Low-carbon operation scheduling system and method of CCUS comprehensive energy system

Abstract

The invention provides a low-carbon operation scheduling system and method of a CCUS integrated energy system, and the method comprises the steps: constructing a first mathematical model of a two-dimensional demand response with a space-time coupling property, and constructing an energy load model containing a plurality of energy types according to the first mathematical model; constructing a load response constraint model for the first mathematical model; constructing an energy price model based on marginal costs of different types of generator sets and gas distribution stations, and constructing a system cost model about the CCUS integrated energy system; and performing power balance constraint and carbon emission balance constraint on the system cost model, taking system cost minimization as a target, constructing a target function according to the system cost model, and solving the target function under various constraint conditions to obtain an optimal system cost model. The energy utilization rate can be effectively increased, the operation cost of the system is reduced, and low-carbon economical operation is achieved.

Description

Technical Field

[0001] The present invention relates to the field of network security protection technology, and in particular to a low-carbon operation scheduling system and method for a CCUS integrated energy system. Background Art

[0002] Faced with the increasingly serious global climate change problem, the construction of a new energy and power system with a gradually increasing proportion of new energy is ready to go, and the system should be promoted to evolve in the direction of adapting to large-scale and high-proportion new energy, and to improve the system's carrying capacity and flexibility for new energy and diversified loads. To achieve this goal, the energy industry is an indispensable part of the "dual carbon" goal. How to achieve the transformation of the energy industry to reduce carbon emissions is an important topic. As a clean and efficient form of energy utilization, the integrated energy system has great development potential and broad prospects.

[0003] The combustion of fossil fuels within the integrated energy system will inevitably emit carbon dioxide. Therefore, in the process of reducing carbon emissions, in addition to vigorously developing and absorbing renewable energy such as wind power and photovoltaic power, the combination of CCUS (carbon capture, utilization, and storage) technology and the integrated energy system is an effective attempt. CCUS captures the carbon dioxide produced before, during, and after fuel combustion. The captured carbon dioxide is either used as a raw material for the reaction of combustible gases (such as natural gas or hydrogen) or stored and isolated from the atmosphere, which can effectively reduce carbon emissions and achieve low-carbon operation. It should be noted that in the context of multiple stakeholders, how to reduce the system operation cost by coordinating the scheduling between the supply side and the user side of the integrated energy system has become an issue that cannot be ignored. Summary of the invention

[0004] The object of the present invention is to provide a low-carbon operation scheduling system and method for a CCUS integrated energy system, aiming to solve at least one problem in the background technology.

[0005] In a first aspect, the present invention provides a low-carbon operation scheduling method for a CCUS integrated energy system, characterized in that the method comprises:

[0006] Constructing a first mathematical model of two-dimensional demand response with time-space coupling properties, and constructing an energy load model including multiple energy types based on the first mathematical model;

[0007] constructing a load response constraint model for the first mathematical model;

[0008] An energy price model is constructed based on the marginal costs of different types of generators and gas distribution stations, and a system cost model for the CCUS integrated energy system is constructed. The system cost model includes a wind power abandonment cost model, a procurement cost model, an operation and maintenance cost model, and a carbon trading cost model.

[0009] The system cost model is subjected to power balance constraints and carbon emission balance constraints, with the goal of minimizing system cost, and an objective function is constructed according to the system cost model, and the objective function is solved under various constraints to obtain an optimal system cost model.

[0010] In summary, according to the low-carbon operation scheduling method of the CCUS integrated energy system mentioned above, by considering the two-dimensional spatiotemporal coupling comprehensive demand response and dynamic price of the CCUS integrated energy system low-carbon operation scheduling model, it can effectively improve energy utilization, reduce the operating cost of the system, and achieve low-carbon economic operation. According to the demand response between the energy supplier and the user side, the price is dynamically adjusted to maximize the benefits of multiple subjects. Specifically, first, the present invention establishes a two-dimensional demand response model with spatiotemporal coupling characteristics, including two dimensions of time and space; secondly, an energy price model is established, and the user side adjusts its energy use through the supplier and the two-dimensional demand model, and finally obtains the optimal value of the energy price; then, a low-carbon operation model of the CCUS integrated energy system is established, and the CCUS part is added to the original integrated energy system to achieve low-carbon economic scheduling optimization; finally, the optimal cost is calculated while ensuring user satisfaction and reducing operating costs.

