Time-sharing green evidence value equivalent dynamic evaluation method and system

Abstract

The invention provides a time-sharing green evidence value equivalent dynamic evaluation method and system, and relates to the related technical field of power markets and green energy certificates, and the method comprises the steps: constructing a power spot market clearing model according to collected multi-dimensional data in a power spot market, and solving the optimal economic dispatching output of a unit; taking the optimal economic dispatching output as a boundary condition, carrying out carbon emission optimization on the premise of not changing a segmented transaction result, and calculating marginal carbon emission of each node; on the basis of marginal carbon emission of each node, by taking a whole network kilowatt-hour electricity carbon emission reference value as a reference, accounting a green certificate value equivalent of each node at each moment, and completing conversion with an actual green certificate number; and based on the green certificate value equivalent of the power generation side, calculating the bearing amount of the renewable energy consumption responsibility weight of the user side and the assessment completion condition, and carrying out a green certificate market transaction. According to the method, the green certificate value can be finely and dynamically evaluated, and a new technical support is provided for the electricity market and the related technology of the green energy certificate.

Description

Technical Field

[0001] This invention relates to the technical field of electricity markets and green energy certificates, and more specifically, to a method and system for dynamic evaluation of the value equivalent of time-of-use green certificates. Background Technology

[0002] Green electricity certificates (hereinafter referred to as "green certificates") are credentials that recognize the environmental value of electricity generated by renewable energy power generation companies and are an important policy tool for promoting the consumption of renewable energy. Specifically, one green certificate is issued for every megawatt-hour of renewable energy fed into the grid, and the value of each green certificate is considered equivalent. However, this "uniform" green certificate value system ignores the spatiotemporal differences in carbon emissions from the power system. The carbon emission intensity of the power system exhibits a dynamic spatiotemporal distribution with changes in load fluctuations, unit combinations, and network topology. During periods of high renewable energy generation and low net carbon emission intensity, the marginal carbon reduction contribution per unit of green electricity is small; conversely, during peak hours and other periods when renewable energy output is insufficient and power generation mainly relies on high-carbon fossil fuel units, the marginal contribution of per unit of green electricity to replacing high-carbon electricity and reducing system carbon emissions is significant. Existing technology treats the value of green certificates across different times and spaces as equal, failing to truly reflect the differences in their environmental value and causing value distortion. This prevents it from providing an effective price signal to guide optimal resource allocation and may lead to a mismatch between renewable energy investment and actual system demand.

[0003] Therefore, there is an urgent need in this field for a new method that can evaluate the value of green certificates in a refined and dynamic way, so as to accurately measure the environmental value of green electricity and guide the high-quality development of the new energy industry. Summary of the Invention

[0004] To address the problems of inaccurate environmental value and market signal failure caused by the "homogenization" of green certificate value in existing technologies, the purpose of this invention is to provide a time-sharing green certificate value equivalent dynamic evaluation technology, which aims to achieve refined measurement of green certificate value in both time and space dimensions.

[0005] To achieve the above technical objectives, this application provides a method for dynamic evaluation of the equivalent value of time-sharing green certificates, comprising the following steps: Based on the collected bidding data of market participants in the electricity spot market, unit technical parameters, system topology parameters, and carbon emission parameters of fossil fuel generator units, an electricity spot market clearing model is constructed to solve for the optimal economic dispatch output of the units; Using the optimal economic scheduling output as the boundary condition, carbon emission optimization is carried out without changing the segmented transaction results, and the marginal carbon emissions of each node are calculated. Based on the marginal carbon emissions of each node, and with the benchmark value of carbon emissions per kilowatt-hour of the entire grid as a reference, the equivalent value of green certificates at each time and at each node is calculated, and the conversion with the actual number of green certificates is completed. Based on the equivalent value of green certificates on the power generation side, calculate the amount of renewable energy consumption responsibility weight to be borne by users and the assessment and completion status, and carry out green certificate market transactions.

[0006] Preferably, in the process of obtaining the optimal economic dispatch output, a sparse modeling approach is used to construct a power spot market clearing model, wherein the objective function is: In the formula, This represents the price quoted by power generation entity i at time t in segment s. Let I represent the winning bid amount of power generation entity i in segment s at time t, where I, T, and S represent the set of market entities, the set of time periods, and the set of segment numbers, respectively. Constraints include: In the above constraint: This represents the electricity load of the d-th user at time t. , , Let and represent the sets of users, renewable energy generators, and fossil fuel generators at node n, respectively. This represents the line reactance value connecting node n and node m. , These represent the voltage phase angles at nodes n and m, respectively. Let m represent the set of nodes connected to node n, where n and m are both node numbers. Let represent the output value of the r-th renewable energy unit at time t. Let represent the output value of the i-th fossil fuel generator unit at time t. This represents the declared power limit of fossil fuel generator unit i at time t in segment s. , Let represent the lower and upper limits of the output of fossil fuel generator set i at time t, respectively. , They are respectively The Lagrange multipliers corresponding to the lower and upper limits of the trading volume, This represents the declared power limit of fossil fuel generator unit i at time t in segment s. , Let represent the lower and upper limits of the output of fossil fuel generator unit i at time t, respectively. , They are respectively The Lagrange multipliers corresponding to the lower and upper limits of the trading volume, This represents the power flow transmission limit of the line between node n and node m, where n=ref represents the reference node of the system.

