A double-layer optimization method for petrochemical park integrated energy system based on nuclear energy small reactor

Abstract

This invention belongs to the field of energy system optimization technology, and relates to a two-layer optimization method for a petrochemical park integrated energy system based on nuclear small modular reactors (SMRs). The method includes: 1. Obtaining the data required for optimization; 2. Constructing the configuration of the integrated energy system based on SMRs; 3. Designing a SMR heat load following strategy; 4. Selecting net present cost, renewable energy supply ratio, and lifecycle carbon emissions as optimization objective functions; 5. Obtaining the optimal equipment capacity of the system through a multi-objective cat swarm algorithm and the advantage-disadvantage distance method; 6. Performing operational optimization based on the optimal solution obtained from capacity optimization, operational optimization constraints, and objective functions. This invention achieves complementary utilization of multiple energy forms by synergistically coupling nuclear energy with renewable energy sources such as wind and solar power, as well as traditional energy systems, thereby improving the overall utilization efficiency of the energy system and enhancing the stability and reliability of energy supply.

Description

Technical Field

[0001] This invention belongs to the field of energy system optimization technology, specifically relating to a two-layer optimization method for integrated energy systems in petrochemical industrial parks based on small nuclear reactors. Background Technology

[0002] Integrated energy systems refer to systems that utilize advanced technologies and management models to integrate various energy sources within a region, organically coordinating energy production, transmission, conversion, distribution, storage, and consumption to form an integrated system with electricity as the primary source and the combined supply of cooling, heating, and gas. By achieving the synergistic and cascaded utilization of multiple energy forms such as electricity and heat, integrated energy systems can effectively improve energy efficiency and reduce system operating costs, and have become an important direction in energy system optimization research. Petrochemical industrial parks, as typical high-energy-consuming industrial settings, have large-scale energy demands and complex load structures, placing high demands on the security, stability, and economy of energy supply. Currently, research on energy systems in petrochemical parks is relatively limited. Traditional energy supply methods in petrochemical parks typically rely on grid power and natural gas, with electricity mainly obtained through participation in the medium- and long-term electricity market via the grid, and heat supplied by gas-fired boilers or gas turbines. This type of energy supply model has a high dependence on fossil fuels, and the overall low-carbon level of the system is limited. Under the "dual-carbon" goal, the energy systems of petrochemical parks urgently need to transform towards low-carbon, high-efficiency, and clean energy. Nuclear energy is characterized by stability, high energy density, and low carbon emissions. By synergistically coupling nuclear energy with renewable energy and traditional energy systems, a nuclear-based integrated energy system can be formed, thereby achieving clean and stable energy supply and the complementary utilization and efficient allocation of multiple energy forms.

[0003] However, existing research largely focuses on single energy systems or single-layer optimization methods, with relatively limited research on integrated energy systems involving small nuclear reactors, especially in petrochemical industrial park scenarios, where there is a lack of collaborative optimization methods that simultaneously consider capacity planning and operation scheduling. Traditional optimization methods typically only optimize equipment capacity configuration or system operation strategies individually, making it difficult to achieve comprehensive improvements in economy, energy efficiency, and low carbon emissions over the entire system lifecycle.

[0004] Therefore, it is necessary to propose a two-layer optimization method for nuclear-based integrated energy systems in petrochemical industrial parks. By constructing a two-layer optimization framework that combines capacity optimization and operation optimization, the method can achieve coordinated optimization of system equipment capacity configuration and operation scheduling strategies, thereby improving the overall system performance and promoting the low-carbon transformation of petrochemical industrial park energy systems, thus solving the aforementioned technical problems. Summary of the Invention

[0005] This invention provides the following technical solution: a two-layer optimization method for an integrated energy system in a petrochemical industrial park based on a small nuclear reactor, comprising the following steps: Step 1: Obtain the data required for optimization. The data includes: electricity purchase and sales prices, natural gas prices, natural endowment data, and typical annual electricity, heat, and cooling loads of the petrochemical park.

