Multi-element energy storage system anti-disturbance cooperative control method and system and medium

Abstract

The invention discloses a multi-element energy storage system anti-disturbance cooperative control method and system and a medium, and the method comprises the steps: obtaining the real-time operation data of a multi-element energy storage system which comprises an energy conversion and storage device, the energy conversion and storage device comprises an electric energy-heat energy conversion device, an electric energy-hydrogen energy conversion device, an electric energy storage device, a heat energy storage device, a hydrogen energy storage device and a superconducting magnetic energy storage device; constructing a multi-energy complementary comprehensive energy system model containing a minimum total operation cost objective function based on the real-time operation data; solving the multi-energy complementary comprehensive energy system model, and generating an anti-disturbance cooperative control strategy; and the charging and discharging instruction is controlled to be sent to the multi-element energy storage system based on the anti-disturbance cooperative control strategy to control cooperative operation of the multi-element energy storage system, so that real-time power balance of the multi-element energy storage system is realized, new energy output fluctuation and user load sudden change can be quickly responded, and the operation stability and anti-risk capability of the multi-element energy storage system are improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of energy storage control and optimization of power systems, and particularly relates to a multi-element energy storage system anti-disturbance collaborative control method, system and medium. BACKGROUND

[0002] The inherent strong randomness, volatility and intermittence of renewable energy generation such as wind power and photovoltaic power are the root cause of the difficulty in power system balance. This makes the temporal and spatial balance of power and electricity of the power system significantly more difficult after large-scale new energy access to the power grid. Specifically, in the ultra-short cycle (milliseconds to seconds), the new energy output fluctuates rapidly and its frequency and voltage tolerance is insufficient, coupled with the large-scale access of power electronic equipment, which reduces the system inertia and reduces the system's ability to resist disturbances, easily causing frequency and voltage stability problems; in the short cycle (minutes to hours), the random fluctuations of new energy output in a short time easily cause system frequency and flow control difficulties, and the hourly maximum power fluctuation of a single station can reach 15%-25% of the installed capacity; in the daily regulation level, the matching degree of new energy generation characteristics and electricity load daily characteristics is poor (such as wind power anti-peaking), which significantly increases the system net load peak-valley difference and aggravates the peaking pressure; in the multi-day or even week time scale, the characteristics of new energy "depending on the weather" are obvious, and weather conditions may cause the output to be persistently low, causing long-term supply and demand imbalance risks.

[0003] In a high-proportion new energy power system, the anti-disturbance ability and transient stability of the power system are severely tested. The "power electronicization" of the system leads to a continuous decrease in its rotational inertia, making the system frequency and voltage change faster and more intense when encountering disturbances such as faults, significantly increasing the difficulty of stability control. The anti-interference ability of new energy equipment is usually weaker than that of conventional synchronous generators, and it is easy to cause large-scale disconnection in system faults, causing serious cascading failures. In extreme environments such as cold regions, low temperature not only increases the difficulty of normal operation and startup of equipment (such as electrolytic cells), but also may cause problems such as degradation of fuel cell catalyst performance, attenuation of lithium battery capacity, and reduction of thermal safety, posing an additional threat to the reliability and safety of the entire power system. Therefore, the system urgently needs a control means that can respond extremely quickly (milliseconds), provide instantaneous power support to suppress disturbances, and enhance stability. SUMMARY

[0004] The purpose of the present application is to set up a multi-energy complementary comprehensive energy system model based on a multi-element energy storage system including a superconducting magnetic energy storage device, and to obtain an anti-disturbance collaborative control strategy by solving the model, so as to realize a multi-element energy storage system anti-disturbance collaborative control method, system and medium for real-time power balance of the multi-element energy storage system.

[0005] In one aspect, to achieve the above object, the present application provides a multi-element energy storage system anti-disturbance cooperative control method, comprising: obtaining real-time operation data of a multi-element energy storage system, the multi-element energy storage system comprising an energy conversion and storage device, the energy conversion and storage device comprising an electric energy-thermal energy conversion device, an electric energy-hydrogen energy conversion device, an electric energy storage device, a thermal energy storage device, a hydrogen energy storage device and a superconducting magnetic energy storage device, the real-time operation data comprising new energy output, electric, heat, hydrogen load and power limit; constructing a multi-energy complementary comprehensive energy system model based on the real-time operation data, the multi-energy complementary comprehensive energy system model comprising a multi-energy complementary comprehensive energy system minimum total operation cost target function based on a constraint condition, the minimum total operation cost comprising start-stop cost, maintenance cost, electric power storage benefit and energy release benefit of power supply, heat supply and hydrogen supply, the constraint condition comprising power constraint; solving the multi-energy complementary comprehensive energy system model to generate an anti-disturbance cooperative control strategy; controlling to send a charge-discharge instruction to the multi-element energy storage system based on the anti-disturbance cooperative control strategy to control cooperative operation of the multi-element energy storage system and realize real-time power balance of the multi-element energy storage system.

[0006] In an optional embodiment, the multi-energy complementary comprehensive energy system model is constructed based on the real-time operation data, specifically comprising: constructing an electric-hydrogen energy conversion and storage model based on the real-time operation data, the electric-hydrogen energy conversion and storage model comprising a hydrogen storage model, the real-time operation data comprising efficiency limit of a hydrogen production process, capacity limit of hydrogen energy total amount in a gas network, hydrogen energy total amount and hydrogen generation rate; constructing a heat storage device model through a model of converting electric energy into thermal energy by an electric boiler; constructing a single cell output voltage based on a chemical reaction equation of a fuel cell;

[0007] constructing an electric-thermal-hydrogen power balance model based on a general model of input-coupling-output of a multi-energy system; constructing the multi-energy complementary comprehensive energy system model based on the electric-hydrogen energy conversion and storage model, the single cell output voltage, the heat storage device model and the electric-thermal-hydrogen power balance model.

[0008] In an optional embodiment, the electric-hydrogen energy conversion and storage model comprises a hydrogen storage model, specifically comprising: constructing a hydrogen production power model based on the minimum value of the efficiency limit of the hydrogen production process and the capacity limit in the gas network; calculating hydrogen energy total amount input to a specific node by electric hydrogen based on the hydrogen production power model; constructing the hydrogen storage model based on the hydrogen energy total amount input to the specific node by the electric hydrogen.

[0009] In an optional embodiment, the hydrogen storage model comprises hydrogen storage amount, and the hydrogen storage amount is a time integral of the hydrogen generation rate.

