Multi-source energy linkage heat storage method and system based on large-temperature-difference unit cascade heating

Abstract

The invention discloses a multi-source energy linkage heat storage method and system based on large-temperature-difference unit cascade heating, and belongs to the technical field of centralized heating and energy comprehensive utilization. The method comprises the steps that water inlet temperature parameters and external environment prediction parameters of a heat supply pipe network are obtained, and load demand characteristics are generated; establishing a dynamic optimization model according to the load demand characteristics and the obtained energy price time sequence parameters; operating parameters of the multi-stage heating unit group and scheduling parameters of the double-medium heat storage tank are calculated through the dynamic optimization model, and a multi-source scheduling instruction is generated; and the multi-source dispatching instruction is executed, and the self-adaptive valve set is controlled to switch a heat source path and is linked with the double-medium heat storage tank to charge and discharge heat. According to the method, the dynamic optimization model is established to cooperatively control the operation mode of the multi-stage heating unit set and the double-medium heat storage tank, cascade efficient utilization and intelligent economic dispatching of multi-source energy can be achieved, and the economical efficiency and the operation stability of the heat supply system are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of central heating and comprehensive utilization of energy, in particular to a multi-source energy linkage heat storage method and system based on cascade heating of large-temperature-difference units. BACKGROUND

[0002] Central heating is an important infrastructure for ensuring urban residents' lives and industrial production. With the advancement of energy structure transformation, the traditional single fossil fuel heating mode is facing challenges such as high cost, heavy pollution, and low energy efficiency. Therefore, integrating and utilizing various energies such as industrial waste heat, solar energy, and natural gas to build a multi-energy complementary regional heating system has become an important direction for the industry. This kind of system aims to improve the overall energy utilization efficiency and reduce the impact on the environment by coordinating the scheduling of different types of energy.

[0003] In the existing multi-source heating technology practice, a scheduling strategy based on fixed priority is usually adopted. The system will set priority to use industrial waste heat, switch to solar energy when the waste heat is insufficient, and finally supplement it with a gas-fired boiler. Although some systems are equipped with heat storage devices, their charging and discharging control mainly depends on preset fixed temperature thresholds or simple time-sharing strategies, i.e., storing or discharging heat within fixed time periods. The linkage between various heat source units and between heat source and heat storage devices is loose, mainly relying on manual experience or simple logical judgment for switching and adjustment.

[0004] However, the fixed-priority-based scheduling method is rigid and cannot dynamically adjust according to real-time changes in energy prices, external environments, and future load demands, resulting in poor economic efficiency of system operation. Secondly, simple threshold control or time-sharing control strategies lack foresight and have a lag in responding to load fluctuations and changes in heat sources, which can easily cause temperature fluctuations in the heating pipe network and affect heating quality. In addition, there is a lack of deep coupling and collaborative optimization between various energy subsystems, making it difficult to achieve optimal matching and cascade utilization of multiple energies in the time and space dimensions, resulting in waste of energy grade and reduction of overall energy efficiency of the system. SUMMARY

[0005] To solve the above problems, the present application provides a multi-source energy linkage heat storage method and system based on cascade heating of large-temperature-difference units, which establishes a dynamic optimization model to collaboratively control the operation mode of multi-stage heating unit groups and double-medium heat storage tanks, enabling efficient cascade utilization and intelligent economic scheduling of multi-source energy, and significantly improving the economic efficiency and operational stability of the heating system.

[0006] The above objectives can be achieved through the following solutions:

[0007] The multi-source energy linkage heat storage method based on large temperature difference unit cascade heating comprises the following steps: obtaining water inlet temperature parameters and external environment prediction parameters of a heat supply pipe network to generate load demand characteristics; establishing a dynamic optimization model according to the load demand characteristics and obtained energy price time sequence parameters; calculating operating parameters of a multi-stage heating unit group and scheduling parameters of a double-medium heat storage tank through the dynamic optimization model to generate multi-source scheduling instructions; and executing the multi-source scheduling instructions to control adaptive valve groups to switch heat source paths and link the double-medium heat storage tank to charge and discharge heat; wherein the multi-stage heating unit group comprises: a primary heating unit that uses industrial waste heat to perform basic heating on return water; a secondary heating unit that uses a solar heat collection source to perform medium temperature lifting on primary outlet water; and a tertiary heating unit that uses a gas heat source to perform peak temperature adjustment on secondary outlet water.

[0008] Optionally, the step of establishing a dynamic optimization model according to the load demand characteristics and obtained energy price time sequence parameters comprises the following steps: calculating a thermodynamic grade loss by using the load demand characteristics; obtaining energy price time sequence parameters for analysis to calculate an economic cost; using preset pipe network temperature difference constraints, heat storage tank state of charge boundaries and energy utilization priorities as model boundary conditions; using the economic cost and the thermodynamic grade loss to construct an objective function; and constructing a dynamic optimization model based on the model boundary conditions and the objective function.

[0009] Optionally, the step of controlling adaptive valve groups to switch heat source paths comprises the following steps: obtaining solar radiation intensity parameters, real-time water flow parameters of the secondary heating unit and target temperature rise parameters; using the real-time water flow parameters and the target temperature rise parameters to calculate and generate a solar energy effective utilization threshold; determining whether the solar radiation intensity parameters are lower than the solar energy effective utilization threshold; if yes, generating a path switching instruction; executing the path switching instruction to close an inlet valve of the secondary heating unit to isolate the secondary heating unit; and synchronously opening a cross-stage heat injection valve that connects the tertiary heating unit and the primary heating unit outlet to inject high-grade heat generated by the tertiary heating unit into the primary heating unit outlet waterway.

[0010] Optionally, the step of linking the double-medium heat storage tank to charge and discharge heat comprises the following steps: obtaining real-time electricity price parameters of a power grid and heat storage state parameters of a phase change layer in the double-medium heat storage tank; when the real-time electricity price parameters are not in a valley electricity period and the heat storage state parameters are lower than a charging threshold set for safe operation, starting an electric heat pump device; using the electric heat pump device to extract low-temperature phase change latent heat in the phase change layer, and performing upgrading by consuming electricity in the valley electricity period to release generated high-temperature heat into a water layer of the double-medium heat storage tank to form a high-temperature heat storage water body.

[0011] Optionally, the forming of the high-temperature heat storage water body comprises: in the evaporator of the electric heat pump device, evaporating the liquid working medium into low-temperature and low-pressure gaseous working medium by absorbing the low-temperature phase change latent heat released by the phase change layer; converting the low-temperature and low-pressure gaseous working medium into high-temperature and high-pressure gaseous working medium by the electric energy driven compressor; in the condenser of the electric heat pump device, releasing heat from the high-temperature and high-pressure gaseous working medium to the water layer of the double-medium heat storage tank and condensing into liquid to generate the high-temperature heat storage water body.

