A restrictive clearing electricity price generation system based on n-oligopoly testing in multiple scenarios

Abstract

This invention relates to a restricted clearing price generation system based on an n-oligopoly test under multiple scenarios, comprising: a generator set classification module for implementing a congestion mitigation criticality test (n-oligopoly test) and classifying critical and non-critical generator sets; a basic data acquisition module for acquiring basic data; a basic price calculation module for calculating benchmark prices; a multi-scenario selection module for selecting multiple bidding market scenarios; and a restricted clearing price determination module for selecting a bidding market scenario from the multi-scenario selection module, setting prices for critical and non-critical generator sets within that scenario, simulating a market clearing process that matches supply and demand, and determining the clearing price for the corresponding scenario, thereby obtaining the restricted clearing price. Compared with existing technologies, this invention, in proposing a rationalized restricted clearing price, can maintain market competitiveness as much as possible and ensure reasonable revenue for the transmission and distribution network.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a restrictive clearing electricity price generation system based on n-oligopoly testing in multiple scenarios. Background Technology

[0002] The restrictive clearing price is a price cap in the short-term competitive electricity market. It is used to replace the clearing price when market prices deviate significantly from a state of perfect competition, in order to curb the market power of generators, stabilize electricity prices, and ensure the efficiency of market resource allocation.

[0003] There are three main existing methods for setting restrictive clearing electricity prices: ① Setting the price based on the marginal cost of the most expensive generating unit. This method is based on the assumption that all generating units quote prices at cost under perfect competition, so the market clearing price will not exceed the marginal cost of the most expensive generating unit. However, in actual operation, the most expensive generating unit and its marginal cost will change with the price of primary energy (coal price) and the state of transmission grid congestion. The price cap set based on the marginal cost of the most expensive generating unit in the previous stage may be too low / too high for the later stage; ② Adding a fixed increment to the historical average clearing price or multiplying it by a coefficient greater than 1 to form the restrictive clearing price. This method is detached from the generation cost, and its rationality depends on whether the historical clearing price itself is reasonable; ③ Using the value of lost load (VOLL) as the restrictive clearing price. VOLL represents the maximum fee that users are willing to pay for 1 kWh of electricity. Its value is often far higher than the generation cost, and its inhibitory effect on market forces is limited.

[0004] In addition to the aforementioned shortcomings in suppressing market power, the existing restrictive clearing electricity pricing method has two common drawbacks: first, it does not consider a linkage mechanism with coal prices, thus failing to guarantee reasonable returns for the power generation side; second, it does not consider a mechanism to guarantee reasonable returns for transmission and distribution. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a rationalized restrictive clearing price generation system that can maintain market efficiency as much as possible and ensure reasonable revenue for power transmission and distribution.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] A restrictive clearing electricity price generation system based on multi-scenario n-oligopoly testing includes:

[0008] Generator Set Classification Module: Used to obtain all generator sets that need to be measured and to implement the congestion mitigation criticality test (n-oligopoly test) to classify the generator sets into critical generator sets and non-critical generator sets.

[0009] The basic data acquisition module is used to acquire the basic data for setting the benchmark price of generator sets.

[0010] The basic quotation calculation module is used to calculate the benchmark quotation based on the basic data using a heuristic algorithm.

[0011] The multi-scenario selection module is used to select multiple bidding market scenarios;

[0012] The restricted clearing price determination module is used to select a bidding market scenario from the multi-scenario selection module. In this bidding market scenario, the price of critical generator sets is set as the benchmark price, and the price of non-critical generator sets is set as the upper limit of the cost curve of the corresponding single unit capacity level. The module simulates the market clearing process of supply and demand matching, and determines the clearing price in the corresponding scenario based on the average power generation cost of the grid-connected units.

[0013] Repeatedly select different bidding market scenarios, determine the clearing price under the corresponding scenario, traverse all scenarios, and set the maximum market clearing price of each scenario as the restrictive clearing price.

[0014] The basic data includes the upper bound of the power generation cost curve for thermal power units of various capacity levels in a region, historical price quotes for generator units under different scenarios, power supply and load distribution in each season, transmission network structure and parameters, allowable reasonable revenue for transmission and distribution, and regional electricity sales pricing system.

