Electric energy conversion and power regulation and control method based on solar heat exchange coupling system

Abstract

The invention relates to the technical field of solar heat utilization, and discloses an electric energy conversion and power regulation and control method based on a solar heat exchange coupling system, which comprises the following steps: calculating the phase change latent heat release rate and pressure and temperature sensitivity of a working medium in real time through a nonlinear prediction model, and establishing a compensation factor to dynamically correct the fusion weight of temperature and pressure signals; the shape memory alloy runner is driven to adjust the branch angle in a self-adaptive mode within the range of 45-75 degrees; constructing an energy potential matching matrix of the temperature gradient of the heat storage module and the output voltage of the power generation system, and combining a pulse type energy release strategy to maintain power stability; and controlling adjacent flow channel branches to generate a phase difference based on pressure fluctuation spectrum characteristics to realize fluctuation offset. According to the method, through closed-loop control of thermodynamic parameter compensation and flow channel dynamic adjustment and space-time collaborative optimization of energy potential matching and pulse release, continuous and stable power generation under the intermittent irradiation condition is achieved, the overall energy efficiency of the system is improved, and operation is more stable.

Description

Technical Field

[0001] The invention relates to an electric energy conversion and power regulation method based on a solar heat exchange coupling system, and belongs to the technical field of solar heat utilization. Background Art

[0002] Solar thermal exchange systems convert solar heat into electrical energy through the circulation of a working fluid. Their core is to efficiently transfer heat energy and maintain stable power output. However, in actual applications, intermittent fluctuations in solar radiation, nonlinear changes in the flow state of the working fluid, and problems with the coordinated control of heat storage and power generation systems have led to a significant reduction in the energy efficiency of traditional systems in dynamic environments.

[0003] In the existing technology, fixed-structure heat exchange pipelines and threshold control strategies are generally used to regulate the flow of working fluids. For example, the pump frequency is adjusted by presetting the flow rate threshold, or static temperature gradient partitions are set in the heat storage module. Although such solutions can adapt to steady-state working conditions, they have the following problems: 1. Dynamic response lag: Traditional linear models are difficult to accurately characterize the thermodynamic lag effect in the phase change process of the working fluid. When the solar radiation suddenly changes, the nonlinear relationship between the latent heat release rate of the working fluid and the temperature and pressure is not captured in real time, resulting in compensation delays (usually more than 3 seconds), causing power fluctuations and even local overheating; 2. Insufficient suppression of pressure fluctuations: Fixed flow The channel structure cannot adapt to changes in flow rate, and the working fluid is prone to high-frequency pressure fluctuations (the amplitude of the 20-30Hz frequency band exceeds the standard) when switching between laminar flow and turbulent flow. Traditional solutions rely on physical damping devices to passively absorb fluctuation energy, but the suppression efficiency is low (<50%), and it increases system complexity and maintenance costs; 3. The coupling of thermal storage and power generation is rigid: the thermal storage module and the power generation system mostly use static proportional distribution or time threshold switching, and lack consideration of the dynamic matching of energy potential gradients. For example, under low irradiation conditions, the waste heat in the high-temperature zone of the thermal storage module is not called upon first, resulting in insufficient power generation continuity; and when the irradiation is restored, the energy distribution hysteresis causes waste.

[0004] To address the above issues, existing improvement schemes attempt to introduce multi-sensor fusion or bionic flow channel design. For example, by combining infrared temperature measurement with pressure sensors to invert the working fluid state, or by using fractal flow channels to optimize laminar flow stability, such schemes still have limitations: multi-source signal fusion relies on linear weighting and does not address the spatiotemporal coupling effect of thermodynamic parameters; the bionic flow channel structure is fixed and cannot dynamically adapt to flow rate changes, and external control equipment is required to suppress high-frequency fluctuations, resulting in high energy consumption. In addition, the coordination of heat storage and power generation still relies on empirical thresholds, and the energy potential relationship between temperature gradient and output voltage has not been incorporated into a unified control framework. Therefore, how to achieve real-time and precise control of the working fluid flow state, efficiently suppress pressure fluctuations, and improve the dynamic coordination capability of the heat storage power generation system has become the technical problem to be solved by the present invention. Summary of the Invention

[0005] The present invention provides an electric energy conversion and power regulation method based on a solar heat exchange coupling system, the main purpose of which is to solve the problems of dynamic response hysteresis, inefficient fluctuation suppression and rigid energy-potential coupling.

[0006] To achieve the above objectives, the present invention provides a method for power conversion and power regulation based on a solar heat exchange coupling system, comprising the following steps: Step 1: Collect the temperature distribution signal of the outer wall of the heat exchange pipeline and the pressure fluctuation signal inside the heat exchange pipeline; Based on the thermodynamic parameters of the working fluid near the critical point of phase change, establish a nonlinear prediction model for characterizing the phase change kinetic process of the working fluid. The nonlinear prediction model is used to calculate the compensation factor , the compensation factor Determined according to the following formula: , in, is the latent heat release rate per unit time of the working fluid calculated in real time based on the temperature distribution signal, The sensitivity of the working fluid pressure to temperature changes is calculated in real time based on the temperature distribution signal and the pressure fluctuation signal. and is the weight coefficient determined based on the historical operating data of the solar thermal system; using the compensation factor Process the fusion weight of the temperature distribution signal and the pressure fluctuation signal, and output the working fluid state data after the thermodynamic hysteresis effect is compensated in real time. The compensated working fluid state data includes the flow rate, phase change state and local thermal resistance of the working fluid; Step 2: Based on the compensated working fluid state data, a bionic fractal flow channel made of a shape memory alloy embedded in the heat exchange pipeline is driven to perform dynamic structural adaptive adjustment. The dynamic structural adaptive adjustment includes: adjusting the flow channel branch angle of the bionic fractal flow channel within a preset first angle adjustment range (45°-75°) and adjusting the fractal level of the bionic fractal flow channel within a preset first fractal level range (levels 3-5) based on the working fluid flow rate and pressure difference in the compensated working fluid state data, so as to optimize the laminar flow stability of the working fluid in the heat exchange pipeline and control the flow pressure drop; Step 3: Construct an energy-potential matching matrix between the temperature gradient of the thermal storage module and the output voltage of the power generation system. Based on the calculation results of the energy-potential matching matrix and in combination with external environmental parameters, dynamically allocate the energy coupling ratio between the thermal storage module and the power generation system. When intermittent fluctuations in the solar irradiance in the environment where the solar heat exchange system is located are detected, a pulsed energy release strategy is activated. By controlling the flow of the working fluid, after a predetermined storage period and according to a predetermined release period, the energy stored in the high-temperature area of ​​the thermal storage module is preferentially called upon to maintain the continuity of the power output of the power generation system. Step 4: extract the pressure fluctuation spectrum characteristics generated by the working fluid flowing in the heat exchange pipeline based on the pressure fluctuation signal; according to the pressure fluctuation spectrum characteristics, control the bionic fractal flow channel made of shape memory alloy material to generate a predetermined phase difference between adjacent flow channel branches downstream of the working fluid flow direction. The predetermined phase difference is intended to make the pressure peaks and troughs generated by the adjacent flow channel branches interact with each other, so as to attenuate the pressure fluctuation amplitude in the heat exchange pipeline.