[0012] Optionally, the method further comprises: receiving and analyzing a cold wave early warning signal issued by an external meteorological system, extracting early warning time and temperature drop range information, and generating a heat storage instruction; in the valley electricity period before the early warning time arrives, executing the heat storage instruction to increase the operating power of the electric heat pump device, transferring the heat in the phase change layer to the water layer of the double-medium heat storage tank, and forming a full-load high-temperature heat storage water body.

[0013] Optionally, the method further comprises: collecting solar radiation intensity parameters at a preset frequency, calculating the change rate of the solar radiation intensity parameters, and generating radiation intensity change rate data; comparing the radiation intensity change rate data with a mutation threshold set for inhibiting temperature fluctuations in the pipe network; when the radiation intensity change rate data exceeds the mutation threshold, determining that there is excess solar heat, and generating a rapid heat storage instruction; executing the rapid heat storage instruction to guide the excess solar heat into the phase change layer for absorption, and simultaneously adjusting the water flow of the secondary heating unit through a proportional-integral-derivative algorithm.

[0014] Optionally, the method further comprises: continuously monitoring the industrial waste heat source parameters of the primary heating unit, and when the industrial waste heat source parameters are lower than a preset maintenance threshold within a preset time, determining that the heat source is interrupted and generating an abnormal working condition signal; in response to the abnormal working condition signal, generating and executing a heat source reconstruction instruction; based on the heat source reconstruction instruction, closing the water inlet valve of the primary heating unit and opening the heat release circuit of the water layer of the double-medium heat storage tank; according to the load demand characteristics, recalculating the water inlet flow of the secondary heating unit to compensate for the heat load gap.

[0015] Optionally, the method further comprises: monitoring the load variation characteristics of the heating pipe network, and dividing the load variation characteristics into short-term load fluctuations and persistent basic load; based on the short-term load fluctuations, opening the heat exchange circuit connected with the phase change layer of the double-medium heat storage tank, and using the characteristic of the phase change layer to release latent heat at a constant temperature to smooth; based on the persistent basic load, opening the heat release circuit of the water layer of the double-medium heat storage tank, and using the sensible heat stored in the water layer of the double-medium heat storage tank to provide stable heat output.

[0016] Based on the same inventive concept, the application also provides a multi-source energy linkage heat storage system based on large temperature difference unit cascade heating, comprising: a parameter acquisition module, configured to acquire water inlet temperature parameters of a heat supply pipe network and external environment prediction parameters, and generate load demand characteristics; a dynamic optimization module, configured to establish a dynamic optimization model according to the load demand characteristics and acquired energy price time sequence parameters; an instruction generation module, configured to calculate operating parameters of a multi-stage heating unit group and scheduling parameters of a double-medium heat storage tank through the dynamic optimization model, and generate multi-source scheduling instructions; and a linkage control module, configured to execute the multi-source scheduling instructions, control adaptive valve group switching of a heat source path, and link the double-medium heat storage tank for heat charging and discharging.

[0017] Compared with the prior art, the application has the following advantages:

[0018] 1. The application realizes significant reduction of heat supply cost and substantial improvement of energy utilization efficiency by constructing a multi-source energy cascade utilization architecture and combining dynamic optimization with energy price time sequence; the system preferentially utilizes low-cost or zero-cost energy such as industrial waste heat and solar energy to meet basic and medium-temperature heat load, and only starts high-grade gas heat source for peak regulation when necessary, thereby following the principle of energy utilization according to quality; at the same time, the system stores energy during valley electricity period, converts low-price electricity into high-grade heat energy reserve, realizes cross-time domain value improvement of energy, and thereby maximizes the reduction of fossil energy consumption and overall operation cost of the system on the premise of guaranteeing heat supply effect;

[0019] 2. The application significantly enhances the stability and reliability of the heat supply system through intelligent response and adaptive control to various abnormal working conditions and load fluctuations; when facing insufficient solar radiation, interruption of main heat source and other sudden situations, the system can automatically switch heat source paths or start standby heat sources, thereby realizing rapid reconstruction of the heat supply system; at the same time, the different thermal physical properties of the phase change layer and the water layer in the double-medium heat storage tank can be used to accurately suppress and support short-time load impact and persistent basic load respectively, thereby effectively inhibiting pipe network temperature fluctuations and guaranteeing high quality and continuity of heat supply services in complex and variable environments;

[0020] 3. The application introduces a prediction-based dynamic optimization scheduling mechanism, so that the operation of the heat supply system changes from passive response to active planning, thereby improving the intelligent level of management; by acquiring and analyzing external environment prediction parameters and energy price time sequence, the system can prospectively formulate an optimal operation strategy for a future period of time, and perform heat storage or adjust heat source output ratio in advance; especially when receiving an extreme weather warning such as a cold wave, the system can execute heat storage instructions in advance to build sufficient heat safety margin, thereby calmly coping with foreseeable load peaks in the future and avoiding the lag and inefficiency caused by temporary scheduling.

[0021] Other features and advantages of the present application will be set forth in the descriptions that follow, and in part will be apparent from the descriptions, or can be learned by practice of the application. The purposes and other advantages of the application will be realized and attained by the structures described in the description, claims, and accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments or the prior art description will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0023] Figure 1 is a flowchart of a multi-source energy linkage heat storage method based on step-by-step heating of a large-temperature-difference unit according to an embodiment of the present application.

[0024] Figure 2 is a schematic diagram of a step-by-step heating process according to an embodiment of the present application.

[0025] Figure 3 is a structural schematic diagram of a multi-source energy linkage heat storage system based on step-by-step heating of a large-temperature-difference unit according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0027] With reference to Figure 1 An embodiment of the present application proposes a multi-source energy linkage heat storage method based on step-by-step heating of a large-temperature-difference unit, which adopts a dynamic optimization model to cooperatively control the operation modes of a multi-stage heating unit group and a double-medium heat storage tank, can realize efficient step-by-step utilization and intelligent economic scheduling of multi-source energy, and significantly improves the economy and operation stability of a heating system.