[0010] In an alternative embodiment, the thermal energy storage device model comprises a thermal energy storage amount at a previous time, a heat absorption power at a given time, a heat absorption efficiency, and a thermal energy storage amount.

[0011] In an alternative embodiment, the electricity-heat-hydrogen power balance model comprises an electricity output power, a heat output power, and a hydrogen output power.

[0012] In an alternative embodiment, the superconducting magnetic energy storage device comprises a bridge circuit.

[0013] In an alternative embodiment, solving the multi-energy complementary comprehensive energy system model to generate the anti-disturbance collaborative control strategy specifically comprises: performing gain summation based on a difference between an initial operating state and an operating state of the system to obtain a deviation value of a system adjustment process; constructing a system performance index based on a storage and release power of an energy storage device, a conventional benefit matrix, a conventional capacity matrix, and the deviation value of the system adjustment process; constructing a solving model based on the system performance index; optimizing the multi-energy complementary comprehensive energy system model based on the solving model to generate an energy storage strategy; and generating the anti-disturbance collaborative control strategy based on the energy storage strategy.

[0014] In another aspect, the present application also provides a multi-element energy storage system anti-disturbance collaborative control system, comprising: a multi-element energy storage system comprising an energy conversion and storage device, the energy conversion and storage device comprising an electricity-heat conversion device, an electricity-hydrogen conversion device, an electricity storage device, a thermal energy storage device, a hydrogen energy storage device, and a superconducting magnetic energy storage device, and real-time operating data comprising new energy output, electricity, heat, hydrogen load, and power limitation; a data processing module in communication connection with the multi-element energy storage system to construct a multi-energy complementary comprehensive energy system model based on real-time operating data of the multi-element energy storage system, the multi-energy complementary comprehensive energy system model comprising a multi-energy complementary comprehensive energy system minimum total operating cost objective function based on a constraint condition, the minimum total operating cost comprising start-stop cost, maintenance cost, electricity storage benefit, and energy release benefit of electricity supply, heat supply, and hydrogen supply, the constraint condition comprising a power constraint; and the data processing module solving the multi-energy complementary comprehensive energy system model to generate an anti-disturbance collaborative control strategy, and controlling to send a charge-discharge instruction to the multi-element energy storage system based on the anti-disturbance collaborative control strategy to control collaborative operation of the multi-element energy storage system, thereby realizing real-time power balance of the multi-element energy storage system.

[0015] In another aspect, the present application also provides a medium storing a computer program, the computer program being executed by a processor to implement any of the multi-element energy storage system anti-disturbance collaborative control methods.

[0016] The beneficial effects of the present application are: by constructing a multi-energy complementary model, breaking the barriers of electric, thermal, hydrogen and other energy flows, optimizing the energy conversion and storage path, and improving the energy comprehensive utilization efficiency; through the closed-loop process of real-time data collection-disturbance prediction-multi-device collaborative control, the new energy output fluctuation and user load mutation can be quickly responded, the system power imbalance caused by single energy storage device failure can be avoided, and the stability and risk resistance of the multi-energy storage system operation are significantly improved. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 A flowchart of a multi-energy storage system anti-disturbance collaborative control method provided for an embodiment of the present application is shown.

[0018] Figure 2 A multi-energy storage system schematic diagram of a multi-energy storage system anti-disturbance collaborative control system provided for another embodiment of the present application is shown.

[0019] Explanation of reference numerals: 100, multi-energy storage system. DETAILED DESCRIPTION

[0020] The prior art communication parameters are fixed, without a dynamic scheduling mechanism, and the communication stability is poor in high-cold high-altitude complex environment: the communication parameters (channel, transmission power, bandwidth allocation) are fixedly set, for example, the channel is fixedly set as a certain preset frequency (such as 7MHz), the transmission power is fixedly set as 10W, and the bandwidth is fixedly set as 31.25Hz (PSK31 technical standard bandwidth). However, in high-cold high-altitude areas, there are strong electromagnetic interference (such as frequent lightning activities leading to sudden increase of channel noise), unstable signal attenuation (large terrain undulation, variable signal propagation path), and multi-node concurrent transmission demand (multiple monitoring points simultaneously transmitting data), and the fixed parameters cannot adapt to environmental changes.

[0021] The present application will be further described in detail through the accompanying drawings and specific embodiments.

[0022] As shown in Figure 1 and Figure 2 According to an embodiment of the present application, on the one hand, a multi-energy storage system anti-disturbance collaborative control method is provided, comprising the following steps:

[0023] Step S101: acquiring real-time operation data of a multi-energy storage system, the multi-energy storage system comprising energy conversion and storage devices, the energy conversion and storage devices comprising electric-thermal energy conversion devices, electric-hydrogen energy conversion devices, electric energy storage devices, thermal energy storage devices, hydrogen energy storage devices and superconducting magnetic energy storage devices, the real-time operation data comprising new energy output, electric, thermal, hydrogen load and power limit;

[0024] Step S103: constructing a multi-energy complementary integrated energy system model based on real-time operation data, the multi-energy complementary integrated energy system model including a multi-energy complementary integrated energy system minimum total operation cost objective function based on constraint conditions, the minimum total operation cost including start-stop cost, maintenance cost, power storage benefit, and energy release benefit of power supply, heat supply, and hydrogen supply, the constraint conditions including power constraints;

[0025] Step S105: solving the multi-energy complementary integrated energy system model to generate a disturbance-resistant collaborative control strategy;

[0026] Step S107: controlling the sending of charging and discharging instructions to the multi-element energy storage system based on the disturbance-resistant collaborative control strategy to control the collaborative operation of the multi-element energy storage system and realize real-time power balance of the multi-element energy storage system.

[0027] In this embodiment, first, a data acquisition network covering the whole link of the multi-element energy storage system is built, and various key data in the system are acquired in real time through sensors, intelligent metering terminals, and communication modules. The energy conversion and storage devices specifically include:

[0028] Electricity-heat conversion devices, such as electric boilers, need to collect real-time conversion efficiency, import and export temperature, and running state (running / stop) data;

[0029] Electricity-hydrogen conversion devices, such as electrolytic cells, need to collect electrolysis efficiency, hydrogen production, electrolysis current / voltage, and cooling water temperature data;

[0030] Electricity storage devices, such as lithium battery storage and vanadium flow battery, need to collect state of charge (SOC), charging and discharging power, single cell voltage, and battery temperature data;

[0031] Heat storage devices, such as phase change heat storage tanks and sensible heat storage devices, need to collect heat storage temperature, heat storage capacity (SOC), and heat release power data;

[0032] Hydrogen storage devices, such as high-pressure hydrogen storage tanks, need to collect hydrogen storage pressure, hydrogen storage amount (SOC), and leakage detection data;

[0033] Superconducting magnetic energy storage devices need to collect magnet current, energy storage capacity, cooling system temperature, and superconducting state data.

