Steam heat release method and system for branching type modular fused salt energy storage

Abstract

The invention discloses a steam heat release method and system for tapping modular fused salt energy storage, and relates to the field of fused salt energy storage.The steam heat release method comprises the steps that an energy storage unit composed of a plurality of vertically-stacked fused salt modules is constructed, and a dynamically-switched series access is formed through opening and closing control over an inlet valve and an outlet valve; predicting module outlet steam temperature based on a neural network model, determining the number of modules connected in series and feed water flow, and opening a corresponding valve combination to start heat release; and the outlet steam temperature is kept stable by dynamically switching the series module sequence and adjusting the water flow, and heat release is stopped until the remaining modules cannot meet the lowest temperature requirement. The number and combination of the fused salt modules can be adjusted at will, and the operation flexibility of the system is improved; through a model of an Elman neural network, the water supply flow is predicted and rapidly adjusted, and it is ensured that the temperature of generated steam is stable; through continuous flow adjustment and adjustment of removal and input of the molten salt modules, the storage temperature of all the molten salt modules is released to the maximum extent.

Description

Technical Field

[0001] The present invention relates to the technical field of molten salt energy storage, and in particular to a steam heat release method and system for tapped modular molten salt energy storage. Background Art

[0002] Molten salt energy storage technology is a highly efficient thermal energy storage solution that is widely used in solar thermal power plants and other applications requiring large-scale thermal energy storage. Molten salt, primarily a mixture of sodium nitrate and potassium nitrate, remains liquid at high temperatures and has a high specific heat capacity and good thermal stability. During the energy storage process, the molten salt is pumped into the collector to absorb solar radiation energy, heating it to over 550°C. Subsequently, the high-temperature molten salt is stored and released when needed to generate steam, which in turn drives turbines to generate electricity, or directly supplies steam and heat. This energy storage method not only smoothes the power supply, but also significantly improves the utilization efficiency of renewable energy, especially at night or on cloudy days when solar energy cannot be directly utilized.

[0003] The modular molten salt system is a new type of molten salt energy storage device. Each unit is composed of multiple flat modules stacked vertically. Each module serves as both a storage space for the molten salt and houses heat exchange coils that convert incoming water into high-temperature, high-pressure steam. The inlets and outlets of the heat exchange coils between each module are connected in series via external piping, ultimately integrating all modules into a unified whole.

[0004] The modular molten salt energy storage system design allows for on-demand expansion of storage capacity, offering a high degree of flexibility. Each storage unit operates independently, simplifying installation and maintenance while improving overall system reliability. Furthermore, the modular design allows the molten salt energy storage system to better adapt to energy storage needs of varying scales, enabling both small commercial facilities and large power companies to find suitable configurations. This approach reduces initial investment costs and allows for the system to be expanded over time as demand grows. Summary of the Invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] Therefore, the technical problem solved by the present invention is: how to ensure the stability and efficiency of steam temperature by precisely controlling the heat release process in the molten salt energy storage system, while being able to dynamically adjust the number of molten salt modules in series and the water flow rate according to different operating requirements, thereby improving the thermal energy utilization efficiency of the system and avoiding problems such as temperature fluctuations and energy efficiency loss in existing systems.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: a steam heat release method for tapped modular molten salt energy storage, which comprises the following steps:

[0008] Construct an energy storage unit consisting of multiple vertically stacked molten salt modules, each with a heat exchange coil inside, and a dynamically switched series path formed by opening and closing the inlet and outlet valves;

[0009] The module outlet steam temperature is predicted based on the neural network model, the number of series modules and feedwater flow that meet the preset temperature requirements are determined, and the corresponding valve combination is opened to start heat release;

[0010] The module temperature is monitored in real time, and the outlet steam temperature is maintained stable by dynamically switching the series module sequence and adjusting the water flow until the heat release is terminated when the remaining modules cannot meet the minimum temperature requirement.

[0011] As a preferred solution of the steam heat release method of a tapped modular molten salt energy storage described in the present invention, the dynamically switched series path is that the heat exchange coil outlet of the current molten salt module is connected to the heat exchange coil inlet of the next layer of molten salt module through an external pipeline, and the inlet and outlet of each module are respectively configured with independent inlet valves and outlet valves, and a series path is formed by opening the inlet valve of the first module and the outlet valve of the last module.