[0007] Preferably, the weight coefficient and The determination is made by: collecting the actual state parameters of multiple groups of working fluids and the corresponding latent heat release rate per unit time during the unsteady-state operation of the solar heat exchange system , Sensitivity of pressure to temperature changes , using machine learning algorithms, with the goal of minimizing the deviation between the compensated working fluid state data and the actual state parameters, iteratively optimizes the weight coefficient and .

[0008] Preferably, the flow channel branch angle of the bionic fractal flow channel is adjusted within a preset first angle adjustment range (45°-75°) based on the working fluid flow rate and pressure difference in the compensated working fluid state data, specifically including: when the working fluid flow rate is lower than the first flow rate threshold determined according to the design parameters of the solar heat exchange system, the flow channel branch angle is increased to maintain laminar flow stability, and the increased angle value is negatively correlated with the difference between the working fluid flow rate and the first flow rate threshold; when the working fluid flow rate is higher than the second flow rate threshold determined according to the design parameters of the solar heat exchange system, the flow channel branch angle is reduced to reduce the flow pressure drop, and the reduced angle value is positively correlated with the difference between the working fluid flow rate and the second flow rate threshold, wherein the second flow rate threshold is greater than the first flow rate threshold.

[0009] Preferably, based on the calculation results of the energy potential matching matrix and combined with the external environmental parameters, the energy coupling ratio between the heat storage module and the power generation system is dynamically allocated, specifically including: real-time monitoring of the temperature gradient of the high temperature area in the heat storage module, recorded as ; Set the first temperature gradient threshold based on the rated efficiency of the power generation system ; When detected When it is determined that the heat storage capacity is weakened, the working fluid is first directed to the power generation system for power generation; when it is detected that When the external environment parameters include real-time solar irradiance and the current load demand of the power generation system , through the preset allocation rule function Calculate and determine the flow distribution ratio of the working fluid to the heat storage module and the power generation system.

[0010] Preferably, a pulsed energy release strategy is enabled to control the flow of the working fluid within a predetermined energy storage time. After that, according to the scheduled release time , give priority to calling the energy stored in the high temperature area of ​​the heat storage module, and the scheduled energy storage time and the scheduled release time The ratio is set to a fixed value or adjusted according to the frequency of solar irradiance fluctuations, and the ratio is maintained within a preset first time ratio range (between 2:1 and 5:1).

[0011] Preferably, according to the pressure fluctuation spectrum characteristics, the bionic fractal flow channel made of shape memory alloy is controlled to generate a predetermined phase difference between adjacent flow channel branches downstream of the working medium flow direction, specifically including: extracting the main frequency component in the pressure fluctuation spectrum characteristics and determining its amplitude within a preset specific frequency band (20-30Hz) ; Set the first amplitude threshold value determined based on the statistical distribution of pressure fluctuations under the stable operation state of the solar heat exchange system ; When the conditions are met When the phase difference control is triggered, the deformation of the shape memory alloy material required to generate the reverse phase pressure wave is calculated, and the deformation of the corresponding flow channel wall of the bionic fractal flow channel is controlled, so that the pressure waves generated by the deformation of the adjacent flow channel branches and the original pressure waves form interference and cancellation in this specific frequency band.

[0012] Preferably, the method also includes establishing a pressure fluctuation self-attenuation mechanism by utilizing the fluid inertia of the working fluid. The pressure fluctuation self-attenuation mechanism is specifically implemented in the following manner: while generating opposite-phase pressure waves in adjacent flow channel branches, the amplitude change of the pressure fluctuation is monitored in real time; according to the trend of the amplitude change, the angle of the flow channel branch is fine-tuned through a feedback control loop: in the area where the pressure fluctuation amplitude is detected to increase, the flow channel branch angle is appropriately increased to suppress the pressure increase by reducing the local flow velocity; in the area where the pressure fluctuation amplitude is detected to decrease, the flow channel branch angle is appropriately reduced to prevent the pressure from decreasing excessively by increasing the local flow velocity, and the fluid inertia is used to guide the working fluid flow toward a dynamic equilibrium state, thereby assisting in suppressing pressure fluctuations.

[0013] Preferably, the method further includes introducing a bioinspired autonomous rhythm synchronization strategy, which specifically includes: based on the main frequency component in the pressure fluctuation spectrum characteristics , dynamically generates a reference rhythm signal that matches the inherent characteristics of the working fluid flow, and the frequency of the reference rhythm signal Set to the main frequency component frequency The reference rhythm signal is used to characterize the slowly changing influencing factors caused by the day and night temperature difference or seasonal changes in the operating environment of the solar heat exchange system. The slowly changing influencing factors are obtained by analyzing the temperature distribution signal of a long time series.

[0014] Compared with the background technology problems, the beneficial effects of the present invention are: 1. A nonlinear prediction model is used to calculate the latent heat release rate and pressure-temperature sensitivity during the working fluid phase change process in real time, and a compensation factor is established to dynamically correct the signal fusion weight, effectively avoiding the distortion of the traditional linear model's representation of the thermodynamic hysteresis effect. This compensation mechanism forms a closed-loop feedback loop with the angle / level adjustment of the shape memory alloy flow channel: the compensated working fluid state data drives the intelligent adjustment of the flow channel branch angle within the range of 45-75°, maintaining laminar flow stability while avoiding a sharp increase in pressure drop. The synergistic effect of this thermodynamic parameter compensation and the physical deformation of the flow channel enables the system to maintain the steady-state characteristics of the working fluid flow even when the irradiation suddenly changes, avoiding the response bottleneck of traditional fixed flow channels and static models.

[0015] 2. By constructing an energy potential matrix of the temperature gradient of the heat storage module and the output voltage of the power generation system, the originally separated heat storage-power generation coupling is transformed into a multi-dimensional mapping relationship in the energy potential space. Combined with a pulsed energy release strategy, the energy storage / release timing is automatically switched when radiation fluctuations are detected, and the transient release characteristics of the working fluid phase change latent heat are used to fill the power gap. This mechanism cleverly combines the time domain characteristics (energy storage duration) and frequency domain characteristics (release pulses) of the thermodynamic process, allowing the system to quickly respond to transient demands when dealing with intermittent fluctuations, while avoiding equipment losses caused by frequent starts and stops, thereby achieving spatiotemporal coordinated optimization of energy buffering.

