Low-carbon integrated energy system optimization planning method and system considering clean energy

Abstract

The present invention relates to a method and system for optimizing planning of a low-carbon integrated energy system considering clean energy, the method comprising the following steps: constructing a typical structure of an integrated energy system with clean energy access; establishing a mathematical model of the energy equipment based on the operating characteristics of various energy equipment in the typical structure; establishing an optimal planning model of the integrated energy system with the goal of minimizing the total planning cost, the constraints adopted by the optimal planning model include power balance constraints, equipment construction quantity constraints, equipment output constraints, clean energy output constraints, and energy equipment operation constraints constructed based on the mathematical model; solving the optimal planning model to obtain the optimal configuration capacity of various energy equipment. Compared with the prior art, the present invention can realize the planning and configuration of multiple types of energy equipment in the integrated energy system, meet various energy requirements of the system, and ensure the safe, stable and economical operation of the system.

Description

Technical Field

[0001] The present invention relates to the field of integrated energy, and in particular to a method and system for optimizing planning of a low-carbon integrated energy system taking clean energy into consideration. Background Art

[0002] The increasing depletion of fossil fuels and environmental pollution have become increasingly prominent, which has played an important role in promoting energy transformation. How to optimize the energy structure and promote the efficient and rational use of energy has become a topic of common concern to all mankind.

[0003] The integrated energy system realizes the coupling, association and complementary assistance of heterogeneous energy sources such as electricity, gas, heat and cold. While meeting the needs of multi-energy loads, it improves the economy and environmental protection of energy utilization, and provides a new way to achieve comprehensive energy management and regulation and build a low-carbon sustainable energy system. The integrated energy system also breaks the existing model of separate planning of traditional heterogeneous energy systems such as electricity, gas, heat and cold, and realizes the unified and coordinated planning of different energy systems.

[0004] The more abundant energy demands of users in the integrated energy system, the more diversified and complex energy equipment, and the access to renewable energy have brought new challenges to the planning and safe and stable operation of the integrated energy system. How to achieve the optimal planning and configuration of the integrated energy system taking into account multiple types of energy equipment, meet the needs of various energy loads, and further improve the economy and reliability of the integrated energy system is a technical problem that needs to be solved in this field. Summary of the invention

[0005] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a low-carbon integrated energy system optimization planning method and system taking clean energy into consideration to effectively ensure the safe, stable and economical operation of the system.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] A low-carbon integrated energy system optimization planning method considering clean energy includes the following steps:

[0008] Construct a typical structure of an integrated energy system with clean energy access;

[0009] Based on the operating characteristics of various energy devices in the typical structure, a mathematical model of the energy device is established;

[0010] Establishing an optimal planning model for a comprehensive energy system with the goal of minimizing the total planning cost, wherein the constraints adopted by the optimal planning model include power balance constraints, equipment construction quantity constraints, equipment output constraints, clean energy output constraints, and energy equipment operation constraints constructed based on the mathematical model;

[0011] The optimal planning model is solved to obtain the optimal configuration capacity of various energy equipment.

[0012] Furthermore, the typical structure of the integrated energy system contains four energy sources: electricity, gas, heat and cold, and is equipped with a variety of energy equipment.

[0013] Furthermore, the energy device includes an energy conversion device and an energy storage device.

[0014] Furthermore, the energy conversion equipment includes transformers, power-to-gas equipment, gas turbines, gas boilers, electric boilers, electric refrigerators and absorption refrigerators, wherein:

[0015] The mathematical model of the transformer is:

[0016]

[0017] Where: is the output power of the transformer at time t; is the input power of the transformer at time t; η TF is the conversion efficiency of the transformer;

[0018] The mathematical model of the power-to-gas device is:

[0019] P P2G,g,t =P P2G,e,t η P2G

[0020] Where: P P2G,g,t is the output natural gas power of power-to-gas at time t; P P2G,e,t is the input power of the power-to-gas converter at time t; η P2G The energy conversion efficiency of electricity to gas;

[0021] The mathematical model of the gas turbine is:

[0022] P GT,e,t =P GT,g,t η GT,e

[0023] P GT,h,t =P GT,g,t η GT,h

[0024] P GT,h,t =P GT,e,t R GT

[0025] Where: P GT,g,t is the natural gas power input to the gas turbine at time t; P GT,e,t and P GT,h,t are the output electrical power and output thermal power of the gas turbine at time t, respectively; ηGT,e and η GT,h are the gas-to-electricity efficiency and gas-to-heat efficiency of the gas turbine respectively; R GT is the thermal-to-electricity ratio coefficient of the gas turbine;