[0006] Step 2: Construct the integrated energy system configuration of the nuclear small modular reactor.

[0007] Step 3: Design a nuclear small reactor heat load following strategy based on the typical annual solar thermal and cooling load characteristics of the petrochemical park and the operating characteristics of the small reactor.

[0008] Step 4: Select net present cost, renewable energy supply ratio, and life cycle carbon emissions as the optimization objective functions from the perspectives of economy, energy efficiency, and environment.

[0009] Step 5: Considering energy balance constraints, obtain the overall optimal equipment capacity of the system through the multi-objective cat swarm algorithm and the advantage-disadvantage distance method.

[0010] Step 6: Perform operational optimization based on the optimal solution obtained from capacity optimization, operational optimization constraints, and objective function to further optimize the system's economic performance.

[0011] The beneficial effects of this invention are: 1. This invention addresses the characteristics of high energy consumption, high load density, and complex energy structure in petrochemical industrial parks by constructing a nuclear small modular reactor integrated energy system suitable for petrochemical industrial park scenarios. By synergistically coupling nuclear energy with renewable energy sources such as wind and solar energy as well as traditional energy systems, it achieves complementary utilization of multiple energy forms, improves the overall utilization efficiency of the energy system, and enhances the stability and reliability of energy supply.

[0012] 2. This invention introduces nuclear energy as a basic energy source to achieve clean energy supply for the petrochemical park's energy system. Compared to the traditional energy supply model that mainly relies on grid power and natural gas, this invention can effectively reduce dependence on fossil fuels, reduce carbon emissions during system operation, thereby improving the low-carbon level of the petrochemical park's energy system and promoting the transformation of the park's energy structure towards a cleaner direction.

[0013] 3. This invention achieves coordinated optimization of system equipment configuration and operation strategies by optimizing equipment capacity configuration at the planning layer and system operation scheduling at the operation layer. This method comprehensively considers economic efficiency, energy efficiency, and environmental benefits across the entire system lifecycle, thereby improving the overall operational performance of the integrated energy system.

[0014] 4. This invention employs a multi-objective cat swarm optimization algorithm to solve for capacity allocation at the capacity optimization layer, and uses the advantage-disadvantage distance method to comprehensively evaluate the Pareto solution set to determine the optimal capacity scheme; at the operation optimization layer, it uses the Gurobi solver to solve the operation scheduling model. By combining intelligent optimization algorithms with mathematical programming solvers, the global optimization capability of capacity optimization and the solution efficiency of operation optimization are improved, thereby enhancing the overall optimization performance of the system. Attached Figure Description

[0015] Figure 1 A schematic diagram of the existing energy supply system for petrochemical industrial parks; Figure 2 This is a schematic diagram of the integrated energy system configuration of a petrochemical industrial park based on a two-layer optimization method for a petrochemical industrial park integrated energy system using a nuclear small modular reactor (SMR). Figure 3 This is a flowchart of the petrochemical park nuclear small modular reactor heat load following strategy of the present invention; Figure 4 This is a flowchart illustrating the two-layer optimization process for capacity planning and operation scheduling of the integrated energy system of small nuclear reactors in petrochemical industrial parks, as described in this invention. Figure 5 This is a diagram illustrating the annual heat load satisfaction of the dual-layer optimized system according to the present invention. Figure 6 This is a diagram illustrating the annual electricity load satisfaction of the dual-layer optimization method according to the present invention. Figure 7 This diagram illustrates the annual cooling load satisfaction of the dual-layer optimization method according to the present invention. Detailed Implementation

[0016] The relevant technologies of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0017] like Figures 1-7 As shown in this embodiment, the two-layer optimization method for the integrated energy system of small nuclear reactors in a petrochemical industrial park scenario includes the following steps: Step 1: Obtain the data required for the two-layer optimization of the integrated energy system of small modular reactors in the petrochemical park, including local natural resources, electricity purchase and sale prices, natural gas prices, and typical annual electricity, heat, and cooling load data of the petrochemical park.

