A method, system, device and medium for electro-thermal-hydrogen low carbon operation balance

Abstract

The application provides a method, system, device and medium for electric-thermal-hydrogen low-carbon operation balance, relates to the field of comprehensive energy system optimization and low-carbon scheduling, and comprises the following steps: obtaining comprehensive energy parameters of a park, inputting the comprehensive energy parameters into a preset upper economic operation model, calculating a minimum operation cost scheme, inputting the minimum cost scheme into a preset carbon emission factor composite model, calculating a carbon emission factor corresponding to the comprehensive energy, inputting the carbon emission factor into a preset lower carbon emission optimization model, and calculating a load corresponding to the minimum carbon emission; updating the upper economic operation model based on the load, generating a new minimum operation cost scheme, repeating the step of inputting the minimum operation cost scheme into the preset carbon emission factor composite model for iteration until a preset iteration condition is reached, obtaining a device output scheme corresponding to the minimum cost and minimum carbon emission balance, and obtaining a carbon emission mapping from a power source to a terminal.

Description

Technical Field

[0001] This invention relates to the field of integrated energy system optimization and low-carbon dispatching technology, specifically to a method, system, equipment, and medium for low-carbon operation balance of electricity, heat, and hydrogen. Background Technology

[0002] Integrated energy systems at the park level have rapidly emerged in recent years due to their unique advantages in integrating multiple energy forms, achieving tiered energy utilization, and efficient allocation. They have become an indispensable and important vehicle for supporting the low-carbon transformation of regional energy. In these integrated energy systems, electricity, heat, hydrogen, and other energy systems are intertwined and operate synergistically. The synergistic optimization of these multi-energy systems not only improves energy utilization efficiency and reduces energy consumption costs but also significantly reduces carbon emissions.

[0003] However, there are some pressing issues to be addressed in the current carbon emission accounting of integrated energy systems at the park level. Currently, most multi-energy systems use a static average factor method for carbon emission accounting. This method simply distributes the total carbon emissions over a period of time evenly across various energy production or consumption stages, ignoring the dynamic changes in carbon emissions over time, energy production structure, and market factors. The operation of an energy system is a dynamic process; energy production and consumption patterns, energy source structures, and the external market environment all change over different time periods, directly affecting the intensity and distribution of carbon emissions. The static average factor method cannot reflect this dynamic evolution of carbon emissions, leading to significant discrepancies between the accounting results and actual conditions. This makes it difficult to accurately assess the carbon emission status of the park's energy system and thus cannot provide effective data support and decision-making basis for coordinated energy and carbon scheduling within the park.

[0004] Meanwhile, existing research on carbon emission analysis has another significant limitation. Most studies focus solely on carbon emissions from equipment within the industrial park system, neglecting the impact of external electricity market carbon emission attributes on the park's energy system. Existing research lacks a mechanism to incorporate external electricity market carbon emission attributes into a unified model for coordinated modeling. This makes it impossible to comprehensively consider various influencing factors when analyzing industrial park carbon emissions, resulting in unclear carbon responsibility allocation and incomplete carbon optimization boundaries.

[0005] Furthermore, as a highly promising clean energy source, hydrogen energy's carbon emission characteristics are not static; they are highly dependent on the electricity source structure. If the electricity used in hydrogen production comes from high-carbon fossil fuel power generation, the process indirectly generates significant carbon emissions. Conversely, if renewable energy is used for hydrogen production, carbon emissions are significantly reduced. However, existing models have not yet established a carbon emission factor mapping mechanism for the entire electricity-heat-hydrogen process, making it impossible to accurately quantify the carbon emission intensity of hydrogen energy at different points in time. In the low-carbon scheduling of the park's energy system, it is difficult to fully consider the carbon emission characteristics of hydrogen energy, and it is impossible to rationally adjust hydrogen energy production and use based on carbon emission conditions at different points in time. This hinders the full utilization of hydrogen energy in low-carbon scheduling and restricts the development of the park's energy system towards a low-carbon and efficient direction. Summary of the Invention

[0006] This invention addresses the problems existing in the prior art by providing a method, system, equipment, and medium for achieving a low-carbon operation balance between electricity, heat, and hydrogen. To achieve the above objectives, the technical solution adopted by this invention is as follows:

[0007] The comprehensive energy parameters of the park are obtained and input into a preset upper-level economic operation model to calculate the minimum operating cost scheme; wherein, the formula of the upper-level economic operation model includes:

[0008] ; For equipment maintenance costs, It is the cost of purchasing energy. This refers to the cost of energy storage device depletion during its charge and discharge lifespan.

[0009] The minimum cost scheme is input into a preset carbon emission factor composite model. The carbon emission factor corresponding to the integrated energy source is obtained through both linear and nonlinear calculations. This integrated energy source carbon emission factor is then input into a preset lower-level carbon emission optimization model to calculate the load corresponding to the minimum carbon emissions. The formulas for the lower-level carbon emission optimization model include: In the formula, For carbon price, , , These represent the park's electricity consumption, heat consumption, and hydrogen and carbon emissions, respectively.

[0010] Based on the load update upper-level economic operation model, a new minimum operating cost scheme is generated. The process of repeatedly inputting the minimum operating cost scheme into the preset carbon emission factor composite model is iterated until the preset iteration conditions are met, thereby obtaining the equipment output scheme corresponding to the minimum cost and minimum carbon emission balance.

[0011] In some embodiments, the step of inputting the minimum cost scheme into a preset carbon emission factor composite model to calculate the carbon emission factor corresponding to the comprehensive energy includes:

[0012] The carbon emissions at the integrated energy input point during the specified time period are obtained based on the minimum cost scheme and the carbon flow conservation law, wherein the integrated energy includes electricity, heat and hydrogen;

[0013] Calculate the carbon emission transfer generated during the charging and discharging of electricity, heat and hydrogen energy storage, and establish an energy-carbon flow coupling relationship between electricity, heat and hydrogen based on the carbon emission transfer and the carbon emissions at the integrated energy input terminal during the time period;

[0014] Based on the energy-carbon flow coupling relationship of electricity, heat and hydrogen, the carbon emissions of the integrated energy input terminal during the time period are allocated to obtain the time-sharing carbon emission factor of electricity-heat-hydrogen.

[0015] In some embodiments, the step of calculating carbon emission transfers generated during the charging and discharging of electrical, thermal, and hydrogen energy storage includes:

[0016] Electric energy storage and hydrogen energy storage can calculate the linear carbon emission transfer and input during the charging and discharging process;

[0017] Thermal energy storage calculates linear energy and nonlinear thermal loss energy during charging and discharging. Specifically, it obtains the input thermal energy and heat source carbon emission factor during the charging phase, and calculates the effective stored linear energy and carbon emissions during the charging phase.

[0018] The thermal energy conversion efficiency curve is fitted, and the nonlinear energy loss and heat release power curves during the charging stage are calculated by using the input thermal energy and the effectively stored linear energy during the charging stage.

[0019] The effective heat release energy during the heat release stage is calculated by integrating the heat release power curve and combining it with the heat energy conversion efficiency curve.

