Carbon reduction benefit distribution method and device for zero-carbon commercial office park

Abstract

The invention provides a zero-carbon commercial park-oriented carbon reduction benefit distribution method and device, and belongs to the technical field of park carbon reduction. The method comprises the steps of analyzing interactive response requirements and operation regulation and control scene features of a target park and a power grid, and constructing a park power grid interactive regulation and control and flexible resource index system based on an analysis result; based on a park power grid interactive regulation and control and flexible resource index system, constructing a logic regression model which takes a regulation and control mode as an input variable and takes a zero carbon potential index as an output variable; wherein the regulation and control mode comprises an operation mode and an energy consumption equipment regulation and control mode; based on a sensitivity analysis method and a logistic regression model, evaluating the carbon reduction contribution degree of the multiple operation modes and the energy consumption equipment regulation and control modes to the target park; and performing cooperative game behavior analysis on each participant of the target park based on the carbon reduction contribution degree corresponding to each operation mode and the energy consumption equipment regulation and control mode so as to perform carbon reduction benefit distribution on each participant. According to the invention, the carbon reduction effect of a complex park with operation mode difference can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon reduction in parks, and particularly to a carbon reduction benefit distribution method and device for a zero-carbon commercial and office park. Background Art

[0002] To achieve the goals of carbon peak and carbon neutrality, energy is the main battlefield and electricity is the main force. As a concentrated carrier of various types of carbon emission elements such as buildings, energy, and industries, parks are an important front for achieving the "dual carbon" goals. The promotion of their zero-carbon transformation is of great significance for coordinated carbon reduction in multiple fields such as industry, energy, and urban and rural construction.

[0003] Parks have distinct energy usage characteristics, generally showing high energy consumption and high carbon emissions, and the overall layout of parks continues to expand in scale and quantity. In addition, parks have multiple identities as energy users and producers, and aggregate various types of resources such as the power grid, load, and energy storage, with excellent potential and ability for low-carbon / zero-carbon transformation. There are differences in the operation and management models and equipment control methods of each subject in the park, resulting in limitations in determining the carbon reduction benefit sharing mechanism for multiple subjects in complex parks, and the carbon reduction effect still needs to be improved. Summary of the Invention

[0004] Embodiments of the present invention provide a carbon reduction benefit distribution method and device for a zero-carbon commercial and office park to solve the problem of improving the carbon reduction effect in complex parks with different operation models.

[0005] In a first aspect, embodiments of the present invention provide a carbon reduction benefit distribution method for a zero-carbon commercial and office park, including:

[0006] Analyze the interactive response requirements and operation regulation scenario characteristics between the target park and the power grid, as well as the carbon reduction potential of flexible resources on the energy consumption side, energy supply side, and energy storage side of the park, and construct an interactive regulation and flexible resource index system for the park power grid based on the analysis results;

[0007] Based on the interactive regulation and flexible resource index system for the park power grid, construct a logistic regression model with the regulation mode as the input variable and the zero-carbon potential index as the output variable; wherein, the regulation mode includes the operation mode and the energy-consuming equipment control method;

[0008] Based on the sensitivity analysis method and the logistic regression model, evaluate the carbon reduction contribution degrees of various operation models and energy-consuming equipment control methods to the target park;

[0009] Based on the carbon reduction contribution degree corresponding to each operation mode and energy-consuming equipment control method, conduct a cooperative game behavior analysis on each participating subject in the target park to distribute the carbon reduction benefits to each participating subject.

[0010] In a possible implementation, based on the interactive regulation of the park power grid and the flexible resource index system, a logistic regression model with the regulation mode as the input variable and the zero-carbon potential index as the output variable is constructed, including:

[0011] Based on the interactive regulation of the park power grid and the flexible resource index system and the fuzzy comprehensive evaluation method, determine the zero-carbon potential index of multiple different types of parks under each regulation mode;

[0012] Take the regulation mode of each park as the input variable and the corresponding zero-carbon potential index as the output variable to construct a logistic regression model.

[0013] In a possible implementation, the interactive regulation of the park power grid and the flexible resource index system include multiple first-level indicators and multiple second-level indicators; based on the interactive regulation of the park power grid and the flexible resource index system and the fuzzy comprehensive evaluation method, determine the zero-carbon potential index of multiple different types of parks under each regulation mode, including:

[0014] Calculate the membership degree of each second-level indicator to each first-level evaluation grade standard based on the linear membership function to obtain the membership degree vector of each second-level indicator;

[0015] Synthesize the weight distribution vector and each membership degree vector through the synthesis operator to obtain the evaluation matrix of each second-level indicator;

[0016] Normalize the evaluation matrix of each second-level indicator and then synthesize it into the total evaluation matrix;

[0017] Calculate the zero-carbon potential index of multiple different types of parks under each operation mode and energy-consuming equipment regulation method based on the total evaluation matrix and the grade standard matrix.

[0018] In a possible implementation, the first-level indicators include energy efficiency and loss, energy demand management, energy price and market, energy supply and structure, green energy and external power adjustment, and the second-level indicators include distribution network loss rate, energy storage ratio, peak shaving and valley filling volume, system response speed, real-time electricity price, demand elasticity, photovoltaic power generation ratio, wind power generation ratio, hydrogen energy ratio, and green external power adjustment ratio.