[0018] Step 2: Construct a nuclear small modular reactor integrated energy system configuration suitable for petrochemical industrial parks.

[0019] Step 3: Based on the typical annual solar thermal and cooling load characteristics of the petrochemical park and the operating characteristics of small modular reactors, design a heat load following strategy for nuclear small modular reactors suitable for the petrochemical park.

[0020] Step 4: Select net present cost, renewable energy supply ratio, and life cycle carbon emissions as the optimization objective functions from the perspectives of economy, energy efficiency, and environment.

[0021] Step 5: Considering constraints such as energy balance, obtain the optimal equipment capacity of the system through the multi-objective cat swarm algorithm and the advantage-disadvantage distance method, so that the system achieves the best economic efficiency, energy efficiency and environmental protection.

[0022] Step 6: Based on the optimal solution obtained from capacity optimization, the operational optimization constraints, and the objective function, use the Gurobi solver to perform operational optimization, further optimizing the system's economic performance.

[0023] Furthermore, the integrated energy system configuration for small nuclear reactors suitable for petrochemical parks established in step 2 includes equipment such as small nuclear reactors, photovoltaic arrays, solar collectors, wind turbines, gas turbines, gas boilers, heat exchangers, absorption chillers, electric chillers, batteries, thermal storage tanks, and cold storage tanks. The small nuclear reactors, photovoltaic arrays, wind turbines, and gas turbines are connected to the batteries, electric chillers, and petrochemical parks via electrical wires. The gas turbines, gas boilers, solar collectors, absorption chillers, and thermal storage tanks are connected to the petrochemical parks via heat exchangers.

[0024] Furthermore, the heat load following strategy designed in step 3 for the integrated energy system of small nuclear reactors in petrochemical parks includes: (1) Determine the heating demand based on the system heat load demand, and give priority to using small nuclear reactors for heating.

[0025] (2) When the heat supply of the small nuclear reactor is insufficient, the solar collector, gas turbine and gas boiler are activated in sequence to supplement the heat supply.

[0026] (3) When the heat supply exceeds the heat load demand, the excess heat is stored in the heat storage tank. When the heat storage tank reaches the maximum heat storage capacity, the excess heat is released through the heat dissipation device.

[0027] After meeting the heat load demand, the system schedules the electrical load, including: (4) Based on the electricity load demand, the small nuclear reactor is used for power generation first, and photovoltaic arrays, wind turbine generators, gas turbines and grid-purchased electricity are used in sequence to supplement the power supply.

[0028] (5) When the power supply exceeds the power load demand, the excess power is stored in the battery. When the battery reaches its maximum capacity, the remaining power is sold to the grid.

[0029] After meeting the heat and electricity load demands, the system schedules the cooling load, including: (6) Priority should be given to using absorption chillers for cooling, and electric chillers should be used to supplement the cooling for the insufficient part, and the excess cooling capacity should be stored in cold storage tanks.

[0030] Furthermore, step 4 selects net present cost, renewable energy supply ratio, and life cycle carbon emissions as optimization objective functions from three perspectives: economy, energy efficiency, and environment.

[0031] Establish the net present cost objective function for the integrated energy system of small modular reactors in the petrochemical industrial park:

[0032] In the formula: NPC is the net present value cost of the integrated energy system / CNY; CC cap Initial investment cost of integrated energy system / CNY; CC om Operation and maintenance costs of integrated energy systems / CNY; CC rep Equipment replacement cost for integrated energy systems / CNY; CC refule Reactor refueling cost for integrated energy systems / CNY; CC dec Reactor decommissioning cost for integrated energy systems / CNY; CC salve Value of equipment at the end of an integrated energy system / CNY The cost of tiered carbon trading is in CNY.

[0033] Establish the objective function for the renewable energy supply ratio of the integrated energy system for small nuclear reactors in petrochemical industrial parks:

[0034] In the formula: EPRS is the renewable energy supply ratio of the integrated energy system; E total Total energy supply of the integrated energy system / kW·h; E sp Solar photovoltaic power generation / kW·h; E st Heat supplied to solar collectors / kW·h; E w Electricity supplied by wind power generation / kW·h.