[0028] The method according to the embodiment specifically includes:

[0029] Obtaining an inlet water temperature parameter of a heating pipe network and external environment prediction parameters, and generating load demand characteristics;

[0030] Specifically, first, the temperature sensor deployed at the inlet of the primary side of the heat supply pipe network collects data in real time to obtain the inlet water temperature parameter representing the current thermal state of the system. At the same time, a communication connection is established with a third-party meteorological service system through an application programming interface to obtain external environment prediction parameters in a specific future period, which mainly include a series of prediction data of environmental temperature, solar radiation intensity, and wind speed arranged according to time steps. Based on the obtained external environment prediction parameters, the system will establish a heat load prediction model to generate load demand characteristics. The load demand characteristics are represented as a prediction time series, which describes the terminal heat demand that the heating system needs to meet in each future scheduling period. The generation process can be quantitatively described by the following heat load calculation formula:

[0031]

[0032] wherein Q load (t) represents the predicted system heat load demand at time t in the future, with the unit of kilowatts. K total represents the comprehensive heat transfer coefficient of the buildings in the entire heating area, with the unit of kilowatts per degree Celsius. This parameter is determined by regression analysis on historical operation data or simulation calculation based on the building information model, and it comprehensively reflects the thermal insulation performance of the building envelope and the heat loss of the permeable wind. T setpoint is the preset indoor design reference temperature, which is the target value to ensure user comfort, and is usually a constant value, such as 20 degrees Celsius. is the external environment prediction temperature at time t, which comes from the aforementioned external environment prediction parameter time series. By substituting the external environment prediction temperature at each time in the prediction time period into the formula, a series of corresponding heat load demand values can be calculated, and the time series of the heat load demand constitutes the core load demand characteristics required for subsequent dynamic optimization. The obtained inlet water temperature parameter serves as the real-time initial condition for system operation, providing a basis for the specific temperature rise value required by the subsequent calculation of the cascade heating unit.

[0033] According to the load demand characteristics and the obtained energy price time series parameters, a dynamic optimization model is established;

[0034] The dynamic optimization model is used to calculate the operating parameters of the multi-stage heating unit group and the scheduling parameters of the double-medium heat storage tank to generate multi-source scheduling instructions;

[0035] The multi-source scheduling instructions are executed to control the adaptive valve group to switch the heat source path and coordinate the charging and discharging of the double-medium heat storage tank;

[0036] The multi-stage heating unit group includes:

[0037] a primary heating unit that uses industrial waste heat to perform basic heating on the return water,

[0038] The secondary heating unit uses a solar heat collection source to raise the temperature of the primary outlet water,

[0039] The tertiary heating unit uses a gas heat source to adjust the temperature of the secondary outlet water.

[0040] Specifically, as shown in Figure 2 The system first determines the dynamic load demand of the heating system by sensing the real-time state of the pipe network water temperature and predicting future external disturbances, i.e., environmental parameters. Secondly, it combines this physical demand with the economic factors of the energy market, i.e., energy prices, to establish a dynamic optimization model with the goal of optimizing overall benefits. The key to this model is that its physical execution layer adopts the "cascade utilization" strategy of energy, i.e., according to the principle of thermodynamic grade from low to high, it sequentially dispatches industrial waste heat, solar energy, and gas heat sources to heat the heating medium in a segmented and relayed manner, ensuring that the energy quality matches the heating temperature zone. At the same time, the dual-medium heat storage tank acts as a flexible link in the system, achieving decoupling and transfer of energy in the time dimension. It can charge and discharge heat according to the optimization instructions, thereby playing a key buffering and balancing role between energy supply and demand. Finally, the system precisely controls the operating state of each heat source and the valve path by executing the dispatching instructions output by the optimization model, achieving deep coupling and linked operation of multiple energy sources. In terms of economy, through dynamic optimization and real-time response to energy prices, the system can preferentially utilize free or low-cost industrial waste heat and solar energy, and store energy using the heat storage tank during low electricity prices, significantly reducing dependence on high-priced fossil fuels and greatly reducing overall heating operation costs. In terms of environmental protection and energy efficiency, the cascade heating mode follows the principle of energy utilization according to quality, avoiding the waste of high-grade energy for low-grade heating, greatly improving the overall utilization efficiency of energy, and effectively reducing carbon emissions caused by gas consumption, achieving green and low-carbon heating. In terms of system operation stability and reliability, through precise load prediction and flexible peak-shaving of the dual-medium heat storage tank, the invention can effectively smooth out disturbances caused by weather changes or energy supply fluctuations, ensuring the stability of the heating pipe network temperature and improving the flexibility and robustness of the entire heating system in complex working conditions, ensuring high-quality and uninterrupted heating services.

[0041] Optionally, the dynamic optimization model is established according to the load demand characteristics and the obtained energy price time sequence parameters, comprising:

[0042] The thermodynamic grade loss is calculated using the load demand characteristics;

[0043] The economic cost is calculated by obtaining and analyzing the energy price time sequence parameters;

[0044] The preset pipe network temperature difference constraint, the state of charge boundary of the heat storage tank, and the energy utilization priority are used as model boundary conditions;

[0045] The economic cost and the thermodynamic grade loss are used to construct an objective function;

[0046] Based on the model boundary conditions and the objective function, a dynamic optimization model is constructed.

[0047] Specifically, the thermodynamic grade loss needs to be calculated first, which aims to quantify the effective energy loss of different quality energy used for heating. The calculation of the thermodynamic grade loss is based on the load demand characteristics and is expressed by the following formula:

[0048] L thermo =∑[λ i *Q i (t)],

[0049] Wherein, L thermo represents the total thermodynamic grade loss, which is a dimensionless index for evaluating the rationality of energy utilization; Q i (t) is the heat power provided by the i-th heating unit at t, which is a decision variable for solving the model; the sum of the heat powers provided by all heating units plus the net heat release power of the double-medium heat storage tank is the system heat load demand; λ i is the thermodynamic grade loss coefficient of the i-th heat source, which is a preset parameter, and its value is set according to the temperature grade of the heat source. High-grade heat sources such as gas heat sources have a higher coefficient, and low-grade heat sources such as industrial waste heat sources have a lower coefficient, so as to punish the unreasonable use of high-grade energy in the optimization objective. Then, the energy price time sequence parameter is obtained, which is used to calculate the economic cost of the system. The energy price time sequence parameter is the sequence of the prices of each energy, especially gas and electricity, changing with time in the future period. The calculation formula of the economic cost is:

[0050]