[0026] The mathematical model of the gas boiler is:

[0027] P GB,h,t =P GB,g,t η GB

[0028] Where: P GB,h,t is the output thermal power of the gas boiler at time t; P GB,g,t is the natural gas power input to the gas boiler at time t; η GB Energy conversion efficiency of gas boilers;

[0029] The mathematical model of the electric boiler is:

[0030] P EB,h,t =P EB,e,t η EB

[0031] Where: P EB,h,t is the output thermal power of the electric boiler at time t; P EB,e,t is the input power of the electric boiler at time t; η EB Energy conversion efficiency of electric boilers;

[0032] The mathematical model of the electric refrigerator is:

[0033] P EC,c,t =P EC,e,t η EC

[0034] Where: P EC,c,t is the cooling power output of the electric refrigerator at time t; P EC,e,t is the input power of the electric refrigerator at time t; η EC is the efficiency of the electric refrigerator;

[0035] The mathematical model of the absorption refrigerator is:

[0036] P AC,c,t =P AC,h,t η AC

[0037] Where: P AC,c,t is the cooling power output of the absorption refrigerator at time t; P AC,h,t is the input heat power of the absorption refrigerator at time t; η AC is the efficiency of the absorption chiller.

[0038] Furthermore, the data model of the energy storage device is:

[0039]

[0040]

[0041]

[0042]

[0043] Where: P t ch and P t dis are the charging and discharging power of the energy storage device at time t; It is a binary variable representing the state of charge and discharge, 1 represents charge and 0 represents discharge; n ES is the number of energy storage devices; and They are the upper limits of charging and discharging power respectively; is the capacity of the energy storage device at time t; η ch and η dis are the charging and discharging efficiencies respectively; Δt is the time interval; E ES is the rated power of the energy storage device; and S They are the upper and lower limit coefficients of energy storage equipment capacity respectively.

[0044] Furthermore, the total planning cost includes energy equipment investment cost and system operation cost.

[0045] Furthermore, the energy equipment investment cost C inv The calculation formula is:

[0046]

[0047] The system operating cost C op The calculation formula is:

[0048]

[0049] Where: V is the candidate energy equipment set; v is the candidate energy equipment type number; w is the energy equipment number; is the unit investment cost of energy equipment with type v and number w; P v,w is the rated power of the energy equipment of type v and number w; X v,w is the number of energy equipment of type v and number w; r is the annual interest rate; y is the number of planning years; D is the set of typical days; d is the typical day number; T is the set of time periods; t is the time period number; θ dis the typical day d weight coefficient; To purchase electrical power value; The unit price of electricity; To purchase natural gas power value; is the unit price of natural gas; Δt is the time interval.

[0050] Furthermore, the power balance constraint is expressed as:

[0051]

[0052]

[0053] P GT,h,t +P GB,h,t +P EB,h,t =L h,t +P AC,h,t

[0054] P EC,c,t +P AC,c,t =L c,t

[0055] Where: P PV,e,t is the output power of the photovoltaic at time t; is the output power of the transformer at time t; P GT,e,t and P GT,h,t are the output electrical power and output thermal power of the gas turbine at time t respectively; P EC,e,t is the input power of the electric refrigerator at time t; P EB,e,t is the input power of the electric boiler at time t; P P2G,e,t is the input power of the power-to-gas converter at time t; L e,t is the electrical load power of the system at time t; and are the charging and discharging power of the energy storage at time t respectively; is the purchased natural gas power of the system at time t; P P2G,g,t is the output natural gas power of power-to-gas at time t; P GB,g,t is the natural gas power input to the gas boiler at time t; P GT,g,t is the natural gas power input to the gas turbine at time t; L g,t is the gas load power of the system at time t; and are the charging and discharging powers of the gas tank at time t respectively; P EB,h,t is the output thermal power of the electric boiler at time t; L h,t is the heat load power of the system at time t; P AC,h,t is the input heat power of the absorption refrigerator at time t; P EC,c,tis the cooling power output of the electric refrigerator at time t; P AC,c,t is the cooling power output of the absorption refrigerator at time t; L c,t is the cooling load power of the system at time t;

[0056] The equipment construction quantity constraint is expressed as:

[0057]

[0058] Where: X v,w is the number of energy equipment of type v and number w, is the corresponding upper limit of quantity;

[0059] The equipment output constraint is expressed as:

[0060]

[0061] Where: P v,w,t is the output power of the energy device of type v and number w at time t; The output limit of the energy device with type v and number w;

[0062] The clean energy output constraint includes a photovoltaic output constraint, which is expressed as:

[0063]

[0064] Where: P PV,e,t is the output power of the photovoltaic at time t; It is the upper limit of photovoltaic output.

