Intelligent solar heat supply temperature management and adjustment system

Abstract

The invention relates to the technical field of temperature control, in particular to an intelligent solar heat supply temperature management and adjustment system which comprises a thermal distribution modeling module, a thermal equilibrium optimization module, a fluid heat transfer design module, a dynamic layout adjustment module and an environmental factor coupling module. According to the method, through calculation based on solar radiation intensity and heat absorption parameters, a thermal distribution field is accurately established, a dynamic optimization basis is provided, thermal gradient differences are reduced, heat distribution balance is achieved, and through optimization of heat absorption coating covering density and pipeline layout, the heat energy transfer efficiency is improved, and local overheating and energy loss are reduced; pipeline distribution and fluid flow rate optimization are combined with heat transfer oil heat exchange performance, heat transfer efficiency is enhanced, radiation angles and layout parameters are dynamically adjusted, the solar energy absorption rate of the heat collection device is improved, output parameters are adjusted in real time in combination with environment temperature and wind speed, the capacity of the system for adapting to complex climate conditions is improved, and efficient and stable heat energy utilization is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of temperature control, and in particular to an intelligent solar heating temperature management and regulation system. Background Art

[0002] The technical field of temperature control includes technologies for monitoring, regulating, and managing temperature through automated means. Its core content is the automated control of temperature based on external environment or internal requirements, and it is widely applied in industrial production, home environment, transportation vehicles, medical equipment, and other fields. The overall technical field includes the coordinated work of sensors for temperature data collection, controllers for analyzing temperature data, and actuators for adjusting temperature conditions. The technologies in this field usually involve the integration and coordination of sensing technologies, thermodynamic principles, and actuating elements, aiming to achieve precise management of temperature variables.

[0003] Among them, the intelligent solar heating temperature management and regulation system refers to a system for intelligently regulating temperature in a heating environment developed based on solar heat sources. The patent theme focuses on how to make full use of solar thermal energy to achieve temperature management in the heating environment. It mainly uses real-time temperature monitoring devices to obtain temperature parameters of the heating system, adjusts the flow rate and heating intensity of the heat transfer medium through regulating devices, and combines a control unit based on logical analysis to dynamically optimize the management of temperature. The involved contents include heat collection in solar collectors, heat transfer in pipeline systems, real-time data collection by temperature sensing elements, and closed-loop control means linked with regulating valves, so as to achieve precise regulation and continuous management of temperature.

[0004] The prior art lacks the ability to accurately model the thermal distribution characteristics and perform real-time dynamic optimization, making it difficult to cope with the unevenness problem in heat transfer, and easily causing local overheating or a decrease in heat transfer efficiency. The fixed-layout pipeline system is difficult to adjust the fluid ratio and path according to actual needs, resulting in low energy utilization efficiency. The influence of external environments such as wind speed and temperature fluctuations on heat transfer is not fully considered, showing poor adaptability in large climate changes. The heat transfer path and heat regulation cannot be adjusted specifically, lacking efficiency and stability in complex environments, and easily causing problems such as insufficient heating or excessive energy consumption, affecting the long-term performance of the system. Summary of the Invention

[0005] The purpose of the present invention is to solve the deficiencies existing in the prior art, and to propose an intelligent solar heating temperature management and regulation system.

[0006] To achieve the above purpose, the present invention adopts the following technical solutions: An intelligent solar heating temperature management and regulation system includes:

[0007] The thermal distribution modeling module calculates the energy absorption and conduction rates based on the solar radiation intensity and the heat absorption parameters of the collector surface, evaluates the characteristics of heat transfer distribution, establishes a thermal distribution field according to the absorption and conduction characteristics, and generates a numerical distribution of the thermal continuous field;

[0008] The thermal equilibrium optimization module analyzes the thermal gradient and variance based on the numerical distribution of the thermal continuous field, calls the covering parameters of the heat-absorbing coating and the performance parameters of the fluid pipeline, adjusts the covering density and pipeline layout, optimizes the balance of heat distribution, and generates the optimized adjustment parameter values of the thermal distribution;

[0009] The fluid heat transfer design module evaluates the flow rate and heat transfer performance of the heat transfer oil based on the optimized adjustment parameter values of the thermal distribution, calculates the relationship between the pipeline distribution and the flow rate, optimizes the fluid ratio and path length, reconfigures the heat transfer path, and generates the optimized parameter values of the fluid heat transfer network;

[0010] The dynamic layout adjustment module calculates the relationship between the dynamic radiation angle and the absorption efficiency per unit area based on the optimized parameter values of the fluid heat transfer network, analyzes the matching of the absorption efficiency and the radiation angle, adjusts the angle and the layout parameters of the heat collection unit, and generates the dynamic layout parameter values of the heat collection unit;

[0011] The environmental factor coupling module evaluates the influence of the wind speed and environmental temperature on the thermal distribution based on the dynamic layout parameter values of the heat collection unit, analyzes the relationship between the heat fluctuation and the external boundary conditions, adjusts the radiation angle and the output parameters, and generates the optimized parameter values of the environmental factor coupling.

[0012] As a further solution of the present invention, the numerical distribution of the thermal continuous field includes the energy absorption rate distribution, the energy conduction rate distribution, and the heat transfer characteristic distribution. The optimized adjustment parameter values of the thermal distribution are specifically the covering density parameter of the heat-absorbing coating, the pipeline layout parameter of the fluid, and the thermal gradient equilibrium parameter. The optimized parameter values of the fluid heat transfer network include the flow rate parameter of the heat transfer oil, the optimized pipeline distribution parameter, the optimized fluid ratio parameter, and the heat transfer path configuration parameter. The dynamic layout parameter values of the heat collection unit specifically refer to the dynamic radiation angle parameter, the absorption efficiency parameter per unit area, and the layout parameter of the heat collection unit. The optimized parameter values of the environmental factor coupling include the radiation angle adjustment parameter, the optimized output parameter value, and the thermal fluctuation boundary condition parameter.

[0013] As a further solution of the present invention, the specific steps for obtaining the numerical distribution of the thermal continuous field are as follows:

[0014] Based on the acquisition results of the solar radiation intensity parameters and the heat absorption parameters of the collector surface, extract the time series values and spatial distribution characteristics of the solar radiation intensity to generate a solar radiation distribution matrix, extract the time series values and spatial distribution characteristics of the heat absorption parameters to generate a heat absorption distribution matrix, and generate a solar radiation and heat absorption distribution matrix through matrix fusion operation;

[0015] Using the solar radiation and heat absorption distribution matrix, combining the regional differences in energy absorption rate and conduction rate, calculate the regional distribution value of the energy absorption rate, calculate the regional distribution value of the energy conduction rate, calculate the regional heat transfer rate by comparing the local heat transfer efficiency differences, and generate the regional heat transfer rate result;

[0016] Through the solar radiation and heat absorption distribution matrix and the regional heat transfer rate result, perform iterative optimization on the heat transfer rate of the target space point, using the formula:

[0017]

[0018] Calculate the numerical characteristics of the heat distribution field and generate the numerical distribution of the thermal continuous field;

[0019] Among them, T d represents the distribution value of the thermal continuous field, S i represents the spatial distribution parameter of the solar radiation intensity, H i represents the heat absorption parameter, E i represents the energy conduction rate parameter, R i represents the regional heat transfer rate parameter, i is the spatial point index, and n is the total number of spatial points.

