A comprehensive energy system scheduling method and terminal based on source-load bilateral response

Abstract

The application discloses a kind of based on source load double-side response comprehensive energy system scheduling method and terminal, first, the comprehensive energy system comprising various equipment is constructed, the model of each device of comprehensive energy system is built, and constraint condition is set;Then the minimum comprehensive cost of the energy supply end of comprehensive energy system is taken as the target to build inner target function, and the minimum energy cost and the highest energy satisfaction of user end are taken as the target to establish outer target function, in this way, the energy supply end and user end are jointly built into double-layer optimization model;Finally, the model is solved to obtain the optimal output plan of comprehensive energy system unit and the optimal energy strategy of user.In this way, the output plan of generator set and the power utilization strategy of user can be effectively adjusted, and the energy satisfaction of user is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy system scheduling, and in particular to a comprehensive energy system scheduling method and terminal based on source-load dual-side response. Background Art

[0002] At present, due to the randomness and volatility of renewable energy generation, the penetration of a high proportion of new energy will inevitably bring challenges to the safe and stable operation of the power grid. The integrated energy supply form of "source, grid, load and storage" can effectively overcome the volatility caused by the access of new energy to the grid. For the user load side, demand response can be used to adjust the user's energy use strategy, reduce peak-to-valley differences, and reduce the pressure on power grid frequency regulation. However, most current demand responses only consider economic indicators, have limited user mobilization capabilities, and ignore user energy satisfaction. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a comprehensive energy system scheduling method and terminal based on source-load dual-side response, which can effectively adjust the output plan of the generator set and the user's electricity consumption strategy, and improve the user's energy satisfaction.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0005] A method for dispatching an integrated energy system based on source-load dual-side response, comprising the steps of:

[0006] Build corresponding device models for each device in the integrated energy system and set corresponding constraints for the integrated energy system;

[0007] An inner objective function is established with the minimum comprehensive cost of the integrated energy system as the first goal, and an outer objective function is established with the minimum energy cost and the maximum energy satisfaction of the user as the second goal;

[0008] A two-layer optimization model of an integrated energy system is constructed by combining the inner layer objective function, the outer layer objective function and the constraint conditions. The inner layer of the two-layer optimization model is the scheduling layer, and the outer layer is the user response layer. The objective function of the scheduling layer is the inner layer objective function, and the objective function of the user response layer is the outer layer objective function. The inner layer sends the solved output plan to the outer layer, and the outer layer returns the solved energy utilization strategy to the inner layer. The two-layer optimization model is solved to obtain the optimal output plan of the generator set and the optimal energy utilization strategy of the user.

[0009] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0010] A comprehensive energy system scheduling terminal based on source-load dual-side response includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, each step of the above-mentioned comprehensive energy system scheduling method based on source-load dual-side response is implemented.

[0011] The beneficial effects of the present invention are as follows: first, an integrated energy system comprising various devices is constructed, a model is built for each device in the integrated energy system, and constraints are set; then, an inner objective function is constructed with the goal of minimizing the comprehensive cost of the energy supply end of the integrated energy system, and an outer objective function is established with the goal of minimizing the energy cost and maximizing the energy satisfaction of the user end. In this way, an inner and outer double-layer optimization model is constructed by combining the energy supply side and the user load side; finally, the model is solved to obtain the optimal output plan of the integrated energy system unit and the optimal energy use strategy of the user. In this way, the output plan of the generator set and the user's electricity use strategy can be effectively adjusted to improve the user's energy satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 This is a flow chart of a method for scheduling an integrated energy system based on source-load dual-side response according to an embodiment of the present invention;

[0013] Figure 2 Schematic diagram of an integrated energy system dispatching terminal based on source-load dual-side response according to an embodiment of the present invention;

[0014] Figure 3 A framework diagram of an integrated energy system according to an embodiment of the present invention;

[0015] Figure 4 A schematic structural diagram of a two-layer optimization model for an integrated energy system according to an embodiment of the present invention;

[0016] Figure 5 This is a flowchart for solving the double-layer optimization model according to an embodiment of the present invention.

[0017] Description of labels:

[0018] 1. An integrated energy system dispatching terminal based on source-load dual-side response; 2. Memory; 3. Processor. DETAILED DESCRIPTION

[0019] To illustrate the technical content, achieved objectives and effects of the present invention in detail, the following description is given in conjunction with the embodiments and accompanying drawings.