[0020] The nonlinear heat loss energy during the heat release stage is calculated based on the effective stored linear energy and the effective heat release energy during the heat release stage.

[0021] The total carbon emissions of thermal energy storage are calculated as the linear energy effectively stored, the nonlinear energy loss during the charging phase, and the nonlinear heat loss during the heat release phase.

[0022] In some embodiments, the step of inputting carbon emission factors into a preset lower-level carbon emission optimization model and calculating the load corresponding to the minimum carbon emissions includes:

[0023] The time-division carbon emission factor of the electric-thermal-hydrogen process is input into a preset lower-level carbon emission optimization model;

[0024] Based on the time-sharing carbon emission factor of the electricity-heat-hydrogen system and the objective function of minimizing carbon emissions, the electricity, heat and hydrogen loads in the park are adjusted in time sequence.

[0025] The resulting load allocation scheme, which shifts load from high-carbon emission periods to low-carbon emission periods while keeping the total load constant, is used as the load corresponding to the minimum carbon emissions.

[0026] In some embodiments, the process of constructing the preset upper-level economic operation model is as follows:

[0027] Historical data of equipment within the park is acquired, preprocessed, and a cost dataset is obtained, which includes equipment parameters, load data, electricity price information, and renewable energy forecast data.

[0028] A mathematical model is constructed with the objective function of minimizing operating costs. The operating constraints of the equipment and the power supply and demand balance constraints are constructed, and the operating strategies of the equipment in each time period are obtained by solving the problem.

[0029] The indicators corresponding to the operating strategy calculated by the mathematical model are compared with the actual data. When the error value does not exceed the threshold, the mathematical model is used as the upper-level economic operating model.

[0030] In some embodiments, the construction process of the preset lower-level carbon emission optimization model is as follows:

[0031] Obtain the carbon emission factors corresponding to electricity, heat, and hydrogen within a specific historical time period;

[0032] A preliminary carbon emission optimization model is constructed by using the minimum carbon emission obtained by multiplying the electricity, heat, and hydrogen loads with their corresponding time-of-use carbon emission factors as the objective function.

[0033] The preliminary carbon emission optimization model is solved by linear programming and nonlinear programming. Based on the objective function, the values ​​of electricity, heat, and hydrogen loads are adjusted at different time periods to obtain the load time sequence allocation scheme that minimizes carbon emissions.

[0034] In some embodiments, the formula for the equipment output scheme is as follows:

[0035] ;

[0036] in, The objective function is to minimize operating cost. It is the objective function for minimizing carbon emissions. λ These are weighting coefficients, 0 ≤ λ ≤ 1. It is the output of the equipment;

[0037] in, Satisfy power balance and constraint conditions;

[0038] Power balance: ∑ =D, where D is the total power demand;

[0039] Equipment output limits: ≤ ≤ ,in and These are the minimum and maximum output limits for device i, respectively.

[0040] This invention proposes a system for low-carbon operation balance of electricity, heat, and hydrogen, comprising:

[0041] The cost unit is configured to acquire the comprehensive energy parameters of the park and input these parameters into a preset upper-level economic operation model to calculate the minimum operating cost scheme; wherein, the formula of the upper-level economic operation model includes:

[0042] ; For equipment maintenance costs, It is the cost of purchasing energy. This refers to the cost of energy storage device depletion during its charge and discharge lifespan.

[0043] A carbon emission unit is configured to input the minimum cost scheme into a preset carbon emission factor composite model, obtain the carbon emission factor corresponding to the comprehensive energy source through linear and nonlinear calculations, and input the carbon emission factor corresponding to the comprehensive energy source into a preset lower-level carbon emission optimization model to calculate the load corresponding to the minimum carbon emissions; wherein, the formula of the lower-level carbon emission optimization model includes: In the formula, For carbon price, , , These represent the park's electricity consumption, heat consumption, and hydrogen and carbon emissions, respectively.

[0044] The iteration unit is configured to update the upper-level economic operation model based on the load, generate a new minimum operating cost scheme, and repeat the step of inputting the minimum cost scheme into the preset carbon emission factor composite model for iteration until the preset iteration conditions are met, so as to obtain the equipment output scheme corresponding to the minimum cost and minimum carbon emission balance.

[0045] This invention proposes a computer device, comprising:

[0046] At least one processor; and a memory storing a computer program executable on the processor, wherein the processor, when executing the program, performs the steps of the method for an electro-thermal-hydrogen low-carbon operating balance.

[0047] The present invention proposes a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the method for an electro-thermal-hydrogen low-carbon operating balance.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] This invention proposes a method, system, equipment, and medium for achieving low-carbon operation balance between electricity, heat, and hydrogen. The method includes: acquiring comprehensive energy parameters of the industrial park and inputting these parameters into a preset upper-level economic operation model to calculate the minimum operating cost scheme; inputting the minimum cost scheme into a preset carbon emission factor composite model and calculating the carbon emission factor corresponding to the comprehensive energy through linear and nonlinear calculations, respectively; inputting the carbon emission factor into a preset lower-level carbon emission optimization model to calculate the load corresponding to the minimum carbon emission; updating the upper-level economic operation model based on the load to generate a new minimum operating cost scheme; and iteratively repeating the step of inputting the minimum operating cost scheme into the preset carbon emission factor composite model until a preset iteration condition is met to obtain the equipment output scheme corresponding to the minimum cost and minimum carbon emission balance.

[0050] This invention enables precise tracing and allocation of carbon emission responsibility. By introducing a composite model of time-sharing carbon emission factors based on the energy-carbon flow coupling mechanism, it can accurately characterize the carbon emission contributions of different energy paths and conversion equipment, realizing carbon emission mapping from power source to end load. This breaks through the limitations of traditional coarse-grained and static accounting of average carbon factors, providing a refined foundation for carbon responsibility allocation and low-carbon management of multi-energy systems in industrial parks.

[0051] A market-industrial park carbon flow coordination mechanism is constructed to improve the integrity of carbon optimization. By introducing the carbon emission attributes of electricity traded in the external electricity market and forming a unified carbon emission flow model with the equipment inside the industrial park, the problem of underestimation of carbon responsibility caused by the lack of carbon emissions from external electricity purchases in existing studies is solved, and the accuracy of system scheduling strategies and the integrity of carbon optimization boundaries are significantly improved.

[0052] Drive proactive low-carbon response on the load side, promote the transformation of energy consumption behavior, embed time-of-use carbon emission factors into the optimization model, guide the migration of three types of terminal loads (electricity, heat, and hydrogen) from high-carbon periods to low-carbon periods, form a load guidance mechanism with carbon as a signal, realize low-carbon energy consumption adjustment on the demand side under the premise of ensuring unchanged energy demand, and significantly improve the overall carbon emission reduction capacity of the system.

[0053] Balancing system economy and carbon emission reduction to enhance overall operational efficiency, a two-layer optimization scheduling model with source-load coordination is constructed. The upper layer aims to minimize operating costs, while the lower layer aims to minimize carbon emissions, achieving synergistic optimization of economic efficiency and low carbon emissions. Simulation results show that after introducing a time-sharing carbon factor mechanism, the system exhibits significant peak-shaving and carbon-avoidance characteristics, resulting in reduced carbon emissions while maintaining good operational economy, providing an engineering feasible path for the low-carbon transformation of steel industrial parks. Attached Figure Description

[0054] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained based on these drawings without creative effort.

