Power distribution network day-ahead and intra-day low-carbon economic dispatching method considering stepped carbon transaction

Abstract

The invention relates to a day-ahead and intra-day low-carbon economic dispatching method for a power distribution network considering stepped carbon transactions. The method comprises the following steps: (1) putting forward a day-ahead scheduling model based on an NSGA-III algorithm by considering the flexibility, the low-carbon property and the economical efficiency of the operation of the power distribution network in a day-ahead stage; (2) in the intra-day stage, flexible resources reserved in the day-ahead stage are released by adjusting the output of the controllable unit; in the step (2), on the basis of releasing the flexible resources reserved in the day-ahead stage, a stepped carbon transaction mechanism is combined, and fine management of low-carbon economic operation of the multi-time-scale power distribution network is realized. According to the method, due to the adoption of a stepped carbon transaction mechanism, the carbon emission of the system in the intra-day stage is lower, and the corresponding carbon transaction cost is also reduced. In addition, by converting the flexibility reserved in the day-ahead stage into the economic advantage in the day, the operating cost in the day of the system is further reduced.

Description

Technical Field

[0001] The present invention relates to a low-carbon economic dispatching method for a distribution network taking into account ladder carbon trading. Background Art

[0002] As global climate change becomes increasingly severe, reducing carbon emissions and protecting the environment have become the consensus of the international community. As one of the main sources of carbon emissions, the low-carbon transformation of the power industry has become an important direction of the global energy revolution. In order to achieve the "dual carbon" goal, my country has made reducing carbon emissions an important binding indicator for the operation of the power system. In recent years, with the rapid development and widespread application of new energy technologies, the penetration rate of new energy has increased significantly in the power system, and the operation of the power system has become more complex, especially the uncertainty of new energy has brought about a surge in the system's demand for flexibility in scheduling strategies. How to effectively balance flexibility, low carbon and economy while ensuring the reliable operation of the system has become a key issue that needs to be solved urgently.

[0003] At present, in the research on low-carbon operation, some scholars have estimated the carbon emissions of equipment by establishing linear models and converted them into carbon emission costs to promote the low-carbon operation of the power system. However, the carbon emission model established by this method is relatively simple, and only calculates the carbon emissions of equipment in a linear relationship, lacking the fine management of the dynamic changes of carbon emissions. In terms of carbon trading, traditional carbon trading mechanisms usually set fixed carbon emission quotas and trading prices, which lack flexibility. In addition, most existing studies focus on the direct carbon emissions of fossil energy on the power generation side, making it difficult to expand the carbon constraints of climate policies from the power generation side to the user side, and it is impossible to trace the indirect carbon emissions of users, so it is impossible to clarify the carbon footprint of users and their carbon responsibilities.

[0004] In the field of flexibility research, some scholars have proposed a coordinated optimization scheduling method that utilizes the complementary characteristics of multiple power sources, but its means are relatively simple and do not take into account flexibility resources such as demand response and energy storage. There are also methods that take the lowest flexibility risk of the power system as the optimization goal, comprehensively consider the flexibility supply capacity of thermal power, energy storage, and interruptible loads to determine the scheduling strategy, but less attention is paid to the flexibility scheduling strategy of distribution networks under multiple time scales. Summary of the invention

[0005] The purpose of the present invention is to provide a method for low-carbon economic dispatching of distribution networks within a day before the day taking into account tiered carbon trading.

[0006] To achieve the above-mentioned purpose, the technical solution of the present invention is: a method for low-carbon economic dispatching of a distribution network within a day before the day taking into account ladder carbon trading, comprising:

[0007] (1) Considering the flexibility, low carbon and economy of distribution network operation in the day-ahead stage, a day-ahead dispatch model based on NSGA-III algorithm is proposed;

[0008] (2) During the intraday stage, the output of controllable units is adjusted to release the flexibility resources reserved in the day-ahead stage.

[0009] In one embodiment of the present invention, in step (2), on the basis of releasing the flexibility resources reserved in the day-ahead stage, a step-by-step carbon trading mechanism is also combined to achieve refined management of the low-carbon economic operation of the distribution network at multiple time scales.