[0034] At the same time, external associated data is collected, including new energy output (photovoltaic power station output power, wind speed and wind power output, and light intensity), electricity / heat / hydrogen load (real-time power consumption of the user side, heat supply demand, and hydrogen consumption rate), and power limit (maximum charging / discharging power of each device, power limit of the grid access point, and maximum flow limit of the pipeline hydrogen), and the collected data is filtered and abnormal values are removed to ensure data accuracy and timeliness.

[0035] Based on real-time operation data, a multi-energy complementary integrated energy system model is constructed, which takes into account economy and stability, and the core includes objective function and constraint condition two parts:

[0036] 1. The minimum total operation cost objective function

[0037] The objective function minimizes the total operation cost of the multi-energy storage system within a period (such as 1 day, 1 dispatch cycle), and the cost is divided into:

[0038] Start-up and shutdown cost: equipment loss cost, preheating / precooling energy consumption cost, and residual energy handling cost (such as heat loss cost after shutdown of heat storage device) when each energy conversion / storage device starts;

[0039] Maintenance cost: daily maintenance fee calculated according to the running time, charge / discharge times, and load rate of each device (such as cycle life loss maintenance fee of battery energy storage, electrode replacement maintenance fee of electrolytic cell);

[0040] Electricity storage benefit: income generated by "peak-valley arbitrage" (charging during low valley period and discharging during peak period) of electric energy storage device, and auxiliary service income obtained by participating in grid frequency regulation and peak regulation, which offsets the total operation cost;

[0041] Energy supply energy release benefit: energy sales income (such as electricity price income, heat price income, and hydrogen energy sales price income) when supplying electricity, heat, and hydrogen to users, which further offsets the total operation cost.

[0042] The final objective function expression can be simplified as: total operation cost = start-up and shutdown cost + maintenance cost - electricity storage benefit - energy supply energy release benefit, and the system economy is optimized by minimizing this formula.

[0043] The external characteristics of the electricity-heat-hydrogen multi-energy storage system (EHH-MESS) can be flexibly adjusted according to the grid demand, and its start-up and shutdown cost, maintenance cost, and energy storage, energy conversion, and release benefit all change with the grid demand.

[0044] Further, in step S103, a multi-energy complementary integrated energy system model is constructed based on real-time operation data, which specifically includes the following steps:

[0045] Step S1031: Constructing an electricity-hydrogen energy conversion and storage model based on real-time operation data, which includes a hydrogen storage model, and the real-time operation data includes efficiency limits of the hydrogen production process, capacity limits of the gas network, total hydrogen energy, and hydrogen generation rate.

[0046] Step S1033: Constructing a heat storage device model by a model of converting electrical energy into thermal energy by an electric boiler.

[0047] Step S1035: Constructing a single cell output voltage based on a chemical reaction equation of a fuel cell.

[0048] Step S1037: Constructing an electric-thermal-hydrogen power balance model based on a general model of input-coupling-output of a multi-energy system.

[0049] Step S1039: Constructing a multi-energy complementary comprehensive energy system model based on the electric-hydrogen energy conversion and storage model, the single cell output voltage, the heat storage device model, and the electric-thermal-hydrogen power balance model.

[0050] In this embodiment, by constructing the electric-hydrogen energy conversion and storage model, the real-time data such as hydrogen production efficiency limit, gas network capacity limit, hydrogen energy total amount, and hydrogen generation rate are fully considered, the whole process characteristics of hydrogen energy from production, storage to utilization are accurately described, the energy conversion and storage process related to hydrogen energy is more in line with the actual working condition, the energy waste or insufficient supply problem caused by inaccurate model is reduced, and the accuracy and reliability of the hydrogen energy system operation are improved.

[0051] The heat storage device model constructed by the electric boiler electrical energy-thermal energy conversion model can accurately grasp the key parameters such as electric-thermal conversion efficiency and heat storage capacity, and realize efficient storage and flexible allocation of thermal energy. When the heat demand fluctuates, the thermal energy of the heat storage device can be called in time to ensure the stability of heat supply, and the conversion process of electrical energy to thermal energy is optimized to improve energy utilization efficiency.

[0052] The single cell output voltage model constructed based on the chemical reaction equation of the fuel cell can accurately reflect the electrochemical characteristics of the fuel cell, and provide a basis for the overall performance analysis and optimization of the fuel cell stack. Through this model, the operating state of the fuel cell can be better controlled to work in the efficient interval, prolong the service life of the fuel cell, and at the same time ensure the stability of the output electrical energy to provide reliable power supply for the system.

[0053] The multi-energy complementary comprehensive energy system model constructed based on the electric-thermal-hydrogen power balance model and the electric-hydrogen energy conversion and storage model, the heat storage device model, and the single cell output voltage model breaks down the barriers between different energy forms such as electricity, heat, and hydrogen. It can realize the collaborative optimization and scheduling of multiple energy sources of electricity, heat, and hydrogen, reasonably allocate energy according to the supply and demand status and conversion characteristics of different energy sources, improve the overall energy utilization efficiency and economy of the multi-energy system, and enhance the ability of the system to respond to energy fluctuations.

[0054] The multi-energy complementary integrated energy system model integrates key information and interaction relationships of each sub-system of electricity, heat and hydrogen, and can provide comprehensive and accurate basis for system operation decision (such as energy scheduling strategy, equipment start-stop arrangement, etc.). The system can achieve the optimization targets of the lowest operation cost and the least energy waste under the premise of meeting various energy demands, and improve the overall operation efficiency of the system.

[0055] In step S1031, an electricity-hydrogen energy conversion and storage model is constructed based on real-time operation data, and the electricity-hydrogen energy conversion and storage model includes a hydrogen storage model, and specifically includes the following steps:

[0056] In step S10311, a hydrogen production power model is constructed based on the minimum value of the efficiency limit of the hydrogen production process and the capacity limit in the gas network.

[0057] In step S10313, the total amount of hydrogen energy input to the specific node by the electricity-to-hydrogen is calculated based on the hydrogen production power model.

[0058] In step S10315, a hydrogen storage model is constructed based on the total amount of hydrogen energy input to the specific node by the electricity-to-hydrogen.

[0059] The hydrogen storage model includes a hydrogen storage amount, and the hydrogen storage amount is a time integral of the hydrogen generation rate.