[0055] Figure 1 A flowchart of a method for achieving low-carbon operation balance between electricity, heat, and hydrogen provided by this invention;

[0056] Figure 2 A system module diagram for a low-carbon operation balance of electricity, heat, and hydrogen provided by the present invention;

[0057] Figure 3 A schematic diagram of the structure of an embodiment of the computer device provided by the present invention;

[0058] Figure 4 This is a schematic diagram of an embodiment of the computer-readable storage medium provided by the present invention. Detailed Implementation

[0059] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and should not be construed as limiting the scope of protection of the present invention. It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application.

[0060] It should be noted that all uses of "first" and "second" in the embodiments of the present invention are for the purpose of distinguishing two entities or parameters with the same name but different names. It is clear that "first" and "second" are only for the convenience of expression and should not be construed as limiting the embodiments of the present invention. Subsequent embodiments will not explain this in detail.

[0061] This invention proposes a method for achieving a low-carbon operation balance between electricity, heat, and hydrogen. Please refer to [link / reference]. Figure 1 ,include:

[0062] S1. Obtain the comprehensive energy parameters of the park and input the comprehensive energy parameters into a preset upper-level economic operation model to calculate the minimum operating cost scheme; wherein, the formula of the upper-level economic operation model includes: ; For equipment maintenance costs, It is the cost of purchasing energy. This refers to the cost of energy storage device depletion during its charge and discharge lifespan.

[0063] S2. Input the minimum cost scheme into a preset carbon emission factor composite model, and obtain the carbon emission factor corresponding to the comprehensive energy source through linear and nonlinear calculations respectively. Input the carbon emission factor corresponding to the comprehensive energy source into a preset lower-level carbon emission optimization model to calculate the load corresponding to the minimum carbon emissions; wherein, the formula of the lower-level carbon emission optimization model includes: In the formula, For carbon price, , , These represent the park's electricity consumption, heat consumption, and hydrogen and carbon emissions, respectively.

[0064] S3. Based on the load update upper-level economic operation model, generate a new minimum operating cost scheme, and repeat the step of inputting the minimum operating cost scheme into the preset carbon emission factor composite model for iteration until the preset iteration conditions are met, so as to obtain the equipment output scheme corresponding to the minimum cost and minimum carbon emission balance.

[0065] This invention can significantly reduce the operating costs of energy systems. Traditional energy equipment output schemes often focus on meeting energy demand, with less consideration for cost and carbon emission factors. The equipment output scheme that balances minimum cost and minimum carbon emissions meticulously adjusts the operating status and output of various equipment. In the power system, the output of thermal power generating units, hydropower generating units, and renewable energy generating units is rationally arranged according to electricity price fluctuations at different times. When electricity prices are low and renewable energy is abundant, the proportion of renewable energy generation is increased, reducing fuel consumption for thermal power generation, thereby lowering power generation costs. The equipment output scheme that balances minimum cost and minimum carbon emissions prioritizes low-carbon or zero-carbon energy equipment and operating modes, reducing carbon emissions. Energy is rationally allocated according to the characteristics of different equipment and changes in energy demand, ensuring more efficient utilization of energy in production, transmission, and use. In combined heat and power (CHP) systems, by optimizing the output of equipment such as boilers and turbines, efficient synergistic production of heat and electricity is achieved, reducing energy losses during conversion. By implementing tiered energy utilization, high-temperature and high-pressure energy is first used for power generation, and then low-temperature and low-pressure waste heat is used for heating or industrial production. This improves the level and efficiency of energy utilization and maximizes energy utilization.

[0066] By integrating equipment maintenance costs, energy purchase costs, energy storage device charging and discharging lifespan losses, and carbon emission-related costs into a single model, a comprehensive and systematic assessment of the total cost of the park's economic operation can be achieved.

[0067] Equipment maintenance costs drive industrial parks to prioritize equipment upkeep and maintenance. Regular maintenance allows for the timely detection and resolution of potential equipment problems, reducing the frequency of equipment failures, extending equipment lifespan, and ensuring stable and reliable operation. This is especially important for equipment-intensive industrial parks, as stable equipment operation can prevent production interruptions due to equipment failures and reduce production losses.

[0068] Energy purchase costs allow industrial parks to optimize their energy procurement decisions based on factors such as price fluctuations and supply stability of different energy sources. This includes increasing purchase volumes when energy prices are low and signing long-term contracts with energy suppliers to obtain more favorable prices, thereby reducing energy purchase costs and improving the park's profitability.

[0069] The charging and discharging process of energy storage devices leads to lifespan loss and corresponding costs. Incorporating these lifespan loss costs into the model allows for more rational planning of energy storage device usage within industrial parks. Based on different production needs and energy price conditions, the optimal timing and frequency of energy storage charging and discharging can be determined, avoiding damage from overcharging and discharging, extending the lifespan of energy storage devices, and reducing energy storage costs.

[0070] Higher carbon prices will encourage industrial parks to take more proactive measures to reduce carbon emission costs, incentivize investment in research and development and application of low-carbon technologies, optimize production processes, and improve energy efficiency, thereby driving the transformation of industrial parks towards a low-carbon production model.

[0071] By considering the carbon emissions from electricity, heat, and hydrogen consumption in the industrial park, the total carbon emissions of the park can be calculated more accurately. Different forms of energy have different carbon emission characteristics during production and use. By measuring and calculating them separately, we can clearly understand the carbon emission situation of the park at each stage, providing accurate data support for the formulation of targeted emission reduction strategies.

[0072] To establish a high-proportion new energy urban power system model for the park with long-term hydrogen energy storage, a sub-model of production equipment, an energy conversion equipment, and an energy storage equipment is to be established. Among them, the production equipment sub-model is a gas turbine.

[0073]

[0074] In the formula, , This represents the electrical and thermal power output by GT at time t; , Indicates the electrical and thermal efficiency of the gas turbine; This represents the gas turbine's power consumption at time t; , , , These are the upper and lower limits of the power and heat output of the gas turbine, respectively.

[0075] The sub-model expression for the energy conversion device is as follows:

[0076] Electrolysis hydrogen production system:

[0077]

[0078] In the formula, This represents the power of hydrogen production at time t; This represents the electrical power consumed by the electrolytic cell at time t; , These are the upper and lower limits of hydrogen production power of the electrolyzer;

[0079] Electric boiler:

[0080]

[0081] In the formula, This represents the thermal power output of the electric boiler at time t; The coefficient of performance for electro-thermal conversion; Let t be the power consumption of the electric boiler. , These are the upper and lower limits of the heat output power of the electric boiler;

[0082] Gas-fired boilers:

[0083]

[0084] In the formula: This represents the thermal power output of the gas-fired boiler at time t; This indicates the heating efficiency of a gas-fired boiler. This represents the gas consumption power of the gas-fired boiler at time t; , These represent the upper and lower limits of the output thermal power of the gas-fired boiler.