[0020] Please refer to Figure 1 The embodiment of the present invention provides a method for scheduling an integrated energy system based on source-load dual-side response, comprising the steps of:

[0021] Build corresponding device models for each device in the integrated energy system and set corresponding constraints for the integrated energy system;

[0022] An inner objective function is established with the minimum comprehensive cost of the integrated energy system as the first goal, and an outer objective function is established with the minimum energy cost and the maximum energy satisfaction of the user as the second goal;

[0023] A two-layer optimization model of an integrated energy system is constructed by combining the inner layer objective function, the outer layer objective function and the constraint conditions. The inner layer of the two-layer optimization model is the scheduling layer, and the outer layer is the user response layer. The objective function of the scheduling layer is the inner layer objective function, and the objective function of the user response layer is the outer layer objective function. The inner layer sends the solved output plan to the outer layer, and the outer layer returns the solved energy utilization strategy to the inner layer. The two-layer optimization model is solved to obtain the optimal output plan of the generator set and the optimal energy utilization strategy of the user.

[0024] From the above description, it can be seen that the beneficial effects of the present invention are as follows: first, an integrated energy system including various devices is constructed, a model is built for each device of the integrated energy system, and constraints are set; then, an inner objective function is constructed with the goal of minimizing the comprehensive cost of the energy supply end of the integrated energy system, and an outer objective function is established with the goal of minimizing the energy cost and maximizing the energy satisfaction of the user end. In this way, an inner and outer double-layer optimization model is constructed by combining the energy supply side and the user load side; finally, the model is solved to obtain the optimal output plan of the integrated energy system unit and the optimal energy use strategy of the user. In this way, the output plan of the generator set and the user's electricity use strategy can be effectively adjusted to improve the user's energy satisfaction.

[0025] Furthermore, corresponding equipment models are built for each device in the integrated energy system, including:

[0026] Establish corresponding equipment models for the power supply equipment, heating equipment, cooling equipment and energy storage devices in the integrated energy system, and establish a carbon emission model for the integrated energy system;

[0027] The power supply equipment includes a gas turbine, the heating equipment includes a waste heat boiler, an electric boiler and a heat pump, and the cooling equipment includes an electric refrigerator and an absorption refrigerator.

[0028] From the above description, it can be seen that in the process of building a model for the integrated energy system, a carbon emission model is also established to facilitate subsequent energy scheduling for carbon trading to reduce the carbon emissions of the integrated energy system.

[0029] Furthermore, corresponding constraints are set for the integrated energy system, including:

[0030] Establishing wind power output constraints and photovoltaic output constraints for the integrated energy system;

[0031] Establishing electric power balance constraints, thermal power balance constraints, and cooling load power balance constraints for the integrated energy system;

[0032] Establish energy selling price constraints for power supply, heating and cooling of the integrated energy system.

[0033] From the above description, it can be seen that establishing operation constraints, energy balance constraints, and energy sales constraints for the integrated energy system can ensure the reliability of energy scheduling.

[0034] Furthermore, an inner objective function is established with minimizing the comprehensive cost of the integrated energy system as the first objective, including:

[0035]

[0036] Where, C om represents the system operation and maintenance cost, C buy,e represents the cost of purchasing electricity from the external power grid, C buy,g represents the electricity purchase cost of the gas turbine, represents the tiered carbon trading cost, C wp represents the cost of curtailed power and solar power, C GT represents the gas turbine startup and shutdown cost;

[0037]

[0038] Where, r represents the carbon trading base price; I Indicates the length of the carbon emission interval; i represents the price growth rate.

[0039] From the above description, it can be seen that adding a tiered carbon trading mechanism to the integrated energy system and influencing the output plans of the integrated energy system operators through carbon trading can effectively reduce the carbon emissions of the integrated energy system.