[0060] In this embodiment, only the process of electricity-to-hydrogen in power-to-gas (P2G) is considered, the energy loss of chemical reaction in the process of power-to-gas can be avoided, and only hydrogen is used as the medium for energy conversion. The hydrogen energy flux in a given time is denoted as E T1 (t), and the power model of the hydrogen production facility, i.e., the hydrogen production power model , is expressed as:

[0061] ;

[0062] wherein, is the upper limit of the rated power of the hydrogen production device; is the upper limit of the hydrogen gas allowed in the gas network; η H2 is the efficiency of the hydrogen production process; is the hydrogen energy flux in time t.

[0063] To determine the power of the hydrogen production facility, i.e., the hydrogen production power , two limiting conditions need to be considered, and the "smaller value" is taken:

[0064] Efficiency limit of the hydrogen production process: based on the hydrogen production efficiency and the hydrogen energy flux in time t, the upper limit of the power determined by the efficiency .

[0065] Gas network capacity limit: hydrogen upper limit allowed by the gas network , and the hydrogen production-related coefficient , jointly constitute the network capacity vs. power limit.

[0066] The final power is the more “strict” (smaller) of the two limits, ensuring that hydrogen production is both efficient and does not exceed the gas network carrying capacity.

[0067] Step S10313, the energy content of hydrogen introduced from the P2G process to node n is given by:

[0068] ;

[0069] The produced hydrogen can be supplied to hydrogen loads, fuel cells, natural gas pipelines, and hydrogen storage tanks.

[0070] The hydrogen energy obtained by node n from the P2G process is the integral result in the time dimension: the hydrogen production power at each time t , multiplied by the hydrogen production efficiency , and then summed (integrated) over the time range. This reflects the total amount of hydrogen energy input by the P2G process to the node over time.

[0071] The hydrogen storage model at time t is described by the following formula:

[0072] ;

[0073] where V H2 is the hydrogen generation rate, and t1 and t2 are the start and end times of hydrogen generation, respectively.

[0074] The hydrogen storage amount is the time integral of the hydrogen generation rate: the hydrogen generation rate is , integrated from the start time to the end time to obtain the total amount of hydrogen stored in this time period. This reflects the storage pattern of hydrogen in the hydrogen storage tank over the “process accumulation”.

[0075] First, “how is the power of hydrogen production constrained by efficiency and network capacity?” is clarified, then “the total amount of hydrogen energy input by the P2G process to a specific node” is calculated, and finally “how the hydrogen storage amount accumulates with the generation rate and time” is described, which fully covers the modeling of the “production—transportation—storage” core links of P2G electricity-to-hydrogen.

[0076] In the EHH-MESS system, a fuel cell is used to convert hydrogen into electrical energy. The chemical reaction of this fuel cell is described by the following equation:

[0077] ;

[0078] The output voltage of a single battery cell can be defined as the result of the following expression:

[0079] ;

[0080] Where E Nernst V is the thermodynamic potential of the battery, representing its reversible voltage; act This refers to the voltage drop caused by the activation of the anode and cathode; V ohmic For ohmic voltage drop; V con This represents the voltage drop caused by the decrease in the concentration of the reacting gas.

[0081] Chemical reactions in a fuel cell (equation portion)

[0082] Fuel cells convert hydrogen into electrical energy through half-reactions at two electrodes; the final overall reaction is the reaction of hydrogen and oxygen to produce water.

[0083] Fuel electrode (anode): Hydrogen ( ) loses electrons and is oxidized into hydrogen ions ( The reaction is .

[0084] Air electrode (cathode): hydrogen ions ( ),oxygen( It gains electrons and is reduced to water. The reaction is .

[0085] Overall reaction: Adding the two half-reactions together, we get the overall reaction of hydrogen and oxygen to produce water. This process is accompanied by the generation of electricity.

[0086] Output voltage of a single fuel cell It is the result of subtracting various loss voltages from the ideal reversible voltage (thermodynamic potential):

[0087] The thermodynamic potential of the battery represents the "ideal reversible voltage" (the upper limit of the voltage without any losses) of the fuel cell.

[0088] Activation voltage drop is the voltage loss caused by the "activation reaction" (the energy barrier that needs to be overcome to start the reaction) at the anode and cathode.

[0089] Ohmic voltage drop is the voltage loss caused by resistance when current flows through the inside of a battery (such as electrolyte, electrodes, etc.).

[0090] Concentration voltage drop occurs when the concentration of gases (hydrogen and oxygen) decreases during the reaction, leading to a decrease in the driving force of the reaction and consequently a voltage loss.

[0091] Final output voltage It is the result of subtracting these three types of actual losses from the "ideal voltage", which reflects the voltage characteristics of the fuel cell when it actually generates electricity (the balance between the ideal value and the losses).

[0092] First, the chemical nature of "hydrogen → electricity" in fuel cells is clarified through "half-reaction + overall reaction". Then, from the perspective of "ideal voltage - various losses", the actual output voltage of a single cell is quantified, which fully covers the core content of "reaction principle" and "voltage characteristics" of fuel cell power generation.

[0093] In the EHH-MESS model, an electric boiler is used to convert electrical energy into heat energy. The power input of the heating facility is represented by the following model:

[0094] ;

[0095] Among them, H eb,T2 (t) represents the heating power of the electric boiler when it consumes eb energy at temperature T2 and within a given time; P eb,T2 (t) represents the power transfer value of the electric boiler at temperature T2 and within a given time; η con This refers to the efficiency of the process of converting electrical energy into heat energy.

[0096] The thermal storage device is modeled using the following formula:

[0097] ;

[0098] Among them, H S,T3 (t) represents the amount of thermal energy stored in object S at time t3, H S,T3 (t−1) represents the amount of thermal energy stored in object S at the moment before time t3, μ is the heat dissipation rate, and Q is the thermal energy stored in object S. C (t) represents the heat absorption power at a given time, η hc For heat absorption efficiency; H cap This refers to thermal energy storage capacity.

[0099] Based on the EHH-MESS modeling, the power balance equations for EHH-MESS were constructed. This model considers only power input and achieves energy storage and release through electro-thermal-hydrogen conversion and energy storage devices. Researchers proposed the concept of an energy hub for multi-energy storage systems; this model uses a matrix to describe the coordinated allocation of input and output among multiple energy sources, as shown below:

[0100] ;

[0101] Where P m L n These represent the input and output of different energies; c nm is the coupling coefficient.

[0102] The left side of the matrix represents the output of different forms of energy (such as electrical output, thermal output, hydrogen output, etc.); the middle of the matrix is ​​the coupling coefficient matrix. It represents the coupling relationship between different energy sources in terms of conversion and distribution, reflecting "how one energy input is transformed into another energy output".

