Low-carbon comprehensive energy system real-time optimization operation method based on hydrogen byproduct utilization

Abstract

The invention discloses a low-carbon comprehensive energy system real-time optimization operation method based on hydrogen byproduct utilization, and belongs to the technical field of low-carbon energy system optimization operation. Comprising the following steps: performing dynamic interconnection and optimization on multiple energy sources of electricity, hydrogen and gas by utilizing a low-carbon technology; hydrogen and carbon dioxide resources are used for synthesizing high-value-added hydrogen byproducts of natural gas, ammonia, urea and methanol; establishing an energy storage system cooperative regulation mechanism, and bidirectionally regulating electric power and heating power; internal energy of the system is converted, and the value is maximized; and establishing an MPC optimization scheduling model, dynamically correcting a control variable and an operation strategy in a rolling time domain, formulating a real-time optimization scheduling mechanism of the IES until a next time period, and carrying out prediction again according to the latest operation state and optimizing the control strategy. According to the method, the economic benefit and the emission reduction effect are both considered, the problem that a traditional day-ahead optimization method is difficult to deal with real-time uncertainty is solved, and stable and sustainable operation is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of low-carbon energy system optimal operation, and particularly relates to a real-time optimal operation method for a low-carbon integrated energy system based on hydrogen by-product utilization. BACKGROUND

[0002] In recent years, environmental problems caused by fossil energy consumption have become increasingly prominent, and low-carbon energy structure transformation has become an important direction in the energy field. Hydrogen energy, as a highly efficient, clean and renewable secondary energy, has broad application prospects in the fields of electricity, heat and industry. At the same time, an integrated energy system (IES) can achieve multi-energy complementation and energy cascade utilization through the coupling and coordinated operation of electricity, heat, gas, hydrogen and other energies, thereby significantly improving the overall energy efficiency of the system and reducing carbon emissions. Therefore, a low-carbon integrated energy system based on hydrogen energy has gradually become a key direction of research and engineering practice. In particular, in the energy conversion and storage link, hydrogen production, hydrogen storage and hydrogen by-product recycling not only improve the flexibility and stability of system operation, but also achieve energy balance and carbon emission reduction optimization when renewable energy output fluctuates greatly. However, fully considering the dynamic characteristics and real-time utilization of hydrogen by-products in the operation of the integrated energy system brings challenges such as increased system modeling complexity, enhanced energy flow coupling and improved real-time requirements for dispatching optimization, thereby putting forward higher requirements for the coordinated operation and optimal control of the system.

[0003] In view of the problems of enhanced energy flow coupling, variable operation state and intensified uncertainty in the dynamic utilization process of hydrogen by-products in a low-carbon integrated energy system, existing optimal operation strategies usually use robust optimization, stochastic programming and chance constraint methods to improve the operation stability of the system in uncertain environments. However, the above methods are mostly based on day-ahead information to make operation decisions, and are difficult to fully reflect the time-varying characteristics of the system caused by fluctuations in hydrogen by-product production, changes in renewable energy output and dynamic responses of loads, and their performance is easily affected by prediction errors and real-time disturbances, which may cause the energy management decision to deviate from the optimal state. Model predictive control (MPC), as a dynamic control method based on the rolling optimization idea, can utilize the latest state information for prediction and optimization at each time, thereby realizing real-time coordinated operation of the low-carbon integrated energy system. This method can effectively cope with the complex coupling of electricity-hydrogen-heat multi-energy flow, dynamically manage the recycling and reuse process of hydrogen by-products, and improve the energy efficiency and operation economy of the system.

[0004] Therefore, a low-carbon comprehensive energy system real-time optimization operation method based on hydrogen by-product utilization is needed, which can ensure the safety, stability and economy of system operation under the conditions of dynamic changes of hydrogen by-product yield and random changes of renewable energy, and realize the optimization control of low-carbon and efficient comprehensive energy system. SUMMARY

[0005] The purpose of the present application is to provide a low-carbon comprehensive energy system real-time optimization operation method based on hydrogen by-product utilization, comprising the following steps:

[0006] Dynamic interconnection and optimization of multi-energy of electricity, hydrogen and gas are carried out by using low-carbon technology;

[0007] An industrial utilization mechanism of hydrogen energy and carbon resources coupling is established, and hydrogen and carbon dioxide resources are used to synthesize high-value hydrogen by-products such as natural gas, ammonia, urea and methanol;

[0008] A storage system collaborative regulation mechanism is established to bidirectionally regulate electricity and heat;

[0009] A cyclic hydrogen economic operation model is established based on low-carbon technology, hydrogen-carbon recycling and storage system collaborative regulation mechanism to convert the internal energy of the system and maximize the value;

[0010] An MPC optimization scheduling model is established to dynamically correct control variables and operation strategies in a rolling time domain, develop a real-time optimization scheduling mechanism of IES, and until the next time period, re-predict and optimize the control strategy according to the latest operation state.

[0011] Further, the low-carbon technology includes water electrolysis hydrogen production, carbon capture and storage, electric gas conversion and gas turbine.