[0085] Energy storage device sub-model:

[0086] Storage battery:

[0087]

[0088] In the formula: This represents the battery's operating power at time t; , These represent the charging and discharging efficiencies of the battery, respectively. , These represent the charging and discharging states of the battery at time t-1, respectively. , These represent the charging and discharging power of the battery at time t-1, respectively. , These are the upper and lower limits of the battery charging power, respectively. , These are the upper and lower limits of the battery's discharge power, respectively. , These are the upper and lower limits of the battery's energy storage capacity, respectively.

[0089] Thermal storage tank:

[0090]

[0091] In the formula, This represents the thermal storage power of the thermal storage tank at time t; , These represent the filling and discharging efficiencies of the thermal storage tank, respectively. , These represent the charging and discharging states of the thermal storage tank at time t-1, respectively. , These represent the charging and discharging power of the thermal storage tank at time t-1, respectively. , These are the upper and lower limits of the thermal storage capacity of the thermal storage tank, respectively. , These are the upper and lower limits of the heat release power of the thermal storage tank; , These are the upper and lower limits of the thermal storage capacity of the thermal storage tank, respectively.

[0092] Hydrogen storage tank:

[0093]

[0094] In the formula, This represents the thermal storage power of the thermal storage tank at time t; , These represent the filling and discharging efficiencies of the thermal storage tank, respectively. , These represent the charging and discharging states of the thermal storage tank at time t-1, respectively. , These represent the charging and discharging power of the thermal storage tank at time t-1, respectively. , These are the upper and lower limits of the thermal storage capacity of the thermal storage tank, respectively. , These are the upper and lower limits of the heat release power of the thermal storage tank, respectively. , These represent the upper and lower limits of the thermal storage capacity of the thermal storage tank.

[0095] This invention constructs a two-layer optimization scheduling model. The upper-layer economic operation model aims to minimize the operating cost of the park by optimizing equipment output and market power purchase strategies. The lower-layer carbon emission optimization model aims to minimize carbon emissions by guiding the time-series transfer of electricity-heat-hydrogen loads through time-of-use carbon emission factors to achieve low-carbon operation.

[0096] Mathematical programming methods are employed to solve the bi-level optimization problem, and a comparative analysis is conducted on carbon emission indicators before and after introducing time-sharing carbon emission factors to guide low-carbon operation. The constructed source-load coordinated bi-level optimization scheduling model is numerically solved using the Python programming language combined with the Gurobi optimization solver. By setting an iterative coupling mechanism between the upper and lower level models, the optimal output strategy for each device is obtained while ensuring solution convergence.

[0097] In some embodiments, please refer to Figure 1 The steps of obtaining the comprehensive energy parameters of the park and inputting the comprehensive energy parameters into a preset upper-level economic operation model to calculate the minimum operating cost scheme include:

[0098] Obtain comprehensive energy parameters of the park, including park load, renewable energy output forecast, electricity market transaction contract information, and equipment operating parameters;

[0099] The comprehensive energy parameters of the park are input into the preset upper-level economic operation model;

[0100] The goal is to minimize operating costs by performing optimization calculations on the power generation and energy storage equipment in the park;

[0101] The optimal equipment operation strategy is obtained to determine the minimum operating cost of the park during the specified time period.

[0102] The upper-level economic operation model comprehensively considers factors such as energy supply, demand, equipment operation, and market prices, simulating and optimizing the operation of the park's energy system through mathematical methods and algorithms. The calculated minimum operating cost scheme brings significant economic benefits to the park's energy management. The model can formulate optimal equipment operation strategies based on energy price fluctuations. It rationally arranges equipment start-up and shutdown times and operating power according to equipment efficiency and energy consumption, avoiding equipment operation in inefficient states and reducing unnecessary energy consumption and equipment damage. The minimum operating cost scheme improves the park's energy utilization efficiency, optimizes the conversion and synergistic utilization between different energy sources, and enables the cascade and comprehensive utilization of energy. It recovers and utilizes waste heat generated during industrial production for heating or power generation, reducing dependence on external energy sources and rationally allocating the supply of various energy sources such as electricity, heat, and hydrogen to meet the park's needs and avoid energy waste and idleness.

[0103] In some embodiments, please refer to Figure 1 The step of inputting the minimum cost scheme into a preset carbon emission factor composite model to calculate the carbon emission factor corresponding to the comprehensive energy includes:

[0104] The carbon emissions at the integrated energy input point during the specified time period are obtained based on the minimum cost scheme and the carbon flow conservation law, wherein the integrated energy includes electricity, heat and hydrogen;

[0105] Calculate the carbon emission transfer generated during the charging and discharging of electricity, heat and hydrogen energy storage, and establish an energy-carbon flow coupling relationship between electricity, heat and hydrogen based on the carbon emission transfer and the carbon emissions at the integrated energy input terminal during the time period;

[0106] Based on the energy-carbon flow coupling relationship of electricity, heat and hydrogen, the carbon emissions of the integrated energy input terminal during the time period are allocated to obtain the time-sharing carbon emission factor of electricity-heat-hydrogen.

[0107] By accurately calculating the carbon emission factor of integrated energy, understanding the carbon emissions of each energy combination throughout its entire life cycle, rationally determining the proportion of various energy sources, and optimizing the energy layout, the park can develop in a low-carbon and sustainable direction from the initial stage of construction, avoiding large-scale renovations and adjustments due to unreasonable energy structure in the later stages, and saving a lot of time and money.

[0108] Real-time monitoring of the relationship between energy consumption and carbon emissions enables refined energy management and carbon reduction control. In integrated energy systems, the supply and demand of various energy sources are dynamic. By monitoring the carbon emission factors of different energy sources, high-carbon emission links in the energy use process can be identified in a timely manner. If a high carbon emission factor for electricity is found during a certain period, it is because the supply relies heavily on high-carbon thermal power. Energy use strategies can be adjusted promptly, such as activating backup energy storage devices and increasing the proportion of renewable energy consumption, to reduce carbon emissions during that period, improve energy efficiency, and reduce unnecessary energy waste and carbon emissions.

[0109] In some embodiments, please refer to Figure 1 The steps for calculating carbon emission transfers generated during the charging and discharging of electrical, thermal, and hydrogen energy storage include:

[0110] Electric energy storage and hydrogen energy storage can calculate the linear carbon emission transfer and input during the charging and discharging process;

[0111] Thermal energy storage calculates linear energy and nonlinear thermal loss energy during charging and discharging. Specifically, it obtains the input thermal energy and heat source carbon emission factor during the charging phase, and calculates the effective stored linear energy and carbon emissions during the charging phase.

[0112] The thermal energy conversion efficiency curve is fitted, and the nonlinear energy loss and heat release power curves during the charging stage are calculated by using the input thermal energy and the effectively stored linear energy during the charging stage.

[0113] The effective heat release energy during the heat release stage is calculated by integrating the heat release power curve and combining it with the heat energy conversion efficiency curve.

[0114] The nonlinear heat loss energy during the heat release stage is calculated based on the effective stored linear energy and the effective heat release energy during the heat release stage.