[0051] Wherein, C econ represents the total economic cost; P i (t) is the price of the i-th energy at t, which is derived from the obtained energy price time sequence parameter; η iis the energy conversion efficiency of the i-th heating unit, which is a device inherent parameter. Subsequently, precise operating boundaries are established for the model, including the pipe network temperature difference constraint, which ensures that the supply and return water temperatures of the heating pipe network are within the safe and efficient operating range allowed by the device; the state of charge boundary of the thermal storage tank, which ensures that the heat storage capacity of the dual-medium thermal storage tank is maintained between the set minimum and maximum thresholds to prevent excessive heat release or storage; and the energy utilization priority, which reflects the principle of step-by-step utilization of industrial waste heat, solar energy, and finally gas heat source by setting different coefficients in the objective function. Finally, the calculated economic cost and thermodynamic grade loss are weighted and summed to construct the final objective function:

[0052] minJ = w econ *C econ +w thermo *L thermo ,

[0053] where J is the comprehensive objective function to be minimized; w econ and w thermo are preset weight coefficients for balancing the relative importance of economic cost and thermodynamic grade loss in the optimization objective. These two weight coefficients also perform the role of normalizing physical quantities of different dimensions, ensuring the physical meaning and logical consistency of the objective function. Finally, combining this objective function with the above model boundary conditions forms a complete dynamic optimization model. This model solves the operating parameters of each heating unit and the scheduling parameters of the thermal storage tank that minimize the comprehensive objective function while satisfying all constraints.

[0054] Optionally, the control of the adaptive valve group switching heat source path comprises:

[0055] obtaining a solar radiation intensity parameter, a real-time water flow parameter of the secondary heating unit, and a target temperature rise parameter;

[0056] using the real-time water flow parameter and the target temperature rise parameter to calculate and generate a solar effective utilization threshold;

[0057] determining whether the solar radiation intensity parameter is lower than the solar effective utilization threshold;

[0058] if yes, generating a path switching instruction;

[0059] executing the path switching instruction to close the inlet valve of the secondary heating unit to isolate the secondary heating unit;

[0060] synchronously opening the cross-stage heat injection valve connecting the outlet of the tertiary heating unit and the primary heating unit to inject high-grade heat generated by the tertiary heating unit into the outlet water path of the primary heating unit.

[0061] Specifically, first, the real-time solar radiation intensity parameter is obtained by deploying the irradiance sensor in the solar heat source field, and at the same time, the real-time water flow parameter is obtained by installing the flow meter in the secondary heating unit, i.e., the solar heat source circuit. In addition, the target temperature rise parameter aiming to meet the terminal load demand characteristics issued by the upper dynamic optimization model is also obtained. These three parameters are the basis for executing the path switching decision. Then, according to the basic principle of thermodynamics, an effective utilization threshold of solar energy is calculated and generated using the obtained real-time water flow parameter and target temperature rise parameter. The threshold represents the minimum effective heat power required to achieve the target temperature rise under the current water flow, which can be expressed by the following formula:

[0062] Q threshold =c p *m flow *ΔT target ,

[0063] Wherein, Q threshold is the effective utilization threshold of solar energy, with the unit of kilowatt, representing the minimum heat power required to be absorbed by the secondary heating unit to play an effective role; c p is the specific heat capacity of water; m flow represents the real-time water flow parameter in the secondary heating unit pipeline, measured by the flow meter, with the unit of kilogram per second; and ΔT target represents the target temperature rise parameter calculated by the dynamic optimization model for the secondary heating unit, with the unit of degree Celsius. Subsequently, the heat power converted from the real-time solar radiation intensity parameter is compared with the calculated effective utilization threshold of solar energy. The judgment logic is that when the solar radiation intensity parameter is too low to provide heat power lower than the effective utilization threshold of solar energy, the system determines that the secondary heating unit cannot effectively complete its heating task. At this time, the system will generate a path switching instruction. The instruction is issued and executed to control the adaptive valve group to act, specifically to close the inlet valve of the secondary heating unit, which isolates the solar heat source from the main heating circuit to avoid the circulating water flowing through the invalid heat source and causing heat loss or insufficient temperature rise. At the same time, a cross-stage heat injection valve connecting the outlet of the primary heating unit and the inlet of the tertiary heating unit is opened. The opening of the valve establishes a bypass channel, so that the water after the basic heating of the primary heating unit directly enters the tertiary heating unit for subsequent peak temperature adjustment by the gas heat source, a high-grade heat source, thereby skipping the invalid secondary heating unit.

[0064] Optionally, the charging and discharging of the linked dual-medium heat storage tank includes:

[0065] Obtaining the real-time electricity price parameter of the power grid and the heat storage state parameter of the phase change layer in the dual-medium heat storage tank;

[0066] starting the electric heat pump device when the real-time electricity price parameter is not in the valley electricity period and the heat storage state parameter is lower than the charging threshold set for safe operation;

[0067] extracting low-temperature phase change latent heat in the phase change layer by the electric heat pump device, and upgrading the heat by consuming electricity in the valley electricity period, and releasing the generated high-temperature heat to the water layer of the double-medium heat storage tank to form a high-temperature heat storage water body.

[0068] Specifically, through the communication interface with the power grid information system, the real-time electricity price parameter is continuously obtained, and the temperature distribution of the phase change layer material is monitored synchronously through the temperature sensor array deployed inside the double-medium heat storage tank, so as to calculate the heat storage state parameter representing the heat storage level, which is a key indicator for measuring the low-temperature phase change latent heat reserve in the phase change layer. Subsequently, the decision-making stage is entered, which compares the real-time electricity price parameter with the preset valley electricity period, and compares the calculated heat storage state parameter with a charging threshold set to ensure safe and efficient operation of the system. When and only when both conditions are met, that is, the electricity price is in the valley period and the heat storage state parameter of the phase change layer is lower than the charging threshold, the system determines that it is economical and necessary to start charging, and generates an instruction to start the electric heat pump device. After the electric heat pump device is started, its core function is to upgrade the heat. It uses the evaporator to extract low-temperature phase change latent heat from the phase change layer of the double-medium heat storage tank, and the latent heat is the low-grade heat released by the phase change material during solidification. The electric heat pump device drives the compressor to work by consuming cheap electricity in the valley electricity period, compresses the working medium that has absorbed the latent heat, and significantly increases its temperature and pressure, that is, the heat grade is upgraded. Finally, the high-temperature and high-pressure working medium carrying high-grade heat flows through the condenser, releases heat to the water layer of the double-medium heat storage tank, thereby heating the water and forming a high-temperature heat storage water body that can be dispatched at any time. The heat storage state parameter can be quantified by the following formula:

[0069]

[0070] wherein S pcm is the heat storage state parameter of the phase change layer, which is a dimensionless ratio; represents the actual heat storage amount of the phase change layer, which is calculated by real-time monitoring of the internal temperature and combining the thermal physical parameters of the material; is the designed maximum heat storage capacity of the phase change layer, which is an inherent known parameter of the device.