[0015] Furthermore, the calculation of the benchmark price using a heuristic algorithm specifically includes the following steps:

[0016] S101: Set the initial benchmark price p based on the historical average of actual market clearing electricity prices. cap ;

[0017] S102: Generate initial benchmark price p cap The power generation supply curve below;

[0018] S103: Calculating the initial benchmark price p based on the power generation supply curve cap Next year's electricity purchase cost in the competitive bidding market F B (p cap );

[0019] S104: Calculation of initial benchmark price p cap Annual electricity revenue F from the downstream electricity sales side S (p cap );

[0020] S105: Verify whether the difference between the market net return rate and the permitted return rate of the transmission and distribution network is within the preset permitted range. If it violates the lower limit, lower the initial benchmark price p. cap And return to step S102; if the upper limit is violated, increase the initial benchmark price p.cap And return to step S102; if it is within the preset allowable range, then p at this time cap The value is the final benchmark price.

[0021] Furthermore, the expression used for testing in step S105 is:

[0022]

[0023] In the formula, α max % represents the maximum permissible deviation rate between market net revenue and reasonable transmission and distribution revenue, F TD This refers to the permitted revenue from power transmission and distribution in that year.

[0024] Furthermore, in each scenario, the process for determining the critical generator set includes the following steps:

[0025] S201: Analyze the historical operating data of the system in the current scenario to obtain a set of transmission lines that are prone to blockage;

[0026] S202: For each branch in the set of transmission lines prone to congestion, conduct a congestion mitigation criticality test, and include the generator sets on the branches that pass the congestion mitigation criticality test in the critical generator set set of the corresponding scenario.

[0027] Furthermore, the expression for the critical test for blocking mitigation is:

[0028] F(l,i)<0

[0029]

[0030] In the formula, F(l,i) is the power transfer distribution factor of power generation node i with respect to branch l, representing the power flow increase on branch l caused by a 1kW increase in output power at node i, and m l and n l These are the first and last node numbers of branch l, respectively; and This represents the reactance value at the corresponding position in the DC power flow impedance matrix; x l Let be the reactance value of branch l.

[0031] Furthermore, the simulation process of the market clearing process includes the following steps:

[0032] Pre-clearing steps: Without considering transmission constraints, the generator set bids are sorted from low to high until supply and demand are balanced;

[0033] Blockage detection step: Under the power generation plan corresponding to the pre-clearing step, check whether there is line overload. If there is line overload, proceed with the step of finding the receiving end area of ​​the blocked line; otherwise, determine the market clearing price of the corresponding scenario according to the preset market rules.

[0034] Steps for finding the receiving end area of ​​a blocked line: Determine the receiving end area of ​​the blocked line for each generator set, thereby dividing the power grid into two areas: the supply end and the receiving end of the blocked line. Then, perform another clearing step.

[0035] The second clearing step involves simulating market clearing again for both the supply and receiving power grids. Generators in the supply and receiving regions are ranked until the regional load demand is met, and the marginal clearing price of the supply and receiving power grids is obtained. Then, the process returns to the congestion check step.

[0036] Furthermore, the criterion for checking whether there is a line overload is:

[0037]

[0038] In the formula, P l max The maximum power that branch l can withstand;

[0039] The expression for determining the receiving-end region of a blocked line is:

[0040] F(l,j)<0.

[0041] Furthermore, in the blockage detection step, if multiple lines are overloaded simultaneously, the process begins with the line that is most severely overloaded.

[0042] Furthermore, multiple bidding market scenarios are selected according to the trend distribution.

[0043] Compared with the prior art, the present invention has the following advantages:

[0044] (1) This invention provides a restricted clearing price generation system based on n-oligopoly test in multiple scenarios, which realizes the efficient generation of a reasonable restricted clearing price through computer processing. In addition, the processing includes a two-level price limit mechanism of "benchmark price - restricted clearing price". Since the benchmark price calculation ensures that the net profit of the market can meet the reasonable income of the transmission and distribution network, and the market clearing price of the imperfectly competitive market that can be tolerated in multiple scenarios will not be higher than the benchmark price, the final restricted clearing price can also guarantee the reasonable income of the transmission and distribution network.

