, and conduct behavior tests and price impact tests; a judgment module, which is used to judge whether the market power level of the power generation enterprise is within a normal range based on the behavior test and the price impact test.

[0047] A computer device includes a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, the steps of the method for identifying the market power of oligopolistic power-generating enterprises based on game theory are implemented as described above.

[0048] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of the method for identifying the market power of oligopolistic power-generating enterprises based on game theory are implemented as described above.

[0049] Beneficial effects of the present invention: Through the game theory model, the behavior and strategies of oligopolistic power generation companies in the market can be more accurately simulated and analyzed, thereby identifying and quantifying market power, helping companies to better understand market structure and competition dynamics and provide support for decision-making. By integrating behavioral testing with price impact testing, companies can use this patented method to evaluate different market strategies, such as pricing strategies, production decisions, etc., to maximize their own market power and profits. For the first time, it is proposed to help regulators monitor the market power of various power generation companies by establishing an evaluation system for market abuse. For policymakers, this patented method provides a tool for monitoring and analyzing market power, which helps to formulate more effective market regulatory policies and promote fair competition in the market. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0051] Figure 1 This is a schematic diagram of the structure of a terminal in the first embodiment of the present invention;

[0052] Figure 2 It is a schematic diagram of a flow chart in the first embodiment of the present invention;

[0053] Figure 3 FIG. 4 is a schematic diagram of the structure of a computer device in a third embodiment of the present invention.

[0054] Figure 4 This is the actual quotation curve of power generation enterprises.

[0055] Figure 5 Schematic diagram of the deviation between the actual bidding curve of power generation enterprises and the reference bidding curve. DETAILED DESCRIPTION

[0056] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0057] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0058] Example 1

[0059] Reference Figure 1 , which is an embodiment of the present invention, provides a method for identifying the market power of oligopolistic power-generating enterprises based on game theory.

[0060] First, the market power identification method of oligopolistic power generation enterprises based on game theory provided in this application can be applied to Figure 1 In the terminal shown. Figure 1 As shown, the terminal may include one or two ( Figure 1 Only one is shown in the figure) processor and memory for storing data, wherein the processor may include but is not limited to a processing system such as a microprocessor MCU or a programmable logic device FPGA. The above terminal may also include a transmission device and an input and output device for communication functions. It can be understood by ordinary technicians in this field that Figure 1 The structure shown is only for illustration and does not limit the structure of the above terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0061] The memory can be used to store computer programs, such as the computer program corresponding to the market power identification method of oligopoly power generation enterprises based on game theory in this embodiment. The processor executes various functional applications and data processing by running the computer program stored in the memory, that is, implementing the above method. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories can be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0062] The transmission device is used to receive or send data via a network. The above network includes a wireless network provided by a communication provider of the terminal. In one example, the transmission device includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0063] like Figure 2 As shown, the embodiment of the present invention provides a method for identifying the market power of oligopolistic electricity-generating enterprises based on game theory, and the method is applied to Figure 1 The terminal in is used as an example to illustrate, including the following steps:

[0064] S1: Collect current electricity market data, build a bidding strategy model for power generation companies, and produce actual quotation curves.

[0065] Specifically, the data required for the current electricity market are collected, including: the market quotations of various power generation companies and the marginal costs of each power generation company in producing electricity commodities.

[0066] The formula for constructing the grid-connected bidding strategy model for power generation enterprises is as follows:

[0067] π i (p i ,p j )=(p i -c)D i (p i ,p j )

[0068] Among them, π i (p i ,p j ) represents the profit of power generation enterprises, p i represents the market price of power generation enterprise i, p j represents the market price of its competitor j, D i (p i ,p j ) represents the market demand function, c represents the marginal cost of each power generation enterprise to produce electricity commodities;

[0069] Market demand function D i (p i ,p j ) is as follows:

[0070]

[0071] Among them, D i(p i ,p j ) represents the market demand function, p i represents the market price of power generation enterprise i, p j represents the market price of its competitor j, n represents the total number of power generation companies, p n represents the market quotation of the nth enterprise, i represents power generation enterprise i, and j represents competitor power generation enterprise j;

