A photoelectric and photo-thermal synergistic direct-drive three-constant environment regulating method and device

Abstract

A kind of photoelectricity photothermal synergistic direct-drive three constant environment deployment method and device.In the method, photovoltaic power data and heat collection data are collected and processed to obtain electrical energy storage state parameters and thermal energy storage state parameters;Indoor environmental parameters are collected and compared with target three constant parameters to generate system load demand data;Based on electrical energy storage state parameters, thermal energy storage state parameters and system load demand data, energy deployment instructions are generated;According to the energy deployment instructions, corresponding adjustment is executed, and indoor three constant state monitoring parameters are collected;Determine the target work link, trigger the waste heat and cold recovery operation, and return the obtained waste heat and cold medium to the feedback heat exchanger;According to the state of waste heat and cold medium, combined with system load demand data, waste heat and cold medium is distributed to heating network and humidification network as needed to perform recycling operation.Implementation of the present solution improves the utilization rate of renewable energy and reduces the energy efficiency loss of three constant environment control.

Description

Technical Field

[0001] This application relates to the field of building environment control technology, specifically to a method and device for adjusting constant, constant, and photoelectric environments through direct drive. Background Technology

[0002] With the increasing demands for building energy conservation and indoor environmental quality, constant temperature, humidity, and oxygen levels have been widely adopted in high-quality buildings. In existing technologies, these systems typically utilize municipal power grids, with variable frequency heat pump units, steam generators, and total heat exchange ventilation units independently controlling temperature, humidity, and oxygen levels. On the energy supply side, while some systems incorporate photovoltaic (PV) panels or solar thermal collectors as auxiliary energy sources, the PV electricity and solar thermal heat are stored and used independently, lacking a unified scheduling mechanism between these two renewable energy sources. Furthermore, waste heat and cold generated during equipment operation are typically discharged directly outdoors without recycling or treatment.

[0003] However, the technical problem with the above solution is that the two renewable energy sources, photovoltaic power and solar thermal energy collection, lack coordinated scheduling. The system cannot generate unified energy allocation instructions for the three constant load requirements based on the surplus and shortage status of electric energy storage and thermal energy storage. As a result, waste heat and waste cooling resources cannot be centrally recovered and redistributed according to the overall load requirements of the system, resulting in low utilization rate of renewable energy and significant energy efficiency loss in the three constant environmental control. Summary of the Invention

[0004] To address the aforementioned technical problems, this application provides a method and apparatus for regulating a three-constant environment through direct drive of photoelectric and photothermal synergy.

[0005] The first aspect of this application provides a method for regulating a three-constant environment through direct drive of photoelectric and photothermal synergy, employing the following technical solution: The photovoltaic power data and solar thermal collection data at the current moment are collected synchronously by the pre-configured photovoltaic solar thermal panel. The photovoltaic power data is input into the preset battery module to perform fluctuation smoothing processing to obtain the electrical energy storage status parameters. The solar thermal collection data is input into the preset buffer water tank to perform buffer thermal storage processing to obtain the thermal energy storage status parameters. Real-time indoor environmental parameters are collected by temperature sensors, humidity sensors, and air quality sensors distributed in the target indoor area and at the return air vent. The indoor environmental parameters are then compared with preset target constant parameters to generate the current system load demand data. Based on the electrical energy storage status parameters, the thermal energy storage status parameters, and the system load demand data, an energy dispatch command is generated. According to the energy allocation instructions, constant temperature regulation, constant humidity regulation and constant oxygen regulation are executed respectively, and indoor constant three state monitoring parameters are collected in real time during the execution of constant temperature regulation, constant humidity regulation and constant oxygen regulation; Based on the indoor constant state monitoring parameters, the target working process currently in operation is determined, and the waste heat and cold recovery operation for the target working process is triggered, and the recovered waste heat and cold medium is returned to the preset feedback heat exchanger. Based on the state of the waste heat and cold medium in the feedback heat exchanger and combined with the system load demand data, the waste heat and cold medium is allocated to the preset heating network and preset humidification network as needed for reuse.