[0016] 3. Based on the spectral characteristics of pressure fluctuations, the phase difference between adjacent flow channel branches is actively adjusted, and high-frequency fluctuation energy is offset by peak-to-trough interference. This further introduces cardiovascular bionic logic: the flow channel regulation is decomposed into fast response (synchronous pressure fluctuations) and slow regulation (matching environmental rhythms) components to simulate the contraction coordination mechanism of vascular smooth muscle. This cross-band energy transfer strategy, combined with the effect of fluid inertia, causes high-frequency fluctuation energy to be transferred to the low-frequency region and then gradually dissipated, forming a self-attenuating network with biological system characteristics, avoiding the technical bottleneck of traditional damping devices' low efficiency in suppressing high-frequency fluctuations.

[0017] 4. The spatial dimension characteristics of the temperature distribution signal (outer wall thermal field gradient) and the temporal dimension characteristics of the pressure fluctuation signal (acoustic spectrum) are nonlinearly fused, and the working fluid state inversion accuracy is improved through dynamic weighting of the compensation factor. This data fusion mechanism and the microscopic lattice deformation of the shape memory alloy produce cross-scale synergy: macroscopic flow channel structure adjustment changes the working fluid flow path, and the microscopic deformation response corrects the local thermal resistance distribution in real time. This cross-scale interaction enables the system to achieve fine regulation of heat transfer efficiency through nanoscale surface deformation while maintaining overall structural stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flow chart of working medium state data processing in the present invention; Figure 2 The weight coefficient determination flow chart of the present invention; Figure 3 This is a flow chart of the adaptive adjustment of the dynamic structure of the bionic fractal flow channel of the present invention.

[0019] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0020] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0021] The present invention provides a method for converting and regulating electric energy based on a solar heat exchange coupling system, comprising the following steps: Step 1: Collect the temperature distribution signal of the outer wall of the heat exchange pipeline and the pressure fluctuation signal inside the heat exchange pipeline; Based on the thermodynamic parameters of the working fluid near the critical point of phase change, establish a nonlinear prediction model for characterizing the phase change kinetic process of the working fluid. The nonlinear prediction model is used to calculate the compensation factor , the compensation factor Determined according to the following formula: , in, is the latent heat release rate per unit time of the working fluid calculated in real time based on the temperature distribution signal, The sensitivity of the working fluid pressure to temperature changes is calculated in real time based on the temperature distribution signal and the pressure fluctuation signal. and is the weight coefficient determined based on the historical operating data of the solar thermal system; using the compensation factor Process the fusion weight of the temperature distribution signal and the pressure fluctuation signal, and output the working fluid state data after the thermodynamic hysteresis effect is compensated in real time. The compensated working fluid state data includes the flow rate, phase change state and local thermal resistance of the working fluid; Step 2: Based on the compensated working fluid state data, a bionic fractal flow channel made of a shape memory alloy embedded in the heat exchange pipeline is driven to perform dynamic structural adaptive adjustment. The dynamic structural adaptive adjustment includes: adjusting the flow channel branch angle of the bionic fractal flow channel within a preset first angle adjustment range (45°-75°) and adjusting the fractal level of the bionic fractal flow channel within a preset first fractal level range (levels 3-5) based on the working fluid flow rate and pressure difference in the compensated working fluid state data, so as to optimize the laminar flow stability of the working fluid in the heat exchange pipeline and control the flow pressure drop; Step 3: Construct an energy-potential matching matrix between the temperature gradient of the thermal storage module and the output voltage of the power generation system. Based on the calculation results of the energy-potential matching matrix and in combination with external environmental parameters, dynamically allocate the energy coupling ratio between the thermal storage module and the power generation system. When intermittent fluctuations in the solar irradiance in the environment where the solar heat exchange system is located are detected, a pulsed energy release strategy is activated. By controlling the flow of the working fluid, after a predetermined storage period and according to a predetermined release period, the energy stored in the high-temperature area of ​​the thermal storage module is preferentially called upon to maintain the continuity of the power output of the power generation system. Step 4: extract the pressure fluctuation spectrum characteristics generated by the working fluid flowing in the heat exchange pipeline based on the pressure fluctuation signal; according to the pressure fluctuation spectrum characteristics, control the bionic fractal flow channel made of shape memory alloy material to generate a predetermined phase difference between adjacent flow channel branches downstream of the working fluid flow direction. The predetermined phase difference is intended to make the pressure peaks and troughs generated by the adjacent flow channel branches interact with each other, so as to attenuate the pressure fluctuation amplitude in the heat exchange pipeline.

[0022] Preferably, the weight coefficient and The determination is made by: collecting the actual state parameters of multiple groups of working fluids and the corresponding latent heat release rate per unit time during the unsteady-state operation of the solar heat exchange system , Sensitivity of pressure to temperature changes , using machine learning algorithms, with the goal of minimizing the deviation between the compensated working fluid state data and the actual state parameters, iteratively optimizes the weight coefficient and .

[0023] Preferably, the flow channel branch angle of the bionic fractal flow channel is adjusted within a preset first angle adjustment range (45°-75°) based on the working fluid flow rate and pressure difference in the compensated working fluid state data, specifically including: when the working fluid flow rate is lower than the first flow rate threshold determined according to the design parameters of the solar heat exchange system, the flow channel branch angle is increased to maintain laminar flow stability, and the increased angle value is negatively correlated with the difference between the working fluid flow rate and the first flow rate threshold; when the working fluid flow rate is higher than the second flow rate threshold determined according to the design parameters of the solar heat exchange system, the flow channel branch angle is reduced to reduce the flow pressure drop, and the reduced angle value is positively correlated with the difference between the working fluid flow rate and the second flow rate threshold, wherein the second flow rate threshold is greater than the first flow rate threshold.

[0024] Preferably, based on the calculation results of the energy potential matching matrix and combined with the external environmental parameters, the energy coupling ratio between the heat storage module and the power generation system is dynamically allocated, specifically including: real-time monitoring of the temperature gradient of the high temperature area in the heat storage module, recorded as ; Set the first temperature gradient threshold based on the rated efficiency of the power generation system ; When detected When it is determined that the heat storage capacity is weakened, the working fluid is first directed to the power generation system for power generation; when it is detected that When the external environment parameters include real-time solar irradiance and the current load demand of the power generation system , through the preset allocation rule function Calculate and determine the flow distribution ratio of the working fluid to the heat storage module and the power generation system.

