Power system low-carbon economic dispatching method considering marginal carbon emission factors

Abstract

The invention provides a power system low-carbon economic dispatching method considering a marginal carbon emission factor, and the method comprises the steps: determining a power system pre-dispatching plan with the lowest comprehensive cost according to a pre-dispatching load optimization curve after the power system carries out the electricity price type demand response in a pre-dispatching stage, and generating a time-varying electricity price scheme; calculating a marginal carbon emission factor of each load node according to the pre-scheduled load capacity and unit output; in the rescheduling stage, the demand response model considering the marginal carbon emission factor is solved, and the load curve is readjusted; and inputting the load optimization curve obtained in the pre-scheduling stage into the demand response model recording the marginal carbon emission factors, and after obtaining a re-scheduling load optimization curve, re-optimizing the comprehensive cost of the power system and making a re-scheduling plan.

Description

Technical Field

[0001] The present invention belongs to the technical fields of power system, low-carbon economy, etc., and specifically relates to a low-carbon economic dispatching method for a power system taking into account a marginal carbon emission factor. Background Art

[0002] As global climate change intensifies, low-carbon economy has become the focus of energy transformation in various countries. As one of the main sources of carbon emissions, the dispatch optimization of the power system plays a key role in achieving low-carbon goals. The economic dispatch of traditional power systems focuses on meeting power demand and reducing production costs. As carbon dioxide emission reduction has become the core consensus of the energy industry, it is difficult to effectively respond to environmental challenges by focusing only on economic costs.

[0003] The marginal carbon emission factor (MCEF) is an important indicator for evaluating the carbon emissions of power production units. Incorporating the marginal carbon emission factor into the unit output decision model can more accurately reflect the impact of each power generation method on the environment. Against the background of the increasing proportion of renewable energy in the power system, how to reasonably allocate the proportion of power generation from traditional fossil fuels and renewable energy while ensuring the security of power supply is the core issue of achieving low-carbon scheduling. Therefore, it is of great significance to study an optimal scheduling method that takes into account both economy and low carbon while ensuring the safe operation of the system.

[0004] At present, the low-carbon economic dispatch (LCED) problem of the system is mainly studied in two aspects: implementing the carbon trading mechanism on the source side and guiding the energy consumption behavior of users on the load side, so as to achieve the reduction of carbon emissions.

[0005] From the power supply side, the carbon trading mechanism is currently one of the most effective emission reduction measures in the low-carbon context. It improves the enthusiasm of power production units for low-carbon emission reduction through measures such as the allocation and trading of carbon emission rights. However, only power generation scheduling on the power supply side cannot fully tap the carbon reduction potential of the system. Demand-side response, as a flexible resource, has great potential in the low-carbon level of the load side of the power system. From the load side, demand response (DR) is an important way to reduce carbon emissions. By mobilizing a variety of flexible resources on the user side, it can effectively reduce the peak-to-valley difference, increase the renewable energy absorption rate, and ultimately improve the low-carbon performance of the system.

[0006] Although the above methods have improved the low-carbon economy of the system to a certain extent, they all reveal the possibility of low-carbon operation of the system from the perspective of energy, and the current demand response strategy only considers the comfort and efficiency of electricity use by users. The guiding factors in the incentive response model have no actual physical meaning. In addition, the current demand response strategy often ignores the user's willingness to "reduce carbon" and fails to explore the low-carbon potential of the system user side from the perspective of "carbon". Summary of the invention

[0007] In view of the defects and shortcomings of the above-mentioned prior art, the present invention provides a low-carbon economic dispatch method for power system considering marginal carbon emission factors, and its main design includes:

[0008] (1) Considering the user's electricity cost, carbon emission cost, electricity utility and the benefits of voluntary emission reduction, a low-carbon demand response mechanism guided by marginal carbon emission factors is established;

[0009] (2) By taking the electricity price-based demand response mechanism as the first-stage incentive strategy and the low-carbon demand response mechanism guided by the marginal carbon emission factor as the second-stage incentive strategy, a load-side two-stage demand response model taking into account the marginal carbon emission factor is constructed;

[0010] (3) A two-stage demand response is considered on the load side, and a reasonable tiered carbon trading mechanism is formulated on the source side. Low-carbon and economic efficiency are comprehensively considered, and a two-stage pre-dispatch-reschedule low-carbon economic dispatch model that considers marginal carbon emission factors is constructed.