[0045] (2) The restricted clearing price of the present invention is obtained by simulating a tolerable imperfect competition market under multiple scenarios. In the setting of the tolerable imperfect competition market scenario, non-critical units are considered to bid at the upper limit of the power generation cost of the corresponding capacity level units, and the upper limit of the power generation cost curve fluctuates with the coal price. Therefore, the proposed method can realize the linkage between the restricted clearing price and the coal price, thereby ensuring reasonable income on the power generation side.

[0046] (3) The restrictive clearing price is obtained through simulation of a tolerable imperfect competition market under multiple scenarios. The setting of the tolerable imperfect competition market state reflects the tolerable upper limit of the bidding behavior of critical and non-critical generator sets. Therefore, the calculated restrictive clearing price plays a certain role in restricting the market power behavior of generators from a mechanism perspective, and maintains market competitiveness as much as possible. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of the overall processing flow of a restricted clearing electricity price generation system based on n-oligopoly testing in multiple scenarios, provided in an embodiment of the present invention.

[0048] Figure 2 This is a flowchart of a benchmark pricing setting process provided in an embodiment of the present invention;

[0049] Figure 3 This is a flowchart illustrating a market clearing simulation in a specific scenario, as provided in an embodiment of the present invention. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0051] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0052] 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 further defined and explained in subsequent figures.

[0053] Example 1

[0054] This embodiment provides a restrictive clearing electricity price generation system based on multi-scenario n-oligopoly testing. It guarantees transmission and distribution revenue by setting a benchmark price based on a heuristic algorithm. By identifying key generating units (i.e., n oligopolies), the system defines the state of key generating units bidding at the benchmark price and non-key generating units bidding at the cost ceiling as a "tolerable imperfect competition market" state. It then implements clearing simulations of the "tolerable imperfect competition market" in multiple scenarios to obtain a price cap with a coal price linkage mechanism that suppresses market forces.

[0055] Specifically, it includes:

[0056] Generator Set Classification Module: Used to obtain all generator sets that need to be measured and to implement the congestion mitigation criticality test (n-oligopoly test) to classify the generator sets into critical generator sets and non-critical generator sets.

[0057] The basic data acquisition module is used to acquire the basic data for setting the benchmark price of generator sets, including: the reasonable upper limit of the power generation cost curve of thermal power units of various capacity levels in a region (province / city) (obtained by statistical analysis of information reported by the units), the historical price of generator sets in typical scenarios, the power supply and load distribution in each season, the transmission network structure and parameters, the reasonable allowable value of transmission and distribution revenue, and the regional electricity sales price system.

[0058] The basic price calculation module is used to calculate the benchmark price based on the aforementioned basic data using a heuristic algorithm. The benchmark price is used to replace the excessively high price when the generator set price is too high. The heuristic algorithm is used to calculate the benchmark price so that the difference between the market net revenue and the reasonable transmission and distribution revenue permitted by the regulatory authorities is within the allowable range.

[0059] The multi-scenario selection module is used to select multiple bidding market scenarios. Due to differences in power supply structure, external power supply conditions, and regional load fluctuation characteristics, the power flow distribution varies significantly during peak / off-peak hours on typical days in different seasons. Therefore, multiple bidding market scenarios are selected based on the power flow distribution.

[0060] The restricted clearing price determination module is used to select a bidding market scenario from the multi-scenario selection module. In this bidding market scenario, the price of critical generator sets is set as the benchmark price, and the price of non-critical generator sets is set as the upper limit of the cost curve of the corresponding single unit capacity level. The module simulates the market clearing process of supply and demand matching, and determines the clearing price in the corresponding scenario based on the average power generation cost of the grid-connected units.

[0061] Specifically, this includes setting a tolerable imperfect competition market state for scenario k: based on the pricing psychology of power generators and in order to constrain the market power behavior of various power generators, the pricing of critical generator sets in scenario k is set as the benchmark pricing (these generator sets have the motivation to price strategically, but are limited to a tolerable range), while the pricing of non-critical generator sets is set as the upper limit of the cost curve of the corresponding single-unit capacity level (these generator sets have little impact on market prices and are usually priced at cost, but are allowed to price at the upper limit of cost).

