Temperature regulation and control method and system based on heat storage and release characteristics of radiant cooling room
By constructing a radiant cooling room model and establishing parameter mapping relationships, the control strategy of the radiant cooling system was optimized, solving the problem that the cold storage and release behavior of the building envelope was difficult to accurately reflect, and achieving stable indoor temperature and energy-saving operation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-02-25
- Publication Date
- 2026-04-10
AI Technical Summary
Existing radiant cooling systems cannot accurately reflect the cold storage and release behavior of the building envelope, resulting in large indoor temperature fluctuations and increased energy consumption, making it difficult to achieve precise control.
By acquiring the thermal performance parameters of the building envelope, a radiant cooling room model is constructed, multiple operating conditions are simulated, and the mapping relationship between the cold storage capacity, cold release capacity, and average supply and return water temperature and the system operating parameters is established. The control strategy is then optimized to meet the constraints.
It achieves precise control over the heat storage and release characteristics of the building envelope, reduces indoor temperature fluctuations, reduces energy consumption, and improves system operating efficiency and energy-saving effect.
Smart Images
Figure CN121828824A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The application belongs to the field of building indoor thermal environment control, and particularly relates to a temperature regulation method and system based on heat storage and release characteristics of a radiant cooling room. BACKGROUND
[0002] With the continuous improvement of building energy-saving standards, the radiant cooling system is increasingly widely used in various buildings such as office buildings, commercial complexes and residential buildings due to its significant advantages of energy saving, high efficiency, silent operation and high indoor thermal comfort. The core operating principle of the system is to lay a cold water pipeline in the ceiling, floor or wall of the building, so that the surface of the pipeline forms a cold radiation surface. The cold radiation surface exchanges heat with indoor air and the surrounding structure through radiation and convection, thereby reducing the indoor temperature and meeting the demand of the building indoor thermal environment.
[0003] During the operation of the radiant cooling system, in addition to the preset cold radiation surface, the walls, floors, furniture and other non-cold surfaces in the room will participate in the entire heat exchange process. Such non-cold surfaces have significant thermal inertia and will continuously absorb cold and complete the cold storage process during the system operation stage, and will gradually release the stored cold after the system is shut down. The cold storage and release behavior directly affects the stability of the indoor operating temperature and plays an important role in the actual cooling load demand of the radiant cooling system.
[0004] The current temperature regulation technology for the radiant cooling system still has obvious deficiencies, especially in the utilization and control of the heat storage and release characteristics of the surrounding structure. The research focus of the existing regulation method is mostly on the optimization of the heat exchange process of the cold radiation surface, and the thermal response law of the non-cold surface such as the surrounding structure in the whole cycle of the system operation is insufficiently concerned, and there is a lack of accurate characterization means for the cold storage and release behavior. In actual regulation, empirical formulas or linear simplified models are often used to estimate the heat storage and release characteristics of the surrounding structure, which is difficult to accurately reflect the dynamic cold storage and release law of the surrounding structure under complex scenarios such as continuous indoor heat source and system variable operating conditions, resulting in large prediction deviation of the indoor thermal environment and system cooling load.
[0005] The operating parameters of the radiant cooling system in the prior art are mostly determined based on engineering experience, and cannot be finely regulated based on the heat storage and release characteristics of the surrounding structure. This may cause large fluctuations in indoor temperature, affect thermal comfort, increase energy consumption of the system and reduce operating efficiency. At the same time, the prior art fails to effectively establish an accurate correlation between the heat storage and release amount of the surrounding structure, the average supply and return water temperature and the system operating parameters, making it difficult to develop a scientific regulation strategy in combination with system operating constraints and unable to fully utilize the optimization effect of the heat storage and release characteristics of the surrounding structure on system operation. SUMMARY
[0006] The technical problem to be solved by the present application is to overcome the low regulation efficiency of the existing radiation cooling system, thereby providing a temperature regulation method and system based on the heat storage and release characteristics of a radiation cooling room.
[0007] A temperature regulation method based on the heat storage and release characteristics of a radiation cooling room, comprising the following steps: Obtain the thermal performance parameters of the envelope structure, and construct a radiation cooling room model; Based on the radiation cooling room model, simulate multiple sets of radiation cooling system operating conditions, and establish an indoor thermal environment and system operating parameter dataset; Based on the indoor thermal environment and system operating parameter dataset, establish a mapping relationship between the cold storage capacity, cold release capacity, and average supply and return water temperature of the radiation cooling room envelope structure and the radiation cooling system operating parameters; Determine the constraints during the operation of the radiation cooling system; Set the indoor target operating temperature, and based on the mapping relationship between the cold storage capacity, cold release capacity, and average supply and return water temperature of the radiation cooling room envelope structure and the radiation cooling system operating parameters and the constraints, optimize the system radiation cooling system regulation strategy.