[0071] Optionally, the forming of the high-temperature heat storage water body comprises:

[0072] In the evaporator of the electric heat pump device, the liquid working medium is evaporated into low-temperature and low-pressure gaseous working medium by absorbing the low-temperature phase change latent heat released by the phase change layer;

[0073] The low-temperature and low-pressure gaseous working medium is converted into high-temperature and high-pressure gaseous working medium by a compressor driven by electric energy;

[0074] In the condenser of the electric heat pump device, the high-temperature and high-pressure gaseous working medium releases heat to the water layer of the double-medium heat storage tank and condenses into liquid state to generate high-temperature heat storage water body.

[0075] Specifically, the process of forming the high-temperature heat storage water body is a complete and continuous thermodynamic cycle performed by the electric heat pump device, which starts from the evaporator of the electric heat pump device, which exchanges heat with the phase change layer of the double-medium heat storage tank. At this stage, the liquid working medium inside the electric heat pump device flows through the evaporator and absorbs the low-temperature phase change latent heat released by the phase change layer during the solidification process. As a result of absorbing heat, the liquid working medium undergoes phase change and evaporates into low-temperature and low-pressure gaseous working medium. Then, the low-temperature and low-pressure gaseous working medium is guided to the core component of the electric heat pump device, i.e. the compressor. The system drives the compressor to work by consuming electric energy during the valley electricity period, and forcibly compresses the incoming low-temperature and low-pressure gaseous working medium. This compression process significantly increases the internal energy of the working medium, which is converted into high-temperature and high-pressure gaseous working medium, which is the key step of heat upgrading. Subsequently, the high-temperature and high-pressure gaseous working medium carrying high-grade heat energy enters the condenser of the electric heat pump device. The condenser exchanges heat with the water layer of the double-medium heat storage tank, and the high-temperature and high-pressure gaseous working medium releases a large amount of heat carried by it to the water layer in the condenser, causing the temperature of the water layer to rise. While releasing heat, the temperature of the working medium decreases and condenses back to liquid state. This liquid working medium flows back to the evaporator to start the next cycle. Through this series of continuous evaporation, compression and condensation processes, the low-grade heat of the phase change layer is continuously transferred and upgraded in grade and then released to the water layer, finally forming a dispatchable high-temperature heat storage water body with higher temperature in the double-medium heat storage tank.

[0076] Optionally, the method further comprises:

[0077] Receiving and analyzing the cold wave early warning signal issued by the external meteorological system, extracting the early warning time and temperature drop range information, and generating a heat storage instruction;

[0078] During the valley electricity period before the early warning time arrives, the heat storage instruction is executed to increase the operating power of the electric heat pump device, and the heat in the phase change layer is transferred to the water layer of the double-medium heat storage tank to form a full-load high-temperature heat storage water body.

[0079] Specifically, when the system receives and successfully parses an official cold wave warning signal issued by an external meteorological system, it immediately initiates a response procedure. First, it extracts two core pieces of information from the warning signal: the warning time, which indicates the time when the cold wave is expected to arrive and start affecting the local environment, and the temperature drop magnitude, which quantifies the expected severity of the temperature drop. Based on these two key pieces of information, the control system automatically generates a high-priority heat storage instruction. The execution of this instruction has strict time constraints, and the system will query the current electricity pricing strategy to lock in the nearest valley electricity period before the warning time arrives. During the determined valley electricity period, the system formally executes the heat storage instruction, sending control signals to the electric heat pump device to instruct it to increase its operating power. This means that the electric heat pump device will work at a higher power level than usual, significantly accelerating the rate of heat transfer. In this high-power operation mode, the electric heat pump device will more quickly extract the low-temperature phase change latent heat stored in the phase change layer of the double-medium heat storage tank and upgrade it by consuming cheap valley electricity, and then release the generated high-grade heat to the water layer of the double-medium heat storage tank. This process will continue until the amount of heat stored in the water layer reaches its design upper limit, ultimately forming a full-load high-temperature heat storage water body, i.e., a fully filled high-temperature heat reserve, fully preparing for the upcoming cold wave weather.

[0080] Optionally, the method further comprises:

[0081] Collecting the solar radiation intensity parameter at a preset frequency, and calculating the change rate of the solar radiation intensity parameter to generate radiation intensity change rate data;

[0082] Comparing the radiation intensity change rate data with a mutation threshold set for suppressing temperature fluctuations in the pipe network;

[0083] When the radiation intensity change rate data exceeds the mutation threshold, it is determined that there is excess solar heat, and a rapid heat storage instruction is generated;

[0084] Executing the rapid heat storage instruction to direct excess solar heat into the phase change layer for absorption, while adjusting the water flow of the secondary heating unit through a proportional-integral-derivative algorithm.

[0085] Specifically, the solar radiation intensity parameter is continuously collected at a preset higher frequency, such as once every second, through the deployment of an irradiance sensor at the secondary heating unit, i.e., the solar thermal source field. Based on the collected time series data, the system calculates the change rate of the solar radiation intensity parameter in real time, thereby generating radiation intensity change rate data R I :

[0086]

[0087] wherein R Iis the solar irradiance rate of change data, whose unit is watt per square meter per second, representing the rate of change of solar input power; I t is the solar irradiance parameter collected at the current time; I t-Δt is the solar irradiance parameter collected at the previous time; and Δt is the preset collection time interval. Subsequently, the real-time calculated irradiance rate of change data is compared with a pre-set mutation threshold value for suppressing the temperature of the heat supply pipe network from fluctuating sharply. When the irradiance rate of change data exceeds the mutation threshold value, the system determines that a sharp increase in heat input has occurred, and such a transient energy surge exceeding the smooth accommodation capacity of the system is defined as solar heat surplus. At this time, the system immediately generates and executes a fast heat storage instruction. The instruction triggers two synchronous operations, one of which is to open the heat import circuit connecting the outlet of the secondary heating unit and the phase change layer of the double-medium heat storage tank, so as to directly import the excess solar heat generated by the irradiance surge into the phase change layer and use the phase change material to absorb a large amount of latent heat at a constant temperature for fast buffering and absorption. The other is to simultaneously start the proportional-integral-derivative algorithm to dynamically adjust the water flow through the secondary heating unit, so as to quickly take away the heat in the collector by increasing the water flow and cooperatively suppress the sharp rise of the outlet water temperature.