[0025] Preferably, a pulsed energy release strategy is enabled to control the flow of the working fluid within a predetermined energy storage time. After that, according to the scheduled release time , give priority to calling the energy stored in the high temperature area of ​​the heat storage module, and the scheduled energy storage time and the scheduled release time The ratio is set to a fixed value or adjusted according to the frequency of solar irradiance fluctuations, and the ratio is maintained within a preset first time ratio range (between 2:1 and 5:1).

[0026] Preferably, according to the pressure fluctuation spectrum characteristics, the bionic fractal flow channel made of shape memory alloy is controlled to generate a predetermined phase difference between adjacent flow channel branches downstream of the working medium flow direction, specifically including: extracting the main frequency component in the pressure fluctuation spectrum characteristics and determining its amplitude within a preset specific frequency band (20-30Hz) ; Set the first amplitude threshold value determined based on the statistical distribution of pressure fluctuations under the stable operation state of the solar heat exchange system ; When the conditions are met When the phase difference control is triggered, the deformation of the shape memory alloy material required to generate the reverse phase pressure wave is calculated, and the deformation of the corresponding flow channel wall of the bionic fractal flow channel is controlled, so that the pressure waves generated by the deformation of the adjacent flow channel branches and the original pressure waves form interference and cancellation in this specific frequency band.

[0027] Preferably, the method also includes establishing a pressure fluctuation self-attenuation mechanism by utilizing the fluid inertia of the working fluid. The pressure fluctuation self-attenuation mechanism is specifically implemented in the following manner: while generating opposite-phase pressure waves in adjacent flow channel branches, the amplitude change of the pressure fluctuation is monitored in real time; according to the trend of the amplitude change, the angle of the flow channel branch is fine-tuned through a feedback control loop: in the area where the pressure fluctuation amplitude is detected to increase, the flow channel branch angle is appropriately increased to suppress the pressure increase by reducing the local flow velocity; in the area where the pressure fluctuation amplitude is detected to decrease, the flow channel branch angle is appropriately reduced to prevent the pressure from decreasing excessively by increasing the local flow velocity, and the fluid inertia is used to guide the working fluid flow toward a dynamic equilibrium state, thereby assisting in suppressing pressure fluctuations.

[0028] Preferably, the method further includes introducing a bioinspired autonomous rhythm synchronization strategy, which specifically includes: based on the main frequency component in the pressure fluctuation spectrum characteristics , dynamically generates a reference rhythm signal that matches the inherent characteristics of the working fluid flow, and the frequency of the reference rhythm signal Set to the main frequency component frequency The reference rhythm signal is used to characterize the slowly changing influencing factors caused by the day and night temperature difference or seasonal changes in the operating environment of the solar heat exchange system. The slowly changing influencing factors are obtained by analyzing the temperature distribution signal of a long time series.

[0029] Preferably, the process of controlling the deformation of the bionic fractal flow channel made of shape memory alloy material further includes decomposing the deformation response of the shape memory alloy material into a fast response component and a slow adjustment component: the fast response component is calculated based on the high-frequency instantaneous fluctuation information in the pressure fluctuation spectrum characteristics, aiming to synchronize and offset the high-frequency instantaneous fluctuation in real time through rapid deformation; the slow adjustment component is calculated based on the reference rhythmic signal, aiming to adjust the reference shape of the bionic fractal flow channel through slow deformation to adapt to the slowly changing influencing factors; the deformation variable corresponding to the fast response component and the deformation variable corresponding to the slow adjustment component are superimposed to obtain a composite deformation variable, driving the bionic fractal flow channel made of shape memory alloy material to produce structural adjustment corresponding to the composite deformation variable.

[0030] Preferably, the method further includes enabling cardiovascular system bionic logic to offset cross-band fluctuation energy under high-frequency pressure fluctuation conditions. High-frequency pressure fluctuation refers to pressure fluctuation with a frequency higher than a first frequency threshold (30 Hz) determined according to the natural frequency of the heat exchange pipeline structure. The cardiovascular system bionic logic is specifically implemented in the following manner: when high-frequency pressure fluctuation is detected, the flow channel branch angle adjustment amplitude of the bionic fractal flow channel is established. Delay time for regulating response with adjacent flow channel branches The dynamic association rules between them are adopted to simulate the synergistic relationship between amplitude and time delay in the contraction and relaxation activities of vascular smooth muscle. The parameters of the composite deformation variable are adjusted according to the dynamic association rules, especially the amplitude and phase of the fast response component and the response rate of the slow regulation component, so as to promote the energy of high-frequency pressure fluctuations to be transferred to the low-frequency region where the reference rhythm signal is located. The slow-varying characteristics of the slow regulation component are combined with the inertia of the fluid to progressively dissipate the transferred low-frequency energy, so as to achieve stable and low-energy suppression of high-frequency pressure fluctuations.

[0031] Example 1: In this example, the latent heat release rate of the working fluid and the sensitivity of pressure to temperature change are calculated in real time through the temperature distribution signal and the pressure fluctuation signal, and a nonlinear prediction model is established. The core purpose of this model is to accurately characterize the thermodynamic hysteresis effect of the working fluid during the phase change process. Specifically, the compensation factor The fusion weights of temperature and pressure signals are dynamically modified by: , in, is the latent heat release rate of the working fluid per unit time, is the sensitivity of the working fluid pressure to temperature changes, and The weight coefficient is obtained by optimizing the historical data. The calculation and dynamic correction can accurately compensate for the thermodynamic hysteresis effect, and use the compensated working fluid state data as input for subsequent flow channel adjustment; at the same time, based on the compensated working fluid state data obtained above, including flow rate, pressure difference and other information, the heat exchange pipeline in this embodiment is embedded with a bionic fractal flow channel made of shape memory alloy. According to the flow rate and pressure difference of the working fluid, the branching angle and fractal level of the flow channel are dynamically adjusted within a preset range. When the working fluid flow rate is lower than the first flow rate threshold, the flow channel branching angle is increased to maintain the laminar stability of the flow; when the working fluid flow rate is higher than the second flow rate threshold, the flow channel branching angle is reduced to reduce the flow pressure drop; this adjustment mechanism dynamically adjusts the angle by calculating the difference between the flow rate and the threshold, and the adjustment angle is negatively correlated or positively correlated with the change in flow rate.

