Power generation side quotation income optimization method, system and device, and storage medium

Abstract

The invention relates to a power generation side quotation income optimization method, system and device and a storage medium. Obtaining to-be-input data and setting different initial values; cyclically traversing the different initial values according to a preset sequence, and setting an accumulated value; for the selected target initial value, circularly traversing a preset target output section, executing single output section loop optimization, performing iteration until quotation convergence of each output section, and outputting the quotation output with the highest target value in the recent preset number of cycles; and when the accumulated value is equal to the initial value, ending the circulation, and obtaining the quotation with the highest optimization target as the final output quotation. The optimal power generation side spot quotation strategy is directly found in a given price scene, and the income influence of spot quotation at all time points of the whole day is simplified. And spot quotation reference is provided for traders. Therefore, the learning cost of traders is reduced, and the income of the power generation side subject in the spot market is improved.

Description

Technical Field

[0001] The present application relates to a power generation side quotation strategy in the power spot market, and in particular to a method, system, device and storage medium for optimizing the power generation side quotation revenue. Background Art

[0002] In recent years, the process of electricity marketization has developed rapidly around the world, especially in my country, where pilot markets are steadily advancing electricity marketization reforms based on their unique grid structures and regional characteristics. This process not only involves the continuous improvement of trading rules and varieties, but also includes the diversification of market participants, such as power generation companies, power sales companies, electricity customers and third-party service providers. These measures are aimed at establishing a more stable, secure and efficient electricity market system. In this system, the spot market plays a vital role.

[0003] In the spot market, market players mainly on the power generation side and the power consumption side will declare the spot information of the trading day in advance, including the power generation and consumption curve, power generation quotation, etc. The market clearing algorithm calculates the settlement electricity price of the power generation side and the power consumption side at each time point during the trading day, as well as the power generation and consumption curves of each power generation and power consumption entity. The principle is mainly to minimize the social electricity cost.

[0004] Existing technologies mainly rely on manual experience. Traders on the power generation side need to formulate appropriate quotation strategies every day based on complex electricity market rules and market information in order to achieve corresponding profit indicators. However, the cost of traders learning spot declaration and clearing rules is very high, and the information that needs to be processed during transactions is very large and complex. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a method, system, device and storage medium for optimizing the quotation profit on the power generation side, so as to solve the problem that the prior art mainly relies on manual experience, and traders on the power generation side need to formulate appropriate quotation strategies according to complex electricity market rules and market information every day to achieve corresponding profit indicators, but the cost of traders learning spot declaration and clearing rules is very high, and the information that needs to be processed during transactions is very large and complex.

[0006] According to a first aspect of an embodiment of the present invention, a method for optimizing a power generation side bidding revenue is provided, comprising:

[0007] Obtaining data to be input and setting different initial values; wherein the data to be input includes: power supply parameters on the power generation side, price scenario data, and empty quotation table data;

[0008] Loop through the different initial values ​​in a preset order and set a cumulative value;

[0009] For the selected target initial value, loop through the preset target output segment, perform single output segment loop optimization, iterate until the quotations of each output segment converge, and output the quotation with the highest target value within the most recent preset number of cycles;

[0010] When the accumulated value reaches the initial value, the loop ends and the quotation with the highest optimization target is obtained as the final output quotation.

[0011] Furthermore, the execution process of the single output stage cycle optimization includes:

[0012] By using the input data and the output section to be optimized, the quotations are traversed and cleared within the preset quotation range limit of the power generation side, and the quotation with the best clearing result is selected as the quotation for this section.

[0013] Further, using the input data and the output segment to be optimized, traversing the quotations within the preset power generation side quotation range limit for clearing, and selecting the quotation with the best clearing result as the quotation for this segment, includes:

[0014] Generate multiple sets of quotations on average for the quotation range of the output section to be optimized;

[0015] Using the results of generating multiple sets of quotations, the power generation side quotation market is cleared, and the day-ahead and real-time winning bid output results for each set of input quotations are obtained;

[0016] Using the day-ahead and real-time winning output results of each set of input quotations, a settlement data matrix is ​​generated for the preset variables; wherein the preset variables include: medium- and long-term holding output, medium- and long-term holding price, day-ahead winning output, real-time winning output, day-ahead price, and real-time price;

[0017] Call the preset settlement formula function to calculate the matrix and obtain the profit results at various points in time under various scenarios;

[0018] For the revenue results at each time point in various scenarios, the preset first calculation method is executed to obtain the optimal quotation under the output range.