[0103] The right side of the matrix represents different forms of energy input (such as electrical input, electrical input used for hydrogen production, etc.).

[0104] The matrix equation describes the overall logical chain of "multiple energy inputs → multiple energy outputs through coupling".

[0105] The EHH-MESS system only considers power input and achieves energy storage / release through "electric-thermal-hydrogen" conversion and energy storage devices. Its power balance needs to be refined to the input-output balance of three types of power: "electricity, heat, and hydrogen".

[0106] The figures on the left represent electrical power output, thermal power output, and hydrogen power output, respectively.

[0107] The intermediate matrix reflects the distribution and efficiency of the conversion from "electrical input" to "electrical, thermal, and hydrogen output," and includes:

[0108] Power distribution factor ( Allocate to hydrogen production. (Assigned to electric water heaters)

[0109] Hydrogen partition coefficient ( To the hydrogen storage tank, (e.g., to hydrogen loading).

[0110] Energy conversion efficiency ( Hydrogen production efficiency, Fuel cell efficiency, etc.

[0111] The right side represents different power inputs (such as electrical input). wait).

[0112] The equation as a whole quantifies the balance relationship of "how electrical input is distributed and converted to finally output electrical, heat and hydrogen power", reflecting the precise flow and conservation of energy within the EHH-MESS system.

[0113] First, a general model of "input-coupling-output" for multi-energy systems is established through "matrix + energy hub". Then, focusing on the "power input only" characteristic of the EHH-MESS system, the specific balance equation of its electric-thermal-hydrogen power is derived, which fully covers the logical chain of "multi-energy coupling modeling → power balance of specific systems".

[0114] The thermal energy storage device model includes the thermal energy storage capacity at the previous moment, the heat absorption power at a given moment, the heat absorption efficiency, and the thermal energy storage capacity.

[0115] Furthermore, the electro-thermal-hydrogen power balance model includes electrical output power, thermal output power, and hydrogen output power.

[0116] EHH-MESS has only power input, and its power balance equation is derived from the following formula.

[0117]

[0118] Among them, P out,E P out,H P out,H2 These represent the electrical power output, thermal power output, and hydrogen output power, respectively; P out,E This represents the electrical power input. λ1 and λ2 represent the distribution coefficients for electrical energy allocation to the hydrogen production unit and the electric water heater, respectively. β1, β2, β3, and β4 represent the distribution coefficients for hydrogen allocation to the hydrogen storage tank, hydrogen load, fuel cell, and gas pipeline, respectively. η P2G η FC , These represent the energy conversion efficiencies of the hydrogen production unit, fuel cell, and electric water heater, respectively.

[0119] For the EHH-MESS system, its energy storage ratio varies across different time periods. To achieve optimal economic benefits while meeting the demands of both new energy sources and energy storage at specific times, differentiated optimization of the electricity-heat-hydrogen energy conversion and storage equipment is necessary. Based on optimal collaborative control theory and the characteristics of new energy output at different times, optimal combinations of energy storage, release, and conversion ratios are established for different energy storage forms and energy conversion modes. An algorithm is proposed to solve the optimal combination of energy conversion, storage, and release. Based on actual energy supply and demand data, the energy storage or release demand at each moment is obtained, and then the optimal combination scheme for EHH-MESS at different time periods under a given time point is selected.

[0120] Specifically, the energy conversion and storage capacity allocation scheme in EHH-MESS not only meets the system's maximum peak-shaving requirements but also offers significant economic benefits. The total operating cost of EHH-MESS varies under different energy conversion and storage capacity allocation conditions. Its optimization objective function aims to minimize the total operating cost of EHH-MESS, and its specific expression is as follows:

[0121] ;

[0122] ;

[0123] ;

[0124] ;

[0125] ;

[0126] Among them, C ST (t) represents the start-up and shutdown cost of the EHH-MESS system at a specific time, C P2G,i C SH2,i C EB,i C FE,i C represents the start-stop coefficients for the P2G device, hydrogen storage tank, electric boiler, and fuel cell, respectively, with values ​​ranging from [0, 1]. MC (t) represents the maintenance cost of the EHH-MESS system at a specific moment, C S (t) represents the energy storage benefit at a specific moment, C O (t) represents the energy release benefits including power supply, heating, and hydrogen supply, U P2G (t), U SH2 (t), U EB (t) represents the unit benefits of electricity, heat, and hydrogen supply, respectively. FE (t) represents the start-up and shutdown status of the electric boiler, C M For the unit maintenance cost of EHH-MESS, P M (t) represents the operating power during maintenance, C EI For the benefit of electricity storage, P EI (t) represents the amount of electricity to be stored, C H2 C H C EO P represents the benefits of hydrogen supply, heating, and electricity supply, respectively. H2 (t), P H (t), P EO(t) represent hydrogen supply power, heating power, and electricity supply power, respectively.

[0127] The constraints are centered on power constraints, while also covering safety and operational boundary constraints.

[0128] 1) Capacity Limitation

[0129] ;

[0130] ;

[0131] ;

[0132] ;

[0133] Among them, E P2G For the capacity of the P2G hydrogen production unit, E SH2 For the capacity of the hydrogen storage tank, E FE For fuel cell capacity, E EB Here, a represents the capacity of the electric boiler, b represents the capacity limit of the P2G hydrogen production unit (determined by both hydrogen load and electrical load), c represents the capacity limit of the hydrogen storage tank (determined by hydrogen load), and d represents the capacity limit of the fuel cell (determined by electrical load).

[0134] 2) Operating power limit

[0135] Based on different operating conditions of EHH-MESS, operating constraints are given according to the power balance equation. Define P... E For the total active power output of new energy sources, P P2G P SH2 P FE P EB P represents the active power of the hydrogen production unit, hydrogen storage tank, fuel cell, and electric boiler, respectively. L This refers to the active power demand on the load side of the power grid.

[0136] (1) When the total output of new energy sources exceeds the power demand of the grid, the fuel cell does not operate and stores electrical energy. In this case, the operating constraints described by EHH-MESS are:

[0137] ;

[0138] At this point, EHH-MESS provides heat and hydrogen based on the demand for heat and hydrogen loads through the storage and conversion of electrical energy.

[0139] (2) When the total output of new energy sources is lower than the grid-side power load demand, fuel cells will be used to supplement the power shortage. In this case, the EHH-MESS operating constraints are described as follows:

[0140] ;

[0141] Among them, V FC V is the operating parameter of the fuel cell. FCmin and V FCmax These represent the upper and lower limits of fuel cell operation. If the fuel cell cannot meet the power shortage demand, power balancing must be achieved through the frequency regulation unit in the power grid system.