[0032] In this embodiment, the energy coupling relationship between the thermal storage module and the power generation system is converted into a mathematical model by constructing an energy-potential matching matrix between the temperature gradient of the thermal storage module and the output voltage of the power generation system. Based on this model and incorporating real-time environmental parameters (such as solar irradiance and load demand), the energy coupling ratio is dynamically adjusted. When the temperature gradient of the thermal storage module falls below a preset threshold, the working fluid is preferentially directed to the power generation system; otherwise, the working fluid is preferentially stored in the thermal storage module. When the system detects intermittent fluctuations in solar irradiance, a pulsed energy release strategy is activated. By controlling the flow of the working fluid and combining the energy of the working fluid in the high-temperature zone within the thermal storage module, the power output continuity of the power generation system is maintained. By analyzing the spectrum of the pressure fluctuation signal, this embodiment extracts the main frequency component based on the pressure fluctuation characteristics of the working fluid flow and determines the amplitude of this frequency. For high-frequency fluctuations (e.g., frequencies of 20-30 Hz), the phase difference between adjacent branches of the shape memory alloy flow channel is controlled, and the interference effect of pressure peaks and troughs is utilized to suppress the fluctuation amplitude, thereby effectively reducing the energy of the high-frequency fluctuations. Furthermore, when the amplitude of the pressure fluctuation increases, the flow channel branch angle is appropriately adjusted through the feedback mechanism to suppress the pressure increase; when the amplitude decreases, the flow channel branch angle is reduced to prevent the pressure from being too low. At this time, the fluid inertia further guides the working medium flow towards a dynamic equilibrium state.

[0033] Under high-frequency pressure fluctuation conditions, this embodiment adjusts the flow channel branching angle of the shape memory alloy flow channel through the bionic logic of the cardiovascular system, decomposing it into two components: fast response and slow adjustment. The fast response component performs real-time synchronous deformation according to the high-frequency instantaneous fluctuations of the pressure fluctuation, and the slow adjustment component adjusts the baseline shape of the flow channel according to the slow-changing influence of the environment, thereby achieving stable and low-energy suppression of high-frequency fluctuations. In addition, when high-frequency pressure fluctuations are detected, the energy of the fluctuation is gradually transferred to the low-frequency area by combining the fluid inertia and the cross-band energy transfer mechanism, and is further dissipated through slow adjustment, so that the system can efficiently suppress high-frequency fluctuations.

[0034] Example 2: This example combines Figures 1 to 3 , the power conversion and power control method based on the solar heat exchange coupling system is illustrated with drawings. Figure 1 As shown, first, the heat exchange pipeline generates a temperature distribution signal and a pressure fluctuation signal, which are collected by the sensing unit, that is, the sensing unit collects the temperature distribution signal and the sensing unit collects the pressure fluctuation signal; then, the signal processing module receives these collected signals and establishes a nonlinear prediction model based on thermodynamic parameters; then, the signal processing module calculates the compensation factor and dynamically corrects the signal fusion weight; finally, the signal processing module outputs the compensated working fluid state data and passes it to the state data output.

[0035] like Figure 2As shown, first, the solar heat exchange system collects data during non-steady-state operation and provides actual state parameters, including the latent heat release rate per unit time and the sensitivity of pressure to temperature changes; then, these data are input into the machine learning optimization module, which contains the minimization deviation objective function and drives the iterative optimization algorithm; through the calculation of the iterative optimization algorithm, the weight coefficient is output to determine the result, and finally the weight coefficient is obtained. and weight coefficient .

[0036] like Figure 3 As shown in the figure, the process starts with the compensated working fluid state data as input; first, the working fluid flow rate is judged. If the working fluid flow rate is lower than the first flow rate threshold, the flow channel branch angle is increased to optimize the laminar flow stability; if the working fluid flow rate is higher than the second flow rate threshold, the flow channel branch angle is reduced to reduce the flow pressure drop; if the working fluid flow rate is between the two thresholds, the current flow channel branch angle is maintained to maintain laminar flow stability and regulate the pressure drop; no matter which branch is processed, the dynamic structure adaptive adjustment will eventually be completed.

[0037] Example 3: This example specifically illustrates the specific implementation of a method for power conversion and power regulation based on a solar heat exchange coupling system. First, in processing the working fluid state data, the latent heat release rate per unit time is calculated by collecting the outer wall temperature distribution signal from multiple temperature sensors arranged along the working fluid flow direction in the heat exchange pipeline. Combined with the known physical parameters of the working fluid's specific heat capacity and phase change latent heat at different temperatures, as well as the working fluid's real-time mass flow rate measured by a flow sensor, the first law of thermodynamics and heat transfer principles are used to calculate the portion of the heat absorbed or released by the working fluid per unit time that is attributed to latent heat conversion when flowing through a certain length of the heat exchange pipeline. The sensitivity of pressure to temperature changes is calculated by collecting the pressure fluctuation signal within the heat exchange pipeline and the outer wall temperature distribution signal. Digital signal processing is then used to calculate the ratio of a small temperature change within a short time window to the resulting pressure fluctuation. This ratio, known as the temperature partial derivative of pressure with respect to temperature, represents the dynamic response sensitivity of the working fluid state to temperature changes. Although the nonlinear prediction model expresses the compensation factor in a linear form, its nonlinearity lies in the fact that its input parameters—the latent heat release rate per unit time and the sensitivity of pressure to temperature changes—are real-time, dynamic representations of the nonlinear phase change process of the working fluid. Furthermore, the compensation factor's processing of the signal fusion weights is a nonlinear mapping relationship. The compensation factor dynamically modifies the fusion weights of the temperature and pressure signals. This can be achieved by establishing a two-dimensional lookup table or employing a nonlinear function. The inputs to this lookup table are the real-time compensation factor value and the current working fluid state (e.g., an approximate temperature range). The outputs are weighting coefficients for the temperature and pressure signals in subsequent state inversion. These weighting coefficients are dynamically adjusted based on the compensation factor value. For example, when the compensation factor value is high, the weighting of the pressure fluctuation signal is appropriately increased to more quickly reflect the dramatic state changes before and after the phase change. The parameters of the lookup table or nonlinear function are optimized through offline training using machine learning methods. The optimization objective is to minimize the root mean square error between the real-time flow rate and phase change state of the working fluid obtained from the fused signal inversion and the corresponding parameters measured by other independent sensors (e.g., flowmeters and phase change detectors). The compensated working fluid state data, such as the working fluid flow rate, can be calculated in real time by fusing the processed temperature and pressure signals in combination with known fluid mechanics models (such as a pressure drop-flow relationship model considering phase change); the phase change state can be comprehensively judged by whether the temperature signal is on the phase change platform, the pressure fluctuation signal characteristics (such as whether a vaporization noise spectrum appears), and the local thermal resistance (the thermal resistance changes significantly during phase change); the local thermal resistance can be calculated based on the known compensated working fluid flow rate, the inner and outer wall temperatures of the heat exchange pipeline, and the correlation model between the heat transfer coefficient and parameters such as the phase change state and flow rate, all of which belong to extended implementation methods known to ordinary technology in this field.