[0010] In one embodiment of the present invention, in step (1), the objective function of the day-ahead scheduling model based on the NSGA-III algorithm includes:

[0011] Objective function 1 includes system operation cost F1, electricity purchase cost c grid,t , diesel engine operating cost C DE,t 、Energy storage operation cost C ESS,t and load interruption compensation cost C IL,t ;

[0012]

[0013] Where: P grid,t is the amount of electricity purchased from the main grid at time t, c grid,t It represents the electricity purchase cost at time t; P DE,t , P ESS,t , P IL,t are the diesel engine power, energy storage charging and discharging power, and load interruption power at time t respectively; α1, α2, α3 are the fuel cost coefficients of the diesel engine, c ESS is the unit power cost of energy storage charging and discharging, c IL is the load interruption compensation coefficient;

[0014] Objective function 2 is the flexibility deficiency rate F2, and its expression is as follows:

[0015]

[0016] Where: are the upward shortage rate and downward shortage rate of system flexibility at time t respectively; are the net load changes of the system at time t; and They are the upward and downward flexibility resources of the system at time t, provided by each controllable distributed generation;

[0017] Objective function 3 is the system carbon emission F3, and its expression is as follows:

[0018]

[0019] Where: grid , χ DEThey are the carbon emission coefficients per unit of purchased electricity and per unit of generated power by the diesel engine respectively.

[0020] In one embodiment of the present invention, in step (1), the constraints of the day-ahead scheduling model based on the NSGA-III algorithm include power balance constraints, diesel engine and energy storage operation constraints, and load interruption constraints.

[0021] In one embodiment of the present invention, the ladder carbon trading mechanism is as follows:

[0022] In order to constrain system carbon emissions, a step-by-step carbon trading model is adopted. The purchase and sale prices of carbon emission rights in different intervals are different. The specific mathematical model is:

[0023]

[0024] Where: F CO2,t represents the carbon trading cost of the system at time t, E G,t is the carbon emission rights trading amount of the system at time t, θ represents the price growth rate, ζ represents the compensation growth rate, ε represents the carbon trading base price, and L represents the length of the carbon emission interval.

[0025] In one embodiment of the present invention, in step (2), the objective function established for the intraday low-carbon economic dispatch of the distribution network taking into account the ladder carbon trading includes a day-ahead phase objective function and an intraday phase objective function, which are specifically as follows:

[0026] The day-ahead stage calculates the operating cost of the diesel engine in the form of a quadratic function, which needs to be linearized using a piecewise linearization method:

[0027]

[0028] Where: and is the parameter of piecewise linearization; and are the minimum and maximum points of the two piecewise functions respectively;

[0029] The intraday stage focuses on economical operation and low carbon performance. The objective function f intra Including system operation costs and carbon trading costs:

[0030]

[0031] In one embodiment of the present invention, in step (2), taking into account the low-carbon economic dispatch of the distribution network during the day of the ladder carbon trading, the constraints of the intraday stage are designed as follows:

[0032] The constraints in the intraday stage include Distflow constraints, output limit constraints, power balance constraints and equipment safe operation constraints. The inherent non-convexity of the Distflow constraints makes the model difficult to solve. The nonlinear terms of voltage and current are relaxed by the second-order cone to facilitate rapid solution. The standard second-order cone form is as follows:

[0033]

[0034] Where: represents the set of first nodes with j as the end node of the branch; is the corresponding end node set; P ij,t and Q ij,t are the forward active power and reactive power flowing through branch i→j at time t; P j,t and Q j,t are the active power and reactive power injected from node j at time t; P jk,t and Q jk,t are the forward active and reactive powers flowing through branch j→k at time t; r i,j 、x i,j is the resistance and reactance of branch ij; and are the squares of the voltage at node i and the current at branch ij during period t, respectively;

[0035] In order to ensure that day-ahead dispatching provides effective guidance for intraday dispatching, the day-ahead and intraday output limits are as follows:

[0036]

[0037] Where: and ΔP DE,t They are the output of the diesel engine at time t in the day-ahead phase and the intra-day phase and their deviation thresholds; and ΔS SOC,t They are the state of charge and deviation threshold at time t in the day-ahead and intra-day phases of energy storage respectively; and ΔP IL,t They are the load shedding power and its deviation threshold in the day-ahead stage and the day-intraday stage of the interruptible load respectively.