[0011] Furthermore, a first mathematical model is constructed according to the following formula:

[0012]

[0013] in, is the load after two-dimensional demand response is achieved. is the initial load, and are the load response amounts of users participating in the horizontal spatial dimension demand response and the vertical temporal dimension demand response, * indicates the implementation of demand response on multiple types of energy, u t is a variable ranging from 0 to 1. is a participation coefficient;

[0014] The energy load model is constructed according to the following formula:

[0015]

[0016] η x,y =(W x ·V x ) / (W y ·V y )

[0017]

[0018] in, and are the electrical loads coupled with the heat load and gas load, and are the heat loads coupled with the electrical load and the gas load, and are the gas loads coupled with the electrical load and the thermal load, represents the change of each load after considering demand response, η x,y is the energy conversion coefficient, Indicates the autocoupling of the electrical load, Indicates the autocoupling quantity of the heat load, Indicates the autocoupling quantity of the gas load, Indicates the electrical load, represents the heat load, Indicates gas load, It represents the total demand of a certain type of load in the vertical time dimension demand response. Represents the coupling demand response between different loads in the longitudinal time dimension, It represents the demand response of electric load in the time dimension, Indicates the change in demand response of heat load in the time dimension, Indicates the change in gas load demand response in the time dimension, They represent the demand response changes of the electric load, heat load and gas load coupled in the time dimension, They represent the demand response changes of the coupling between heat load, electricity load and gas load in the time dimension. They represent the demand response variation of gas load coupled with electric load and heat load in the time dimension, W x , W y Respectively represent the calorific value and utilization efficiency of unit energy of different loads in the horizontal dimension, V x 、V y They respectively represent the calorific value and utilization efficiency of unit energy of different loads in the vertical dimension.

[0019] Furthermore, the response constraint model is constructed according to the following formula:

[0020]

[0021] in, It represents the change of each load after considering the demand response. and Represent the minimum switching load and the maximum switching load, respectively. is the maximum transferable load, Represents the demand response amount of different loads in the time dimension, represents the demand response amount on different loads in the spatial dimension, It represents the initial response amount of different load demand responses.

[0022] Furthermore, the energy price model is constructed according to the following formula:

[0023]

[0024] in, and are the operating cost of the generator set and the cost of the gas station supplier, P e,t , P g,t are the electricity load and gas load of CCUS integrated energy system, a x ,b x ,c x are all cost operation parameters, x∈{e,g}, represents the dynamic electricity price, represents the dynamic gas price, Indicates the dynamic rate of change of electricity price, Indicates the dynamic change rate of gas price, χ e,t , χ g,t Respectively represent the profit coefficients of electricity and gas, χ e,t and χ g,t All of them are profit coefficients greater than 1.

[0025] Furthermore, the system cost model is constructed according to the following formula:

[0026]

[0027] C un =c un (p un,e +p un,h +p un,g )

[0028] Among them, C buy represents the purchase cost, C Ο&Μ represents the system operation and maintenance cost, C cur represents the cost of wind power abandonment of renewable energy, C un Indicates the penalty for non-delivery of carbon trading, and are the prices of electricity and natural gas, respectively, chp , c gb , c eb , c pv , c wt , c cc , c p2g , c cs , c ees , c tes , c gesThey are the cost coefficients of CHP (combined heat and power), GB (gas boiler), EB (electric boiler), PV (photovoltaic), WT (wind power), CC (carbon capture), P2G (power to gas), CS (carbon storage), EES (electric energy storage), TES (thermal energy storage), and GES (gas energy storage). They represent CHP (combined heat and power) output, GB (gas boiler) output, EB (electric boiler) output, photovoltaic unit output, abandoned light amount, wind turbine unit output, abandoned wind amount, carbon capture equipment output, P2G (power to gas) equipment output, carbon storage, electric energy storage charging amount, electric energy storage discharging amount, thermal energy storage charging amount, thermal energy storage discharging amount, gas energy storage charging amount, gas energy storage discharging amount, p un,e 、p un,h 、p un,g Respectively represent the undelivered electricity, heat and gas loads, c cur and c un are the penalty coefficients for absorbing renewable energy and undelivered load, respectively, un,e 、p un,h 、p un,g Represents the undelivered electricity, heat and gas loads respectively.