[0115] The total carbon emissions of thermal energy storage are calculated as the linear energy effectively stored, the nonlinear energy loss during the charging phase, and the nonlinear heat loss during the heat release phase.

[0116] In some embodiments, please refer to Figure 1 The step of inputting carbon emission factors into a preset lower-level carbon emission optimization model and calculating the load corresponding to the minimum carbon emissions includes:

[0117] The time-division carbon emission factor of the electric-thermal-hydrogen process is input into a preset lower-level carbon emission optimization model;

[0118] Based on the time-sharing carbon emission factor of the electricity-heat-hydrogen system and the objective function of minimizing carbon emissions, the electricity, heat and hydrogen loads in the park are adjusted in time sequence.

[0119] The resulting load allocation scheme, which shifts load from high-carbon emission periods to low-carbon emission periods while keeping the total load constant, is used as the load corresponding to the minimum carbon emissions.

[0120] In terms of power supply, the installed capacity of power generation equipment should be rationally planned according to the power load at the minimum carbon emission level to avoid over-construction leading to idle and wasteful equipment. At the same time, it can also prevent the inability to meet demand due to insufficient capacity, which would force the adoption of emergency power generation methods with high carbon emissions, thereby achieving low-carbon planning of the energy system at the source.

[0121] Determining the load corresponding to minimum carbon emissions enables refined energy dispatching and optimized operation. Load is constantly changing, influenced by various factors such as production activities, seasonal changes, and time of day. Real-time monitoring of load changes and prediction of trends are crucial, allowing for timely adjustments to energy supply strategies when the load deviates from the minimum carbon emission point.

[0122] In some embodiments, please refer to Figure 1 The construction process of the preset upper-level economic operation model is as follows:

[0123] Historical data of equipment within the park is acquired, preprocessed, and a cost dataset is obtained, which includes equipment parameters, load data, electricity price information, and renewable energy forecast data.

[0124] A mathematical model is constructed with the objective function of minimizing operating costs. The operating constraints of the equipment and the power supply and demand balance constraints are constructed, and the operating strategies of the equipment in each time period are obtained by solving the problem.

[0125] The indicators corresponding to the operating strategy calculated by the mathematical model are compared with the actual data. When the error value does not exceed the threshold, the mathematical model is used as the upper-level economic operating model.

[0126] Upper-level operational economic model:

[0127] Objective function:

[0128]

[0129] Among these, equipment maintenance costs are incorporated into the economic model, making the model more realistic and comprehensively considering various costs during park operation, thus improving the accuracy of the model's economic assessment. By calculating and analyzing equipment maintenance costs, we can understand the maintenance costs of different equipment, which helps in developing reasonable equipment maintenance plans, extending equipment lifespan, reducing equipment failure rates, and thereby minimizing production interruptions and economic losses caused by equipment failures. The formula is as follows:

[0130]

[0131]

[0132]

[0133]

[0134]

[0135] Clearly defining energy purchase costs helps industrial parks make informed decisions regarding energy procurement. Based on price fluctuations of different energy sources and the park's energy needs, the optimal energy procurement plan can be selected to reduce costs. Analyzing energy purchase costs allows for the assessment of the economics of different energy combinations, guiding the park to optimize its energy structure, improve energy efficiency, and reduce reliance on high-cost energy sources. The formula is as follows:

[0136]

[0137]

[0138] In the formula: This refers to the cost of purchasing natural gas from the higher-level gas network for the industrial park.

[0139] Incorporating the charge-discharge lifespan loss cost of energy storage devices into the model allows for a more accurate assessment of the economics of energy storage systems. This avoids focusing solely on the initial investment cost while neglecting the lifespan loss costs during operation, providing a basis for the rational configuration and operation of energy storage systems. By analyzing the charge-discharge lifespan loss cost of energy storage devices, charging and discharging strategies can be optimized, extending the lifespan of energy storage devices and reducing the total lifespan cost of the energy storage system.

[0140]

[0141] In the formula: , , These are the costs associated with the charging and discharging lifespan of the batteries, thermal storage tanks, and hydrogen storage tanks, respectively.

[0142] Power supply and demand balance constraints ensure a balance between power supply and demand within the park, preventing safety issues such as equipment damage and voltage fluctuations caused by power mismatch, and guaranteeing the stable and reliable operation of the park's power system. By satisfying power supply and demand balance constraints, power resources can be allocated rationally, avoiding waste and improving utilization efficiency.

[0143] The one-to-one energy mapping relationship between the "source and terminal" clearly defines the destination of the total power input in three paths: power flow to electrical loads, electric heating equipment, and the electrolysis hydrogen production system. This makes the energy flow clearer, facilitating the analysis and management of energy conversion and utilization processes within the park, and improving energy efficiency. The formula is as follows:

[0144]

[0145] in,

[0146]

[0147] In the formula: This indicates the total input power of a power source. , , These represent the destinations of three paths: electricity flowing to electrical loads, electric heating equipment, and the electrolysis hydrogen production system.

[0148] The overall electricity-heat-hydrogen energy balance constraint of the system considers the balance constraints of electricity, heat, and hydrogen energy within the park, promoting the coordinated operation of the multi-energy complementary system and achieving optimized allocation and efficient utilization of different energy sources. This ensures the stable operation of the park's integrated energy system, avoids system failures caused by imbalances in the supply and demand of any one energy source, and improves the reliability and security of the park's energy supply. The formula is as follows:

[0149]

[0150] In the formula: Let t be the electrical load of the users in the steel industrial park. Let t be the heat load of users in the steel industrial park at time t; Let t be the hydrogen load of users in the steel industrial park.

[0151] A mathematical model is constructed with the goal of minimizing operating costs, along with constraints on equipment operation and power supply-demand balance. This mathematical model transforms complex energy system operation problems into quantifiable and solvable mathematical problems. Minimizing operating costs as the objective function guides the model to find optimal equipment operation strategies to reduce the overall energy costs of the park. Simultaneously, the equipment operation constraints and power supply-demand balance constraints ensure the model's rationality and feasibility, avoiding problems such as equipment damage or insufficient energy supply due to excessive pursuit of cost reduction. The solved equipment operation strategies for different time periods provide a scientific basis for energy management in the park, enabling equipment to operate under optimal conditions and improving energy utilization efficiency.

[0152] In some embodiments, please refer to Figure 1 The construction process of the preset lower-level carbon emission optimization model is as follows:

[0153] Obtain the carbon emission factors corresponding to electricity, heat, and hydrogen within a specific historical time period;

[0154] A preliminary carbon emission optimization model is constructed by using the minimum carbon emission obtained by multiplying the electricity, heat, and hydrogen loads with their corresponding time-of-use carbon emission factors as the objective function.

[0155] The preliminary carbon emission optimization model is solved by linear programming and nonlinear programming. Based on the objective function, the values ​​of electricity, heat, and hydrogen loads are adjusted at different time periods to obtain the load time sequence allocation scheme that minimizes carbon emissions.

[0156] The lower-level carbon emission optimization model and the upper-level operational economic model work together to form a two-tier optimization system. The upper level optimizes operations from an economic perspective, while the lower level optimizes carbon emissions from an environmental perspective, achieving a balance between economic and environmental goals and making the overall operation of the park more scientific and rational.