[0007] Preferably, when calculating the marginal carbon emissions at each node, the objective function and constraints are adjusted by constructing a carbon-coupled emission reduction scheduling model, and the objective function is adjusted to: in, This represents the output value of coal-fired power generating units in the new stage scheduling model. , , These are the quadratic coefficient, linear coefficient, and constant term of the coal consumption curve for fossil fuel generator unit i, respectively. The constraint conditions are adjusted as follows: For each unit, find the last transaction segment at each time point, and the selection principle is as follows: Non-zero, and If the value is 0, then the output force at the end of the (s+1)th segment is defined as... ; The constraints are adjusted as follows: In the formula, The variables that need to be solved in the second-stage model, Lagrange multipliers for nodal power balance constraints; Solve the model and obtain the dual variables of the equilibrium constraints. This represents the marginal carbon emissions of the system. .

[0008] Preferably, when calculating the equivalent value of green certificates at each time point and node, the benchmark value of carbon emissions per kilowatt-hour of the entire grid is used as a reference, through... By comparing the quantitative value with the benchmark value, the value of green certificates at each time point and node can be accurately calculated.

[0009] Preferably, when accurately calculating the equivalent value of green certificates at each time point and node, the objective function value is used as the basis. and total power generation of the system Calculate the baseline value of carbon emissions per kilowatt-hour of electricity generated by the entire grid. : Calculate the equivalent value of green certificates for each node at each time step. For each node n at time t, use the marginal carbon emission intensity of that node. Compared with the benchmark value of carbon emissions per kilowatt-hour of electricity in the whole grid The ratio of the two values ​​is used as the equivalent value of the green certificate at that node and at that moment. ; ; The equivalent value of green certificates is balanced and converted with the power generation of renewable energy units, and the conversion factor is calculated. This represents the environmental value of 1 MWh of renewable energy generation equivalent to the value of 1 green certificate. In the formula, The amount of electricity generated by renewable energy units during the accounting period. , This represents the total amount of green certificate equivalent within the statistical accounting period. , This represents the renewable energy power generation output at node n.

[0010] Standard green certificates will be issued for each renewable energy unit, with the number of certificates issued being [number missing]. .

[0011] Preferably, before conducting green certificate market transactions, the amount of renewable energy consumption responsibility weight to be borne by users and the assessment and completion status should be calculated. The assessment amount to be borne by users is determined by the method of calculating the carbon emission equivalent of the user's electricity consumption at that node. : In the formula, This represents the equivalent value of the green certificate of the node where user u is located.

[0012] Based on the constraint requirements of the renewable energy power consumption responsibility weight Further calculate the final assessment score for each user. .

[0013] Preferably, when conducting green certificate market transactions, the number of green certificates issued, their equivalent value, and surplus status on the power generation side are publicized, along with the green certificate demand information on the power consumption side; listing and auction trading modes are supported, and the optimal counterparty is selected for both parties through intelligent matching algorithms; the entire process of transaction offer initiation, contract generation, and settlement is processed online, and transaction data is recorded simultaneously to form an immutable transaction ledger.

[0014] Regarding the same inventive concept, this invention also discloses a dynamic evaluation system for the equivalent value of time-sharing green certificates, comprising: Multi-source data acquisition module: used to complete the acquisition and preprocessing of multi-dimensional data, and output standardized data marts; Economic dispatch output calculation module: used to build and solve the electricity spot market clearing model and output the optimal economic dispatch result; Node marginal carbon emission calculation module: used to build a carbon emission reduction optimization scheduling model and output node marginal carbon emission data; The time-sharing green certificate value equivalent calculation module is used to calculate the green certificate value equivalent and complete the conversion with the actual number of green certificates; User-side consumption responsibility assessment module: used to calculate the completion status of user-side consumption responsibility assessment and generate assessment reports; Green Certificate Market Transaction Support Module: This module provides functions such as green certificate information disclosure, transaction matching, process management, and data traceability.

[0015] The present invention discloses the following technical effects: (1) It has realized the refinement and dynamization of the value of green certificates and accurately guided the synergy of source and load.

[0016] This invention constructs a time-of-use green certificate value equivalent that dynamically changes over time by coupling the real-time node marginal carbon emission intensity of the power system. This not only quantifies the environmental value of renewable energy more scientifically, but more importantly, it conveys a clear price signal to the power generation side to "generate more electricity when the system's carbon intensity is high," while guiding the user side to "use more green electricity when the green certificate value equivalent is low." This bidirectional incentive encourages proactive matching between the source and load sides in the time dimension, systematically improving the capacity for renewable energy absorption.

[0017] (2) A fair and efficient user-side responsibility assessment and market transaction mechanism has been established.

[0018] This invention links users' carbon footprint to their electricity consumption responsibilities, realizing the principle of "whoever emits, is responsible; whoever is friendly, benefits." The assessment cost for users whose electricity consumption patterns match the characteristics of renewable energy output is significantly reduced, while it increases otherwise, reflecting the fairness of the assessment and stimulating demand-side response through economic levers. Simultaneously, the differentiated value of green certificates provides the market with abundant trading instruments, enhancing the liquidity and effectiveness of the green certificate market and making it a key link connecting the electricity market and transmitting environmental value. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the method described in this invention. Figure 2 This is the user load curve in an embodiment of the present invention. Figure 3 This is the renewable energy output curve in the embodiment of the present invention. Figure 4 This is a system topology diagram in an embodiment of the present invention. Figure 5 This is the economic dispatch output result in the embodiment of the present invention. Figure 6 This refers to the marginal carbon emissions of the system in this embodiment of the invention. Figure 7 The equivalent value of the time-sharing green certificate for each node in this embodiment of the invention. Figure 8 The percentage of renewable energy generation and the percentage of standard green certificates in the embodiments of this invention are the percentages of renewable energy unit time-based power generation and the percentages of standard green certificates. Figure 9 The user-side electricity consumption ratio and the assessment load ratio in this embodiment of the invention. Figure 10 This is a schematic diagram of the module architecture of the system described in this invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0022] like Figures 1-10 As shown, this invention provides a dynamic evaluation technology for the equivalent value of time-of-use green certificates, belonging to a generation-side time-of-use green certificate value evaluation technology based on the real-time operating status of the power system. This technology specifically includes the following processes: S1: Collect market participant bidding data, generator unit technical parameters, system topology parameters, and carbon emission parameters of fossil fuel generator units in the electricity spot market.