[0029] Furthermore, the power balance constraint is performed according to the following formula:

[0030]

[0031] in, and Respectively represent the electrical power output of PV (photovoltaic) and WT (wind power), and is the abandoned power of PV (photovoltaic) and WT (wind power), Indicates the purchased electrical power, Indicates the electrical power generated by the CHP (combined heat and power) unit, Indicates the discharge power of the energy storage device, Indicates the electrical power consumed by P2G (power-to-gas), Indicates the electric power consumed by the EB (electric boiler) unit. Indicates the charging power of the energy storage device, Indicates the power consumed in achieving carbon capture, Represents the user's demand for electricity, Indicates the electrical power that has not been delivered, They represent the heat generation power of CHP (combined heat and power), GB (gas boiler), and EB (electric boiler) units respectively. and represent the heat release and heat storage power of the thermal energy storage device, Indicates the user's demand for thermal power, Indicates the electrical power not delivered;

[0032] Carbon emission balance constraint is performed according to the following formula:

[0033]

[0034] in, is the direct CO2 emission of the proposed system, and They are the carbon dioxide produced by CHP (combined heat and power) units and GB (gas boiler) equipment. represents the amount of carbon dioxide captured, and denoted as carbon storage and CO2 from power-to-gas, respectively;

[0035] The additional constraints are constructed according to the following formula:

[0036]

[0037] in, p chp , They represent the lower and upper limits of the output of the CHP (combined heat and power) unit, p gb , They represent the lower and upper limits of the GB (gas boiler) unit output respectively. Indicates the upper limit of EB (electric boiler) unit power. p p2g,e , They represent the lower and upper limits of the power consumption of P2G (power-to-gas) equipment. Represent the power of different energy storage components, Respectively represent the charging and discharging status of different energy storage elements. p st , They respectively represent the lower and upper power limits of different energy storage elements.

[0038] Furthermore, the objective function is constructed according to the following formula:

[0039] minC sys =C buy +C O&M +C cur +C un

[0040] Among them, minC sys Minimize system cost.

[0041] In a second aspect, the present invention provides a low-carbon operation scheduling system for a CCUS integrated energy system, the system comprising:

[0042] A first model building module, used to build a first mathematical model of two-dimensional demand response with time-space coupling properties, and to build an energy load model containing multiple energy types according to the first mathematical model;

[0043] A constraint model building module, used for building a load response constraint model for the first mathematical model;

[0044] A cost model building module is used to build an energy price model based on the marginal costs of different types of generators and gas distribution stations themselves, and to build a system cost model for the CCUS integrated energy system, which includes a wind power abandonment cost model, a procurement cost model, an operation and maintenance cost model, and a carbon trading cost model;

[0045] The objective function construction module is used to perform power balance constraints and carbon emission balance constraints on the system cost model, with the goal of minimizing the system cost, and to construct an objective function based on the system cost model, and to solve the objective function under various constraints to obtain an optimal system cost model.

[0046] In a third aspect, the present invention provides a storage medium storing one or more programs, which, when executed by a processor, implement the low-carbon operation scheduling method of the CCUS integrated energy system.

[0047] In a fourth aspect, the present invention provides an electronic device, the electronic device comprising a memory and a processor, wherein:

[0048] The memory is used to store computer programs;

[0049] When the processor is used to execute the computer program stored in the memory, the low-carbon operation scheduling method of the CCUS integrated energy system is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A flowchart of a low-carbon operation scheduling method for a CCUS integrated energy system proposed in one embodiment of the present invention;

[0051] Figure 2 The overall framework diagram of the CCUS integrated energy system in one embodiment of the present invention;

[0052] Figure 3 A prediction curve diagram of different energy loads in one embodiment of the present invention;

[0053] Figure 4 A comparison diagram of dynamic electricity price changes under four different simulation situations exemplified in an embodiment of the present invention;

[0054] Figure 5A comparison diagram of dynamic gas price changes under four different simulation situations exemplified in an embodiment of the present invention;

[0055] Figure 6 A schematic diagram of the structure of a low-carbon operation scheduling system for a CCUS integrated energy system proposed in one embodiment of the present invention.

