A Regional Power Grid Surplus Renewable Energy Trading Method and System Based on Equivalent Consumption Price
By constructing an equivalent consumption price model and a trading model, the grid transmission capacity and renewable energy restricted capacity are assessed, renewable energy trading is optimized, the problem of insufficient renewable energy consumption under grid congestion is solved, and the renewable energy consumption capacity is improved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- STATE GRID SHANDONG ELECTRIC POWER CO MARKETING SERVICE CENT (MEASURING CENT)
- Filing Date
- 2022-10-21
- Publication Date
- 2026-07-17
Smart Images
Figure CN115601171B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of dispatch operation and electricity market intersection, and in particular to a method and system for trading surplus renewable energy in regional power grids based on equivalent consumption prices. Background Technology
[0002] Grid congestion is a significant factor limiting the absorption of new energy sources. In some provinces and regions, wind and solar power curtailment due to grid transmission capacity limitations exceeds 50% of their total curtailment. Given the long construction cycle of power grid infrastructure and the difficulty in increasing grid transmission capacity in the short term, improving grid absorption capacity and reducing wind and solar power curtailment caused by grid congestion has become a key research focus.
[0003] Current research in the aforementioned fields focuses on three aspects:
[0004] First, we will focus on optimizing power generation dispatch, rationally arrange power generation plans for conventional power sources such as hydropower and thermal power in areas with grid congestion, and fully tap the potential for new energy consumption.
[0005] Second, we will focus on the participation of new energy business models such as energy storage and flexible transformation of coal-fired power plants, and study measures to improve the capacity for new energy consumption under the optimization and coordination of new energy power generation output.
[0006] Third, we will focus on multi-energy complementarity and study ways to optimize the operation of various energy sources such as cold, heat, gas, electricity, and hydrogen, and improve the capacity for new energy consumption.
[0007] Overall, current research on solving the problem of renewable energy consumption under grid congestion focuses on the generation side. By optimizing the operation of power generation, the problem of surplus renewable energy consumption under regional grid constraints can be effectively solved, thereby improving the renewable energy consumption capacity. Summary of the Invention
[0008] To at least partially overcome the problem of renewable energy consumption under grid congestion in related technologies and to improve the renewable energy consumption capacity, this application provides a method and system for trading surplus renewable energy in regional power grids based on equivalent consumption prices.
[0009] The proposed solution is as follows:
[0010] A regional power grid surplus renewable energy trading method based on equivalent consumption price includes: collecting load forecast datasets, renewable energy forecast datasets and evaluating power grid transmission capacity.
[0011] Based on the load forecast dataset, the new energy forecast dataset, and the evaluation results of the power grid transmission capacity, the restricted capacity of new energy sources in each time period within the evaluation area is assessed.
[0012] Based on the calculation results of the restricted capacity of new energy sources in the region for each time period, market applications are submitted to obtain the expected transaction price;
[0013] Based on the expected transaction price and the calculation results of the restricted capacity of new energy in the region for each time period, an equivalent consumption price optimization model is constructed to obtain the equivalent consumption price optimization results;
[0014] Based on the optimized equivalent consumption price, constraints for trading surplus new energy are constructed.
[0015] Based on the optimization results of the equivalent absorption price and the calculation results of the constraints of the surplus renewable energy trading, a regional power grid surplus renewable energy trading model based on the equivalent absorption price is constructed to obtain the optimization results of the regional power grid's surplus renewable energy absorption capacity.
[0016] Furthermore, the steps for assessing the limited renewable energy capacity in each time period within the assessment area include:
[0017] S1: Based on the load forecast dataset, the new energy forecast dataset, and the evaluation results of the power grid transmission capacity, calculate the sum of squares of the limited capacity deviations of each new energy power station in each time period;
[0018] S2: Calculate the constraints on the restricted capacity of new energy sources in the region for each time period. The constraints include: power constraints on the operating section and transmission capacity constraints on the operating section.