[0012] As a preferred solution of the steam heat release method of the tapped modular molten salt energy storage described in the present invention, wherein: the neural network model is an Elman neural network model;

[0013] An Elman neural network model for a single molten salt module is established to predict the output under actual input conditions. The input layer is the inlet water temperature, water flow rate, and molten salt temperature of a single molten salt module, and the output layer is the steam temperature at the outlet of the molten salt module. The expression is:

[0014]

[0015] in, is the hidden layer output at time k, n is the number of nodes in the hidden layer and the receiving layer; The number of input layer nodes is 3; is the hidden layer threshold, is the weight matrix between the input layer and the hidden layer, is the weight matrix between the hidden layer and the connecting layer, is the receiving layer node, is the output at time k, and α is the feedback gain;

[0016] Among them, y(k) is the output, is the weight matrix between the hidden layer and the output layer, b y is the output layer threshold.

[0017] As a preferred solution of the steam heat release method of the tapped modular molten salt energy storage described in the present invention, the hidden layer activation function of the Elman neural network is a Sigmoid function, and the output layer activation function is a linear function.

[0018] As a preferred solution of the steam heat release method of the tapped modular molten salt energy storage described in the present invention, the number of modules in series that meet the preset temperature requirements is determined by predicting the outlet temperature layer by layer starting from the bottom molten salt module. If the predicted temperature after the q-1th layer in series is lower than the preset temperature requirement, and the predicted temperature after the qth layer in series exceeds the preset temperature requirement for the first time, the number of modules finally put into series operation is q-1, and the water supply flow rate is adjusted to meet the predicted flow rate when q-1 modules are connected in series.

[0019] As a preferred solution of the steam heat release method of the tapped modular molten salt energy storage described in the present invention, the dynamic water flow regulation is to control the speed of the water pump through the frequency converter, and adjust the water flow in real time so that the predicted outlet temperature of the series operation module is equal to the preset temperature requirement.

[0020] As a preferred solution of the steam heat release method of the tapped modular molten salt energy storage described in the present invention, the dynamic switching of the series module sequence is that when the molten salt temperature of the bottom module in the current series sequence is lower than the melting point temperature plus a safety margin, the inlet valve of the bottom module and the outlet valve of the last module in the current series sequence are closed, and the inlet valve of the next bottom module and the outlet valve of the new last module are opened at the same time.

[0021] Another object of the present invention is to provide a tap-type modular molten salt energy storage steam heat release system, which can solve the existing problems of unstable steam temperature, low energy efficiency and over-reliance on fixed series modules through real-time steam temperature prediction and dynamic adjustment of valve opening and closing, water flow and switching of series module sequences based on a neural network model.

[0022] In order to solve the above technical problems, the present invention provides the following technical solutions: a tapped modular molten salt energy storage steam heat release system, comprising: a molten salt module, a valve module, a water flow control module, and a neural network prediction module;

[0023] The molten salt module is responsible for storing and releasing heat. Each module is equipped with a heat exchange coil for heat exchange. The temperature change of the molten salt module affects the steam release process.

[0024] Using multiple vertically stacked molten salt modules, the temperature of each module is adjusted according to demand to achieve efficient heat energy release;

[0025] The valve module includes an inlet valve and an outlet valve for each molten salt module, which controls the fluid flow path and water flow. By opening or closing the valve, the series path is dynamically switched;

[0026] The inlet valve controls the flow of water into the molten salt module, and the outlet valve controls the outflow of steam. The opening and closing of the valve are dynamically adjusted according to the temperature of the molten salt module and the preset steam temperature.

[0027] The water flow control module controls the change of water flow to ensure that the water flow matches the heat exchange capacity of the molten salt module. The water pump and the frequency converter work together to maintain a stable outlet steam temperature by adjusting the water flow in real time.

[0028] The neural network prediction module predicts the steam temperature and determines the appropriate number of modules in series and the feed water flow rate based on the input conditions through the neural network model.

[0029] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the steam heat release method of the tapped modular molten salt energy storage are implemented.

[0030] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the steam heat release method of the tapped modular molten salt energy storage as described above.