[0019] In a possible implementation, based on the sensitivity analysis method and the logistic regression model, evaluate the carbon reduction contribution degree of multiple operation modes and energy-consuming equipment regulation methods to the target park, including:

[0020] Based on the logistic regression model, determine the zero-carbon potential index of the target park under each operation mode and energy-consuming equipment regulation method;

[0021] Based on the zero-carbon potential index of the target park under each operation mode and energy-consuming equipment regulation method, calculate the second-order Sobol index of each operation mode and energy-consuming equipment regulation method as the carbon reduction contribution degree of this operation mode and energy-consuming equipment regulation method.

[0022] In a possible implementation manner, the calculation formula of the second-order Sobol index is:

[0023]

[0024] Among them, S i is the first-order Sobol index, V(·) is the variance, E(·) is the expectation, Y is the output variable, and X i is the i-th input variable, and S ij is the second-order Sobol index.

[0025] In a possible implementation manner, the operation modes include autonomous, outsourced, and consulting; the energy-consuming equipment regulation methods include monitorable and controllable, only monitored and not controlled, and not monitored and not participated in.

[0026] In a possible implementation manner, based on the carbon reduction contribution degree corresponding to each operation mode and energy-consuming equipment regulation method, conduct a cooperative game behavior analysis on each participating entity in the target park, including:

[0027] Take the zero-carbon potential index as the characteristic function value, take the carbon reduction contribution degree after each participating entity joins the alliance as the marginal contribution of this participating entity, and determine the weighting factor based on the number of participating entities in the alliance;

[0028] Calculate the Shapley value of each participating entity, and determine the distribution share of each participating entity based on the proportion of the Shapley values of each participating entity.

[0029] In a second aspect, an embodiment of the present invention provides a carbon reduction benefit distribution device for a zero-carbon commercial and office park, including:

[0030] A system construction module, configured to analyze the interactive response requirements and operation regulation scenario characteristics between the target park and the power grid, as well as the carbon reduction potential of flexible resources on the energy consumption side, energy supply side, and energy storage side of the park, and construct a park power grid interactive regulation and flexible resource index system based on the analysis results;

[0031] A model construction module, configured to construct a logistic regression model with the regulation mode as the input variable and the zero-carbon potential index as the output variable based on the park power grid interactive regulation and flexible resource index system; where the regulation mode includes the operation mode and the energy-consuming equipment regulation method;

[0032] Contribution assessment module, which is used to evaluate the contribution of various operation modes and energy-consuming equipment control methods to carbon reduction in the target park based on sensitivity analysis and logistic regression model;

[0033] The benefit allocation module is used to analyze the cooperative game behavior of each participant in the target park based on the carbon reduction contribution corresponding to each operation mode and energy-consuming equipment control method, so as to allocate carbon reduction benefits to each participant.

[0034] The embodiments of the present invention provide a carbon reduction benefit distribution method and device for a zero-carbon commercial and office park. By studying the energy flow of each flexible resource equipment, a comprehensive carbon reduction effectiveness evaluation method for the park and the power grid is established for parks with different operation and management modes and equipment control methods. The carbon reduction effectiveness is evaluated through the zero-carbon potential index. By evaluating the carbon reduction contribution of multiple users in the park, a carbon reduction benefit sharing mechanism for multiple entities in the park with different operation modes is established. This provides reference experience for similar parks, helps parks across the country develop in a low-carbon and intelligent direction, solves the limitations of existing technologies in dealing with complex park multi-entity carbon reduction benefit sharing mechanisms, meets the market demand for considering the differences in carbon reduction modes of parks, and improves the carbon reduction effect of parks. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0036] Figure 1 It is a flow chart of the implementation of the carbon reduction benefit allocation method for a zero-carbon commercial and office park provided by an embodiment of the present invention;

[0037] Figure 2 It is a flow chart of the implementation of the carbon reduction benefit allocation method for a zero-carbon commercial and office park provided by an embodiment of the present invention;

[0038] Figure 3 It is a structural schematic diagram of a carbon reduction benefit allocation device for a zero-carbon commercial and office park provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0039] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0040] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will be described through specific embodiments in conjunction with the accompanying drawings.

[0041] Figure 1 The following is a flowchart for implementing the carbon reduction benefit distribution method for a zero-carbon commercial and office park provided in an embodiment of the present invention, which is described in detail as follows:

[0042] Step 101: Analyze the interactive response requirements and operation regulation scenario characteristics between the target park and the power grid, as well as the carbon reduction potential of flexible resources on the energy consumption side, energy supply side, and energy storage side of the park. Based on the analysis results, construct an interactive regulation and flexible resource index system for the park power grid.

[0043] In this embodiment, a typical low-carbon commercial and office park is selected. By obtaining data such as the power loss on the power grid side, external power supply of the system, power consumption, response time of the system to power grid changes, electricity price data, as well as the capacity, operation efficiency, and green power generation of energy storage and photovoltaic equipment on the park side, an interactive regulation and flexible resource index system for the park power grid is constructed, considering aspects such as power and heat loss, load management, price response, and the performance and efficiency of multi-agent flexible resources on the energy consumption side, energy supply side, and energy storage side of the park, to quantitatively and qualitatively evaluate the carbon emission situation and carbon reduction effectiveness of the park.

[0044] Step 102: Based on the interactive regulation and flexible resource index system of the park power grid, construct a logistic regression model with the regulation mode as the input variable and the zero-carbon potential index as the output variable; where the regulation mode includes the operation mode and the regulation method of energy-consuming equipment.