[0012] Further, the MPC optimization scheduling model comprises:

[0013] Objective function:

[0014] ;

[0015] ;

[0016] ;

[0017] wherein, and represent the income and cost of IES at time; , , and represent the electric power of the electric load, the hydrogen load demand, the non-TPP natural gas demand and the ammonia demand, respectively; and These represent the production of urea and methanol, respectively. Indicates the gas flow rate supplied by liquefied natural gas; This indicates the amount of nitrogen consumed during ammonia production. This indicates the equipment's net CO2 emissions; , , , , , , , and These represent the prices of electricity, hydrogen, natural gas, urea, ammonia, methanol, liquefied natural gas, and nitrogen, respectively. Emissions penalty price; and They represent the first The operating costs incurred by a thermal power unit during startup and shutdown; This represents the degradation cost of a battery energy storage system; and These represent the power purchased and sold, respectively. Represents a set of thermal power units; This represents the time-domain set of system running pairs;

[0018] Constraints:

[0019] Power balance constraints

[0020] ;

[0021] ;

[0022] ;

[0023] in, and These represent the electrical power generated by PV and the electrical power generated by WT, respectively. Indicates the first The electrical power generated by the thermal power unit; and These represent the electrical power output of BESS in charging and discharging states, respectively. and These represent the electrical power generated by the hydrogen power generation equipment and the electrical power consumed by the electro-hydrogen production equipment, respectively. , , and These represent the electrical power consumption during the production processes of CCUS, methanol, urea, and ammonia, respectively. an upper limit for the transmission of electric power between the CHEM and the main grid;

[0024] material balance constraints

[0025] ;

[0026] ;

[0027] ;

[0028] wherein, and respectively represent the amount of hydrogen consumed by the hydrogen power generation device and the amount of hydrogen produced by the hydrogen production device; and respectively represent the amount of hydrogen transferred by the HSS in the hydrogen charging and hydrogen discharging states; and respectively represent the amount of hydrogen required by the system, the amount of hydrogen consumed in the conversion of hydrogen into natural gas, the amount of hydrogen used in the ammonia synthesis process, and the amount of hydrogen used in the methane synthesis process; and respectively represent the amount of natural gas generated in the conversion of hydrogen into natural gas, the amount of natural gas supplied as liquefied natural gas, the amount of natural gas required by non-TPPs, and the amount of natural gas required by TPPs; and respectively represent the amount of ammonia used in the ammonia production process and the amount of ammonia used in the urea production process;

[0029] device constraints:

[0030] hydrogen-electricity interconnection device constraints

[0031] ;

[0032] ;

[0033] ;

[0034] ;

[0035] ;

[0036] wherein, and respectively represent the energy conversion efficiency of the hydrogen production device and the hydrogen power generation device; represents the compression factor of hydrogen; and respectively represent the high and low heating values of hydrogen.​​​​ and for limiting the upper limit of hydrogen transmission for hydrogen production and hydrogen power generation equipment, and is a binary decision variable for avoiding the simultaneous occurrence of hydrogen production and hydrogen power generation processes;

[0037] Carbon capture and storage device constraints:

[0038] ;

[0039] ;

[0040] ;

[0041] ;

[0042] ;

[0043] ;

[0044] ;

[0045] ;

[0046] ;

[0047] wherein, CO2 emissions for characterizing CCUS; and respectively represent the amount of CO2 absorbed and released by the CCUS device; , and respectively correspond to the consumption of CO2 in the methanol, urea and methanation production processes; and respectively represent the carbon capture efficiency of the CCUS device and its electrical power consumption coefficient; and respectively represent the CO2 emission rate of the power grid and the TPPS; for representing the operating state of the carbon storage system; and respectively represent the lower and upper limits of the storage capacity of the carbon storage system; and respectively serve to limit the upper limit values of CO2 absorption and release by the CCUS device during operation;

[0048] Ammonia production process constraints:

[0049] ;

[0050] ;

[0051] ;

[0052] wherein, and are process coefficients of the ammonia synthesis process; represents the electric power consumption coefficient of the ammonia synthesis process;

[0053] Methanol production constraints

[0054] ;

[0055] ;

[0056] ;

[0057] wherein, and are process coefficients of the methanol synthesis process; represents the electric power consumption coefficient of the methanol synthesis process;

[0058] Urea production constraints

[0059] ;

[0060] ;

[0061] ;

[0062] wherein, and are process coefficients of the urea synthesis process; represents the electric power consumption coefficient of the urea synthesis process;

[0063] Methanation reaction constraints

[0064] ;

[0065] ;

[0066] ;

[0067] wherein, is used to characterize the volumetric conversion relationship between hydrogen and natural gas; is used to define an upper limit to the natural gas production in the methanation process; represents the process coefficient of the natural gas synthesis process;

[0068] Thermal power plant constraints

[0069] ;

[0070] ;

[0071] ;

[0072] ;

[0073] ;

[0074] ;

[0075] ;

[0076] ;

[0077] ;

[0078] ;

[0079] ;

[0080] ;

[0081] ;

[0082] ;

[0083] ;

[0084] ;

[0085] in, This indicates the fuel consumption of TPPs; , and The coefficients represent the heat rate function of TPPs; and Indicates the first The lower and upper limits of the electrical power output of the TPP; A binary variable representing the state of TPPs; and To avoid simultaneous start-up and shutdown of TPPs, binary decision variables are used; the power generation range of each unit is divided into... Section, No. The unit heat consumption coefficient of the section is The corresponding power is ; and They represent the first Unit start-up and shut-down operation cost of the TPPT; and denote the first minimum start-up and shut-down time of the TPPT; and denote the first maximum ramp-up and ramp-down rate of the TPPT; denotes the total heating value of natural gas;

[0086] Energy storage system constraints

[0087] ;

[0088] ;

[0089] ;

[0090] ;

[0091] ;

[0092] ;

[0093] ;

[0094] ;

[0095] ;

[0096] ;

[0097] ;

[0098] ;

[0099] wherein, and denote the state of charge of the BESS and the state of hydrogen storage of the HSS in CHEM, respectively; and denote the conversion efficiency of the BESS device and the unit electrical power decay cost coefficient; and are binary decision variables for avoiding simultaneous charging and discharging processes of the BESS; and are used to limit the upper values of the charging and discharging power of the BESS device during operation, respectively; and denote the lower and upper limits of the BESS battery capacity, respectively; and a binary decision variable for avoiding simultaneous hydrogen charging and discharging of the HSS; and respectively represent the upper limit of the hydrogen charging and discharging rate of the HSS device during operation; and respectively represent the lower limit and upper limit of the hydrogen storage capacity of the HSS.