[0038] In one embodiment of the present invention, in step (2), taking into account the low-carbon economic dispatch of the distribution network during the day of the ladder carbon trading, the carbon emission flow calculation is also performed, as follows:

[0039] Carbon flow calculation can evaluate the carbon emission distribution of the system and determine the unit injection distribution matrix P according to the working conditions of the generator set. G and the carbon emission intensity vector E of the generator set G , and obtain the carbon potential E of each node in the system N, and its calculation formula is as follows:

[0040]

[0041] Where: P N is the node active flux matrix, P B is the branch power flow distribution matrix;

[0042] Then combined with the load distribution matrix P L and branch power loss matrix P1, determine the load carbon flow rate vector R L And branch power loss carbon emission R1:

[0043]

[0044] In one embodiment of the present invention, a day-ahead-intraday scheduling framework is also proposed to achieve day-ahead-intraday scheduling connection, as follows:

[0045] 1) Day-ahead scheduling: A scheduling plan for the next two days is formulated at 00:00 every day with a resolution of 1 hour. The operating status of the controllable units including diesel engines, energy storage and interruptible loads on the day of scheduling and the next day is determined based on the NSGA-III algorithm. The plan for the second day will be revised at the next 00:00.

[0046] 2) Intraday scheduling: The execution frequency is 96 times / day, with a resolution of 15 minutes. The output of each controllable unit in the system is dynamically adjusted based on the day-ahead strategy. The forward-looking window for rolling optimization is 4 hours. After each optimization, only the scheduling plan for the first 15 minutes in the forward-looking window is updated, and the plans for subsequent time periods will be adjusted in the subsequent rolling cycles.

[0047] The present invention also provides a computer-readable storage medium, on which computer program instructions that can be executed by a processor are stored. When the processor executes the computer program instructions, the method steps described above can be implemented.

[0048] Compared with the prior art, the present invention has the following beneficial effects: the method of the present invention achieves a comprehensive trade-off between system flexibility, low carbon and economy in the day-ahead stage, and provides guidance for subsequent intraday scheduling. In the intraday scheduling stage, the scheduling accuracy is further improved, and the flexibility resources reserved in the day-ahead stage are converted into economic benefits. In addition, the actual carbon emissions of the system are traced using the carbon emission flow theory, which can provide guidance and suggestions for the transformation and construction of the power grid. Combined with the analysis of specific examples, as shown in the table, the results of day-ahead and intraday scheduling are shown. It can be observed that due to the adoption of a step-by-step carbon trading mechanism, the system carbon emissions in the intraday stage are lower, and the corresponding carbon trading costs are also reduced. In addition, by converting the flexibility reserved in the day-ahead stage into intraday economic advantages, the intraday operating costs of the system can be further reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 The figure is a flow chart of the method of the present invention.

[0050] Figure 2 This is the solution process of the day-ahead scheduling model of the present invention.

[0051] Figure 3 This is the day-ahead and intra-day scheduling framework of the present invention.

[0052] Figure 4 Carbon emissions of each node in the system. DETAILED DESCRIPTION

[0053] The technical solution of the present invention is described in detail below in conjunction with the accompanying drawings.

[0054] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0055] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0056] The present invention provides a method for low-carbon economic dispatching of a distribution network within a day ahead taking into account tiered carbon trading, comprising:

[0057] (1) Considering the flexibility, low carbon and economy of distribution network operation in the day-ahead stage, a day-ahead dispatch model based on NSGA-III algorithm is proposed;

[0058] (2) During the intraday stage, the output of controllable units is adjusted to release the flexibility resources reserved in the day-ahead stage.

[0059] In step (2), on the basis of releasing the flexibility resources reserved in the day-ahead stage, the step-by-step carbon trading mechanism is also combined to achieve refined management of the low-carbon economic operation of the distribution network at multiple time scales.

[0060] The following is the specific implementation process of the present invention.