[0035] Establish the life-cycle carbon emission objective function for the integrated energy system of small nuclear reactors in petrochemical industrial parks:

[0036] In the formula: LCCE Carbon emissions per kg over the lifecycle of an integrated energy system; C tLet t be the carbon emission coefficient of the integrated energy system at time t; F t Let t represent the carbon emissions of the integrated energy system at time t, expressed as a percentage (kg).

[0037] Furthermore, step 5 considers constraints such as energy balance, including: Based on the supply and demand balance, determine the heat balance constraint:

[0038] In the formula: For heat load, To provide heat for the small nuclear reactor, To provide heat to solar collectors, To provide heat for the gas turbine, To provide heat for gas-fired boilers, To release heat from the heat storage tank, To store heat in the thermal storage tank; Based on the supply and demand balance, determine the power balance constraints:

[0039] In the formula: For electrical load, To supply power to the photovoltaic array, Power supply for wind turbine generators Power supply for the gas turbine Power supply for small nuclear reactors, Purchase electricity for the power grid This refers to the battery discharge capacity. Charge the battery; Based on the supply and demand balance, determine the cold balance constraint:

[0040] In the formula: For cooling load, For absorption refrigeration, the cooling capacity is... For the cooling capacity of electric refrigeration machines, This refers to the amount of cold released from the cold storage tank. This refers to the cold storage capacity of the cold storage tank.

[0041] Furthermore, the optimal capacity configuration scheme for the integrated energy system of small modular reactors (SMRs) is obtained by solving objective functions such as net present cost, renewable energy supply ratio, and life cycle carbon emissions using a multi-objective cat swarm algorithm. The steps of the multi-objective cat swarm algorithm are as follows: (1) Population initialization: Randomly generate an initial cat population of size N within the constraint boundary. P 0, each cat is determined by the optimal decision variable. X =( x 1, x2,…, x D ) and the corresponding optimization objective function F =( f 1, f 2,… f M The system consists of N, where N is the preset population size, D is the number of optimization decision variables (e.g., photovoltaic area, small nuclear reactor capacity, number of wind turbines), and M is the number of optimization evaluation objective functions (e.g., net present cost, renewable energy supply ratio, life cycle carbon emissions).

[0042] (2) Objective function evaluation: Calculate the objective function value for each cat. F =( f 1, f 2,… f M Based on the objective function value, determine the quality of each cat.

[0043] (3) Mode switching: Based on the mode switching probability, the cat group is divided into "search mode" and "tracking mode".

[0044] Pattern finding: The cat randomly searches the solution space to explore new areas.

[0045] Tracking mode: The cat moves closer to the individual optimal solution and the global optimal solution to explore local potential.

[0046] (4) Speed ​​and position update (for cats in tracking mode only): Update speed:

[0047] In the formula: For the updated speed, Current position pbest i This is the optimal solution for the individual. gbest This is the globally optimal solution. r 1, r 2 is a random number.

[0048] (5) Update location:

[0049] In the formula: This is the updated position.

[0050] (6) External files and decompression updates: External archive: Stores non-dominated solutions. Compare the population's non-dominated solutions with the archive solutions; if a new solution is not dominated, it is added to the archive; when the capacity is exceeded, redundant solutions are deleted according to the crowding level.

[0051] Individual / Global Optimal Update: Update the individual optimal solution for each cat; select one or more global optimal solutions from the archive to guide the search.

[0052] (7) Diversity maintenance: In order to prevent the algorithm from converging too early, overly dense solutions are deleted based on crowding or other indicators; random perturbation or local search is introduced to increase the diversity of solutions.

[0053] (8) Termination condition: The algorithm terminates when the termination condition is met. The solution set in the external archive is the Pareto optimal solution set for the current problem.