[0157] The objective function takes minimizing carbon emission costs as its core objective, taking into account the economic costs of carbon emissions. It combines carbon prices with the carbon emissions from electricity, heat, and hydrogen to form a comprehensive carbon emission cost index, which can more comprehensively and accurately reflect the impact of carbon emissions on the park's economy and provide a more scientific basis for the park to formulate emission reduction strategies.

[0158]

[0159] In the formula, For carbon price, , , These figures represent the carbon emissions from electricity, heat, and hydrogen consumption in the industrial park. The carbon price directly impacts the park's carbon emission costs, thus incentivizing the park to adopt energy-saving and emission-reduction technologies and optimize its energy structure to reduce carbon emissions and improve resource utilization efficiency. Considering the park's carbon emissions from electricity, heat, and hydrogen consumption separately comprehensively covers the main carbon emission sources in the production process. Analyzing the carbon emissions from different energy forms allows us to understand the contribution of various energy sources to carbon emissions, providing guidance for the park to optimize its energy structure, select low-carbon energy sources, and promote the clean and efficient use of energy.

[0160] in,

[0161]

[0162] In the formula: , , These represent the changes in energy load in the industrial park at time period t after the low-carbon response. The dynamic impact of the low-carbon response on energy load allows the model to flexibly adjust the park's energy load at different times based on varying low-carbon needs and actual conditions, thereby improving the park's ability to cope with changes in carbon emissions. By optimizing the changed energy load, the park's electricity, heat, and hydrogen loads can be rationally allocated and scheduled, improving energy efficiency and reducing carbon emissions.

[0163] Constraints:

[0164]

[0165] In addition, the lower-level load transfer must also meet the following constraints to ensure system stability:

[0166]

[0167] In the formula: , , These represent the allowable load transfer proportions when the electric, thermal, and hydrogen systems participate in the carbon response; , , These represent the 0-1 variables of the electricity, heat, and hydrogen systems transitioning to load status during time period t. The constraints ensure system stability during the load transfer process, preventing system failures or operational anomalies due to excessive or unreasonable load transfer, thus guaranteeing the continuity and reliability of production in the industrial park. Considering the allowable load transfer ratios of the electricity, heat, and hydrogen systems participating in the carbon response, as well as the 0-1 variables representing the transition to load status, the optimization model is made more closely reflective of reality, improving the operability and feasibility of the optimization scheme.

[0168] A preliminary carbon emission optimization model is constructed by using the minimum carbon emission obtained by multiplying the electricity, heat, and hydrogen loads with their corresponding time-of-use carbon emission factors as the objective function. This model aims to guide the energy system towards a low-carbon operation with carbon minimization as its core objective. The preliminary carbon emission optimization model is solved using linear and nonlinear programming. Based on the objective function, the values ​​of electricity, heat, and hydrogen loads are adjusted at different time periods to obtain the load time-series allocation scheme that minimizes carbon emissions. The optimal allocation of electricity, heat, and hydrogen loads across different time periods ensures that the overall carbon emissions of the energy system are minimized.

[0169] In some embodiments, please refer to Figure 1 The preset iteration condition is:

[0170] If the change in the objective function between the upper and lower layers remains unchanged or the number of iterations reaches a preset value, the iteration stops.

[0171] In some embodiments, please refer to Figure 1 The formula for the power output scheme of the equipment is as follows:

[0172] ;

[0173] in, The objective function is to minimize operating cost. It is the objective function for minimizing carbon emissions. λ These are weighting coefficients, 0 ≤ λ ≤ 1. It is the output of the equipment;

[0174] in, Satisfy power balance and constraint conditions;

[0175] Power balance: ∑ =D, where D is the total power demand;

[0176] Equipment output limits: ≤ ≤ ,in and These are the minimum and maximum output limits for device i, respectively.

[0177] Minimum operating cost objective function and minimum carbon emission objective function A comprehensive evaluation is conducted using a weighting coefficient λ. The optimization process does not aim for the lowest operating costs or the lowest carbon emissions, but rather seeks a balance between the two to achieve coordinated economic and environmental development. For an energy system, this approach considers both operating costs such as energy purchases and equipment maintenance, while also taking into account the environmental impact of reducing carbon emissions, resulting in more comprehensive and sustainable operation. By adjusting the value of the weighting coefficient λ, the relative importance of operating costs and carbon emissions in the optimization objectives can be flexibly changed according to different actual needs and policy orientations. When policies have high environmental requirements, the value of 1 - λ can be increased to focus more on reducing carbon emissions; when the industrial park faces significant economic pressure, the value of λ can be increased to prioritize reducing operating costs.

[0178] By clearly defining equipment output as an optimization variable, precise control of the operating status of each piece of equipment can be achieved. Through optimization... The value of this value allows for the reasonable adjustment of equipment output power based on the actual needs of the system, thereby improving equipment operating efficiency and performance. In power systems, generator output is adjusted in real time according to load changes to ensure a stable and efficient power supply.

[0179] Power balance constraints ensure that the total output of equipment within a system meets the total power demand, guaranteeing stable system operation. Power imbalance can lead to problems such as voltage fluctuations and frequency instability, affecting equipment operation and even causing system collapse. By satisfying power balance constraints, the system can remain stable under various operating conditions, providing users with a reliable energy supply. Achieving power balance rationally allocates energy resources and avoids energy waste. When the total output of equipment matches the total power demand, energy can be fully utilized, improving energy efficiency and reducing energy costs.

[0180] Equipment output limits take into account the physical characteristics and safe operating range of the equipment, ensuring that the equipment will not be damaged due to exceeding its limits during operation. Each piece of equipment has its designed operating range; exceeding this range may lead to overheating, mechanical failures, and other problems, affecting the equipment's lifespan and safety. By setting output limits, equipment can be protected, the occurrence of equipment failures can be reduced, and maintenance costs and downtime losses can be lowered.

[0181] This invention proposes a system for low-carbon operation balance of electricity, heat, and hydrogen. Please refer to [link / reference]. Figure 2 ,include:

[0182] Cost unit 100 is configured to acquire comprehensive energy parameters of the park and input these parameters into a preset upper-level economic operation model to calculate the minimum operating cost scheme; wherein, the formula of the upper-level economic operation model includes:

[0183] ; For equipment maintenance costs, It is the cost of purchasing energy. This refers to the cost of energy storage device depletion during its charge and discharge lifespan.

[0184] Carbon emission unit 200 is configured to input the minimum cost scheme into a preset carbon emission factor composite model, obtain the carbon emission factor corresponding to the comprehensive energy source through linear and nonlinear calculations, and input the carbon emission factor corresponding to the comprehensive energy source into a preset lower-level carbon emission optimization model to calculate the load corresponding to the minimum carbon emissions; wherein, the formula of the lower-level carbon emission optimization model includes: In the formula, For carbon price, , , These represent the park's electricity consumption, heat consumption, and hydrogen and carbon emissions, respectively.