[0045] In this embodiment, the contribution degree of multi-agent users in carbon reduction activities is evaluated through the sensitivity analysis method, and the influence mechanism of different cooperation operation modes and equipment regulation methods on the carbon reduction cost and benefit of the park is deeply analyzed. By selecting several different types of parks, the operation modes (autonomous, outsourced, consulting) and energy-consuming equipment regulation methods (monitorable and controllable, only monitored, not monitored and not participated) of the park are numerically encoded for quantitative analysis. According to the fuzzy comprehensive evaluation method, the carbon reduction effectiveness y of the park is calculated. Taking the operation mode and energy-consuming equipment regulation method of the park as input variables and the carbon reduction effectiveness level as the output variable, a logistic regression model is constructed. Through the prediction framework of the logistic regression model and using the sensitivity analysis method, the influence degree of the input variable on the output variable (carbon reduction effectiveness level) is quantified. According to the results of the sensitivity analysis, the influence degree value of the participating entity (such as autonomous and monitorable and controllable) on the carbon reduction effectiveness, that is, the carbon reduction contribution degree, is obtained.

[0046] Step 103: Based on the sensitivity analysis method and the logistic regression model, evaluate the carbon reduction contribution degrees of various operation modes and energy-consuming equipment regulation methods to the target park.

[0047] In this embodiment, investigate the mechanisms and characteristics of the operation, cooperation, and management operation models (self-operated, outsourced, consulting) of each participating entity in the park and the energy-consuming equipment regulation methods (monitorable and controllable, only monitored but not controllable, not monitored and not controllable, etc.), and analyze the sources of increased carbon reduction costs and increased benefits in the park caused by different cooperative operation models and equipment regulation methods.

[0048] Select several different types of parks, calculate the zero-carbon potential index y of different types of parks through the fuzzy comprehensive evaluation method. At the same time, perform one-hot encoding on the operation models (self-operated, outsourced, consulting) and energy-consuming equipment regulation methods (monitorable and controllable, only monitored but not controllable, not monitored and not controllable participation) of the parks to convert the character type into a numerical type and eliminate the order influence.

[0049] Then construct a logistic regression model, with the park operation model and energy-consuming equipment regulation method as input variables and the zero-carbon potential index as the output variable. The prediction function of the model can be expressed as:

[0050]

[0051] where θ is the model parameter and x is the input feature.

[0052] The core idea of logistic regression is to use a linear combination to predict the relationship between input features and output categories, and map the result of the linear combination to between 0 and 1 through a logistic function (also known as the Sigmoid function) to obtain a probability value. This probability value represents the possibility that a certain sample belongs to a certain category. The zero-carbon potential index level of the park can be quickly determined through the logistic regression model.

[0053] Step 104: Based on the carbon reduction contribution degrees corresponding to each operation model and energy-consuming equipment regulation method, conduct cooperative game behavior analysis on each participating entity in the target park to allocate the carbon reduction benefits to each participating entity.

[0054] In this embodiment, conduct cooperative game behavior analysis on each participating entity in the park, predict the strategic interactions, interest conflicts, and cooperation possibilities among different participants from the perspective of game analysis, and establish a multi-agent carbon reduction benefit sharing mechanism for the park considering the operation model and cost settlement method based on the cooperative game behavior of each participating entity to ensure the fairness and reasonableness of the sharing mechanism and encourage all parties to jointly participate in the carbon reduction action.

[0055] In the embodiments of the present invention, by studying the energy flow of each flexible resource device, for parks with different operation and management modes and equipment regulation methods, a comprehensive carbon reduction effectiveness evaluation method for the park and the power grid is established. The carbon reduction effectiveness is evaluated through the zero-carbon potential index, and by evaluating the carbon reduction contribution degrees of multiple main users in the park, a carbon reduction benefit sharing mechanism for multiple main bodies in parks with different operation modes is established, providing referenceable experience for similar parks, facilitating the development of national parks towards low-carbon and intelligent directions, solving the limitations of the prior art in dealing with the complex carbon reduction benefit sharing mechanism of multiple main bodies in parks, meeting the market demand for considering the differences in carbon reduction modes in parks, and improving the carbon reduction effect of parks.

[0056] In a possible implementation manner, based on the interactive regulation of the park power grid and the flexible resource index system, a logistic regression model with the regulation mode as the input variable and the zero-carbon potential index as the output variable is constructed, including:

[0057] Based on the interactive regulation of the park power grid and the flexible resource index system and the fuzzy comprehensive evaluation method, determine the zero-carbon potential indexes of multiple different types of parks under each regulation mode;

[0058] Take the regulation mode of each park as the input variable and the corresponding zero-carbon potential index as the output variable to construct a logistic regression model.

[0059] In this embodiment, there are many and complex relevant factors involved in the park. Considering the above multiple indicators and factors comprehensively, the fuzzy comprehensive evaluation method is used to calculate the zero-carbon potential index of the park to evaluate the carbon reduction effectiveness and zero-carbon potential of the park. A high zero-carbon potential index means that the park performs well in multiple evaluation indicators, has strong zero-carbon potential, and has good performance in aspects such as energy structure optimization and energy conservation and emission reduction measures; a low zero-carbon potential index indicates that there are certain challenges for the park to achieve the zero-carbon goal, and it may be necessary to improve some key indicators, such as improving energy use efficiency and strengthening emission reduction measures. This method can better handle the uncertainty and fuzziness of information, is suitable for evaluating complex problems such as zero-carbon potential, provides comprehensive, accurate and scientific evaluation results for decision-making and management, and promotes the sustainable development of the park.