[0038] Secondly, regarding the adaptive dynamic structure adjustment of biomimetic fractal flow channels made of shape memory alloys, the physical adjustment of the branch angle and fractal level of the shape memory alloy flow channel is achieved by integrating shape memory alloy wires or sheets into the hinges or joints of the flow channel branches. By controlling the current applied to the shape memory alloy or the heat from the hot working fluid flowing through it, it undergoes a phase change, causing a preset contraction or extension deformation, thereby driving the flow channel wall to change angle or disconnect / connect to change the fractal level. For example, one or more pairs of shape memory alloy actuators can be installed at each branch connection, and their deformation can be differentially controlled to achieve precise angle adjustment. When adjusting the flow channel branch angle based on the working fluid flow rate in the compensated working fluid state data, the first flow rate threshold is set to the flow rate corresponding to the critical Reynolds number for the transition from laminar flow to turbulent flow at the current flow channel fractal level and typical temperature and pressure, ensuring that laminar flow stability is maintained below this threshold. The second flow rate threshold is set to the flow rate at which a significant increase in the working fluid flow rate causes a sharp increase in flow pressure drop or may induce structural vibration. The relationship between increasing or decreasing the angle value and the difference between the flow rate and the threshold value can be achieved by establishing a piecewise linear function or a lookup table. For example, when the working fluid flow rate is between the first flow rate threshold and the second flow rate threshold, the current angle is maintained; when the flow rate is lower than the first threshold, the angle increase value is inversely proportional to the degree to which the flow rate is lower than the first threshold; when the flow rate is higher than the second threshold, the angle decrease value is proportional to the degree to which the flow rate is higher than the second threshold. The specific proportional coefficient is determined by fitting the experimental data of the system under different working conditions, aiming to achieve a smooth transition and control the pressure drop. The flow channel branch angle is adjusted according to the pressure difference. When the pressure difference exceeds the preset range, the angle of the relevant flow channel branch can be adjusted to change the local flow resistance. For example, the angle can be increased to reduce the local flow rate and reduce the pressure difference, or the angle can be decreased to increase the local flow rate and increase the pressure difference. The adjustment amount is related to the degree to which the pressure difference exceeds the range. The specific adjustment function is also determined by experimental calibration or simulation. The fractal level adjustment logic can be triggered when the flow channel branch angle adjustment is not sufficient to cope with large changes in flow rate or pressure. For example, when the flow rate is continuously far below the first threshold and the flow resistance needs to be further increased to maintain laminar flow, the fractal level can be increased; when the flow rate is continuously far above the second threshold and the pressure drop needs to be significantly reduced, the fractal level can be reduced.

[0039] Again, regarding the energy potential matching between the temperature gradient of the heat storage module and the output voltage of the power generation system and the pulsed energy release strategy, an energy potential matching matrix is ​​constructed. The temperature of the high-temperature area of ​​the heat storage module (a representation of the temperature gradient) and the output voltage of the power generation system can be measured in real time. These two parameters are used as the index or input of the matrix. The value of the matrix is ​​the efficiency prediction value or benefit score of the energy coupling output of electrical energy under the temperature and voltage state. The matrix data can be obtained through statistical analysis of the system's long-term operation data, theoretical calculation or simulation. The calculation result of the energy potential matching matrix, for example, obtains an energy potential matching index by inputting the current temperature and voltage query matrix. The higher the index, the more the "grade" of the energy stored in the current heat storage module matches the current "appetite" of the power generation system, and the more suitable it is for outputting energy. The energy coupling ratio between the heat storage module and the power generation system is dynamically allocated based on the calculation result of the energy potential matching matrix. When the energy potential matching index is high and the power generation system has a load demand, energy is preferentially called from the heat storage module. Allocation rule function It can be a multivariable function or a rule-based expert system, whose input is the temperature gradient of the high-temperature area of ​​the thermal storage module (for example, the difference between the highest and lowest temperatures), the real-time solar irradiance, and the current load demand of the power generation system, and the output is the ratio of the working fluid flow to the thermal storage module and the power generation system. For example, when the solar irradiance is high, the function output tends to flow the working fluid to the thermal storage module for energy storage; when the load demand is large and the energy potential matching index is high, the function output tends to flow the working fluid to the power generation system. The first temperature gradient threshold The determination is based on the minimum working fluid inlet temperature required to ensure stable operation of the power generation system near rated efficiency, which is converted into the minimum temperature gradient required in the high-temperature area of ​​the thermal storage module. When the pulsed energy release strategy is enabled, the predetermined storage and release durations are not fixed but are dynamically adjusted within a preset overall fluctuation period based on the frequency of the real-time solar irradiance fluctuation signal (for example, the dominant frequency determined by Fourier transform analysis of the irradiance signal). When the irradiance fluctuation frequency is high, the storage and release durations are shortened to enable faster response; when the fluctuation frequency is low, the durations are appropriately extended for smoother energy management. The storage-to-release duration ratio is maintained between 2:1 and 5:1, an empirically determined range based on balancing energy buffering capacity and power generation continuity. Energy stored in the high-temperature area of ​​the thermal storage module is prioritized by providing multiple independent working fluid outlets and associated control valves along the temperature gradient within the thermal storage module. Based on real-time temperature monitoring, the outlet valves in the high-temperature area are opened first, directing the hottest working fluid to the power generation system.