[0054] Furthermore, in step 5, the solutions obtained from the cat swarm algorithm are filtered using the advantage-disadvantage distance method. The specific steps of the advantage-disadvantage distance method are as follows: (1) Evaluation System Construction: Given m evaluation indicators and n objects to be evaluated, an initial evaluation matrix is ​​established. The evaluation indicators are subjected to trend-following and standardization processing. Among them, cost-type indicators, which are better the smaller the value, are transformed using the reciprocal method, so that all evaluation indicators are unified into benefit-type indicators, which are better the larger the value. Common trend-following processing methods include linear transformation, 0-1 standardization transformation, and interval indicator transformation.

[0055] (2) After completing the trend-following process, the evaluation matrix is ​​standardized to eliminate the influence of differences in dimensions and orders of magnitude among different indicators. Then, the weights of each evaluation indicator are determined based on the pecking order method, and the standardized evaluation indicators are weighted to obtain the weighted evaluation matrix.

[0056] (3) Ideal solution determination: The optimal value is taken in each evaluation index dimension to form a positive ideal solution, and the worst value is taken in each evaluation index dimension to form a negative ideal solution, which is used to calculate the distance between the evaluation object and the ideal solution in the subsequent evaluation.

[0057]

[0058]

[0059] In the formula: , These are efficiency-based and cost-based indicators.

[0060] (4) Distance calculation: Calculate the distance between each evaluation object and the ideal solution and the negative ideal solution respectively, and make a comprehensive evaluation based on this distance difference.

[0061]

[0062]

[0063] In the formula: , This represents the distance between each solution and the ideal solution and the negative ideal solution.

[0064] (5) Ranking of options: By calculating the relative similarity of each evaluation object, the ranking of their merits and demerits is determined, thereby providing a scientific basis for decision-making.

[0065]

[0066] In the formula: The relative similarity of each solution.

[0067] Furthermore, in step 6, operational optimization constraints are determined based on the capacity optimization results, including renewable energy output constraints, energy storage constraints, and energy storage charging and discharging power constraints, as detailed below:

[0068] In the formula, This represents the actual power generation of the photovoltaic array. This represents the maximum power output of the photovoltaic array.

[0069] In the formula, The actual heating power of the solar collector. This represents the maximum heating capacity of the solar collector.

[0070] In the formula: This represents the actual power generation capacity of the wind turbine. This represents the maximum power output of the wind turbine.

[0071]

[0072]

[0073]

[0074] In the formula: S t Indicates time t Energy storage level at that time S min and S max These are the minimum and maximum energy storage capacities, respectively. P charge and P discharge It refers to charging and discharging power.

[0075] Furthermore, in step 6, the objective function expression for optimization is:

[0076] In the formula: C oper Typical daily total operating cost / CNY; C O&M System maintenance cost / CNY; C fuel Fuel cost / CNY; C grid The cost of purchasing and selling electricity from the power grid / CNY; C heat Cost of purchased heat / CNY; C peak System peak shaving cost / CNY.

[0077] Furthermore, in step 6, based on the optimal capacity configuration scheme obtained through capacity optimization, and combining the operational optimization constraints and objective function, a system operation scheduling optimization model is established. The Gurobi solver is then used to solve the operational scheduling optimization model to obtain the system operation results. The specific steps are as follows: (1) Determine the installed capacity of various energy equipment in the system based on the optimal capacity configuration scheme obtained from capacity optimization; (2) Based on the equipment capacity parameters, combined with the system operation constraints and the operation optimization objective function, construct an operation scheduling optimization model for the integrated energy system of small nuclear reactors in the petrochemical park; (3) Solve the operation scheduling optimization model using the Gurobi solver to obtain the optimal operation scheduling results for each scheduling period of the system.