[0056] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Unless otherwise defined, the technical terms or scientific terms used herein should be understood by people with general skills in the field to which the present invention belongs. "Including" and similar words used in this article 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.

[0058] like Figure 1 and Figure 2 As shown, an embodiment of the present invention provides a low-carbon operation scheduling method for a CCUS integrated energy system, the method comprising steps S101 to S104, wherein:

[0059] Step S101: constructing a first mathematical model of a two-dimensional demand response with a time-space coupling property, and constructing an energy load model including multiple energy types according to the first mathematical model;

[0060] It should be pointed out that the first mathematical model is constructed according to the following formula:

[0061]

[0062] in, is the load after two-dimensional demand response is achieved. is the initial load, and are the load response amounts of users participating in the horizontal spatial dimension demand response and the vertical temporal dimension demand response, * indicates the implementation of demand response on multiple types of energy, u t is a 0-1 variable, is a participation coefficient, which is used to explore the relationship between users’ willingness to participate in demand response and their energy use comfort.

[0063] In addition, if Figure 3 As shown in Figure 1, the model takes into account the potential dependencies between different electricity, heating and gas loads. For example, when the demand for heating and gas increases, the user's electricity demand will decrease. The specific expressions of different types of energy load models are as follows:

[0064]

[0065] η x,y =(W x ·V x ) / (W y ·V y )

[0066]

[0067] In the formula and are the electrical loads coupled with the heat load and gas load, and are the heat loads coupled with the electrical load and the gas load, and are the gas loads coupled with the electrical load and the thermal load, Indicates the change of each load after considering demand response. η x,y It is the energy conversion coefficient (effective calorific value ratio per unit energy). Indicates the autocoupling of the electrical load, Indicates the autocoupling quantity of the heat load, Indicates the autocoupling quantity of the gas load, Indicates the electrical load, represents the heat load, Indicates gas load, It represents the total demand of a certain type of load in the vertical time dimension demand response. Represents the coupling demand response between different loads in the longitudinal time dimension, It represents the demand response of electric load in the time dimension, Indicates the change in demand response of heat load in the time dimension, Indicates the change in gas load demand response in the time dimension, They represent the demand response changes of the electric load, heat load and gas load coupled in the time dimension, They represent the demand response changes of the coupling between heat load, electricity load and gas load in the time dimension. They represent the demand response variation of gas load coupled with electric load and heat load in the time dimension, W x , W y Respectively represent the calorific value and utilization efficiency of unit energy of different loads in the horizontal dimension, V x 、Vy They respectively represent the calorific value and utilization efficiency of unit energy of different loads in the vertical dimension.

[0068] Step S102: constructing a load response constraint model for the first mathematical model;

[0069] In this step, the response constraint model is constructed according to the following formula:

[0070]

[0071] in, It represents the change of each load after considering the demand response. and Represent the minimum switching load and the maximum switching load, respectively. is the maximum transferable load, Represents the demand response amount of different loads in the time dimension, represents the demand response amount on different loads in the spatial dimension, It represents the initial response amount of different load demand responses.

[0072] Step S103: constructing an energy price model based on the marginal costs of different types of generator sets and gas distribution stations themselves, and constructing a system cost model for the CCUS integrated energy system, wherein the system cost model includes a wind power abandonment cost model, a procurement cost model, an operation and maintenance cost model, and a carbon trading cost model;

[0073] It should be pointed out that the marginal cost of energy suppliers increases with the increase of equipment output, and the energy procurement cost of system operators also increases quadratically with the increase of energy purchases. Therefore, different types of generators and gas distribution stations in energy suppliers have formulated different electricity price curves based on their own marginal cost functions, as follows:

[0074]

[0075] In the formula, and are the operating cost of the generator set and the cost of the gas station supplier, P e,t , P g,t are the electricity load and gas load of CCUS integrated energy system, a x ,b x ,c x , x∈{e,g} is the cost operation parameter, represents the dynamic electricity price, represents the dynamic gas price, Indicates the dynamic rate of change of electricity price, Indicates the dynamic change rate of gas price, χe,t , χ g,t Represent the profit coefficients of electricity and gas respectively.

[0076]

[0077] The above two formulas are expressed as the electricity price change curve, that is, the energy price model, χ e,t and χ g,t is a profit coefficient greater than 1.