[0065] Furthermore, the energy equipment operation constraints include energy conversion equipment operation constraints and energy storage equipment operation constraints.

[0066] The present invention also provides a low-carbon integrated energy system optimization planning system taking clean energy into consideration, comprising one or more processors, a memory and one or more programs stored in the memory, wherein the one or more programs include instructions for executing the low-carbon integrated energy system optimization planning method as described above.

[0067] Compared with the prior art, the present invention has the following beneficial effects:

[0068] The present invention constructs a typical structure of an integrated energy system with clean energy access, takes into account various types of energy equipment in the integrated energy system, and constructs an optimal planning model for the integrated energy system with the goal of minimizing the total planning cost. It can accurately and effectively optimize the optimal configuration capacity of energy equipment, and can realize the planning and configuration of multiple types of energy equipment in the integrated energy system, meet various energy needs of the system, and ensure the safe, stable and economical operation of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 It is a schematic diagram of the process of the present invention;

[0070] Figure 2 This is a typical structural diagram of IES;

[0071] Figure 3 It is the typical day multi-energy load and photovoltaic coefficient curve;

[0072] Figure 4 This is a schematic diagram of the balance of electric power and natural gas power on a typical day under scenario 1;

[0073] Figure 5 This is a schematic diagram of the balance of electric power and natural gas power on a typical day under scenario 2;

[0074] Figure 6 Schematic diagram of the balance of electric power and natural gas power on a typical day under scenario 3. DETAILED DESCRIPTION

[0075] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0076] like Figure 1 As shown, this embodiment provides a method for optimizing the planning of a low-carbon integrated energy system considering clean energy, including the following steps: S1, constructing a typical structure of an integrated energy system with clean energy access, including four types of energy: electricity, gas, heat, and cold, and a variety of energy equipment; S2, abstracting based on the operating characteristics of various types of energy equipment in the typical structure, and establishing a mathematical model of the energy equipment; S3, establishing an optimal planning model for the integrated energy system with the goal of minimizing the total planning cost, and the constraints adopted by the optimal planning model include power balance constraints, equipment construction quantity constraints, equipment output constraints, clean energy output constraints, and energy equipment operation constraints based on the mathematical model; S4, solving the optimal planning model to obtain the optimal configuration capacity of various types of energy equipment. This method can realize the planning and configuration of multiple types of energy equipment in the integrated energy system, meet various energy requirements of the system, and ensure the safe, stable and economical operation of the system.

[0077] 1. Typical structure of integrated energy system

[0078] The typical structure of an integrated energy system (IES) that includes electricity, gas, heat and cold is as follows: Figure 2As shown. IES mainly consists of three parts: energy input, energy conversion and storage, and energy utilization. IES obtains energy through the upper-level power grid, upper-level gas grid and photovoltaics, transforms and stores energy through energy conversion and storage equipment, and finally transmits energy to users. The power load is powered by the upper-level power grid, photovoltaics, gas turbines and electric energy storage connected by transformers. When the system has sufficient power, the electric energy storage is charged to store excess power, and when the power is insufficient, the electric energy storage is discharged to provide power supply. The heat load is powered by gas turbines, gas boilers and electric boilers. The cold load is powered by electric refrigerators and absorption refrigerators. The gas load is powered by the upper-level gas grid, power-to-gas and gas storage tanks.

[0079] 2. Energy Equipment Modeling

[0080] 2.1 Energy conversion equipment

[0081] Energy conversion equipment realizes the coupling and conversion of energy. Figure 2 The energy conversion equipment in is specifically modeled as follows:

[0082] (1) Transformer

[0083] Transformer is the basic equipment for power transmission and distribution. It has the functions of voltage conversion, current conversion, impedance conversion, etc. The relationship between its input and output power can be modeled as follows:

[0084]

[0085] Where: is the output power of the transformer at time t; is the input power of the transformer at time t; η TF is the conversion efficiency of the transformer.