[0031] Beneficial effects of the present invention: The present invention can arbitrarily adjust the number and combination of molten salt modules through the combination of multiple switching valves, greatly improving the operational flexibility of the system; by establishing an Elman neural network model, the water feed flow rate can be quickly adjusted in a predictive manner to ensure the temperature stability of the generated steam; through continuous flow adjustment and adjustment of the cut-off of molten salt modules, the temperature stored in all molten salt modules can be released to the maximum extent, thereby improving the overall utilization rate of the molten salt energy storage device. When a molten salt module fails, such as when the internal coil leaks, the module can be quickly cut off by switching the valve. After cutting off, the system can still continue to release heat through other modules. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0033] Figure 1 An overall flow chart of a steam heat release method for a tapped modular molten salt energy storage provided by the first embodiment of the present invention;

[0034] Figure 2 A schematic diagram of the integrated operation of multiple lava modules in a steam heat release method for a tapped modular molten salt energy storage system according to a first embodiment of the present invention;

[0035] Figure 3 Schematic diagram of an Elman neural network model for a steam heat release method for a tapped modular molten salt energy storage provided in the first embodiment of the present invention. DETAILED DESCRIPTION

[0036] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0037] Example 1, with reference to Figures 1 to 3 According to one embodiment of the present invention, a method for releasing heat from steam in a tapped modular molten salt energy storage system is provided, comprising:

[0038] Construct an energy storage unit consisting of multiple vertically stacked molten salt modules, each with a heat exchange coil inside, and form a dynamically switched series path through the opening and closing control of the inlet and outlet valves;

[0039] The module outlet steam temperature is predicted based on the neural network model, the number of series modules and feedwater flow that meet the preset temperature requirements are determined, and the corresponding valve combination is opened to start heat release;

[0040] The module temperature is monitored in real time, and the outlet steam temperature is maintained stable by dynamically switching the series module sequence and adjusting the water flow until the heat release is terminated when the remaining modules cannot meet the minimum temperature requirement.

[0041] It should be further explained that:

[0042] Construct an energy storage unit consisting of multiple vertically stacked molten salt modules, each with a heat exchange coil inside, and a dynamically switched series path formed by opening and closing the inlet and outlet valves;

[0043] The module outlet steam temperature is predicted based on the neural network model, the number of series modules and feedwater flow that meet the preset temperature requirements are determined, and the corresponding valve combination is opened to start heat release;

[0044] Real-time monitoring of the temperature of each molten salt module. When the temperature of the bottom module in the series operation sequence falls below the set threshold, the series module sequence is dynamically switched and the water flow is adjusted to maintain a stable outlet steam temperature.

[0045] When the predicted outlet temperature of the remaining modules is lower than the preset requirement and the water flow rate reaches the minimum value, heat release is terminated and all valves and water pumps are closed.

[0046] The dynamically switched series path is that the heat exchange coil outlet of the current molten salt module is connected to the heat exchange coil inlet of the next layer of molten salt module through an external pipeline, and the inlet and outlet of each module are respectively equipped with independent inlet valves and outlet valves. The series path is formed by opening the inlet valve of the first module and the outlet valve of the last module.

[0047] It should be further explained that:

[0048] Reference Figure 2 The molten salt energy storage unit is composed of p molten salt modules stacked vertically. The heat exchange coils within each molten salt module are connected via external piping valves, forming a modular connection method. Specifically, the lower inlet of each molten salt module's heat exchange coil passes through an inlet valve and is then connected to the main pipe to the feedwater pump inlet. The upper outlet of each molten salt module's heat exchange coil passes through an outlet valve and is then connected to the main steam supply pipe. The outlet of each molten salt module is connected to the inlet pipe of the molten salt module one level above.

[0049] Figure 2 In the figure, Vp.i is the inlet valve, Vp.o is the outlet valve, each molten salt module has a temperature measuring point Tp, the total inlet feed water and outlet steam have temperature measuring points Ti and To, and the feed water pump has a flow measuring point L.

[0050] When the molten salt energy storage system releases heat, it activates the water pump. Using valve control, water can be directed through any number of consecutive molten salt modules for heat exchange. Simply open the inlet valve of the first module and the outlet valve of the last module, while keeping all other valves closed. For example, to direct water through only the second molten salt module for heat exchange, simply open the inlet valve V2.i and outlet valve V2.o of the second molten salt module, while keeping all other valves closed. To direct water through only the third, fourth, and fifth molten salt modules for heat exchange, simply open the inlet valve V2.i of the third module and the outlet valve V5.o of the fifth module.

[0051] Reference Figure 3 , Based on the neural network model to predict the module outlet steam temperature, the Elman neural network model of a single molten salt module is first established to predict the output under actual input conditions. The neural network model is as follows Figure 2 As shown in the figure, the input layer is the inlet water temperature, water flow rate, and molten salt temperature of a single molten salt module, which are denoted as u1, u2, and u3. The output layer is the steam temperature at the outlet of the molten salt module, which is denoted as y.