[0060] In a possible implementation manner, the interactive regulation of the park power grid and the flexible resource index system include multiple primary indicators and multiple secondary indicators; based on the interactive regulation of the park power grid and the flexible resource index system and the fuzzy comprehensive evaluation method, determine the zero-carbon potential indexes of multiple different types of parks under each regulation mode, including:

[0061] Calculate the membership degrees of each secondary indicator to each primary evaluation grade standard based on the linear membership function to obtain the membership degree vector of each secondary indicator;

[0062] The weight distribution vector is combined with each membership degree vector through a synthesis operator to obtain the evaluation matrix of each secondary index;

[0063] After normalizing the evaluation matrices of each secondary index, they are combined into a total evaluation matrix;

[0064] Based on the total evaluation matrix and the grade standard matrix, calculate the zero-carbon potential index of multiple different types of parks under each operation mode and energy-consuming equipment regulation method.

[0065] In this embodiment, the specific steps for calculating the zero-carbon potential index by the fuzzy comprehensive evaluation method are as follows:

[0066] (1) Establish an evaluation vector

[0067] Objectively calculate the membership degrees of each secondary index to each primary evaluation grade standard by using a linear membership function. The specific form is as follows:

[0068]

[0069] In the formula: x is the index value corresponding to the evaluation index; e is the evaluation grade standard; μ is the membership degree of the evaluation index. If the index value x ≤ e(1), take μ1(x) = 1, and the rest μj(x) = 0; if μj(x) = 0, take μ10(x) = 1 and μj(x) = 0.

[0070] (2) Establish the comprehensive evaluation matrix of each primary index

[0071] Combine the weight distribution vector Ai and each evaluation vector Ui (i = 1, 2, 3) with a synthesis operator to synthesize the corresponding factor evaluation matrix:

[0072] B i = A i · U i (i = 1, 2, 3)

[0073] Use the normalized Bi to establish the total evaluation matrix B = [B1, B2, B3] T .

[0074] (3) Establish the evaluation matrix of the park zero-carbon potential evaluation system and perform normalization processing, that is:

[0075] C = A · B

[0076] (4) Finally, determine the total zero-carbon potential score through the following formula to obtain the zero-carbon potential index:

[0077] F = C · S T

[0078] In the formula: ST is the matrix formed by each grade standard

[0079] In a possible implementation, the first-level indicators include energy efficiency and losses, energy demand management, energy price and market, energy supply and structure, green energy and externally transferred power, and the second-level indicators include distribution network loss rate, energy storage proportion, peak shaving and valley filling volume, system response speed, real-time electricity price, demand elasticity, photovoltaic power generation proportion, wind power generation proportion, hydrogen energy proportion, and green externally transferred power ratio.

[0080] In this embodiment, the corresponding relationship between the first-level indicators and the second-level indicators is shown in Table 1.

[0081] Table 1

[0082]

[0083]

[0084] The specific meanings of various indicators are as follows:

[0085] 1) Distribution network loss rate: It refers to the ratio of the amount of power loss to the external power supply of the target system, and the calculation formula is where E ρ is the external power supply (kW·h), and E σ is the total actual electricity consumption (kW·h).

[0086] 2) Peak shaving and valley filling volume: According to the electricity consumption patterns of different users, reasonably and systematically arrange and organize the electricity consumption time of various users to reduce the peak load and fill the valley load. The calculation formula of λ is λ = ∑V i , where V is the contribution of the equipment to peak shaving and valley filling (kW·h).

[0087] 3) System response speed: It refers to the response time of the system to changes in the power grid, and the calculation formula is where S is the optimization time consumption for the i-th time (ms), and n is the number of optimization times per hour for daily optimization.

[0088] 4) Real-time electricity price: It is calculated based on the average electricity price before demand response and the real-time floating factor, and the formula is p(t) = α(t)·p r , where α(t) is the real-time floating factor, and p r is the average electricity price before demand response.

[0089] 5) Demand elasticity: It is used to describe the impact of price changes on load changes, and the formula is where p0(t 0 ) is the electricity price at time t before demand response, and p(t 0 ) is the real-time electricity price. 0 )

[0090] 6) Energy storage device capacity indicator:

[0091] Energy storage device capacity: It refers to the electricity storage capacity of the energy storage device, such as an energy storage device with a capacity of 232 kWh.

[0092] Energy storage ratio: It is the ratio of the difference between the electricity supplied by the energy storage in the park and the energy storage loss during the evaluation period to the comprehensive energy consumption in the park during the period. The calculation formula is E storage_supply is the electricity supplied by the energy storage, E storage_loss is the difference in energy storage loss, E total is the comprehensive energy consumption in the park.

[0093] 7) Clean energy supply index:

[0094] Photovoltaic power generation ratio: It is the ratio of the photovoltaic power generation built in the park to the comprehensive energy consumption in the park. Wind power generation ratio: It is the ratio of the wind power generation in the park to the comprehensive energy consumption in the park. Hydrogen energy ratio: It is the ratio of the hydrogen production in the park to the comprehensive energy consumption in the park. E pv_gen 、e wind_gen 、H prod are the photovoltaic power generation, wind power generation, and hydrogen production in the park.