[0040] Furthermore, an outer objective function is established with the second goal of minimizing the user's energy cost and maximizing the user's energy satisfaction, including:

[0041]

[0042]

[0043]

[0044] Where,F m It represents the energy preference cost caused by the deviation of the user's actual load from the user's demand load. F m The smaller the value, the higher the energy satisfaction. k m represents the user's preference coefficient for the mth type of energy, P m,load ( t ) represents the initial load of the user’s mth energy type at time t; represents the optimized load of the user's mth energy type at time t;

[0045] C BUY represents the cost of purchasing electricity, α e ( t ), α h ( t ), α c ( t ) represent the unit price of electricity, heat and cooling energy at time t, P e,load ( t ) represents the electric load power at time t, P h,load ( t ) represents the heat load power at time t, P c,load ( t ) represents the cooling load power at time t.

[0046] From the above description, it can be seen that integrating time-of-use electricity prices and energy satisfaction on the user side can effectively adjust the user's load-side electricity consumption strategy while improving the user's energy satisfaction.

[0047] Please refer to Figure 2 Another embodiment of the present invention provides an integrated energy system scheduling terminal based on source-load dual-side response, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the various steps of the above-mentioned integrated energy system scheduling method based on source-load dual-side response.

[0048] The above-mentioned integrated energy system scheduling method and terminal based on source-load dual-side response of the present invention are suitable for adjusting the output plan of the generator set and the user's electricity consumption strategy, and can effectively improve the user's energy satisfaction. The following is an explanation through specific implementation methods:

[0049] Example 1

[0050] Please refer to Figure 1 , a comprehensive energy system scheduling method based on source-load dual-side response, comprising the steps of:

[0051] S1. Build a corresponding device model for each device in the integrated energy system and set corresponding constraints for the integrated energy system.

[0052] Among them, the integrated energy system (IES), as a multi-energy coupling structure, can break down barriers between energy sources, improve the system's renewable energy consumption level, and reduce the system's carbon emissions. The integrated energy system framework constructed in this embodiment is as follows: Figure 3 As shown in the figure, the energy supply side includes wind power, photovoltaic power, external power grid, and natural gas. Power supply equipment primarily includes gas turbines (GT). Heating equipment primarily includes GTs, heat pumps (HP), waste heat boilers (WHB), and electric boilers (EB). Cooling equipment primarily includes absorption chillers (AC) and electricity chillers (EC). Energy storage equipment primarily includes batteries and thermal storage tanks.

[0053] Specifically, corresponding equipment models are established for the power supply equipment, heating equipment, cooling equipment and energy storage devices in the integrated energy system, and a carbon emission model is established for the integrated energy system;

[0054] The power supply equipment includes a gas turbine, the heating equipment includes a waste heat boiler, an electric boiler and a heat pump, and the cooling equipment includes an electric refrigerator and an absorption refrigerator.

[0055] In this embodiment, (1) a gas turbine model is established:

[0056]

[0057] Where, P e,GT ( t ) represents the electric power output of the gas turbine at time t, or e,GT represents the gas turbine's electricity conversion efficiency, P GT ( t ) represents the input power of the gas turbine at time t; P h,GT ( t ) represents the thermal power output of the gas turbine at time t, or h,GTIndicates the heat conversion efficiency of the gas turbine; Respectively represent the upper and lower limits of gas turbine input power; are the upper and lower limits of the gas turbine's ramp power respectively.

[0058] (2) Establishing waste heat boiler model:

[0059]

[0060] Where, P h,WHB ( t ) represents the output thermal power of the waste heat boiler at time t, or WHB Indicates the preheat recovery efficiency of the waste heat boiler, P WHB ( t ) represents the input power of the waste heat boiler at time t; 、 They represent the upper and lower limits of the waste heat boiler input power respectively.

[0061] (3) Establishing an electric boiler model:

[0062]

[0063] Where, P h,EB ( t ) represents the output thermal power of the electric boiler at time t, or EB Indicates the electric-to-heat conversion efficiency of the electric boiler. P EB ( t ) represents the input power of the electric boiler at time t; 、 They respectively represent the upper and lower limits of the electric boiler input power.

[0064] (4) Establishing a heat pump model:

[0065]

[0066] Where, P h,HP ( t ) represents the output thermal power of the heat pump at time t, or HP Indicates the heat pump's electrical-to-thermal conversion efficiency, P HP ( t ) represents the input power of the heat pump at time t; 、 They represent the upper and lower limits of the heat pump input power respectively.

