Planning Methodology for Integrated Energy Systems in Industrial Parks Considering Demand Response under Carbon Constraints

Abstract

The present invention discloses a planning method for a park integrated energy system considering comprehensive demand response under carbon constraints, including: 1. According to the closing price of historical carbon transactions, establish a carbon transaction income sequence and analyze the volatility and leverage effect of the sequence; 2. Use the exponential generalized autoregressive conditional heteroskedasticity model to establish a prediction model for carbon trading prices; 3. Establish an industrial park integrated energy system planning model considering the comprehensive demand response on the demand side; 4. Establish a mathematical model of replaceable loads and transferable loads of electricity / heat / cold loads on the demand side; 5. Input equipment parameters, typical day load data and energy demand on the demand side, use a mixed integer nonlinear programming solver to solve, output the planning results and control. The present invention can configure the capacity of the equipment under the condition of meeting the energy demand of users under the consideration of dynamic carbon trading prices and comprehensive demand response, thereby improving the energy utilization efficiency of the system.

Description

Technical Field

[0001] The present invention relates to the field of integrated energy technology for industrial parks, and in particular to a planning method for an integrated energy system for industrial parks that takes demand response into consideration under carbon constraints. Background Art

[0002] The park integrated energy system is an integrated energy system close to the user side. Its scale is between the regional integrated energy system and the user-side integrated energy system. It is the hub connecting the regional integrated energy system and the user-side integrated energy system, which can effectively improve the energy utilization efficiency and the absorption capacity of renewable energy. There is a demand for electric heating and cooling energy in the park. Considering the comprehensive demand response can make full use of the multi-energy complementary characteristics of the integrated energy system. Considering the comprehensive demand response in the planning can further reduce the planning cost and improve the economy of the system operation. The comprehensive demand response combines the multi-energy complementary characteristics of each energy in the integrated energy with the traditional power demand response, and expands the demand response that originally existed only in electric energy to multiple types of energy such as electric heating and cooling. Compared with the traditional power demand response, it has a higher demand response potential. However, the comprehensive demand response is more applied to the scheduling of the integrated energy system, and the impact of the comprehensive demand response on the planning is rarely considered. In summary, it is necessary to apply the comprehensive demand response to the planning of the park integrated energy system to improve the scientificity and rationality of the system.

[0003] At present, my country has established a national carbon trading market. Regulatory authorities issue carbon emission quotas to each trading entity, and each trading entity participates in carbon trading based on its own carbon emissions. The carbon trading market has gradually become an effective means to guide the integrated energy system to control carbon emission reduction. At present, most studies focus on the dispatch of carbon trading on the integrated energy system, and rarely consider its impact on planning. Moreover, the integrated energy system only considers the participation in the carbon trading market to trade at a fixed carbon trading price, and the guiding role of the market is limited. Therefore, scholars introduced ladder carbon trading to further constrain the carbon emissions of the integrated energy system. However, this method is limited by the determination of the carbon trading base price and the setting of the interval length. Therefore, there is an urgent need for a method that can reasonably reflect the dynamic changes of the carbon trading market, and combine this method with the integrated energy system planning to provide a more reasonable and practical planning scheme. Summary of the invention

[0004] The present invention aims to address the deficiencies of the above-mentioned prior art and proposes a planning method for a park integrated energy system taking into account demand response under carbon constraints, so as to consider the impact of comprehensive demand response on the basis of a carbon trading prediction model, and to configure the capacity of equipment while meeting the energy needs of users, thereby improving the energy utilization efficiency of the system.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] The planning method of a park integrated energy system considering demand response under carbon constraints of the present invention is characterized in that it includes the following steps:

[0007] Step 1) Obtain the historical carbon trading closing price sequence, and use formula (1) to establish a carbon trading price prediction model based on the historical carbon trading price sequence for the future trend of carbon trading prices:

[0008]

[0009] In formula (1), r d is the carbon emissions trading income on day d; and is the closing price of carbon emission trading on day d; is the closing price of carbon emission trading on day d-1; r d-1 is the carbon emission trading income on the d-1th day; β0 and β1 are the persistence parameters of the sequence; β2 is the asymmetric parameter of the sequence; α1 is the new information parameter; is a constant less than 1; v d It indicates the dth parameter that follows a normal white noise process with a mean of 0 and a variance of 1; ε d is the disturbance term on the dth day, ε d-1 is the disturbance term on day d-1, σ d is the conditional standard deviation on the dth day, α0 is a non-random variable, σ d-1 is the conditional standard deviation on day d-1;