[0019] S3: Based on the sum of squares of the limited capacity deviations of each new energy power station in each time period and the constraints, perform linear calculations to obtain the limited capacity of new energy in each time period within the region.
[0020] Furthermore, the equivalent absorption price optimization model is constructed, including:
[0021] Based on the expected transaction price and the calculation results of the restricted capacity of new energy sources in the region for each time period, the equivalent power consumption is calculated. The formula for calculating the equivalent power consumption is as follows:
[0022]
[0023] Among them, F S To determine the equivalent amount of electricity absorbed, ΔT represents the number of optimization periods. For renewable energy power plants, the additional capacity to absorb electricity demand during time period t is determined by the demand response mechanism of electricity users. For electricity users, the demand response capacity during time period t (b) The equivalent consumption price declared by new energy power plants and power users, respectively, N T To evaluate the number of time periods, N N This refers to the number of new energy power plants.
[0024] Furthermore, the constraints for the trading of surplus renewable energy are constructed, including: constraints on the incremental operating section, trading price constraints, constraints on the newly added renewable energy absorption capacity, and constraints on the demand response of electricity users. The calculation formulas are as follows:
[0025]
[0026] p n ≥p b
[0027]
[0028]
[0029] Where, N N For the number of new energy power plants, ΔP s,t This represents the incremental constraint of the operating section, that is, the capacity margin of the operating section in time period t (s).
[0030] Transaction price constraints include: p n Expected transaction price and p of new energy power plants b Electricity users submit their expected transaction prices;
[0031] This indicates the constraint on the newly added renewable energy consumption capacity, that is, the newly added consumption capacity of renewable energy power plants in time period t through the demand response of electricity users;
[0032] This represents the restricted capacity of a new energy power plant during time period t (n-th time).
[0033] This represents the demand response constraint for electricity users, specifically the demand response capacity for electricity users during time period t (b). This represents the maximum responsive capacity for power user b during time period t.
[0034] Furthermore, the regional power grid surplus renewable energy trading model based on equivalent consumption price includes: performing linear solution operations through the constraints of the equivalent consumption power and the surplus renewable energy trading to obtain the optimization results of the regional power grid's surplus renewable energy consumption capacity.
[0035] In addition, this application also provides a regional power grid surplus renewable energy trading system based on equivalent consumption price, including: a data acquisition module for collecting load forecast datasets, renewable energy forecast datasets and evaluating power grid transmission capacity;
[0036] The surplus renewable energy restricted capacity assessment module is used to assess the renewable energy restricted capacity in the region for each time period based on the load forecast dataset, renewable energy forecast dataset, and the assessment results of the power grid transmission capacity.
[0037] The market application module is used to submit market applications based on the calculation results of the restricted capacity of new energy sources in the region for each time period, and to obtain the expected transaction price.
[0038] The equivalent consumption price optimization module is used to construct an equivalent consumption price optimization model based on the expected transaction price and the calculation results of the restricted capacity of new energy in the region for each time period, and to obtain the equivalent consumption price optimization results.
[0039] The surplus new energy trading constraint calculation module is used to construct the constraints for surplus new energy trading based on the equivalent consumption price optimization results.
[0040] The surplus renewable energy trading module is used to construct a regional power grid surplus renewable energy trading model based on the equivalent consumption price optimization results and the calculation results of the constraints of the surplus renewable energy trading, and to obtain the optimization results of the regional power grid's surplus renewable energy consumption capacity.
[0041] Furthermore, the surplus renewable energy restricted capacity assessment module includes:
[0042] The unit for calculating the sum of squares of the limited capacity deviation of new energy power plants calculates the sum of squares of the limited capacity deviation of each new energy power plant in each time period based on the load forecast dataset, the new energy forecast dataset, and the evaluation results of the power grid transmission capacity.
[0043] The constraint calculation unit for the limited capacity of new energy calculates the constraint conditions for the limited capacity of new energy in each time period within the region. The constraint conditions include: power constraints of the operating section and transmission capacity constraints of the operating section.