[0067] (5) Establishing an electric refrigerator model:

[0068]

[0069] Where, P h,EC ( t ) represents the output cooling power of the electric refrigerator at time t, or EC Indicates the electric-to-cooling conversion efficiency of the electric refrigerator. P EC ( t ) represents the input power of the electric refrigerator at time t; 、 They respectively represent the upper and lower limits of the electric refrigerator input power.

[0070] (6) Establishing an absorption chiller model:

[0071]

[0072] Where, P h,AC ( t ) represents the output cooling power of the absorption chiller at time t, or AC represents the conversion efficiency of the absorption chiller, P AC ( t ) represents the input power of the absorption chiller at time t; 、 They represent the upper and lower limits of the absorption chiller input power respectively.

[0073] (7) Establishing energy storage device model:

[0074]

[0075] Where i represents the energy type, including electrical energy and thermal energy; S i ( t ) represents the energy stored in the energy storage device at time t; 、 They represent the charging and discharging power of the energy storage device at time t respectively; 、 Respectively represent the charging and discharging efficiency of the energy storage device; 、 Respectively represent the upper limits of charging and discharging power of energy storage equipment; m i ( t ) represents a binary variable, when m i ( t)=0, energy is released at time t. m i ( t ) = 1, energy storage is performed at time t; 、 Respectively represent the upper and lower limits of the energy storage device capacity; S i (1) S i ( T ) represent the energy stored in the energy storage device from the start to the end of the system operation; Indicates unit duration.

[0076] (8) Establishing a carbon emission model for an integrated energy system:

[0077]

[0078] Where, E IES,r represents the actual carbon emissions of the integrated energy system, E e,BUY,r Indicates the actual carbon emissions of coal-fired power generation units, E GT,r Indicates the actual carbon emissions of gas turbines in the integrated energy system; P e,BUY (t) represents the electricity purchase cost at time t; P eh,GT (t) represents the total output power of the gas turbine at time t; a 1. b 1. c 1 represents the carbon emission parameters of coal-fired power generation units; a 2. b 2. c 2 represent the carbon emission parameters of gas turbines.

[0079] Specifically, corresponding constraints are set for the integrated energy system, specifically:

[0080] (1) Establish wind power output constraints and photovoltaic output constraints for the integrated energy system:

[0081]

[0082] Where, P WT (t), P PV (t) represents the wind power and photovoltaic output power at time t respectively; 、 They represent the upper limits of wind power and photovoltaic output power respectively.

[0083] (2) Establishing the power balance constraints of the integrated energy system:

[0084] Electric power balance constraints:

[0085]

[0086] Where, P e,Load (t) represents the electric load power at time t; 、 They represent the charging power and discharging power of the energy storage device at time t respectively; Indicates the upper limit of electricity purchase.

[0087] Thermal power balance constraints:

[0088]

[0089] Where, P h,Load (t) represents the heat load at time t; 、 They represent the charging power and discharging power of the heat storage device at time t respectively.

[0090] Cooling load power balance constraints:

[0091]

[0092] Where, P c,Load (t) represents the cooling load at time t; P c,EC (t) represents the cooling power of the electric refrigerator at time t; P c,AC (t) represents the cooling power of the absorption chiller at time t.

[0093] (3) Establishing price constraints for the electricity, heating and cooling supply of the integrated energy system:

[0094]

[0095] Where, α e ( t ), α h ( t ), α c ( t ) represent the unit prices of electricity, heating and cooling energy sold at time t respectively; 、 Respectively represent the lower limit and upper limit of the electricity sales price; 、 Respectively represent the lower and upper limits of the heat selling price; 、 They represent the lower and upper limits of the cold selling price respectively.

[0096] S2. Establish an inner objective function with the first goal of minimizing the comprehensive cost of the integrated energy system, and establish an outer objective function with the second goal of minimizing the energy cost of users and maximizing their energy satisfaction.

[0097] S21. Establish an inner objective function with minimizing the comprehensive cost of the integrated energy system as the first objective.

[0098]

[0099] Where, C om represents the system operation and maintenance cost, C buy,e represents the cost of purchasing electricity from the external power grid, C buy,g represents the electricity purchase cost of the gas turbine, represents the carbon trading cost, C wp represents the cost of curtailed power and solar power, C GT represents the gas turbine start-up and shutdown cost.