[0095] 8) Proportion of green externally sourced electricity: It is the ratio of the green electricity purchased from outside the park to the comprehensive energy consumption in the park. The formula is E green_import is the green electricity purchased from outside.

[0096] In a possible implementation, based on the sensitivity analysis method and the logistic regression model, the carbon reduction contribution degrees of various operation modes and energy-consuming equipment regulation methods to the target park are evaluated, including:

[0097] Based on the logistic regression model, determine the zero-carbon potential index of the target park under each operation mode and energy-consuming equipment regulation method;

[0098] Based on the zero-carbon potential index of the target park under each operation mode and energy-consuming equipment regulation method, calculate the second-order Sobol index of each operation mode and energy-consuming equipment regulation method as the carbon reduction contribution degree of this operation mode and energy-consuming equipment regulation method.

[0099] In this embodiment, sensitivity analysis, as a method for studying how to allocate the uncertainty in the output of a model (numerical or otherwise) to different sources of uncertainty in the model input, is very suitable for evaluating the influence degrees of various factors and measures on the carbon reduction benefits evaluation of multi-agent users.

[0100] Sensitivity analysis assumes that the model is expressed as y = f(xi), where xi represents the i-th parameter of the model. Each parameter value is allowed to vary within a certain range, and the degree of influence of these parameters on the model output value y is studied and predicted, that is, the sensitivity coefficient of the parameter. In most literatures, sensitivity analysis is based on derivatives. For thermal systems and building energy consumption simulation systems, sensitivity analysis is usually quantified by the differences in simulation results caused by changes in input parameters. The derivative of the output value with respect to the input value can be regarded as the definition of the sensitivity coefficient:

[0101]

[0102] In the formula: OP represents the output value, and IP represents the input value.

[0103] In a possible implementation, the calculation formula for the second-order Sobol index is:

[0104]

[0105] where S i is the first-order Sobol index, V(·) is the variance, E(·) is the expectation, Y is the output variable, and X i is the i-th input variable, and S ij is the second-order Sobol index.

[0106] In this embodiment, the Sobol index is a method for measuring the contribution of input variables to the variance of output variables, which can measure the influence of interactions in non-additive systems. The global sensitivity analysis of the logistic regression model is performed through the SALib library in python, and the total variance of the model is decomposed into the contributions of each input variable and its combinations, including the first-order and second-order Sobol indices.

[0107] a. First-order Sobol index:

[0108] The first-order Sobol index measures the contribution of a single input variable to the variance of the output variable, and the calculation formula is:

[0109]

[0110] where V represents the variance, E represents the expectation, Y is the output variable, and X i is the i-th input variable.

[0111] b. Second-order Sobol index:

[0112] The second-order Sobol index measures the contribution of two input variables and their combinations to the variance of the output variable, and the calculation formula is:

[0113]

[0114] Among them, X i and X j are two different input variables.

[0115] Determine the variables that have a significant impact on the carbon reduction effect according to the first-order Sobol index of the sensitivity analysis results, and obtain the contribution of different combinations of operation modes (autonomous, outsourced, consulting) and energy-consuming equipment control modes (monitorable and controllable, only monitored but not controlled, not monitored and not controlled and participated) to the variance of the carbon reduction effect according to the second-order Sobol index, that is, the carbon reduction contribution degree.

[0116] The larger the sensitivity coefficient, the greater the impact of the parameter on the model output, which should be considered key in building energy efficiency analysis; the smaller the sensitivity coefficient, the smaller the impact of the parameter on the model output, which can be considered secondary or even negligible in the actual process.

[0117] In a possible implementation, the operation modes include autonomous, outsourced, and consulting; the energy-consuming equipment control modes include monitorable and controllable, only monitored but not controlled, and not monitored and not controlled and participated.

[0118] In this embodiment, the specific relationships between various operation modes and energy-consuming equipment control modes and each index are shown in Table 2.

[0119] Table 2

[0120]

[0121]

[0122] In a possible implementation, based on the carbon reduction contribution degrees corresponding to each operation mode and energy-consuming equipment control mode, conduct a cooperative game behavior analysis on each participating subject in the target park, including:

[0123] Take the zero-carbon potential index as the characteristic function value, take the carbon reduction contribution degree after each participating subject joins the alliance as the marginal contribution of the participating subject, and determine the weighting factor based on the number of participating subjects in the alliance;

[0124] Calculate the Shapley value of each participating subject, and determine the distribution share of each participating subject based on the proportion of the Shapley values of each participating subject.

[0125] In this embodiment, the specific steps for conducting the game analysis include:

[0126] 1) Define the characteristic function:

[0127] First, define the characteristic function v(S), which represents the total benefit generated by a coalition S of a group of entities participating in cooperation in any park. In the scenario of this embodiment, v(S) is the function for calculating the carbon reduction effectiveness of the park according to the fuzzy comprehensive evaluation method in step 102, and can be quickly calculated through the subsequently constructed logistic regression model.

[0128] 2) Calculate the marginal contribution:

[0129] For park participant i and coalition S, calculate the marginal contribution generated after participant i joins coalition S, that is, v(S ∪ {i}) - v(S), and calculate the carbon reduction contribution degree as the marginal contribution through the sensitivity analysis method in step 102.

[0130] 3) Determine the weighting factor:

[0131] Calculate the weighting factor w(|s|), which is determined based on the size of coalition S, and the calculation formula is where n is the total number of park participants, and |s| is the number of elements in coalition S.