[0062] Simulation of market clearing process in scenario k: Simulate the market clearing process of supply and demand matching. When transmission line congestion occurs, the power grid is divided into two parts, the supply end and the receiving end, according to the congested line. Supply and demand matching is implemented separately, and the clearing price in the corresponding scenario is determined according to the average generation cost of the grid-connected units (based on the bid).

[0063] Repeatedly select different bidding market scenarios, determine the clearing price under the corresponding scenario, traverse all scenarios, and set the maximum market clearing price of each scenario as the restrictive clearing price.

[0064] The specific implementation process of the above scheme mainly includes three core links: setting benchmark electricity prices, testing the oligopoly of n companies, and simulating the tolerable imperfect competition market clearing process under various scenarios.

[0065] (1) Benchmark Price Calculation Method

[0066] Figure 2 The benchmark pricing calculation method based on heuristic algorithms includes the following steps:

[0067] A. Set the initial benchmark price p cap This value is taken as the average of the historical market clearing electricity prices, i.e.

[0068]

[0069] In the above formula, p clear,k Let n represent the clearing price of the k-th market clearing event during the observation period (e.g., one year). M This indicates the number of market clearing events during the observation period.

[0070] B. In p cap To generate the power generation supply curve: Calculate the average bids from each power generator across all capacity segments on typical days of each season. Sort these bids from highest to lowest, then sum the capacities at the same bid level to obtain the original power generation supply curve for the corresponding season. Then, select the capacity segment on this supply curve where the bid level exceeds p. cap The part is set to p cap p is thus generated cap The power generation supply curve below.

[0071] C. Find pcap Next year's electricity purchase cost in the competitive bidding market F B (p cap Market clearing simulations are performed on typical days of each season without considering network constraints. The market clearing point is determined by the intersection of the power generation supply curve and the load demand curve. The annual cost of purchasing electricity in the competitive bidding market is calculated using the following formula.

[0072]

[0073] In the above formula, and P s,t These are the market clearing price and total trading volume for a typical day in season s during time period t. The number of days in season s.

[0074] D. Calculate p cap Annual electricity revenue F from the downstream electricity sales side S (p cap According to the "Notice on Further Deepening the Market-Oriented Reform of On-Grid Tariffs for Coal-fired Power Generation" issued by the National Development and Reform Commission on October 11, 2021, the catalog tariff for 10kV and above users was abolished starting October 15, 2021. Therefore, the annual electricity cost for 10kV and above users is calculated using the following formula.

[0075]

[0076] in, The transmission and distribution price that users at voltage level v need to pay for each unit of electricity purchased; P s,v,t This refers to the electricity purchase amount for users at voltage level v during a typical day in season s, specifically during time period t. For users below 10kV, the electricity price is calculated using the catalog price.

[0077]

[0078] in, This represents the catalog electricity price for users at voltage level v. Finally, the electricity charges under both pricing systems are summed to obtain the total annual electricity cost.

[0079]

[0080] E. Market Return Balance Test: The following formula is used to test whether the market net return rate meets the requirements for reasonable returns in transmission and distribution.

[0081]

[0082] In the above formula, F TD For the permitted revenue from power transmission and distribution in that year, α max The percentage represents the maximum permissible deviation rate between market net revenue and reasonable transmission and distribution revenue. Both of these values ​​are set by the regulatory authorities upon review.

[0083] F. Perturbation p cap Value: If equation (6) violates the lower limit (i.e., insufficient returns), then adjust p downwards. cap Value; if the upper limit is violated, increase p. cap Value; then return to step B until equation (6) is satisfied, at which point p cap The value is a reasonable value that takes into account both market competitiveness and grid revenue.