[0100] The beneficial effects of the present application are:

[0101] 1、The present application can realize dynamic coordinated control of electrolytic hydrogen production, carbon capture and utilization, methanation and multi-energy storage units in the system by introducing the MPC rolling optimization framework, effectively improving the adaptability of the system to renewable energy fluctuations and uncertainties, and ensuring the safe operation of the system.

[0102] 2、The present application can realize the collaborative conversion of hydrogen and captured CO2 by establishing an "electricity-hydrogen-gas" deep coupling carbon cycle mechanism, producing high value-added products such as methanol, ammonia, urea and synthetic natural gas, promoting carbon resource closed-loop utilization, and significantly improving the low carbon and economic efficiency of the system.

[0103] 3、The present application utilizes the collaborative operation of hydrogen energy storage system (HSS) and electrochemical energy storage system (BESS), improves the energy time distribution efficiency, and enables the system to store energy during low load period and release energy during peak period, thereby enhancing the system operation flexibility and energy utilization efficiency.

[0104] 4、The present application takes into account economic benefits and emission reduction effects under the premise of ensuring system operation constraints, overcomes the problem that traditional day-ahead optimization methods are difficult to cope with real-time uncertainties, and realizes stable and sustainable operation. BRIEF DESCRIPTION OF DRAWINGS

[0105] Figure 1 The flowchart of the present application is a real-time optimization operation method for a low-carbon comprehensive energy system based on hydrogen by-product utilization.

[0106] Figure 2 The overall structure framework diagram of the low-carbon comprehensive energy system based on hydrogen by-product utilization.

[0107] Figure 3 The MPC real-time optimization scheduling flowchart of the low-carbon comprehensive energy system.

[0108] Figure 4 (a) (b) (c) are the optimal energy distribution results of electricity, hydrogen energy and natural gas in the comprehensive energy system.

[0109] Figure 5 The carbon capture, utilization and storage (CCUS) collaborative scheduling result diagram.

[0110] Figure 6 A space distribution and utilization path result map for capturing carbon dioxide.

[0111] Figure 7 A stacked area chart for high value-added product output based on hydrogen by-product conversion. DETAILED DESCRIPTION

[0112] The present application provides a low-carbon comprehensive energy system real-time optimization operation method based on hydrogen by-product utilization, which is further described below in conjunction with the drawings and specific examples.

[0113] Figure 1 A flow chart of the low-carbon comprehensive energy system real-time optimization operation method based on hydrogen by-product utilization of the present application. Figure 2 The overall structure framework diagram of the low-carbon comprehensive energy system based on hydrogen by-product utilization of the present application integrates water electrolysis hydrogen production, electric gas conversion, carbon capture and storage, and hydrogen energy utilization, etc. multiple low-carbon technologies, builds a multi-energy collaborative operation system with hydrogen energy as the core, and realizes efficient interconnection and dynamic balance of multi-energy flow such as electricity, heat, gas, and hydrogen. Figure 3 The MPC real-time optimization scheduling flow chart of the low-carbon comprehensive energy system of the present application is based on MPC principle, dynamically predicts the system state and external disturbance in the rolling time domain, and establishes a short-term optimization model of the multi-energy system. The MPC controller solves the optimal operation strategy according to the prediction result, and updates the optimization boundary and constraint condition at each time to realize dynamic correction and continuous optimization of system operation. Specifically, the following steps are included:

[0114] Step 1: Based on water electrolysis hydrogen production, carbon capture and storage, electric gas conversion, and gas turbine, etc. low-carbon technologies, realize dynamic interconnection and optimal operation of electricity, hydrogen, and gas multi-energy;

[0115] (1) Hydrogen-electricity interconnection system

[0116] When there is power surplus in the comprehensive energy system, the system converts the surplus electricity into hydrogen energy through the water electrolysis hydrogen production device, realizes the space-time transfer and reuse of energy. The hydrogen produced can be stored through the hydrogen storage device for transportation, industrial raw material supply, and fuel power generation, etc. multiple purposes, thereby improving the energy utilization rate and economic benefit of the system. The power system and the hydrogen energy system are connected through the energy flow channel, and their energy exchange relationship can be defined by equations (1)~(5). This relationship includes the energy conversion constraints of the water electrolysis hydrogen production process, the energy release constraints of the fuel cell power generation process, the equipment output power range limitations, and the energy flow control mechanism.

[0117] wherein the electrolysis hydrogen generation device absorbs electric energy to generate hydrogen when the electric power is abundant; and the fuel cell device converts the stored hydrogen into electric energy when the electric power demand increases, so as to realize the energy complementation within the system. By setting the power upper and lower limits and the one-way energy flow constraint, the energy transmission between the power system and the hydrogen energy system is ensured to be safe, stable and unique, thereby effectively supporting the flexible scheduling and low-carbon operation of the integrated energy system.

[0118] (1)

[0119] (2)

[0120] (3)

[0121] (4)

[0122] (5)

[0123] wherein, and respectively represent the electric power generated by the hydrogen power generation device and the electric power consumed by the hydrogen production device; and respectively represent the hydrogen consumption of the hydrogen power generation device and the hydrogen output of the hydrogen production device; and respectively represent the energy conversion efficiencies of the hydrogen production device and the hydrogen power generation device; represents the compression factor of hydrogen; and respectively represent the high heat value and the low heat value of hydrogen; and are used to limit the upper limit of the hydrogen transmission amount of the hydrogen production device and the hydrogen power generation device, and are binary decision variables used to avoid the simultaneous occurrence of the hydrogen production and the hydrogen power generation processes.