[0020] As a further solution of the present invention, the steps for obtaining the optimized adjustment parameter value of the thermal distribution are specifically as follows:

[0021] Extract the calculation data of the thermal gradient and variance from the numerical distribution of the thermal continuous field. When calculating the thermal gradient, perform directional differentiation based on the temperature change rate of multiple spatial points. When calculating the variance, perform a normalization operation on the sum of the squared deviations of the regional thermal distribution value from the mean to generate the initial thermal distribution characteristic data;

[0022] According to the heat absorption coating coverage parameter and the fluid pipeline performance parameter, use the coverage parameter to calculate the relationship between the density change of the heat absorption coating and the heat absorption efficiency, and analyze the influence of the pipeline layout on the heat flow balance based on the pipeline performance parameter to generate a preliminary pipeline layout and coverage density scheme;

[0023] Through the initial thermal distribution characteristic data and the preliminary pipeline layout and coverage density scheme, optimize the heat distribution balance for the target space point, using the formula:

[0024]

[0025] Calculate the optimized parameter value as the optimized adjustment parameter value of the thermal distribution;

[0026] Among them, P opt represents the optimized thermal distribution parameter value, G i represents the thermal gradient, Vi represents variance, C d represents coverage density, P d represents pipeline layout parameter, A d represents area parameter, β is the weight adjustment coefficient, and n is the number of spatial points.

[0027] As a further solution of the present invention, the steps for obtaining the optimized parameter values of the fluid heat transfer network are specifically as follows:

[0028] Extract the relationship between the flow velocity and the heat transfer performance from the optimized adjustment parameter values of the thermal distribution, calculate the change value of the flow velocity of the heat transfer oil in the differential pipeline area, analyze the local difference of the flow velocity distribution based on the linear change trend of the heat exchange efficiency with the flow velocity, and generate preliminary flow velocity and heat transfer performance data;

[0029] According to the relationship between the pipeline distribution and the flow velocity, proportionally adjust the flow velocity in combination with the preliminary data, optimize the flow velocity distribution and adjust the path length, calculate the adaptation value of the fluid ratio according to the path optimization result, and generate fluid ratio adjustment parameter and path length configuration data;

[0030] Through the preliminary flow velocity and heat transfer performance data and the fluid ratio adjustment parameter and path length configuration data, combine the fluid parameters to optimize the fluid heat transfer path, and use the formula:

[0031]

[0032] Calculate the optimized value of the fluid heat transfer path and generate the optimized parameter values of the fluid heat transfer network;

[0033] where, F opt represents the optimized parameter value of the fluid heat transfer network, V i represents the flow velocity, Q i represents the heat exchange performance, γ is the fluid ratio adjustment coefficient, L i represents the path length, δ is the pipeline path adjustment coefficient, i is the spatial point index, and n is the number of calculation points.

[0034] As a further solution of the present invention, the steps for obtaining the dynamic layout parameter values of the heat collection unit are specifically as follows:

[0035] Extract the correlation data between the dynamic radiation angle and the absorption efficiency per unit area from the optimized parameter values of the fluid heat transfer network, calculate the change rate of the radiation angle at different positions, combine the spatial distribution characteristics of the absorption efficiency per unit area, analyze the fluctuation value of the absorption characteristics of different spatial points, and generate radiation angle and absorption efficiency relationship data;

[0036] Based on the data of the relationship between the radiation angle and the absorption efficiency, by calculating the proportional relationship of the deviation between the radiation angle and the absorption efficiency, the heat collection units with relatively large absorption efficiency deviations are screened, the radiation angle parameters are adjusted point by point according to the screening results, the matching degree values of multiple spatial points are recalibrated, and the data of the radiation angle and the layout adjustment are generated;

[0037] Based on the data of the radiation angle and the layout adjustment, combined with the characteristic parameters of the heat collection unit, the optimization ratio of the dynamic absorption efficiency and the matching degree of the radiation angle is analyzed, and the formula is used:

[0038]

[0039] Calculate the dynamic layout optimization adjustment value of the heat collection unit, and generate the dynamic layout parameter value of the heat collection unit;

[0040] Among them, D adj represents the dynamic layout optimization adjustment value, A i represents the absorption efficiency per unit area, R i represents the matching value of the radiation angle and the absorption efficiency, E i represents the radiation angle adjustment amount, μ is the dynamic absorption adjustment coefficient, L i represents the square root value of the sum of the squared coordinates of the center point of the heat collection unit, η is the layout matching correction coefficient, i is the spatial point index, and n is the number of calculation points.

[0041] As a further solution of the present invention, the steps for obtaining the environmental factor coupling optimization parameter value are specifically as follows:

[0042] Based on the dynamic layout parameter value of the heat collection unit, environmental data including wind speed and environmental temperature are collected, the local effects of wind speed and temperature on the thermal distribution are statistically analyzed, the dynamic response value of the wind speed change on the thermal distribution and the correction value of the temperature change on the absorption efficiency are calculated, and the preliminary analysis result of the environmental impact is generated;

[0043] Using the preliminary analysis result of the environmental impact, for the environmental parameters and the heat distribution change values of multiple heat collection units, the correlation between the environmental parameter fluctuations and the boundary conditions is analyzed, the radiation angle is adjusted to reduce the heat distribution deviation, and the output parameters are updated based on the adjusted thermal field, and the data of the radiation angle and the boundary condition adjustment are generated;

[0044] Integrate the data of the radiation angle and the boundary condition adjustment, calculate the combined influence of the radiation angle adjustment and the environmental parameters, and optimize the dynamic coupling parameters in combination with the combined fluctuations of the wind speed and the temperature, and use the formula:

[0045]

[0046] Calculate the environmental factor coupling optimization adjustment value, and establish the environmental factor coupling optimization parameter value after adjustment;

[0047] Among them, E adj represents the optimized adjustment value of environmental factor coupling, V i represents the wind speed value of the i-th heat collection unit, U i represents the environmental temperature value of the i-th heat collection unit, P i represents the radiation angle adjustment value of the i-th heat collection unit, ζ is the radiation angle reference value, X i represents the horizontal coordinate value of the i-th heat collection unit, Y i represents the absorption efficiency value of the i-th heat collection unit, ω is the environmental correction coefficient, i is the spatial point index, and n is the total number of calculation points.