[0023] S2: Calculate the optimal economic dispatch output of each market participant: By constructing a power spot market clearing model, the optimal economic dispatch output of the generating units is obtained.

[0024] S3: Calculate the marginal carbon emissions of each node: Construct a carbon emission reduction optimization scheduling model, take the economic scheduling result of S2 as the boundary, carry out the second stage of carbon emission optimization without changing the segmented transaction results, and calculate the marginal carbon emissions of each node.

[0025] S4: Calculate the equivalent value of time-of-use green certificates: Using the benchmark value of carbon emissions per kilowatt-hour of the entire network as a reference, calculate the equivalent value of green certificates at each time and at each node, and complete the conversion with the actual number of green certificates.

[0026] S5: Based on the equivalent value of green certificates on the power generation side, calculate the amount of renewable energy consumption responsibility weight to be borne by users and the assessment completion status.

[0027] S6: Conduct green certificate market transactions: Power generation entities and power consumption entities conduct transactions in the green certificate market based on the issued green certificate equivalent and surplus, thereby realizing the market-based circulation of green certificate value.

[0028] In calculating the optimal economic dispatch output of each market participant, a sparse modeling approach is used to construct a power spot market clearing model, where the objective function is: In the formula, represents the bid price of power generation entity i in the s-th segment at time t, and represents the winning bid volume of power generation entity i in the s-th segment at time t. I, T, and S represent the set of market participants, the set of time periods, and the set of segment numbers, respectively.

[0029] The constraints include: In the above constraint: This represents the electricity load of the d-th user at time t. , , Let and represent the sets of users, renewable energy generators, and fossil fuel generators at node n, respectively. This represents the line reactance value connecting node n and node m. , These represent the voltage phase angles at nodes n and m, respectively. This represents the set of nodes connected to node n, where n and m are both node numbers. Let represent the output value of the r-th renewable energy unit at time t. Let represent the output value of the i-th fossil fuel generator unit at time t. This represents the declared power limit of fossil fuel generator unit i at time t in segment s. , Let represent the lower and upper limits of the output of fossil fuel generator set i at time t, respectively. , They are respectively The Lagrange multipliers corresponding to the lower and upper limits of the transaction volume. This represents the declared power limit of fossil fuel generator unit i at time t in segment s. , Let represent the lower and upper limits of the output of fossil fuel generator set i at time t, respectively. , They are respectively The Lagrange multipliers corresponding to the lower and upper limits of the transaction volume. This represents the power flow transmission limit of the line between node n and node m, where n=ref represents the reference node of the system.

[0030] Solving the electricity spot market clearing model consisting of the above objective function and constraints yields the scheduling results for each segment of fossil fuel generating units. And the Lagrange multipliers of the segmented output constraint of the machine components , .

[0031] In step S3, when calculating the marginal carbon emissions of nodes, the objective function and constraints in step S2 are adjusted by constructing a carbon-coupled emission reduction scheduling model: Adjust the objective function as follows: in, This represents the output value of coal-fired power generating units in the new stage scheduling model. , , These are the quadratic coefficient, linear coefficient, and constant term of the coal consumption curve for fossil fuel generator unit i, respectively.

[0032] The constraint conditions are adjusted as follows: For each unit, find the last transaction segment at each time point, and the selection principle is as follows: Non-zero, and If the value is 0, then the output force at the end of the (s+1)th segment is defined as... .

[0033] The constraints are adjusted as follows: In the formula, The variables that need to be solved in the second-stage model, For the Lagrange multiplier of the nodal power balance constraint.

[0034] Solve the model and obtain the dual variables of the equilibrium constraints. This represents the marginal carbon emissions of the system. .

[0035] In step S4, during the calculation of the equivalent value of time-of-use green certificates, the benchmark value of carbon emissions per kilowatt-hour of the entire grid is used as a reference. By comparing the quantitative value with the benchmark value, the value of green certificates at each time point and node can be accurately calculated.

[0036] Based on the optimization objective function value in the model of S3 and total power generation of the system Calculate the baseline value of carbon emissions per kilowatt-hour of electricity generated by the entire grid. Calculate the equivalent value of green certificates for each node at each time step. For each node n at time t, use the marginal carbon emission intensity of that node. Compared with the benchmark value of carbon emissions per kilowatt-hour of electricity in the whole grid The ratio of the two values ​​is used as the equivalent value of the green certificate at that node and at that moment. .

[0037] .

[0038] The equivalent value of green certificates is balanced and converted with the power generation of renewable energy units, and the conversion factor is calculated. This represents the environmental value of 1 MWh of renewable energy generation equivalent to the value of 1 green certificate. In the formula, The amount of electricity generated by renewable energy units during the accounting period. , This represents the total amount of green certificate equivalent within the statistical accounting period. , This represents the renewable energy power generation output at node n.