[0124] (2) Methanation reaction

[0125] Based on the modeling results of the aforementioned electricity-hydrogen interconnection system, a methanation process is introduced to realize further energy conversion from electric energy to natural gas. This process realizes the conversion of hydrogen and carbon dioxide through the Sabatier reaction (also known as the CO2 hydrogenation reaction). Specifically, hydrogen and carbon dioxide are mixed in the reactor, and under the action of a metal nickel catalyst, a chemical reaction occurs under certain temperature and pressure conditions to generate methane and water, thereby realizing energy conversion from electric energy to renewable fuel. This process not only realizes efficient utilization of hydrogen energy, but also fully utilizes the CO2 resources captured in the CCUS device, promoting carbon recycling and low-carbon operation of the system.

[0126] Equation (6) represents the hydrogen stored in the HSS, which can be used as the input gas source for the methanation reaction. The operating range of the methanation process is controlled by the energy constraints and equipment capacity limitations of the system, which is defined by Equation (7). The consumption of CO2 is modeled and calculated according to the reaction ratio relationship in Equation (8). A rolling scheduling strategy is used to optimize the control of the system, and relevant research results are combined to ensure the feasibility and real-time performance of the model by not setting a ramp rate constraint for the methanation unit in the model construction.

[0127] Equation (6)

[0128] Equation (7)

[0129] Equation (8)

[0130] wherein, represents the consumption of hydrogen in the process of converting into natural gas; is used to represent the volume conversion relationship between hydrogen and natural gas; represents the amount of natural gas generated in the process of converting hydrogen into natural gas; is used to limit the upper limit of the natural gas production in the methanation process; represents the process coefficient of the natural gas synthesis process.

[0131] (3) Carbon capture and storage technology

[0132] The carbon capture process is used to separate and capture carbon dioxide emissions from various emission sources such as power generation devices, industrial facilities, and transportation, to achieve greenhouse gas emission reduction and carbon resource recycling. Currently, carbon capture, utilization and storage (CCUS) technology has formed various types, among which post-combustion carbon capture technology is widely used due to its mature process and wide application range. The present invention uses post-combustion carbon capture to process carbon emissions in the integrated energy system. Equations (9) to (17) describe the operating mechanism of the CCUS process and mathematically model the relationship between the system's carbon dioxide emissions, capture amount, and energy consumption. Specifically, the system's carbon emissions are determined by the energy conversion and fuel consumption characteristics, the capture capacity of the CCUS device is limited by its equipment capacity and operating efficiency, and the energy consumption of the capture process is determined by the power characteristics of the device. The part of carbon dioxide that is not captured is defined as the residual emission amount of the system to reflect the constraint characteristics of the CCUS efficiency. The captured carbon dioxide can be introduced into the downstream industrial link as raw material for processes such as methanol synthesis, urea production, and methanation, achieving carbon resource recycling and low-carbon operation of the overall system.

[0133] During operation, CCUS must meet corresponding constraints to ensure the safety of its storage and release process and the overall feasibility of the system. Specifically, the carbon dioxide storage capacity of the CCS unit at each moment is limited by equation (14) and changes dynamically according to the system's operating status; its storage capacity is limited by the equipment design parameters and must meet the upper and lower limits of the preset capacity in equation (15); the carbon dioxide charging rate and release rate of the carbon capture device during the operating cycle are both limited by the maximum allowable values ​​in equations (16) and (17) to prevent the equipment from overloading. In the process of optimizing the scheduling, in order to enhance the system's flexibility and carbon capture capability, equal constraints are not imposed on the storage status of the CCUS storage unit at the beginning and end of the scheduling cycle, so that it can autonomously adjust the storage level according to the system's operating requirements. Carbon dioxide that is not resealed in the storage unit can be transported to downstream devices for resource utilization, but this part is not within the control scope of this embodiment.

[0134] ; (9)

[0135] ; (10)

[0136] ; (11)

[0137] ;(12)

[0138] ; (13)

[0139] ;(14)

[0140] ; (15)

[0141] ; (16)

[0142] ; (17)

[0143] in, and Used to characterize the CO2 emissions and net CO2 emissions of CCUS; and These represent the amounts of CO2 absorbed and released by the CCUS device, respectively. , and They represent the first The electrical power generated by the thermal power units, the power purchased, and the electrical power consumption of the CCUS equipment; , and respectively represent the CO2consumption of the methanol, urea and methanation production processes; and respectively represent the carbon capture efficiency of the CCUS device and its electrical power consumption coefficient; and respectively represent the CO2emission rates of the power grid and the TPPS; for representing the operating state of the carbon sequestration system; and respectively represent the lower and upper limits of the storage capacity of the carbon sequestration system; and respectively represent the upper limits of CO2absorption and release of the CCUS device during operation.

[0144] (4) Thermal power plant

[0145] To ensure the safe and economic operation of the power system, the operating characteristics and scheduling constraints of the gas turbine unit (Thermal Power Plant, TPP) are modeled. The modeling process is described by equations (18) to (33). The power output of the gas turbine unit needs to meet certain operating range limits to ensure stable operation within the rated capacity range. To represent the nonlinear relationship between fuel consumption and output power of the unit, a heat rate function is introduced, and a piecewise linearization method is used to approximate it mathematically, thereby improving the calculation efficiency and solution accuracy of the optimization model. The fixed cost and start-up cost generated during the start-up and shutdown of the unit are modeled respectively to reflect the economic impact of the change in the operating state of the unit. To fully characterize the operating rules of the gas turbine unit within the scheduling period, an operating constraint system is established, including start-up and shutdown time constraints, minimum start-up and shutdown time constraints, ramp-up and ramp-down rate limit constraints, and start-up and shutdown logic constraints.

[0146] It should be noted that the methanation process in this embodiment can convert a certain proportion of hydrogen and carbon dioxide resources into natural gas, thereby offsetting the fuel consumption of the gas turbine unit to some extent and improving the overall energy utilization efficiency of the system. The fuel demand of the gas turbine unit is determined based on its heat rate characteristics and can be quantitatively calculated by establishing a fuel consumption model. The natural gas system is responsible for providing the required fuel for the gas turbine unit, achieving dynamic matching of the fuel supply and energy conversion process, and thus ensuring the stability and economy of the integrated energy system under different operating conditions.