[0040] Furthermore, for the suppression of pressure fluctuations and bio-inspiration strategies, the pressure fluctuation spectrum characteristics are extracted. Real-time fast Fourier transform can be used to periodically analyze the pressure fluctuation signal in the heat exchange pipeline to obtain the amplitude and phase information of different frequency components. The selection of a specific frequency band (20-30Hz) is based on the analysis of the inherent frequency characteristics of the solar heat exchange system that is prone to structural resonance or fluid oscillation under typical operating conditions, and it is used as a frequency band that needs to be suppressed. The first amplitude threshold The determination of the pressure fluctuation is achieved by collecting a large amount of pressure fluctuation data during stable system operation (e.g., constant irradiation and stable power output), performing statistical analysis (e.g., calculating the standard deviation or average fluctuation amplitude), and setting the value above the normal fluctuation range as the threshold for triggering fluctuation suppression. The deformation of the shape memory alloy required to generate the anti-phase pressure wave is calculated by analyzing the propagation characteristics of the main frequency component within the flow channel and establishing a physical model or lookup table linking the deformation to the generated pressure wave characteristics. For example, finite element simulation can be used to analyze the impact of different channel wall deformation locations and degrees on the pressure wave within the flow channel. A mapping relationship can be established between the deformation and the amplitude, phase, and frequency of the generated pressure wave. Based on the main frequency component characteristics of the original pressure wave to be offset, the deformation required to achieve anti-phase interference is calculated. The deformation of the corresponding channel wall is generated by integrating a shape memory alloy actuator in a specific area of ​​the channel wall. By precisely controlling the current or heat applied to the actuator, the calculated deformation is generated, thereby changing the local channel geometry, causing precise perturbations in the fluid and generating a pressure wave in anti-phase with the original pressure wave in the target frequency band. The fluid inertia self-attenuation mechanism uses a feedback control system to continuously monitor the rate of change (i.e., trend) of pressure fluctuation amplitude. When the amplitude shows an increasing trend, the system determines that the fluctuation may intensify and immediately issues a command to the shape memory alloy actuator to slightly increase the flow channel branch angle, increasing local resistance. This uses the inertia of the working fluid to resist sudden changes in flow velocity, thereby suppressing pressure increases. When the amplitude shows a decreasing trend, the angle is slightly reduced to reduce resistance and prevent excessive pressure drops. This synergistic effect of fine-tuning the angle and fluid inertia causes the working fluid flow to tend to restore dynamic equilibrium through local kinetic energy conversion and resistance adjustment when subjected to fluctuation disturbances.

[0041] Regarding bio-inspired autonomous rhythmic synchronization strategies, the inherent characteristics of working fluid flow can be understood as the natural oscillation frequencies or response patterns that exist in a working fluid flow system under specific flow channel structures and working fluid properties. The generation of a baseline rhythmic signal can be achieved by extracting slowly varying periodic components (such as temperature variations associated with diurnal and seasonal cycles) from a long-term series of external ambient temperature signals through low-frequency filtering and trend analysis. These patterns are then converted into a low-frequency periodic signal serving as the baseline rhythmic signal. Its frequency is set within a preset ratio (1 / 3 to 1 / 2) of the frequency of the dominant component of the pressure fluctuation spectrum. This is based on the fact that maintaining a steady-state environment within an organism often relies on converting rapid, high-frequency external disturbances into slow, low-frequency internal adjustments, achieved through synchronization with the organism's inherent rhythms.

[0042] The shape memory alloy's deformation response is decomposed into a fast-response component and a slow-adjustment component, which are then controlled in a superimposed manner. The fast-response component is calculated based on the transient signal of high-frequency pressure fluctuations processed by a high-pass filter, generating a deformation command to quickly track and offset these transient fluctuations. The slow-adjustment component is calculated based on the baseline rhythmic signal processed by a low-pass filter, generating a deformation command to slowly adjust the baseline flow channel shape to accommodate gradual changes in the external environment. The composite deformation variable is the sum of the fast-response and slow-adjustment deformation commands, resulting in the total deformation control signal acting on the shape memory alloy actuator.

[0043] Under high-frequency pressure fluctuation conditions, the bionic logic of the cardiovascular system is activated to offset cross-band fluctuation energy. Dynamic association rules can establish a nonlinear mapping that maps the amplitude, frequency, and other characteristics of the current high-frequency pressure fluctuation to the required flow channel branch angle adjustment amplitude and the delay time of the adjacent branch response. This rule simulates the contraction strength and response delay characteristics of vascular smooth muscle under different physiological signal stimulation. According to this rule, the parameters of the composite deformation variable are adjusted. For example, when the high-frequency fluctuation amplitude is large, the amplitude of the fast response component can be appropriately increased, and a certain delay time can be introduced to control the deformation timing of adjacent branches. This allows the high-frequency fluctuation energy to be converted into a low-frequency periodic force on the fluid through the periodic and sequential changes of the flow channel structure, thereby pumping the high-frequency energy into the low-frequency region. During this process, the slow regulation component adjusts the baseline shape of the flow channel and, combined with the fluid inertia, continuously and slowly dissipates the energy transferred to the low-frequency area, just like the regulation of blood flow by vasoconstriction, thereby achieving overall stability and energy management. The entire cardiovascular bionic logic control receives the pressure fluctuation spectrum characteristics and baseline rhythmic signals through an independent control module, and outputs a composite deformation control signal to the shape memory alloy actuator, which works in synergy with the flow channel regulation based on flow velocity and pressure difference to achieve precise control of the flow state of the working fluid.

[0044] In the overall control system, the sensing unit continuously collects temperature and pressure signals, the signal processing module performs real-time calculations and state inversion, and transmits the compensated working fluid state data to the flow channel regulation control module and the energy potential matching control module. The pressure fluctuation analysis module processes the pressure signal and transmits its characteristics to the pressure fluctuation suppression control module. The energy potential matching control module controls the energy coupling distribution mechanism based on external environmental parameters and load requirements. The pressure fluctuation suppression control module and the flow channel regulation control module act together on the shape memory alloy flow channel actuator to achieve dynamic adjustment and fluctuation suppression of the structure. The data communication and control signal coordination between all modules are uniformly managed by a central controller or distributed control system to ensure that all parts work together to achieve stable regulation of the electrical energy conversion and power output of the solar thermal exchange system. These are all extended implementation methods known to ordinary technicians in this field.

[0045] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0046] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. 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.

Claims

1. The electric energy conversion and power control method based on the solar heat exchange coupling system is characterized in that: The method comprises the following steps: Step 1: Collect the temperature distribution signal of the outer wall of the heat exchange pipeline and the pressure fluctuation signal inside the heat exchange pipeline; Based on the thermodynamic parameters of the working fluid near the critical point of phase change, establish a nonlinear prediction model for characterizing the phase change kinetic process of the working fluid. The nonlinear prediction model is used to calculate the compensation factor , the compensation factor Determined according to the following formula: ， in, is the latent heat release rate per unit time of the working fluid calculated in real time based on the temperature distribution signal, The sensitivity of the working fluid pressure to temperature changes is calculated in real time based on the temperature distribution signal and the pressure fluctuation signal. and is the weight coefficient determined based on the historical operating data of the solar thermal system; using the compensation factor Process the fusion weight of the temperature distribution signal and the pressure fluctuation signal, and output the working fluid state data after the thermodynamic hysteresis effect is compensated in real time. The compensated working fluid state data includes the flow rate, phase change state and local thermal resistance of the working fluid; Step 2: Based on the compensated working fluid state data, a bionic fractal flow channel made of a shape memory alloy embedded in the heat exchange pipeline is driven to perform dynamic structural adaptive adjustment. The dynamic structural adaptive adjustment includes: adjusting the flow channel branch angle of the bionic fractal flow channel within a preset first angle adjustment range of 45°-75° and adjusting the fractal level of the bionic fractal flow channel within a preset first fractal level range of 3-5 levels based on the working fluid flow rate and pressure difference in the compensated working fluid state data, so as to optimize the laminar flow stability of the working fluid in the heat exchange pipeline and control the flow pressure drop; Step 3: Construct an energy-potential matching matrix between the temperature gradient of the thermal storage module and the output voltage of the power generation system. Based on the calculation results of the energy-potential matching matrix and in combination with external environmental parameters, dynamically allocate the energy coupling ratio between the thermal storage module and the power generation system. When intermittent fluctuations in the solar irradiance in the environment where the solar heat exchange system is located are detected, a pulsed energy release strategy is activated. By controlling the flow of the working fluid, after a predetermined storage period and according to a predetermined release period, the energy stored in the high-temperature area of ​​the thermal storage module is preferentially called upon to maintain the continuity of the power output of the power generation system. Step 4: extract the pressure fluctuation spectrum characteristics generated by the working fluid flowing in the heat exchange pipeline based on the pressure fluctuation signal; according to the pressure fluctuation spectrum characteristics, control the bionic fractal flow channel made of shape memory alloy material to generate a predetermined phase difference between adjacent flow channel branches downstream of the working fluid flow direction. The predetermined phase difference is intended to make the pressure peaks and troughs generated by the adjacent flow channel branches interact with each other, so as to attenuate the pressure fluctuation amplitude in the heat exchange pipeline.