[0088] Optionally, the method further comprises:

[0089] continuously monitoring the industrial waste heat source parameter of the primary heating unit, and determining that the heat source is interrupted and generating an abnormal working condition signal when the industrial waste heat source parameter is lower than the preset maintenance threshold value within a preset time;

[0090] in response to the abnormal working condition signal, generating and executing a heat source reconstruction instruction;

[0091] based on the heat source reconstruction instruction, closing the water inlet valve of the primary heating unit and opening the heat release circuit of the water layer of the double-medium heat storage tank;

[0092] recomputing the water inlet flow of the secondary heating unit according to the load demand characteristics to compensate for the heat load gap.

[0093] Specifically, the system monitors the industrial waste heat source parameters through the sensors deployed in the industrial waste heat source heat exchange circuit, which represents the running state of the industrial waste heat source. The parameter is usually the outlet temperature of the heat source side or the calculated heat power. The system compares the real-time monitored industrial waste heat source parameter with a preset maintenance threshold, which is the minimum working condition standard to ensure that the primary heating unit can effectively heat the heating pipe network return water. In order to avoid misjudgment caused by instantaneous disturbance, the system sets a preset time window. Only when the industrial waste heat source parameter is continuously lower than the maintenance threshold for more than the preset time, the system will determine that it is an abnormal working condition of heat source interruption, and immediately generate an abnormal working condition signal. The signal is the starting point of triggering all subsequent emergency response actions. After responding to the abnormal working condition signal, the system will immediately generate and execute the heat source reconstruction instruction. The instruction contains a series of precise linkage control actions. First, the instruction controls the closing of the water inlet valve of the primary heating unit, isolating the failed industrial waste heat source from the main heating circuit to prevent low-temperature return water from flowing through the unit to cause invalid circulation. Then, the instruction synchronously opens the heat release circuit valve connected with the water layer of the double-medium heat accumulator, and introduces the high-temperature heat storage water stored therein into the heating pipe network as a replacement heat source to inject heat immediately. Finally, in order to make up for the heat load gap caused by the absence of the primary heating unit, the system will recalculate and adjust the parameters of the subsequent normal running heat source unit according to the existing load demand characteristics, especially for the secondary heating unit. The system will recalculate the water inlet flow to ensure that the total heating capacity of the entire system can accurately match the load demand of the terminal under the new water inlet temperature condition.

[0094] Optionally, the method further comprises:

[0095] Monitoring the load change characteristics of the heating pipe network, and distinguishing the load change characteristics into short-term load fluctuation and persistent basic load;

[0096] Based on the short-term load fluctuation, opening the heat exchange circuit connected with the phase change layer of the double-medium heat accumulator, and using the characteristic of the phase change layer to release latent heat at a constant temperature for smoothing;

[0097] Based on the persistent basic load, opening the heat release circuit of the water layer of the double-medium heat accumulator, and using the sensible heat stored in the water layer of the double-medium heat accumulator to provide stable heat output.

[0098] Specifically, first, the load variation characteristics of the heat supply pipe network are continuously monitored and analyzed. The system calculates the real-time heat load demand by collecting the return water temperature, supply water temperature and flow of the heat supply pipe network in real time. Subsequently, the signal processing or time series analysis technology is used to decompose the continuously changing load demand curve into two components, namely the short-term load fluctuation and the persistent base load. This distinction process can be quantified, for example, by calculating the moving average of real-time heat load data to obtain the persistent base load representing the trend, and then subtracting the base load from the real-time load to obtain the short-term load fluctuation representing the instantaneous change. The calculation can be expressed by the following formula:

[0099]

[0100] Q fluctuation (t)=Q realtime (t)-Q base (t),

[0101] Where Q realtime (t) is the real-time heat load at time t; Q base (t) is the calculated persistent base load, which is the average value of the real-time heat load within a time window containing N data points; Q fluctuation (t) is the short-term load fluctuation, and i is 0 to N-1. Based on the distinction result, the system executes differentiated heat release strategies. When significant short-term load fluctuations are monitored, the system determines that fast and high-power heat response is needed, and immediately generates an instruction to start the heat exchange circuit connected to the phase change layer of the double-medium heat accumulator. By using the physical property of the phase change layer that can quickly release or absorb a large amount of latent heat at a constant phase change temperature, instantaneous heat compensation is provided for the pipe network, thereby realizing accurate suppression of load fluctuations. For the persistent base load part analyzed, the system determines that stable and persistent heat supply is needed, so it starts the heat release circuit of the water layer of the double-medium heat accumulator, uses the large capacity sensible heat stored in the water layer to provide a smooth heat output, and provides reliable support for the base load.

[0102] Based on the same inventive concept, as shown in Figure 3 , the present application also provides a multi-source energy linkage heat storage system based on cascade heating of large temperature difference units, which comprises:

[0103] A parameter acquisition module is configured to acquire the inlet water temperature parameter of the heat supply pipe network and the external environment prediction parameter, and generate a load demand characteristic.

[0104] A dynamic optimization module is configured to establish a dynamic optimization model according to the load demand characteristic and the acquired energy price time sequence parameter.

[0105] An instruction generation module is configured to calculate operation parameters of the multi-stage heating unit group and scheduling parameters of the double-medium heat storage tank through the dynamic optimization model, and generate multi-source scheduling instructions;

[0106] A linkage control module is configured to execute the multi-source scheduling instructions, control the adaptive valve group to switch the heat source path, and link the double-medium heat storage tank to charge and discharge heat.

[0107] In order to verify the feasibility and advancement of the present application in implementation, the present application is applied to a newly built central heating system of an ecological industrial park. The park contains production plants, research and development office buildings and supporting residential areas, and has high requirements for the stability, economy and environmental protection of heating. The park has available industrial waste heat resources (cooling water waste heat of a factory), sufficient roof area for laying solar heat collectors, and a central energy station with a gas-fired boiler and a double-medium heat storage tank as the core.

[0108] After the present application is applied to the heating system, it aims to realize the cascade utilization and intelligent scheduling of industrial waste heat, solar energy and gas, to maximize the reduction of operation cost and carbon emissions through the linkage of the double-medium heat storage tank, and to ensure the reliability of heating under various external environmental and working condition changes. In order to verify the effectiveness of the present application, the system collects operation data for a heating season of four months, and compares and analyzes it with the scheme of direct heating by a traditional gas-fired boiler.

[0109] On a typical working day in winter, the outdoor environmental temperature is-5℃, the return water temperature of the heating pipe network is 40℃, and the target water supply temperature of the system is 80℃. The system of the present application first obtains the above pipe network temperature parameters through the parameter acquisition module, and generates a load demand characteristic in combination with the future 24-hour environmental temperature and solar radiation intensity prediction provided by the meteorological system. The dynamic optimization module calculates the optimal scheduling strategy with the lowest operation cost and the smallest thermodynamic grade loss according to the load demand characteristic and the real-time time-of-use electricity price and natural gas price obtained.