[0044] The renewable energy restricted capacity calculation unit is used to perform linear calculations based on the sum of squares of the restricted capacity deviations of each renewable energy power station in each time period and the constraints, to obtain the renewable energy restricted capacity in the region for each time period.
[0045] Furthermore, the construction of the equivalent absorption price optimization model includes:
[0046] Based on the expected transaction price and the calculation results of the restricted capacity of new energy sources in the region for each time period, the equivalent power consumption is calculated. The formula for calculating the equivalent power consumption is as follows:
[0047]
[0048] Among them, F S To determine the equivalent amount of electricity absorbed, ΔT represents the number of optimization periods. For renewable energy power plants, the additional capacity to absorb electricity demand during time period t is determined by the demand response mechanism of electricity users. For electricity users, the demand response capacity during time period t (b) The equivalent consumption price declared by new energy power plants and power users, respectively, N T To evaluate the number of time periods, N N This refers to the number of new energy power plants.
[0049] The technical solution provided in this application can include the following beneficial effects: by collecting load forecast datasets and new energy forecast datasets and evaluating the power grid transmission capacity, assessing the restricted capacity of new energy in each time period within the region, conducting market bidding, and constructing a regional power grid surplus new energy trading model based on equivalent consumption price, the optimization results of the regional power grid surplus new energy consumption capacity are obtained. This application effectively solves the problem of surplus new energy consumption under regional power grid constraints and improves the new energy consumption capacity.
[0050] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description
[0051] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0052] Figure 1 This is a flowchart of a method for trading surplus renewable energy in a regional power grid based on an equivalent consumption price, provided in one embodiment of this application.
[0053] Figure 2 This is a structural diagram of regional power grid surplus renewable energy trading based on equivalent consumption price, provided in another embodiment of this application. Detailed Implementation
[0054] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.
[0055] In existing technologies, grid congestion restricts the consumption of new energy sources, resulting in wind and solar power curtailment exceeding 50% of the total amount of wind and solar power curtailed.
[0056] In view of this, the purpose of this application is to provide a method and system for trading surplus renewable energy in regional power grids based on equivalent consumption prices, so as to overcome the problem of renewable energy consumption under grid congestion in the prior art, and improve the renewable energy consumption capacity by effectively solving the problem of surplus renewable energy consumption under regional power grid constraints.
[0057] Figure 1This is a flowchart illustrating a method for trading surplus renewable energy in a regional power grid based on an equivalent absorption price, according to one embodiment of this application. Please refer to... Figure 1 This embodiment provides a method for trading surplus renewable energy in a regional power grid based on equivalent consumption prices, including the following steps:
[0058] S1. Collect load forecast datasets and renewable energy forecast datasets and assess grid transmission capacity;
[0059] S2. Based on the load forecast dataset, renewable energy forecast dataset, and the evaluation results of grid transmission capacity, assess the renewable energy capacity constraints in the region for each time period.
[0060] In this embodiment of the application, the assessment of the restricted capacity of new energy sources in different time periods within the assessment area specifically includes the following steps:
[0061] S21: Based on the load forecast dataset, the new energy forecast dataset, and the evaluation results of the power grid transmission capacity, calculate the sum of squares of the limited capacity deviations of each new energy power station in each time period;
[0062] Specifically, the purpose of this step is to assess the restricted capacity of renewable energy in the restricted area during different time periods based on load forecasting, renewable energy forecasting, and grid transmission capacity.
[0063] In this embodiment, the optimization model for assessing and optimizing renewable energy capacity constraints aims to make the proportion of renewable energy capacity constraints as similar as possible across different time periods, and can be expressed as follows:
[0064]
[0065] In the formula, F A N represents the sum of squares of the restricted capacity deviations of each new energy power station in each time period. T N represents the number of evaluation periods. N This represents the number of new energy power plants. γ n,t This represents the proportion of restricted capacity of a new energy power plant during time period t (n-th time period). The percentage of renewable energy power plants subject to load balancing constraints during time period t.