[0132] 4.) Calculate the Shapley value:

[0133] For each participant i, calculate its Shapley value φ i (v), and the formula is:

[0134]

[0135] This formula means that the Shapley value of participant i is the weighted average of its marginal contributions in all possible coalitions.

[0136] 5) Allocate the carbon reduction benefits:

[0137] According to the calculated Shapley value, allocate the total carbon reduction benefits according to the Shapley value, and the allocation share of each participant is proportional to its Shapley value.

[0138] The Shapley value uses the characteristic function to determine the marginal contribution of each participating entity, and adjusts the importance of these marginal contributions through the weighting factor, thus providing a method for fairly distributing the total benefits. This method ensures that each player is rewarded according to their contribution to the coalition.

[0139] In a specific embodiment, the method provided by the present invention can be applied and verified as follows.

[0140] 1) Select the Xiongan Innovation Center as a demonstration project pilot, apply and verify the zero-carbon park evolution path planning method, and build a zero-carbon operation foundation.

[0141] 2) Use the zero-carbon operation evaluation index system to provide guidance for the operation and control of the Xiongan Park and conduct operation level evaluation. Through the interactive carbon reduction resource panoramic perception and regulation effect display system of the commercial and office park, realize the interactive display of the general overview of the energy of the Xiongan Innovation Center, the excavation of emission reduction potential, operation evaluation, regulation effect, etc.

[0142] 3) Promote the application of technologies through the evaluation and sharing mechanism of the park's carbon reduction effect. Verify and evaluate the theory and system of the project research in the demonstration project of the Xiongan Innovation Center, and provide solutions and demonstration models for the zero-carbon transformation of the park under the background of the development of the new power system.

[0143] As can be seen from the above, the technical solutions of the invention include key steps such as comprehensive carbon reduction effect evaluation, carbon reduction benefit contribution degree, carbon reduction benefit sharing mechanism, and example verification. The specific process is as Figure 2 shown, including:

[0144] 1. Study the interactive response requirements between the park and the power grid and the characteristics of the operation regulation scenario, as well as the carbon reduction potential of flexible resources on the energy consumption side, energy supply side, and energy storage side of the park, and construct an index system for the interactive regulation between the park power grid and flexible resources.

[0145] 2. Use the fuzzy evaluation method to construct an evaluation method for the comprehensive carbon reduction effect between the park and the power grid.

[0146] 3. Investigate and analyze the mechanisms and characteristics of the operation, cooperation, management operation models of each participating entity in the park and the regulation methods of energy-consuming equipment

[0147] 4. Evaluate the contribution degree of multi-agent users in carbon reduction activities through the sensitivity analysis method, and deeply analyze the influence mechanisms of different cooperation operation models and equipment regulation methods on the carbon reduction cost and benefit of the park.

[0148] 5. Conduct an analysis of the cooperative game behavior of each participating entity in the park, and establish a multi-agent carbon reduction benefit sharing mechanism for the park considering the operation model and cost settlement method.

[0149] 6. Conduct simulation of the multi-agent carbon reduction benefit sharing mechanism for the park and verification with park examples.

[0150] The application fields of the present invention can include:

[0151] 1. For the zero-carbon transformation judgment stage, give the path guidance of "how to become a zero-carbon park", construct a zero-carbon technology system, zero-carbon feasibility analysis method and evolution path planning tool for the park, and guide the park to meet the preconditions for achieving zero-carbon operation.

[0152] 2. For the park operation and control stage, construct a specific method of "how to achieve zero-carbon operation".

[0153] 3. Application and Promotion of Zero-Carbon Technologies. This invention can be used as an empirical demonstration for "achieving grid-friendly zero-carbon". It proposes a benefit evaluation method and sharing mechanism for the park to participate in grid interactive regulation, solves the problem of implementing the solution for grid-friendly zero-carbon parks from research to application, forms demonstration and technology leadership, and promotes the popularization and application of the overall project solution.

[0154] 4. Carbon Reduction Scheme for Park Operation. This invention can be used as the evaluation boundary, evaluation period, and evaluation scenario for park operation, providing a model basis for flexible regulation inside and outside the park and zero-carbon operation evaluation.

[0155] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0156] The following is an apparatus embodiment of the present invention. For details not described in detail, reference can be made to the corresponding method embodiments above.

[0157] Figure 3 The structural schematic diagram of the carbon reduction benefit distribution apparatus for a zero-carbon commercial and office park provided by the embodiment of the present invention is shown. For the sake of convenience of description, only the parts related to the embodiment of the present invention are shown and are described in detail as follows:

[0158] As Figure 3 shown, the carbon reduction benefit distribution apparatus 3 for a zero-carbon commercial and office park includes:

[0159] A system construction module 31, configured to analyze the interactive response requirements and operation regulation scenario characteristics between the target park and the power grid, as well as the carbon reduction potential of flexible resources on the energy consumption side, energy supply side, and energy storage side of the park, and construct an index system for park-grid interactive regulation and flexible resources based on the analysis results;

[0160] A model construction module 32, configured to construct a logistic regression model with the regulation mode as the input variable and the zero-carbon potential index as the output variable based on the index system for park-grid interactive regulation and flexible resources; wherein, the regulation mode includes the operation mode and the regulation method of energy-consuming equipment;

[0161] A contribution evaluation module 33, configured to evaluate the carbon reduction contribution degrees of various operation modes and regulation methods of energy-consuming equipment to the target park based on the sensitivity analysis method and the logistic regression model;

[0162] A benefit distribution module 34, configured to perform cooperative game behavior analysis on each participating subject of the target park based on the carbon reduction contribution degree corresponding to each operation mode and regulation method of energy-consuming equipment, so as to distribute the carbon reduction benefits to each participating subject.