[0061] like Figure 1 As shown, this embodiment provides a low-carbon economic dispatch method for a distribution network within a day ahead taking into account the tiered carbon trading, including:

[0062] 1. Day-ahead dispatch strategy of distribution network based on NSGA-III

[0063] With the continuous improvement of the penetration rate of new energy and the continuous transformation of the low-carbon energy structure, the power system has an increasing demand for flexibility and low carbon. This paper proposes a day-ahead dispatch model based on the NSGA-III algorithm, which aims to balance the economy, flexibility and low carbon of the system and provide effective guidance for intraday dispatch.

[0064] (1) Objective function

[0065] Objective function 1 includes system operation cost F1, electricity purchase cost c grid,t , diesel engine operating cost C DE,t 、Energy storage operation cost C ESS,t and load interruption compensation cost C IL,t .

[0066]

[0067] Where: P grid,t is the amount of electricity purchased from the main grid at time t, c grid,t It represents the electricity purchase cost at time t; P DE,t , P ESS,t , P IL,t are the diesel engine power, energy storage charging and discharging power, and load interruption power at time t respectively; α1, α2, α3 are the fuel cost coefficients of the diesel engine, c ESS is the unit power cost of energy storage charging and discharging, c IL is the load interruption compensation coefficient.

[0068] Objective function 2 is the flexibility deficiency rate F2, and its expression is shown in formula (2).

[0069]

[0070] Where: are the upward shortage rate and downward shortage rate of system flexibility at time t respectively; are the net load changes of the system at time t; and They are the upward and downward flexibility resources of the system at time t, which are mainly provided by various controllable distributed power sources.

[0071] Objective function 3 is the system carbon emission F3, and its expression is shown in formula (3).

[0072]

[0073] Where: grid , χ DEThey are the carbon emission coefficients per unit of purchased electricity and per unit of generated power by the diesel engine respectively.

[0074] (2) Constraints

[0075] The constraints of the day-ahead dispatch model mainly include power balance constraints, diesel engine and energy storage operation constraints, and load interruption constraints.

[0076] (3) Solution process

[0077] The day-ahead scheduling model is solved using the NSGA-III algorithm. The specific process is as follows: Figure 2 shown.

[0078] 2. Intraday low-carbon economic dispatch of distribution network taking into account tiered carbon trading

[0079] The prediction accuracy of renewable energy output and load in the intraday stage is higher, and the prediction results can be optimized and the controllable resources in the system can be adjusted in time. This process effectively converts the flexibility reserved in the day-ahead stage into economic benefits, and also ensures the low-carbon operation of the system based on a step-by-step carbon trading mechanism.

[0080] (1) Tiered carbon trading mechanism

[0081] In order to further constrain system carbon emissions, this paper adopts a ladder carbon trading model, with different purchase and sale prices of carbon emission rights in different intervals. The specific mathematical model is:

[0082]

[0083] Where: F CO2,t represents the carbon trading cost of the system at time t, E G,t is the carbon emission rights trading amount of the system at time t, θ represents the price growth rate, ζ represents the compensation growth rate, ε represents the carbon trading base price, and L represents the length of the carbon emission interval.

[0084] (2) Objective function

[0085] The day-ahead stage calculates the operating cost of the diesel engine in the form of a quadratic function, which needs to be linearized using a piecewise linearization method:

[0086]

[0087] Where: and is the parameter of piecewise linearization; and are the minimum and maximum points of the two piecewise functions respectively.

[0088] The intraday stage focuses more on economical operation and low carbon performance. The objective function f intra Including system operating costs and carbon trading costs.

[0089]

[0090] (3) Constraints

[0091] The constraints in the intraday stage include Distflow power flow constraints, output limit constraints, power balance constraints and equipment safe operation constraints. Among them, the Distflow branch power flow model does not need to consider the phase difference between voltage and current, and is suitable for radial networks. However, its inherent non-convexity makes the model difficult to solve. The nonlinear terms of voltage and current can be relaxed by the second-order cone to facilitate rapid solution. The standard second-order cone form is as follows:

[0092]

[0093] Where: represents the set of first nodes with j as the end node of the branch; is the corresponding end node set; P ij,t and Q ij,t are the forward active power and reactive power flowing through branch i→j at time t; P j,t and Q j,t are the active power and reactive power injected from node j at time t; P jk,t and Q jk,t are the forward active and reactive powers flowing through branch j→k at time t; r i,j 、x i,j is the resistance and reactance of branch ij; and They are the squares of the voltage at node i and the current at branch ij during period t, respectively.