[0185] The iteration unit 300 is configured to update the upper-level economic operation model based on the load, generate a new minimum operating cost scheme, and repeat the step of inputting the minimum cost scheme into the preset carbon emission factor composite model for iteration until the preset iteration conditions are met, so as to obtain the equipment output scheme corresponding to the minimum cost and minimum carbon emission balance.

[0186] This invention enables precise tracing and allocation of carbon emission responsibility. By introducing a composite model of time-sharing carbon emission factors based on the energy-carbon flow coupling mechanism, it can accurately characterize the carbon emission contributions of different energy paths and conversion equipment, realizing carbon emission mapping from power source to end load. This breaks through the limitations of traditional coarse-grained and static accounting of average carbon factors, providing a refined foundation for carbon responsibility allocation and low-carbon management of multi-energy systems in industrial parks.

[0187] A market-industrial park carbon flow coordination mechanism is constructed to improve the integrity of carbon optimization. By introducing the carbon emission attributes of electricity traded in the external electricity market and forming a unified carbon emission flow model with the equipment inside the industrial park, the problem of underestimation of carbon responsibility caused by the lack of carbon emissions from external electricity purchases in existing studies is solved, and the accuracy of system scheduling strategies and the integrity of carbon optimization boundaries are significantly improved.

[0188] Drive proactive low-carbon response on the load side, promote the transformation of energy consumption behavior, embed time-of-use carbon emission factors into the optimization model, guide the migration of three types of terminal loads (electricity, heat, and hydrogen) from high-carbon periods to low-carbon periods, form a load guidance mechanism with carbon as a signal, realize low-carbon energy consumption adjustment on the demand side under the premise of ensuring unchanged energy demand, and significantly improve the overall carbon emission reduction capacity of the system.

[0189] Balancing system economy and carbon emission reduction to enhance overall operational efficiency, a two-layer optimization scheduling model with source-load coordination is constructed. The upper layer aims to minimize operating costs, while the lower layer aims to minimize carbon emissions, achieving synergistic optimization of economic efficiency and low carbon emissions. Simulation results show that after introducing a time-sharing carbon factor mechanism, the system exhibits significant peak-shaving and carbon-avoidance characteristics, resulting in reduced carbon emissions while maintaining good operational economy, providing an engineering feasible path for the low-carbon transformation of steel industrial parks.

[0190] This invention optimizes the operation strategies of gas turbines, electrolyzers, electric boilers, gas boilers, and electric-thermal-hydrogen energy storage systems within the industrial park through a two-layer optimization scheduling method, achieving synergy between low-carbon economic scheduling and optimal overall operating cost of multi-energy systems in steel industrial parks under a high proportion of renewable energy access.

[0191] Based on the same inventive concept, according to another aspect of the present invention, such as Figure 3 As shown, an embodiment of the present invention also provides a computer device 30, which includes a processor 310 and a memory 320. The memory 320 stores a computer program 321 that can be run on the processor. When the processor 310 executes the program, it performs the steps of the method described above.

[0192] Based on the same inventive concept, according to another aspect of the present invention, such as Figure 4 As shown, embodiments of the present invention also provide a computer-readable storage medium 40, which stores a computer program 410 that, when executed by a processor, performs the methods described above.

[0193] Embodiments of the present invention may also include a corresponding computer device. The computer device includes a memory, at least one processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes any of the methods described above when executing the program.

[0194] The memory, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as program instructions / modules in the embodiments of this application. The processor executes various functional applications and data processing of the device by running the non-volatile software programs, instructions, and modules stored in the memory, thereby implementing the above-described method.

[0195] The memory may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the device. Furthermore, the memory may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In embodiments, the memory may optionally include memory remotely located relative to the processor, which can be connected to the local module via a network. Examples of such networks include, but are not limited to, the Internet, a campus intranet, a local area network, a mobile communication network, and combinations thereof.

[0196] Finally, it should be noted that those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The storage medium for the program can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc. The above computer program embodiments can achieve the same or similar effects as any of the corresponding foregoing method embodiments.

[0197] Those skilled in the art will also understand that the various exemplary logic blocks, modules, circuits, and algorithm steps described in connection with this disclosure can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the functionality of various illustrative components, blocks, modules, circuits, and steps has been generally described. Whether a function is implemented as software or as hardware depends on the specific application and the design constraints imposed on the overall system. Those skilled in the art can implement the functionality in various ways for each specific application, but such implementation decisions should not be construed as departing from the scope of the embodiments disclosed herein.

[0198] The above are exemplary embodiments disclosed in this invention. However, it should be noted that various changes and modifications can be made without departing from the scope of the embodiments of this invention as defined by the claims. The functions, steps, and / or actions of the methods according to the disclosed embodiments described herein do not need to be performed in any particular order. The sequence numbers of the disclosed embodiments of this invention are merely for descriptive purposes and do not represent the superiority or inferiority of the embodiments. Furthermore, although the elements disclosed in the embodiments of this invention may be described or claimed individually, they may be understood as multiple unless explicitly limited to a singular number.

[0199] It should be understood that, as used herein, the singular form “a” is intended to include the plural form as well, unless the context clearly supports an exception. It should also be understood that, as used herein, “and / or” refers to any and all possible combinations of one or more of the associated listed items.

[0200] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the invention (including the claims) is limited to these examples. Within the framework of the invention, technical features of the above embodiments or different embodiments can be combined, and many other variations of different aspects of the invention exist, which are not provided in the details for the sake of brevity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the protection scope of the invention.

Claims

1. A method for achieving low-carbon operation balance between electricity, heat, and hydrogen, characterized in that, include: The comprehensive energy parameters of the park are obtained and input into a preset upper-level economic operation model to calculate the minimum operating cost scheme; wherein, the formula of the upper-level economic operation model includes: ; For equipment maintenance costs, It is the cost of purchasing energy. This refers to the cost of energy storage device depletion during its charge and discharge lifespan. The minimum operating cost scheme is input into a preset carbon emission factor composite model. The carbon emission factor corresponding to the integrated energy source is obtained through linear and nonlinear calculations. Specifically, the carbon emissions at the integrated energy input during operation are obtained based on the minimum operating cost scheme and the carbon flow conservation law. The integrated energy source includes electricity, heat, and hydrogen. Carbon emission transfer during the charging and discharging of electricity, heat, and hydrogen energy storage is calculated. For electricity and hydrogen energy storage, linear carbon emission transfer and input are calculated during charging and discharging. For heat energy storage, linear energy and nonlinear heat loss energy are calculated during charging and discharging. The input heat energy and heat source carbon emission factor during the charging phase are obtained, and the effectively stored linear energy and carbon emissions during the charging phase are calculated. A heat conversion efficiency curve is fitted. The nonlinear energy loss and heat release power curve during the charging phase are calculated using the input heat energy and effectively stored linear energy. The effective heat release energy during the heat release phase is calculated by integrating the heat release power curve and combining it with the heat conversion efficiency curve. The nonlinear energy loss during the heat release phase is calculated based on the effectively stored linear energy and the effective heat release energy during the heat release phase. Linear heat loss energy; the effectively stored linear energy, the nonlinear energy loss during the charging phase, and the nonlinear heat loss energy during the heat release phase are taken as the total carbon emissions of thermal energy storage; an energy-carbon flow coupling relationship between electricity, heat, and hydrogen is established based on carbon emission transfer and the carbon emissions of the integrated energy input during the operating period; the carbon emissions of the integrated energy input during the operating period are allocated based on the energy-carbon flow coupling relationship between electricity, heat, and hydrogen to obtain the time-sharing carbon emission factor of electricity-heat-hydrogen; the carbon emission factor corresponding to the integrated energy is input into a preset lower-level carbon emission optimization model to calculate the load corresponding to the minimum carbon emissions; wherein, the time-sharing carbon emission factor of electricity-heat-hydrogen is input into the preset lower-level carbon emission optimization model; based on the time-sharing carbon emission factor of electricity-heat-hydrogen and the objective function of minimizing carbon emissions, the electricity, heat, and hydrogen loads in the park are adjusted in time sequence; a load allocation scheme that migrates the load from high-carbon emission periods to low-carbon emission periods when the total load remains unchanged is obtained as the load corresponding to the minimum carbon emissions; wherein, the formula of the lower-level carbon emission optimization model includes: In the formula, For carbon price, , , These represent the park's electricity consumption, heat consumption, and hydrogen and carbon emissions, respectively. Based on the load update upper-level economic operation model, a new minimum operating cost scheme is generated. The process of repeatedly inputting the minimum operating cost scheme into the preset carbon emission factor composite model is iterated until the preset iteration conditions are met, thereby obtaining the equipment output scheme corresponding to the minimum cost and minimum carbon emission balance.