[0019] Furthermore, the preset settlement formula function is as shown below:

[0020] R = Q 中 *P 中 +(Q 日 -Q 中 )*P 日 +(Q 实 -Q 日 )*P 实 -Q 实 *C (1)

[0021] Among them, R is the total gross profit, in yuan, Q 中 P is the medium- and long-term holding of grid-connected electricity by the power generation entity. 中 Q is the medium- and long-term holding price of the power generation entity. 日 P is the current winning bid output converted into grid-connected power. 日 is the day-ahead settlement price, Q 实 The real-time market bid output is converted to the actual grid power, P 实 is the real-time settlement price, C is the variable cost of power generation, and Q 中 , Q 日 , Q 实 The unit is MWh, P 中 , P 日 The unit of P and C is Yuan / MWh.

[0022] Furthermore, the method of executing a preset first calculation method on the revenue results at each time point in multiple scenarios to obtain the optimal quotation in the output range includes:

[0023] Using the revenue results at various points in time under various scenarios, sum the results of a single quotation throughout the day to get the total gross profit for the day;

[0024] Using the total gross profit for the whole day, obtain the profit result of each generated input quote;

[0025] Select the input quotation corresponding to the result with the highest profit to obtain the optimal quotation under this output range.

[0026] According to a second aspect of an embodiment of the present invention, a system for optimizing the generation side quotation revenue is provided, which is applied to the system method for optimizing the generation side quotation revenue described in any one of the above items, including:

[0027] An acquisition module is used to acquire data to be input and set different initial values; wherein the data to be input includes: power supply parameters on the power generation side, price scenario data, and empty quotation table data;

[0028] A data processing module, used for looping through the different initial values ​​in a preset order and setting a cumulative value;

[0029] For the selected target initial value, loop through the preset target output segment, perform single output segment loop optimization, iterate until the quotations of each output segment converge, and output the quotation with the highest target value within the most recent preset number of cycles;

[0030] When the accumulated value reaches the initial value, the loop ends and the quotation with the highest optimization target is obtained as the final output quotation.

[0031] According to a third aspect of an embodiment of the present invention, a device for optimizing the bidding revenue on the power generation side is provided, comprising:

[0032] a memory having an executable program stored therein;

[0033] A processor is used to execute the executable program in the memory to implement the steps of any one of the methods described above.

[0034] According to a fourth aspect of an embodiment of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the steps of any one of the above methods.

[0035] The technical solution provided by the embodiments of the present invention may have the following beneficial effects:

[0036] It is understandable that the technical solution provided by the present invention simplifies the profit impact of spot quotes at all times of the day by directly finding the optimal spot quote strategy on the power generation side under a given price scenario, and provides spot quote references for traders, thereby reducing the learning cost of traders and increasing the profits of power generation side entities in the spot market.

[0037] It can be understood that the technical solution provided by the present invention, under the general electricity spot market clearing conditions, through the way of automated algorithm process, under the constraint of given quotation monotonicity, cyclically traverses the clearing and quickly settles, so as to find the optimal electricity energy quotation on the power generation side, thereby maximizing the profit on the power generation side, providing a theoretical reference basis for traders' decision-making, assisting traders in spot trading and reviewing, effectively reducing the cost of traders learning spot rules and spot trading, and simplifying the factors that traders need to consider; providing traders with key information on quotation strategies in a visual way, reducing the time and learning cost required for traders to formulate quotation strategies.

[0038] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0040] Figure 1 It is a schematic diagram of steps of a method for optimizing the bidding revenue on the power generation side according to an exemplary embodiment;

[0041] Figure 2 It is a schematic diagram of design steps of a method for optimizing the bidding revenue on the power generation side according to an exemplary embodiment;

[0042] Figure 3It is a schematic diagram of implementing single output section cycle optimization of a method for optimizing the power generation side quotation revenue according to an exemplary embodiment;

[0043] Figure 4 It is a schematic diagram of implementing the traversal initial setting of a method for optimizing the bidding revenue on the power generation side according to an exemplary embodiment;