[0094] In order to ensure that day-ahead dispatching provides effective guidance for intraday dispatching, the day-ahead and intraday output limits are as follows.

[0095]

[0096] Where: and ΔP DE,t They are the output of the diesel engine at time t in the day-ahead phase and the intra-day phase and their deviation thresholds; and ΔS SOC,t They are the state of charge and deviation threshold at time t in the day-ahead and intra-day phases of energy storage respectively; and ΔP IL,t They are the load shedding power and its deviation threshold in the day-ahead stage and the day-intraday stage of the interruptible load respectively.

[0097] (4) Calculation of carbon emission flow

[0098] Carbon flow calculation can evaluate the carbon emission distribution of the system and determine the unit injection distribution matrix P according to the working conditions of the generator set. G and the carbon emission intensity vector E of the generator set G , we can get the carbon potential E of each node in the system N , and its calculation formula is as follows.

[0099]

[0100] Where: P N is the node active flux matrix, P B is the branch power flow distribution matrix.

[0101] Then combined with the load distribution matrix P L and branch power loss matrix P1, determine the load carbon flow rate vector R L And branch power loss carbon emission R1:

[0102]

[0103] 3. Day-ahead and intraday scheduling connection

[0104] The day-ahead and intraday scheduling time scales are different. In order to ensure the effectiveness of constraints and time consistency, it is necessary to determine the day-ahead-intraday scheduling framework and connection strategy. The day-ahead-intraday scheduling framework proposed in this invention is as follows: Figure 3 shown.

[0105] (1) Day-ahead scheduling: A scheduling plan for the next two days is prepared at 00:00 every day with a resolution of 1 hour. The operating status of the diesel engine, energy storage and interruptible load on the day of scheduling and the next day is determined based on the NSGA-III algorithm. The plan for the second day will be revised at the next 00:00.

[0106] (2) Intraday scheduling: The execution frequency is 96 times / day, with a resolution of 15 minutes. The output of each controllable unit of the system is dynamically adjusted based on the day-ahead strategy. The forward-looking window of rolling optimization is 4 hours. After each optimization, only the scheduling plan for the first 15 minutes in the forward-looking window is updated, and the plans for subsequent time periods will be adjusted in the subsequent rolling cycles.

[0107] Given the difference in time resolution between day-ahead scheduling and intraday scheduling, the diesel engine may experience a sudden and significant power increase during the day-ahead phase, which may cause it to fail to meet the ramp constraints during the intraday phase. In order to ensure that the operation of the diesel engine meets both the actual operating constraints and minimizes the deviation from the actual situation, it is necessary to adaptively adjust the day-ahead output of the diesel engine. The deviation before and after the adjustment needs to be as small as possible, and the adjusted diesel engine output curve meets the intraday ramp constraints. The deviation is:

[0108]

[0109] The constraints for adjusting the output are as follows:

[0110]

[0111] Where: sgn(·) is the sign function, which takes 1 when the value in the bracket is greater than 0, and takes 0 otherwise; and They are the maximum and minimum output of the diesel engine respectively. It is the output of the diesel engine after adaptation treatment, which can provide a reference for the daily diesel engine output.

[0112] The method of the present invention achieves a comprehensive trade-off between system flexibility, low carbon and economy in the day-ahead stage, and provides guidance for subsequent intraday scheduling. In the intraday scheduling stage, the accuracy of scheduling is further improved, and the flexibility resources reserved in the day-ahead stage are converted into economic benefits. In addition, the actual carbon emissions of the system are traced using the carbon emission flow theory, which can provide guidance and suggestions for the transformation and construction of the power grid. Combined with the analysis of specific examples, as shown in the table, the results of day-ahead and intraday scheduling are demonstrated. It can be observed that due to the adoption of a step-by-step carbon trading mechanism, the system carbon emissions in the intraday stage are lower, and the corresponding carbon trading costs are also reduced. In addition, by converting the flexibility reserved in the day-ahead stage into intraday economic advantages, the intraday operating costs of the system can be further reduced. Table 1 is a comparison of the day-ahead and intraday scheduling results.