[0008] Further, the indoor thermal environment and system operating parameter dataset includes the envelope heat absorption coefficient, envelope area, radiation heat transfer coefficient, envelope surface area ratio, indoor heat source power, indoor heat source operation time, average operating temperature, average supply and return water temperature, radiation cooling system operation time, water flow, envelope cold storage capacity, and cold release capacity. The radiation cooling system operating parameters include radiation cooling system operation time, indoor heat source operation time, system water flow, average operating temperature, average supply and return water temperature, envelope heat absorption coefficient, envelope area, radiation heat transfer coefficient, envelope surface area ratio, and indoor heat source power.
[0009] Further, establishing a mapping relationship between the cold storage capacity, cold release capacity, and average supply and return water temperature of the radiation cooling room envelope structure and the radiation cooling system operating parameters comprises the following steps: Take the cold storage capacity, cold release capacity, and average supply and return water temperature as dependent variables, and take the radiation cooling system operating parameters as independent variables, construct a multiple linear regression model, and perform regression fitting on the multiple linear regression model to form the mapping relationship.
[0010] Further, in the establishment of the mapping relationship between the cold storage capacity, cold release capacity, and average supply and return water temperature of the radiation cooling room envelope structure and the radiation cooling system operating parameters: The mapping relationship between the heat storage capacity of the radiation cooling room envelope and the operation parameters of the radiation cooling system is: the heat storage capacity is mapped with the heat absorption coefficient of the envelope, the envelope area, the average operating temperature of the heat source equipment in the envelope during operation, the operation time of the radiation cooling system, the specific heat capacity of water, the water flow of the radiation cooling system, the average supply and return water temperature of the radiation cooling system, and the radiation heat exchange coefficient between the surface of the radiation cooling system and the envelope. The mapping relationship between the heat storage capacity of the radiation cooling room envelope and the operation parameters of the radiation cooling system is: the heat storage capacity is mapped with the heat absorption coefficient of the envelope, the envelope area, the average operating temperature of the heat source equipment in the envelope during operation, the operation time of the radiation cooling system, the specific heat capacity of water, the water flow of the radiation cooling system, the average supply and return water temperature of the radiation cooling system, and the radiation heat exchange coefficient between the surface of the radiation cooling system and the envelope. The mapping relationship between the heat storage capacity of the radiation cooling room envelope and the operation parameters of the radiation cooling system is: the heat storage capacity is mapped with the heat absorption coefficient of the envelope, the envelope area, the average operating temperature of the heat source equipment in the envelope during operation, the operation time of the radiation cooling system, the specific heat capacity of water, the water flow of the radiation cooling system, the average supply and return water temperature of the radiation cooling system, and the radiation heat exchange coefficient between the surface of the radiation cooling system and the envelope.
[0011] Further, the constraint condition during the operation of the radiation cooling system is determined, which is that the heat storage capacity of the envelope is greater than the heat release capacity, and the supply and return water temperature is greater than the air dew point temperature in the envelope.
[0012] Further, the optimization system radiation cooling system control strategy includes the following steps: Selecting optimization variables from the working parameters in the radiation cooling system; Defining the value range and step length of each optimization variable to form a variable value set; based on the variable value set, constructing variable combinations to form a global search space; For each variable combination in the global search space, based on the mapping relationship between the heat storage capacity, the heat release capacity and the average supply and return water temperature of the radiation cooling room envelope and the operation parameters of the radiation cooling system, the heat storage capacity, the heat release capacity and the average supply and return water temperature of the radiation cooling room envelope are calculated; Based on the heat storage capacity, the heat release capacity and the average supply and return water temperature, filtering the variable combinations in the global search space through the constraint condition and the preset indoor target operating temperature; Based on the variable combinations in the filtered global search space, calculating the operation cost of the radiation cooling system of each variable combination, and taking the variable combination with the lowest operation cost as the system radiation cooling system control strategy.
[0013] Further, the operation cost of the radiant cooling system includes an electricity cost, which is calculated based on the operation time length of the radiant cooling system and peak-valley electricity price information.
[0014] Further, based on the indoor thermal environment and system operation parameter dataset, a mapping relationship between the cold storage amount, cold release amount and average supply and return water temperature of the radiant cooling room envelope and the operation parameters of the radiant cooling system is established, including the following steps: For the indoor thermal environment and system operation parameter dataset, standardization processing based on the mean and standard deviation is adopted for each variable; For the standardized indoor thermal environment and system operation parameter dataset, a multiple linear regression model is established and regression fitted; For the regression fitted multiple linear regression model, reverse standardization processing is performed to obtain the mapping relationship.