[0010] Step 2) According to the energy demand of the park, determine the energy types and equipment on the supply side, so as to establish a comprehensive energy system for the park, including: photovoltaic equipment, cogeneration units, gas boilers GB, electric boilers EB, P2G equipment, electric / heat / cold energy storage equipment, electric refrigerators, absorption refrigerators and ground source heat pumps;

[0011] Step 3) Collect typical daily load data and equipment parameters of electricity / heat / cold of the park's comprehensive energy system, establish mathematical models of each device and constraints on photovoltaic output and installation capacity, cogeneration unit output and installation capacity, gas boiler and electric boiler output and installation capacity, absorption chiller and electric chiller output and installation capacity, energy storage equipment capacity and output, ground source heat pump capacity and output, and system power balance constraints;

[0012] Step 4) Consider dividing the load into three types: fixed load, transferable load and replaceable load, and consider longitudinal load transfer, so as to establish a comprehensive demand response model on the demand side consisting of mathematical models of fixed load, transferable load and replaceable load;

[0013] Step 5) Determine the objective function of the park's integrated energy system, including: the park's total The efficiency is maximized and the carbon trading cost is minimized, and the mixed integer nonlinear programming solver is used to solve the objective function to obtain the planning results, including: the capacity investment of system equipment, the total Efficiency and carbon trading costs.

[0014] The planning method of a park integrated energy system considering demand response under carbon constraints described in the present invention is also characterized in that the mathematical model and constraints of each device in step 3) are:

[0015] 1) Use formula (2) to establish the mathematical model of photovoltaic equipment:

[0016]

[0017] In formula (2), P PV (t) represents the photovoltaic output at time t, represents the maximum photovoltaic output at time t, S PV Represents the installed capacity of photovoltaics, Indicates the upper and lower limits of the capacity of the photovoltaic installation;

[0018] 2) Use formula (3) to establish the mathematical model of the cogeneration unit:

[0019]

[0020] In formula (3), P CHP (t), H CHP (t) represents the heating power and power supply power of the cogeneration unit at the tth moment; G CHP (t) represents the natural gas power consumed by the CHP unit at time t; η P,CHP , η H,CHP Indicates the power supply efficiency and heating efficiency of the CHP unit; They represent the maximum electric power and thermal power output at the tth moment respectively; S CHP represents the installed capacity of CHP; Indicates the upper and lower limits of the installed capacity;

[0021] 3) Use formula (4) to establish the mathematical model of gas boiler GB, electric boiler EB, and P2G equipment:

[0022]

[0023] In formula (4), H i , G i and η i Respectively represent the output power, consumed input power, and conversion efficiency of any of the gas boiler GB, electric boiler EB, and P2G equipment; QGB (t), Q EB (t) and Q P2G (t) represent the output power of gas boiler GB, electric boiler EB and P2G equipment respectively, and Indicates the output power upper limit of gas boiler GB, electric boiler EB and P2G equipment; S i , and Indicates the installed capacity of any equipment among gas boiler GB, electric boiler EB and P2G equipment, and the upper and lower limits of the installed capacity;

[0024] 4) Use formula (5) to establish the mathematical model of energy storage equipment:

[0025]

[0026] In formula (5), ES, HS, and CS represent electrical, thermal, and cold energy storage devices, respectively; W j (t), W j (t-1) represents the energy state of the j-th type of energy storage device at time t and time t-1; Represents the charging and discharging power of the j-th type of energy storage device at time t; represents the charging and storage efficiency of the j-th type of energy storage device; Δt represents the operating time;

[0027] 5) Use formula (6) to establish the mathematical model of electric refrigerator and absorption refrigerator:

[0028]

[0029] In formula (6), Q AC (t), COP AC and H AC (t) respectively represent the cooling power of the absorption refrigerator, the performance coefficient of the absorption refrigerator, i.e. the cooling-heating ratio, and the thermal power consumed by the absorption refrigerator; Q EC (t), COP EC and P EC (t) represent the cooling power of the electric refrigerator, the coefficient of performance of the electric refrigerator, i.e., the cooling-heating ratio, and the electric power consumed by the electric refrigerator; S k , and Respectively represent the installed capacity of any equipment in the absorption refrigerator and the electric refrigerator, the upper and lower limits of the installed capacity; Q0, N0 and η AC They represent the actual output power, rated output power and efficiency of the absorption chiller respectively;