[0044] Figure 5 It is a schematic diagram of implementing the upper and lower limits of the spot quotation of the power generation side in different time periods according to an exemplary embodiment;

[0045] Figure 6 It is a schematic diagram of an implementation of a spot quotation quantity and price declaration curve on the power generation side according to an exemplary embodiment;

[0046] Figure 7 It is a schematic diagram of an implementation of a spot quotation quantity quotation table on the power generation side according to an exemplary embodiment;

[0047] Figure 8 This is a schematic diagram of a system composition for optimizing the bidding revenue on the power generation side according to an exemplary embodiment;

[0048] Fig. 9 The present invention is a schematic diagram of the composition of a device for optimizing the bidding revenue on the power generation side according to an exemplary embodiment. DETAILED DESCRIPTION

[0049] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0050] Embodiment 1

[0051] See also Figure 1 , Figure 1 The present invention is a schematic diagram of steps of a method for optimizing the bidding revenue of a power generation side according to an exemplary embodiment, the method comprising:

[0052] S1. Obtain the data to be input and set different initial values; wherein the data to be input includes: power supply parameters on the power generation side, price scenario data, and empty quotation table data;

[0053] S2. Loop through the different initial values ​​in a preset order and set the cumulative value;

[0054] S3. For the selected target initial value, loop through the preset target output segment, perform single output segment loop optimization, iterate until the quotations of each output segment converge, and output the quotation with the highest target value within the most recent preset number of cycles;

[0055] S4. When the accumulated value reaches the initial value, the loop ends and the quotation with the highest optimization target is obtained as the final output quotation.

[0056] In one embodiment, the input data includes:

[0057] Power supply parameters on the power generation side: installed capacity, upper and lower limits of operation in different time periods, power generation variable cost function (unit variable cost under different outputs), plant power consumption rate, start and stop time;

[0058] Price scenarios: medium- and long-term holding prices of power generation entities, medium- and long-term holding output, day-ahead price scenarios, and real-time price scenarios. The price scenarios can be spot prices predicted based on market supply and demand conditions, or node prices used for electricity bill settlement on the power generation side after the market is cleared.

[0059] Empty quotation table: If there are quotation restrictions (such as reporting 0 in the first section to ensure startup), they can be filled in, and the algorithm can adapt the recommended quotation according to the quotation restrictions.

[0060] In one embodiment, the execution process of the single output stage cycle optimization includes:

[0061] By using the input data and the output section to be optimized, the quotations are traversed and cleared within the preset quotation range limit of the power generation side, and the quotation with the best clearing result is selected as the quotation for this section.

[0062] Further, using the input data and the output segment to be optimized, traversing the quotations within the preset power generation side quotation range limit for clearing, and selecting the quotation with the best clearing result as the quotation for this segment, includes:

[0063] Generate multiple sets of quotations on average for the quotation range of the output section to be optimized;

[0064] Using the results of generating multiple sets of quotations, the power generation side quotation market is cleared, and the day-ahead and real-time winning bid output results for each set of input quotations are obtained;

[0065] Using the day-ahead and real-time winning output results of each set of input quotations, a settlement data matrix is ​​generated for the preset variables; wherein the preset variables include: medium- and long-term holding output, medium- and long-term holding price, day-ahead winning output, real-time winning output, day-ahead price, and real-time price;

[0066] Call the preset settlement formula function to calculate the matrix and obtain the profit results at various points in time under various scenarios;

[0067] For the revenue results at each time point in various scenarios, the preset first calculation method is executed to obtain the optimal quotation under the output range.

[0068] In specific implementation, the preset settlement formula function is as shown below:

[0069] R = Q 中 *P 中 +(Q 日 -Q 中 )*P 日 +(Q 实 -Q 日 )*P 实 -Q 实 *C (1)

[0070] Where R is the total gross profit in RMB. 中 P is the medium- and long-term holding of grid-connected electricity by the power generation entity. 中 Q is the medium- and long-term holding price of the power generation entity. 日 P is the current winning bid output converted into grid-connected power. 日 is the day-ahead settlement price, Q 实 The real-time market bid output is converted to the actual grid power, P 实 is the real-time settlement price, and C is the variable cost of power generation. 中 , Q 日 , Q 实 The unit is MWh, P 中 , P 日 The unit of P and C is Yuan / MWh.