[0113] Table 1 Comparison of scheduling results before and during the day

[0114]

[0115]

[0116] In the intraday stage, carbon flow tracing is performed. Table 2 shows that the total carbon emissions generated by electricity purchase and diesel generator power generation are basically equal to the total carbon emissions from the line and load ends, which verifies the law of conservation of carbon emissions. Figure 4 It can be observed that the carbon emissions of the nodes where new energy is installed are relatively low, while the carbon emissions of the 24th node in each period are relatively high. New energy can be installed near this node to promote the low-carbon transformation of the power grid.

[0117] Table 2 Carbon emissions from distribution networks

[0118]

[0119] The present invention also provides a computer-readable storage medium, on which computer program instructions that can be executed by a processor are stored. When the processor executes the computer program instructions, the method steps described above can be implemented.

[0120] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0121] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0122] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0123] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0124] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any technician familiar with the profession may use the above disclosed technical content to change or modify it into an equivalent embodiment with equivalent changes. However, any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention still belongs to the protection scope of the technical solution of the present invention.

Claims

1. A method for low-carbon economic dispatching of distribution network within the day before taking into account tiered carbon trading, characterized in that: include: (1) Considering the flexibility, low carbon and economy of distribution network operation in the day-ahead stage, a day-ahead dispatch model based on NSGA-III algorithm is proposed; (2) During the intraday stage, the output of controllable units is adjusted to release the flexibility resources reserved in the day-ahead stage.

2. A method for low-carbon economic dispatching of distribution network taking into account ladder carbon trading according to claim 1, characterized in that: In step (2), on the basis of releasing the flexibility resources reserved in the day-ahead stage, the step-by-step carbon trading mechanism is also combined to achieve refined management of the low-carbon economic operation of the distribution network at multiple time scales.

3. The method for low-carbon economic dispatching of distribution network taking into account ladder carbon trading according to claim 1 is characterized in that: In step (1), the objective function of the day-ahead scheduling model based on the NSGA-III algorithm includes: Objective function 1 includes system operation cost F1, electricity purchase cost c grid,t , diesel engine operating cost C DE,t 、Energy storage operation cost C ESS,t and load interruption compensation cost C IL,t ; Where: P grid,t is the amount of electricity purchased from the main grid at time t, c grid,t It represents the electricity purchase cost at time t; P DE,t , P ESS,t , P IL,t are the diesel engine power, energy storage charging and discharging power, and load interruption power at time t respectively; α1, α2, α3 are the fuel cost coefficients of the diesel engine, c ESS is the unit power cost of energy storage charging and discharging, c IL is the load interruption compensation coefficient; Objective function 2 is the flexibility deficiency rate F2, and its expression is as follows: Where: F t inf,up 、F t inf,down are the upward shortage rate and downward shortage rate of system flexibility at time t respectively; are the net load changes of the system at time t; f t up and f t down They are the upward and downward flexibility resources of the system at time t, provided by each controllable distributed generation; Objective function 3 is the system carbon emission F3, and its expression is as follows: Where: grid , χ DE They are the carbon emission coefficients per unit of purchased electricity and per unit of generated power by the diesel engine respectively.

4. A method for low-carbon economic dispatching of distribution network taking into account ladder carbon trading according to claim 3, characterized in that: In step (1), the constraints of the day-ahead scheduling model based on the NSGA-III algorithm include power balance constraints, diesel engine and energy storage operation constraints, and load interruption constraints.

5. A method for low-carbon economic dispatching of distribution network taking into account ladder carbon trading according to claim 2, characterized in that: The details of the tiered carbon trading mechanism are as follows: In order to constrain system carbon emissions, a step-by-step carbon trading model is adopted. The purchase and sale prices of carbon emission rights in different intervals are different. The specific mathematical model is: Where: represents the carbon trading cost of the system at time t, E G,t is the carbon emission rights trading amount of the system at time t, θ represents the price growth rate, represents the compensation growth rate, ε represents the carbon trading base price, and L represents the length of the carbon emission interval.