[0072] The formula for maximizing profit of power generation enterprise i is as follows:

[0073]

[0074] Among them, π i represents the maximum profit of power generation enterprise i, p i represents the market quotation of power generation enterprise i, c represents the marginal cost of each power generation enterprise to produce electricity commodities, D i (p i ) represents the profit demand function;

[0075] The market quotations of each power generation enterprise and the marginal cost of each power generation enterprise in producing electricity commodities are input into the power generation enterprise bidding strategy model to obtain the maximum profit of each power generation enterprise.

[0076] Furthermore, the steps of making the actual bid curve are as follows: the actual bid is calculated based on the maximum profit of the power generation enterprise, and the actual bid curve is drawn. The calculation formula is as follows:

[0077] Q=D i (p i ,p j )*π i

[0078] Among them, Q represents the actual quoted value, D i (p i ,p j ) represents the market demand function, π i represents the maximum profit of power generation enterprise i.

[0079] It should be noted that the input of the power generation enterprise bidding strategy model is the market quotation of each power generation enterprise and the marginal cost of each power generation enterprise in producing electricity commodities; the output is the maximized profit of each power generation enterprise.

[0080] S2: Based on current electricity market data, establish an indicator system for identifying abuse of market power.

[0081] Collect relevant data on the actual situation of the electricity market, including: the declared electricity price, declared electricity volume, transaction electricity volume, declared electricity volume share, transaction electricity volume share and the number of high bids for each enterprise in each time period.

[0082] Based on the collected relevant data, an indicator system for identifying abuse of market power is constructed. The indicators in the indicator system for identifying abuse of market power include the bid data of power generation enterprises, the share of electricity bid in each section, the share of electricity sold in each section, the success rate of bids in each section, whether the price is high in this section, and the number of high bids;

[0083] The calculation formula for the power generation enterprise quotation data is as follows:

[0084]

[0085] Among them, x 1i Indicates the bid data of power generation enterprises; They represent the electricity price, electricity quantity and transaction quantity of the i-th power generation enterprise in the j-th period respectively; i represents the number of power generation enterprises, and n represents the number of quotation periods;

[0086] The calculation formula for the declared electricity share of each section is as follows:

[0087] x 2i =(x 2i1 ,x 2i2 ,…,x 2in )

[0088]

[0089] Among them, x 2i Indicates the declared electricity share, x 2ij represents the electricity share reported by the i-th enterprise in the j-th period, represents the declared electricity price of the i-th power generation enterprise in the j-th period;

[0090] The calculation formula for the transaction power share of each segment is as follows:

[0091] x 3i =(x 3i1 ,x 3i2 ,…,x 3in ),

[0092]

[0093] Among them, x 3ij represents the transaction electricity share of the i-th enterprise in the j-th period, It represents the transaction volume of the i-th power generation enterprise in the j-th period;

[0094] The calculation formula for the success rate of each stage of application is as follows:

[0095] x 4i =(x 4i1 ,x 4i2 ,…,x 4in )

[0096]

[0097] Among them, x 4i Indicates the success rate of each segment, x 4ij represents the success rate of the j-th stage declaration of the i-th enterprise, They represent the declared electricity and traded electricity of the i-th power generation enterprise in the j-th period respectively;

[0098] The calculation formula for determining whether it is the high price in this paragraph is as follows:

[0099] x 5i =(x 5i1 ,x 5i2 ,…,x 5in )

[0100]

[0101] Among them, x 5i Indicates whether it is a high price indicator for this section, x 5ij Indicates whether the i-th enterprise's quotation in the j-th segment is the highest price in this segment;

[0102] The calculation formula for the number of high quotations is as follows:

[0103]

[0104] Among them, x 6i Indicates the number of high bids, x 6ij represents the number of high bids of the i-th power generation enterprise in the j-th period, and n represents the total number of bids in the period

[0105] Based on the indicators in the above-mentioned index system for identifying abuse of market power, the steps for constructing an index system for identifying abuse of market power are as follows: construct an index system for identifying abuse of market power based on the behavior of power market entities, their subject-related characteristics and the current status of the power market. The system includes the above-mentioned six indicators. Through the system, it is preliminarily determined whether the entity has abused its market power. If so, policy intervention and timely adjustment are carried out. If the value is normal, the next step of behavior testing and price impact testing is carried out.