[0086] (2) Power-to-gas

[0087] Power-to-gas technology uses electricity to generate natural gas, which strengthens the coupling between the power system and the natural gas system. The power-to-gas technology can be modeled as follows:

[0088] P P2G,g,t =P P2G,e,t η P2G (2)

[0089] Where: P P2G,g,t is the output natural gas power of power-to-gas at time t; P P2G,e,t is the input power of the power-to-gas converter at time t; η P2G The energy conversion efficiency of electricity to gas.

[0090] (3) Gas turbine

[0091] The gas turbine consumes natural gas to output electrical energy and thermal energy. Assuming that it works in a constant heat-to-electricity ratio mode, it can be modeled as follows:

[0092] P GT,e,t =P GT,g,t η GT,e (3)

[0093] P GT,h,t =P GT,g,t η GT,h (4)

[0094] P GT,h,t =P GT,e,t R GT (5)

[0095] Where: P GT,g,t is the natural gas power input to the gas turbine at time t; P GT,e,t and P GT,h,t are the output electrical power and output thermal power of the gas turbine at time t, respectively; η GT,e and η GT,h are the gas-to-electricity efficiency and gas-to-heat efficiency of the gas turbine respectively; R GT is the thermal-to-electricity ratio of the gas turbine.

[0096] (4) Gas boiler

[0097] Gas boilers burn natural gas to generate heat energy and are coupling elements between the natural gas system and the thermal system. The relationship between the natural gas input power and the thermal output power of a gas boiler is as follows:

[0098] P GB,h,t =P GB,g,t η GB (6)

[0099] Where: P GB,h,t is the output thermal power of the gas boiler at time t; P GB,g,t is the natural gas power input to the gas boiler at time t; η GB Energy conversion efficiency of gas boilers.

[0100] (5) Electric boiler

[0101] An electric boiler converts electrical energy into thermal energy, which can be modeled as follows:

[0102] P EB,h,t =P EB,e,t η EB (7)

[0103] Where: P EB,h,t is the output thermal power of the electric boiler at time t; P EB,e,t is the input power of the electric boiler at time t; η EBThe energy conversion efficiency of electric boiler.

[0104] (6) Electric Refrigerator

[0105] The electric refrigerator generates cold energy by consuming electrical energy. The specific modeling is as follows:

[0106] P EC,c,t =P EC,e,t η EC (8)

[0107] Where: P EC,c,t is the cooling power output of the electric refrigerator at time t; P EC,e,t is the input power of the electric refrigerator at time t; η EC is the efficiency of the electric refrigerator.

[0108] (7) Absorption Refrigeration Machine

[0109] The absorption chiller generates cold energy by consuming heat energy. The specific modeling is as follows:

[0110] P AC,c,t =P AC,h,t η AC (9)

[0111] Where: P AC,c,t is the cooling power output of the absorption refrigerator at time t; P AC,h,t is the input heat power of the absorption refrigerator at time t; η AC is the efficiency of the absorption chiller.

[0112] 2.2 Energy storage devices

[0113] Energy storage devices can alleviate the contradiction between supply and demand of IES through their flexible charging and discharging behaviors. Energy storage devices can be modeled as follows:

[0114]

[0115]

[0116]

[0117]

[0118] Where: P t ch and P t dis are the charging and discharging power of the energy storage device at time t; It is a binary variable representing the state of charge and discharge, 1 represents charge and 0 represents discharge; n ES is the number of energy storage devices; and They are the upper limits of charging and discharging power respectively; is the capacity of the energy storage device at time t; η ch and η dis are the charging and discharging efficiencies respectively; Δt is the time interval; E ES is the rated power of the energy storage device; and S They are the upper and lower limit coefficients of energy storage equipment capacity respectively.

[0119] 3. Optimal Planning Model for Integrated Energy Systems

[0120] 3.1 Objective Function

[0121] The IES optimal planning model established in this embodiment aims to minimize the total system cost, as shown below:

[0122] min C=C inv +C op (14)

[0123] Where: C is the total cost during the IES planning period; C inv and C op They are energy equipment investment cost and system operation cost respectively.