[0011] The technical solution specifically adopted by the present invention to solve the technical problem is:

[0012] A low-carbon economic dispatch method for power systems considering marginal carbon emission factors:

[0013] In the pre-dispatch stage, the pre-dispatch plan with the lowest comprehensive cost is determined based on the pre-dispatch load optimization curve after the power system implements the electricity price-based demand response, and a time-varying electricity price plan is generated; and the marginal carbon emission factor of each load node is calculated based on the load volume and unit output after pre-dispatch;

[0014] In the re-dispatch stage, the demand response model considering the marginal carbon emission factor is solved and the load curve is readjusted. The load optimization curve obtained in the pre-dispatch stage is input into the demand response model taking into account the marginal carbon emission factor. After obtaining the re-dispatch load optimization curve, the comprehensive cost of the power system is re-optimized and a re-dispatch plan is formulated.

[0015] Furthermore, in the pre-dispatch stage, the electricity consumption behavior of users is adjusted by changing the electricity price, thereby changing the power load demand; the price elasticity coefficient matrix is ​​used to describe the mutual influence of electricity price and power load, as shown below:

[0016]

[0017] Where: q t is the power load during period t; p t is the electricity price in period t; Δq t is the change in power load during period t; Δp t is the change in electricity price in period t; E is the price elasticity coefficient matrix, and T is the number of optimal dispatch periods of the power system;

[0018] The load power after adjustment by electricity price demand response is as follows:

[0019] P t PDR =P t +Δq t

[0020] Where: represents the load power after the user participates in demand response at time t; P t represents the original load power at time t; Δq t Indicates the load change at time t.

[0021] Furthermore, the marginal carbon emission factor of each load node is calculated based on the pre-scheduled load and unit output as follows:

[0022] The load after optimization of electricity price demand response is pre-dispatched to obtain the output of each unit and the carbon emissions of the system; on this basis, each node increases the unit load, and the system is optimized and dispatched again to obtain a new unit dispatch plan and a new total carbon emission of the system; the marginal carbon emission factor of each node is obtained by subtracting the total carbon emission before and after the load is increased, as shown below:

[0023]

[0024] Where: is the marginal carbon emission factor of load i at time t; D is the set of all loads, G is the set of all generators, is the output of generator set i at time t; e i is the unit carbon emission intensity of generator set i.

[0025] Furthermore, the pre-dispatch stage aims to minimize the overall system cost, including the power generation cost of thermal power units, the gas purchase cost of gas units, the wind power penalty cost, and the carbon trading cost; as shown below:

[0026] F=min(F E +F G +F W +F CET )

[0027] Where: F is the comprehensive cost; F E F is the power generation cost of thermal power units; G F is the gas purchase cost of the gas unit; W Penalty cost for wind curtailment; F CET is the carbon trading cost; the specific operating costs of each part are as follows:

[0028]

[0029] Where: P G,i,t and P GT,i,t are the power generation of thermal power unit i and gas turbine i respectively; Ω e is the collection of thermal power units; a i , b i 、c i is the consumption cost coefficient of thermal power units. Ω gt is the collection of gas units; k g is the natural gas cost coefficient; η gt is the conversion efficiency of the gas turbine; H HV High calorific value of natural gas; Ω w is the set of fans; k w is the wind abandonment penalty coefficient, ξ is the daily carbon trading price on the power generation side; E p and E q are carbon emission quota and actual carbon emission respectively; γ, γ g and γ gt are the carbon emission quota per unit active output of the generator, the carbon emission intensity of the thermal power unit and the carbon emission intensity of the gas turbine respectively; d and κ represent the step interval length and the step growth rate respectively.