[0006] By adopting the above technical solution, photovoltaic thermal panels are used to collect data synchronously and drive the system in coordination. Based on the surplus and shortage of electrical and thermal energy storage and the demand for constant, non-constant, and high-temperature loads, unified dispatch instructions are generated. Waste heat and cold are centrally recovered and distributed to the heating and humidification networks for reuse as needed, thereby improving the utilization rate of renewable energy and reducing energy loss in the control of constant, non-constant, and high-temperature environments.

[0007] Optionally, generating energy dispatch instructions based on the electrical energy storage status parameters, the thermal energy storage status parameters, and the system load demand data includes: The energy storage state parameters are compared with a preset power safety judgment threshold, and the overflow power data exceeding the power safety judgment threshold is extracted. The thermal energy storage state parameters are compared with a preset thermal safety judgment threshold, and the overflow heat data exceeding the thermal safety judgment threshold is extracted. The system load demand data is decomposed into constant temperature load demand parameters, constant humidity load demand parameters, and constant oxygen load demand parameters. The overflow power data, the overflow heat data, the constant temperature load demand parameters, the constant humidity load demand parameters, and the constant oxygen load demand parameters are input into a preset energy allocation decision model, and the corresponding energy allocation weight coefficients are output through the energy allocation decision model. The energy allocation command is generated by performing instruction encoding operations based on the energy allocation weight coefficient.

[0008] By adopting the above technical solution, the overflow electricity and heat are extracted according to the energy storage surplus and shortage status, and input into the decision model along with the disassembled constant temperature, constant humidity, and constant oxygen load demand. The output allocation weight coefficient generates a unified energy dispatch command, realizing the coordinated dispatch of the two renewable energy sources. This enables the waste heat and waste cooling to be centrally recovered and redistributed according to the overall load demand, effectively improving the utilization rate of renewable energy and reducing system energy efficiency loss.

[0009] Optionally, the step of performing constant temperature regulation, constant humidity regulation, and constant oxygen regulation according to the energy allocation command includes: The energy allocation command is processed by signal decoding to extract the target values ​​for constant temperature control, constant humidity control, and constant oxygen control. The indoor environmental parameters are classified and analyzed to separate the real-time indoor temperature, real-time indoor humidity, and real-time indoor oxygen concentration. The difference between the constant temperature control target value and the real-time indoor temperature value is calculated to obtain the temperature deviation adjustment amount, and the pre-configured variable frequency heat pump host is controlled to perform the constant temperature adjustment according to the temperature deviation adjustment amount. The difference between the constant humidity control target value and the real-time indoor humidity value is calculated to obtain the humidity deviation adjustment amount, and the preset steam generator is triggered to perform the constant humidity adjustment according to the humidity deviation adjustment amount. The difference between the constant oxygen control target value and the real-time indoor oxygen concentration value is calculated to obtain the fresh air supply deviation, and the preset total heat exchange exhaust device is driven to perform the constant oxygen regulation according to the fresh air supply deviation.

[0010] By adopting the above technical solution, the uniformly generated energy allocation instructions are decoded, the constant control targets are extracted and the deviation is calculated with the real-time indoor parameters, and the variable frequency heat pump host, steam generator and total heat exchange exhaust device are driven to perform coordinated regulation. This achieves precise matching and closed-loop linkage control between renewable energy supply and the demand for the three constant loads, eliminates energy supply redundancy and improves the system regulation efficiency.

[0011] Optionally, the step of determining the currently operating target working process based on the indoor constant-state monitoring parameters and triggering a waste heat and cold recovery operation for the target working process, and returning the recovered waste heat and cold medium to a preset feedback heat exchanger, includes: The operating condition feature extraction operation is performed on the indoor constant three state monitoring parameters to generate a real-time operating condition feature vector; The real-time operating condition feature vector is matched and compared with the preset system link feature library to determine the target working link that is currently running; Generate a corresponding recovery trigger command based on the target working step, and open a preset medium recovery valve based on the recovery trigger command; The waste heat and cold recovery operation is performed on the target working process through the medium recovery valve to extract the waste heat and cold medium. A pre-set reflux booster pump is driven to transport the waste heat and waste cooling medium along a pre-set guide pipeline to the feedback heat exchanger.