[0110] Under the execution of the linkage control module, the system operates according to the cascade heating path. The first stage heating is that the 40℃ return water of the pipe network first flows through the industrial waste heat exchanger, and the free waste heat generated by the factory is used to heat it to 55℃, completing the basic heating. The water after the first stage heating continues to enter the solar heat collector array, and under the sufficient solar radiation at that time, the water temperature is raised to 70℃, realizing the medium temperature rise. Finally, the 70℃ hot water enters the gas-fired boiler for precise peak temperature adjustment, and finally reaches the target water supply temperature of 80℃ and is sent into the pipe network. In this process, the gas-fired boiler only needs to provide a temperature rise of 10℃, greatly saving the consumption of fossil fuels.

[0111] During a morning period of a day, the sky is cloudy, and the solar radiation intensity is reduced to 200W / m 2After the system acquires this parameter in real time, it calculates that the solar collector cannot effectively raise the temperature of 55℃ hot water under this irradiance condition. The system determines that the secondary heating unit is too low in efficiency, and immediately generates a path switching command: automatically close the inlet valve of the secondary heating unit to isolate it; at the same time, open the cross-stage heat injection valve connecting the primary and tertiary heating units, so that the 55℃ hot water directly enters the gas-fired boiler for heating, avoiding the loss of heat in the ineffective solar circuit and ensuring the continuity of heating.

[0112] During the night valley electricity period (1:00 to 5:00), the real-time electricity price drops to 0.3 yuan / kWh. The system detects that the state of charge of the water layer in the double-medium heat storage tank is 60%, while the phase change layer still stores a large amount of low-temperature latent heat. The system automatically starts the electric heat pump device, consumes cheap valley electricity, extracts low-temperature heat from the phase change layer, and releases high-temperature heat to the water layer after upgrading through heat pump work. After 4 hours of operation, the water layer temperature is successfully raised from 65℃ to 85℃, and the state of charge of the heat storage tank reaches 95%, making a high-grade heat reserve for the next day's heating peak.

[0113] On January 15, the system receives a warning signal from the meteorological department that "a strong cold wave will hit in the next 48 hours, with a temperature drop of 15℃". After analyzing the warning information, the system immediately generates a heat storage command with the highest priority. During the night valley electricity period before the cold wave arrives, the system instructs the electric heat pump to run at 120% of the rated power to quickly and completely transfer the latent heat in the phase change layer to the water layer, forming a full-load 85℃ high-temperature heat storage water body to comfortably cope with the upcoming extreme low-temperature weather and the surge in heating load.

[0114] On February 5, the factory as the primary heat source is temporarily overhauled, and the industrial waste heat source is interrupted. After monitoring that the waste heat side parameters have been below the maintenance threshold for 5 minutes, the system determines that the heat source is interrupted and immediately generates and executes a heat source reconstruction command: close the water inlet valve of the primary heating unit, and at the same time open the heat release circuit of the water layer of the double-medium heat storage tank, using the stored 85℃ high-temperature water mixed with the pipe network return water as an alternative basic heat source. At the same time, the system recalculates and increases the water inflow of the secondary solar heating unit according to the load demand characteristics, ensuring that the total heating capacity of the system can still meet the user's demand in the absence of the primary heat source, demonstrating the system's high fault tolerance and reliability.

[0115] The system continuously monitors the load changes and distinguishes between short-term fluctuations and persistent base load. When the experimental equipment in a research and development building in the park is turned on, causing a short-term load to increase by 15%, the system starts the heat exchange circuit connected to the phase change layer of the heat storage tank, and uses the constant temperature and rapid release of latent heat of the phase change material to respond and stabilize the load impact within a few minutes. For the daily stable base load, the water layer of the heat storage tank or the heating units at each level are used to provide stable heating.

[0116] Table 1 Comparison of system operating parameters under different working conditions

[0117]

[0118] Table 2 Double-medium heat storage tank scheduling effect data table

[0119]

[0120] Table 3 Comparison of system operation economy and energy efficiency (daily average)

[0121] Comparison item Invention system Traditional gas boiler system Optimization effect Daily gas consumption 800 m 3 ]] 2500 m 3 ]] Reduced by 68% Daily power consumption (valley electricity) 1200 kWh 50 kWh (water pump) -(for energy storage enhancement) Daily comprehensive operation cost 3860 yuan 8750 yuan Reduced by 56% Daily carbon emissions 1.8 tons 5.5 tons Reduced by 67%

[0122] From the above Tables 1-3, it can be seen that the present application greatly optimizes the energy structure through the cascade utilization and intelligent scheduling of multiple energy sources. The data in Table 1 shows that the system can flexibly reconstruct the heating path according to external conditions, and always maintain high efficiency. The data in Table 2 verifies the key role of the double-medium heat storage tank in energy time shifting, peak load shifting, and stabilizing the system. The data in Table 3 directly proves the great advantages of the present application in economy and environmental protection. Compared with the traditional scheme, the operation cost and carbon emissions are reduced by more than 50%. This embodiment fully proves the practical value and promotion prospect of the present application in the field of modern central heating.

[0123] It should be noted that the above formulas can be translated into unitless standard values or parameters of the same dimension that can be superimposed by using the principle of dimensional consistency and mathematical standardization methods (such as normalization processing, dimensionless parameter conversion, or unit system unification). This eliminates the interference of different dimensions on the operation logic, making the formula retain the original data distribution characteristics while having mathematical operation rationality and objective law adaptability. It is a conventional technical means and will not be repeated here. The electrical connections between the above-mentioned units do not necessarily represent direct connections, and indirect connections can also be used as long as the purpose of the present application is achieved. The above-described embodiments are only exemplary embodiments of the present application and cannot limit the scope of the present application.

[0124] intended to encompass any and all embodiments of the application with equivalents as would be ascertained by those skilled in the art to which the application pertains. Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.

Claims

1. A multi-source energy linkage heat storage method based on large temperature difference unit cascade heating, characterized in that, The method comprises: obtaining the water inlet temperature parameter of the heat supply pipe network and the external environment prediction parameter to generate the load demand characteristics; establishing a dynamic optimization model according to the load demand characteristics and the obtained energy price time sequence parameter; calculating the operation parameters of the multi-stage heating unit group and the scheduling parameters of the double-medium heat storage tank through the dynamic optimization model to generate multi-source scheduling instructions; executing the multi-source scheduling instructions to control the adaptive valve group to switch the heat source path and drive the double-medium heat storage tank to charge and discharge heat; wherein the multi-stage heating unit group comprises: a primary heating unit that uses industrial waste heat to perform basic heating on return water, a secondary heating unit that uses a solar heat collection source to perform medium-temperature lifting on primary outlet water, a tertiary heating unit that uses a gas heat source to perform peak temperature adjustment on secondary outlet water.