[0066] The renewable energy curtailment ratio is the ratio of curtailed capacity to projected power generation, while the balanced curtailment ratio is the average curtailment ratio of all renewable energy power plants, which can be expressed as:
[0067]
[0068]
[0069] In the formula, These represent the restricted capacity and predicted power output of the new energy power plant during time period t, respectively.
[0070] S22: Calculate the constraints on the restricted capacity of new energy sources in the region for each time period. The constraints include: power constraints on the operating section and transmission capacity constraints on the operating section.
[0071] Specifically, the constraints of the renewable energy capacity constraint assessment and optimization model include operating section power constraints and operating section transmission capacity constraints, which can be expressed as:
[0072]
[0073]
[0074] In the formula, P s,t The power during time period t at the operating section. G n,s G b,s P represents the power generation output of the new energy power plant during time period n t, the predicted load at load node b during time period t, and the power transfer factor between the operating section and the load. s Max The transmission capacity limit for the operating section s.
[0075] S23: Based on the sum of squares of the limited capacity deviations of each new energy power station in each time period and the constraints, perform linear calculations to obtain the limited capacity of new energy in each time period within the region.
[0076] Specifically, in this embodiment, the optimization model for assessing the limited capacity of new energy sources can be expressed as follows:
[0077] Min F A
[0078]
[0079] In the formula, Min indicates that the optimization model is a minimization optimization problem, and st represents the constraints that need to be considered.
[0080] This model is essentially a linear programming problem, which can be solved using commercial planning software such as Cplex or the simplex method. In practice, the Cplex software package is generally used. By inputting the boundary data according to its format and calling the software package, the solution can be obtained, and the result is the restricted capacity of new energy sources in the region for each time period.
[0081] In particular, the renewable energy limited capacity evaluation model in this application mainly considers the case without conventional power sources. For grids with conventional power sources, it can be further improved by adding conventional power source peak-shaving constraints.
[0082] When multiple renewable energy power plants are involved, the ratio of the restricted capacity of each renewable energy power plant to its predicted power output should be consistent. A renewable energy restricted capacity assessment and optimization model can be used to assess the restricted capacity of renewable energy plants.
[0083] S3. Based on the calculation results of the restricted capacity of new energy sources in the region for each time period, conduct market bidding and obtain the expected transaction price;
[0084] In this embodiment, the purpose of this step is to organize new energy enterprises and power users to conduct market declarations for demand response.
[0085] Specifically, new energy companies can declare their expected transaction prices for participating in user demand response based on their limited capacity.
[0086] Furthermore, electricity users within grid-restricted areas can declare the response electricity volume, response price, and response period for their participation in user demand response, based on their own production needs.
[0087] S4. Based on the expected transaction price and the calculation results of the restricted capacity of new energy in the region at different times, construct an equivalent consumption price optimization model and obtain the equivalent consumption price optimization results;
[0088] In this embodiment, the purpose of this step is to construct an optimization objective for surplus renewable energy trading under grid constraints, maximizing renewable energy consumption at an equivalent absorption price. The purpose of surplus renewable energy trading is to increase renewable energy consumption by incentivizing electricity users' demand response. In this problem, the location of electricity users and renewable energy power plants, the expected trading price, and the user's demand response capacity all affect surplus renewable energy trading.