[0015] A temperature regulation system based on the heat storage and release characteristics of a radiant cooling room, comprising: A radiant cooling room, comprising a radiant cooling device and an envelope; the radiant cooling device is arranged inside the envelope and is used for realizing radiant heat exchange; A control module for adjusting the working parameters of the radiant cooling device according to the temperature regulation method based on the heat storage and release characteristics of the radiant cooling room.
[0016] Further, the envelope of the radiant cooling room comprises a cold storage wall, and the heat capacity characteristics of the cold storage cavity are stronger than those of other parts of the envelope.
[0017] Beneficial effects: the present application provides a temperature regulation method based on the heat storage and release characteristics of a radiant cooling room, a room model is constructed by obtaining envelope thermal performance parameters, a dataset is established by combining multiple working condition simulations, and then a precise mapping relationship between the cold storage amount, cold release amount and average supply and return water temperature and system operation parameters is formed, which can accurately reflect the dynamic heat storage and release law of the envelope in complex scenarios, effectively reduce the prediction deviation of indoor thermal environment and cooling load, and provide data and model support for fine regulation and control.
[0018] The present application is oriented to the indoor target operating temperature, optimizes the regulation and control strategy in combination with the established mapping relationship and system operation constraint conditions, can be targeted to match the heat storage and release characteristics of the envelope and the system operation state, avoids indoor temperature fluctuations caused by regulation and control lag and unreasonable parameters, accurately maintains the stability of the indoor thermal environment; at the same time, reduces invalid energy consumption through scientific regulation and control, solves the problems of low system operation efficiency and energy waste in the prior art, and realizes the energy saving operation goal. BRIEF DESCRIPTION OF DRAWINGS
[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the accompanying drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.
[0020] Figure 1 The main method steps of the present application are shown in the schematic block diagram. DETAILED DESCRIPTION
[0021] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings. In the following description, a lot of specific details are set forth in order to fully understand the present application. However, the present application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without departing from the spirit of the present application, so the present application is not limited to the specific embodiments disclosed below.
[0022] In the description of the present application, it should be understood that in the description of the present application, the meaning of "a plurality of" is at least two, such as two, three, etc., unless otherwise explicitly specified. In the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connection", "connection", "fixing" and other terms should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the internal communication of two elements or the interaction relationship between two elements, unless otherwise explicitly limited. For those skilled in the art, the specific meaning of the above-mentioned terms in the present application can be understood according to the specific circumstances.
[0023] Embodiment one: Referring to Figure 1 The present embodiment provides a temperature regulation method based on the heat storage and release characteristics of a radiant cooling room, comprising the following steps: Step S1: Obtain the thermal performance parameters of the envelope structure, and construct a radiant cooling room model; In the present embodiment, according to the meteorological parameters and the thermal performance parameters of the envelope structure of the target building in the region, a radiant cooling room model is constructed in the EnergyPlus software, and is verified by the measured room data.
[0024] Step S2: Given the indoor heat source condition, based on the radiant cooling room model, simulate a plurality of groups of radiant cooling system operating conditions, and establish an indoor thermal environment and system operating parameter data set; Step S3: Based on the indoor thermal environment and system operation parameter dataset, establish a mapping relationship between the cold storage capacity, cold release capacity, and average supply and return water temperature of the radiant cooling room envelope and the radiant cooling system operation parameters; In this embodiment, the cold storage capacity Q X It is a characterization of the cooling capacity of the building envelope during the operation of a radiant cooling system, which is formed by radiative heat exchange with the radiant cooling surface and convective heat exchange with the indoor air. It reflects the cooling capacity of the building envelope during the nighttime operation phase and is used to determine the operating time and intensity of the radiant cooling system.
[0025] Cooling capacity Q F During working hours, without the participation of active cooling equipment, the building envelope releases stored cold energy into the room through passive heat exchange under the influence of indoor heat sources and environmental conditions. The magnitude of this release directly affects the indoor operating temperature level.
[0026] Average supply and return water temperature T w,avg It is used to comprehensively reflect the operating intensity, heat exchange capacity and energy consumption level of the radiant cooling system, and is a key decision variable in the process of system optimization and control.
[0027] Step S4: Determine the constraints during the operation of the radiant cooling system; In this embodiment, the constraint is that the cold storage capacity of the building envelope is greater than the cold release capacity. Furthermore, the supply and return water temperatures are greater than the air dew point temperature (T) within the building envelope. s >T dp ).
[0028] Specifically, by calculating the nighttime operating conditions of the radiant cooling system through mapping relationships, it is found that the cold storage capacity of the building envelope is greater than the cold release capacity. This allows for further calculation of the average supply and return water temperatures of the radiant cooling system during the operating period, and further determination of the minimum temperature limit for the supply water.