[0147] In addition, the amount of fuel consumed by the gas turbine unit during operation will directly affect the fuel cost and carbon emission level of the system. By constructing a fuel cost function, this part is comprehensively modeled to achieve the low-carbon and economic optimization goals of the power system operation.

[0148] ; (18)

[0149] ; (19)

[0150] ; (20)

[0151] ; (twenty one)

[0152] ; (twenty two)

[0153] ; (twenty three)

[0154] ; (twenty four)

[0155] ; (25)

[0156] ; (26)

[0157] ;(27)

[0158] ; (28)

[0159] ; (29)

[0160] ; (30)

[0161] ; (31)

[0162] ; (32)

[0163] ; (33)

[0164] in, This indicates the fuel consumption of TPPs; , and The coefficients represent the heat rate function of TPPs; and Indicates the first The lower and upper limits of the electrical power output of the TPP; A binary variable representing the state of TPPs; and To avoid simultaneous start-up and shutdown of TPPs, binary decision variables are used; the power generation range of each unit is divided into... Section, No. The unit heat consumption coefficient of the section is The corresponding power is ; and represent the unit start-up and shut-down operation cost of the thTPP, respectively; and represent the minimum start-up and shut-down time of the thTPP, respectively; and represent the maximum ramp-up and ramp-down rate of the thTPP, respectively; represents the total heating value of natural gas.

[0165] Step 2: Establish an industrial utilization mechanism for coupling hydrogen energy and carbon resources, and use the obtained hydrogen and carbon dioxide resources to synthesize natural gas, ammonia, urea, methanol and other high-value hydrogen by-products;

[0166] (1) Ammonia production

[0167] The preparation of ammonia is realized by Haber-Bosch process, which is a chemical reaction between nitrogen and hydrogen under the action of iron-based catalyst at high temperature and high pressure to generate ammonia. In order to model the ammonia synthesis process, a corresponding mathematical description model is established to describe the quantitative relationship between hydrogen consumption and ammonia yield, determine the nitrogen raw material demand, and calculate the energy consumption required to complete the reaction. The generated ammonia can be directly used as a chemical raw material, or as an input material for the urea production process, realizing efficient conversion and comprehensive utilization of hydrogen resources within the system.

[0168] ; (34)

[0169] ; (35)

[0170] ; (36)

[0171] wherein, and represent the ammonia gas consumption and hydrogen gas consumption in the ammonia production process, respectively, and are the process coefficients of the ammonia synthesis process; represents the electric power consumption coefficient of the ammonia synthesis process.

[0172] (2) Methanol production

[0173] The synthesis process of methanol is realized by CO2 hydrogenation reaction (also known as CO2 methanation). The process converts CO2 and hydrogen into methanol in a high-temperature and high-pressure reactor under the action of copper, zinc or iron-based catalysts. To establish the energy and material balance relationship of the methanol synthesis process, a mathematical model is constructed, and equations (37) to (39) are used to describe the methanol production, the required CO2 raw material quantity and the reaction energy consumption.

[0174] wherein the power consumption ratio corresponding to the byproduct yield is obtained by experimental calibration, and is used to describe the energy consumption characteristics of the methanol production process. Through the model, the collaborative optimization scheduling of the methanol synthesis unit and the electrolytic hydrogen production, carbon capture and energy storage units in the system can be realized, thereby improving the overall carbon resource utilization efficiency and energy conversion efficiency of the system.

[0175] ; (37)

[0176] ; (38)

[0177] ; (39)

[0178] wherein, and represent the yield of urea and the hydrogen consumption in the methane synthesis process, respectively; represents the CO2 consumption in the methanol production process; represents the electric power consumption in the methanol production process; and are the process coefficients of the methanol synthesis process; represents the electric power consumption coefficient of the methanol synthesis process.

[0179] (3) Urea production

[0180] The preparation process of urea is realized by high-temperature and high-pressure catalytic reaction. Specifically, the ammonia synthesized in the early stage is placed under high-temperature and high-pressure conditions, and reacts with carbon dioxide to generate urea under the action of metal oxide catalyst. In the reaction process, ammonia and CO2 first react in the high-pressure reactor to generate ammonium carbamate (NH2COONH4), and then generate urea through dehydration reaction. The generated urea solution is cooled, purified and dried to finally obtain solid particles or spherical urea.

[0181] To describe the material and energy conversion law of the urea production process, a corresponding mathematical model is established, and equations (40) to (42) are used to represent the corresponding relationship between ammonia consumption and urea yield, calculate the required CO2 raw material quantity, and determine the energy consumption required in the reaction process. Through the model, the coordinated operation and energy optimization of the urea synthesis process and the front-end ammonia preparation and CCUS process can be realized.

[0182] ; (40)

[0183] ; (41)

[0184] ; (42)

[0185] wherein, and respectively represent the yield of urea and the ammonia consumption in the urea production process; represents the electric power consumption in the ammonia production process; and are the process coefficients of the urea synthesis process; represents the electric power consumption coefficient of the urea synthesis process.

[0186] Step 3: Establish the coordinated regulation mechanism of the energy storage system, and bidirectionally regulate the electric power and the thermal power;

[0187] For the electrochemical energy storage system, the relevant constraints and limitations are described by equations (43)-(48), the dynamic evolution of the state of charge (SOC) and its upper and lower bound constraints are used to describe the available energy range of the energy storage unit. To ensure system energy balance and sustainable operation of the energy storage device, the SOC values at the start and end times of the dispatching period must meet the set balance conditions. The charging and discharging power of the energy storage system is constrained by the device capacity and control signal, and the simultaneous occurrence of charging and discharging process is prevented by logical constraints to ensure the consistency of energy flow and safe operation of the device. In addition, to reflect the performance degradation and life loss of the energy storage device in the process of frequent charging and discharging, the invention introduces a depreciation cost term based on power cycle in the model to quantify the economic impact of the BESS in the dispatching period.