[0012] By adopting the above technical solution, operating condition characteristics are extracted from monitoring parameters in real time and the target working links are matched and identified. The medium recovery valve is precisely triggered to recover the waste heat and cold medium that was originally directly discharged to the outside and transport it to the feedback heat exchanger. This realizes the centralized recovery of waste heat and cold from the system operation and provides a stable and reliable medium source for subsequent on-demand reuse.

[0013] Optionally, the step of matching and comparing the real-time operating condition feature vector with a preset system component feature library to determine the currently running target operating component includes: Retrieve multiple pre-stored benchmark feature vectors and associated feature labels from the preset system feature library; The real-time operating condition feature vector is compared with multiple sets of reference link feature vectors to calculate the vector distance, resulting in multiple sets of feature distance values. The multiple sets of feature distance values ​​are sorted according to the numerical increment rule, and the candidate feature distance value with the smallest value is selected. Extract the process identification label associated with the distance value of the candidate feature, and confirm the process identification label as the target work process.

[0014] By adopting the above technical solution, and using the system's feature library and real-time operating condition feature vectors to calculate vector distance and filter for the minimum distance, the target operating process is accurately matched. This enables automatic identification and positioning of the operating status of various equipment, laying the foundation for subsequent targeted triggering of waste heat and cold recovery operations, avoiding blind recovery operations, and improving recovery efficiency.

[0015] Optionally, the step of allocating the waste heat and cold medium to a preset heating network and a preset humidification network for reuse based on the state of the waste heat and cold medium stored in the feedback heat exchanger and the system load demand data includes: The real-time inventory value and real-time medium temperature value inside the feedback heat exchanger are obtained by pre-set liquid level sensor and temperature sensor respectively, and the real-time inventory value and the real-time medium temperature value are combined to determine the state of the waste heat and waste cold medium. The system load demand data is parsed and extracted to separate the target heating demand and the target humidification demand. Based on the target heating demand, the target humidification demand, and the real-time inventory value, an allocation calculation is performed to generate heating pipeline allocation opening parameters and humidification pipeline allocation opening parameters. According to the opening parameters of the heating pipeline and the opening parameters of the humidification pipeline, the preset three-way diversion valve is adjusted to form the corresponding heating flow channel and humidification flow channel; The waste heat and cold medium is introduced into the heat dissipation coil of the heating network through the heating channel to perform heat exchange and dissipation operation, and the waste heat and cold medium is introduced into the atomizing terminal of the humidification network through the humidification channel to perform water evaporation and spraying operation, so as to perform the reuse operation.

[0016] By adopting the above technical solution, the distribution calculation is performed based on the medium storage and temperature status in the feedback heat exchanger, combined with the target demand for heating and humidification. The three-way diversion valve is controlled to form a corresponding flow channel, and the recovered waste heat and cold medium is directionally supplied to the heat dissipation coil and atomization terminal. This achieves precise reuse of recovered energy on demand, avoids secondary energy loss, and significantly improves the overall energy efficiency of the system and the utilization level of renewable resources.

[0017] Optionally, the step of performing allocation calculations based on the target heating demand, the target humidification demand, and the real-time inventory value to generate heating pipeline allocation opening parameters and humidification pipeline allocation opening parameters includes: The total load demand is obtained by summing the target heating demand and the target humidification demand. Divide the real-time inventory value by the total load demand value to calculate the medium allocation ratio coefficient. The target heating demand and the target humidification demand are respectively multiplied by the medium distribution ratio coefficient to obtain the corrected heating volume value and the corrected humidification volume value. The corrected heating volume value is converted into the corresponding heating diversion angle value by using a preset flow angle mapping table, and the corrected humidification volume value is converted into the corresponding humidification diversion angle value. The heating diversion angle value is set as the opening parameter of the heating pipeline, and the humidification diversion angle value is set as the opening parameter of the humidification pipeline.

[0018] By adopting the above technical solution, the heating and humidification demands are adjusted in conjunction with the ratio of total load demand to real-time inventory and converted into diversion angle parameters based on the ratio of total load demand. This enables the recovered waste heat and cold media to be accurately allocated proportionally according to the overall load demand, avoiding insufficient or excessive supply from a single circuit, and achieving refined allocation and maximization of reuse efficiency of recovered energy.

[0019] A second aspect of this application provides an electronic device including a processor, a memory, a user interface, and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform the method as described in any of the foregoing.