[0039] Standard green certificates will be issued for each renewable energy unit, with the number of certificates issued being [number missing]. .

[0040] In S5, the amount of renewable energy consumption responsibility weight to be borne by users and the assessment of completion status are calculated. The assessment amount to be borne by users is determined by the method of calculating the carbon emission equivalent of the user's electricity consumption at that node. : In the formula, This represents the equivalent value of the green certificate of the node where user u is located.

[0041] Based on the constraint requirements of the renewable energy power consumption responsibility weight Further calculate the final assessment score for each user. .

[0042] During the S6 process, the number of green certificates issued, their equivalent value, and surplus status of the power generation entities are publicized, as well as the green certificate demand information of the power consumption entities; it supports listing and auction trading modes, and uses intelligent matching algorithms to select the best counterparty for both parties in the transaction; it realizes the online processing of the entire process of transaction offer initiation, contract generation, delivery and settlement, and synchronously records transaction data to form an immutable transaction ledger.

[0043] Based on the above method, the present invention also provides a dynamic assessment system for the value equivalent of time-sharing green certificates, including a multi-source data acquisition module, an economic dispatch output calculation module, a node marginal carbon emission calculation module, a time-sharing green certificate value equivalent accounting module, a user-side consumption responsibility assessment module, and a green certificate market trading support module. Each module achieves data interaction through a standardized data interface. Multi-source data acquisition module: used to execute step S1, complete the acquisition and preprocessing of multi-dimensional data, and output a standardized data mart; Economic dispatch output calculation module: used to execute step S2, construct and solve the electricity spot market clearing model, and output the optimal economic dispatch result; Node marginal carbon emission calculation module: used to execute step S3, build a carbon emission reduction optimization scheduling model, and output node marginal carbon emission data; Time-sharing green certificate value equivalent calculation module: used to execute step S4, calculate the green certificate value equivalent and complete the conversion with the actual number of green certificates; User-side consumption responsibility assessment module: used to execute step S5, calculate the completion status of user-side consumption responsibility assessment and generate an assessment report; Green Certificate Market Transaction Support Module: Used to execute step S6, providing functions such as green certificate information disclosure, transaction matching, process management, and data traceability.

[0044] Example: The present invention provides a method for dynamic evaluation of the equivalent value of time-sharing green certificates, which is implemented according to the following steps: (1) In step S1, market participants’ bid data, generator technical parameters, line parameters, and carbon emission parameters of fossil fuel generators are collected in the spot electricity market.

[0045] 1) Market participant bidding data includes the bid electricity price-electricity combination of fossil fuel power generation enterprises in the electricity spot market and the projected output of renewable energy. Forecasted load of electricity users The electricity price-electricity combination declared by fossil fuel power generation companies in the electricity spot market is expressed in a segmented declaration format. , respectively represent the electricity price and electricity demand declared by power generation entity i during the time interval s at time t.

[0046] 2) The main technical parameter of the unit is its gradient climbing ability. , These represent the up-regulation capability and down-regulation capability of unit i, respectively.

[0047] 3) Line parameters include the line's power flow limit. and line reactance value 4) Carbon emission parameters of fossil fuel power generation units , , Used to represent the coal consumption of unit i This represents the coal consumption at the corresponding power output level.

[0048] (2) In step S2, the optimal economic dispatch output of power generation under the existing reporting data is calculated. By constructing a power spot market clearing model and solving for the optimal economic dispatch output of the unit, the following steps are performed: S21: The objective function for constructing the model is as follows: in, Let be the decision variable for the model's demand solution, representing the winning bid amount of power generation entity i in the s-th segment at time t. Let I represent the price quoted by power generation entity i at time t in segment s, where I, T, and S represent the set of market entities, the set of time periods, and the set of segment numbers, respectively.

[0049] S22: Construct the constraints of the model, and gradually construct the following constraints: 1) Node power balance constraints: The above equation represents the balance constraint between net injection and outflow power at each node. This represents the electricity load of the d-th user at time d. , , Let and represent the sets of users, renewable energy generators, and fossil fuel generators at node n, respectively. This represents the line reactance value connecting node n and node m. , These represent the voltage phase angles at nodes n and m, respectively. This represents the set of nodes connected to node n, where n and m are both node numbers. Let represent the output value of the r-th renewable energy unit at time t. Let represent the output value of the i-th fossil fuel generator unit at time t.

[0050] 2) Unit output constraints: The above formulas respectively represent the segmented transaction sum as the actual output of the generator set, the segmented transaction volume constraint of the generator set, and the upper and lower limits constraint of the generator set's output, where, This represents the declared power limit of fossil fuel generator unit i at time t in segment s. , Let represent the lower and upper limits of the output of fossil fuel generator set i at time t, respectively. , They are respectively The Lagrange multipliers corresponding to the lower and upper limits of the transaction volume.

[0051] 3) Unit ramp-up constraints: The above formula indicates that the output of unit i at any given moment cannot exceed the unit's climbing ability. , These represent the up-regulation capability and down-regulation capability of unit i, respectively.

[0052] 4) Branch flow constraints: The above formula represents the power flow constraints for each line; the actual power flow through each line cannot exceed the line transmission baseline. This represents the power flow transmission limit value of the line between node n and node m.

[0053] 5) Balance node constraints: This indicates that the node with the number ref is set as a balanced node, and its phase angle is set to 0.