[0142] (3) When the total output of new energy sources equals the power demand of the grid-side load, the fuel cell stops working. At this time, the operating constraints described by EHH-MESS take effect.

[0143] ;

[0144] At this time, if the EHH-MESS system has excess energy, it can supply heat and hydrogen to the system according to the needs of heat load and hydrogen load.

[0145] A smart optimization algorithm is used to solve the multi-energy complementary integrated energy system model. During the solution process, a "disturbance prediction and compensation" mechanism is introduced, taking into account the dynamic changes in real-time operating data (such as fluctuations in renewable energy output and sudden load changes).

[0146] Step S107: Based on the generated anti-disturbance cooperative control strategy, the central control system issues precise charging and discharging commands, start / stop commands, and power supply commands to each device in the multi-element energy storage system.

[0147] The energy storage device sends out the target charging / discharging power and SOC control threshold.

[0148] For the electrical energy to thermal energy / hydrogen energy conversion device, issue the target conversion power and operating status command;

[0149] For thermal / hydrogen energy storage devices, issue commands for the target charging / discharging rate.

[0150] At the same time, the execution status of instructions from each device and system operation data are monitored in real time. If there is a deviation between the actual operating status and the strategy (such as insufficient power due to a failure of a certain energy storage device), secondary optimization is immediately triggered to dynamically adjust the instructions, ensuring that the multi-energy storage system always operates in coordination, and ultimately achieving real-time power balance to resist disturbances such as fluctuations in new energy output and load changes.

[0151] Through a closed-loop process of "real-time data acquisition - disturbance prediction - multi-device collaborative control", it can quickly respond to fluctuations in new energy output (such as the intermittency of photovoltaic and wind power) and sudden changes in user load, avoid system power imbalance caused by the failure of a single energy storage device, and significantly improve the stability and risk resistance of multi-energy storage system operation.

[0152] With "minimum total operating cost" as the objective function, the system integrates start-up and shutdown costs, maintenance costs, and energy supply revenue. Through intelligent algorithms, it optimizes the operation strategies of each device to achieve "peak-valley arbitrage" and "multi-energy complementary energy supply." This maximizes the system's economic benefits and reduces long-term operating costs while meeting users' energy needs.

[0153] By constructing a multi-energy complementary model, the barriers between energy flows such as electricity, heat, and hydrogen are broken down, and energy conversion and storage paths are optimized (such as prioritizing the conversion of excess new energy electricity into thermal / hydrogen energy storage to avoid wind and solar curtailment), thereby improving the comprehensive energy utilization efficiency and promoting the upgrade of diversified energy storage systems from "single energy supply" to "multi-energy synergy".

[0154] By imposing strict power and energy storage capacity constraints, overcharging / over-discharging and over-power operation of each device are avoided, reducing equipment wear and tear. At the same time, optimizing start-up and shutdown frequencies and maintenance strategies reduces the probability of device failure and effectively extends the service life of core equipment such as energy storage and hydrogen conversion.

[0155] This method can flexibly connect to new energy power generation and diversified energy needs of users, providing stable energy storage support for new power systems (high proportion of new energy and high proportion of power electronics) and reducing dependence on fossil fuels.

[0156] Further, step S105 involves solving the multi-energy complementary integrated energy system model to generate a disturbance-resistant cooperative control strategy, specifically including the following steps:

[0157] Step S1051: Sum the gains based on the difference between the initial operating state and the operating state of the system to obtain the deviation value of the system adjustment process.

[0158] Step S1053: Construct system performance indicators based on the energy storage and release power of the energy storage device, the conventional revenue matrix, the conventional capacity matrix, and the deviation value of the system regulation process.

[0159] Step S1055: Construct a solution model based on system performance indicators.

[0160] Step S1057: Optimize the multi-energy complementary integrated energy system model based on the solution model to generate an energy storage strategy.

[0161] Step S1059: Generate an anti-disturbance cooperative control strategy based on the energy storage strategy.

[0162] The EHH-MESS operating state at time point i is described by the following formula:

[0163] ;

[0164] in, This represents the operating rate of the energy storage and conversion devices in the EHH-MESS system at time i, including parameters such as hydrogen state of charge, thermoelectric state, and energy conversion power; p i,E This indicates the energy storage and release power of each energy storage device; Indicates the operating status of the energy conversion equipment; This indicates the energy state of the conversion device.

[0165] Based on the different operating states of the electrothermal hydrogen energy conversion device, the flexible electro-thermal-hydrogen conversion in the EHH-MESS system can be described as follows:

[0166] ;

[0167] in, , , These represent the operating rates of P2G, fuel cells, and electric boilers, respectively.

[0168] Energy status of each energy storage device in EHH-MESS Described by the following formula:

[0169] ;

[0170] Among them, g SH2 (x) represents the state of hydrogen and electrical energy; g SH (x) represents the state of thermal energy and electrical energy.

[0171] Deviation in the system adjustment process Defined as:

[0172] ;

[0173] Where K is the coupling adjustment gain of the electrothermal hydrogen energy conversion device in EHH-MESS, x0, x i x j These represent the initial running state, running state i, and running state j of the system, respectively.

[0174] The system performance index i is obtained through the following methods:

[0175] ;

[0176] in, This is the standard return matrix for EHH-MESS. It is the standard capacity matrix of EHH-MESS.

[0177] Based on the necessary conditions of optimal control principle, the system energy storage strategy is obtained through the following formula. .

[0178] ;

[0179] Based on the economic efficiency of EHH-MESS and its flexibility in grid regulation, and by combining the energy conversion characteristics of EHH-MESS with the energy input and output characteristics of the entire energy storage system, collaborative optimization control of EHH-MESS can be achieved.

[0180] The superconducting magnetic energy storage device includes a bridge circuit.

[0181] The superconducting magnetic energy storage device consists of a Y-Δ connected 500 kV / 5 kV transformer, an AC / DC thyristor-controlled bridge converter, and a 0.5 H superconducting coil or inductor. The converter applies positive and negative voltages to the superconducting coil. Charging and discharging are easily controlled by simply changing the delay angle that controls the sequential conduction of the thyristors. When the delay angle is less than 90°, the converter is in rectification mode (charging); when the delay angle is greater than 90°, the converter switches to inverter mode (discharging). This allows energy to be absorbed or released from the grid as needed. During steady-state operation, the superconducting energy storage system should not consume any active or reactive power.