[0020] A third aspect of this application provides a computer-readable storage medium storing instructions that, when executed, perform the method described in any of the preceding descriptions.

[0021] A fourth aspect of this application provides a computer program product that, when run on an electronic device, causes the electronic device to perform the method as described in any of the preceding claims.

[0022] In summary, one or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: By combining photovoltaic and solar thermal energy collection and direct drive, and based on the surplus and shortage status of electrothermal energy storage and the constant temperature, humidity, and oxygen load requirements after dismantling, a unified energy allocation command is generated using a decision model. This achieves coordinated scheduling and precise closed-loop control of the two renewable energy sources. At the same time, the system automatically matches target working links based on real-time operating characteristics, centrally recovers waste heat and cold, and allocates it to the heating and humidification networks for reuse in proportion to the total load demand and media inventory. This breaks down the barriers of independent operation of photovoltaic power and solar thermal collection and direct emission of waste heat and cold, enabling unified allocation of renewable energy and full utilization of waste heat and cold resources. This significantly improves the utilization rate of renewable energy and greatly reduces the energy efficiency loss of the three constant environment control. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the system architecture of an embodiment of the photoelectric and photothermal synergistic direct-drive three constant environment regulation method of this application; Figure 2 This is a flowchart illustrating a photoelectric and photothermal synergistic direct-drive three-constant environment regulation method disclosed in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application.

[0024] Explanation of reference numerals in the attached figures: 100, System architecture; 101, First terminal device; 102, Second terminal device; 103, Third terminal device; 104, Network; 105, Server; 301, Processor; 302, Communication bus; 303, User interface; 304, Network interface; 305, Memory. Detailed Implementation

[0025] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0026] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0027] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0028] like Figure 1 As shown, the system architecture 100 may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0029] Users can use the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 via the network 104 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103, such as model training applications, video recognition applications, web browser applications, social platform software, etc.

[0030] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be hardware or software. When the first terminal device 101, the second terminal device 102, and the third terminal device 103 are hardware, they can be various electronic devices with displays, including but not limited to smartphones, tablets, e-book readers, MP3 (Moving Picture Experts Group Audio Layer III) players, MP4 (Moving Picture Experts Group Audio Layer IV) players, laptops, and desktop computers, etc. When the first terminal device 101, the second terminal device 102, and the third terminal device 103 are software, they can be installed in the aforementioned electronic devices. They can be implemented as multiple software programs or software modules (e.g., multiple software programs or software modules used to provide distributed services) or as a single software program or software module. No specific limitations are made here.

[0031] This embodiment discloses a method for regulating a three-constant environment through photoelectric and photothermal synergistic direct drive. Figure 2 This is a schematic flowchart of a photoelectric and photothermal synergistic direct-drive three-constant environment regulation method disclosed in an embodiment of this application, as shown below. Figure 2 As shown, the method includes the following steps: S201. Photovoltaic power data and solar thermal collection data are collected synchronously at the current moment through a pre-configured photovoltaic solar thermal panel. The photovoltaic power data is input into a preset battery module to perform fluctuation smoothing processing to obtain electrical energy storage status parameters. The solar thermal collection data is input into a preset buffer water tank to perform buffer thermal storage processing to obtain thermal energy storage status parameters. Specifically, the system first extracts energy information from two sources simultaneously through a pre-configured photovoltaic thermal panel. The "pre-configuration" mentioned here specifically refers to: the integrated panel, which combines upper photovoltaic cell modules and a back-side heat conduction channel, is pre-installed in the sunny area of ​​the building, and voltage and current sensors are pre-installed at its electrical output end, while temperature probes and liquid flow meters are pre-installed at the inlet and outlet of its heat conduction channel. Based on this hardware preset, the system can simultaneously collect the current voltage and current values ​​and calculate the photovoltaic power data at the same sampling time, while also collecting the inlet and outlet water temperature difference and the circulation medium flow rate and calculating the solar thermal collection data according to thermodynamic formulas, thereby ensuring the alignment of the two unstable natural energy sources in the time dimension. Subsequently, the system needs to eliminate random disturbances caused by intermittent changes in solar irradiance: On the one hand, the acquired photovoltaic power is input into the preset battery module to perform fluctuation smoothing processing. The specific implementation mechanism can be, for example, through the bidirectional DC-DC steady current conversion algorithm built into the module, combined with the supercapacitor to absorb the millisecond-level high-frequency voltage pulse peaks, and then the smoothed low-frequency steady-state DC power is charged into the main lithium battery. After the smoothing is completed, the battery management system calculates and outputs the current state of charge (SOC) and its health limit in real time as energy storage state parameters. On the other hand, the fluid carrying the above heat is simultaneously guided into the preset buffer water tank to perform buffer heat storage processing. The specific physical implementation method is to use the high specific heat capacity of the large volume of water to perform dynamic charging and discharging temperature equalization, or preferably to absorb the latent heat at the temperature peak through the phase change heat storage material layer added to the inner wall of the tank to smooth out the severe heat wave peaks and valleys. After the thermal field stabilizes, the current water storage temperature level and effective heat capacity liquid level are output through multi-point detection as heat storage state parameters. Through the above process, the system transforms the original, fluctuating photoelectric and photothermal energy into a numerically stable and centrally controllable dual energy storage base for electricity and heat.