[0124] C inv and C op The calculation formula is as follows:

[0125]

[0126]

[0127] Where: V is the candidate energy equipment set; v is the candidate energy equipment type number; w is the energy equipment number; is the unit investment cost of energy equipment with type v and number w; P v,w is the rated power of the energy equipment of type v and number w; X v,w is the number of energy equipment of type v and number w; r is the annual interest rate; y is the number of planning years; D is the set of typical days; d is the typical day number; T is the set of time periods; t is the time period number; θ d is the typical day d weight coefficient; To purchase electrical power value; The unit price of electricity; To purchase natural gas power value; is the unit price of natural gas; Δt is the time interval.

[0128] 3.2 Constraints

[0129] (1) Power balance constraints

[0130] The electricity, gas, heat, and cooling buses of IES must meet the following power balance constraints:

[0131]

[0132]

[0133] P GT,h,t +P GB,h,t +P EB,h,t =L h,t +P AC,h,t (19)

[0134] P EC,c,t +P AC,c,t =L c,t (20)

[0135] Where: P PV,e,t is the output power of the photovoltaic at time t; L e,t is the electrical load power of the system at time t; and are the charging and discharging power of the energy storage at time t respectively; is the purchased natural gas power of the system at time t; L g,t is the gas load power of the system at time t; and are the charging and discharging powers of the gas tank at time t; L h,t is the heat load power of the system at time t; L c,t is the cooling load power of the system at time t.

[0136] (2) Equipment construction quantity constraints

[0137] Due to practical factors such as site restrictions, the number of new energy equipment of various types must meet the following constraints:

[0138]

[0139] Where: The upper limit of the number of energy equipment of type v and number w that can be built.

[0140] (3) Equipment output constraints

[0141] To ensure the safe and stable operation of the system and the normal and stable operation of the equipment, the output power of the energy equipment must be lower than its upper limit:

[0142]

[0143] Where: P v,w,tis the output power of the energy device of type v and number w at time t; The output limit of energy equipment of type v and number w.

[0144] (4) Photovoltaic output constraints

[0145] The photovoltaic output in IES must not exceed its upper limit:

[0146]

[0147] Where: P PV,e,t is the output power of the photovoltaic at time t; It is the upper limit of photovoltaic output.

[0148] (5) Energy conversion equipment operation constraints

[0149] The energy conversion equipment in the system must satisfy the constraints shown in equations (1) to (9).

[0150] (6) Energy storage equipment operation constraints

[0151] The energy storage devices in the system must satisfy the constraints shown in equations (10) to (13).

[0152] 4. Application Analysis

[0153] by Figure 2 The IES shown in the figure is used as an example for calculation and analysis. Set 10 types of energy equipment to be planned, and their specific parameters are shown in Table 1; set the electricity prices in peak, flat and valley periods to 1.09 yuan / kWh, 0.62 yuan / kWh and 0.34 yuan / kWh respectively; the natural gas price is 0.2395 yuan / kWh. The typical day multi-energy load and photovoltaic coefficient curves are shown in Figure 3 In order to study the impact of photovoltaic access and natural gas prices on IES planning results, the following three scenarios are set:

[0154] Scenario 1: Considering the access of photovoltaic power generation, the natural gas price is 0.2395 yuan / kWh;

[0155] Scenario 2: Without considering the access of photovoltaic power generation, the natural gas price is 0.2395 yuan / kWh;

[0156] Scenario 3: Considering the access of photovoltaic power generation, the price of natural gas is 0.3814 yuan / kWh.

[0157] Table 1 Parameters of energy equipment to be planned

[0158]

[0159] The planning costs under the three scenarios are shown in Table 2, the planning schemes are shown in Table 3, and the balance of electric power and natural gas power on a typical day under the three scenarios are shown in Table 2. Figure 4 , 5 、6.

[0160] By comparing the planning results of scenario 1 and scenario 2, we can see that, except for the different photovoltaic configuration capacity, the planning results of other energy equipment in these two scenarios are the same. Among them, power-to-gas and electric boilers were not built due to low economic efficiency. Although photovoltaic grid connection increases investment costs, it reduces the cost of purchasing energy from the upper network, thereby reducing the total planning cost. In addition, from Figure 4 and Figure 5 It can be seen that when photovoltaic power is not connected to the system, the power load in the system is only supplied by purchased electricity, electric energy storage and gas turbines. Especially during the daytime in summer, due to the lack of photovoltaic power supply, the amount of purchased electricity increases significantly.