[0071] In the specific implementation, the electricity energy settlement formula consists of four parts: the first three parts are electricity bill income, namely medium- and long-term electricity bills, day-ahead deviation electricity bills and real-time deviation electricity bills; the fourth part is the total cost.

[0072] In an operating day, the electricity spot market is generally cleared every 15 minutes, with a total of 96 clearing time points throughout the day. Each time point has a corresponding set of medium- and long-term, day-ahead, and real-time clearing and settlement electricity and prices. Each time point is settled once according to the above electricity energy formula, and the full-day income is obtained by summing up each time point.

[0073] In specific implementation, the first calculation method is executed for the revenue results at each time point in multiple scenarios to obtain the optimal quotation under the output range, including:

[0074] Using the revenue results at various points in time under various scenarios, sum the results of a single quotation throughout the day to get the total gross profit for the day;

[0075] Using the total gross profit for the whole day, obtain the profit result of each generated input quote;

[0076] Select the input quotation corresponding to the result with the highest profit to obtain the optimal quotation under this output range.

[0077] In specific implementation, the optimization process of a single output section is as follows:

[0078] When other segments remain unchanged, there is a quotation range limit for any segment of power generation side quotation. The quotations within the limit are traversed for clearing, and the quotation with the best clearing result is selected as the quotation for this segment.

[0079] 1) Generate multiple sets of quotes:

[0080] For a certain output section to be optimized, there is a quotation range, and multiple sets of quotations are generated on average within the quotation range. For example, the quotation range for this section is 1-1499 yuan / MWh, and a quotation is generated within the quotation range of each dP. Generally, dP is set to 1, and 1499 sets of quotations can be generated for this section.

[0081] 2) Power generation quotation market clearing:

[0082] Under the general market clearing rules, for each set of generated bids, as input, the calculation results are mainly the day-ahead and real-time winning bid output. Calculate the day-ahead and real-time winning bid output results for each set of input bids.

[0083] 3) Clearing results:

[0084] Since there are multiple sets of day-ahead and real-time winning output results, a settlement data matrix is ​​generated for each variable that may affect the settlement result. The matrix size of each variable is [96, N]. Among them, 96 is the number of settlement time points in the market within a certain day, and N is the number of generated quotes. The variables that need to generate the settlement data matrix are: medium- and long-term position output, medium- and long-term position price, day-ahead winning output, real-time winning output, day-ahead price, and real-time price.

[0085] 4) Call the settlement formula function:

[0086] Since the settlement formula is the same for any clearing result and any time point, the matrix can be directly calculated, and the profit results at various time points in various scenarios can be directly output after calculation. The profit output result is in matrix form, and the output matrix size is consistent with the input data.

[0087] 5) Generate quotation-gross profit function:

[0088] After the settlement matrix is ​​calculated, the results of a single quotation for the whole day are summed up to get the total gross profit for the whole day. Since the total gross profit changes with the change of the quotation, the quotation-gross profit function curve can be output as a reference for the quotation strategy.

[0089] 6) Select the best result:

[0090] The output results are summed over time to obtain the revenue result of each generated input quotation. Select the input quotation corresponding to the result with the highest revenue to obtain the optimal quotation under the output range.

[0091] For specific implementation, please refer to Figure 2 As described in step S3, for the selected target initial value, loop through the preset target output segment, perform single output segment loop optimization, iterate until the quotations of each output segment converge, and output the quotation output with the highest target value in the most recent preset number of cycles, including:

[0092] By giving the initial settings, a single output segment is cyclically optimized. In the specific implementation, due to the monotonically non-decreasing or monotonically increasing restrictions on the power generation side quotation, the quotation of each output segment is limited by the quotation of the previous output segment and the next output segment. The first segment quotation is limited by the lower limit of the quotation, and the last segment quotation is limited by the upper limit of the quotation. Therefore, the optimization method of multi-segment quotation is a single-segment cyclic optimization process. After the initial quotation settings are given, one of the segments is selected for the above optimization, and the quotations of other segments are restricted. After this segment of cyclic optimization is completed, the next segment quotation is optimized. Iterate until the quotations of each output segment converge.

[0093] Specifically, convergence is defined as the same quotation in each output segment in the last N cycles, where N is the number of free optimization segments. After convergence, the quotation with the highest target value in the last N cycles is selected for output.