[0100]

[0101] Where x represents the equipment type; M represents the set of integrated energy system equipment, M = {gas turbine, electric boiler, heat pump, wind power generation, photovoltaic power generation, electric chiller, absorption chiller, power storage device, heat storage device, waste heat boiler}; P out,x ( t ) represents the output power of device x at time t; K x Indicates the operation and maintenance cost per unit of output power of the device.

[0102]

[0103] Where, P e,BUY ( t ) represents the amount of electricity purchased from the external power grid at time t; c 1 represents the unit price of electricity purchased from the external power grid at time t.

[0104]

[0105] Where, P g,BUY ( t ) represents the gas purchase volume at time t; c 2 represents the unit price of gas purchased from the external power grid at time t.

[0106]

[0107] Where, E IES represents the carbon quota of the integrated energy system, E Indicates the actual carbon emission balance.

[0108] The tiered carbon trading model divides different intervals according to different carbon emissions. When the actual carbon emissions at a certain moment are less than the quota, E When the value is negative, the integrated energy system can sell excess carbon emission quotas to realize profits; when the actual carbon emissions exceed the quota, E If the value is positive, the integrated energy system needs to purchase carbon emission quotas. The price of carbon emission quotas will increase with the increase of carbon emissions to limit carbon emissions. The tiered carbon trading model is:

[0109]

[0110] Where, r represents the carbon trading base price; I Indicates the length of the carbon emission interval; i represents the price growth rate.

[0111]

[0112] Where, P wp ( t ) represents the wind and solar power curtailed at time t; c wp Represents the penalty cost coefficient for curtailing wind and solar power.

[0113]

[0114] Where, α ( t ) represents the 0-1 variable indicating the start / stop status of the gas turbine at time t, where 0 represents stop and 1 represents start; f GT Represents the start-stop penalty coefficient.

[0115] S22. Establish an outer objective function with the second goal of minimizing the user's energy cost and maximizing the user's energy satisfaction.

[0116] Specifically, the user energy preference cost can be simplified to a quadratic function expression of the load as shown in the formula, which refers to the quantification of the energy comfort caused by the deviation of the user's actual load from the user's required load during the load reduction process. k mIt represents the user's preference coefficient for type m energy, reflecting the user's demand for type m energy and affecting the size of the actual load. It is assumed that it can be set based on the user's historical energy consumption information and user survey results. If the user has a high comfort requirement for type m energy use, then the user k m If the user has a larger energy cost, he or she will be willing to bear a higher energy cost to meet the energy demand; if the user has a lower comfort requirement for the use of Class M energy, then the user k m Smaller, willing to cut more load to reduce energy costs.

[0117]

[0118]

[0119]

[0120] Where, F m It represents the energy preference cost caused by the deviation of the user's actual load from the user's demand load. F m The smaller the value, the higher the energy satisfaction. k m represents the user's preference coefficient for the mth type of energy, P m,load ( t ) represents the initial load of the user’s mth energy type at time t; represents the optimized load of the user's mth energy type at time t;

[0121] C BUY represents the cost of purchasing electricity, α e ( t ), α h ( t ), α c ( t ) represent the unit price of electricity, heat and cooling energy at time t, P e,load ( t ) represents the electric load power at time t, P h,load ( t ) represents the heat load power at time t, P c,load ( t ) represents the cooling load power at time t.

[0122] S3. Construct a two-layer optimization model of the integrated energy system by combining the inner objective function, the outer objective function and the constraint conditions, and solve the two-layer optimization model to obtain the optimal output plan of the generator set and the optimal energy utilization strategy of the user.

[0123] Specifically, a two-layer optimization model of the integrated energy system is constructed and solved using the NSGA-Ⅱ algorithm to obtain the optimal output plan of the units in the integrated energy system and the optimal energy utilization strategy of the users.

[0124] In this embodiment, the two-layer model of the integrated energy system includes an inner layer and an outer layer. The inner layer scheduling layer is obtained according to the inner layer objective function, and the outer layer user response layer is obtained according to the outer layer objective function. The model framework is as follows: Figure 4 As shown in the figure, the inner layer takes the output scheduling solution and sends it to the outer layer, taking into account the time-of-use electricity price. The outer layer returns the user energy utilization strategy to the inner layer. Through data transmission and iterative optimization, the inner and outer layer models obtain the final optimized scheduling solution and user energy utilization optimization strategy.