2. The method for achieving low-carbon operation balance between electricity, heat, and hydrogen according to claim 1, characterized in that, The process of constructing the preset upper-level economic operation model is as follows: Historical data of equipment within the park is acquired, preprocessed, and a cost dataset is obtained, which includes equipment parameters, load data, electricity price information, and renewable energy forecast data. A mathematical model is constructed with the objective function of minimizing operating cost. The operating constraints of the equipment and the power supply and demand balance constraints are constructed, and the operating strategies of the equipment in each operating segment are obtained by solving the problem. The indicators corresponding to the operating strategy calculated by the mathematical model are compared with the actual data. When the error value does not exceed the threshold, the mathematical model is used as the upper-level economic operating model.

3. The method for achieving low-carbon operation balance between electricity, heat, and hydrogen according to claim 1, characterized in that, The construction process of the preset lower-level carbon emission optimization model is as follows: Obtain the carbon emission factors corresponding to electricity, heat, and hydrogen within a specific historical time period; A preliminary carbon emission optimization model is constructed by using the minimum carbon emission obtained by multiplying the electricity, heat, and hydrogen loads with their corresponding time-of-use carbon emission factors as the objective function. The preliminary carbon emission optimization model is solved by linear programming and nonlinear programming. Based on the objective function, the values ​​of electricity, heat, and hydrogen loads are adjusted at different time periods to obtain the load time sequence allocation scheme that minimizes carbon emissions.

4. The method for achieving low-carbon operation balance between electricity, heat, and hydrogen according to claim 1, characterized in that, The formula for the equipment output scheme is as follows: ； in, The objective function is to minimize operating cost. It is the objective function for minimizing carbon emissions. λ These are weighting coefficients, 0 ≤ λ ≤ 1. It is the output of the equipment; in, Satisfy power balance and constraint conditions; Power balance: ∑ =D, where D is the total power demand; Equipment output limits: ≤ ≤ ,in and These are the minimum and maximum output limits for device i, respectively.

5. A system for low-carbon operation balance of electricity, heat, and hydrogen, characterized in that, include: The cost unit is configured to acquire the comprehensive energy parameters of the park and input these parameters into a preset upper-level economic operation model to calculate the minimum operating cost scheme; wherein, the formula of the upper-level economic operation model includes: ; For equipment maintenance costs, It is the cost of purchasing energy. This refers to the cost of energy storage device depletion during its charge and discharge lifespan. A carbon emission unit is configured to input the minimum operating cost scheme into a preset carbon emission factor composite model, and obtain the carbon emission factor corresponding to the integrated energy through linear and nonlinear calculations, respectively. Specifically, it calculates the carbon emissions at the integrated energy input during operation based on the minimum operating cost scheme and the carbon flow conservation law, where the integrated energy includes electricity, heat, and hydrogen. It calculates the carbon emission transfer generated during the charging and discharging of electricity, heat, and hydrogen energy storage, where electricity and hydrogen energy storage calculate the linear carbon emission transfer amount and the charging amount during charging and discharging; and heat energy storage calculates linear energy and nonlinear heat loss energy during charging and discharging, where the input heat energy and heat source carbon emission factor during the charging stage are obtained, and the effectively stored linear energy and carbon emissions during the charging stage are calculated. It fits the heat energy conversion efficiency curve, calculates the nonlinear energy loss and heat release power curve during the charging stage using the input heat energy and effectively stored linear energy during the charging stage, integrates the heat release power curve with the heat energy conversion efficiency curve to calculate the effective heat release energy during the heat release stage, and calculates the carbon emission based on the effectively stored linear energy and the effective heat release energy during the heat release stage. The nonlinear heat loss energy during the exothermic phase; the effective stored linear energy, the nonlinear energy loss energy during the charging phase, and the nonlinear heat loss energy during the exothermic phase are taken as the total carbon emissions of thermal energy storage; an energy-carbon flow coupling relationship between electricity, heat, and hydrogen is established based on carbon emission transfer and the carbon emissions of the integrated energy input during the operating period; the carbon emissions of the integrated energy input during the operating period are allocated based on the energy-carbon flow coupling relationship between electricity, heat, and hydrogen to obtain the time-sharing carbon emission factor of electricity-heat-hydrogen; the carbon emission factor corresponding to the integrated energy is input into a preset lower-level carbon emission optimization model to calculate the load corresponding to the minimum carbon emissions; wherein, the time-sharing carbon emission factor of electricity-heat-hydrogen is input into the preset lower-level carbon emission optimization model; based on the time-sharing carbon emission factor of electricity-heat-hydrogen and the objective function of minimizing carbon emissions, the electricity, heat, and hydrogen loads in the park are adjusted in time sequence; a load allocation scheme that migrates the load from high carbon emission periods to low carbon emission periods when the total load remains unchanged is obtained as the load corresponding to the minimum carbon emissions; wherein, the formula of the lower-level carbon emission optimization model includes: In the formula, For carbon price, , , These represent the park's electricity consumption, heat consumption, and hydrogen and carbon emissions, respectively. The iteration unit is configured to update the upper-level economic operation model based on the load, generate a new minimum operating cost scheme, and repeat the step of inputting the minimum operating cost scheme into the preset carbon emission factor composite model for iteration until the preset iteration conditions are met, so as to obtain the equipment output scheme corresponding to the minimum cost and minimum carbon emission balance.

6. A computer device, comprising: At least one processor; And a memory storing a computer program executable on the processor, characterized in that, when the processor executes the program, it performs the steps of a method for an electro-thermal-hydrogen low-carbon operating balance as described in any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it performs the steps of the method for balancing an electro-thermal-hydrogen low-carbon operation as described in any one of claims 1 to 4.

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