[0078] Example This example uses a petrochemical industrial park in Lanzhou, whose main businesses are oil refining, chemical production, and fertilizer production. The average wind speed in this industrial park is 5.76 m / s. -1 The average annual irradiance was 201.69 W·m. -2 The average annual temperature is 4.07℃, belonging to the temperate continental monsoon climate zone, with four distinct seasons and large temperature differences throughout the year. The annual electricity load demand is stable at approximately 240MW per hour. The heat load differs significantly between the heating and non-heating seasons, with approximately 400MW per hour during the heating season and approximately 360MW per hour during the non-heating season. The project's lifespan is 40 years. The multi-objective cat swarm algorithm has 50 iterations, a population size of 100, 60 archives, a search mode probability of 0.8, a tracking mode switching probability of 0.5, and acceleration factors of 0.5 and 1.

[0079] The integrated energy system for small modular reactors in petrochemical parks proposed in this embodiment can meet the needs of petrochemical park scenarios in terms of heat, electricity, and cooling loads. Furthermore, it achieves comprehensive system performance optimization through a two-tier optimization method combining capacity planning and operation scheduling. To verify the effectiveness of this invention, the operational results of traditional grid-purchased electricity and gas-fired heating schemes were compared, and the results are shown in Table 1.

[0080]

[0081] Table 2 shows the objective function values ​​of the two energy supply schemes after bi-level optimization and their proximity in terms of advantages and disadvantages. Compared with traditional energy supply schemes, the nuclear small modular reactor integrated energy system proposed in this invention shows significant advantages in overall performance, including a net current cost reduction of approximately 25.1%, a life-cycle carbon emission reduction of approximately 64.3%, an increase in the renewable energy supply ratio from 0 to 20.82%, and a total operating cost reduction of approximately 21%. Furthermore, the proximity in terms of advantages and disadvantages is better than that of traditional schemes, indicating that the proposed bi-level optimization method can effectively improve the system's economy, low carbon emissions, and overall operational performance.

[0082]

[0083] Figure 5-7 This demonstrates the annual thermal load, electrical load, and cooling load requirements of the integrated energy system for small nuclear reactors proposed in this invention, serving to verify the system's annual operational performance.

[0084] In summary, the two-layer optimization method for integrated energy systems of small nuclear reactors in petrochemical parks proposed in this invention constructs a system configuration including small nuclear reactors, renewable energy equipment, and energy storage devices. It designs a heat load-priority operation scheduling strategy and uses net present value (NPV) cost, renewable energy supply ratio, and lifecycle carbon emissions as optimization objectives. It combines a multi-objective cat swarm algorithm and the advantage-disadvantage distance method for capacity planning, and then uses the Gurobi solver for operational optimization, forming a complete system optimization scheme. In an application example in a petrochemical park in Lanzhou, this method not only meets the park's annual heat, electricity, and cooling load demands but also significantly reduces the system's NPV cost and lifecycle carbon emissions, and increases the proportion of renewable energy supply. This verifies its effectiveness in improving the system's economy, energy efficiency, and environmental friendliness, providing a feasible path for the optimization and upgrading of energy systems in petrochemical parks.

[0085] It should be emphasized that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any way. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention shall still fall within the scope of the technical solution of the present invention.

Claims

1. A two-layer optimization method for integrated energy systems in petrochemical industrial parks based on small nuclear reactors, characterized in that, Includes the following steps: Step 1: Obtain the data required for optimization, including: electricity purchase and sales prices, natural gas prices, and typical annual daily, heat, and cooling loads of the petrochemical park; Step 2: Construct the integrated energy system configuration of a small nuclear reactor; Step 3: Design a nuclear small reactor heat load following strategy based on the typical annual solar thermal and cooling load characteristics of the petrochemical park and the operating characteristics of the small reactor; Step 4: Select net present cost, renewable energy supply ratio, and life cycle carbon emissions as the optimization objective function from the perspectives of economy, energy efficiency, and environment; Step 5: Considering energy balance constraints, obtain the overall optimal equipment capacity of the system through the multi-objective cat swarm algorithm and the advantage-disadvantage distance method; Step 6: Perform operational optimization based on the optimal solution obtained from capacity optimization, operational optimization constraints, and objective function to further optimize the system's economic performance.