[0030] Furthermore, in the pre-dispatch stage, the optimal dispatch constraints of the power system include line flow constraints, upper and lower limits of the normal output of each unit, ramp constraints, power balance constraints, and electricity price-based demand response constraints, specifically including:

[0031] (1) Line flow constraints

[0032]

[0033] Where: Ω EL is the set of grid nodes; P ij,t , x ij are the transmission power, transmission power upper limit and reactance of branch ij respectively; θ i,t is the phase angle of node i; and θ re,t are the phase angle upper limit of node i and the phase angle of the reference node respectively;

[0034] (2) Output constraints of conventional units

[0035]

[0036] Where: They are the upper and lower limits of thermal power unit and gas turbine output respectively;

[0037] (3) Conventional unit climbing constraints

[0038]

[0039] Where: They are the downward ramp rate and upward ramp rate of thermal power unit and gas turbine respectively;

[0040] (4) Fan output constraints

[0041]

[0042] Where: P W,i,t and are the predicted amount and actual absorption amount of wind turbine i respectively;

[0043] (5) Node power balance constraints

[0044]

[0045] Where: is the electrical load of node i at time t after PDR; Ω i is the set of nodes connected to node i;

[0046] (6) Electricity price-based demand response constraints

[0047]

[0048] Where: min This is the lowest value for satisfaction with electricity usage. is the minimum value of satisfaction with electricity expenditure; α is the single-point load transfer limit of electricity price-based demand response.

[0049] Furthermore, according to the calculation results of the carbon emission factor, users adjust the load in each period in combination with their own electricity cost, carbon emission cost, and electricity utility; the specific expressions of each part are as follows:

[0050]

[0051] Where: ΔU i,t are the change in electricity cost, carbon cost, and electricity utility of load i at time t, respectively; p c is the carbon price on the load side of the carbon market, is the change in load i at time t after load-side demand response taking into account marginal carbon emissions, and θ i It is the electricity utility parameter.

[0052] Furthermore, in the redispatch phase, a demand response model taking into account the marginal carbon emission factor is constructed with the goal of maximizing user benefits; considering that the marginal carbon emission rate of the node where load i is located is 0 at a certain moment, the marginal unit is a renewable energy unit; when the node marginal carbon emission rate is set to 0, the load increases electricity consumption and obtains additional CCER rewards from the renewable energy unit; the objective function is as follows:

[0053]

[0054] Where: F is the total revenue increment on the load side; is the CCER reward amount of load i at time t;

[0055]

[0056] Where: a i,t is a binary variable if and only if When it is 0, its value is 1; μ is the CCER exchange parameter;

[0057] The constraints in the load rescheduling phase include load transfer constraints and user response constraints, as shown below:

[0058]

[0059]

[0060] Where: is the result after load i is re-dispatched at time t, and β is the single-point load transfer limit in the load re-dispatching stage.

[0061] Furthermore, in the re-dispatch stage, the unit output is realized according to the load curve of the user after deep low-carbon transfer; the objective function and constraints of the unit output plan in the re-dispatch stage are the same as those in the pre-dispatch stage, except for the electricity price-type demand response constraints.

[0062] And, a low-carbon economic dispatching system for a power system considering marginal carbon emission factors, comprising:

[0063] The pre-dispatch module is used to determine the pre-dispatch plan of the power system with the lowest comprehensive cost based on the pre-dispatch load optimization curve after the power system implements the electricity price-based demand response, and generate a time-varying electricity price plan; and calculate the marginal carbon emission factor of each load node based on the load volume and unit output after pre-dispatch;

[0064] The re-dispatching module is used to solve the demand response model considering the marginal carbon emission factor and readjust the load curve; the load optimization curve obtained in the pre-dispatching stage is input into the demand response model taking into account the marginal carbon emission factor, and by solving the re-dispatching load optimization curve, the re-optimized power system re-dispatching plan with the lowest comprehensive cost is obtained.

[0065] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of a method for low-carbon economic dispatch of an electric power system taking into account a marginal carbon emission factor are implemented as described above.

[0066] A non-transitory computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a method for low-carbon economic dispatch of a power system that considers marginal carbon emission factors as described above.