[0054] S23: Solve the model. The model is a linear programming model, which can be modeled and solved using solvers such as Gurobi, COPT, and SCIP. The optimal output of the coal-fired power generating unit is obtained after solving. And the Lagrange multipliers constraining the unit output , .

[0055] (3) In step S3, the marginal carbon emission value of each node is calculated. Using the economic scheduling result of S2 as the boundary, a carbon emission reduction optimization scheduling model is constructed. Under the premise of not changing the segmented transaction result, the second stage of carbon emission reduction optimization is carried out, and the marginal carbon emission of each node is calculated. The specific steps are as follows: S31: Construct a new objective function for the carbon emission reduction optimization scheduling model, and adjust the objective function as follows: in, This represents the output value of coal-fired power generating units in the new stage scheduling model. , , These are the quadratic coefficient, linear coefficient, and constant term of the coal consumption curve for fossil fuel generator unit i, respectively.

[0056] S32: The last segment number of each transaction in each time period of the selected unit.

[0057] According to S2 Based on the optimization results, and according to the complementary relaxation theorem and the value characteristics of Lagrange multipliers, the set of fully traded segments, the set of partially traded segments, and the set of untraded segments are identified. Non-zero, When it is 0, To complete the transaction segment; when and All are 0. This refers to a portion of the transactions. =0, When it is not 0, This is a segment that has not yet been traded.

[0058] S33: Reconfigurable unit output constraints: For each unit, find the last transaction segment at each time point, using the following selection criteria: Non-zero, and If the value is 0, then the output force at the end of the (s+1)th segment is defined as... .

[0059] Furthermore, the economic scheduling model in step S2... Modify to the following constraints: For the variables that need to be solved in the second-stage model, the meaning of this constraint is as follows: exist The prefix segment of a transaction must be fully executed because the next segment has already been completed; any adjustments are prohibited (increasing it upwards would exceed the segment's capacity, while decreasing it downwards would leave the next segment without a basis for execution). During a given period, if there are no subsequent transactions, minor adjustments can be made in both directions within that period, provided they do not exceed the upper or lower limits of that period; The subsequent trading segments, i.e., the untraded segments, are strictly locked at 0 to prevent new trading segments from altering the clearing results. Adjustments made according to this method will not change the original economic scheduling results.

[0060] Other constraints are as follows: In the formula, For the Lagrange multiplier of the nodal power balance constraint.

[0061] S34: Solve the model, which is a quadratic programming problem. Solvers such as Guroi, COPT, and SCIP can be used to model and solve the problem, obtaining the output value of the coal-fired power generating unit under the new model. And obtain the dual variables of the balance constraint. This represents the marginal carbon emissions of the system when the load on node n increases by 1 MWh at time t. .

[0062] (4) In step S4, using the overall grid-wide carbon emission benchmark value, calculate the equivalent value of green certificates at each time point and at each node, and complete the conversion with the actual number of green certificates. The steps for calculating the equivalent value of time-of-use green certificates are as follows: S41: Based on the solution results in step S34, calculate the baseline value of carbon emissions per kilowatt-hour for the entire network. , in is the optimal objective function value of the model in step S3, representing the total carbon emissions of all coal-fired power generating units.

[0063] S42: Calculate the equivalent value of green certificates for each node at each time step. For each node n at time t, use the marginal carbon emission intensity of that node. Compared with the benchmark value of carbon emissions per kilowatt-hour of electricity in the whole grid The ratio of the two values ​​is used as the equivalent value of the green certificate at that node and at that moment. .when A value greater than 1 indicates that the marginal carbon reduction contribution of green electricity at that node at that moment is higher than the average level of the entire network, and the value of green certificates receives a premium; when When the value is less than 1, it indicates that the marginal carbon emission reduction contribution of green electricity at that node at that moment is lower than the average level of the entire network, and the value of green certificates is discounted accordingly.

[0064] S43: Convert the value equivalent of green certificates to standard green certificates, first by calculating the on-grid electricity generated by renewable energy power generation enterprises within the accounting period. Then calculate the total amount of green certificate equivalent within the accounting period. , This represents the renewable energy generation output at node n. Finally, the green certificate conversion ratio is calculated. This represents the environmental value of 1 MWh of renewable energy generation equivalent to the value of 1 green certificate.

[0065] S44: Number of standard green certificates to be issued for each renewable energy unit; the number to be issued is... (5) In step S5, calculate the amount of renewable energy consumption responsibility weight to be borne by the user and the assessment completion status. Follow these steps: S51: Calculate the assessment amount that each user should bear under the renewable energy power consumption responsibility weight constraint. The calculation is based on the principle of carbon emission reduction equivalence between the power generation and consumption sides. That is, at the same node and moment, the value of additional electricity consumption on the consumption side is the same as the value of additional renewable energy generation on the power generation side. However, except for green electricity direct connection projects, it is impossible to trace the source of renewable energy power consumed by the consumption side. In order to reflect the time-of-use electricity guidance characteristics, the calculation is first performed according to the time-of-use dimension. Further calculate the carbon emission cost of the electricity consumed by the user, and obtain the time-of-use assessment amount based on the user's electricity consumption and the carbon emission equivalent corresponding to that node. : Based on the constraint requirements of the renewable energy power consumption responsibility weight Further calculate the final assessment score for each user. .

[0066] S52: Calculate the user's renewable energy consumption responsibility weight completion status. When calculating the user's renewable energy consumption responsibility weight completion status, it is necessary to consider green electricity direct connection projects, that is, the user has simultaneously consumed green electricity and purchased corresponding green electricity certificates. This part is based on the actual amount of electricity consumed. The green certificates will be deducted according to the average load standard of the entire network, which recognizes the consumption contribution of direct green electricity connection, while preventing individual users from excessively reducing their assessment volume through high-value direct green electricity connection projects.