[0125] In addition, the double-layer planning of the integrated energy system constructed in this embodiment uses the Yalmip toolbox to model and simulate the inner scheduling model in Matlab. According to the mathematical model of the constructed objective function and constraint conditions, the solver Cplex is called to solve. The outer model adopts an evaluation model of subjective and objective combined weighting. This model integrates the hierarchical analysis method and the entropy weight method, avoiding the subjective assumptions generated by the hierarchical analysis method and the deviation from reality caused by the entropy weight method, and finally obtains a set of optimal solutions. The solution process is as follows: Figure 5 As shown:

[0126] In the scheduling layer, an inner objective function is set, and Cplex is called to solve the equipment output strategy of the integrated energy system and calculate the comprehensive cost of the integrated energy system at that time. When the cost is minimized, the corresponding equipment output plan of the integrated energy system is obtained and transmitted to the user scheduling layer.

[0127] The user's energy purchase price is obtained, and an outer objective function with the goals of minimizing the user's energy purchase cost and maximizing the energy satisfaction is set in the user scheduling layer. The problem is solved by combining the hierarchical analysis method and the entropy weight method, and finally the user's energy adjustment strategy is obtained.

[0128] Example 2

[0129] Please refer to Figure 2 A comprehensive energy system scheduling terminal 1 based on source-load dual-side response includes a memory 2, a processor 3, and a computer program stored in the memory 2 and executable on the processor 3. When the processor 3 executes the computer program, each step of a comprehensive energy system scheduling method based on source-load dual-side response in embodiment 1 is implemented.

[0130] In summary, the present invention provides a method and terminal for scheduling an integrated energy system based on source-load dual-side response. First, an integrated energy system including various energy supply and energy storage equipment is constructed, and a mathematical model is built, including the operating constraints of various types of equipment and the energy balance constraints of the system. Then, a step-by-step carbon trading mechanism is added to the integrated energy system to influence the output plan of the integrated energy system operator through carbon trading; time-of-use electricity prices and energy satisfaction are integrated on the user side to optimize the user's energy use strategy; an internal and external double-layer optimization model is constructed by combining the energy supply end and the user end, and finally, the optimization solution method of the cplex is nested in the evaluation model with subjective and objective combined empowerment to solve the model, so as to obtain the optimal output plan of the integrated energy system unit and the optimal energy use strategy of the user. The present invention can effectively reduce the carbon emissions of the integrated energy system, adjust the user's energy use strategy through the user incentive mechanism, promote peak shaving and valley filling, and reduce the peak and frequency regulation pressure of the power grid.

[0131] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's description and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for dispatching an integrated energy system based on source-load dual-side response, characterized in that: Including steps: Establish corresponding equipment models for the power supply equipment, heating equipment, cooling equipment and energy storage devices in the integrated energy system, establish a carbon emission model for the integrated energy system, and set corresponding constraints for the integrated energy system; An inner objective function is established with the minimum comprehensive cost of the integrated energy system as the first goal, and an outer objective function is established with the minimum energy cost and the maximum energy satisfaction of the user as the second goal; A two-layer optimization model for an integrated energy system is constructed by combining the inner layer objective function, the outer layer objective function, and the constraint conditions. The inner layer of the two-layer optimization model is a scheduling layer, and the outer layer is a user response layer. The objective function of the scheduling layer is the inner layer objective function, and the objective function of the user response layer is the outer layer objective function. The inner layer sends the solved output plan to the outer layer, and the outer layer returns the solved energy utilization strategy to the inner layer. Solving the two-layer optimization model obtains the optimal output plan of the generator set and the optimal energy utilization strategy of the user. An inner objective function is established with the minimum comprehensive cost of the integrated energy system as the first goal, including: Where, C om represents the system operation and maintenance cost, C buy,e represents the cost of purchasing electricity from the external power grid, C buy,g represents the electricity purchase cost of the gas turbine, represents the tiered carbon trading cost, C wp represents the cost of curtailed power and solar power, C GT represents the gas turbine startup and shutdown cost; Where, ρ represents the carbon trading base price; I Indicates the length of the carbon emission interval; θ represents the price growth rate; The outer objective function is established with the lowest energy cost and the highest energy satisfaction of users as the second goal, including: Where, F m It represents the energy preference cost caused by the deviation of the user's actual load from the user's demand load. F m The smaller the value, the higher the energy satisfaction. k m represents the user's preference coefficient for the mth type of energy, P m,load ( t ) represents the initial load of the user’s mth energy type at time t; represents the optimized load of the user's mth energy type at time t; C BUY represents the cost of purchasing electricity, α e ( t ), α h ( t ), α c ( t ) represent the unit price of electricity, heat and cooling energy at time t, P e,load ( t ) represents the electric load power at time t, P h,load ( t ) represents the heat load power at time t, P c,load ( t ) represents the cooling load power at time t.