[0052]

[0053] in: is the hidden layer output at time k, n is the number of nodes in the hidden layer and the receiving layer; The number of input layer nodes is 3; is the hidden layer threshold;

[0054] is the weight matrix between the input layer and the hidden layer, is the weight matrix between the hidden layer and the connecting layer, is the receiving layer node,

[0055]

[0056] in, is the output at time k, and α is the feedback gain.

[0057]

[0058] Among them, y(k) is the output, is the weight matrix between the hidden layer and the output layer, b y is the output layer threshold.

[0059] The above formulas establish a mathematical model from input to output, and then use the error correction learning algorithm to calculate the weights and thresholds. The output of the neural network is y(k), and the expected value is The objective function is:

[0060]

[0061] Network learning is to continuously iterate and calculate Right now Minimize the objective function.

[0062] The weight matrix is updated as follows:

[0063]

[0064] μ is the learning rate.

[0065] The correction calculation formulas are:

[0066]

[0067] Where j = 1, 2, ..., n, q = 1, 2, ..., r, l = 1, 2, ..., n, r is the number of input layer nodes 3, n is the number of hidden layer nodes. m is the number of output layer nodes 1.

[0068] Starting from the bottom molten salt module, the outlet temperature is predicted layer by layer in series. If the predicted temperature after the q-1th layer in series is lower than the preset temperature requirement, and the predicted temperature after the qth layer in series exceeds the preset temperature requirement for the first time, the number of modules finally put into series operation is q-1, and the water supply flow rate is adjusted to meet the predicted flow rate when q-1 modules are connected in series.

[0069] It should be further explained that:

[0070] When the molten salt energy storage system is fully charged with heat and all molten salt modules are already at a high temperature, they are about to release heat through heat exchange between water and the molten salt modules and enter the heat release operation state. Based on the Elman neural network model of a single molten salt module obtained in the above section, a prediction method is used in the heat release operation startup phase. When the operator specifies the required final outlet steam temperature, the control system automatically calculates the number of molten salt modules required, opens and closes the corresponding valves, and puts the estimated number of molten salt modules into operation. This allows the system to be put into operation quickly and enter a stable operating state. The specific method is as follows:

[0071] (1) First, the prediction is made starting from the first layer of molten salt module at the bottom. The inlet water temperature, water flow rate (the flow rate when the water pump is running at maximum output) and the temperature of the molten salt in the first layer of module are input into the Elman neural network model of a single molten salt module. The steam temperature at the outlet of the first layer of molten salt module can be predicted.

[0072] (2) When the system's final required steam temperature is not reached, the first layer outlet temperature is used as the second layer inlet temperature, that is, the first and second layers of molten salt modules are operated in series, and the second layer outlet steam temperature is predicted. If the temperature is still insufficient, the third, fourth, and subsequent molten salt modules are added in sequence to join the series operation sequence until the number of modules put in is sufficient to make the predicted outlet steam temperature exceed the required temperature for the first time. The number of molten salt modules that need to be put in at this time is calculated as q;

[0073] (3) Since the increase or decrease in the number of molten salt modules cannot continuously adjust the outlet temperature, the temperature is fine-tuned by controlling the water flow rate. The final number of modules put into operation is q-1. Since one molten salt module is reduced, the heat exchange amount is reduced, which will make the predicted outlet temperature slightly lower than the required temperature.

[0074] (4) When the number of modules put into operation is q-1, the water flow rate is gradually reduced and the outlet temperature is re-predicted until the predicted outlet temperature is equal to the required temperature. The water flow rate at this time is the initial water flow rate.

[0075] (5) Through the prediction algorithm of the first four steps, it has been calculated that the molten salt modules put into series operation are the first layer to the q-1 layer, and the water pump flow rate is calculated. At this time, the water pump is started, the inlet valve V1.i of the first layer and the outlet valve Vq-1.o of the q-1 layer are opened and closed, all other valves are closed, and the water flow rate is adjusted to the final predicted flow rate in the previous step through the water pump inverter, and the system is put into operation.

[0076] The effect achieved in this stage is: after the inlet water passes through the first q-1 molten salt modules at the predicted flow rate, the temperature accurately reaches the required value, and the system starts heat release operation at the fastest speed.