[0089] Specifically, an equivalent absorption price index is proposed to assess the difference between the transaction prices declared by renewable energy power plants and electricity users within a restricted area and the renewable energy absorption capacity of their respective nodes. The equivalent absorption price for a renewable energy power plant is the ratio of its declared price to the power transfer factor of its node. That is, the higher its expected transaction price, the higher its ranking among renewable energy power plants; conversely, the smaller its node's power transfer factor, the greater the renewable energy output it can absorb under an equal change in the power transmission capacity of its operating section. The equivalent absorption price for an electricity user is the product of its declared price and the power transfer factor of its node. That is, the higher its expected transaction price, the higher its ranking among electricity users; conversely, the larger its node's power transfer factor, the greater the renewable energy output it can absorb under an equal change in the power transmission capacity of its operating section. Therefore, the equivalent absorption prices for renewable energy power plants and electricity users can be expressed as follows:
[0090]
[0091]
[0092] In the formula, The equivalent consumption price declared by new energy power plants and power users, respectively, p n p bThese are the expected transaction prices submitted by new energy power plants and electricity users, respectively.
[0093] Preferably, under the equivalent consumption price model, the optimization objective of surplus renewable energy trading can be expressed as maximizing the equivalent consumption of electricity, which can be represented as:
[0094]
[0095] In the formula, F S This represents the equivalent electricity consumption under the equivalent consumption price model. ΔT represents the number of optimization periods. These represent the newly added absorption capacity of new energy power plants during time period n t through demand response from electricity users, and the demand response capacity of electricity users during time period b t, respectively.
[0096] S5. Based on the optimization results of the equivalent consumption price, construct the constraints for the trading of surplus new energy;
[0097] The purpose of this step is to establish constraints for trading surplus renewable energy. The constraints to be considered include constraints on the incremental operating capacity, trading prices, new renewable energy absorption capacity, and electricity user demand response, which can be expressed as:
[0098]
[0099] p n ≥p b (11)
[0100]
[0101]
[0102] In the formula, N N For the number of new energy power plants, ΔP s,t This represents the incremental constraint of the operating section, that is, the capacity margin of the operating section in time period t (s). This represents the maximum responsive capacity for power user b during time period t.
[0103] Transaction price constraints include: p n Expected transaction price and p of new energy power plants b Electricity users submit their expected transaction prices;
[0104] This indicates the constraint on the newly added renewable energy consumption capacity, that is, the newly added consumption capacity of renewable energy power plants in time period t through the demand response of electricity users;
[0105] This represents the restricted capacity of a new energy power plant during time period t (n-th time).
[0106] This represents the demand response constraint for electricity users, specifically the demand response capacity for electricity users during time period t (b). This represents the maximum responsive capacity for power user b during time period t.
[0107] S6. Based on the optimization results of the equivalent consumption price and the calculation results of the constraints of the surplus renewable energy trading, construct a regional power grid surplus renewable energy trading model based on the equivalent consumption price, and obtain the optimization results of the regional power grid surplus renewable energy consumption capacity.
[0108] In this embodiment, the purpose of this step is to construct a regional power grid surplus renewable energy trading model based on equivalent absorption price, thereby improving the renewable energy absorption capacity. This model can be expressed as:
[0109] Max F S
[0110]
[0111] In the formula, Max indicates that the optimization model is a maximization optimization problem. This model is essentially a linear programming problem, which can be solved using commercial planning software such as Cplex or the simplex method. In practice, the Cplex software package is generally used. By inputting boundary data according to its format and calling the software package, the solution can be obtained. The result is the optimization result of the new energy absorption capacity.
[0112] Example 2
[0113] Figure 2 This is a structural diagram illustrating the trading of surplus renewable energy in a regional power grid based on equivalent absorption prices, according to one embodiment of this application. Please refer to... Figure 2 This embodiment provides a regional power grid surplus renewable energy trading system based on equivalent consumption price, including:
[0114] Data acquisition module 101 is used to collect load forecast datasets and new energy forecast datasets and to evaluate the power grid transmission capacity;
[0115] The surplus renewable energy restricted capacity assessment module 102 is used to assess the renewable energy restricted capacity in each time period within the region based on the load forecast dataset, the renewable energy forecast dataset, and the assessment results of the power grid transmission capacity.