[0161] By comparing the planning results of scenario 1 and scenario 3, we can see that when the price of natural gas rises, electricity is more economical in comparison. The configuration capacity of transformers increases, gas turbines that consume natural gas are no longer built, the configuration capacity of gas boilers that consume natural gas is reduced, the configuration capacity of electric refrigerators increases, absorption refrigerators are no longer built, and electric boilers change from not being built to a configuration capacity of 0.72MW. Electricity-to-gas conversion is also not built due to its high price. Further analysis of Table 2 shows that Figure 4 and Figure 6 It can be seen that when the price of natural gas rises, the configuration of equipment consuming natural gas in the system is reduced, and the total natural gas load of the system is reduced, so the purchase of natural gas is significantly reduced, thereby reducing the cost of purchased natural gas; but the configuration of equipment consuming electricity in the system increases, and the purchase of electricity is significantly increased, thereby increasing the cost of purchased electricity; in addition, the equipment investment cost also increases, which ultimately leads to an increase in the total planning cost.

[0162] Table 2 Planning costs under different scenarios

[0163]

[0164] Table 3 Planning schemes under different scenarios

[0165] Device Type Scenario 1 Scenario 2 Scene 3 Photovoltaic 0.6MW 0 0.6MW transformer 2MW 2MW 4MW Power-to-gas 0 0 0 Electric boiler 0 0 0.72MW Gas boiler 6.5MW 6.5MW 5.2MW gas turbine 2MW 2MW 0 Electric Refrigerator 1.5MW 1.5MW 1.6MW Absorption Chiller 0.36MW 0.36MW 0 Electric energy storage 3MWh 3MWh 3MWh gas tank 1.5MWh 1.5MWh 1.5MWh

[0166] If the above method is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0167] In another embodiment, a low-carbon integrated energy system optimization planning system considering clean energy is provided, comprising one or more processors, a memory and one or more programs stored in the memory, wherein the one or more programs include instructions for executing the low-carbon integrated energy system optimization planning method as described above.

[0168] The preferred specific embodiments of the present invention are described in detail above. It should be understood that a person skilled in the art can make many modifications and changes based on the concept of the present invention without creative work. Therefore, any technical solution that can be obtained by a person skilled in the art through logical analysis, reasoning or limited experiments based on the concept of the present invention on the basis of the prior art should be within the scope of protection determined by the claims.