[0078] In addition, the purpose of constructing the system cost model is to minimize the system cost and optimize the low-carbon operation, as follows:

[0079] The system cost model is constructed according to the following formula:

[0080]

[0081] C un =c un (p un,e +p un,h +p un,g )

[0082] Among them, C buy represents the purchase cost, C Ο&Μ represents the system operation and maintenance cost, C cur represents the cost of wind power abandonment of renewable energy, C un Indicates the penalty for non-delivery of carbon trading, and are the prices of electricity and natural gas, respectively, chp , c gb , c eb , c pv , c wt , c cc , c p2g , c cs , c ees , c tes , c ges They are the cost coefficients of CHP (combined heat and power), GB (gas boiler), EB (electric boiler), PV (photovoltaic), WT (wind power), CC (carbon capture), P2G (power to gas), CS (carbon storage), EES (electric energy storage), TES (thermal energy storage), and GES (gas energy storage). They represent CHP (combined heat and power) output, GB (gas boiler) output, EB (electric boiler) output, photovoltaic unit output, abandoned light, wind turbine output, abandoned wind, carbon capture equipment output, P2G (power to gas) equipment output, carbon storage, electric energy storage charging, electric energy storage discharging, thermal energy storage charging, thermal energy storage releasing, gas storage charging, gas storage releasing, p un,e 、p un,h 、p un,g Respectively represent the undelivered electricity, heat and gas loads, c cur and c un are the penalty coefficients for absorbing renewable energy and undelivered load, respectively, un ,e 、p un,h 、p un,g Represents the undelivered electricity, heat and gas loads respectively.

[0083] Step S104: The system cost model is subjected to power balance constraints and carbon emission balance constraints, with the goal of minimizing system cost, and an objective function is constructed according to the system cost model, and the objective function is solved under various constraints to obtain an optimal system cost model.

[0084] It should be noted that this step mainly involves power balance constraints, carbon emission balance constraints and other constraints on the system cost model, as follows:

[0085] (1) Power balance constraints:

[0086] The electrical power balance is subject to the following constraints:

[0087]

[0088] Where: and Represent the electrical power output of PV (photovoltaic) and WT (wind power), and is the abandoned power of PV (photovoltaic) and WT (wind power), Indicates the purchased electrical power, Indicates the electrical power generated by the CHP (combined heat and power) unit, Indicates the discharge power of the energy storage device, Indicates the electrical power consumed by P2G (power-to-gas), Indicates the electric power consumed by the EB (electric boiler) unit. Indicates the charging power of the energy storage device, Indicates the power consumed in achieving carbon capture, Represents the user's demand for electricity, Indicates electrical power that was not delivered.

[0089] The thermal power balance is subject to the following constraints:

[0090]

[0091] In the formula They represent the heat generation power of CHP (combined heat and power unit), GB (gas boiler), and EB (electric boiler) units respectively. and represent the heat release and heat storage power of the thermal energy storage device, Indicates the user's demand for thermal power.

[0092] (2) Carbon emission balance constraints:

[0093]

[0094] The first line in the above formula represents the carbon balance at the system level. is the direct CO2 emission of the proposed system, and They are the carbon dioxide produced by CHP (combined heat and power) units and GB (gas boiler) equipment. represents the amount of captured CO2, and the second row represents the carbon balance within CCUS, indicating that the captured CO2 is either stored or converted into natural gas. and denoted as carbon storage and power-to-gas CO2, respectively.

[0095] (3) Other constraints:

[0096]

[0097] In the formula, p chp , They represent the lower and upper limits of the CHP (combined heat and power) output, p gb , They represent the lower and upper limits of GB (gas boiler unit) output respectively. Indicates the upper limit of EB (electric boiler unit) power. p p2g,e , They represent the lower and upper limits of the power consumption of P2G (power-to-gas) equipment. Represent the power of different energy storage components, Respectively represent the charging and discharging status of different energy storage elements. p st , They respectively represent the lower and upper power limits of different energy storage elements.

[0098] Furthermore, the objective function is constructed according to the following formula:

[0099] minC sys =C buy +C O&M +C cur +C un

[0100] Among them, minC sys Minimize system cost.