[0084] (2) Identification of critical generator sets

[0085] In the electricity market, the key generating units (i.e., oligopolies) that significantly influence bidding results are primarily those located at the receiving end of congested lines. In the k-th scenario, the steps for searching for these key generating units are as follows:

[0086] A. Identify the set of transmission lines prone to congestion: By analyzing historical system operation data under the corresponding scenario, identify the set of transmission lines prone to congestion, denoted as I. TL,k ;

[0087] B. Critical test for congestion mitigation: For each branch l∈I TL,k Implement the key test for blockage relief as follows:

[0088] F(l,i)<0 (7)

[0089] Where F(l,i) is called the power transfer distribution factor of power generation node i with respect to branch l, representing the power flow increase in branch l (with node i as the receiving end) caused by a 1kW increase in output power at node i. Its calculation formula is:

[0090]

[0091] In the above formula, m l and n l These are the first and last node numbers of branch l, respectively; and This represents the reactance value at the corresponding position in the DC power flow impedance matrix; x l Let l be the reactance value of branch l. Units satisfying equation (9) pass the criticality test for congestion mitigation and are included in the critical generator set for the corresponding scenario.

[0092] (3) Simulation method for tolerable imperfect competition market clearing process

[0093] Figure 3 This simulates a clearing process for a tolerable imperfectly competitive market under a specific scenario. For the k-th scenario, the specific implementation steps are as follows:

[0094] A. Pricing Settings: For critical generator sets For the generator sets listed, the price is set as the benchmark price; for the remaining generator sets, the price is set as the upper limit of the cost curve for the corresponding single-unit capacity level.

[0095] B. Market clearing simulation, which includes the following steps:

[0096] Step 1: Pre-clearing. Without considering transmission constraints, the generator unit prices are sorted from low to high until supply and demand are balanced.

[0097] Step 2: Congestion Check. Under the pre-clearance generation plan, check for line overload, the criterion being...

[0098]

[0099] F(l,i) is evaluated according to equation (8). If any line satisfies the above equation, proceed to the next step (if multiple lines are overloaded at the same time, start from the line with the most severe overload and proceed to the third to fifth steps below).

[0100] Step 3: Locate the receiving end region of the blocked line. This will satisfy...

[0101] Node j of F(l,j)<0 (10) is taken as the receiving end region node. Thus, the power grid is divided into two regions: the blocking line supply end and the receiving end.

[0102] Step 4: Re-clearing of the supply and receiving grids. Simulations of market clearing are then performed again on both the supply and receiving grids. This time, congested lines are treated as loads with capacity at their transmission capacity limit (for the supply grid) / power sources with capacity at their transmission capacity limit and a bid equal to the marginal generation cost of the supply grid (for the receiving grid). Within the supply / receiving regional grids, the bids of generating units within the region are ranked from low to high until the regional load demand is met, thus obtaining the marginal clearing price for both the supply and receiving grids.

[0103] Step 5: Perform a congestion check on the clearing scheme again. If there is still line overload, return to step 3 until there is no longer any line overload.

[0104] Step 6: Determine the clearing price for the corresponding scenario based on the regional pricing rules (based on the marginal generation cost of grid-connected units or the average generation cost of grid-connected units).