[0032] S202. Real-time indoor environmental parameters are collected by temperature sensors, humidity sensors and air quality sensors distributed in the indoor target area and return air vents, and the indoor environmental parameters are compared with the preset target three constant parameters to generate the current system load demand data. Specifically, the system first addresses the issue of bias in perception dimensions: it explicitly stipulates that relevant hardware must be distributed in the "indoor target area" (i.e., low-lying areas close to people's daily activities, such as next to the sofa in the living room, to capture real local sensory data) and the "return air vent" (i.e., the return flow of hot and cold fluids, to capture the macroscopic average state of the entire controlled space), thereby eliminating blind zone errors caused by single-point measurements; temperature sensors, humidity sensors, and air quality sensors (such as CO2 probes or TVOC (Total Volatile Organic Compounds) detectors) deployed in the above areas operate in real time, and the measured dry-bulb temperature, relative humidity, and indoor oxygen content parameters are linked together to form real-time indoor environmental parameters; among them, there is a clear inverse correlation between indoor CO2 concentration and indoor oxygen concentration (i.e., an increase in CO2 concentration corresponds to a decrease in oxygen concentration). The system obtains the real-time indoor oxygen concentration value by collecting CO2 concentration values ​​and converting them according to the standard atmospheric composition conversion relationship, which serves as a direct feedback parameter for constant oxygen control, thereby realizing a low-cost engineering solution that uses CO2 probes to replace direct oxygen sensors for constant oxygen monitoring. Subsequently, the system's underlying control core performs a multi-dimensional difference comparison operation between the measured value and the preset "target three constant parameters". It must be clarified here that the "target three constant parameters" refer to the steady-state threshold points of constant temperature, constant humidity and constant oxygen (or constant cleanliness) that are pre-configured according to human health standards or selected by the user (for example, preferably set to a comfortable temperature of 24°C, humidity of 50% and CO2 below 800ppm). The so-called "comparison operation" refers to calculating the absolute deviation of the current measured state from this three-dimensional benchmark (i.e., calculating the specific temperature difference, humidity difference and gaseous concentration difference). Furthermore, to ensure that the terminal devices clearly understand what actions to take, the system does not directly output the aforementioned deviation amplitude. Instead, it embeds a thermodynamic conversion model (e.g., based on the standard enthalpy-humidity diagram equations or proportional-integral-differential strategy) to convert the determined temperature difference into the required cooling or heating sensible heat load (unit: kW), convert the humidity difference into the required dehumidification or humidification latent heat load (unit: kg / h), and convert the difference between the real-time indoor oxygen concentration (obtained by inverse conversion from CO2 concentration) and the target oxygen concentration into the required additional ventilation volume. Specifically, when the CO2 concentration monitoring value exceeds the preset upper limit threshold (e.g., 800 ppm), the system determines that the indoor oxygen concentration is lower than the target value, calculates the corresponding oxygen concentration deviation, and converts it into an equivalent fresh air supply. Finally, it encapsulates and sets these three types of calculated and converted physical supply amounts to formally generate the current "system load demand data." In this way, it successfully translates the relatively abstract perception of environmental deviation into precise data standards for the next execution unit to absorb energy storage on demand.