[0067] Compared with the prior art, the present invention and its preferred solution take into account both the economy and low carbon of the system. First, the initial load of the system is adjusted once through electricity price-based demand response, and a low-carbon economic pre-dispatch model is constructed with the goal of minimizing the comprehensive cost of the system, which preliminarily realizes the system's peak shaving and valley filling, and reduces the peak-to-valley difference of the output of the generator set; secondly, based on the pre-dispatch results, the marginal carbon emission factor of the load node is calculated, and its low-carbon incentive benefit is analyzed, with the goal of maximizing the reduction of relevant costs on the user side and the increase in emission reduction benefits, and combined with the marginal carbon emission factor, a load-side low-carbon demand response mechanism is established to encourage users to transfer loads to the period when new energy power generation is abundant, and promote the consumption of new energy; finally, a two-stage demand response model on the load side is constructed, and a low-carbon economic dispatch model considering the marginal carbon emission factor is constructed in combination with the ladder carbon trading mechanism, which effectively reduces the economic cost of the system while further reducing the carbon emissions of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments:

[0069] Figure 1 The figure is a flow chart of a method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0070] In order to make the features and advantages of this patent more obvious and easy to understand, the following embodiments are specifically described in detail as follows:

[0071] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in this specification have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0072] 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.

[0073] 1 Two-stage demand response model on the load side

[0074] In the solution provided in this embodiment, the price-based demand response (PDR) method is adopted in the pre-dispatch stage. After the power system implements PDR, the user's electricity consumption behavior is adjusted by changing the electricity price, thereby changing the power load demand. This embodiment uses a price elasticity coefficient matrix to describe the mutual influence between electricity price and power load, as shown below:

[0075]

[0076] Where: q t is the power load during period t; p t is the electricity price in period t; Δq t is the change in power load during period t; Δp t is the change in electricity price in period t. E is the price elasticity coefficient matrix, and T is the number of optimal dispatch periods of the power system.

[0077] The load power after PDR adjustment is as follows:

[0078] P t PDR =P t +Δq t (2)

[0079] Where: represents the load power after the user participates in demand response at time t; P t represents the original load power at time t; Δq t Indicates the load change at time t.

[0080] The load after PDR optimization is pre-scheduled to obtain the output of each unit and the carbon emissions of the system. On this basis, each node increases the unit load, and the system is optimized and dispatched again to obtain a new unit scheduling plan and a new total carbon emission of the system. By subtracting the total carbon emissions before and after the load is increased, the marginal carbon emission factor of each node is obtained, as shown below:

[0081]

[0082] Where: is the marginal carbon emission factor of load i at time t; D is the set of all loads, G is the set of all generators, is the output of generator set i at time t; e i is the unit carbon emission intensity of generator set i.

[0083] According to the calculation results of the carbon emission factor, users adjust the load in each period based on their own electricity cost, carbon emission cost, and electricity utility. The specific expressions of each part are as follows:

[0084]

[0085] Where: ΔU i,t They are the change in electricity cost, carbon cost, and electricity utility of load i at time t. c is the carbon price on the load side of the carbon market, is the change in load i at time t after load-side demand response taking into account marginal carbon emissions, and θ i It is the electricity utility parameter.

[0086] 2 Pre-dispatch-re-dispatch two-stage low-carbon economic dispatch model

[0087] The goal of the pre-dispatch stage is to minimize the overall system cost, which mainly includes the power generation cost of thermal power units, the gas purchase cost of gas units, the penalty cost of wind power abandonment, and the carbon trading cost. As shown below:

[0088] F=min(F E +F G +F W +F CET ) (5)

[0089] Where: F is the comprehensive cost; F E F is the power generation cost of thermal power units; G F is the gas purchase cost of the gas unit; W Penalty cost for wind curtailment; F CET is the carbon trading cost. The specific operating costs of each part are as follows:

[0090]

[0091]

[0092] Where: P G,i,t and P GT,i,t are the power generation of thermal power unit i and gas turbine (GT) i respectively. Ω e is the collection of thermal power units; a i , bi 、c i is the consumption cost coefficient of thermal power units. Ω gt is the collection of gas units; k g is the natural gas cost coefficient. gt is the conversion efficiency of GT; H HV It is the high calorific value of natural gas. w is the set of fans; k w is the wind abandonment penalty coefficient, ξ is the daily carbon trading price on the power generation side; E p and E q are carbon emission quota and actual carbon emission respectively. g and γ gt are the carbon emission quota per unit active output of the generator, the carbon emission intensity of the thermal power unit and the carbon emission intensity of the GT. d and κ represent the step interval length and the step growth rate, respectively.