[0163] In a possible implementation manner, the model construction module 32 is specifically configured to:

[0164] Based on the interactive regulation of the park power grid, the flexible resource index system, and the fuzzy comprehensive evaluation method, determine the zero-carbon potential index of multiple different types of parks under each regulation mode;

[0165] Take the regulation mode of each park as the input variable and the corresponding zero-carbon potential index as the output variable to construct a logistic regression model.

[0166] In a possible implementation, the interactive regulation of the park power grid and the flexible resource index system include multiple primary indicators and multiple secondary indicators; the model construction module 32 is specifically used for:

[0167] Calculate the membership degree of each secondary indicator to each primary evaluation grade standard based on the linear membership function to obtain the membership degree vector of each secondary indicator;

[0168] Synthesize the weight distribution vector and each membership degree vector through the synthesis operator to obtain the evaluation matrix of each secondary indicator;

[0169] Normalize the evaluation matrices of each secondary indicator and synthesize them into the total evaluation matrix;

[0170] Based on the total evaluation matrix and the grade standard matrix, calculate the zero-carbon potential index of multiple different types of parks under each operation mode and energy-consuming equipment regulation mode.

[0171] In a possible implementation, the primary indicators include energy efficiency and loss, energy demand management, energy price and market, energy supply and structure, green energy and externally transferred power, and the secondary indicators include distribution network loss rate, energy storage ratio, peak shaving and valley filling volume, system response speed, real-time electricity price, demand elasticity, photovoltaic power generation ratio, wind power generation ratio, hydrogen energy ratio, and green externally transferred power ratio.

[0172] In a possible implementation, the contribution evaluation module 33 is specifically used for:

[0173] Based on the logistic regression model, determine the zero-carbon potential index of the target park under each operation mode and energy-consuming equipment regulation mode;

[0174] Based on the zero-carbon potential index of the target park under each operation mode and energy-consuming equipment regulation mode, calculate the second-order Sobol index of each operation mode and energy-consuming equipment regulation mode as the carbon reduction contribution degree of this operation mode and energy-consuming equipment regulation mode.

[0175] In a possible implementation, the calculation formula of the second-order Sobol index is:

[0176]

[0177] Among them, Si is the first-order Sobol index, V(·) is the variance, E(·) is the expectation, Y is the output variable, and X i is the i-th input variable, and S ij is the second-order Sobol index.

[0178] In a possible implementation, the operation modes include autonomous, outsourced, and advisory; the regulation methods of energy-consuming devices include monitorable and controllable, only monitored and not controllable, and not monitored and not participating in control.

[0179] In a possible implementation, the benefit distribution module 34 is specifically configured to:

[0180] Take the zero-carbon potential index as the characteristic function value, take the carbon reduction contribution degree after each participating entity joins the alliance as the marginal contribution of the participating entity, and determine the weighting factor based on the number of participating entities in the alliance;

[0181] Calculate the Shapley value of each participating entity, and determine the distribution share of each participating entity based on the proportion of the Shapley values of each participating entity.

[0182] By studying the energy flow of each flexible resource device, the embodiments of the present invention establish a comprehensive carbon reduction effectiveness evaluation method for the park and the power grid for parks with different operation and management modes and device regulation methods. The carbon reduction effectiveness is evaluated through the zero-carbon potential index, and by evaluating the carbon reduction contribution degrees of multi-subject users in the park, a multi-subject carbon reduction benefit sharing mechanism with different operation modes is established, providing referenceable experience for similar parks, assisting the development of parks across the country towards low-carbon and intelligent directions, solving the limitations of the prior art in dealing with the complex multi-subject carbon reduction benefit sharing mechanism, meeting the market demand for considering the differences in park carbon reduction modes, and improving the carbon reduction effect of the park.

[0183] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For parts not detailed or recorded in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0184] Those of ordinary skill in the art can realize that the templates, units, and algorithm steps of the various examples described in combination with the embodiments disclosed herein can be implemented in electronic hardware, or in combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0185] When the module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-described embodiment methods of the present invention, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described embodiments of the carbon emission reduction benefit distribution method for a zero-carbon commercial and office park can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0186] The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A carbon reduction benefit distribution method for zero-carbon commercial and office parks, characterized in that Including: Analyze the interactive response requirements and operation regulation scenario characteristics between the target park and the power grid, as well as the carbon reduction potential of flexible resources on the energy consumption side, energy supply side, and energy storage side of the park. Based on the analysis results, construct an interactive regulation and flexible resource index system for the park power grid; Based on the interactive regulation and flexible resource index system of the park power grid, construct a logistic regression model with the regulation mode as the input variable and the zero-carbon potential index as the output variable; wherein, the regulation mode includes the operation mode and the regulation method of energy-consuming equipment; Based on the sensitivity analysis method and the logistic regression model, evaluate the carbon reduction contribution degrees of various operation modes and energy-consuming equipment regulation methods to the target park; Based on the carbon reduction contribution degrees corresponding to each operation mode and energy-consuming equipment regulation method, conduct a cooperative game behavior analysis on each participating subject in the target park to allocate the carbon reduction benefits to each participating subject.