[0030] 6) Use formula (7) to establish the mathematical model of ground source heat pump:

[0031]

[0032] In formula (7), Q HP (t), COP HP and P HP (t) represent the energy supply power, performance coefficient and power consumption of the ground source heat pump at time t respectively; H HP (t) represents the output power and upper limit of the ground source heat pump at time t; S HP , and Indicates the installation capacity, upper and lower limits of the installation capacity of the ground source heat pump;

[0033] 7) Power balance constraints:

[0034] Use equation (8) to establish the electric power balance:

[0035]

[0036] In formula (8), represents the electricity purchased from the grid at time t; Indicates the charging and discharging power of the electric energy storage; P L (t) represents the load power at the tth moment;

[0037] Use equation (9) to establish thermal power balance:

[0038]

[0039] In formula (9), represents the discharge and charging power of the thermal storage device at time t; H L (t) represents the power of the heat load at the tth moment;

[0040] Use equation (10) to establish cooling power balance:

[0041]

[0042] In formula (10), Indicates the charging and discharging power of cold energy storage; Q L (t) represents the cooling load power at the tth moment.

[0043] The mathematical model of transferable load is established using formula (11):

[0044]

[0045] In formula (11), They represent the power of any z-th load demand in the electricity / heating / cooling load demand at time t before and after it participates in demand response; They represent the transfer-in and transfer-out power after responding to any z-th load demand in the electricity / heating / cooling load demand; It is a 0-1 variable. Any z-th load demand in the electricity / heating / cooling load demand at time t is converted to 1 and converted to 0;

[0046] The mathematical model of the alternative load is established using formula (12):

[0047]

[0048] In formula (12), and They are the power values ​​of electricity, heat and cold substitution loads after participating in demand response at time t; and The power of electricity, heat and cooling participating in demand response at time t respectively; and They represent the transfer power of electric, thermal and cold transferable loads at time t respectively; and They represent the output power of electric, thermal and cold transferable loads at time t respectively; Represents three 0-1 variables;

[0049] The comprehensive demand response model is constructed using formula (13):

[0050]

[0051] In formula (13), and They are the fixed load, transferable load and alternative load of any z-th load demand in the electricity / heating / cooling load demand at time t.

[0052] The objective function of the planning model in step 5) is shown in formula (14):

[0053] min E+C env (14)

[0054] In formula (14), E represents the total efficiency, and have:

[0055]

[0056] In formula (15), and Respectively represent the cooling power, electrical power and thermal power output of the system; A c , A e and A h They represent the energy quality coefficients of cold, electricity and heat respectively; and Respectively represent the input gas energy and electrical energy;

[0057]

[0058] In formula (16), is the annual average carbon emission closing price obtained according to the prediction model; E represents the actual carbon emission and is obtained through formula (17), E * represents the carbon emission quota, and equation (18) is obtained;

[0059]

[0060] In formula (17), E e,buy 、E CHP 、E GB and E P2G They represent the carbon emissions generated by the purchase of electricity, the carbon emissions generated by the CHP unit, the GB, and the carbon dioxide absorbed by P2G; β e , β h , and β g They respectively represent the carbon emissions per unit of electricity and heat, the conversion coefficient of the CHP unit's power generation to heat, and the carbon capture coefficient of P2G.

[0061]

[0062] In formula (18), Represents the unit carbon emission quota per unit electricity and per unit heat respectively; and They represent the carbon emission quotas of purchased electricity, CHP units and gas boilers GB respectively.

[0063] Compared with the prior art, the present invention has the following beneficial effects:

[0064] 1. The present invention establishes a revenue series model based on the historical carbon trading closing price series, considers the volatility and leverage effect of carbon trading prices, and uses the exponential generalized autoregressive conditional heteroskedasticity model to establish a prediction model for carbon trading prices. It also proposes carbon emission influencing factors and a carbon emission calculation method for the park's comprehensive energy system, and establishes a carbon trading cost mathematical model based on carbon emission quotas. Combining this with the park's comprehensive energy system planning can eliminate the drawbacks of fixed carbon trading methods to a certain extent, making the planning method more reasonable and scientific.