[0067] Further, based on the green electricity assessment quota and the deduction amount for direct green electricity connection projects, the completion status of each user's consumption responsibility weight is obtained. .

[0068] If the value is positive, it means that the user has not fulfilled the renewable energy power consumption responsibility weight assessment and needs to make up for the shortfall in the green certificate market; if the value is negative, it means that the user has exceeded the renewable energy power consumption responsibility weight assessment and the surplus consumption value can be sold in the green certificate market.

[0069] (6) In step S6, the power generation entity and the power consumption entity transmit the data to the green certificate trading institution based on the issued green certificate equivalent and surplus status. Trading activities are carried out in the green certificate market to realize the market-based circulation of green certificate value.

[0070] By publicizing the number of green certificates issued, their equivalent value, and surplus for power generation entities, as well as the green certificate demand information for power consumption entities; supporting listing and auction trading models; using intelligent matching algorithms to select the best counterparty for both parties in a transaction; realizing online processing of the entire process from transaction offer initiation, contract generation, and delivery settlement; and synchronously recording transaction data to form an immutable transaction ledger.

[0071] Example: This example uses an IEEE 14-node network structure, and the market participants include 5 thermal power units, 7 electricity users, and 3 renewable energy units. Time t is 24 hours, and the number of bidding segments is 5.

[0072] According to step S1: First, obtain the market participant bidding data, unit technical parameters, system topology parameters, and carbon emission parameters of fossil fuel generator units in the electricity spot market.

[0073] The technical parameters of the unit are shown in Table 1: Table 1 Unit Parameter Table Market price data is applied in practice based on the actual declared quantity and price of each market participant. In this embodiment, the market price data is generated based on the parameters in Table 1. It is assumed that each generator set declares in 5 segments, with the first segment declared based on minimum output, and the remaining 4 segments allocated equally based on remaining capacity. The price is based on the marginal cost of the output load of the corresponding segment. (where x represents cumulative output) is used for declaration, with the coal price assumed to be 1000 yuan / ton. Taking G1 as an example, the 5-segment declaration quantity-price combination is as follows: The load curves of electricity users and the output curves of renewable energy units are as follows: Figure 2 , Figure 3 As shown, they exhibit different time-sharing characteristics.

[0074] Line topology as follows Figure 4 As shown, it contains 14 nodes and 20 lines, where Gi represents fossil fuel generator sets and Ri represents renewable energy generator sets. This indicates the load. Line parameters are shown in Table 2: Table 2 Line Parameters After obtaining all parameters, the objective function and constraints are constructed according to the modeling method in step S2, and the Gurobi solver is used to solve for the optimal output. Figure 5 ), and the Lagrange multipliers of the output constraints of each section of the unit. , .

[0075] Furthermore, the model in S2 is reconstructed based on the modeling method in S3, and new objective functions and constraints are constructed sequentially. The constraints require adjustments to the output of each unit at its marginal segment. First, the Lagrange multipliers of the output constraints for each segment of the units in S2 are used. , Values, filtering criteria are Non-zero, and If the value is 0, then the output force at the end of the (s+1)th segment is defined as... The end segment numbers of each unit at different times are shown in Table 3: Table 3 Last Segment Numbering Further adjustments are made to the marginal segments in Table 3 using the following formula: The model with the adjusted objective function and constraints is solved using Gurobi to obtain new results and equilibrium constraints. dual variables We obtained the marginal carbon emission values ​​of 14 nodes at 24 time points. ( Figure 6 ).

[0076] Further calculations are performed according to step S4, calculating the equivalent value of green certificates for each node, based on the solution results in S3 and the formula. Calculate the baseline value of carbon emissions per kilowatt-hour of electricity generated by the entire grid. The value is 0.6392 tons / MWh.

[0077] Further calculation of the green certificate value equivalent ( Figure 7 ).

[0078] when A value greater than 1 indicates that the marginal carbon reduction contribution of green electricity at that node at that moment is higher than the average level of the entire network, and the value of green certificates receives a premium; when A value less than 1 indicates that the marginal carbon reduction contribution of green electricity at that node at that moment is lower than the average level of the entire grid, and the value of green certificates is discounted accordingly. Among them, at times 10-12, due to the large amount of renewable energy generation and the fact that coal-fired power units are in a high-efficiency processing segment, the value of green certificates at that moment is reduced. At other times, due to the influence of system congestion, different green certificate value equivalents are also reflected.

[0079] Further calculations based on step S43 yielded the corrected result. Value, the total amount of green certificate equivalent within this accounting period. The figure was 19824.49734, and the amount of renewable energy fed into the grid was... ,therefore It is 0.969126611.

[0080] Further based on step S44, according to the formula The number of standard green certificates for each new energy unit is calculated, as shown in Table 4: Table 4 Number of Standard Green Certificates for Each Renewable Energy Unit As shown in Table 4, compared to the sum of power generation at each time point, in terms of standard green certificates, R1 increases accordingly, while R2 and R3 decrease by a certain proportion. Figure 8 It can be seen that R1 generates a higher proportion of electricity during off-peak hours, while R2 and R3 generate a higher proportion of electricity during peak hours. After the impact of the equivalent value of green certificates is added, R1 gains additional green certificate value and can obtain higher returns.