[0029] Step S5: Set the target operating temperature indoors, and optimize the system's radiant cooling system control strategy based on the mapping relationship and constraints between the cold storage capacity, cold release capacity, and average supply and return water temperatures of the radiant cooling room envelope and the operating parameters of the radiant cooling system.
[0030] In this embodiment, the adjustable operating parameters of the radiant cooling system include the water supply temperature T. s Runtime t, system traffic m.
[0031] Specifically, in step S2, the indoor thermal environment and system operating parameter dataset includes the heat absorption coefficient of the building envelope, the area of the building envelope, the radiative heat transfer coefficient, the surface area ratio of the building envelope, the indoor heat source power, the indoor heat source operating time, the average operating temperature, the average temperature of the supply and return water, the operating time of the radiant cooling system, the water flow rate, and the cold storage capacity and cold release capacity of the building envelope.
[0032] In step S3, the operating parameters of the radiant cooling system include the operating time of the radiant cooling system, the operating time of the indoor heat source, the system water flow rate, the average operating temperature, the average temperature of the supply and return water, the heat absorption coefficient of the building envelope, the area of the building envelope, the radiant heat transfer coefficient, the surface area ratio of the building envelope, and the power of the indoor heat source.
[0033] In this embodiment, in step S3, the cold storage capacity, cold release capacity, and average supply and return water temperature are used as dependent variables, and the variables of the radiant cooling system operating parameters are used as dependent variables to construct a multiple linear regression model. The multiple linear regression model is then fitted to form a mapping relationship.
[0034] Specifically, step S3 involves modeling using standardized multiple linear regression, which includes the following steps: Step S3.1: For the indoor thermal environment and system operating parameter dataset, standardize the independent variables based on the mean and standard deviation; Specifically, the collected data was preprocessed, retaining only numerical variables. The cold storage capacity, cold release capacity, or average supply and return water temperature were used as dependent variables, while system runtime, indoor heat source power, water flow rate, average operating temperature, and thermal parameters of the building envelope were used as independent variables to construct a regression matrix. The StandardScaler method was used to standardize each input variable, converting the feature variables into a form with zero mean and unit standard deviation, thus avoiding the influence of differences in the magnitude of different physical quantities on the regression results.
[0035] The independent variables are standardized based on the mean and standard deviation to eliminate the influence of differences in the dimensions and numerical scales of different physical quantities on the regression results, as shown below: ; Among them, X i Represents the original independent variable. and These represent the mean and standard deviation of the variable, respectively. This represents the standardized variable.
[0036] Step S3.2: For the standardized dataset of indoor thermal environment and system operating parameters, establish a multiple linear regression model and perform regression fitting, expressed as: ; Where Y represents the cold storage capacity, cold release capacity, or average supply and return water temperature. 0 represents the regression intercept. This represents the regression coefficient corresponding to the independent variable.
[0037] Step S3.3: For the regression-fitted multiple linear regression model, perform inverse scaling transformation, i.e., destandardization, to obtain the mapping relationship, thereby giving the mapping relationship an unstandardized regression formula with clear physical meaning and engineering units, which can be directly used for engineering calculations and system operation control.
[0038] In the mapping relationship of step S3: The mapping relationship between the cold storage capacity of the radiant cooling room envelope and the operating parameters of the radiant cooling system is established as follows: the mapping relationship between the cold storage capacity and the heat absorption coefficient of the envelope, the area of the envelope, the average operating temperature of the heat source equipment within the envelope during operating time, the operating time of the radiant cooling system, the specific heat capacity of water, the water flow rate of the radiant cooling system, the average supply and return water temperature of the radiant cooling system, and the radiant heat exchange coefficient between the surface of the radiant cooling system and the envelope is expressed as: ; The mapping relationship between the cooling capacity of the radiant cooling room envelope and the operating parameters of the radiant cooling system is established as follows: the mapping relationship between the cooling capacity and the heat absorption coefficient of the envelope, the area of the envelope, the average operating temperature of the heat source equipment within the envelope during operating time, the operating time of the indoor heat source equipment, the time during which the radiant cooling system and indoor heat sources have not been turned on within 24 hours, the specific heat capacity of water, the water flow rate of the radiant cooling system, the average supply and return water temperature of the radiant cooling system, the surface area ratio of the envelope, and the power of the indoor heat sources is expressed as follows: ; The mapping relationship between the average supply and return water temperatures and the operating parameters of the radiant cooling system is established as follows: the mapping relationship between the cold storage capacity and the heat absorption coefficient of the building envelope, the area of the building envelope, the average operating temperature of the heat source equipment within the building envelope, the operating time of the radiant cooling system, the operating time of the indoor heat source equipment, the specific heat capacity of water, the water flow rate of the radiant cooling system, the radiant heat exchange coefficient between the radiant cooling surface and the building envelope, the surface area ratio of the building envelope, and the power of the indoor heat source is expressed as follows: ; in, This indicates the cold storage capacity of the building envelope (kJ). B represents the cooling capacity of the building envelope (kJ); B represents the heat absorption coefficient of the building envelope (W / (m²)). 2 ·℃); A represents the area of the building envelope (m²) 2 ); T op t represents the average operating temperature (°C) during the operation of the indoor heat source equipment. C Indicates the operating time (h) of the radiant cooling system; C p The unit of temperature (T) represents the specific heat capacity of water (J / (kg·℃)); m represents the water flow rate of the radiant cooling system (kg / s); T represents the total flow rate of the radiant cooling system. avg This indicates the average supply and return water temperatures (°C) of the radiant cooling system. This represents the radiative heat exchange coefficient between the radiative cooling surface and the building envelope; Indicates the operating time (h) of indoor heating equipment; This indicates the time (h) during which no radiant cooling system or indoor heat source was turned on within 24 hours; i represents the surface area ratio of the building envelope; P represents the power of the indoor heat source (W); and k represents the number of different building envelopes.