[0106] S3: Based on the actual quotation curve and the indicator system for identifying abuse of market power, the reference quotations of electricity market players are calculated, and behavioral tests and price impact tests are conducted.

[0107] Specifically, the behavioral test mainly detects whether the bidding behavior of the generator set is normal. By comparing the actual bidding curve of the unit with the characteristics of the reference bidding curve, it determines whether the relevant evaluation indicators exceed the threshold.

[0108] Furthermore, the calculation of the reference quotations of the power market players includes the calculation of the quotations deviation, quotations volatility and quotations reaching the limit rate;

[0109] The quotation deviation is (actual quotation curve area - reference quotation curve area) / reference quotation curve area;

[0110] The quotation volatility is (highest quotation - lowest quotation) / lowest quotation;

[0111] The quotation limit rate is (quotation upper limit - highest quotation) / quotation upper limit.

[0112] S4: Determine whether the market power level of power generation enterprises is within the normal range based on behavioral tests and price impact tests.

[0113] Specific price impact testing involves calculating the original market price against the surrogate market price to determine the impact of product prices on consumer purchasing behavior.

[0114] Furthermore, the market-clearing price level of the actual bid (called the actual result) and the market-clearing price level formed after replacing the bid of the tested power generation entity with the reference bid (called the benchmark result) are compared to perform a threshold determination.

[0115] Furthermore, the price impact test factor is defined as:

[0116]

[0117] Among them, β price impact test factor, x represents the market price when the dispatching center uses the original quotation of the unit for clearing, called the original market price, y represents the market price when the dispatching center uses the benchmark quotation instead of the original quotation for clearing, called the alternative market price.

[0118] Furthermore, based on the price impact test factor, the result is compared with the benchmark result. If it does not exceed the threshold, it means that the market power is within the normal range. If the comparison result exceeds the threshold, it means that the market power is abnormal and market power control measures are required.

[0119] Example 2

[0120] Reference Figure 1-2 , which is an embodiment of the present invention, provides a market power identification system for oligopolistic electricity-generating enterprises based on game theory, including:

[0121] The model building module is used to collect current power market data, build a power generation enterprise bidding strategy model, and produce actual quotation curves;

[0122] An indicator system construction module is used to construct an indicator system for identifying market power abuse behaviors based on current electricity market data;

[0123] The test module is used to calculate the reference quotes of power market players based on the actual quote curve and the indicator system for identifying abuse of market power, and to conduct behavior tests and price impact tests;

[0124] The determination module is used to determine whether the market power level of the power generation enterprise is within a normal range based on the behavior test and the price impact test.

[0125] For the specific definition of the market power identification system of oligopolistic power-generating enterprises based on game theory, please refer to the definition of the market power identification method of oligopolistic power-generating enterprises based on game theory in the above text, which will not be repeated here. Each module in the above-mentioned market power identification system of oligopolistic power-generating enterprises based on game theory can be implemented in whole or in part through software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device 0 in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0126] Example 3

[0127] Reference Figure 3 , which is the third embodiment of the present invention. Based on the first two embodiments, the embodiment of the present invention provides a computer device, which may be a server, and its internal structure diagram may be as shown in FIG. Figure 3 As shown. The computer device includes a processor, a memory and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium.

[0128] The database of the computer device is used to store action detection data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in any of the above-mentioned sparse tensor operation acceleration method embodiments are implemented.

[0129] Those skilled in the art will understand that Figure 3The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0130] In one embodiment, an embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in any of the above-mentioned sparse tensor operation acceleration method embodiments are implemented.