2. The multi-source energy linkage regenerative method based on the cascade heating of large-temperature-difference unit according to claim 1, characterized in that, The dynamic optimization model is established according to the load demand characteristics and the obtained energy price time sequence parameter, which comprises: calculating the thermodynamic grade loss by using the load demand characteristics; obtaining the energy price time sequence parameter for analysis to calculate the economic cost; using the preset pipe network temperature difference constraint, the state of charge boundary of the heat storage tank, and the energy utilization priority as the model boundary condition; using the economic cost and the thermodynamic grade loss to construct the objective function; constructing the dynamic optimization model based on the model boundary condition and the objective function.

3. The multi-source energy linkage regenerative method based on large-temperature- difference unit cascade heating according to claim 1, characterized in that, The control of the adaptive valve group to switch the heat source path comprises: obtaining the solar radiation intensity parameter, the real-time water flow parameter of the secondary heating unit, and the target temperature rise parameter; using the real-time water flow parameter and the target temperature rise parameter to calculate and generate the solar effective utilization threshold value; determining whether the solar radiation intensity parameter is lower than the solar effective utilization threshold value; if yes, generating a path switching instruction; executing the path switching instruction to close the inlet valve of the secondary heating unit to isolate the secondary heating unit; synchronously opening the cross-stage heat injection valve that connects the tertiary heating unit and the primary heating unit outlet to inject the high-grade heat generated by the tertiary heating unit into the primary heating unit outlet waterway.

4. The multi-source energy linkage regenerative method based on large-temperature- difference unit cascade heating according to claim 1, characterized in that, The linkage of the double-medium heat storage tank to charge and discharge heat comprises: obtaining the real-time electricity price parameter of the power grid and the heat storage state parameter of the phase change layer in the double-medium heat storage tank; when the real-time electricity price parameter is not in the valley electricity period and the heat storage state parameter is lower than the charging threshold value set for safe operation, starting the electric heat pump device; using the electric heat pump device to extract the low-temperature phase change latent heat in the phase change layer, and through the work of consuming the electricity in the valley electricity period, the generated high-temperature heat is released to the water layer of the double-medium heat storage tank to form a high-temperature heat storage water body.

5. The multi-source energy linkage regenerative method based on large-temperature- difference unit cascade heating according to claim 4, characterized in that, The formation of the high-temperature heat storage water body comprises: in the evaporator of the electric heat pump device, the liquid working medium is evaporated into low-temperature and low-pressure gaseous working medium by absorbing the low-temperature phase change latent heat released by the phase change layer; the low-temperature and low-pressure gaseous working medium is converted into high-temperature and high-pressure gaseous working medium by the compressor driven by electricity; in the condenser of the electric heat pump device, the high-temperature and high-pressure gaseous working medium releases heat to the water layer of the double-medium heat storage tank and condenses into liquid to generate a high-temperature heat storage water body.

6. The multi-source energy linkage regenerative method based on large-temperature- difference unit cascade heating according to claim 4, characterized in that, The method further comprises: Receive and analyze the cold wave warning signal issued by the external meteorological system, extract the warning time and temperature drop range information, and generate a heat storage instruction; During the valley electricity period before the warning time arrives, execute the heat storage instruction to increase the operation power of the electric heat pump device, transfer the heat in the phase change layer to the water layer of the double-medium heat storage tank, and form a full-load high-temperature heat storage water body.

7. The multi-source energy linkage regenerative method based on large-temperature- difference unit cascade heating according to claim 6, characterized in that, The method further comprises: Collecting the solar radiation intensity parameter at a preset frequency, and calculating the change rate of the solar radiation intensity parameter to generate radiation intensity change rate data; Comparing the radiation intensity change rate data with a mutation threshold set to suppress temperature fluctuations in the pipe network; When the radiation intensity change rate data exceeds the mutation threshold, it is determined that there is excess solar heat, and a rapid heat storage instruction is generated; Executing the rapid heat storage instruction to guide the excess solar heat into the phase change layer for absorption, while adjusting the water flow of the secondary heating unit through a proportional-integral-derivative algorithm. 8.The multi-source energy linkage regenerative method based on the cascade heating of large-temperature-difference unit according to claim 1, wherein, The method further comprises: Continuously monitoring the industrial waste heat source parameter of the primary heating unit, and when the industrial waste heat source parameter is lower than the preset maintenance threshold within a preset time, determining that the heat source is interrupted and generating an abnormal working condition signal; In response to the abnormal working condition signal, a heat source reconstruction instruction is generated and executed; Based on the heat source reconstruction instruction, the water inlet valve of the primary heating unit is closed, and the heat release circuit of the water layer of the double-medium heat storage tank is opened; According to the load demand characteristics, the water inlet flow of the secondary heating unit is recalculated to compensate for the heat load gap. 9.The multi-source energy linkage regenerative method based on the cascade heating of large-temperature-difference unit according to claim 1, wherein, The method further comprises: Monitoring the load change characteristics of the heating pipe network, and dividing the load change characteristics into short-term load fluctuations and persistent basic load; Based on the short-term load fluctuations, the heat exchange circuit connected to the phase change layer of the double-medium heat storage tank is opened, and the characteristics of the phase change layer in releasing latent heat at a constant temperature are used for smoothing; Based on the persistent basic load, the heat release circuit of the water layer of the double-medium heat storage tank is opened, and the sensible heat stored in the water layer of the double-medium heat storage tank is used to provide stable heat output.

10. The multi-source energy linkage heat storage system based on cascade heating of large temperature difference unit, applied to the multi-source energy linkage heat storage method based on cascade heating of large temperature difference unit according to any one of claims 1-9, characterized in that, The system comprises: A parameter acquisition module for acquiring the inlet water temperature parameter of the heating pipe network and the external environment prediction parameter to generate load demand characteristics; A dynamic optimization module for establishing a dynamic optimization model according to the load demand characteristics and the acquired energy price time sequence parameter; An instruction generation module for calculating the operation parameters of the multi-stage heating unit group and the scheduling parameters of the double-medium heat storage tank through the dynamic optimization model, and generating a multi-source scheduling instruction; A linkage control module for executing the multi-source scheduling instruction to control the adaptive valve group to switch the heat source path and link the double-medium heat storage tank for charging and discharging heat.

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