[0048] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0049] In the present invention, by calculating based on the solar radiation intensity and heat absorption parameters, a thermal distribution field is accurately established, providing a basis for dynamic optimization, reducing the difference in thermal gradients, and achieving a balanced heat distribution. By optimizing the coverage density of the heat-absorbing coating and the pipeline layout, the heat transfer efficiency is improved, and local overheating and energy loss are reduced. The combination of the pipeline distribution and the fluid flow rate with the heat transfer performance of the heat transfer oil enhances the heat transfer efficiency. The radiation angle and layout parameters are dynamically adjusted to improve the solar energy absorption rate of the heat collection device. By combining the environmental temperature and wind speed to adjust the output parameters in real time, the ability of the system to adapt to complex climate conditions is enhanced, and efficient and stable heat energy utilization is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is the system flow chart of the present invention;

[0051] Figure 2 is the flow chart of the steps for obtaining the numerical distribution of the thermal continuous field of the present invention;

[0052] Figure 3 is the flow chart of the steps for obtaining the optimized adjustment parameter values of the thermal distribution of the present invention;

[0053] Figure 4 is the flow chart of the steps for obtaining the optimized parameter values of the fluid heat transfer network of the present invention;

[0054] Figure 5 is the flow chart of the steps for obtaining the dynamic layout parameter values of the heat collection unit of the present invention;

[0055] Figure 6 is the flow chart of the steps for obtaining the optimized parameter values of the environmental factor coupling of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0056] To make the objectives, technical solutions and advantages of the present invention more comprehensible, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0057] In the description of the present invention, it should be understood that the orientation or positional relationships indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. are based on the orientation or positional relationships shown in the accompanying drawings. These are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention. In addition, in the description of the present invention, "a plurality of" means two or more unless otherwise specifically defined.

[0058] Embodiment 1

[0059] Please refer to Figure 1 , an intelligent solar heating temperature management and regulation system includes:

[0060] The thermal distribution modeling module calculates the energy absorption and conduction rate based on the solar radiation intensity and the heat absorption parameters of the collector surface, evaluates the heat transfer distribution characteristics, establishes a thermal distribution field according to the absorption and conduction characteristics, and generates a numerical distribution of the thermal continuous field;

[0061] The thermal equilibrium optimization module analyzes the thermal gradient and variance based on the numerical distribution of the thermal continuous field, calls the covering parameters of the heat-absorbing coating and the performance parameters of the fluid pipeline, adjusts the covering density and pipeline layout, optimizes the heat distribution balance, and generates the optimized adjustment parameter values of the thermal distribution;

[0062] The fluid heat transfer design module evaluates the flow rate and heat transfer performance of the heat transfer oil based on the optimized adjustment parameter values of the thermal distribution, calculates the relationship between the pipeline distribution and the flow rate, optimizes the fluid ratio and path length, reconfigures the heat transfer path, and generates the optimized parameter values of the fluid heat transfer network;

[0063] The dynamic layout adjustment module calculates the relationship between the dynamic radiation angle and the absorption efficiency per unit area based on the optimized parameter values of the fluid heat transfer network, analyzes the matching of the absorption efficiency and the radiation angle, adjusts the angle and the layout parameters of the heat collection unit, and generates the dynamic layout parameter values of the heat collection unit;

[0064] The environmental factor coupling module evaluates the influence of the wind speed and environmental temperature on the thermal distribution based on the dynamic layout parameter values of the heat collection unit, analyzes the relationship between the heat fluctuation and the external boundary conditions, adjusts the radiation angle and the output parameters, and generates the optimized parameter values of the environmental factor coupling.

[0065] The numerical distribution of the thermal continuous field includes the energy absorption rate distribution, the energy conduction rate distribution, and the heat transfer characteristic distribution. The specific values of the optimized adjustment parameters for the thermal distribution are the heat absorption coating coverage density parameter, the fluid pipeline layout parameter, and the thermal gradient equilibrium parameter. The optimized parameter values for the fluid heat transfer network include the heat transfer oil flow rate parameter, the pipeline distribution optimization parameter, the fluid ratio optimization parameter, and the heat transfer path configuration parameter. The specific values of the dynamic layout parameters for the heat collection unit refer to the dynamic radiation angle parameter, the absorption efficiency parameter per unit area, and the heat collection unit layout parameter. The optimized parameter values for the coupling of environmental factors include the radiation angle adjustment parameter, the optimized output parameter value, and the thermal fluctuation boundary condition parameter.

[0066] Please refer to Figure 2 , and the specific steps for obtaining the numerical distribution of the thermal continuous field are as follows:

[0067] Based on the acquisition results of the solar radiation intensity parameter and the heat absorption parameter on the surface of the collector, extract the time series values and spatial distribution characteristics of the solar radiation intensity, generate a solar radiation distribution matrix, extract the time series values and spatial distribution characteristics of the heat absorption parameter, generate a heat absorption distribution matrix, and through matrix fusion operation, generate a solar radiation and heat absorption distribution matrix;

[0068] Based on the acquisition results of the solar radiation intensity parameter and the heat absorption parameter on the surface of the collector, the solar radiation intensity parameter first calculates the average radiation intensity per hour in the time series according to the intensity curve recorded by the radiation detector during the daily sunshine period, generating a set of daily average solar radiation intensity values based on time. The spatial distribution characteristics are generated by interpolating the radiation measurement values at multiple sampling points within the observation area to form a radiation distribution matrix. The heat absorption parameter measures the absorptivity of the surface material of the collector, calculates the heat absorption amount value for each area in combination with the daily radiation intensity, and generates an absorption distribution matrix through the layout of the sampling points on the surface of the collector. Through matrix fusion operation, the joint distribution matrix is obtained by multiplying the radiation distribution value and the absorption distribution value at the corresponding positions, generating a solar radiation and heat absorption distribution matrix;

[0069] Using the solar radiation and heat absorption distribution matrix, combined with the regional differences in the energy absorption rate and conduction rate, calculate the regional distribution values of the energy absorption rate, calculate the regional distribution values of the energy conduction rate, and calculate the regional heat transfer rate by comparing the local heat transfer efficiency differences, generating the regional heat transfer rate result;

[0070] Using the solar radiation and heat absorption distribution matrix, the energy absorption rate parameter is tested through the thermal physics experiment to test the heat absorption efficiency curve of the absorption surface, and the absorbed heat distribution value per unit area is calculated. The energy conduction rate parameter is calculated through the thermal conductivity experiment of the material combined with the heat absorption distribution value to calculate the thermal conductivity of each spatial point. The regional heat transfer rate is calculated by the difference in the distribution values ​​of the energy absorption rate and the conduction rate. After the heat transfer rate distribution value of each point is obtained by the point-by-point calculation method, the regional average transfer rate is statistically calculated, and the results are optimized by eliminating local abnormal points to generate the regional heat transfer rate results.

[0071] Through the solar radiation and heat absorption distribution matrix and the regional heat transfer rate results, the heat transfer rate of the target space point is iteratively optimized using the formula:

[0072]

[0073] Calculate the numerical characteristics of the heat distribution field and generate the numerical distribution of the thermal continuous field;

[0074] Among them, T d Represents the distribution value of the thermal continuous field, S i Represents the spatial distribution parameter of solar radiation intensity, H i represents the heat absorption parameter, E i Represents the energy transfer rate parameter, R i Represents the regional heat transfer rate parameter, i is the spatial point index, and n is the total number of spatial points.