[0101] Finally, under the conditions of ensuring power balance constraints and capacity constraints of various devices, the cplex solver is used to solve the problem and obtain the optimal solution that minimizes the system cost.

[0102] like Figure 4 and Figure 5 As shown, this example simulates the low-carbon operation scheduling model of the CCUS integrated energy system considering two-dimensional spatiotemporal coupling integrated demand response and dynamic price in the environment of MATLAB2022R2022A. The present invention considers four cases: (1) the energy price, total system cost, and carbon emissions of the CCUS integrated energy system without considering the integrated demand response; (2) the energy price, total system cost, and carbon emissions of the CCUS integrated energy system considering only the time demand response; (3) the energy price, total system cost, and carbon emissions of the CCUS integrated energy system considering only the spatial demand response; (4) the energy price, total system cost, and carbon emissions of the CCUS integrated energy system considering the two-dimensional spatiotemporal coupling integrated demand response. The simulation parameters are shown in Tables 1 to 4 below:

[0103] Table 1 Initial energy prices

[0104]

[0105] Table 2 System operation cost parameters

[0106]

[0107] Table 3 Carbon emissions of the final system

[0108]

[0109] Table 4 Total dispatch cost of the final system

[0110]

[0111] Result description:

[0112] The four modes are simulated and analyzed respectively to obtain the final costs and carbon emissions. It can be found that the total cost of the present invention is the lowest, and the carbon emissions are also the least, which meets the standard of low-carbon economic operation.

[0113] In summary, according to the low-carbon operation scheduling method of the CCUS integrated energy system mentioned above, by considering the two-dimensional spatiotemporal coupling comprehensive demand response and dynamic price of the CCUS integrated energy system low-carbon operation scheduling model, it can effectively improve energy utilization, reduce the operating cost of the system, and achieve low-carbon economic operation. According to the demand response between the energy supplier and the user side, the price is dynamically adjusted to maximize the benefits of multiple subjects. Specifically, first, the present invention establishes a two-dimensional demand response model with spatiotemporal coupling characteristics, including two dimensions of time and space; secondly, an energy price model is established, and the user side adjusts its energy use through the supplier and the two-dimensional demand model, and finally obtains the optimal value of the energy price; then, a low-carbon operation model of the CCUS integrated energy system is established, and the CCUS part is added to the original integrated energy system to achieve low-carbon economic scheduling optimization; finally, the optimal cost is calculated while ensuring user satisfaction and reducing operating costs.

[0114] like Figure 6 As shown, an embodiment of the present invention further provides a low-carbon operation scheduling system for a CCUS integrated energy system, the system comprising:

[0115] A first model building module 10 is used to build a first mathematical model of a two-dimensional demand response with a time-space coupling property, and to build an energy load model including multiple energy types according to the first mathematical model;

[0116] A constraint model building module 20, used to build a load response constraint model for the first mathematical model;

[0117] A cost model building module 30 is used to build an energy price model based on the marginal costs of different types of generator sets and gas distribution stations themselves, and to build a system cost model for the CCUS integrated energy system, wherein the system cost model includes a wind power abandonment cost model, a procurement cost model, an operation and maintenance cost model, and a carbon trading cost model;

[0118] The objective function building module 40 is used to perform power balance constraints and carbon emission balance constraints on the system cost model, with the goal of minimizing the system cost, and to build an objective function based on the system cost model, and to solve the objective function under various constraints to obtain the optimal system cost model.

[0119] On the other hand, the present invention further proposes a storage medium on which one or more programs are stored, and when the program is executed by a processor, the low-carbon operation scheduling method of the CCUS integrated energy system is implemented.

[0120] On the other hand, the present invention further proposes an electronic device, including a memory and a processor, wherein the memory is used to store computer programs, and the processor is used to execute the computer programs stored in the memory to implement the low-carbon operation scheduling method of the CCUS integrated energy system mentioned above.

[0121] Those skilled in the art will appreciate that the logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable instructions for implementing logical functions, and may be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For purposes of this specification, "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0122] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0123] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0124] Although the embodiments of the present invention are described in detail above, it is obvious to those skilled in the art that various modifications and variations can be made to these embodiments. However, it should be understood that such modifications and variations are within the scope and spirit of the present invention as described in the claims. Moreover, the present invention described herein may have other embodiments and may be implemented or realized in a variety of ways.