[0093] The system optimization scheduling constraints in the pre-scheduling stage include network flow constraints, upper and lower limit constraints of the normal output of each unit, climbing constraints, electric power balance constraints, and PDR constraints.

[0094] (1) Line flow constraints

[0095] The branch transmission power is constrained by the phase angle at both ends of the branch and the branch reactance. In order to ensure the safety of line transmission, the upper limit of the transmission power needs to be specified, as shown in formula (11):

[0096]

[0097] Where: Ω EL is the set of grid nodes; P ij,t , x ij are the transmission power, transmission power upper limit and reactance of branch ij respectively; θ i,t is the phase angle of node i; and θ re,t are the phase angle upper limit of node i and the phase angle of the reference node respectively.

[0098] (2) Output constraints of conventional units

[0099] Due to the limitation of unit installed capacity, the unit output needs to be constrained, as shown in formula (12):

[0100]

[0101] Where: They are the upper and lower limits of thermal power units and GT output respectively.

[0102] (3) Unit climbing constraints

[0103] Due to the inertia of unit operation, the unit output in adjacent time periods must meet the ramp constraint, as shown in formula (13):

[0104]

[0105] Where: They are the downward climbing rate and upward climbing rate of thermal power units and GT respectively.

[0106] (4) Fan output constraints

[0107] The fan output is affected by the external environment, and the actual output needs to be limited to a certain range, as shown in formula (14):

[0108]

[0109] Where: P W,i,t and are the predicted and actual consumption of wind turbine i respectively.

[0110] (5) Node power balance constraints

[0111] Node power balance requires that the algebraic sum of the power flowing into and out of a node at any time is zero, as shown in formula (15):

[0112]

[0113] Where: is the electrical load of node i at time t after PDR; Ω i is the set of nodes connected to node i. (6) PDR constraint

[0114]

[0115] Where: min This is the lowest value for satisfaction with electricity usage. is the minimum value of electricity expenditure satisfaction. α is the PDR single point load transfer limit.

[0116] In the load redispatch stage, a demand response model taking into account the marginal carbon emission factor is constructed with the goal of maximizing user benefits. Considering that the marginal carbon emission rate of the node where load i is located is 0 at a certain moment, the marginal unit is a renewable energy unit. Since renewable energy units can sell Chinese certified emission reduction (CCER) corresponding to the power generation as carbon income. In order to further promote the consumption of renewable energy, it is set here that the node marginal carbon emission rate is 0 and the load increases electricity consumption to obtain additional CCER rewards from renewable energy units. In summary, the objective function is as follows:

[0117]

[0118] Where: F is the total revenue increment on the load side. is the CCER reward amount of load i at time t.

[0119]

[0120] Where: a i,t is a binary variable if and only if When it is 0, its value is 1. μ is the CCER exchange parameter.

[0121] The constraints in the load rescheduling stage mainly include load transfer constraints and user response constraints, as shown below:

[0122]

[0123] Where: is the result after load i is re-dispatched at time t, and β is the single-point load transfer limit in the load re-dispatching stage.

[0124] In the re-dispatch phase, the unit output is realized according to the load curve after the users are driven to make deep low-carbon transition in the second phase. The objective function and constraints of the unit output plan in the re-dispatch phase are the same as those in the pre-dispatch phase (except for the PDR constraint).

[0125] 3 Method flow

[0126] The model solution flow chart of the low-carbon economic dispatch method of the power system considering the marginal carbon emission factor proposed in the present invention is as follows: Figure 1 As shown, it includes a pre-scheduling stage and a re-scheduling stage;

[0127] The pre-scheduling stage includes:

[0128] Input electric load forecast data and PDR parameters;

[0129] Solve the pre-dispatch load optimization curve;

[0130] Determine the system pre-dispatch plan with the lowest overall cost;

[0131] and solving the marginal carbon emission factor of each load node;

[0132] For the mulligan phase, it includes:

[0133] Input the pre-dispatch load curve into the demand response model taking into account the marginal carbon emission factor;

[0134] Solve the redispatch load optimization curve;

[0135] Determine the system redispatch plan with the lowest overall cost.