[0081] Further calculations are made on the user-side assessment, and the user-side green certificates are calculated according to step S5, assuming the renewable energy power consumption responsibility weight constraint index. If the percentage is 30%, then the equivalent after assessment is shown in Table 5: Table 5 User-side assessment equivalent As shown in Table 5, comparing User 7 and User 8, after considering the equivalent value of the time-sharing green certificate, User 7's assessment workload decreased significantly (reduced to 82.25% of the original workload), while User 8's assessment workload decreased less significantly, based on the time-sharing percentage. Figure 9 This is because most of User 7's load times are when the green certificate equivalent is low, and the output of renewable energy is also high at this time. The carbon emission impact generated by the system is small, so it bears a lower assessment and can reduce the user's electricity costs.

[0082] After completing the above steps, the equivalent of green certificates issued for renewable energy and the assessment equivalent that users should bear are transmitted to the green certificate trading system. This can provide additional revenue or reduce electricity costs for both the generation and user sides, thereby guiding both sides to change their electricity generation and consumption behavior, ultimately promoting the grid's absorption of new energy and reducing system carbon emissions.

[0083] By applying the time-sharing green certificate value evaluation method of this invention, the efficiency and fairness of the green value system of the power system can be significantly improved in the following aspects: On the generation side, this approach enables a refined assessment and incentive of the environmental value of renewable energy generation. Traditional green certificate mechanisms, based solely on equal issuance of power generation, fail to differentiate the actual contributions of power generation to the system at different times. This method introduces time-of-use value equivalents, allowing units that maintain high output during off-peak grid periods (when system regulation pressure is high and conventional unit output is limited) (such as R1) to receive higher green certificate benefits, accurately compensating for their system regulation and absorption support value. Simultaneously, while the number of green certificates for units concentrated in peak hours (such as R2 and R3) is slightly adjusted, it more accurately reflects their value contribution during periods of high system demand. This differentiated incentive effectively guides renewable energy to optimize its generation timing, proactively align with system operation needs, and promotes source-grid coordination.

[0084] On the user side, a fairer and more reasonable assessment mechanism for the responsibility weighting of green certificate consumption has been established. The traditional "one-size-fits-all" assessment method failed to consider the environmental impact of the temporal characteristics of users' electricity consumption behavior. This method links the assessment amount borne by a user to the "green certificate value equivalent" within their electricity consumption period. For example, User 7, because its load is largely distributed during periods with lower green certificate equivalent (i.e., abundant renewable energy output and low system carbon intensity), has a significantly reduced actual assessment amount (82.25%). This truly reflects the "friendliness" of its electricity consumption behavior to the low-carbon operation of the system, achieving a match between electricity costs and environmental contributions. Conversely, User 8, due to different electricity consumption patterns, experiences a smaller reduction in assessment amount. This guides users to reduce green certificate consumption costs by adjusting their electricity consumption periods (demand-side response) and proactively shift their load to periods of high renewable energy output.

[0085] Regarding the grid's renewable energy integration, this method constructs a market signal bridge connecting the time-series value of power generation with users' electricity consumption behavior. Through the transmission of the time-of-use value of green certificates, it incentivizes renewable energy generators to actively track load or shift to periods with greater absorption capacity, while simultaneously incentivizing users to proactively adapt to the output characteristics of renewable energy. This two-way synergy effectively mitigates the time-series imbalance between renewable energy generation and electricity load. This provides a new market-value-driven approach to improving the overall renewable energy integration capacity of the grid and reducing wind and solar curtailment rates. Furthermore, the "green certificate value equivalent," as a transparent and quantifiable indicator, provides a more refined decision-making reference for grid dispatch and operation, helping to optimize the dispatch priority of renewable energy while ensuring safety.

[0086] In summary, the time-of-use green certificate value evaluation method proposed in this invention transcends the traditional model that solely relies on electricity consumption. By introducing a time-series value dimension, it constructs a dynamic green certificate system that links "generation behavior, system value, and user responsibility." This not only more scientifically assesses and incentivizes the green value of renewable energy, promoting its high-quality development, but also guides electricity consumption towards greener and more flexible consumption patterns. Ultimately, through coordinated efforts across multiple levels—source, grid, and load—it systematically improves the renewable energy absorption capacity and overall operational economy of the power system.

[0087] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0088] In the description of this invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0089] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for dynamic evaluation of the equivalent value of time-sharing green certificates, characterized in that, Includes the following steps: Based on the collected bidding data of market participants in the electricity spot market, unit technical parameters, system topology parameters, and carbon emission parameters of fossil fuel generator units, an electricity spot market clearing model is constructed to solve for the optimal economic dispatch output of the units; Using the optimal economic scheduling output as the boundary condition, carbon emission optimization is carried out without changing the segmented transaction results, and the marginal carbon emissions of each node are calculated. Based on the marginal carbon emissions of each node, and with the benchmark value of carbon emissions per kilowatt-hour of the entire grid as a reference, the equivalent value of green certificates at each time and at each node is calculated, and the conversion with the actual number of green certificates is completed. Based on the equivalent value of green certificates on the power generation side, calculate the amount of renewable energy consumption responsibility weight to be borne by users and the assessment and completion status, and carry out green certificate market transactions.