2. The carbon reduction benefit distribution method for zero-carbon commercial and office parks according to claim 1, wherein The constructing a logistic regression model with the regulation mode as the input variable and the zero-carbon potential index as the output variable based on the interactive regulation and flexible resource index system of the park power grid includes: Based on the interactive regulation and flexible resource index system of the park power grid and the fuzzy comprehensive evaluation method, determine the zero-carbon potential indexes of multiple different types of parks under each regulation mode; Take the regulation mode of each park as the input variable and the corresponding zero-carbon potential index as the output variable to construct a logistic regression model.

3. The carbon reduction benefit distribution method for zero-carbon commercial and office parks according to claim 2, wherein The interactive regulation and flexible resource index system of the park power grid includes multiple first-level indexes and multiple second-level indexes; the determining the zero-carbon potential indexes of multiple different types of parks under each regulation mode based on the interactive regulation and flexible resource index system of the park power grid and the fuzzy comprehensive evaluation method includes: Calculate the membership degrees of each second-level index to each first-level evaluation grade standard based on the linear membership function to obtain the membership degree vector of each second-level index; Synthesize the weight distribution vector and each membership degree vector through a synthesis operator to obtain the evaluation matrix of each second-level index; Normalize the evaluation matrices of each second-level index and then synthesize them into a total evaluation matrix; Based on the total evaluation matrix and the grade standard matrix, calculate the zero-carbon potential indexes of multiple different types of parks under each operation mode and energy-consuming equipment regulation method.

4. The carbon reduction benefit distribution method for zero-carbon commercial and office parks according to claim 3, characterized in that The first-level indexes include energy efficiency and loss, energy demand management, energy price and market, energy supply and structure, green energy and externally transferred power, and the second-level indexes include distribution network loss rate, energy storage ratio, peak shaving and valley filling volume, system response speed, real-time electricity price, demand elasticity, photovoltaic power generation ratio, wind power generation ratio, hydrogen energy ratio, and green externally transferred power ratio.

5. The carbon reduction benefit distribution method for zero-carbon commercial and office parks according to claim 1, wherein, The evaluating the carbon reduction contribution degrees of various operation modes and energy-consuming equipment regulation methods to the target park based on the sensitivity analysis method and the logistic regression model includes: Based on the logistic regression model, determine the zero-carbon potential indexes of the target park under each operation mode and energy-consuming equipment regulation method; Based on the zero-carbon potential indexes of the target park under each operation mode and energy-consuming equipment regulation method, calculate the second-order Sobol index of each operation mode and energy-consuming equipment regulation method as the carbon reduction contribution degree of this operation mode and energy-consuming equipment regulation method.

6. The carbon reduction benefit distribution method for zero-carbon commercial and office parks according to claim 5, wherein The calculation formula of the second-order Sobol index is as follows: Among them, S i is the first-order Sobol index, V(·) is the variance, E(·) is the expectation, Y is the output variable, and X i is the i-th input variable, and S ij is the second-order Sobol index.

7. The carbon reduction benefit distribution method for zero-carbon commercial and office parks according to claim 5, characterized in that, The operation modes include autonomous mode, outsourcing mode, and consulting mode; the regulation methods of energy-consuming equipment include monitorable and controllable, only monitored and not controllable, and not monitored and not participated in.

8. The carbon reduction benefit distribution method for zero-carbon commercial and office parks according to claim 1, wherein Based on the carbon reduction contribution degrees corresponding to each operation mode and energy-consuming equipment regulation method, conduct cooperative game behavior analysis on each participating entity in the target park, including: Taking the zero-carbon potential index as the characteristic function value, taking the carbon reduction contribution degree after each participating entity joins the alliance as the marginal contribution of this participating entity, and determining the weighting factor based on the number of participating entities in the alliance; Calculate the Shapley value of each participating entity, and determine the distribution share of each participating entity based on the proportion of the Shapley values of each participating entity.

9. A carbon reduction benefit distribution device for a zero-carbon commercial and office park, characterized in that, Including: A system construction module for analyzing the interactive response requirements and operation regulation scenario characteristics between the target park and the power grid, as well as the carbon reduction potential of flexible resources on the energy consumption side, energy supply side, and energy storage side of the park, and constructing an interactive regulation index system for the park power grid and flexible resources based on the analysis results; A model construction module for constructing a logistic regression model with the regulation mode as the input variable and the zero-carbon potential index as the output variable based on the interactive regulation index system for the park power grid and flexible resources; among them, the regulation mode includes the operation mode and the regulation method of energy-consuming equipment; A contribution evaluation module for evaluating the carbon reduction contribution degrees of multiple operation modes and energy-consuming equipment regulation methods to the target park based on the sensitivity analysis method and the logistic regression model; A benefit distribution module for conducting cooperative game behavior analysis on each participating entity in the target park based on the carbon reduction contribution degrees corresponding to each operation mode and energy-consuming equipment regulation method, so as to distribute the carbon reduction benefits to each participating entity.

10. The carbon reduction benefit distribution device for a zero-carbon commercial and office park according to claim 9, wherein, The model construction module is specifically used for: Based on the interactive regulation index system for the park power grid and flexible resources and the fuzzy comprehensive evaluation method, determine the zero-carbon potential indexes of multiple different types of parks under each regulation mode; Taking the regulation mode of each park as the input variable and the corresponding zero-carbon potential index as the output variable, construct a logistic regression model.

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