[0094] For specific implementation, please refer to Figure 3 , Figure 3 It is a schematic diagram of the implementation of a single output segment cyclic optimization of a method for optimizing the power generation side quotation revenue according to an exemplary embodiment. By giving an initialization quotation, the target output segment is optimized to obtain the optimized output segments and related quotations of each segment.

[0095] In one embodiment, as described in step S4, when the accumulated value reaches the initial value, the loop ends and the quotation with the highest optimization target is obtained as the final output quotation. For specific implementation, please refer to Figure 4Different initial settings and different initial optimization segments will affect the final optimization results. Therefore, during the optimization process, different initial settings will be set for optimization, and finally the quotation with the highest optimization target will be found as the final output quotation. The number of initial settings is N+1, which is the initial quotation combination with the minimum or maximum quotation for each output segment. Due to the monotonically non-decreasing or monotonically increasing quotation limit, the number of initial quotation settings is limited.

[0096] In one embodiment, the technical solution provided by the present invention, under the general electricity spot market clearing conditions, through an automated algorithm process, under the constraint of given quotation monotonicity, cyclically traverses the clearing and quickly settles, so as to find the optimal electricity energy quotation on the power generation side, thereby maximizing the profit on the power generation side, providing a theoretical reference basis for traders' decision-making, assisting traders in spot trading and reviewing, effectively reducing the cost of traders learning spot rules and spot trading, and simplifying the factors that traders need to consider; providing traders with key information on quotation strategies in a visual way, reducing the time and learning cost required for traders to formulate quotation strategies.

[0097] In one embodiment, the spot quotation rules on the power generation side are:

[0098] See also Figure 5 , Figure 6 , mainly provided by the quotation table, including the upper and lower limits of the operation in different time periods throughout the day. And multiple sections of declared quantity and price curves (generally no more than 10 sections), including the start and end output and quotation of each section. The spot quotation needs to be declared one day before the operation day, which is used for clearing before the operation day and at various times of the day in the real-time market. For the upper and lower limits of the operation in different time periods, please refer to Figure 5 , please refer to the volume price declaration curve Figure 6 .

[0099] The main power generation entities are usually thermal power companies that make quotations, while other power generation entities usually declare their output at different times. In the market rules of some provinces, other power generation entities such as wind power, photovoltaic power, and hydropower can participate in market quotations.

[0100] General rules for clearing electricity on the power generation side:

[0101] From the perspective of the power generation entity, the quotation table establishes the output stage and the corresponding price of the output stage. Figure 7 For example, at a certain point in time, the spot price is 380 yuan / MWh (milliwatt hour), which falls into the second output range. At this time, the winning output of the power plant is 250MW.

[0102] In one embodiment, the quotation optimization algorithm provided by this method can directly find the optimal spot quotation strategy on the power generation side under a given price scenario, simplifying the impact of spot quotation on revenue at all times of the day, and providing spot quotation references for traders. This reduces the learning cost of traders and increases the revenue of power generation entities in the spot market.

[0103] See also Figure 8 , Figure 8 The present invention is a schematic diagram of a system composition for optimizing the bidding revenue of a power generation side according to an exemplary embodiment, wherein the system comprises:

[0104] The acquisition module 10 is used to acquire the data to be input and set different initial values; wherein the data to be input includes: power supply parameters of the power generation side, price scenario data, and empty quotation table data;

[0105] The data processing module 20 is used to loop through the different initial values ​​in a preset order and set a cumulative value;

[0106] For the selected target initial value, loop through the preset target output segment, perform single output segment loop optimization, iterate until the quotations of each output segment converge, and output the quotation with the highest target value within the most recent preset number of cycles;

[0107] When the accumulated value reaches the initial value, the loop ends and the quotation with the highest optimization target is obtained as the final output quotation.

[0108] See also Fig. 9 , Fig. 9 This is a schematic diagram of a device composition for optimizing the bidding revenue on the power generation side according to an exemplary embodiment, wherein the device comprises:

[0109] A memory 91 on which an executable program is stored;

[0110] The processor 92 is used to execute the executable program in the memory 91 to implement the steps of any one of the above methods.