[0077] The speed of the water supply pump is controlled by the frequency converter, and the water flow is adjusted in real time so that the predicted outlet temperature of the series operation module is equal to the preset temperature requirement.

[0078] When the molten salt temperature of the bottom module in the current series sequence is lower than the melting point temperature plus the safety margin, the inlet valve of the bottom module and the outlet valve of the last module in the current series sequence are closed, and the inlet valve of the next bottom module and the outlet valve of the new last module are opened at the same time.

[0079] It should be further explained that:

[0080] When the system is just running, the lower q-1 layer of molten salt modules is put into use. As the heat release process proceeds, the temperature of each layer of molten salt continues to decrease. At this time, the control system continuously predicts the outlet temperature of the q-1 layer by reducing the water flow rate based on the real-time molten salt temperature of each layer of molten salt modules until the predicted temperature is equal to the required temperature, and then adjusts the water pump frequency according to the water flow rate obtained by real-time prediction.

[0081] When the molten salt temperature of the bottom molten salt module drops to a certain safety margin ΔT above the melting point of the molten salt (such as 10°C), in order to prevent the molten salt from solidifying and blocking, the bottom first layer of the molten salt module is removed from the molten salt module sequence in series heat release operation, and a new molten salt module (the qth layer) is added from the upper layer to the heat release module sequence. The valve adjustment method is: close the inlet valve V1.i of the first layer and the outlet valve Vq-1.o of the q-1th layer, and open the inlet valve V2.i of the second layer and the outlet valve Vq.o of the qth layer at the same time. After the switch is completed, the temperature of the molten salt modules from the second to the qth layer now in the control system is re-predicted, and the water flow rate is calculated and quickly adjusted through the water pump inverter.

[0082] Referring to the above method, whenever the temperature of the lowest module in the series heat release operation sequence drops to the lowest temperature, the module is cut off and exits the heat release operation sequence, and the higher-level high-temperature molten salt module is added to enter the heat release operation sequence.

[0083] After the top-level molten salt module has been added to the heat release sequence, the molten salt modules added are from layers p-q+2 to p (the topmost layer). As the molten salt temperature decreases, each time the temperature of the module at the bottom of the current series heat release sequence falls below the melting point plus ΔT, the valve switches to exit that molten salt module. At this point, the series heat release sequence is reduced by one. The water flow rate is then reduced using a predictive algorithm to maintain the outlet steam temperature. As the number of molten salt modules in the series heat release sequence decreases, the temperature continues to drop, and the water flow rate reaches its minimum value, the predicted outlet steam temperature cannot reach the required temperature. This indicates that the molten salt energy storage system is no longer able to release steam to meet the required temperature. All valves and feedwater pumps are closed, and the heat release operation of the molten salt energy storage system is complete. The minimum water flow rate is determined by the minimum adjustable value of the water pump inverter. At this point, the water pump should be operating normally.

[0084] Example 2, an embodiment of the present invention, provides a system for a steam heat release method of a tapped modular molten salt energy storage, comprising: a molten salt module, a valve module, a water flow control module, and a neural network prediction module;

[0085] The molten salt module is responsible for storing and releasing heat. Each module is equipped with a heat exchange coil for heat exchange. The temperature change of the molten salt module affects the steam release process.

[0086] Using multiple vertically stacked molten salt modules, the temperature of each module is adjusted according to demand to achieve efficient heat energy release;

[0087] The valve module includes an inlet valve and an outlet valve for each molten salt module, which controls the fluid flow path and water flow. By opening or closing the valve, the series path is dynamically switched;

[0088] The inlet valve controls the flow of water into the molten salt module, and the outlet valve controls the outflow of steam. The opening and closing of the valve are dynamically adjusted according to the temperature of the molten salt module and the preset steam temperature.

[0089] The water flow control module controls the change of water flow to ensure that the water flow matches the heat exchange capacity of the molten salt module. The water pump and the frequency converter work together to maintain a stable outlet steam temperature by adjusting the water flow in real time.

[0090] The neural network prediction module predicts the steam temperature and determines the appropriate number of modules in series and the feed water flow rate based on the input conditions through the neural network model.