[0182] During the initial charging process of the SMES device, the V of the bridge circuit... sm The voltage is maintained at a constant positive value. The inductor current I... sm The current increases exponentially, and magnetic energy is stored in the inductor accordingly. When the inductor current reaches its rated value I... sm0 At this time, the current is maintained constant by reducing the voltage across the inductor to zero. The SMES unit can then be connected to a multi-energy storage system for stable regulation. Ideally, the rated inductor current should be set so that the maximum permissible energy absorption equals the maximum permissible energy release.

[0183] ;

[0184] Among them, V sm0 This is the ideal no-load maximum DC voltage for a bridge circuit. The current-voltage relationship of a superconducting inductor is as follows:

[0185] ;

[0186] Among them, I sm0 The initial current of the inductor. The actual power P absorbed or released by the superconducting magnetic energy storage device. sm It can be given by the following formula:

[0187] ;

[0188] Because the bridge current is irreversible, the bridge output power depends solely on a parameter, and its sign depends on that parameter. When the parameter is positive, power is transferred from the grid to the superconducting energy storage device; when the parameter is negative, power is released from the superconducting energy storage device. The energy stored in the superconducting sensor is...

[0189] ;

[0190] in, It is the initial energy in the inductor.

[0191] The following assumptions were considered when modeling the current SMES element:

[0192] 1) The superconducting coil has a large inductance, so the effect of DC ripple can be ignored;

[0193] 2) The resistance of the superconducting coil is zero;

[0194] 3) The voltage drop across the inverter thyristors is negligible;

[0195] 4) The harmonic power generated by the inverter is negligible.

[0196] Fuzzy logic differs from "clear logic" in Boolean theory, which uses only two logical levels (0 and 1). It is a branch of logic that acknowledges an infinite number of logical levels (from 0 to 1) and is used to solve problems involving uncertainty or imprecision. Fuzzy control is a process control method based on fuzzy logic, typically characterized by the "IF-THEN" rule. The design of the proposed fuzzy logic controller (FLC) will be described below.

[0197] A. Blurring

[0198] The fuzzification process involves finding suitable membership functions to describe the precise data. In designing the proposed fuzzy logic controller, the speed deviation of the synchronous generator is considered. The thyristor firing angle is selected as the input and output variables. Let be the trigonometric membership function, where linguistic variables N, Z, and P represent negative, zero, and positive values, respectively. To obtain optimal system performance, a trial-and-error method was used to determine the membership function. The trigonometric membership function equation used to determine the membership level is as follows:

[0199] ;

[0200] in, "b" represents the membership value, "a" represents the width, "x" represents the coordinates of the point with a membership degree of 1, and "x" represents the value of the input variable.

[0201] B. Fuzzy rule base

[0202] The rule base is the core of the fuzzy controller, as the control strategy for controlling the closed-loop system is stored therein as a set of control rules. The unique feature of the proposed fuzzy controller lies in its extremely simple design—containing only one input variable and one output variable. The use of a single-input single-output (SISO) variable makes the fuzzy controller highly intuitive. The membership function of the output variable consists of three single-element fuzzy sets: SMALL, MEDIUM, and BIG. The control rules of the proposed controller are determined based on the perspective of actual system operation and through a trial-and-error method.

[0203] C. Fuzzy reasoning

[0204] The basic operation of an inference engine is to perform reasoning, that is, to deduce logical conclusions based on evidence or data. In essence, an inference engine is a program that uses a rule base and input data from the controller to draw conclusions. The conclusion of the inference engine is the fuzzy output of the controller, which then becomes the input to the defuzzification interface. The Mamdani method is employed in the inference mechanism of the proposed Fuzzy Logic Controller (FLC). Fuzzy rules typically have the following "IF-THEN" format:

[0205]

[0206] Where X1 and X2 are fuzzy input variables; Z1 is a fuzzy output variable. i It is the rule number. r It is the total number of rules, A i B i and C i These are fuzzy subsets of the discussion sets X, Y, and Z, respectively. Therefore, according to Mamdani theory, the conformity W of each fuzzy rule... i as follows:

[0207] ;

[0208] in, and These are the membership degree values.

[0209] D. Deblurring

[0210] In the final step, the fuzzy conclusions of the inference engine are defuzzified, i.e., converted into precise signals. This final signal is the output of the fuzzy logic controller (FLC), and naturally, the precise control signal transmitted to the process. The region center method, as the most well-known and relatively simple defuzzification method, is used to determine the precise output value. Its calculation formula is as follows:

[0211] ;

[0212] Where Z is the exact output function, C i It has been defined in the previous section.

[0213] To verify the effect of fuzzy control SMES unit on improving transient stability, its performance was compared with that of traditional PI control SMES scheme. The PI controller parameters were determined through repeated experiments to obtain good system performance.

[0214] On the other hand, the present invention also provides a disturbance rejection and cooperative control system for a multi-element energy storage system, comprising:

[0215] The multi-element energy storage system includes energy conversion and storage devices, which include electrical-thermal energy conversion devices, electrical-hydrogen energy conversion devices, electrical energy storage devices, thermal energy storage devices, hydrogen energy storage devices, and superconducting magnetic energy storage devices. Real-time operating data includes new energy output, electrical, thermal, and hydrogen loads, and power limitations.

[0216] The data processing module communicates with the multi-energy storage system to construct a multi-energy complementary integrated energy system model based on the real-time operating data of the multi-energy storage system. The multi-energy complementary integrated energy system model includes a constraint-based objective function for the minimum total operating cost of the multi-energy complementary integrated energy system. The minimum total operating cost includes start-up and shutdown costs, maintenance costs, electricity storage benefits, and energy release benefits from power supply, heating, and hydrogen supply. The constraints include power constraints. The data processing module solves the multi-energy complementary integrated energy system model, generates an anti-disturbance collaborative control strategy, and sends charging and discharging commands to the multi-energy storage system based on the anti-disturbance collaborative control strategy to control the collaborative operation of the multi-energy storage system and achieve real-time power balance of the multi-energy storage system.

[0217] This invention proposes an electro-thermal-hydrogen multi-energy storage system topology (EHH-MESS) for accessing a multi-energy network. This system utilizes electro-thermal-hydrogen conversion technology to replace battery energy storage systems, aiming to improve grid regulation flexibility, promote the consumption of new energy sources, and reduce system operating costs. Based on this architecture, this invention further introduces a thyristor-controlled superconducting magnetic energy storage system (SMES) to enhance the power system's disturbance rejection performance and transient stability. Finally, based on the proposed method, a disturbance rejection collaborative control method for multi-energy storage systems based on multi-objective optimization is proposed, realizing the coordinated operation of multiple energy storage forms such as electricity, heat, hydrogen, and superconducting magnetic energy storage, effectively improving the system's dynamic response capability and overall stability under complex operating conditions.