[0033] S203. Based on the electrical energy storage status parameters, the thermal energy storage status parameters, and the system load demand data, generate an energy dispatching command; In specific implementation, the system's overall calculation module uses the electrical energy storage state parameters and thermal energy storage state parameters as available boundary conditions, and the system load demand data as the target to be met, and performs matching calculations through a built-in energy allocation algorithm. For example, this matching calculation can be achieved through a preset priority decision tree: the algorithm prioritizes parsing the thermal gap in the load demand and directs it to prioritize scheduling thermal energy storage (such as hot water storage bodies) to meet it, while directing the power and mechanical gaps in the load demand (such as the power consumption of wind turbine units) and the fallback portion of insufficient thermal energy to schedule electrical energy storage for matching, thereby deriving the power allocation table that each module needs to output; or, the embedded economic optimization function can be called to calculate online the "electricity-heat" joint dispatch ratio with the lowest total energy consumption cost. Subsequently, the system performs low-level compilation and transformation on the obtained allocation strategy or ratio data to generate targeted energy allocation instructions. To ensure full disclosure in the manual, the "energy allocation instructions" here refer not only to an abstract conclusion, but specifically to a series of specific execution parameter settings for the corresponding hardware. For example, it includes the device ID of the corresponding end device (such as a circulating water pump, compressor, and fresh air blower), as well as the targeted operating frequency (Hz), valve target opening percentage (%), and start-stop timing signals to control these devices to accurately execute the allocation strategy. This establishes a closed-loop control system that empowers the underlying physical hardware components from top-level data analysis.

[0034] Optionally, generating an energy allocation command based on the electrical energy storage status parameters, the thermal energy storage status parameters, and the system load demand data includes: comparing the electrical energy storage status parameters with a preset energy safety threshold to extract overflow energy data exceeding the energy safety threshold; comparing the thermal energy storage status parameters with a preset heat safety threshold to extract overflow heat data exceeding the heat safety threshold; decomposing the system load demand data dimensionally to obtain constant temperature load demand parameters, constant humidity load demand parameters, and constant oxygen load demand parameters; inputting the overflow energy data, the overflow heat data, the constant temperature load demand parameters, the constant humidity load demand parameters, and the constant oxygen load demand parameters into a preset energy allocation decision model, and outputting corresponding energy allocation weight coefficients through the energy allocation decision model; and performing command encoding operations based on the energy allocation weight coefficients to generate the energy allocation command.

[0035] Specifically, before executing the formal allocation, the system first needs to establish the "safety reserve" and "actual available capacity" of the supply-side resources. In terms of electrical energy, the system performs a one-way numerical comparison between the acquired electrical storage state parameters (such as the current available SOC value of the lithium battery pack) and a preset "electricity safety judgment threshold." The "electricity safety judgment threshold" refers to the most basic electricity warning line reserved in advance to prevent sudden power outages in the main grid, ensure basic power consumption of the controller, and maintain black start of equipment (its configuration parameters can be, for example, a specific value between 10% and 20% of the total storage capacity). By calculating the difference through the comparison operation, the system can accurately identify this protected reserve of electrical energy, and then extract the "overflow electricity data" (i.e., the absolute available electrical storage capacity) that is truly allowed to participate in the current scheduling. Similarly, in the thermal energy dimension, the system synchronously compares the acquired thermal energy storage state parameters (such as the current total enthalpy of the phase change thermal storage tank or the current average water temperature of the water tank) with the preset "thermal safety judgment threshold". This "thermal safety judgment threshold" usually refers to the thermodynamic bottom line that must be maintained to prevent the circulation pipeline from freezing and breaking in winter, or to ensure the basic domestic hot water supply in the building (for example, setting the water temperature not lower than the antifreeze calibration point of 35°C). Through the same comparison and deduction calculation, the system accurately extracts the "overflowing heat data", thereby clarifying the system's real-time available total net resources from both physical and logical perspectives.