2. The method for dynamic evaluation of the equivalent value of time-sharing green certificates according to claim 1, characterized in that: In obtaining the optimal economic dispatch output, a sparse modeling approach is used to construct a power spot market clearing model, where the objective function is: In the formula, This represents the price quoted by power generation entity i at time t in segment s. Let I represent the winning bid amount of power generation entity i in segment s at time t, where I, T, and S represent the set of market entities, the set of time periods, and the set of segment numbers, respectively. Constraints include: In the above constraint: This represents the electricity load of the d-th user at time t. , , Let and represent the sets of users, renewable energy generators, and fossil fuel generators at node n, respectively. This represents the line reactance value connecting node n and node m. , These represent the voltage phase angles at nodes n and m, respectively. Let m represent the set of nodes connected to node n, where n and m are both node numbers. Let represent the output value of the r-th renewable energy unit at time t. Let represent the output value of the i-th fossil fuel generator unit at time t. This represents the declared power limit of fossil fuel generator unit i at time t in segment s. , Let represent the lower and upper limits of the output of fossil fuel generator unit i at time t, respectively. , They are respectively The Lagrange multipliers corresponding to the lower and upper limits of the trading volume, This represents the declared power limit of fossil fuel generator unit i at time t in segment s. , Let represent the lower and upper limits of the output of fossil fuel generator unit i at time t, respectively. , They are respectively The Lagrange multipliers corresponding to the lower and upper limits of the trading volume, This represents the power flow transmission limit of the line between node n and node m, where n=ref represents the reference node of the system.

3. The method for dynamic evaluation of the equivalent value of time-sharing green certificates according to claim 2, characterized in that: When calculating the marginal carbon emissions at each node, a carbon-coupled emission reduction scheduling model is constructed to adjust the objective function and constraints. The objective function is adjusted to: in, This represents the output value of coal-fired power generating units in the new stage scheduling model. , , These are the quadratic coefficient, linear coefficient, and constant term of the coal consumption curve for fossil fuel generator unit i, respectively. The constraint conditions are adjusted as follows: For each unit, find the last transaction segment at each time point, and the selection principle is as follows: Non-zero, and If the value is 0, then the output force at the end of the (s+1)th segment is defined as... ; The constraints are adjusted as follows: In the formula, The variables that need to be solved in the second-stage model, Lagrange multipliers for nodal power balance constraints; Solve the model and obtain the dual variables of the equilibrium constraints. This represents the marginal carbon emissions of the system. .

4. The method for dynamic evaluation of the equivalent value of time-sharing green certificates according to claim 3, characterized in that: When calculating the equivalent value of green certificates at each time point and node, the benchmark value of carbon emissions per kilowatt-hour of the entire grid is used as a reference. By comparing the quantitative value with the benchmark value, the value of green certificates at each time point and node can be accurately calculated.

5. The method for dynamic evaluation of the equivalent value of time-sharing green certificates according to claim 4, characterized in that: When accurately calculating the equivalent value of green certificates at each time point and node, the objective function value is used as the basis. and total power generation of the system Calculate the baseline value of carbon emissions per kilowatt-hour of electricity generated by the entire grid. : Calculate the equivalent value of green certificates for each node at each time step. For each node n at time t, use the marginal carbon emission intensity of that node. Compared with the benchmark value of carbon emissions per kilowatt-hour of electricity in the whole grid The ratio of the two values ​​is used as the equivalent value of the green certificate at that node and at that moment. ; ； The equivalent value of green certificates is balanced and converted with the power generation of renewable energy units, and the conversion factor is calculated. This represents the environmental value of 1 MWh of renewable energy generation equivalent to the value of 1 green certificate. In the formula, The amount of electricity generated by renewable energy units during the accounting period. , This represents the total amount of green certificate equivalent within the statistical accounting period. , This represents the renewable energy power generation output at node n; Standard green certificates will be issued for each renewable energy unit, with the number of certificates issued being [number missing]. .

6. The method for dynamic evaluation of the equivalent value of time-sharing green certificates according to claim 5, characterized in that: Before launching the green certificate market, the amount of renewable energy consumption responsibility weight to be borne by users and the assessment status should be calculated. The assessment amount to be borne by users is determined by the method of calculating the carbon emission equivalent of the user's electricity consumption at that node. : In the formula, This represents the equivalent value of the green certificate for the node where user u is located; Based on the constraint requirements of the renewable energy power consumption responsibility weight Further calculate the final assessment score for each user. .

7. The method for dynamic evaluation of the equivalent value of time-sharing green certificates according to claim 6, characterized in that: When conducting green certificate market transactions, the number of green certificates issued, their equivalent value, and surplus status on the power generation side are publicized, along with the green certificate demand information on the power consumption side. The system supports listing and auction trading models, and uses intelligent matching algorithms to select the best counterparty for both parties. It achieves online processing of the entire process from transaction offer initiation to contract generation and settlement, and synchronously records transaction data to form an immutable transaction ledger.

8. A dynamic evaluation system for the equivalent value of time-sharing green certificates, used to implement the dynamic evaluation method for the equivalent value of time-sharing green certificates as described in claim 1, characterized in that, include: Multi-source data acquisition module: used to complete the acquisition and preprocessing of multi-dimensional data, and output standardized data marts; Economic dispatch output calculation module: used to build and solve the electricity spot market clearing model and output the optimal economic dispatch result; Node marginal carbon emission calculation module: used to build a carbon emission reduction optimization scheduling model and output node marginal carbon emission data; The time-sharing green certificate value equivalent calculation module is used to calculate the green certificate value equivalent and complete the conversion with the actual number of green certificates; User-side consumption responsibility assessment module: used to calculate the completion status of user-side consumption responsibility assessment and generate assessment reports; Green Certificate Market Transaction Support Module: This module provides functions such as green certificate information disclosure, transaction matching, process management, and data traceability.

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