[0218] On the other hand, the present invention also proposes a medium storing a computer program, which, when executed by a processor, implements a disturbance-resistant collaborative control method for a multi-element energy storage system.

[0219] Computer storage media may be simply referred to as media. Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Dual Data SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), Rambus Direct RAM (RDRAM), Direct Memory Bus Dynamic RAM (DRDRAM), and Memory Bus Dynamic RAM (RDRAM). The various embodiments described in this specification are presented in a progressive manner, with reference allowed to each other for similar or identical parts. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments for apparatuses, devices, and non-volatile computer storage media are described simply because they are substantially similar to the method embodiments; relevant details can be found in the descriptions of the method embodiments.

[0220] The above embodiments are merely illustrative examples and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A disturbance-resistant collaborative control method for a multi-element energy storage system, characterized in that, include: The system acquires real-time operational data of a multi-energy storage system, which includes energy conversion and storage devices, such as an electrical-thermal energy conversion device, an electrical-hydrogen energy conversion device, an electrical energy storage device, a thermal energy storage device, a hydrogen energy storage device, and a superconducting magnetic energy storage device. The real-time operational data includes new energy output, electrical, thermal, and hydrogen loads, and power limitations. Based on the real-time operating data, a multi-energy complementary integrated energy system model is constructed. The multi-energy complementary integrated energy system model includes a minimum total operating cost objective function based on constraints. The minimum total operating cost includes start-up and shutdown costs, maintenance costs, electricity storage benefits, and energy release benefits from power supply, heating, and hydrogen supply. The constraints include power constraints. Solve the multi-energy complementary integrated energy system model to generate an anti-disturbance cooperative control strategy; Based on the aforementioned anti-disturbance collaborative control strategy, charging and discharging commands are sent to the multi-element energy storage system to control its collaborative operation and achieve real-time power balance.

2. The disturbance rejection and cooperative control method for a multi-element energy storage system according to claim 1, characterized in that, Based on the aforementioned real-time operational data, a multi-energy complementary integrated energy system model is constructed, specifically including: An electro-hydrogen energy conversion and storage model is constructed based on the real-time operating data. The electro-hydrogen energy conversion and storage model includes a hydrogen storage model. The real-time operating data includes the efficiency limit of the hydrogen production process, the capacity limit of the total hydrogen energy in the gas network, the total hydrogen energy, and the hydrogen generation rate. A model of a thermal storage device is constructed using a model of an electric boiler converting electrical energy into thermal energy. The output voltage of a single cell is constructed based on the chemical reaction equations of a fuel cell; An electric-thermal-hydrogen power balance model is constructed based on a general input-coupling-output model for multi-energy systems. The multi-energy complementary integrated energy system model is constructed based on the electro-hydrogen energy conversion and storage model, the single-cell battery output voltage, the thermal storage device model, and the electro-thermal-hydrogen power balance model.

3. The disturbance rejection and cooperative control method for a multi-element energy storage system according to claim 2, characterized in that, Based on the real-time operating data, an electro-hydrogen energy conversion and storage model is constructed. This model includes a hydrogen storage model, specifically comprising: A hydrogen production power model is constructed based on the minimum of the efficiency constraints of the hydrogen production process and the capacity constraints of the gas network. The total amount of hydrogen energy input to a specific node is calculated based on the hydrogen production power model. The hydrogen storage model is constructed based on the total amount of hydrogen energy input to a specific node via the electro-hydrogen conversion.

4. The disturbance rejection and cooperative control method for a multi-element energy storage system according to claim 3, characterized in that, The hydrogen storage model includes the amount of hydrogen stored, which is the time integral of the hydrogen generation rate.

5. The disturbance rejection and cooperative control method for a multi-element energy storage system according to claim 2, characterized in that, The thermal energy storage device model includes the thermal energy storage capacity at the previous moment, the heat absorption power at a given moment, the heat absorption efficiency, and the thermal energy storage capacity.

6. The disturbance rejection and cooperative control method for a multi-element energy storage system according to claim 2, characterized in that, The electro-thermal-hydrogen power balance model includes electrical output power, thermal output power, and hydrogen output power.

7. The disturbance rejection cooperative control method for a multi-element energy storage system according to any one of claims 1 to 6, characterized in that, The superconducting magnetic energy storage device includes a bridge circuit.

8. The disturbance rejection cooperative control method for a multi-element energy storage system according to any one of claims 1 to 6, characterized in that, Solving the multi-energy complementary integrated energy system model and generating a disturbance-resistant cooperative control strategy specifically includes: The deviation value of the system adjustment process is obtained by summing the gains based on the difference between the initial operating state and the operating state. The system performance index is constructed based on the energy storage and release power of the energy storage device, the conventional revenue matrix, the conventional capacity matrix, and the deviation value of the system adjustment process. A solution model is constructed based on the system performance indicators; Based on the solution model, the multi-energy complementary integrated energy system model is optimized to generate an energy storage strategy; The disturbance-resistant cooperative control strategy is generated based on the energy storage strategy.

9. A disturbance-resistant collaborative control system for a multi-element energy storage system, characterized in that, include: A multi-energy storage system includes energy conversion and storage devices, which include an electrical-thermal energy conversion device, an electrical-hydrogen energy conversion device, an electrical energy storage device, a thermal energy storage device, a hydrogen energy storage device, and a superconducting magnetic energy storage device. The real-time operating data includes new energy output, electrical, thermal, and hydrogen loads, and power limitations. The data processing module is communicatively connected to the multi-energy storage system. It constructs a multi-energy complementary integrated energy system model based on the real-time operating data of the multi-energy storage system. This model includes a constraint-based objective function for minimizing the total operating cost of the multi-energy complementary integrated energy system. The minimum total operating cost includes start-up and shutdown costs, maintenance costs, electricity storage benefits, and energy release benefits from power supply, heating, and hydrogen supply. The constraints include power constraints. The data processing module solves the multi-energy complementary integrated energy system model, generates an anti-disturbance collaborative control strategy, and sends charging and discharging commands to the multi-energy storage system based on this strategy to control its collaborative operation and achieve real-time power balance.

10. A medium, characterized in that, The system contains a computer program that, when executed by a processor, implements the disturbance-resistant collaborative control method for a multi-element energy storage system as described in any one of claims 1 to 8.

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