[0188] ; (43)

[0189] ; (44)

[0190] ; (45)

[0191] ; (46)

[0192] ; (47)

[0193] ; (48)

[0194] For hydrogen storage system, its operation constraints are described by equations (49)-(54), which have similar logical structure with electrochemical storage system. The storage state of hydrogen storage system is characterized by the time-varying change of its hydrogen storage amount, and the capacity boundary is determined by the upper and lower limits of the device design. To ensure the feasibility of energy cycle and the steady-state operation of the system, the hydrogen storage amount at the start and end of the scheduling period needs to be consistent. The hydrogen charging and discharging power of hydrogen storage system is limited by the operation ability of the system and the characteristics of the device, and the simultaneous occurrence of hydrogen charging and discharging process is avoided through mutual exclusion constraints, so as to ensure the directionality of energy flow and the effectiveness of control strategy.

[0195] ; (49)

[0196] ; (50)

[0197] ; (51)

[0198] ; (52)

[0199] ; (53)

[0200] ; (54)

[0201] wherein, and respectively represent the state of charge of the BESS and the state of hydrogen storage of the HSS in the Circular Hydrogen Economy Model (CHEM); and represent the conversion efficiency of the BESS device and the unit electric power attenuation cost coefficient; and are binary decision variables for avoiding the simultaneous occurrence of BESS charging and discharging process; and respectively limit the upper limit values of the charging and discharging power of the BESS device during operation; and respectively represent the lower and upper limits of the BESS battery capacity; and are binary decision variables for avoiding the simultaneous occurrence of hydrogen charging and discharging process of the HSS; and respectively limit the upper limit values of the hydrogen charging and discharging rate of the HSS device during operation; and respectively represent the lower and upper limits of the HSS hydrogen storage capacity.

[0202] Step 4: Based on low-carbon technology, hydrogen-carbon recycling and energy storage, CHEM is established to realize efficient conversion of internal energy and maximize value;

[0203] On the basis of the deployment of low-carbon technology, hydrogen-carbon resource recycling and energy storage, the CHEM model aims to maximize the profit of the system and make decisions on the operation strategy of the integrated energy system through the establishment of an optimal scheduling model. The profit is given by equation (55) and consists of revenue and cost. The revenue includes the sales revenue of hydrogen by-products (such as natural gas, ammonia, urea, methanol, etc.) and other achievable energy values; the cost includes the purchase of electricity from the main grid, the cost of natural gas procurement, the depreciation cost of the electricity storage system (ESS), the operation cost of the gas turbine unit, and the penalty cost related to carbon dioxide emissions.

[0204] ; (55)

[0205] ; (56)

[0206] ; (57)

[0207] wherein, and represent the revenue and cost of IES at time ; , , and represent the electric power of the electric load, the hydrogen load demand, the non-TPP natural gas demand and the ammonia demand, respectively; and represent the production of urea and methanol, respectively; represents the gas flow supplied by liquefied natural gas; represents the consumption of nitrogen gas in the ammonia production process; represents the net CO2 emission of the equipment; , , , , , , , and represent the electricity price, hydrogen price, natural gas price, urea price, ammonia price, methanol price, liquefied natural gas price, nitrogen price and emission penalty price, respectively; and represent the operation cost of the th thermal power unit during start-up and shutdown, respectively; represents the degradation cost of battery energy storage system; and respectively represent the power purchase and sale power; represents the set of thermal power units; represents the set of scheduling time domain of system operation pairs.

[0208] In addition to satisfying formulas (1)-(54), the CHEM must also satisfy all operating constraints including power balance constraints and material balance constraints, as shown in formulas (58)-(63):

[0209] (1) Power balance constraint

[0210] ; (58)

[0211] ; (59)

[0212] ; (60)

[0213] wherein, and respectively represent the PV power generation and WT power generation; represents the power generated by the i-th thermal power unit; and respectively represent the power output of the battery energy storage system (BESS) in charging and discharging states; and respectively represent the power generated by the hydrogen power generation device and the power consumed by the electric hydrogen production device; , , , and respectively represent the power consumption in the processes of carbon capture, utilization and storage (CCUS), methanol, urea and ammonia production; represents the upper limit of the power transmission between the CHEM and the main grid.

[0214] (2) Material balance constraint: the material balance constraint relationship should be satisfied for hydrogen, natural gas, ammonia and other hydrogen by-products.

[0215] ; (61)

[0216] ; (62)

[0217] (63)

[0218] wherein, and respectively represent the hydrogen consumption of the hydrogen power generation equipment and the hydrogen production of the hydrogen production equipment by electricity; and respectively represent the hydrogen transmission amount of the hydrogen storage system (HSS) in the hydrogen charging and hydrogen discharging states; , , and respectively represent the hydrogen demand of the system, the hydrogen consumption in the conversion of hydrogen into natural gas, the hydrogen consumption in the ammonia synthesis process, and the hydrogen consumption in the methane synthesis process; , , and respectively represent the natural gas generated in the conversion of hydrogen into natural gas, the supply amount of liquefied natural gas, the natural gas demand of non-TPPs, and the natural gas demand of TPPs; and respectively represent the ammonia consumption in the ammonia production process and the ammonia consumption in the urea production process.

[0219] Step 5: Establishing the MPC optimization scheduling model, dynamically correcting the control variables and operation strategies in the rolling time domain, formulating the real-time optimization scheduling mechanism of the IES, until the next time period, re-predicting and optimizing the control strategy according to the latest operation state.