[0075] formula:

[0076]

[0077] The benefit of the formula is that by introducing the interaction of solar radiation intensity, heat absorption parameters and energy conduction rate and combining them with regional heat transfer rate parameters for normalized calculation, the accuracy and sophistication of the thermal field distribution results are improved.

[0078] Detailed explanation of the formula and the process of formula calculation and derivation:

[0079] S i The solar radiation intensity distribution value representing the sampling point is obtained by calculating the daily average radiation intensity through the radiation intensity record values ​​of multiple periods of the day;

[0080] H i Represents the heat absorption distribution value of the sampling point, which is obtained by calculating the material absorption rate and solar radiation intensity. The formula is:

[0081] H i =A i ·S i ;

[0082] Among them, Ai is the absorption rate of the sampling point;

[0083] E i represents the energy conduction rate, which is obtained by calculating the conduction efficiency and the unit heat absorption through a thermophysical experiment. The formula is:

[0084] E i = k·H i ;

[0085] where k is the thermal conductivity;

[0086] R i represents the regional heat transfer rate, which is obtained by calculating the difference in the distribution values of the heat absorption and the heat conduction rate;

[0087] Substitute the example parameters: Assume five sampling points, S 1 = 400, S 2 = 350, S 3 = 300, S 4 = 450, S 5 = 380, A 1 = 0.8, A 2 = 0.75, A 3 = 0.85, A 4 = 0.78, A 5 = 0.82, k = 0.9. Through formula calculation, we get:

[0088] H 1 = 0.8·400 = 320, H 2 = 0.75·350 = 262.5, H 3 = 0.85·300 = 255, H 4

[0089] = 0.78·450 = 351, H 5 = 0.82·380 = 311.6;

[0090] E 1 = 0.9·320 = 288, E 2 = 0.9·262.5 = 236.25, E 3 = 0.9·255 = 229.5, E 4

[0091] = 0.9·351 = 315.9, E 5 = 0.9·311.6 = 280.44;

[0092] Assume the regional heat transfer rates are R 1 = 0.9, R 2 = 0.85, R 3= 0.88, R 4 = 0.87, R 5

[0093] = 0.86, substitute into the formula:

[0094]

[0095] Calculate step by step:

[0096]

[0097] The result shows that the overall intensity of the numerical distribution of the thermal continuous field is 6043.53. This value, combined with the regional heat transfer rate, normalizes the thermal distribution field and is the core parameter for subsequent analysis of the thermal distribution characteristics.

[0098] Please refer to Figure 3 , and the specific steps for obtaining the optimized adjustment parameter values of the thermal distribution are as follows:

[0099] Extract the calculation data of the thermal gradient and variance from the numerical distribution of the thermal continuous field. When calculating the thermal gradient, perform directional differentiation based on the temperature change rate of multiple spatial points. When calculating the variance, perform a normalization operation on the sum of the squared deviations of the regional thermal distribution values from the mean value to generate initial thermal distribution characteristic data;

[0100] Extract the calculation data of the thermal gradient and variance from the numerical distribution of the thermal continuous field. The extraction of the thermal gradient is based on the temperature distribution of each spatial point. Calculate the temperature change rate between adjacent spatial points in the continuous field in a directional differentiation manner. The calculation formula is where ΔT represents the temperature difference between adjacent points, and Δx represents the distance between adjacent points. When specifically extracting, the temperature values of each point need to be read according to the data of the temperature sensor grid. Assume that the temperature data is T = [T 1 , T 2 , T 3 ,..., T n collected. Then calculate the thermal gradient of each point one by one. The calculation of the variance is based on the thermal distribution values within the region. Perform a normalization process by calculating the sum of the squared differences between each point and the regional average temperature. The calculation formula is where represents the regional average temperature. When collecting data, divide the distribution of spatial points into fixed grid units, and take multiple temperature measurement values within each unit to ensure the calculation accuracy. After all operations are completed, the initial thermal distribution characteristic data can be obtained.

[0101] According to the heat absorption coating coverage parameters and the fluid pipeline performance parameters, calculate the relationship between the density change of the heat absorption coating and the heat absorption efficiency using the coverage parameters, and analyze the influence of the pipeline layout on the heat flow balance based on the pipeline performance parameters to generate a preliminary pipeline layout and coverage density plan;

[0102] Based on the heat-absorbing coating coverage parameters and the fluid pipeline performance parameters, the calculation of the heat-absorbing coating coverage parameters needs to be based on the thickness of the coating and the material absorptivity. The heat absorption efficiency calculation formula is η c = α·d, where α represents the material absorptivity and d is the coating thickness. The absorptivity of various materials can be measured in the laboratory and combined with the actual coating thickness for calculation. The fluid pipeline performance parameters need to be comprehensively evaluated based on the thermal conductivity and internal flow velocity of the pipeline. The calculation formula for the thermal conductivity is where q is the heat transfer rate, L is the pipeline length, A is the cross-sectional area, and ΔT is the temperature difference. The thermal conductivity is calculated by reading the data of the pipeline material and the fluid velocity sensor. Combining the results of the heat absorption efficiency and the thermal conductivity, the best combination of the coverage density and the pipeline layout on the heat flow balance can be screened by comparing the simulation schemes of different combinations of coating thickness and pipeline layout, and finally a preliminary pipeline layout and coverage density scheme can be generated.

[0103] Based on the initial thermal distribution characteristic data and the preliminary pipeline layout and coverage density scheme, optimize the heat distribution balance for the target space points, using the formula:

[0104]

[0105] Calculate the optimized parameter value as the optimized adjustment parameter value for the thermal distribution;

[0106] where, P opt represents the optimized thermal distribution parameter value, G i represents the thermal gradient, V i represents the variance, C d represents the coverage density, P d represents the pipeline layout parameter, A d represents the area parameter, β is the weight adjustment coefficient, and n is the number of space points.

[0107] Formula:

[0108]

[0109] The benefit of the formula is that by introducing the combined weight analysis of the thermal gradient G i and the variance V i , combined with the coverage density C d of the heat-absorbing coating and the fluid pipeline layout parameter P d , as well as the area parameter A d and the adjustment coefficient β, it is possible to accurately optimize the heat distribution balance under the interaction of multiple parameters.