2. The two-layer optimization method for a petrochemical industrial park integrated energy system based on a small nuclear reactor, as described in claim 1, is characterized in that... In step 2, the system equipment includes: a small nuclear reactor, a photovoltaic array, a solar collector, a wind turbine, a gas turbine, a gas boiler, a heat exchange device, an absorption chiller, an electric chiller, a battery, a thermal storage tank, and a cold storage tank; the small nuclear reactor, the photovoltaic array, the wind turbine, and the gas turbine are all electrically connected to the battery, the electric chiller, and the petrochemical park; the gas turbine, the gas boiler, the solar collector, the absorption chiller, and the thermal storage tank are connected to the petrochemical park through the heat exchange device.

3. The two-layer optimization method for a petrochemical industrial park integrated energy system based on a small nuclear reactor as described in claim 1, characterized in that, In step 3, the nuclear small reactor heat load following strategy includes: The heating demand is determined based on the system's heat load requirements, with priority given to using small nuclear reactors for heating. When the heating supply from small nuclear reactors is insufficient, solar collectors, gas turbines, and gas boilers are activated in sequence to supplement the heating supply. When the heating supply exceeds the heat load requirements, the excess heat is stored in a heat storage tank. When the heat storage tank reaches its maximum heat storage capacity, the excess heat is released through a heat dissipation device. After the system meets the heat load demand, it prioritizes the use of nuclear small modular reactors to generate electricity according to the electrical load demand, and then activates photovoltaic arrays, wind turbine generators, gas turbines, and grid-purchased electricity in sequence to supplement the power supply; when the power supply exceeds the electrical load demand, the excess electricity is stored in batteries; when the batteries reach their maximum capacity, the remaining electricity is sold to the grid. Once the system meets the heat and electrical load requirements, it prioritizes using absorption chillers for cooling, supplementing the remaining cooling capacity with electric chillers, and storing excess cooling capacity in cold storage tanks.

4. The two-layer optimization method for a petrochemical industrial park integrated energy system based on a small nuclear reactor as described in claim 1, characterized in that, In step 4: The objective function for net present cost is: In the formula, NPC represents net present cost, and CC represents net present cost. cap For the initial investment cost, CC om For operation and maintenance costs, CC rep For equipment replacement costs, CC refule For reactor refueling costs, CC dec For reactor decommissioning costs, CC salve For the end value of equipment, For tiered carbon trading costs; The objective function for the renewable energy supply ratio is: In the formula, EPRS represents the renewable energy supply ratio. E total For total energy supply, E sp For solar photovoltaic power generation, E st To provide heat to solar collectors, E w Power generation for wind power; The life-cycle carbon emission objective function is: In the formula: LCCE For life cycle carbon emissions, C t Let be the carbon emission coefficient at time t. F t Let t be the carbon emissions at time t.

5. The two-layer optimization method for a petrochemical industrial park integrated energy system based on a small nuclear reactor as described in claim 1, characterized in that, In step 5, the energy balance constraint includes: Thermal equilibrium constraint: In the formula: For heat load, To provide heat for the small nuclear reactor, To provide heat to solar collectors, To provide heat for the gas turbine, To provide heat for gas-fired boilers, To release heat from the heat storage tank, To store heat in the thermal storage tank; Electrical balance constraints: In the formula: For electrical load, To supply power to the photovoltaic array, Power supply for wind turbine generators, Power supply for the gas turbine Power supply for small nuclear reactors, Purchase electricity for the power grid This refers to the battery discharge capacity. Charge the battery; Cold balance constraint: In the formula: For cooling load, For absorption refrigeration, the cooling capacity is... For the cooling capacity of electric refrigeration machines, This refers to the amount of cold released from the cold storage tank. This refers to the cold storage capacity of the cold storage tank.