Claims

1. A low-carbon operation scheduling method for a CCUS integrated energy system, characterized in that: The method comprises: Constructing a first mathematical model of two-dimensional demand response with time-space coupling properties, and constructing an energy load model including multiple energy types based on the first mathematical model; constructing a load response constraint model for the first mathematical model; An energy price model is constructed based on the marginal costs of different types of generators and gas distribution stations, and a system cost model for the CCUS integrated energy system is constructed. The system cost model includes a wind power abandonment cost model, a procurement cost model, an operation and maintenance cost model, and a carbon trading cost model. The system cost model is subjected to power balance constraints and carbon emission balance constraints, with the goal of minimizing system cost, and an objective function is constructed according to the system cost model, and the objective function is solved under various constraints to obtain an optimal system cost model.

2. The low-carbon operation scheduling method of the CCUS integrated energy system according to claim 1 is characterized in that: The first mathematical model is constructed according to the following formula: in, is the load after achieving two-dimensional demand response, is the initial load, and are the load response amounts of users participating in the horizontal spatial dimension demand response and the vertical temporal dimension demand response, * indicates the implementation of demand response on multiple types of energy, u t is a variable ranging from 0 to 1. is a participation coefficient; The energy load model is constructed according to the following formula: η x,y =(In x ·V x ) / (IN y ·V y ) in, and are the electrical loads coupled with the heat load and gas load, and are the heat loads coupled with the electrical load and the gas load, and are the gas loads coupled with the electrical load and the thermal load, represents the change of each load after considering demand response, η x,y is the energy conversion coefficient, Indicates the autocoupling of the electrical load, Indicates the autocoupling quantity of the heat load, Indicates the autocoupling quantity of the gas load, Indicates the electrical load, represents the heat load, Indicates gas load, It represents the total demand of a certain type of load in the vertical time dimension demand response. Represents the coupling demand response between different loads in the longitudinal time dimension, It represents the demand response of electric load in the time dimension, Indicates the change in demand response of heat load in the time dimension, Indicates the change in gas load demand response in the time dimension, They represent the demand response changes of the electric load, heat load and gas load coupled in the time dimension, They represent the demand response changes of the coupling between heat load, electricity load and gas load in the time dimension. They represent the demand response variation of gas load coupled with electric load and heat load in the time dimension, W x , W y Respectively represent the calorific value and utilization efficiency of unit energy of different loads in the horizontal dimension, V x 、V y They respectively represent the calorific value and utilization efficiency of unit energy of different loads in the vertical dimension.

3. The low-carbon operation scheduling method of the CCUS integrated energy system according to claim 2 is characterized in that: The response constraint model is constructed according to the following formula: in, It represents the change of each load after considering the demand response. and Represent the minimum switching load and the maximum switching load, respectively. is the maximum transferable load, Represents the demand response amount of different loads in the time dimension, represents the demand response amount on different loads in the spatial dimension, It represents the initial response amount of different load demand responses.

4. The low-carbon operation scheduling method of the CCUS integrated energy system according to claim 3 is characterized in that: The energy price model is constructed according to the following formula: in, and are the operating cost of the generator set and the cost of the gas station supplier, P e,t , P g,t are the electricity load and gas load of CCUS integrated energy system, a x ,b x ,c x are all cost operation parameters, x∈{e,g}, represents the dynamic electricity price, represents the dynamic gas price, Indicates the dynamic rate of change of electricity price, Indicates the dynamic change rate of gas price, χ e,t , χ g,t Respectively represent the profit coefficients of electricity and gas, χ e,t and χ g,t All of them are profit coefficients greater than 1.