[0105] The functional modules described above in this document can be implemented, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that can be used include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0106] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0107] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A method based on multiple scenarios n The oligopoly test-based restrictive clearing electricity price generation system is characterized by, include: Generator Set Classification Module: Used to obtain all generator sets that need to be measured, and to perform critical tests to mitigate congestion, classifying the generator sets into critical generator sets and non-critical generator sets. The basic data acquisition module is used to acquire the basic data for setting the benchmark price of generator sets; The basic quotation calculation module is used to calculate the benchmark quotation based on the basic data using a heuristic algorithm. The multi-scenario selection module is used to select multiple bidding market scenarios; The restrictive clearing price determination module is used to select a bidding market scenario from the multi-scenario selection module. Under this bidding market scenario, the bid price of critical generating units is set as the benchmark bid price, and the bid price of non-critical generating units is set as the upper limit of the cost curve of the corresponding single unit capacity level. This simulates the market clearing process of supply and demand matching, and determines the clearing price under the corresponding scenario based on the average generation cost of the grid-connected units. The module repeatedly selects different bidding market scenarios to determine the clearing price under the corresponding scenario, iterates through all scenarios, and sets the maximum value of the market clearing price of each scenario as the restrictive clearing price. In each scenario, the determination process for the critical generator set includes the following steps: S201: Analyze the historical operating data of the system in the current scenario to obtain a set of transmission lines that are prone to blockage; S202: For each branch in the set of easily congested transmission lines, conduct a congestion mitigation criticality test, and include the generator sets on the branches that pass the congestion mitigation criticality test into the critical generator set set of the corresponding scenario. The expression for the critical test for blocking mitigation is: In the formula, For power generation nodes i Regarding the branch road l The power generation transfer distribution factor represents the node i An increase of 1kW in the output power will affect the branch circuit. l The trend of increasing, and Branch roads The first and last node numbers; and This represents the reactance value at the corresponding position in the DC power flow impedance matrix; branch road The reactance value; The simulation process of the market clearing process includes the following steps: Pre-clearing steps: Without considering transmission constraints, the generator set bids are sorted from low to high until supply and demand are balanced; Blockage detection step: Under the power generation plan corresponding to the pre-clearing step, check whether there is line overload. If there is line overload, proceed with the step of finding the receiving end area of ​​the blocked line; otherwise, determine the market clearing price of the corresponding scenario according to the preset market rules. Steps for finding the receiving end area of ​​a blocked line: Determine the receiving end area of ​​the blocked line for each generator set, thereby dividing the power grid into two areas: the supply end and the receiving end of the blocked line. Then, perform another clearing step. The second clearing step involves simulating market clearing again for both the supply and receiving power grids. Generators in the supply and receiving regions are ranked until the regional load demand is met, and the marginal clearing price of the supply and receiving power grids is obtained. Then, the process returns to the congestion check step.

2. A method based on multiple scenarios as described in claim 1 n The oligopoly test-based restrictive clearing electricity price generation system is characterized by, The basic data includes the upper bound of the power generation cost curve for thermal power units of various capacity levels in a region, historical price quotes for generator units under different scenarios, power supply and load distribution in each season, transmission network structure and parameters, allowable reasonable revenue for transmission and distribution, and regional electricity sales pricing system.

3. A method based on multiple scenarios as described in claim 1 n The oligopoly test-based restrictive clearing electricity price generation system is characterized by, The benchmark price is calculated using a heuristic algorithm, which includes the following steps: S101: Set initial benchmark offer according to historical market actual clearing price mean value ; S102: Generate initial benchmark quote The power generation supply curve below; S103: Calculating the initial benchmark price based on the power generation supply curve Electricity purchase fees in the competitive bidding market for the next year ; S104: Calculation of Initial Base Price Annual electricity revenue from the downstream electricity sales side ; S105: Verify whether the difference between the market net return rate and the permitted return rate of the transmission and distribution network is within the preset permitted range. If it violates the lower limit, lower the initial benchmark price. Then return to step S102; if the upper limit is violated, increase the initial benchmark price. Then return to step S102; if it is within the preset allowable range, then at this time... The value is the final benchmark price.

4. A method based on multiple scenarios as described in claim 3 n The oligopoly test-based restrictive clearing electricity price generation system is characterized by, The expression used for testing in step S105 is: In the formula, This represents the maximum permissible deviation rate between market net revenue and reasonable transmission and distribution revenue. This refers to the permitted revenue from power transmission and distribution in that year.

5. A method based on multiple scenarios as described in claim 1 n The oligopoly test-based restrictive clearing electricity price generation system is characterized by, The criterion for checking for line overload is: wherein is the maximum sustained power of the branch l ; The expression for determining the receiving-end region of a blocked line is: 。 6. A method based on multiple scenarios as described in claim 1 n The oligopoly test-based restrictive clearing electricity price generation system is characterized by, In the blockage detection step, if multiple lines are overloaded simultaneously, the process starts with the line that is most severely overloaded.

7. A method based on multiple scenarios as described in claim 1 n The oligopoly test-based restrictive clearing electricity price generation system is characterized by, A plurality of bidding market scenarios are selected according to the distribution of the tides.

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