[0110] Detailed explanation of the formula and the formula calculation derivation process:

[0111] Assign the thermal gradient and variance to G i = [5, 6, 7] and V i = [3, 4, 2], the coverage density of the heat-absorbing coating is C d = 0.85, the fluid pipeline layout parameter is P d = 0.75, the area parameter is A d = 10, the adjustment coefficient is β = 1.2, and solve by substituting the parameter values:

[0112] 1. Calculate the product sum of the thermal gradient and variance:

[0113]

[0114] 2. Calculate the weighted sum of the adjustment coefficient, coverage density, and pipeline layout parameter:

[0115] β×(C d +P d ) = 1.2×(0.85 + 0.75) = 1.2×1.6 = 1.92;

[0116] 3. Substitute the above results into the optimization formula:

[0117]

[0118] The result shows that the optimized thermal distribution parameter value is 5.492. This value indicates that the heat balance parameter after optimizing factors such as the thermal gradient, variance, heat-absorbing coating coverage density, and pipeline layout can achieve the best balance state with the ratio of the target area. This result is directly used as the optimized adjustment parameter value of the thermal distribution for subsequent adjustment of the thermal system.

[0119] Please refer to Figure 4 , and the specific steps for obtaining the optimized parameter value of the fluid heat transfer network are as follows:

[0120] Extract the relationship between the flow rate and heat transfer performance from the optimized adjustment parameter value of the thermal distribution, calculate the change value of the flow rate of the heat transfer oil in different pipeline regions, analyze the local differences in the flow rate distribution based on the linear change trend of the heat exchange efficiency with the flow rate, and generate preliminary flow rate and heat transfer performance data;

[0121] Extract the relationship between flow velocity and heat transfer performance from the optimized adjustment parameter values of thermal distribution. The flow velocity data of the heat transfer oil can be obtained through the real-time records of monitoring equipment in different pipeline areas. The recorded flow velocity data will include position index, time, and flow velocity value. Based on this data, the regional distribution characteristics of the flow velocity can be analyzed. Further, the acquisition of heat exchange efficiency data depends on the real-time temperature difference between the outlet and inlet of the heat exchange unit by the temperature sensor and the measurement results of the flow sensor, and is calculated by the formula Q = m·C·ΔT, where m is the flow rate, C is the specific heat capacity of the heat transfer oil, and ΔT is the temperature difference. The heat exchange efficiency data obtained through calculation can be linearly regressed with different flow velocity values. By fitting the relationship curve of heat exchange efficiency changing with flow velocity, the distribution characteristics of flow velocity in different pipeline areas can be obtained. Finally, based on the flow velocity differences in local areas, preliminary flow velocity and heat transfer performance data are generated.

[0122] According to the relationship between pipeline distribution and flow velocity, combined with the preliminary data, adjust the flow velocity proportionally, optimize the flow velocity distribution and adjust the path length. Calculate the adaptation value of the fluid proportion according to the path optimization result, and generate the fluid proportion adjustment parameter and path length configuration data;

[0123] According to the preliminary flow velocity and heat transfer performance data and the basic data of pipeline distribution, combined with the physical parameters of the pipeline (including length, diameter, curvature, etc.), adjust the flow velocity proportionally. It can be calculated by the adjustment formula V′ i =V i ·R i where R i is the adjustment ratio factor, which is dynamically adjusted according to the flow velocity requirements in different pipelines; the optimization calculation of the path length needs to be based on the time required for the fluid to reach the terminal and the goal of maximizing heat exchange efficiency. The optimization path is solved by constructing a mathematical model of the shortest time problem for the heat transfer path, and can be determined by the formula L′ i =L i ·f(Q i ,T i ) where f(Q i ,T i ) represents the influence function of the path heat transfer efficiency. Recombine the adjusted flow velocity and path length to generate the fluid proportion adjustment parameter and path length configuration data.

[0124] Through the preliminary flow velocity and heat transfer performance data, the fluid proportion adjustment parameter and path length configuration data, combined with the fluid parameters, optimize the fluid heat transfer path, using the formula:

[0125]

[0126] Calculate the optimized value of the fluid heat transfer path and generate the optimized parameter value of the fluid heat transfer network;

[0127] where, Fopt Represents the optimized fluid heat transfer network parameter value, V i Represents the flow velocity, Q i Represents the heat exchange performance, γ is the fluid ratio adjustment coefficient, L i Represents the path length, δ is the pipeline path adjustment coefficient, i is the spatial point index, and n is the number of calculation points.

[0128] Formula:

[0129]

[0130] The benefit of the formula is that by introducing the flow velocity V i , the heat exchange performance Q i , the path length L i Combined with the ratio adjustment coefficient γ and the path adjustment coefficient δ, it can dynamically reflect the optimization of the fluid heat transfer path, and at the same time achieve the balanced adjustment of the flow velocity, heat transfer performance and path length.

[0131] Detailed explanation of the formula and the formula calculation derivation process:

[0132] V i The value of is obtained through the aforementioned flow velocity monitoring device. For example, the flow velocity measured in pipeline area A is 2.5 m / s, and in area B is 3.0 m / s, Q i is calculated through the heat exchange efficiency formula Q = m·C·ΔT. Among them, the measured flow rate m in area A is 0.8 kg / s, the specific heat capacity C is 2.1 kJ / (kg·K), and the temperature difference ΔT is 20 K, then Q i

[0133] = 0.8·2.1·20 = 33.6 kW; for L i , the path length is directly obtained through a pipeline measuring tool. For example, the path length in area A is 25 m, and in area B is 30 m. The values of γ and δ are determined by multiple thermodynamic experiments based on the pipeline parameters in the area. γ = 1.2, δ = 1.1.

[0134] Substitute the above parameters into the formula:

[0135]

[0136] Calculate step by step:

[0137]

[0138] F opt ≈ 4.05;

[0139] The results show that the optimized parameter value of the fluid heat transfer network is 4.05, which is directly related to the adjustment of the heat transfer path and the optimization of the flow rate and heat exchange performance. This indicates that through this optimization adjustment, the efficiency of the heat transfer path has been significantly improved, and it provides a feasible parameter basis for the precise configuration of the subsequent heat transfer network.

[0140] Please refer to Figure 5 , and the steps for obtaining the dynamic layout parameter value of the heat collection unit are specifically as follows:

[0141] Extract the correlation data between the dynamic radiation angle and the absorption efficiency per unit area from the optimized parameter value of the fluid heat transfer network, calculate the change rate of the radiation angle at different positions, combine the spatial distribution characteristics of the absorption efficiency per unit area, analyze the fluctuation value of the absorption characteristics at different spatial points, and generate the relationship data between the radiation angle and the absorption efficiency;

[0142] Extract the correlation data between the dynamic radiation angle and the absorption efficiency per unit area from the optimized parameter value of the fluid heat transfer network. For the dynamic radiation angle, quantify the heat transfer rate of the pipeline heat transfer fluid to different heat collection units as the heat absorption value per unit time. By monitoring the radiation intensity distribution of the absorption surface at different angles, based on the actual heat absorption efficiency of the heat collection unit, combined with the calculation of the heat transfer coefficient and radiation energy, analyze the heat absorption fluctuation range of each unit point by point, establish the change trend curve of the heat absorption efficiency, calculate the change rate of the radiation angle at different positions, determine the spatial distribution characteristics of the absorption efficiency per unit area at different spatial points by combining the heat absorption trend curve, divide the area with higher heat absorption efficiency and the low-efficiency area within the area based on this distribution characteristic, further determine the heat absorption deviation value through area comparison, and generate the relationship data between the radiation angle and the absorption efficiency;