[0111] In addition, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a computer to execute the steps of any of the above methods. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory (Flash Memory), a hard disk (HDD) or a solid-state drive (SSD), etc.; the storage medium may also include a combination of the above-mentioned types of memory.

[0112] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

[0113] It should be noted that, in the description of the present invention, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, the meaning of "plurality" refers to at least two.

[0114] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0115] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0116] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0117] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0118] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0119] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0120] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for optimizing the power generation side quotation revenue, characterized in that: The method comprises: Obtaining data to be input and setting different initial values; wherein the data to be input includes: power supply parameters on the power generation side, price scenario data, and empty quotation table data; Loop through the different initial values ​​in a preset order and set a cumulative value; For the selected target initial value, loop through the preset target output segment, perform single output segment loop optimization, iterate until the quotations of each output segment converge, and output the quotation with the highest target value within the most recent preset number of cycles; When the accumulated value reaches the initial value, the loop ends and the quotation with the highest optimization target is obtained as the final output quotation.

2. The method according to claim 1, characterized in that The execution process of the single output section cycle optimization includes: By using the input data and the output section to be optimized, the quotations are traversed and cleared within the preset quotation range limit of the power generation side, and the quotation with the best clearing result is selected as the quotation for this section.

3. The method according to claim 2, characterized in that The method of using the input data and the output segment to be optimized, traversing quotations within a preset power generation side quotation range limit for clearing, and selecting the quotation with the best clearing result as the quotation for the segment includes: Generate multiple sets of quotations on average for the quotation range of the output section to be optimized; Using the results of generating multiple sets of quotations, the power generation side quotation market is cleared, and the day-ahead and real-time winning bid output results for each set of input quotations are obtained; Using the day-ahead and real-time winning output results of each set of input quotations, a settlement data matrix is ​​generated for the preset variables; wherein the preset variables include: medium- and long-term holding output, medium- and long-term holding price, day-ahead winning output, real-time winning output, day-ahead price, and real-time price; Call the preset settlement formula function to calculate the matrix and obtain the profit results at various points in time under various scenarios; For the revenue results at each time point in various scenarios, the preset first calculation method is executed to obtain the optimal quotation under the output range.

4. The method according to claim 3, characterized in that The preset settlement formula function is as shown below: R = Q 中 *P 中 +(Q 日 -Q 中 )*P 日 +(Q 实 -Q 日 )*P 实 -Q 实 *C (1) Among them, R is the total gross profit, in yuan, Q 中 P is the medium- and long-term holding of grid-connected electricity by the power generation entity. 中 Q is the medium- and long-term holding price of the power generation entity. 日 P is the current winning bid output converted into grid-connected electricity. 日 is the day-ahead settlement price, Q 实 The real-time market bid output is converted to the actual grid power, P 实 is the real-time settlement price, C is the variable cost of power generation, and Q 中 , Q 日 , Q 实 The unit is MWh, P 中 , P 日 The unit of P and C is Yuan / MWh.

5. The method according to claim 3, characterized in that: The method of executing a preset first calculation method on the revenue results at each time point in multiple scenarios to obtain the optimal quotation under the output range includes: Using the revenue results at various points in time under various scenarios, sum the results of a single quotation throughout the day to get the total gross profit for the day; Using the total gross profit for the whole day, obtain the profit result of each generated input quote; Select the input quotation corresponding to the result with the highest profit to obtain the optimal quotation under this output range.

6. A system for optimizing the power generation side quotation revenue, applied to the system method for optimizing the power generation side quotation revenue as described in any one of claims 1 to 5, characterized in that: The system comprises: An acquisition module is used to acquire data to be input and set different initial values; wherein the data to be input includes: power supply parameters on the power generation side, price scenario data, and empty quotation table data; A data processing module, used for looping through the different initial values ​​in a preset order and setting a cumulative value; For the selected target initial value, loop through the preset target output segment, perform single output segment loop optimization, iterate until the quotations of each output segment converge, and output the quotation with the highest target value within the most recent preset number of cycles; When the accumulated value reaches the initial value, the loop ends and the quotation with the highest optimization target is obtained as the final output quotation.

7. A device for optimizing the quotation revenue of the power generation side, characterized in that: The device comprises: A memory having an executable program stored therein; A processor, configured to execute the executable program in the memory to implement the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the steps of the method according to any one of claims 1 to 5.

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