[0131] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database 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 may include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0132] Example 4

[0133] As an embodiment of the present invention, a satellite positioning method with multi-frequency and multi-system and anti-electromagnetic interference is provided. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation.

[0134] Specifically, five power generation companies were selected for market identification. The market quotations of the five companies and the marginal cost of electricity produced by each power generation company were collected and input into the power generation company bidding strategy model. The actual quotations were as shown in the following table, and the actual quotation curve was generated. See the attached manual for details. Figure 4 .

[0135] Table 1 Actual Quotation

[0136]

[0137]

[0138] Furthermore, the collected data were further calculated using the market power abuse behavior identification index system. Taking the quotations of each company in the first time period as an example, the results are shown in Table 2.

[0139] Table 2 Quotations of various companies in the first period

[0140]

[0141] Furthermore, after calculation and threshold comparison, power generation enterprises 3 and 4 have abused their market power and have made high bids, and then the next behavior test is carried out on each power generation enterprise. The calculated bid deviation, bid volatility and bid limit rate of each power generation enterprise and the threshold comparison are shown in Table 3, as well as the reference bid curve of the power market players, as shown in the Appendix of the Instructions. Figure 5 shown.

[0142] Table 3 Comparison of quotation deviation, quotation volatility, quotation limit rate and threshold value

[0143]

[0144]

[0145] Furthermore, according to the data in Table 3, it is found that power generation companies 4 and 5 have exceeded the threshold, and the market power of the two power generation companies is abnormal and requires policy intervention and timely adjustment.

[0146] Furthermore, the market clearing price levels of actual quotations of various enterprises and the market clearing price levels formed after replacing the quotations of the tested power generation entities with the reference quotations are collected, the price impact factors are calculated, and the price impact test is conducted. The results are shown in Table 4.

[0147] Table 4 Price Impact Table

[0148]

[0149] From the price impact factor calculation data in the above table, it can be concluded that power generation companies 3 and 4 have abnormal market power and need to carry out market power control.

[0150] Based on the results of the overall system of the present invention, it is obtained that power generation enterprise 3, power generation enterprise 4, and power generation enterprise 5 have abnormal market power and must be subject to market power control.

[0151] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for identifying the market power of oligopolistic electricity-generating enterprises based on game theory, characterized in that: include: Collect current power market data, build a bidding strategy model for power generation companies, and create actual quotation curves; Based on current electricity market data, a system of indicators for identifying market power abuse is established; Based on the actual quotation curve and the indicator system for identifying abuse of market power, the reference quotation of power market players is calculated, and behavioral tests and price impact tests are conducted; Based on behavioral tests and price impact tests, determine whether the market power level of power generation enterprises is within the normal range.

2. The method for identifying the market power of oligopolistic electricity-generating enterprises based on game theory as claimed in claim 1, characterized in that: The formula for constructing the power generation enterprise bidding strategy model is as follows: π i ( p i ,p j )=(p i -c)D i ( p i ,p j ) Among them, π i (p i ,p j ) represents the profit of power generation enterprises, p i represents the market price of power generation enterprise i, p j represents the market price of its competitor j, D i (p i ,p j ) represents the market demand function, c represents the marginal cost of each power generation enterprise to produce electricity commodities; Market demand function D i (p i ,p j ) is as follows: Among them, D i (p i ,p j ) represents the market demand function, p i represents the market price of power generation enterprise i, p j represents the market price of its competitor j, n represents the number of power generation companies, p n represents the market quotation of power generation enterprise n, i represents power generation enterprise i, and j represents power generation enterprise j; The formula for maximizing profit of power generation enterprise i is as follows: Among them, π i represents the maximum profit of power generation enterprise i, p i represents the market quotation of power generation enterprise i, c represents the marginal cost of each power generation enterprise to produce electricity commodities, D i (p i ) represents the market demand function.

3. The method for identifying the market power of oligopolistic electricity-generating enterprises based on game theory as claimed in claim 2, characterized in that: The actual bid curve is prepared by calculating the actual bid according to the maximum profit of the power generation enterprise, and drawing the actual bid curve. The calculation formula is as follows: Q=D i ( p i ,p j )*π i Among them, Q represents the actual quoted value, D i (p i ,p j ) represents the market demand function, π i represents the maximum profit of power generation enterprise i.