[0143] Based on the relationship data between the radiation angle and the absorption efficiency, by calculating the proportional relationship between the deviation of the radiation angle and the absorption efficiency, screen the heat collection units with larger absorption efficiency deviations, adjust the radiation angle parameters point by point for the screening results, and re-correct the matching degree values of multiple spatial points to generate the radiation angle and layout adjustment data;

[0144] Based on the relationship data between the radiation angle and the absorption efficiency, by calculating the proportional relationship between the deviation of the radiation angle and the absorption efficiency, perform superposition calculation on the radiation angle distribution and the actual absorption efficiency distribution using a spatial matrix, screen one by one the points in the matrix with deviation values greater than a certain threshold, take the points with deviations greater than the threshold as the areas of heat collection units that need to be adjusted, reduce the deviation value by adjusting the tilt angle of the radiation angle of the heat collection unit, through the simple formula: ΔR = |R i -A iCalculate the change in the radiation angle of each unit, and adjust the inclination amplitude of the radiation angle point by point, so that the adjusted radiation angle gradually approaches zero with the deviation of the absorption efficiency. At the same time, limit the amplitude change of the inclination angle by setting the target value of the absorption efficiency. After multiple iterative corrections, the finally set angle inclination is used as the radiation adjustment parameter of the heat collection unit, and finally the matching degree values of each spatial point are re-calibrated to generate radiation angle and layout adjustment data;

[0145] Based on the radiation angle and layout adjustment data, combined with the characteristic parameters of the heat collection unit, analyze the optimization ratio of the dynamic absorption efficiency and the radiation angle matching degree, and use the formula:

[0146]

[0147] Calculate the dynamic layout optimization adjustment value of the heat collection unit to generate the dynamic layout parameter value of the heat collection unit;

[0148] Among them, D adj represents the dynamic layout optimization adjustment value, A i represents the absorption efficiency per unit area, R i represents the matching value of the radiation angle and the absorption efficiency, E i represents the radiation angle adjustment amount, μ is the dynamic absorption adjustment coefficient, L i represents the square root of the sum of the squared coordinates of the center point of the heat collection unit, η is the layout matching correction coefficient, i is the spatial point index, and n is the number of calculation points.

[0149] Formula:

[0150]

[0151] The advantage of the formula is that by calculating the difference between the absorption efficiency per unit area and the radiation angle matching value, combined with the adjustment amount and the distribution characteristics of the spatial points, the dynamic layout parameters of the heat collection unit are further optimized, thus improving the balance and overall optimization level of the heat absorption efficiency;

[0152] Detailed explanation of the formula and the derivation process of the formula calculation:

[0153] Obtaining and explanation of parameter values:

[0154] A i is the absorption efficiency per unit area, which is obtained by measuring the heat absorption per unit area of the heat absorption surface at different radiation angles, and is measured by a sensor. For example, the measured value at a certain point is 8.5 kW / m 2 ;

[0155] R i is the matching value of the radiation angle and the absorption efficiency, which is calculated from the radiation distribution characteristics of the standard absorption angle. For example, the corresponding value at a certain point is 9.0 kW / m 2 ;

[0156] E i is the radiation angle adjustment amount, which is the amplitude of the radiation angle change calculated according to the spatial matrix. For example, the calculated value at a certain point is 0.5;

[0157] μ is the dynamic absorption adjustment coefficient, which depends on the amplitude of the angle change and the heat absorption fluctuation amount. Assume the fluctuation at this point is ±0.3;

[0158] L i is the horizontal coordinate of the center point of the heat collection unit in the plane coordinate system, which is directly obtained according to the plane coordinate system. For example, the coordinate value of this point is 6.0;

[0159] η is the layout matching correction coefficient, which is corrected according to the actual heat distribution characteristics. For example, this value is 1.2;

[0160] n is the total number of points. For example, a total of 30 points are calculated;

[0161] Formula calculation process:

[0162] 1. Calculate the absolute difference between the absorption efficiency and the radiation angle matching value at each point: |A i -R i | = |8.5 - 9.0| = 0.5;

[0163] 2. Calculate the sum of the angle adjustment amount and the adjustment coefficient: E i +μ = 0.5 + 0.3 = 0.8;

[0164] 3. Calculate the square root of the absolute difference multiplied by the adjustment amount:

[0166] 4. Accumulate the values of all points:

[0167] 5. Calculate the denominator part:

[0169] 6. Calculate the final result:

[0170] This result indicates that the calculated dynamic layout optimization adjustment value is 0.4983, representing a small optimization amplitude for the current heat collection unit layout adjustment, close to the optimized matching value, and can be used as a reference basis for the final optimization adjustment to generate the dynamic layout parameter values of the heat collection unit.

[0171] Please refer to Figure 6 , and the specific steps for obtaining the coupling optimization parameter values of environmental factors are as follows:

[0172] Based on the dynamic layout parameter values of the heat collection unit, collect environmental data, including wind speed and environmental temperature, conduct statistics on the local influence of wind speed and temperature on the thermal distribution, calculate the dynamic response value of wind speed change on the thermal distribution and the correction value of temperature change on the absorption efficiency, and generate a preliminary analysis result of environmental impact;

[0173] Based on the dynamic layout parameter values of the heat collection unit, through collecting wind speed and environmental temperature data, comprehensively process the dynamic change of wind speed and the spatio-temporal distribution of environmental temperature. First, sample the wind speed per hour through a meteorological sensor to obtain the wind speed data sequence within 24 hours, and use the moving average method to smooth the short-term wind speed fluctuations and calculate the median wind speed at different heat collection units; Secondly, measure the local temperature change of each unit based on the thermal distribution field, collect the temperature distribution image through a high-resolution thermal imaging device, partition the temperature range, extract the average temperature value of each unit and the extreme points in the thermal distribution, and calculate through the temperature difference calculation formula ΔT=T max -T avg Obtain the temperature fluctuation characteristic value; Subsequently, combine the wind speed change and the temperature fluctuation characteristic value to construct a data matrix, normalize both to the interval range of 0 to 1, and determine the interaction relationship between the wind speed change and the temperature fluctuation through the covariance analysis method between matrix columns, and extract the coupling degree between the two; Finally, conduct a correlation analysis on the results of the wind speed and temperature coupling analysis and the dynamic layout parameters to obtain the sensitivity parameters of the thermal distribution response to environmental factors and generate a preliminary analysis result of environmental impact.