[0039] Specifically, the average operating temperature T during the operation of indoor heat source equipment op The average operating temperature during the working period is obtained by accumulating the hourly operating temperatures from the beginning to the end of the working period and taking the average value. It is expressed as: T op =(T a +MRT) / 2; Among them, T a Indicates indoor air temperature; MRT represents mean radiant temperature.
[0040] In some implementations of this embodiment, the obtained mapping relationship is represented as follows: ; .
[0041] ; .
[0042] ; .
[0043] In this embodiment, the indoor heat source power is set to 100W, the working time is 8 hours, the indoor target operating temperature during the working time is set to 26°C, the air dew point temperature is set to 17°C, and the water flow rate of the radiant cooling system is set to 0.1kg / s.
[0044] Step S4 also includes calculating the nighttime radiant cooling system operating parameters, including average supply and return water temperatures and operating time, based on the mapping relationship.
[0045] Specifically, step S4, under the premise of meeting the average operating temperature requirement during indoor working hours, reversely determines the reasonable operating parameters of the nighttime radiant cooling system. Based on the established radiant cooling room model and its mapping relationship with the system's average supply and return water temperatures, using the average operating temperature during daytime working hours as input, the required cooling capacity Q of the building envelope to meet this requirement is calculated. F Further determine the required cooling capacity Q of the building envelope at night. X The average supply and return water temperatures and operating time of the nighttime radiant cooling system were calculated using a multiple linear regression model.
[0046] In step S5, based on the established prediction model of the mapping relationship between cold storage capacity, cold release capacity, and average supply and return water temperatures, and in conjunction with indoor environmental requirements and electricity price constraints, multiple sets of operating parameters are jointly optimized. The optimization strategy for the radiant cooling system control includes the following steps: Step S5.1: Select optimization variables from the operating parameters of the radiant cooling system; Specifically, the system runtime t at night c and average supply and return water temperature T avg By using water flow rate as an optimization variable and setting it to a fixed value, the model dimensionality is reduced and the solution stability is improved.
[0047] In this embodiment, the system runs for t during the night. c The operating hours are during non-working periods, such as 8:00 PM to 8:00 AM the next day. Average supply and return water temperature T avg The average supply and return water temperatures of the radiant cooling system represent the overall cooling level during operation. This is achieved by establishing a system operation dataset and its mapping relationship with the heat storage and release of the building envelope. The average supply and return water temperatures T0 represent the average supply and return water temperatures during operation. avg This can characterize the average cooling capacity required by a nighttime radiant cooling system during operation. Under the condition of meeting a given operating time, the required T is determined... avg To achieve the accumulation of the required cooling capacity of the building envelope at night and ensure that it has sufficient cooling capacity during working hours.
[0048] Step S5.2: Define the value range and step size for each of the optimization variables to form a variable value set; based on the variable value set, construct variable combinations to form a global search space; Specifically, a reasonable range and step size are defined for each optimization variable. In this embodiment, the nighttime operating time varies within the range of 2–12 hours, and the average supply and return water temperatures are discretely selected within the allowable range. A global search space is generated by combining variables, enabling the algorithm to cover all possible operating states of the system.
[0049] Step S5.3: For each combination of variables in the global search space, calculate the cold storage capacity, cold release capacity, and average supply and return water temperature of the radiant cooling room envelope based on the mapping relationship between the cold storage capacity, cold release capacity, and average supply and return water temperature of the radiant cooling room envelope and the operating parameters of the radiant cooling system. For each combination in the global search space, the three mapping relationship prediction models established in this invention are invoked to calculate the wall's cold storage capacity Q. X Cooling capacity Q F and average supply and return water temperature T avg This enables the prediction of everything from operating parameters to room thermal behavior.