6. The two-layer optimization method for a petrochemical industrial park integrated energy system based on a small nuclear reactor as described in claim 1, characterized in that, In step 5, the multi-target cat swarm algorithm includes: Step 5-A-1, Population Initialization: Optimization decision variables include: photovoltaic area, nuclear small reactor capacity, number of wind turbines, and optimization evaluation objective function includes: net present cost, renewable energy supply ratio, and life cycle carbon emissions; Step 5-A-2, Objective Function Evaluation: Calculate the objective function value for each cat. ， The quality of each cat is determined based on the objective function value; Step 5-A-3, Mode Switching: Based on the mode switching probability, divide the cat group into "search mode" and "tracking mode"; Step 5-A-4, Speed ​​and Position Update; Step 5-A-5: Update location; Step 5-A-6: External files and unpacking / updating; Step 5-A-7, Diversity Maintenance: To prevent the algorithm from converging prematurely, remove overly dense solutions based on indicators; introduce random perturbations or local searches to increase the diversity of solutions; Step 5-A-8, Termination Condition: When the termination condition is met, the algorithm ends; the solution set in the external archive is the Pareto optimal solution set for the current problem.

7. A two-layer optimization method for a petrochemical industrial park integrated energy system based on a small nuclear reactor, as described in claim 6, is characterized in that... In step 5, the advantage / disadvantage distance method includes: Step 5-B-1, Evaluation System Construction: Set evaluation indicators and objects to be evaluated, and establish an initial evaluation matrix; perform trend-following and standardization processing on the evaluation indicators. Among them, cost-type indicators that are better the smaller the value, are transformed using the reciprocal method, so that all evaluation indicators are unified into benefit-type indicators that are better the larger the value. Step 5-B-2: After completing the trend-following process, the evaluation matrix is ​​standardized; then, the weights of each evaluation index are determined based on the pecking order graph method, and the standardized evaluation indexes are weighted to obtain the weighted evaluation matrix. Step 5-B-3: Determining the ideal solution: The optimal value is taken in each evaluation index dimension to form a positive ideal solution, and the worst value is taken in each evaluation index dimension to form a negative ideal solution. Step 5-B-4, Distance Calculation: Calculate the distance between each evaluation object and the ideal solution and the negative ideal solution, and make a comprehensive evaluation based on this distance difference; Step 5-B-5, Scheme Ranking: By calculating the relative similarity of each evaluation object, their superiority and inferiority are determined, thereby providing a scientific basis for decision-making.

8. The two-layer optimization method for a petrochemical industrial park integrated energy system based on a small nuclear reactor as described in claim 1, characterized in that, In step 6, the optimization constraints include: In the formula, This represents the actual power generation of the photovoltaic array. This represents the maximum power output of the photovoltaic array. In the formula, The actual heating power of the solar collector. This represents the maximum heating capacity of the solar collector. In the formula, This represents the actual power generation capacity of the wind turbine. This represents the maximum power generation capacity of the wind turbine. In the formula: S t Indicates time t Energy storage level at that time S min , S max These represent the minimum and maximum energy storage capacities, respectively. , These represent the charging and discharging power at time t, respectively. , These represent the maximum charging and discharging power, respectively.

9. A two-layer optimization method for a petrochemical industrial park integrated energy system based on a small nuclear reactor, as described in claim 1, is characterized in that... In step 6, the objective function for optimization is: In the formula, C oper The typical daily total operating cost, C O&M For system operation and maintenance costs, C fuel For fuel costs, C grid To negotiate the cost of purchasing and selling electricity with the power grid, C heat To cover the cost of purchasing heat, C peak This refers to the system's peak-shaving cost.

10. A two-layer optimization method for a petrochemical industrial park integrated energy system based on a small nuclear reactor, as described in claim 1, is characterized in that... In step 6, the specific steps for optimization include: Based on the optimal capacity configuration scheme obtained from capacity optimization, determine the installed capacity of various energy equipment in the system; Based on equipment capacity parameters, combined with system operation constraints and operation optimization objective function, an operation scheduling optimization model for integrated energy system of small nuclear reactor in petrochemical park is constructed. The operation scheduling optimization model is solved using a solver to obtain the optimal operation scheduling results for each scheduling period of the system.

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