[0174] Using the preliminary analysis result of environmental impact, analyze the correlation between the environmental parameters and the change value of heat distribution of multiple heat collection units, adjust the radiation angle to reduce the heat distribution deviation, and update the output parameters based on the adjusted thermal field to generate the radiation angle and boundary condition adjustment data;

[0175] Using the preliminary analysis result of environmental impact, for the environmental parameters and the change value of heat distribution of each heat collection unit, first, input the wind speed characteristic value and the temperature characteristic value of each unit into the local heat distribution model. The model uses the formula Q = k·A·ΔT, where k is the thermal conductivity, A is the unit surface area, and ΔT is the temperature difference of the unit. Calculate the heat distribution according to the physical properties of the unit to obtain the theoretical heat value of each unit; Then, by comparing the actual heat distribution value of the unit with the theoretical heat value, calculate the heat distribution deviation value ΔQ = Q actual -Q theoryAnd screen the units with deviation values greater than the standard deviation. For the units with large deviations, locally optimize and adjust the model, adjust their radiation angle parameters, and after optimization, use the objective function Min(ΔQ) to minimize the deviation value to obtain the optimized heat distribution value. Finally, bring the optimized thermal distribution result into the overall thermal field simulation, update the radiation angle and thermal distribution data output by the system, and generate the radiation angle and boundary condition adjustment data.

[0176] Integrate the radiation angle and boundary condition adjustment data, calculate the combined effect of the radiation angle adjustment and environmental parameters, and optimize the dynamic coupling parameters in combination with the combined fluctuations of wind speed and temperature. Use the formula:

[0177]

[0178] Calculate the optimized adjustment value of the environmental factor coupling, and establish the optimized parameter value of the environmental factor coupling after adjustment;

[0179] Among them, E adj represents the optimized adjustment value of the environmental factor coupling, V i represents the wind speed value of the i-th heat collection unit, U i represents the environmental temperature value of the i-th heat collection unit, P i represents the i-th radiation angle adjustment value, ζ is the radiation angle reference value, X i represents the horizontal coordinate value of the i-th heat collection unit, Y i represents the absorption efficiency value of the i-th heat collection unit, ω is the environmental correction coefficient, i is the spatial point index, and n is the total number of calculation points.

[0180] Formula:

[0181]

[0182] The advantage of the formula is that by taking the square root of the sum of the squares of the wind speed and temperature, the fluctuation effect of the environmental factors is quantified, and the deviation degree of the adjustment parameters is analyzed in combination with the absolute difference of the radiation angle adjustment value, so as to optimize the thermal distribution of the system under dynamic environmental conditions.

[0183] Detailed explanation of the formula and the derivation process of the formula calculation:

[0184] For the wind speed parameter V i and the temperature parameter U i , collect 24 groups of data every hour through environmental sensors respectively, and calculate their daily average values as the wind speed V i = 5.6 m / s and the temperature

[0185] $\text{U}_i = 28.3\,\degree\text{C}$; the radiation angle adjustment value P iOutput from the optimization result of the previous paragraph, take P i = 45.5, the radiation angle reference value ζ = 40.0, the horizontal coordinate value X i = 15.2 m, the absorption efficiency value Y i = 0.85, the environmental correction coefficient ω = 2.0.

[0186] Substitute into the formula:

[0187] First step, calculate the numerator part:

[0188]

[0189] |P i - ζ| = |45.5 - 40.0| = 5.5;

[0190] The sum of the numerator = 28.85·5.5 = 158.675;

[0191] Second step, calculate the denominator part:

[0192] X i ·Y i = 15.2·0.85 = 12.92;

[0193] X i ·Y i + ω = 12.92 + 2.0 = 14.92;

[0194] The sum of the denominator = 14.92;

[0195] Third step, calculate the final value:

[0196]

[0197] The result shows that the final optimized adjustment value of environmental factor coupling is E adj = 10.64, this value indicates that through the coordinated adjustment of environmental factors (wind speed and temperature) and radiation angle, the environmental adaptability and dynamic thermal distribution optimization ability of the current system reach a stable value, and can be further used as the input parameters for system coupling optimization.

[0198] The above is only the preferred embodiment of the present invention, and it does not limit the present invention in other forms. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution content of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. An intelligent solar heating temperature management and regulation system, characterized in that: The system comprises: The thermal distribution modeling module calculates the energy absorption and conduction rate based on the solar radiation intensity and the heat absorption parameters of the collector surface, evaluates the heat transfer distribution characteristics, establishes the thermal distribution field according to the absorption and conduction characteristics, and generates the numerical distribution of the thermal continuous field; The thermal balance optimization module analyzes the thermal gradient and variance based on the numerical distribution of the thermal continuous field, calls the heat absorption coating coverage parameters and the fluid pipeline performance parameters, adjusts the coverage density and pipeline layout, optimizes the heat distribution balance, and generates the thermal distribution optimization adjustment parameter value; The fluid heat transfer design module optimizes and adjusts parameter values ​​based on the thermal distribution, evaluates the flow rate and heat transfer performance of the thermal oil, calculates the relationship between pipeline distribution and flow rate, optimizes the fluid ratio and path length, reconfigures the heat transfer path, and generates optimized parameter values ​​for the fluid heat transfer network; The dynamic layout adjustment module calculates the relationship between the dynamic radiation angle and the absorption efficiency per unit area based on the optimized parameter value of the fluid heat transfer network, analyzes the matching between the absorption efficiency and the radiation angle, adjusts the angle and the layout parameters of the heat collection unit, and generates the dynamic layout parameter value of the heat collection unit; The environmental factor coupling module evaluates the influence of wind speed and ambient temperature on thermal distribution based on the dynamic layout parameter value of the solar collector unit, analyzes the relationship between heat fluctuation and external boundary conditions, adjusts the radiation angle and output parameters, and generates environmental factor coupling optimization parameter values.

2. The intelligent solar heating temperature management and regulation system according to claim 1 is characterized in that: The numerical distribution of the thermal continuous field includes energy absorption rate distribution, energy conduction rate distribution, and heat transfer characteristic distribution. The thermal distribution optimization adjustment parameter values ​​are specifically heat absorption coating coverage density parameters, fluid pipeline layout parameters, and thermal gradient balance parameters. The fluid heat transfer network optimization parameter values ​​include heat transfer oil flow rate parameters, pipeline distribution optimization parameters, fluid ratio optimization parameters, and heat transfer path configuration parameters. The dynamic layout parameter values ​​of the thermal collection unit specifically refer to dynamic radiation angle parameters, unit area absorption efficiency parameters, and thermal collection unit layout parameters. The environmental factor coupling optimization parameter values ​​include radiation angle adjustment parameters, output parameter optimization values, and thermal fluctuation boundary condition parameters.