[0050] Step S5.4: Based on the cold storage capacity, the cold release capacity, and the average supply and return water temperature, filter the combination of variables in the global search space through constraints and a preset indoor target operating temperature; The operating constraints are checked, and each set of operating parameters is screened based on the indoor operating temperature requirements and anti-condensation needs. Variable combinations that do not meet the constraints established in step S4 are filtered out; and variable combinations that do not meet the indoor target operating temperature are also filtered out.
[0051] In this embodiment, the average operating temperature of the room during the working period is determined by mapping the cold storage capacity and cold release capacity of the building envelope and the average supply and return water temperature of the radiant cooling system with the system operating parameters. The average operating temperature is used as an input item. As a preferred embodiment, the average operating temperature during the working period is determined to be 26°C.
[0052] Step S5.5: Based on the variable combinations in the filtered global search space, calculate the operating cost of the radiant cooling system for each variable combination, and take the variable combination with the lowest operating cost as the system's radiant cooling system control strategy.
[0053] In some implementations of this embodiment, an hourly electricity pricing method is adopted, setting three time periods: peak, flat, and valley. The electricity price is highest during the peak period, lowest during the valley period, and between the two during the normal period.
[0054] The calculation of energy consumption and economic indicators is used to find feasible solutions that satisfy all safety constraints. The system power consumption is calculated by combining hourly electricity prices, and the cooling COP is estimated based on the input water temperature, heat source intensity, and temperature parameters obtained from the regression model, thereby obtaining the corresponding operating energy consumption and operating cost.
[0055] As one method of calculating operating costs in this embodiment, operating cost = total power consumption * unit electricity price.
[0056] Specifically, in this embodiment, the water supply temperature T is set. in =T avg -1℃, return water temperature is T out =2*T avg -T in Q cooling = Cp*m*(T out -T in )*3.6*t c COP = 0.0843 * T in +1.8771, Total power consumption E cooling =Q cooling / COP / 3600.
[0057] The solution with the lowest energy consumption or operating cost is selected from all feasible solutions as the optimal operating strategy, thus obtaining the optimal combination of nighttime operating time and average supply and return water temperature parameters. As one implementation method in this embodiment, the solution with the lowest operating cost is directly selected as the optimal operating strategy.
[0058] In this embodiment, the operating cost of the radiant cooling system includes electricity costs, which are calculated based on the operating time of the radiant cooling system and peak and off-peak electricity prices.
[0059] This embodiment uses traversal search as the core optimization method. It does not rely on an initial point and avoids getting trapped in local minima, making it more suitable for handling coupled models including multiple nonlinear relationships. It can simultaneously satisfy multiple conditions such as "cold storage capacity requirement," "anti-condensation requirement," and "operating temperature constraint." Furthermore, it can directly use the mapping relationship between cold storage capacity, cold release capacity, and average supply and return water temperatures to predict the model output, without needing to solve complex analytical gradients. Further, it is easy to extend to control factors such as electricity prices and weather. The traversal method can easily incorporate hourly electricity prices, future weather forecasts, and water flow restrictions, supporting subsequent expansion to multi-objective optimization. The optimization method proposed in this embodiment can automatically generate control strategies that balance energy efficiency and operational feasibility while ensuring indoor environmental requirements, thereby improving the intelligence level and operational efficiency of the radiant cooling system.
[0060] As an optimization strategy result of this embodiment, the optimal economic operating condition obtained in this embodiment is: the radiant cooling system operates continuously for 9 hours at night, from 23:00 to 08:00, with a system water flow rate of 0.1 kg / s, an average supply and return water temperature of 26.56℃, and a corresponding supply water temperature of 25.56℃. Under this operating condition, the coefficient of performance (COP) of the radiant cooling system is 4.06, the total power consumption of the system is 1.88 kWh, and the power consumption per unit area is 0.47 kWh / m². With a nighttime off-peak electricity price of 0.26 yuan / kWh, the cost corresponding to this operating strategy is 0.49 yuan, which can meet the thermal environment requirement of an average operating temperature of 26℃ during working hours.
[0061] Calculations were performed in comparison to the normal operating mode during regular working hours. In this mode, with the radiant cooling system set at a supply water temperature of 23℃ and running for 8 hours, the system COP was 3.84, the total power consumption was 1.75 kWh, and the power consumption per unit area was 0.44 kWh / m². Under the condition of a peak electricity price of 0.64 yuan / kWh, the operating cost was 1.12 yuan. Therefore, although the system's power consumption is slightly higher during nighttime operation than during regular working hours, due to the nighttime control strategy combined with the off-peak electricity price, the operating cost decreased from 1.12 yuan to 0.49 yuan, a reduction of 56.25%.