[0136] The corresponding specific steps are as follows:

[0137] Step 1: Determine the unit dispatch plan based on the load curve after PDR, and generate a reasonable time-varying electricity price plan;

[0138] Step 2: Calculate the marginal carbon emission factor of each load node based on the pre-dispatched load and unit output;

[0139] Step 3: Solve the demand response model considering the marginal carbon emission factor and readjust the load curve;

[0140] Step 4: Input the load curve obtained in step 3 into the system scheduling model to obtain the scheduling result after the system is re-optimized.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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 in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0145] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0146] 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.

[0147] This patent is not limited to the above-mentioned optimal implementation mode. Anyone can derive various other forms of a low-carbon economic dispatching method for power systems that consider marginal carbon emission factors under the inspiration of this patent. All equal changes and modifications made within the scope of the patent application of this invention shall fall within the scope of coverage of this patent.

Claims

1. A low-carbon economic dispatch method for power system considering marginal carbon emission factors, characterized by: In the pre-dispatch stage, the pre-dispatch plan with the lowest comprehensive cost is determined based on the pre-dispatch load optimization curve after the power system implements the electricity price-based demand response, and a time-varying electricity price plan is generated; and the marginal carbon emission factor of each load node is calculated based on the load volume and unit output after pre-dispatch; In the re-dispatch phase, the demand response model considering the marginal carbon emission factor is solved to readjust the load curve; The load optimization curve obtained in the pre-dispatch stage is input into the demand response model with the marginal carbon emission factor. After obtaining the re-dispatch load optimization curve, the comprehensive cost of the power system is re-optimized and a re-dispatch plan is formulated.

2. The method for low-carbon economic dispatch of a power system based on considering marginal carbon emission factors according to claim 1, characterized in that: In the pre-dispatch stage, the electricity consumption behavior of users is adjusted by changing the electricity price, thereby changing the power load demand; the price elasticity coefficient matrix is ​​used to describe the mutual influence of electricity price and power load, as shown below: Where: q t is the power load during period t; p t is the electricity price in period t; Δq t is the change in power load during period t; Δp t is the change in electricity price in period t; E is the price elasticity coefficient matrix, and T is the number of optimal dispatch periods of the power system; The load power after adjustment by electricity price demand response is as follows: Where: represents the load power after the user participates in demand response at time t; P t represents the original load power at time t; Δq t Indicates the load change at time t.

3. The method for low-carbon economic dispatch of power system considering marginal carbon emission factors according to claim 1, characterized in that: The marginal carbon emission factor of each load node is calculated based on the pre-scheduled load and unit output. Specifically: The load after optimization of electricity price demand response is pre-dispatched to obtain the output of each unit and the carbon emissions of the system; on this basis, each node increases the unit load, and the system is optimized and dispatched again to obtain a new unit dispatch plan and a new total carbon emission of the system; the marginal carbon emission factor of each node is obtained by subtracting the total carbon emission before and after the load is increased, as shown below: Where: is the marginal carbon emission factor of load i at time t; D is the set of all loads, G is the set of all generators, is the output of generator set i at time t; e i is the unit carbon emission intensity of generator set i.

4. The method for low-carbon economic dispatch of power system considering marginal carbon emission factors according to claim 1, characterized in that: The goal of the pre-dispatch stage is to minimize the overall system cost, including the power generation cost of thermal power units, the gas purchase cost of gas units, the wind power penalty cost, and the carbon trading cost; as shown below: F=min(F E +F G +F W +F CET ) Where: F is the comprehensive cost; F E F is the power generation cost of thermal power units; G F is the gas purchase cost of the gas unit; W Penalty cost for wind curtailment; F CET is the carbon trading cost; the specific operating costs of each part are as follows: Where: P G,i,t and P GT,i,t are the power generation of thermal power unit i and gas turbine i respectively; Ω e is the collection of thermal power units; a i , b i 、c i is the consumption cost coefficient of thermal power units. Ω gt is the collection of gas units; k g is the natural gas cost coefficient; η gt is the conversion efficiency of the gas turbine; H HV High calorific value of natural gas; Ω w is the set of fans; k w is the wind abandonment penalty coefficient, ξ is the daily carbon trading price on the power generation side; E p and E q are carbon emission quota and actual carbon emission respectively; γ, γ g and γ gt are the carbon emission quota per unit active output of the generator, the carbon emission intensity of the thermal power unit and the carbon emission intensity of the gas turbine respectively; d and κ represent the step interval length and the step growth rate respectively.