[0065] 2. The present invention fully considers the multi-energy complementary characteristics of comprehensive demand response in the comprehensive energy system, and divides the electric heating and cooling loads required by the park into fixed loads, transferable loads and replaceable loads on the basis of meeting the energy needs of users. Combined with the carbon trading prediction model, the capacity configuration of the system planning and the total energy consumption of the system can be obtained. Efficiency and carbon trading results can fully tap the response potential of the demand side under the dual carbon background, improve the flexibility of system operation and energy utilization efficiency, reduce the overall carbon emissions of the industrial park, and be conducive to the construction of a low-carbon industrial park. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 A flow chart of a method for planning a comprehensive energy system for a park considering demand response under carbon constraints of the present invention;

[0067] Figure 2 This is a structural diagram of the park comprehensive energy system of the present invention. DETAILED DESCRIPTION

[0068] In this embodiment, a park integrated energy system planning method considering demand response under carbon constraints is as follows: Figure 1 As shown, the steps are:

[0069] 1) Obtain the historical carbon trading closing price series, and establish the carbon trading income series by taking the first-order difference of the natural logarithm of the closing price. Considering the asymmetry of the volatility of carbon emission income and the leverage effect, the exponential generalized autoregressive conditional heteroskedasticity model is used to simulate the volatility of carbon trading income, and the future trend of carbon trading prices is predicted through a recursive formula, so as to;

[0070]

[0071] In formula (1), r d is the carbon emissions trading income on day d; and is the closing price of carbon emission trading on day d; is the closing price of carbon emission trading on day d-1; r d-1 is the carbon emission trading income on the d-1th day; β0 and β1 are the persistence parameters of the sequence; β2 is the asymmetric parameter of the sequence; α1 is the new information parameter; is a constant less than 1; v d It indicates the dth parameter that follows a normal white noise process with a mean of 0 and a variance of 1; ε d is the disturbance term on the dth day, ε d-1 is the disturbance term on the d-1th day, describing the independent and identically distributed white noise process, indicating the role of accidental factors, σ d is the conditional standard deviation on the dth day, α0 is a non-random variable, σ d-1 is the conditional standard deviation on day d-1.

[0072] 2) According to Figure 2The energy demand of the park is shown, and the energy types and equipment on the supply side are determined to establish a comprehensive energy system for the park, including: photovoltaic equipment, cogeneration units, gas boilers GB, electric boilers EB, P2G equipment, electric / heat / cold energy storage equipment, electric refrigerators, absorption refrigerators and ground source heat pumps;

[0073] 3) Collect typical daily load data and equipment parameters of electricity / heat / cold of the park's comprehensive energy system, establish mathematical models of each device and constraints on photovoltaic output and installation capacity, cogeneration unit output and installation capacity, gas boiler and electric boiler output and installation capacity, absorption chiller and electric chiller output and installation capacity, energy storage equipment capacity and output, ground source heat pump capacity and output, and system power balance constraints;

[0074] (3.1) Using formula (2), the mathematical model of photovoltaic equipment is established:

[0075]

[0076] In formula (2), P PV (t) represents the photovoltaic output at time t, represents the maximum photovoltaic output at time t, S PV Represents the installed capacity of photovoltaics, Indicates the upper and lower limits of the capacity of the photovoltaic installation;

[0077] (3.2) Using formula (3), the mathematical model of the cogeneration unit is established:

[0078]

[0079] In formula (3), P CHP (t), H CHP (t) represents the heating power and power supply power of the cogeneration unit at the tth moment; G CHP (t) represents the natural gas power consumed by the CHP unit at time t; η P,CHP , η H,CHP Indicates the power supply efficiency and heating efficiency of the CHP unit; They represent the maximum electric power and thermal power output at the tth moment respectively; S CHP represents the installed capacity of CHP; Indicates the upper and lower limits of the installed capacity;

[0080] (3.3) Using formula (4), the mathematical model of gas boiler GB, electric boiler EB and P2G equipment is established:

[0081]

[0082] In formula (4), H i , Gi and η i Respectively represent the output power, consumed input power, and conversion efficiency of any of the gas boiler GB, electric boiler EB, and P2G equipment; Q GB (t), Q EB (t) and Q P2G (t) represent the output power of gas boiler GB, electric boiler EB and P2G equipment respectively, and Indicates the output power upper limit of gas boiler GB, electric boiler EB and P2G equipment; S i , and Indicates the installed capacity of any equipment among gas boiler GB, electric boiler EB and P2G equipment, and the upper and lower limits of the installed capacity;