Claims

1. A low-carbon integrated energy system optimization planning method considering clean energy, characterized in that: The following steps are involved: Construct a typical structure of an integrated energy system with clean energy access; Based on the operating characteristics of various energy devices in the typical structure, a mathematical model of the energy device is established; Establishing an optimal planning model for a comprehensive energy system with the goal of minimizing the total planning cost, wherein the constraints adopted by the optimal planning model include power balance constraints, equipment construction quantity constraints, equipment output constraints, clean energy output constraints, and energy equipment operation constraints constructed based on the mathematical model; Solving the optimal planning model to obtain the optimal configuration capacity of various energy equipment; The typical structure of the comprehensive energy system contains four energy sources: electricity, gas, heat and cold, and is equipped with a variety of energy equipment; The energy equipment includes energy conversion equipment and energy storage equipment; The energy conversion equipment includes transformers, power-to-gas equipment, gas turbines, gas boilers, electric boilers, electric refrigerators and absorption refrigerators, wherein: The mathematical model of the transformer is: Where: is the output power of the transformer at time t; is the input power of the transformer at time t; η TF is the conversion efficiency of the transformer; The mathematical model of the power-to-gas device is: P.S P2G,g,t JP P2G,e,t η P2G Where: P P2G,g,t is the output natural gas power of power-to-gas at time t; P P2G,e,t is the input power of the power-to-gas converter at time t; η P2G The energy conversion efficiency of electricity to gas; The mathematical model of the gas turbine is: P.S GT,e,t JP GT,g,t η GT,e P.S GT,h,t JP GT,g,t η GT,h P GT,h,t =P GT,e,t R GT Where: P GT,g,t is the natural gas power input to the gas turbine at time t; P GT,e,t and P GT,h,t are the output electrical power and output thermal power of the gas turbine at time t, respectively; η GT,e and η GT,h are the gas-to-electricity efficiency and gas-to-heat efficiency of the gas turbine respectively; R GT is the thermal-to-electricity ratio coefficient of the gas turbine; The mathematical model of the gas boiler is: P.S GB,h,t JP GB,g,t η GB Where: P GB,h,t is the output thermal power of the gas boiler at time t; P GB,g,t is the natural gas power input to the gas boiler at time t; η GB Energy conversion efficiency of gas boilers; The mathematical model of the electric boiler is: P.S EB,h,t JP EB,e,t η EB Where: P EB,h,t is the output thermal power of the electric boiler at time t; P EB,e,t is the input power of the electric boiler at time t; η EB Energy conversion efficiency of electric boilers; The mathematical model of the electric refrigerator is: P.S EC,c,t JP EC,e,t η EC Where: P EC,c,t is the cooling power output of the electric refrigerator at time t; P EC,e,t is the input power of the electric refrigerator at time t; η EC is the efficiency of the electric refrigerator; The mathematical model of the absorption refrigerator is: P.S AC,c,t JP AC,h,t η AC Where: P AC,c,t is the cooling power output of the absorption refrigerator at time t; P AC,h,t is the input heat power of the absorption refrigerator at time t; η AC is the efficiency of the absorption chiller; The data model of the energy storage device is: Where: and are the charging and discharging power of the energy storage device at time t; It is a binary variable representing the state of charge and discharge, 1 represents charge and 0 represents discharge; n ES is the number of energy storage devices; and They are the upper limits of charging and discharging power respectively; is the capacity of the energy storage device at time t; η ch and η dis are the charging and discharging efficiencies respectively; Δt is the time interval; E ES is the rated power of the energy storage device; and S are the upper and lower limit coefficients of energy storage equipment capacity respectively; The total planning cost includes the energy equipment investment cost and system operation cost; The energy equipment investment cost C inv The calculation formula is: The system operating cost C op The calculation formula is: Where: V is the candidate energy equipment set; v is the candidate energy equipment type number; w is the energy equipment number; is the unit investment cost of energy equipment with type v and number w; P v,w is the rated power of the energy equipment of type v and number w; X v,w is the number of energy equipment of type v and number w; r is the annual interest rate; y is the number of planning years; D is the set of typical days; d is the typical day number; T is the set of time periods; t is the time period number; θ d is the typical day d weight coefficient; To purchase electrical power value; The unit price of electricity; To purchase natural gas power value; is the unit price of natural gas; Δt is the time interval; The power balance constraint is expressed as: P GT,h,t +P GB,h,t +P EB,h,t =L h,t +P AC,h,t P EC,c,t +P AC,c,t =L c,t Where: P PV,e,t is the output power of the photovoltaic at time t; is the output power of the transformer at time t; P GT,e,t and P GT,h,t are the output electrical power and output thermal power of the gas turbine at time t respectively; P EC,e,t is the input power of the electric refrigerator at time t; P EB,e,t is the input power of the electric boiler at time t; P P2G,e,t is the input power of the power-to-gas converter at time t; L e,t is the electrical load power of the system at time t; and are the charging and discharging power of the energy storage at time t respectively; is the purchased natural gas power of the system at time t; P P2G,g,t is the output natural gas power of power-to-gas at time t; P GB,g,t is the natural gas power input to the gas boiler at time t; P GT,g,t is the natural gas power input to the gas turbine at time t; L g,t is the gas load power of the system at time t; and are the charging and discharging powers of the gas tank at time t respectively; P EB,h,t is the output thermal power of the electric boiler at time t; L h,t is the heat load power of the system at time t; P AC,h,t is the input heat power of the absorption refrigerator at time t; P EC,c,t is the cooling power output of the electric refrigerator at time t; P AC,c,t is the cooling power output of the absorption refrigerator at time t; L c,t is the cooling load power of the system at time t; The equipment construction quantity constraint is expressed as: Where: X v,w is the number of energy equipment of type v and number w, is the corresponding upper limit of quantity; The equipment output constraint is expressed as: Where: P v,w,t is the output power of the energy device of type v and number w at time t; The output limit of the energy device with type v and number w; The clean energy output constraint includes a photovoltaic output constraint, which is expressed as: Where: P PV,e,t is the output power of the photovoltaic at time t; It is the upper limit of photovoltaic output.

2. The low-carbon integrated energy system optimization planning method considering clean energy according to claim 1 is characterized in that: The energy equipment operation constraints include energy conversion equipment operation constraints and energy storage equipment operation constraints.

3. A low-carbon integrated energy system optimization planning system considering clean energy, characterized in that: It comprises one or more processors, a memory and one or more programs stored in the memory, wherein the one or more programs include instructions for executing the low-carbon integrated energy system optimization planning method as described in any one of claims 1-2.

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