[0116] In this embodiment, the surplus renewable energy restricted capacity assessment module specifically includes the following:
[0117] The unit for calculating the sum of squares of the limited capacity deviation of new energy power plants calculates the sum of squares of the limited capacity deviation of each new energy power plant in each time period based on the load forecast dataset, the new energy forecast dataset, and the evaluation results of the power grid transmission capacity.
[0118] The constraint calculation unit for the limited capacity of new energy calculates the constraint conditions for the limited capacity of new energy in each time period within the region. The constraint conditions include: power constraints of the operating section and transmission capacity constraints of the operating section.
[0119] The renewable energy restricted capacity calculation unit is used to perform linear calculations based on the sum of squares of the restricted capacity deviations of each renewable energy power station in each time period and the constraints, to obtain the renewable energy restricted capacity in the region for each time period.
[0120] The market application module 103 is used to apply for market access based on the calculation results of the restricted capacity of new energy in the region for each time period and to obtain the expected transaction price.
[0121] The equivalent consumption price optimization module 104 is used to construct an equivalent consumption price optimization model based on the expected transaction price and the calculation results of the restricted capacity of new energy in the region for each time period, and to obtain the equivalent consumption price optimization results.
[0122] The surplus new energy trading constraint calculation module 105 is used to construct the constraints for surplus new energy trading based on the equivalent consumption price optimization results.
[0123] The surplus renewable energy trading module 106 is used to construct a regional power grid surplus renewable energy trading model based on the equivalent absorption price optimization results and the calculation results of the constraints of the surplus renewable energy trading, and to obtain the optimization results of the regional power grid's surplus renewable energy absorption capacity.
[0124] It is understood that the same or similar parts in the above embodiments can be referred to each other, and the contents not described in detail in some embodiments can be referred to the same or similar contents in other embodiments.
[0125] It should be noted that in the description of this application, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, in the description of this application, unless otherwise stated, "a plurality of" means at least two.
[0126] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the function involved, as will be understood by those skilled in the art to which embodiments of this application pertain.
[0127] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.
[0128] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.
[0129] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.
[0130] The storage media mentioned above can be read-only memory, disk, or optical disk, etc.
[0131] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.
[0132] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.
Claims
1. A regional power grid surplus renewable energy trading method based on equivalent consumption price, characterized in that, include: Collect load forecast datasets and renewable energy forecast datasets and assess grid transmission capacity; Based on the load forecast dataset, the new energy forecast dataset, and the evaluation results of the power grid transmission capacity, the restricted capacity of new energy sources in each time period within the evaluation area is assessed. Based on the calculation results of the restricted capacity of new energy sources in the region for each time period, market applications are submitted to obtain the expected transaction price; Based on the expected transaction price and the calculation results of the restricted capacity of new energy in the region for each time period, an equivalent consumption price optimization model is constructed to obtain the equivalent consumption price optimization results; Based on the optimized equivalent consumption price, constraints for trading surplus new energy are constructed. Based on the optimization results of the equivalent absorption price and the calculation results of the constraints of the surplus renewable energy trading, a regional power grid surplus renewable energy trading model based on the equivalent absorption price is constructed to obtain the optimization results of the regional power grid's surplus renewable energy absorption capacity. The steps for assessing the limited renewable energy capacity in each time period within the assessment area include: S1: Based on the load forecast dataset, the new energy forecast dataset, and the evaluation results of the power grid transmission capacity, calculate the sum of squares of the limited capacity deviations of each new energy power station in each time period; S2: Calculate the constraints on the restricted capacity of new energy sources in the region for each time period. The constraints include: power constraints on the operating section and transmission capacity constraints on the operating section. S3: Based on the sum of squares of the restricted capacity deviations of each new energy power station in each time period and the constraints, perform linear calculations to obtain the restricted capacity of new energy in each time period within the region; Constructing the equivalent absorption price optimization model includes: Based on the expected transaction price and the calculation results of the restricted