[0083] (3.4) Using formula (5), the mathematical model of energy storage equipment is established:

[0084]

[0085] In formula (5), ES, HS, and CS represent electrical, thermal, and cold energy storage devices, respectively; W j (t), W j (t-1) represents the energy state of the j-th type of energy storage device at time t and time t-1; Represents the charging and discharging power of the j-th type of energy storage device at time t; represents the charging and storage efficiency of the j-th type of energy storage device; Δt represents the operating time;

[0086] (3.5) Using equation (6), the mathematical model of electric refrigerator and absorption refrigerator is established:

[0087]

[0088] In formula (6), Q AC (t), COP AC and H AC (t) respectively represent the cooling power of the absorption refrigerator, the performance coefficient of the absorption refrigerator, i.e. the cooling-heating ratio, and the thermal power consumed by the absorption refrigerator; Q EC (t), COP EC and P EC (t) represent the cooling power of the electric refrigerator, the coefficient of performance of the electric refrigerator, i.e., the cooling-heating ratio, and the electric power consumed by the electric refrigerator; S k , and Respectively represent the installed capacity of any equipment in the absorption refrigerator and the electric refrigerator, the upper and lower limits of the installed capacity; Q0, N0 and η ACThey represent the actual output power, rated output power and efficiency of the absorption chiller respectively;

[0089] (3.6) Using formula (7), the mathematical model of ground source heat pump is established:

[0090]

[0091] In formula (7), Q HP (t), COP HP and P HP (t) represent the energy supply power, performance coefficient and power consumption of the ground source heat pump at time t respectively; H HP (t) represents the output power and upper limit of the ground source heat pump at time t; S HP , and Indicates the installation capacity, upper and lower limits of the installation capacity of the ground source heat pump;

[0092] (3.7) Power balance constraint:

[0093] Use equation (8) to establish the electric power balance:

[0094]

[0095] In formula (8), represents the electricity purchased from the grid at time t; Indicates the charging and discharging power of the electric energy storage; P L (t) Load power at time t.

[0096] Use equation (9) to establish thermal power balance:

[0097]

[0098] In formula (9), it is represented by represents the discharge and charging power of the thermal storage device at time t; H L (t) represents the power of the heat load at the tth moment.

[0099] Use equation (10) to establish cooling power balance:

[0100]

[0101] In formula (10), Indicates the charging and discharging power of cold energy storage; Q L (t) represents the cooling load power at the tth moment.

[0102] 4) Consider dividing the load into three types: fixed load, transferable load and replaceable load, and consider longitudinal load transfer, so as to establish a comprehensive demand response model on the demand side composed of mathematical models of fixed load, transferable load and replaceable load.

[0103] (4.1) Transferable load is load transfer in the time dimension based on meeting user needs, and the total load remains unchanged throughout the entire time period.

[0104] The mathematical model of transferable load is established using formula (11):

[0105]

[0106] In formula (11), They represent the power of any z-th load demand in the electricity / heating / cooling load demand at time t before and after it participates in demand response; They represent the transfer-in and transfer-out power after responding to any z-th load demand in the electricity / heating / cooling load demand; It is a 0-1 variable. Any z-th load demand in the electricity / heating / cooling load demand at time t is converted to 1 and converted to 0;

[0107] (4.2) Alternative loads such as air conditioning cooling / heating or induction cookers can meet user needs through energy conversion.

[0108] The mathematical model of the alternative load is established using formula (12):

[0109]

[0110] In formula (12), and They are the power values ​​of electricity, heat and cold substitution loads after participating in demand response at time t; and The power of electricity, heat and cooling participating in demand response at time t respectively; and They represent the transfer power of electric, thermal and cold transferable loads at time t respectively; and They represent the output power of electric, thermal and cold transferable loads at time t respectively; Represents a 0-1 variable.

[0111] The comprehensive demand response model is constructed using formula (13):

[0112]

[0113] In formula (13), and They are the fixed load, transferable load and alternative load of any z-th load demand in the electricity / heating / cooling load demand at time t.

[0114] 5) Determine the objective function of the park's integrated energy system, including: the park's total The efficiency is maximized and the carbon trading cost is minimized, and the mixed integer nonlinear programming solver is used to solve the objective function to obtain the planning results, including: the capacity investment of system equipment, the total Efficiency and carbon trading costs.