3. The intelligent solar heating temperature management and regulation system according to claim 2 is characterized in that: The steps for obtaining the numerical distribution of the thermal continuous field are specifically as follows: Based on the collection results of solar radiation intensity parameters and collector surface heat absorption parameters, the time series values ​​and spatial distribution characteristics of solar radiation intensity are extracted to generate a solar radiation distribution matrix. The time series values ​​and spatial distribution characteristics of heat absorption parameters are extracted to generate a heat absorption distribution matrix. Through matrix fusion operations, solar radiation and heat absorption distribution matrices are generated. Using the solar radiation and heat absorption distribution matrix, combined with the regional differences in energy absorption rate and conduction rate, the regional distribution value of the energy absorption rate is calculated, the regional distribution value of the energy conduction rate is calculated, and the regional heat transfer rate is calculated by comparing the local heat transfer efficiency differences to generate the regional heat transfer rate result; Through the solar radiation and heat absorption distribution matrix and the regional heat transfer rate results, the heat transfer rate of the target space point is iteratively optimized using the formula: Calculate the numerical characteristics of the heat distribution field and generate the numerical distribution of the thermal continuous field; Among them, T d Represents the distribution value of the thermal continuous field, S i Represents the spatial distribution parameter of solar radiation intensity, H i represents the heat absorption parameter, E i Represents the energy transfer rate parameter, R i Represents the regional heat transfer rate parameter, i is the spatial point index, and n is the total number of spatial points.

4. The intelligent solar heating temperature management and regulation system according to claim 3 is characterized in that: The steps for obtaining the thermal distribution optimization adjustment parameter value are specifically as follows: Extracting calculation data of thermal gradient and variance from the numerical distribution of the thermal continuous field, differentiating the temperature change rate of multiple spatial points in the direction when calculating the thermal gradient, and performing normalization operation on the square sum of deviations between the regional thermal distribution value and the mean when calculating the variance, to generate initial thermal distribution characteristic data; According to the coverage parameters of the heat-absorbing coating and the performance parameters of the fluid pipeline, the relationship between the density change of the heat-absorbing coating and the heat absorption efficiency is calculated using the coverage parameters. The influence of the pipeline layout on the heat flow balance is analyzed based on the pipeline performance parameters, and a preliminary pipeline layout and coverage density plan is generated; By using the initial thermal distribution characteristic data and the preliminary pipeline layout and coverage density plan, the heat distribution balance is optimized for the target spatial point, using the formula: Calculate the optimized parameter value as the thermal distribution optimization adjustment parameter value; Among them, P opt Represents the optimized thermal distribution parameter value, G i represents the thermal gradient, V i represents the variance, C d represents the coverage density, P d Represents the pipeline layout parameters, A d represents the area parameter, β is the weight adjustment coefficient, and n is the number of spatial points.

5. The intelligent solar heating temperature management and regulation system according to claim 4 is characterized in that: The steps for obtaining the optimized parameter values ​​of the fluid heat transfer network are specifically as follows: Extracting the relationship between flow rate and heat exchange performance from the thermal distribution optimization adjustment parameter value, calculating the change value of the flow rate of the heat transfer oil in the differentiated pipeline area, analyzing the local difference of the flow rate distribution based on the linear change trend of the heat exchange efficiency with the flow rate, and generating preliminary flow rate and heat exchange performance data; According to the relationship between pipeline distribution and flow velocity, the flow velocity is proportionally adjusted in combination with preliminary data, the flow velocity distribution is optimized and the path length is adjusted, the adaptation value of the fluid ratio is calculated according to the path optimization result, and the fluid ratio adjustment parameter and path length configuration data are generated; The fluid heat transfer path is optimized by combining the preliminary flow rate and heat transfer performance data with the fluid ratio adjustment parameters and path length configuration data and the fluid parameters, using the formula: Calculate the optimized value of the fluid heat transfer path and generate the optimized parameter value of the fluid heat transfer network; Among them, F opt represents the optimized fluid heat transfer network parameter value, V i represents the flow rate, Q i represents the heat exchange performance, γ is the fluid ratio adjustment coefficient, L i represents the path length, δ is the pipeline path adjustment coefficient, i is the spatial point index, and n is the number of calculation points.

6. The intelligent solar heating temperature management and regulation system according to claim 5 is characterized in that: The specific steps for obtaining the dynamic layout parameter value of the heat collection unit are: Extracting the correlation data between the dynamic radiation angle and the absorption efficiency per unit area from the optimization parameter values ​​of the fluid heat transfer network, calculating the rate of change of the radiation angle at the differentiated position, combining the spatial distribution characteristics of the absorption efficiency per unit area, analyzing the absorption characteristic fluctuation values ​​of the differentiated spatial points, and generating the radiation angle and absorption efficiency relationship data; Based on the radiation angle and absorption efficiency relationship data, by calculating the proportional relationship between the radiation angle and the absorption efficiency deviation, the heat collecting units with large absorption efficiency deviation are screened, and the radiation angle parameters are adjusted point by point according to the screening results, and the matching values ​​of multiple spatial points are recalibrated to generate radiation angle and layout adjustment data; Through the radiation angle and layout adjustment data, combined with the characteristic parameters of the heat collection unit, the optimization ratio of dynamic absorption efficiency and radiation angle matching is analyzed, using the formula: Calculate the dynamic layout optimization adjustment value of the heat collecting unit and generate the dynamic layout parameter value of the heat collecting unit; Among them, D adj Represents the dynamic layout optimization adjustment value, A i Represents the absorption efficiency per unit area, R i Represents the matching value between radiation angle and absorption efficiency, E i represents the radiation angle adjustment, μ is the dynamic absorption adjustment coefficient, L i represents the square root of the sum of the squares of the center point coordinate values ​​of the collector unit, η is the layout matching correction coefficient, i is the spatial point index, and n is the number of calculation points.

7. The intelligent solar heating temperature management and regulation system according to claim 6 is characterized in that: The steps for obtaining the environmental factor coupling optimization parameter value are specifically as follows: Based on the dynamic layout parameter values ​​of the heat collecting units, environmental data including wind speed and ambient temperature are collected, local effects of wind speed and temperature on thermal distribution are statistically analyzed, dynamic response values ​​of wind speed changes on thermal distribution and correction values ​​of temperature changes on absorption efficiency are calculated, and preliminary analysis results of environmental impacts are generated; Using the preliminary analysis results of environmental impact, the correlation between environmental parameter fluctuations and boundary conditions is analyzed for environmental parameters and heat distribution change values ​​of multiple collector units, the radiation angle is adjusted to reduce the heat distribution deviation, and the output parameters are updated based on the adjusted thermal field to generate radiation angle and boundary condition adjustment data; Integrate the radiation angle and boundary condition adjustment data, calculate the synergistic effect of radiation angle adjustment and environmental parameters, and optimize the dynamic coupling parameters in combination with the combined fluctuation of wind speed and temperature, using the formula: Calculate the environmental factor coupling optimization adjustment value, and establish the environmental factor coupling optimization parameter value after adjustment; Among them, E adj Represents the environmental factor coupling optimization adjustment value, V i Represents the wind speed value of the i-th collector unit, U i represents the ambient temperature value of the i-th collector unit, P i represents the ith radiation angle adjustment value, ζ is the radiation angle reference value, and X i Represents the horizontal coordinate value of the i-th collector unit, Y i Represents the absorption efficiency value of the i-th collector unit, ω is the environmental correction coefficient, i is the spatial point index, and n is the total number of calculation points.

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