5. The method for low-carbon economic dispatch of power system considering marginal carbon emission factors according to claim 1, characterized in that: In the pre-dispatch stage, the optimal dispatch constraints of the power system include line flow constraints, upper and lower limits of the conventional output of each unit, ramp constraints, power balance constraints, and electricity price demand response constraints. Specifically, they include: (1) Line flow constraints Where: Ω EL is the set of grid nodes; P ij,t , x ij are the transmission power, transmission power upper limit and reactance of branch ij respectively; θ i,t is the phase angle of node i; and θ re,t are the phase angle upper limit of node i and the phase angle of the reference node respectively; (2) Output constraints of conventional units Where: They are the upper and lower limits of thermal power unit and gas turbine output respectively; (3) Conventional unit climbing constraints Where: They are the downward ramp-up rate and upward ramp-up rate of thermal power units and gas turbines respectively; (4) Fan output constraints Where: P W,i,t and are the predicted amount and actual absorption amount of wind turbine i respectively; (5) Node power balance constraints Where: is the electrical load of node i at time t after PDR; Ω i is the set of nodes connected to node i; (6) Electricity price-based demand response constraints Where: min This is the lowest value for satisfaction with electricity usage. is the minimum value of satisfaction with electricity expenditure; α is the single-point load transfer limit of electricity price-based demand response.

6. The method for low-carbon economic dispatch of power system considering marginal carbon emission factors according to claim 1, characterized in that: According to the calculation results of the carbon emission factor, users adjust the load in each period based on their own electricity cost, carbon emission cost, and electricity utility; the specific expressions of each part are as follows: Where: ΔU i,t are the change in electricity cost, carbon cost, and electricity utility of load i at time t, respectively; p c is the carbon price on the load side of the carbon market, is the change in load i at time t after load-side demand response taking into account marginal carbon emissions, and θ i It is the electricity utility parameter.

7. The method for low-carbon economic dispatch of power system considering marginal carbon emission factors according to claim 1, characterized in that: In the redispatch phase, a demand response model taking into account the marginal carbon emission factor is constructed with the goal of maximizing user benefits; considering that the marginal carbon emission rate of the node where load i is located is 0 at a certain moment, the marginal unit is a renewable energy unit; when the marginal carbon emission rate of the node is set to 0, the load increases electricity consumption and obtains additional CCER rewards from the renewable energy unit; the objective function is as follows: Where: F is the total revenue increment on the load side; is the CCER reward amount of load i at time t; Where: a i,t is a binary variable if and only if When it is 0, its value is 1; μ is the CCER exchange parameter; The constraints in the load rescheduling phase include load transfer constraints and user response constraints, as shown below: Where: is the result after load i is re-dispatched at time t, and β is the single-point load transfer limit in the load re-dispatching stage.

8. The method for low-carbon economic dispatch of power system considering marginal carbon emission factors according to claim 1, characterized in that: During the re-dispatch phase, the unit output is realized according to the load curve of users after deep low-carbon transfer; the objective function and constraints of the unit output plan in the re-dispatch phase are the same as those in the pre-dispatch phase, except for the electricity price-type demand response constraints.

9. A low-carbon economic dispatching system for power systems considering marginal carbon emission factors, characterized in that: include: A pre-dispatch module is used to determine the pre-dispatch plan of the power system with the lowest comprehensive cost according to the pre-dispatch load optimization curve after the power system implements the electricity price-based demand response, and generate a time-varying electricity price plan; And according to the pre-dispatched load and unit output, the marginal carbon emission factor of each load node is calculated; The re-dispatch module is used to solve the demand response model considering the marginal carbon emission factor and readjust the load curve; The load optimization curve obtained in the pre-dispatch stage is input into the demand response model with the marginal carbon emission factor. After obtaining the re-dispatch load optimization curve, the comprehensive cost of the power system is re-optimized and a re-dispatch plan is formulated.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of a low-carbon economic dispatch method for a power system taking into account a marginal carbon emission factor as described in any one of claims 1-8 are implemented.

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