[0115] (5.1)The objective function is:

[0116] The objective function of the planning model is Maximize efficiency and minimize carbon trading costs:

[0117] min E+C env (14)

[0118] In formula (14), E represents the total efficiency, and have:

[0119]

[0120] In formula (15), and Respectively represent the cooling power, electrical power and thermal power output of the system; A c , A e and A h They represent the energy quality coefficients of cold, electricity and heat respectively; and Respectively represent the input gas energy and electrical energy;

[0121]

[0122] In formula (16), is the annual average carbon emission closing price obtained based on the forecast model; E represents the actual carbon emissions, E * Represents carbon emission quota.

[0123] (5.2) The actual carbon emissions E of the park's integrated energy system include electricity and natural gas purchased from the upper power grid. The park's carbon dioxide is mainly generated by cogeneration units, gas boilers and purchased electricity, and the carbon dioxide generated by the P2G equipment absorption system.

[0124]

[0125] In formula (17), E e,buy 、E CHP 、E GB and E P2GThey represent the carbon emissions generated by the purchase of electricity, the carbon emissions generated by the CHP unit, the GB, and the carbon dioxide absorbed by P2G; β e , β h , and β g They respectively represent the carbon emissions per unit of electricity and heat, the conversion coefficient of the CHP unit's power generation to heat, and the carbon capture coefficient of P2G.

[0126] (5.3) The initial carbon emission quota of the park E * Allocated free of charge by the government, the initial carbon quota model is:

[0127]

[0128] In formula (18), Represents the unit carbon emission quota per unit electricity and per unit heat respectively; and They represent the carbon emission quotas of purchased electricity, CHP units and gas boilers GB respectively.

[0129] 6) According to the above steps, the mixed integer nonlinear model is used to solve and output the planning results, including: the capacity investment of equipment and the total energy system of the park. Efficiency and carbon trading costs.

[0130] For this example, the following three scenarios can be used for analysis.

[0131] Scenario 1: All equipment is selected without considering the dynamic carbon trading price mechanism and comprehensive demand response;

[0132] Scenario 2: All equipment is selected, and only the traditional carbon trading mechanism is considered;

[0133] Scenario 3: All equipment is selected, and only the dynamic carbon trading mechanism is considered

[0134] Scenario 4: All equipment is selected, and the dynamic carbon trading price model and comprehensive demand response are considered simultaneously.

[0135] Table 1 shows the annual equivalent total cost of the park integrated energy system under different scenarios

[0136] Table 1 Planning results (ten thousand yuan)

[0137]

[0138] Table 2 Equipment capacity configuration planning results (KW)

[0139]

[0140] It can be concluded from Table 1 that the carbon trading cost of the park comprehensive energy system considering the carbon trading mechanism increases compared with the system without considering the carbon trading mechanism, indicating that the operation of the system is constrained by carbon emissions, and compared with the traditional carbon trading mechanism, the carbon trading mechanism considering the carbon trading prediction model further constrains the system's carbon emissions; in addition, after considering the comprehensive demand response, the carbon trading cost is significantly reduced compared with the system without considering the comprehensive demand response, and it can be clearly seen that the total cost of the system is significantly reduced. The increase in efficiency indicates that the energy utilization rate of the system has been improved. It can be seen from Table 2 that while comprehensively considering the dynamic carbon trading price and the comprehensive demand side response, the system's equipment capacity configuration is more optimized, and the capacity of the selected equipment is reduced, reflecting the optimization of system planning by considering the comprehensive demand response. Therefore, it can be seen that the method of the present invention can further improve the efficiency of system planning by considering the comprehensive demand side response on the basis of considering the carbon trading mechanism, which is of great significance to the construction of the park's comprehensive energy system.