6. A method for low-carbon economic dispatching of distribution network taking into account ladder carbon trading according to claim 5, characterized in that: In step (2), the objective function established for the intraday low-carbon economic dispatch of the distribution network taking into account the ladder carbon trading includes the day-ahead phase objective function and the intraday phase objective function, which are as follows: The day-ahead stage calculates the operating cost of the diesel engine in the form of a quadratic function, which needs to be linearized using a piecewise linearization method: Where: and is the parameter of piecewise linearization; and are the minimum and maximum points of the two piecewise functions respectively; The intraday stage focuses on economical operation and low carbon performance. The objective function f intra Including system operation costs and carbon trading costs:

7. A method for low-carbon economic dispatching of distribution network taking into account ladder carbon trading according to claim 6, characterized in that: In step (2), the intraday low-carbon economic dispatch of the distribution network taking into account the ladder carbon trading is designed with the following constraints in the intraday stage: The constraints in the intraday stage include Distflow constraints, output limit constraints, power balance constraints and equipment safe operation constraints. The inherent non-convexity of the Distflow constraints makes the model difficult to solve. The nonlinear terms of voltage and current are relaxed by the second-order cone to facilitate rapid solution. The standard second-order cone form is as follows: Where: represents the set of first nodes with j as the end node of the branch; is the corresponding end node set; P ij,t and Q ij,t are the forward active power and reactive power flowing through branch i→j at time t; P j,t and Q j,t are the active power and reactive power injected from node j at time t; P jk,t and Q jk,t are the forward active and reactive powers flowing through branch j→k at time t; r i,j 、x i,j is the resistance and reactance of branch ij; and are the squares of the voltage at node i and the current at branch ij during period t, respectively; In order to ensure that day-ahead dispatching provides effective guidance for intraday dispatching, the day-ahead and intraday output limits are as follows: Where: and ΔP DE,t They are the output of the diesel engine at time t in the day-ahead phase and the intra-day phase and their deviation thresholds; and ΔS SOC,t They are the state of charge and deviation threshold at time t in the day-ahead and intra-day phases of energy storage respectively; and ΔP IL,t They are the load shedding power and its deviation threshold in the day-ahead stage and the day-intraday stage of the interruptible load respectively.

8. A method for low-carbon economic dispatching of distribution network taking into account ladder carbon trading according to claim 7, characterized in that: In step (2), the low-carbon economic dispatch of the distribution network within the day taking into account the ladder carbon trading is also calculated for the carbon emission flow, as follows: Carbon flow calculation can evaluate the carbon emission distribution of the system and determine the unit injection distribution matrix P according to the working conditions of the generator set. G and the carbon emission intensity vector E of the generator set G , and obtain the carbon potential E of each node in the system N , and its calculation formula is as follows: Where: P N is the node active flux matrix, P B is the branch power flow distribution matrix; Then combined with the load distribution matrix P L and branch power loss matrix P1, determine the load carbon flow rate vector R L And branch power loss carbon emission R1:

9. A method for low-carbon economic dispatching of distribution network taking into account ladder carbon trading according to claim 2, characterized in that: A day-ahead-intraday scheduling framework is also proposed to achieve the connection between day-ahead-intraday scheduling, as follows: 1) Day-ahead scheduling: A scheduling plan for the next two days is formulated at 00:00 every day with a resolution of 1 hour. The operating status of the controllable units including diesel engines, energy storage and interruptible loads on the day of scheduling and the next day is determined based on the NSGA-III algorithm. The plan for the second day will be revised at the next 00:

00. 2) Intraday scheduling: The execution frequency is 96 times / day, with a resolution of 15 minutes. The output of each controllable unit in the system is dynamically adjusted based on the day-ahead strategy. The forward-looking window for rolling optimization is 4 hours. After each optimization, only the scheduling plan for the first 15 minutes in the forward-looking window is updated, and the plans for subsequent time periods will be adjusted in the subsequent rolling cycles.

10. A computer-readable storage medium having stored thereon computer program instructions that can be executed by a processor, and when the processor executes the computer program instructions, the method steps according to any one of claims 1 to 9 can be implemented.

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