5. The low-carbon operation scheduling method of the CCUS integrated energy system according to claim 4 is characterized in that: The system cost model is constructed according to the following formula: C un =c un (p un,e +p un,h +p un,g ) Among them, C buy represents the purchase cost, C Ο&Μ represents the system operation and maintenance cost, C cur represents the cost of wind power abandonment of renewable energy, C un Indicates the penalty for non-delivery of carbon trading, and are the prices of electricity and natural gas, respectively, chp , c gb , c eb , c pv , c wt , c cc , c p2g , c cs , c ees , c tes , c ges They are the cost coefficients of CHP (combined heat and power), GB (gas boiler), EB (electric boiler), PV (photovoltaic), WT (wind power), CC (carbon capture), P2G (power to gas), CS (carbon storage), EES (electric energy storage), TES (thermal energy storage), and GES (gas energy storage). They represent CHP (combined heat and power) output, GB (gas boiler) output, EB (electric boiler) output, photovoltaic unit output, abandoned light, wind turbine output, abandoned wind, carbon capture equipment output, P2G (power to gas) equipment output, carbon storage, electric energy storage charging, electric energy storage discharging, thermal energy storage charging, thermal energy storage releasing, gas storage charging, gas storage releasing, p un,e 、p un,h 、p un,g Respectively represent the undelivered electricity, heat and gas loads, c cur and c un are the penalty coefficients for absorbing renewable energy and undelivered load, respectively, un,e 、p un,h 、p un,g Represents the undelivered electricity, heat and gas loads respectively.

6. The low-carbon operation scheduling method of the CCUS integrated energy system according to claim 5 is characterized in that: The power balance constraint is performed according to the following formula: in, and Represent the electrical power output of PV (photovoltaic) and WT (wind power), and is the abandoned power of PV (photovoltaic) and WT (wind power), Indicates the purchased electrical power, Indicates the electrical power generated by the CHP (combined heat and power) unit, Indicates the discharge power of the energy storage device, Indicates the electrical power consumed by P2G (power-to-gas), Indicates the electric power consumed by the EB (electric boiler) unit. Indicates the charging power of the energy storage device, Indicates the power consumed in achieving carbon capture, Represents the user's demand for electricity, Indicates the electrical power that has not been delivered, They represent the heat generation power of CHP (combined heat and power), GB (gas boiler), and EB (electric boiler) units respectively. and represent the heat release and heat storage power of the thermal energy storage device, Indicates the user's demand for thermal power, Indicates the electrical power not delivered; Carbon emission balance constraint is performed according to the following formula: in, is the direct CO2 emission of the proposed system, and They are the carbon dioxide produced by CHP (combined heat and power) units and GB (gas boiler) equipment. represents the amount of carbon dioxide captured, and denoted as carbon storage and CO2 from power-to-gas, respectively; The additional constraints are constructed according to the following formula: in, p chp , They represent the lower and upper limits of the output of the CHP (combined heat and power) unit, p gb , They represent the lower and upper limits of the GB (gas boiler) unit output respectively. Indicates the upper limit of EB (electric boiler) unit power. p p2g,e , They represent the lower and upper limits of the power consumption of P2G (power-to-gas) equipment. Represent the power of different energy storage components, Respectively represent the charging and discharging status of different energy storage elements. p st , They respectively represent the lower and upper power limits of different energy storage elements.

7. The low-carbon operation scheduling method of the CCUS integrated energy system according to claim 6 is characterized in that: The objective function is constructed according to the following formula: minC sys =C buy +C O&M +C cur +C un Among them, minC sys Minimize system cost.

8. A low-carbon operation and dispatching system for a CCUS integrated energy system, characterized in that: The system comprises: A first model building module, used to build a first mathematical model of two-dimensional demand response with time-space coupling properties, and to build an energy load model containing multiple energy types according to the first mathematical model; A constraint model building module, used for building a load response constraint model for the first mathematical model; A cost model building module is used to build an energy price model based on the marginal costs of different types of generators and gas distribution stations themselves, and to build a system cost model for the CCUS integrated energy system, which includes a wind power abandonment cost model, a procurement cost model, an operation and maintenance cost model, and a carbon trading cost model; The objective function construction module is used to perform power balance constraints and carbon emission balance constraints on the system cost model, with the goal of minimizing the system cost, and to construct an objective function based on the system cost model, and to solve the objective function under various constraints to obtain an optimal system cost model.

9. A storage medium, characterized in that: The storage medium stores one or more programs, which, when executed by a processor, implement the low-carbon operation scheduling method for a CCUS integrated energy system as described in any one of claims 1 to 7.

10. An electronic device, comprising a memory and a processor, wherein: The memory is used to store computer programs; When the processor is used to execute the computer program stored in the memory, the low-carbon operation scheduling method of the CCUS integrated energy system as described in any one of claims 1 to 7 is implemented.

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