Claims

1. A planning method for a comprehensive energy system in a park considering demand response under carbon constraints, characterized in that: The following steps are involved: Step 1) Obtain the historical carbon trading closing price sequence, and use formula (1) to establish a carbon trading price prediction model based on the historical carbon trading closing price sequence for the future trend of carbon trading prices: (1) In formula (1), For the carbon emissions trading revenue per day; and , For the The closing price of carbon emissions trading on the day; For the The closing price of carbon emissions trading on the day; For the Carbon emissions trading revenue per day; is the persistence parameter of the sequence; is the persistence parameter of the sequence; is the asymmetry parameter of the sequence; is the new information parameter; is a constant less than 1; It indicates the dth parameter that follows a normal white noise process with a mean of 0 and a variance of 1; For the The disturbance term of the day, For the The disturbance term of the day, For the The daily conditional standard deviation, is a non-random variable, For the The daily conditional standard deviation; Step 2) According to the energy demand of the park, determine the energy types and equipment on the supply side, so as to establish a comprehensive energy system for the park, including: photovoltaic equipment, cogeneration units, gas boilers GB, electric boilers EB, P2G equipment, electric energy storage, thermal energy storage, cold energy storage equipment, electric refrigerators, absorption refrigerators and ground source heat pumps; Step 3) Collect typical daily load data and equipment parameters of electricity, heat and cooling of the park's comprehensive energy system, establish mathematical models of each device and constraints on photovoltaic output and installation capacity, cogeneration unit output and installation capacity, gas boiler and electric boiler output and installation capacity, absorption chiller and electric chiller output and installation capacity, energy storage equipment capacity and output, ground source heat pump capacity and output, and system power balance constraints; Step 4) Consider dividing the load into three types: fixed load, transferable load and replaceable load, and consider longitudinal load transfer, so as to establish a comprehensive demand response model on the demand side consisting of mathematical models of fixed load, transferable load and replaceable load; The mathematical model of transferable load is established using formula (11): (11) In formula (11), It represents the power of any z-th load demand among the electricity, heating and cooling load demands at time t before participating in the demand response; It represents the power of any z-th load demand among the electricity, heating and cooling load demands at time t after participating in the demand response; It represents the power transferred in after the response of any z-th load demand among the electricity, heating and cooling load demands; It represents the output power after responding to any z-th load demand among the electricity, heating and cooling load demands; It is a 0-1 variable. Any z-th load demand in the electricity, heating and cooling load demand at time t is converted to 1 and converted to 0; e, h, c represent electricity, heating and cooling loads respectively; The mathematical model of the alternative load is established using formula (12): (12) In formula (12), is the power value of the electricity substitution load after participating in demand response at time t; is the power value of the heat replacement load after participating in demand response at time t; is the power value of the cold substitution load after participating in demand response at time t; is the power participating in demand response at time t; is the power of thermal energy participating in demand response at time t; is the power of cold demand response at time t; It represents the transfer power of the electrically transferable load at time t; represents the transfer power of the heat transferable load at time t; It represents the transfer power of cold transferable load at time t; It represents the output power of the electrically transferable load at time t; represents the output power of the heat transferable load at time t; They represent the output power of the cold transferable load at time t respectively; Represents three 0-1 variables at time t; The comprehensive demand response model is constructed using formula (13): (13) In formula (13), It is the fixed load of any z-th load demand among the electricity, heating and cooling load demands at time t; It is a transferable load of any z-th load demand among the electricity, heating and cooling load demands at time t; It is the substitute load for any z-th load demand among the electricity, heating and cooling load demands at time t; Step 5) Use equation (14) to determine the objective function of the park's integrated energy system , including: maximizing the total exergy efficiency of the park and minimizing the carbon trading cost, and using a mixed integer nonlinear programming solver to solve the objective function to obtain planning results, including: capacity investment and construction of system equipment, the total exergy efficiency of the system and the carbon trading cost; (14) In formula (14), represents the total exergy efficiency of the system, and: (15) In formula (15), Indicates the cooling power output by the system; Indicates the electrical power output of the system; Indicates the thermal power output of the system; represents the energy quality coefficient of cold; It represents the energy quality coefficient of electricity; The energy quality coefficient of heat; Indicates the input gas energy; Respectively represent the input electrical energy; A g Indicates the energy quality coefficient of gas; (16) In formula (16), is the annual average carbon emission closing price obtained according to the prediction model; E represents the actual carbon emission and is obtained by formula (17); represents the carbon emission quota, and equation (18) is obtained; (17) In formula (17), represents the carbon emissions from purchasing electricity; Indicates the carbon emissions generated by the CHP unit; represents the carbon emissions generated by GB; represents the carbon dioxide absorbed by P2G; Indicates the carbon emissions per unit of electricity; Indicates the carbon emissions per unit of heat; Indicates the conversion factor of CHP unit power generation to heat; represents the carbon capture coefficient of P2G; (18) In formula (18), Indicates the unit carbon emission quota per unit electricity; Indicates the unit carbon emission quota per unit heat; represents the carbon emission allowance for purchasing electricity; It represents the carbon emission quota of CHP unit; Represents the carbon emission quota of the gas boiler GB.

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