4. The method for identifying market power of oligopolistic electricity-generating enterprises based on game theory as claimed in claim 3, characterized in that: The indicators in the index system for identifying abuse of market power include the bid data of power generation enterprises, the share of electricity declared in each section, the share of electricity sold in each section, the success rate of declaration in each section, whether it is a high price in this section, and the number of high bids; The calculation formula for the power generation enterprise quotation data is as follows: Among them, x 1i Indicates the bid data of power generation enterprises; They represent the electricity price, electricity quantity and transaction quantity of the i-th power generation enterprise in the j-th period respectively; i represents the number of power generation enterprises, and n represents the number of quotation periods; The calculation formula for the declared electricity share of each section is as follows: x 2i =(x 2i1 ,x 2i2 ,…,x 2in ) Among them, x 2i Indicates that x 2ij represents the electricity share reported by the i-th enterprise in the j-th period, represents the declared electricity price of the i-th power generation enterprise in the j-th period; The calculation formula for the transaction power share of each segment is as follows: x 3i =(x 3i1 ,x 3i2 ,…,x 3in ) Among them, x 3ij represents the transaction electricity share of the i-th enterprise in the j-th period, It represents the transaction volume of the i-th power generation enterprise in the j-th period; The calculation formula for the success rate of each stage of application is as follows: x 4i =(x 4i1 ,x 4i2 ,…,x 4in ) Among them, x 4ij It represents the success rate of the j-th segment declaration of the i-th enterprise; The calculation formula for determining whether it is the high price in this paragraph is as follows: x 5i =(x 5i1 ,x 5i2 ,…,x 5in ) Among them, x 5ij Indicates whether the i-th enterprise's quotation in the j-th segment is the highest price in this segment; The calculation formula for the number of high quotations is as follows: Among them, x 6ij It indicates the number of high bids made by the i-th power generation enterprise in the j-th period.

5. The method for identifying market power of oligopolistic electricity-generating enterprises based on game theory as claimed in claim 4, characterized in that: The calculation of the reference quotation of the power market entity includes calculating the quotation deviation, quotation volatility and quotation limit rate; 6. The method for identifying market power of oligopolistic electricity-generating enterprises based on game theory as claimed in claim 5, characterized in that: The behavioral test includes comparing the reference quotations of power market entities, including the calculated quotation deviation, quotation volatility and quotation limit rate, with the thresholds of various indicators in the power market to determine whether there are any abnormal market power situations.

7. The method for identifying market power of oligopolistic electricity-generating enterprises based on game theory as claimed in claim 6, characterized in that: The price impact test includes: Compare the market clearing price level of the actual quotation with the market clearing price level formed after replacing the quotation of the tested power generation entity with the reference quotation, and make a threshold determination; Define the price impact test factor as: Among them, β price impact test factor, x represents the market price when the dispatching center uses the original quotation of the unit for clearing, called the original market price, y represents the market price when the dispatching center uses the benchmark quotation instead of the original quotation for clearing, called the alternative market price.

8. A system using the method for identifying the market power of oligopolistic electricity-generating enterprises based on game theory as claimed in any one of claims 1 to 7, characterized in that: include: The model building module is used to collect current power market data, build a power generation enterprise bidding strategy model, and produce actual quotation curves; An indicator system construction module is used to construct an indicator system for identifying market power abuse behaviors based on current electricity market data; The test module is used to calculate the reference quotes of power market players based on the actual quote curve and the indicator system for identifying abuse of market power, and to conduct behavior tests and price impact tests; The determination module is used to determine whether the market power level of the power generation enterprise is within a normal range based on the behavior test and the price impact test.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for identifying the market power of oligopolistic power-generating enterprises based on game theory according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for identifying the market power of oligopolistic electricity producers based on game theory according to any one of claims 1 to 7 are implemented.

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