2. The method for dispatching an integrated energy system based on source-load dual-side response according to claim 1, characterized in that: The power supply equipment includes a gas turbine, the heating equipment includes a waste heat boiler, an electric boiler and a heat pump, and the cooling equipment includes an electric refrigerator and an absorption refrigerator.

3. The method for dispatching an integrated energy system based on source-load dual-side response according to claim 2, characterized in that: Setting corresponding constraints for the integrated energy system includes: Establishing wind power output constraints and photovoltaic output constraints for the integrated energy system; Establishing electric power balance constraints, thermal power balance constraints, and cooling load power balance constraints for the integrated energy system; Establish energy selling price constraints for power supply, heating and cooling of the integrated energy system.

4. A comprehensive energy system dispatching terminal based on source-load dual-side response, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the following steps are implemented: Establish corresponding equipment models for the power supply equipment, heating equipment, cooling equipment and energy storage devices in the integrated energy system, establish a carbon emission model for the integrated energy system, and set corresponding constraints for the integrated energy system; An inner objective function is established with the minimum comprehensive cost of the integrated energy system as the first goal, and an outer objective function is established with the minimum energy cost and the maximum energy satisfaction of the user as the second goal; A two-layer optimization model for an integrated energy system is constructed by combining the inner layer objective function, the outer layer objective function, and the constraint conditions. The inner layer of the two-layer optimization model is a scheduling layer, and the outer layer is a user response layer. The objective function of the scheduling layer is the inner layer objective function, and the objective function of the user response layer is the outer layer objective function. The inner layer sends the solved output plan to the outer layer, and the outer layer returns the solved energy utilization strategy to the inner layer. Solving the two-layer optimization model obtains the optimal output plan of the generator set and the optimal energy utilization strategy of the user. An inner objective function is established with the minimum comprehensive cost of the integrated energy system as the first goal, including: Where, C om represents the system operation and maintenance cost, C buy,e represents the cost of purchasing electricity from the external power grid, C buy,g represents the electricity purchase cost of the gas turbine, represents the tiered carbon trading cost, C wp represents the cost of curtailed power and solar power, C GT represents the gas turbine startup and shutdown cost; Where, ρ represents the carbon trading base price; I Indicates the length of the carbon emission interval; θ represents the price growth rate; The outer objective function is established with the lowest energy cost and the highest energy satisfaction of users as the second goal, including: Where, F m It represents the energy preference cost caused by the deviation of the user's actual load from the user's demand load. F m The smaller the value, the higher the energy satisfaction. k m represents the user's preference coefficient for the mth type of energy, P m,load ( t ) represents the initial load of the user’s mth energy type at time t; represents the optimized load of the user's mth energy type at time t; C BUY represents the cost of purchasing electricity, α e ( t ), α h ( t ), α c ( t ) represent the unit price of electricity, heat and cooling energy at time t, P e,load ( t ) represents the electric load power at time t, P h,load ( t ) represents the heat load power at time t, P c,load ( t ) represents the cooling load power at time t.

5. The integrated energy system dispatching terminal based on source-load dual-side response according to claim 4 is characterized in that: The power supply equipment includes a gas turbine, the heating equipment includes a waste heat boiler, an electric boiler and a heat pump, and the cooling equipment includes an electric refrigerator and an absorption refrigerator.

6. The integrated energy system dispatching terminal based on source-load dual-side response according to claim 5, characterized in that: Setting corresponding constraints for the integrated energy system includes: Establishing wind power output constraints and photovoltaic output constraints for the integrated energy system; Establishing electric power balance constraints, thermal power balance constraints, and cooling load power balance constraints for the integrated energy system; Establish energy selling price constraints for power supply, heating and cooling of the integrated energy system.

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