2. The method for electric energy conversion and power regulation based on a solar heat exchange coupling system according to claim 1, characterized in that: Weight coefficient and The determination is made by: collecting the actual state parameters of multiple groups of working fluids and the corresponding latent heat release rate per unit time during the unsteady-state operation of the solar heat exchange system , Sensitivity of pressure to temperature changes , using machine learning algorithms, with the goal of minimizing the deviation between the compensated working fluid state data and the actual state parameters, iteratively optimizes the weight coefficient and .

3. The method for electric energy conversion and power regulation based on a solar heat exchange coupling system according to claim 1, characterized in that: Based on the working fluid flow rate and pressure difference in the compensated working fluid state data, the flow channel branch angle of the bionic fractal flow channel is adjusted within a preset first angle adjustment range of 45°-75°, specifically including: when the working fluid flow rate is lower than the first flow rate threshold determined according to the design parameters of the solar heat exchange system, the flow channel branch angle is increased to maintain laminar flow stability, and the increased angle value is negatively correlated with the difference between the working fluid flow rate and the first flow rate threshold; when the working fluid flow rate is higher than the second flow rate threshold determined according to the design parameters of the solar heat exchange system, the flow channel branch angle is reduced to reduce the flow pressure drop, and the reduced angle value is positively correlated with the difference between the working fluid flow rate and the second flow rate threshold, wherein the second flow rate threshold is greater than the first flow rate threshold.

4. The method for electric energy conversion and power regulation based on a solar heat exchange coupling system according to claim 1, characterized in that: Based on the calculation results of the energy potential matching matrix and combined with external environmental parameters, the energy coupling ratio between the heat storage module and the power generation system is dynamically allocated, specifically including: real-time monitoring of the temperature gradient of the high-temperature area in the heat storage module, recorded as ; Set the first temperature gradient threshold based on the rated efficiency of the power generation system ; When detected When it is determined that the heat storage capacity is weakened, the working fluid is first directed to the power generation system for power generation; when it is detected that When the external environment parameters include real-time solar irradiance and the current load demand of the power generation system , through the preset allocation rule function Calculate and determine the flow distribution ratio of the working fluid to the heat storage module and the power generation system.

5. The method for electric energy conversion and power regulation based on a solar heat exchange coupling system according to claim 1, characterized in that: Enable pulse energy release strategy, by controlling the flow of working fluid, within the predetermined energy storage time After that, according to the scheduled release time , give priority to calling the energy stored in the high temperature area of ​​the heat storage module, and the scheduled energy storage time and the scheduled release time The ratio is set to a fixed value or adjusted according to the frequency of solar irradiance fluctuations, and the ratio is maintained within a preset first time ratio range of 2:1 to 5:

1.

6. The method for electric energy conversion and power regulation based on a solar heat exchange coupling system according to claim 1, characterized in that: Based on the pressure fluctuation spectrum characteristics, the bionic fractal flow channel made of shape memory alloy is controlled to produce a predetermined phase difference between adjacent flow channel branches downstream of the working fluid flow direction. Specifically, the main frequency component in the pressure fluctuation spectrum characteristics is extracted and its amplitude is determined within a preset specific frequency band of 20-30Hz. ; Set the first amplitude threshold value determined based on the statistical distribution of pressure fluctuations under the stable operation state of the solar heat exchange system ; When the conditions are met When the phase difference control is triggered, the deformation of the shape memory alloy material required to generate the reverse phase pressure wave is calculated, and the deformation of the corresponding flow channel wall of the bionic fractal flow channel is controlled, so that the pressure waves generated by the deformation of the adjacent flow channel branches and the original pressure waves form interference and cancellation in this specific frequency band.

7. The method for electric energy conversion and power regulation based on a solar heat exchange coupling system according to claim 6, characterized in that: The method also includes using the fluid inertia of the working fluid to establish a pressure fluctuation self-attenuation mechanism, which is specifically implemented in the following manner: while generating anti-phase pressure waves in adjacent flow channel branches, the amplitude changes of the pressure fluctuations are monitored in real time; according to the trend of the amplitude change, the angle of the flow channel branch is fine-tuned through a feedback control loop: in an area where an increasing trend of the pressure fluctuation amplitude is detected, the flow channel branch angle is moderately increased to suppress the pressure increase by reducing the local flow velocity; in an area where a decreasing trend of the pressure fluctuation amplitude is detected, the flow channel branch angle is moderately reduced to prevent excessive pressure reduction by increasing the local flow velocity, and the fluid inertia is used to guide the working fluid flow toward a dynamic equilibrium state, thereby assisting in suppressing pressure fluctuations.

8. The method for electric energy conversion and power regulation based on a solar heat exchange coupling system according to claim 7, characterized in that: The method also includes introducing a bio-inspired autonomous rhythm synchronization strategy, which specifically includes: based on the main frequency component in the pressure fluctuation spectrum characteristics , dynamically generates a reference rhythm signal that matches the inherent characteristics of the working fluid flow, and the frequency of the reference rhythm signal Set to the main frequency component frequency The reference rhythm signal is used to characterize the slowly changing influencing factors caused by the day and night temperature difference or seasonal changes in the operating environment of the solar heat exchange system, and the slowly changing influencing factors are obtained by analyzing the temperature distribution signal of the long time series.

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