[0220] Steps 1-4 establish the CHEM model based on low-carbon technologies, hydrogen-carbon recycling, and energy storage collaboration, introduce the CHEM model as an optimization objective and constraint condition into the MPC framework, construct the real-time optimization scheduling mechanism of the low-carbon comprehensive energy system, and obtain the MPC optimization scheduling model. In the rolling time domain, according to the latest operation state and prediction information of the system, the control variables and operation strategies are dynamically corrected to realize the rolling optimization scheduling of the multi-energy system, and the system is continuously updated to the next time period to ensure the efficient, low-carbon, and stable operation of the system under the fluctuation of multiple sources and uncertain environment.

[0221] In this embodiment, from Figure 4(a) It can be seen that the output of TPPs is significantly improved and tends to be stable, becoming the main source of supply for the whole day load, and the output level is significantly higher than that of wind power and photovoltaic power. This phenomenon is mainly due to the introduction of CCUS technology and the generation and utilization of hydrogen byproducts, which makes TPPs not subject to CO2 emission constraints and can participate in power supply and hydrogen production at the same time, thus meeting the dual demand of power load and hydrogen production power growth. Renewable energy provides auxiliary support only in part of the time due to its intermittency and volatility, and BESS has limited participation in overall scheduling, with power change close to zero, reflecting its limited actual role in the system. The system appears to buy and sell electricity in some time periods, realizing two-way flexible interaction with the external grid. From Figure 4 (b) It can be seen that the hydrogen energy system presents an operation mode of "charging hydrogen at night and releasing hydrogen during the day", and hydrogen is produced by electrolysis and stored in HSS during the low valley electricity price period, and hydrogen is released during the peak period of methanation, realizing demand peak shaving. The methanation process runs stably, which is the main hydrogen consumption link and forms synergy with electricity hydrogen production, and the hydrogen byproduct is used to produce natural gas, which is the main gas source of the natural gas system. Figure 4 (c) It can be seen that the generated natural gas becomes the main gas source of the natural gas system, accounting for more than 70% throughout the day, significantly reducing the dependence on LNG, and only small-scale supplement is carried out during the peak load period, realizing self-sufficiency of natural gas. The IES system based on CHEM enhances the coordinated regulation ability of electricity, hydrogen energy and natural gas systems through the comprehensive utilization of CCUS and hydrogen byproducts, realizes the three-energy interconnection of electricity-hydrogen-gas and the internal energy circulation of the system, and thus improves the flexibility and low carbon of the IES.

[0222] To further analyze the operation state of the CCS device in CHEM, from Figure 5 It can be seen that the capture, storage and release process of CO2 by the CCUS system at different time points reflects the dynamic change of CO2 over time. The overall carbon emission level of the system is positively correlated with the output of TPPs, and CCUS undertakes the main carbon reduction task, and enhances the carbon capture intensity during high load periods to preferentially store emission gases; during low load periods, part of the stored CO2 is released to the urea, methanol and methanation production modules for hydrogen byproduct synthesis, realizing the recycling of carbon resources.

[0223] To analyze the influence of carbon resource utilization on system operation, the production of hydrogen byproducts such as methane, urea and methanol is studied. From Figure 6 It can be seen that urea production dominates in terms of carbon resource utilization and economic benefits, while ammonia production and utilization rate are also improved, reflecting the high efficiency of resource flow within CHEM; methanation production also significantly promotes carbon resource utilization. Under the proposed CHEM framework, CO2 can be effectively recycled and utilized, realizing multi-byproduct production centered on hydrogen energy, promoting carbon emission reduction, improving economic efficiency and enhancing system sustainability.

[0224] From Figure 7The hydrogen by-products (natural gas, urea, ammonia) can be seen to vary in production throughout the day, reflecting the dynamic scheduling and flexible use of CO2 and H2 by the system. Methanation-generated natural gas dominates, especially during high-load periods, with CCS-captured CO2 being used preferentially; urea and ammonia, although in smaller quantities, play an important role in system resource utilization, with urea production being prioritized over ammonia to achieve the production of high-value-added products. The overall scheduling strategy embodies the staggered use of H2 and carbon sources, improving energy utilization efficiency and reducing operating costs.

[0225] In summary, the IES based on CHEM proposed by the present application achieves flexibility improvement and effective control of carbon emissions through efficient use of low-carbon resources, optimization of multi-energy collaborative operation, and real-time optimization scheduling based on MPC. The system dynamically corrects control variables and operation strategies in the rolling time domain through MPC, enabling the cyclic use of hydrogen energy and carbon resources while supporting the collaborative scheduling of multiple energy forms, providing a feasible technical solution and implementation path for green, low-carbon, and sustainable energy development.