[0062] Therefore, the control method proposed in this invention, based on the cold storage and release characteristics of the building envelope and economic constraints, can effectively utilize the low nighttime temperature and low electricity price conditions, enabling the building envelope to store cold at night and release cold during working hours. This significantly reduces system operating costs while ensuring indoor thermal comfort requirements, demonstrating clear energy-saving and economic advantages.
[0063] Example 2: This embodiment provides a temperature control system based on the heat storage and release characteristics of a radiant cooling room, including: A radiant cooling room, comprising radiant cooling devices and an enclosure structure; the radiant cooling devices are disposed inside the enclosure structure for radiant heat exchange. The control module is used to adjust the operating parameters of the radiant cooling device according to the temperature control method based on the heat storage and release characteristics of the radiant cooling room described above.
[0064] In this embodiment, the enclosure structure of the radiant cooling room includes a cold storage wall, and the heat capacity of the cold storage cavity is stronger than that of other parts of the enclosure structure. The enclosure structure includes: walls, floors, roofs, or other enclosure structures that are not equipped with radiant cooling pipes or serve as radiant heat exchange terminals. These structures do not perform active cooling functions during system operation, but only achieve passive cold storage and release through radiant heat exchange with the radiant cooling surface and convective heat exchange with the indoor air.
[0065] Specifically, as a preferred embodiment, the radiant cooling room features a cold storage wall with significant heat capacity on its west side. The remaining enclosure structure, including the south, north, and east walls, as well as the roof and floor, is made of lightweight materials. This emphasizes the impact of the enclosure structure's cold storage and release processes on the system's energy consumption and control strategies. The cold storage wall is a 200mm thick solid concrete structure, whose thermal conductivity and specific heat capacity are significantly higher than other lightweight structures. The cold storage and release capacity of the enclosure structure are thus limited to the net heat transfer process relative to the west-facing cold storage wall.
[0066] The radiant cooling system is installed inside the room's ceiling in the form of a cold ceiling. Embedded cold water capillaries within the ceiling lower the temperature of the ceiling's inner surface, thus controlling radiant heat exchange. During system operation, the radiant cold ceiling provides cooling to the room and drives the cold storage walls to undergo cold storage and release processes at different times.
[0067] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0068] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.
Claims
1. A temperature control method based on the heat storage and release characteristics of a radiant cooling room, characterized in that, Includes the following steps: Obtain the thermal performance parameters of the building envelope and construct a radiant cooling room model; based on the radiant cooling room model, simulate the operating conditions of multiple radiant cooling systems and establish a dataset of indoor thermal environment and system operating parameters. Based on the indoor thermal environment and system operation parameter dataset, establish the mapping relationship between the cold storage capacity, cold release capacity, and average supply and return water temperature of the radiant cooling room envelope and the radiant cooling system operation parameters; determine the constraints during the operation of the radiant cooling system. Set the target operating temperature indoors, and optimize the system's radiant cooling system control strategy based on the mapping relationship and constraints between the cold storage capacity, cold release capacity, and average supply and return water temperatures of the radiant cooling room envelope and the operating parameters of the radiant cooling system.
2. The temperature control method based on the heat storage and release characteristics of a radiant cooling room according to claim 1, characterized in that, The indoor thermal environment and system operation parameter dataset includes the building envelope heat absorption coefficient, building envelope area, radiative heat transfer coefficient, building envelope surface area ratio, indoor heat source power, indoor heat source operating time, average operating temperature, average supply and return water temperature, radiative cooling system operating time, water flow rate, building envelope cold storage capacity, and cold release capacity; the radiative cooling system operation parameters include the radiative cooling system operating time, indoor heat source operating time, system water flow rate, average operating temperature, average supply and return water temperature, building envelope heat absorption coefficient, building envelope area, radiative heat transfer coefficient, building envelope surface area ratio, and indoor heat source power.
3. The temperature control method based on the heat storage and release characteristics of a radiant cooling room according to claim 1, characterized in that, Establishing a mapping relationship between the cold storage capacity, cold release capacity, and average supply and return water temperature of the radiant cooling room envelope and the operating parameters of the radiant cooling system includes the following steps: taking the cold storage capacity, cold release capacity, and average supply and return water temperature as dependent variables, taking the variables of the radiant cooling system operating parameters as dependent variables, constructing a multiple linear regression model, and performing regression fitting on the multiple linear regression model to form a mapping relationship.