capacity of new energy sources in the region for each time period, the equivalent power consumption is calculated. The formula for calculating the equivalent power consumption is as follows: in, To achieve equivalent power consumption, To optimize the number of time periods, For new energy power plants Time period Increased power consumption capacity through demand response by electricity users For electricity users Time period Demand response capacity , These are the equivalent consumption prices declared by new energy power plants and electricity users, respectively. To assess the number of time periods, This refers to the number of new energy power plants; The constraints for the trading of surplus renewable energy include: incremental constraints on operating sections, trading price constraints, constraints on newly added renewable energy absorption capacity, and constraints on electricity user demand response. The calculation formulas are shown below: in, For the number of new energy power plants, This indicates the incremental constraint of the operating section, i.e., the operating section. Time period Capacity margin; Transaction price constraints include: Expected transaction price of new energy power plants and Electricity users submit their expected transaction prices; This indicates the constraint on the newly added capacity for renewable energy consumption, i.e., renewable energy power plants. Time period Increased capacity through demand response to electricity users; Indicates new energy power station Time period Limited capacity; This represents the demand response constraint for electricity users, i.e., electricity users Time period Demand response capacity; Indicates electricity user Time period Maximum responsive capacity; The regional power grid surplus renewable energy trading model based on equivalent consumption price includes: performing linear calculations based on the equivalent consumption power and the constraints of the surplus renewable energy trading to obtain the optimization results of the regional power grid's surplus renewable energy consumption capacity.
2. A regional power grid surplus renewable energy trading system based on equivalent absorption price, applied to the regional power grid surplus renewable energy trading method based on equivalent absorption price described in claim 1. Its features are, Includes: a data acquisition module, used to collect load forecast datasets, renewable energy forecast datasets, and assess grid transmission capacity; The surplus renewable energy restricted capacity assessment module is used to assess the renewable energy restricted capacity in the region for each time period based on the load forecast dataset, renewable energy forecast dataset, and the assessment results of the power grid transmission capacity. The market application module is used to submit market applications based on the calculation results of the restricted capacity of new energy sources in the region for each time period, and to obtain the expected transaction price. The equivalent consumption price optimization module is used to construct an equivalent consumption price optimization model based on the expected transaction price and the calculation results of the restricted capacity of new energy in the region for each time period, and to obtain the equivalent consumption price optimization results. The surplus new energy trading constraint calculation module is used to construct the constraints for surplus new energy trading based on the equivalent consumption price optimization results. The surplus renewable energy trading module is used to construct a regional power grid surplus renewable energy trading model based on the equivalent consumption price optimization results and the calculation results of the constraints of the surplus renewable energy trading, and to obtain the optimization results of the regional power grid's surplus renewable energy consumption capacity. The surplus renewable energy restricted capacity assessment module includes: The unit for calculating the sum of squares of the limited capacity deviation of new energy power plants calculates the sum of squares of the limited capacity deviation of each new energy power plant in each time period based on the load forecast dataset, the new energy forecast dataset, and the evaluation results of the power grid transmission capacity. The constraint calculation unit for the limited capacity of new energy calculates the constraint conditions for the limited capacity of new energy in each time period within the region. The constraint conditions include: power constraints of the operating section and transmission capacity constraints of the operating section. The renewable energy restricted capacity calculation unit is used to perform linear calculations based on the sum of squares of the restricted capacity deviations of each renewable energy power station in each time period and the constraints, to obtain the renewable energy restricted capacity in the region for each time period. The construction of the equivalent absorption price optimization model includes: Based on the expected transaction price and the calculation results of the restricted capacity of new energy sources in the region for each time period, the equivalent power consumption is calculated. The formula for calculating the equivalent power consumption is as follows: in, To achieve equivalent power consumption, To optimize the number of time periods, For new energy power plants Time period Increased power consumption capacity through demand response by electricity users For electricity users Time period Demand response capacity , These are the equivalent consumption prices declared by new energy power plants and electricity users, respectively. To assess the number of time periods, This refers to the number of new energy power plants.