[0091] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0092] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0093] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0094] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0095] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A steam heat release method for tapped modular molten salt energy storage, characterized in that: include: Construct an energy storage unit consisting of multiple vertically stacked molten salt modules, each with a heat exchange coil inside, and a dynamically switched series path formed by opening and closing the inlet and outlet valves; The module outlet steam temperature is predicted based on the neural network model, the number of series modules and feedwater flow that meet the preset temperature requirements are determined, and the corresponding valve combination is opened to start heat release; The module temperature is monitored in real time, and the outlet steam temperature is maintained stable by dynamically switching the series module sequence and adjusting the water flow until the heat release is terminated when the remaining modules cannot meet the minimum temperature requirement.

2. The steam heat release method for tapped modular molten salt energy storage according to claim 1, characterized in that: The dynamically switched series path is that the heat exchange coil outlet of the current molten salt module is connected to the heat exchange coil inlet of the next layer of molten salt module through an external pipeline, and the inlet and outlet of each module are respectively equipped with independent inlet valves and outlet valves. The series path is formed by opening the inlet valve of the first module and the outlet valve of the last module.

3. The steam heat release method for tapped modular molten salt energy storage according to claim 2, characterized in that: The neural network model is an Elman neural network model; An Elman neural network model for a single molten salt module is established to predict the output under actual input conditions. The input layer is the inlet water temperature, water flow rate, and molten salt temperature of a single molten salt module, and the output layer is the steam temperature at the outlet of the molten salt module. The expression is: in, is the hidden layer output at time k, n is the number of nodes in the hidden layer and the receiving layer; r is the number of input layer nodes 3, is the hidden layer threshold, is the weight matrix between the input layer and the hidden layer, is the weight matrix between the hidden layer and the connecting layer, is the receiving layer node, is the output at time k, α is the feedback gain, y(k) is the output, is the weight matrix between the hidden layer and the output layer, b y is the output layer threshold.

4. The steam heat release method for tapped modular molten salt energy storage according to claim 3, characterized in that: The hidden layer activation function of the Elman neural network is a Sigmoid function, and the output layer activation function is a linear function.

5. The steam heat release method for tapped modular molten salt energy storage according to claim 4, characterized in that: The number of modules in series that meet the preset temperature requirement is determined by predicting the outlet temperature layer by layer starting from the bottom molten salt module. If the predicted temperature after the q-1th layer in series is lower than the preset temperature requirement, and the predicted temperature after the qth layer in series exceeds the preset temperature requirement for the first time, the final number of modules put into series operation is q-1, and the water supply flow rate is adjusted to the predicted flow rate when q-1 modules are connected in series.

6. The steam heat release method for tapped modular molten salt energy storage according to claim 5, characterized in that: The dynamic water flow regulation is to control the speed of the water pump through the frequency converter, and adjust the water flow in real time so that the predicted outlet temperature of the series operation module is equal to the preset temperature requirement.

7. The steam heat release method for tapped modular molten salt energy storage according to claim 6, characterized in that: The dynamic switching of the series module sequence is that when the molten salt temperature of the bottom module in the current series sequence is lower than the melting point temperature plus a safety margin, the inlet valve of the bottom module and the outlet valve of the last module in the current series sequence are closed, and the inlet valve of the next bottom module and the outlet valve of the new last module are opened at the same time.

8. A system using the steam heat release method of the tapped modular molten salt energy storage according to any one of claims 1 to 7, characterized in that: Including molten salt module, valve module, water flow control module, neural network prediction module; The molten salt module is responsible for storing and releasing heat. Each module is equipped with a heat exchange coil for heat exchange. The temperature change of the molten salt module affects the steam release process. Using multiple vertically stacked molten salt modules, the temperature of each module is adjusted according to demand to achieve efficient heat energy release; The valve module includes an inlet valve and an outlet valve for each molten salt module, which controls the fluid flow path and water flow. By opening or closing the valve, the series path is dynamically switched. The inlet valve controls the flow of water into the molten salt module, and the outlet valve controls the outflow of steam. The opening and closing of the valve are dynamically adjusted according to the temperature of the molten salt module and the preset steam temperature. The water flow control module controls the change of water flow to ensure that the water flow matches the heat exchange capacity of the molten salt module. The water pump and the frequency converter work together to maintain a stable outlet steam temperature by adjusting the water flow in real time. The neural network prediction module predicts the steam temperature and determines the appropriate number of modules in series and the feed water flow rate based on the input conditions through the neural network model.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the steam heat release method of the tapped modular molten salt energy storage according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the steam heat release method of the tapped modular molten salt energy storage according to any one of claims 1 to 7 are implemented.

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