4. A temperature control method based on the heat storage and release characteristics of a radiant cooling room according to claim 1, characterized in that, In establishing the mapping relationship between the cold storage capacity, cold release capacity, and average supply and return water temperatures of the radiant cooling room envelope and the operating parameters of the radiant cooling system, the mapping relationship between the cold storage capacity of the radiant cooling room envelope and the operating parameters of the radiant cooling system is as follows: The cold storage capacity is mapped to the heat absorption coefficient of the envelope, the area of the envelope, the average operating temperature of the heat source equipment within the envelope during operating time, the operating time of the radiant cooling system, the specific heat capacity of water, the water flow rate of the radiant cooling system, the average supply and return water temperatures of the radiant cooling system, and the radiant heat exchange coefficient between the surface of the radiant cooling system and the envelope. The mapping relationship between the cold release capacity of the radiant cooling room envelope and the operating parameters of the radiant cooling system is as follows: The cold storage capacity is mapped to the heat absorption coefficient of the envelope, the area of the envelope, the average operating temperature of the heat source equipment within the envelope, the operating time of the radiant cooling system, the specific heat capacity of water, the water flow rate of the radiant cooling system, the average supply and return water temperatures of the radiant cooling system, and the radiant heat exchange coefficient between the surface of the radiant cooling system and the envelope. The mapping relationship between the average operating temperature of the heat source equipment during operation time, the operating time of the indoor heat source equipment, the time during which no radiant cooling system or indoor heat source is turned on within 24 hours, the specific heat capacity of water, the water flow rate of the radiant cooling system, the average supply and return water temperature of the radiant cooling system, the surface area ratio of the building envelope, and the power of the indoor heat source is established. The mapping relationship between the average supply and return water temperature and the operating parameters of the radiant cooling system is established as follows: the mapping relationship between the cold storage capacity and the heat absorption coefficient of the building envelope, the area of the building envelope, the average operating temperature of the heat source equipment during operation time within the building envelope, the operating time of the radiant cooling system, the operating time of the indoor heat source equipment, the specific heat capacity of water, the water flow rate of the radiant cooling system, the radiant heat exchange coefficient between the radiant cooling surface and the building envelope, the surface area ratio of the building envelope, and the power of the indoor heat source is established.
5. A temperature control method based on the heat storage and release characteristics of a radiant cooling room according to claim 1, characterized in that, Determine the constraints for the operation of the radiant cooling system, wherein the cold storage capacity of the building envelope is greater than the cold release capacity, and the supply and return water temperatures are greater than the air dew point temperature inside the building envelope.
6. A temperature control method based on the heat storage and release characteristics of a radiant cooling room according to claim 1, characterized in that, Optimizing the control strategy of the radiant cooling system includes the following steps: selecting optimization variables from the operating parameters of the radiant cooling system; defining the value range and step size for each optimization variable to form a variable value set; constructing variable combinations based on the variable value set to form a global search space; calculating the cold storage capacity, cold release capacity, and average supply and return water temperature of the radiant cooling room envelope and the operating parameters of the radiant cooling system for each variable combination in the global search space; filtering the variable combinations in the global search space based on the cold storage capacity, cold release capacity, and average supply and return water temperature through constraints and a preset indoor target operating temperature; calculating the radiant cooling system operating cost for each variable combination based on the filtered variable combinations in the global search space, and selecting the variable combination with the lowest operating cost as the control strategy for the radiant cooling system.
7. A temperature control method based on the heat storage and release characteristics of a radiant cooling room according to claim 6, characterized in that, The operating cost of the radiant cooling system includes electricity costs, which are calculated based on the operating time of the radiant cooling system and peak and off-peak electricity prices.
8. A temperature control method based on the heat storage and release characteristics of a radiant cooling room according to claim 1, characterized in that, Based on the aforementioned indoor thermal environment and system operating parameter dataset, a mapping relationship is established between the cold storage capacity, cold release capacity, and average supply and return water temperatures of the radiant cooling room envelope and the operating parameters of the radiant cooling system. This includes the following steps: For the aforementioned indoor thermal environment and system operating parameter dataset, standardization is applied to each independent variable based on mean and standard deviation; for the standardized dataset, a multiple linear regression model is established and regression fitting is performed; for the fitted multiple linear regression model, inverse standardization is performed to obtain the mapping relationship.
9. A temperature control system based on the heat storage and release characteristics of a radiant cooling room, characterized in that, include: A radiant cooling room, comprising a radiant cooling device and an enclosure structure; the radiant cooling device is disposed inside the enclosure structure for radiant heat exchange; a control module is used to adjust the operating parameters of the radiant cooling device according to the temperature control method based on the heat storage and release characteristics of the radiant cooling room according to any one of claims 1-8.
10. A temperature control system based on the heat storage and release characteristics of a radiant cooling room according to claim 9, characterized in that, The enclosure structure of the radiant cooling room includes a cold storage wall, and the heat capacity characteristics of the cold storage cavity are stronger than those of other parts of the enclosure structure.