Claims

1. A method for real-time optimal operation of a low-carbon integrated energy system based on hydrogen by-product utilization, characterized in that, The method comprises the following steps: Utilizing low-carbon technology to dynamically interconnect and optimize multi-energy of electricity, hydrogen and gas; Establishing an industrial utilization mechanism of hydrogen energy and carbon resources coupling, and utilizing hydrogen and carbon dioxide resources to synthesize natural gas, ammonia, urea and high-value hydrogen by-products of methanol; Establishing a collaborative regulation mechanism of energy storage system, and bidirectionally regulating electricity and heat; Based on the low-carbon technology, hydrogen-carbon recycling and the collaborative regulation mechanism of energy storage system, a circulating hydrogen economic operation model is established to convert the internal energy of the system and maximize the value; An MPC optimization scheduling model is established to dynamically correct the control variables and operation strategies in a rolling time domain, to formulate a real-time optimization scheduling mechanism of the IES, and to optimize the control strategy until the next time period, and to re-predict and optimize the control strategy according to the latest operation state. 2.The real-time optimal operation method of a low-carbon integrated energy system based on hydrogen by-product utilization according to claim 1, wherein, The low-carbon technology comprises water electrolysis for hydrogen production, carbon capture and storage, electric-to-gas and gas turbine. 3.The real-time optimization operation method of a low-carbon integrated energy system based on hydrogen by-product utilization according to claim 1, characterized in that, The MPC optimization scheduling model comprises: Objective function: ； ； ； wherein, and denote the IES’s revenue and cost at time ; , , and denote the electrical power of the electrical load, the hydrogen load demand, the non-TPPs natural gas demand, and the ammonia demand, respectively; and denote the production of urea and methanol, respectively; denotes the gas flow supplied by liquefied natural gas; denotes the consumption of nitrogen gas in the ammonia production process; denotes the net CO2 emission of the equipment; , , , , , , , and denote the price of electricity, hydrogen, natural gas, urea, ammonia, methanol, liquefied natural gas, nitrogen, and emission penalty price, respectively; and denote the operation cost of the th thermal power unit during start-up and shut-down, respectively; denotes the degradation cost of the battery energy storage system; and denote the power purchase and sale, respectively; denotes the set of thermal power units; denotes the set of dispatching time horizons of the system operation. Constraint condition: Power balance constraint ； ； ； wherein, and Pvand Pwdenote the electrical power generated by PV and WT, respectively; Pfdenotes the electrical power generated by the fth thermal power unit; Pfdenotes the electrical power generated by the fth thermal power unit; and Pchand Pd denote the electrical power output of the BESS in charging and discharging state, respectively; and Pheand Pehdenote the electrical power generated by the hydrogen generation equipment and consumed by the hydrogen production equipment, respectively; , , and Pccus, Pmeth, Pures, and Pam denote the electrical power consumption in the CCUS, methanol, urea and ammonia production processes, respectively; Pcheand Pche denote the upper limit of the electrical power transferred between the CHEM and the main grid. Material balance constraint ； ； ； wherein, and respectively represent the amount of hydrogen consumed by the hydrogen power generation facility and the amount of hydrogen produced by the electricity-to-hydrogen facility; and respectively represent the amount of hydrogen transferred by the HSS in the hydrogen charging and hydrogen discharging states; , , and respectively represent the amount of hydrogen required by the system, the amount of hydrogen consumed in the conversion of hydrogen to natural gas, the amount of hydrogen used in the ammonia synthesis process, and the amount of hydrogen used in the methane synthesis process; , , and respectively represent the amount of natural gas produced in the conversion of hydrogen to natural gas, the amount of natural gas supplied as LNG, the amount of natural gas required by non-TPPs, and the amount of natural gas required by TPPs; and respectively represent the amount of ammonia used in the ammonia production process and the amount of ammonia used in the urea production process; Device constraint: Hydrogen-electricity interconnected device constraint ； ； ； ； ； wherein, and respectively represent the energy conversion efficiency of the electricity-to-hydrogen plant and the hydrogen-to-electricity plant; represents the compression factor of hydrogen gas; and respectively represent the higher heating value and the lower heating value of hydrogen gas; and for limiting the upper limit of the hydrogen gas transmission amount of the electricity-to-hydrogen plant and the hydrogen-to-electricity plant, and are binary decision variables for avoiding the simultaneous occurrence of the electricity-to-hydrogen process and the hydrogen-to-electricity process. Carbon capture and storage device constraint: ； ； ； ； ； ； ； ； ； wherein, CO2 emissions for characterizing CCUS; and respectively represent the amount of CO2 absorbed and released by the CCUS plant; , and respectively correspond to the amount of CO2 consumed in the methanol, urea and methanation production processes; and respectively represent the carbon capture efficiency of the CCUS plant and its electrical power consumption coefficient; and respectively represent the CO2 emission rate of the electrical grid and of the TPPS; for indicating the operating state of the carbon sequestration system; and respectively represent the lower and upper limits of the storage capacity of the carbon sequestration system; and respectively serve to define the upper limit values of CO2 absorption and release by the CCUS plant during operation; Ammonia production process constraint: ； ； ； wherein and is a process coefficient of the ammonia synthesis process; represents an electrical power consumption coefficient of the ammonia synthesis process; Methanol production constraint ； ； ； wherein and is a process coefficient for the methanol synthesis process; represents an electrical power consumption coefficient for the methanol synthesis process; Urea production constraint ； ； ； wherein and is a process coefficient for the urea synthesis process; represents an electrical power consumption coefficient for the urea synthesis process; Methanation reaction constraint ； ； ； wherein, for characterizing the volumetric conversion relationship between hydrogen and natural gas; for defining an upper limit of natural gas production in a methanation process; process coefficients representing a natural gas synthesis process; Thermal power plant constraint ； ； ； ； ； ； ； ； ； ； ； ； ； ； ； ； in, This indicates the fuel consumption of TPPs; , and The coefficients represent the heat rate function of TPPs; and Indicates the first The lower and upper limits of the electrical power output of the TPP; A binary variable representing the state of TPPs; and To avoid simultaneous start-up and shutdown of TPPs, binary decision variables are used; the power generation range of each unit is divided into... Section, No. The unit heat consumption coefficient of the section is The corresponding power is ; and They represent the first The unit start-up and shutdown operating costs of a TPP; and They represent the first The minimum start and stop times for the Taiwan TPP; and They represent the first The maximum ramp and descent rates of the TPP platform; This indicates the total calorific value of natural gas; Energy storage system constraint ； ； ； ； ； ； ； ； ； ； ； ； wherein, and SoS and HSS SoS in CHEM represent the state of charge of the BESS and the state of hydrogen storage of the HSS, respectively; and η and c represent the conversion efficiency of the BESS device and the unit electric power decay cost coefficient, respectively; and and are binary decision variables for avoiding the simultaneous occurrence of the charging and discharging processes of the BESS; and and are used to limit the upper values of the charging and discharging power of the BESS device during operation, respectively; and and represent the lower and upper limits of the BESS battery capacity, respectively; and and are binary decision variables for avoiding the simultaneous occurrence of the hydrogen charging and discharging processes of the HSS; and and are used to limit the upper values of the hydrogen charging and discharging rates of the HSS device during operation, respectively; and and represent the lower and upper limits of the HSS hydrogen storage capacity, respectively.

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