[0036] After clarifying the net resource base on the supply side, the system's focus shifted to the demand side, performing a dimensionally targeted breakdown of the previously generated, aggregated system load demand data. Specifically, since the back-end implementation mechanisms of the three constant (constant temperature, constant humidity, constant oxygen) systems differ in physical attributes—for example, chiller and heat source water heaters are responsible for temperature control, specific modules with independent compression systems are responsible for humidity intervention, and fresh air units are responsible for oxygen metabolism—the overall control module must rely on its internal decoupling program to separate the originally mixed load data into "bills" with independent control targets. First, it extracts the "constant temperature load demand parameters" specifically characterizing sensible heat exchange tasks (primarily calculating the cooling and heating power required to overcome indoor and outdoor temperature differences and equipment heat dissipation); second, it extracts the "constant humidity load demand parameters" characterizing latent heat treatment tasks (reflecting the energy consumption requirements for decondensation and humidification); and third, it extracts the "constant oxygen load demand parameters" characterizing air quality replacement tasks (reflecting the mechanical power compensation required by the fresh air supply and exhaust fans to overcome filter and duct resistance). Thus, it was successfully realized that large-particle indoor environmental deviations were transformed into highly concrete multi-dimensional "request variables" for the three types of end-effectors.

[0037] Furthermore, the system enters the core matching and game theory calculation stage. That is, the supply-side net assets (i.e., the overflow electricity data and the overflow heat data) and the demand-side detailed bills (i.e., the constant temperature load demand parameters, the constant humidity load demand parameters, and the constant oxygen load demand parameters) defined above are used as independent variable factors and simultaneously input into the preset energy allocation decision model. As a technical implementation, this energy allocation decision model can be a weight allocation algorithm matrix composed of multiple sets of linear programming equations, or an optimization model pre-trained based on a Long Short-Term Memory (LSTM) network. Its core operating mechanism lies in exploring the optimal combination of electrical energy and thermal energy among various load demands. For example, in cooling or heating (constant temperature) tasks, if the model determines that the current overflow of thermal energy storage (or chilled water energy storage) is extremely abundant and the cost of calling it is lower than that of electric compressor cooling, the model will automatically calculate and output the corresponding energy allocation weight coefficients (for example, specifying that in the current constant temperature load task, the proportion of response by thermal energy storage is increased to 80%, and the proportion of support by electrical energy storage is reduced to 20%). For fresh air systems driven purely by mechanical kinetic energy (constant oxygen load), the model will output a weight coefficient distribution that is 100% fully covered by electrical energy storage.

[0038] Furthermore, to transform the logical values ​​calculated by the aforementioned high-order model into instructions that the underlying physical devices can understand and strictly execute, the system will perform standard instruction encoding operations within the underlying control motherboard based on the energy allocation weight coefficients derived above. Instruction encoding refers to digitally packaging, checking headers and tails, framing, and mapping the percentage or absolute values ​​of each weight according to the underlying message format of a predetermined communication protocol (such as Modbus TCP or BACnet building IoT protocols). This transforms the abstract weights into the target operating frequency (Hz) required by the host, the specific opening degree command (%) of the electric two-way / three-way valve, and the operating gear or start / stop signal of the water pump controller. Through the aforementioned step-by-step data cleaning, transformation, and compilation, the energy allocation instructions that can be directly read and mounted by the devices are formally generated. This ensures that the system can safely, accurately, and economically drive the stable operation of the three constant environment system based on real-time energy storage reserves and environmental deviations.

[0039] S204. According to the energy allocation command, constant temperature regulation, constant humidity regulation and constant oxygen regulation are executed respectively, and indoor constant three state monitoring parameters are collected in real time during the execution of constant temperature regulation, constant humidity regulation and constant oxygen regulation. Specifically, the system's central gateway sends encapsulated execution messages to various levels of drive controller modules via the underlying communication bus: thereby driving the heat pump host compressor to run at the target frequency, or controlling the electric two-way water valve on the radiant capillary network to reach a specified opening degree to perform the "constant temperature regulation"; driving the surface cooling coil of the independent dehumidifier or starting the ultrasonic micro-mist humidifier to match the moisture load to perform the "constant humidity regulation"; and synchronously adjusting the speed of the brushless DC fan of the total heat exchange fresh air unit to drive the replacement of fresh and exhaust air to perform the "constant oxygen regulation". It must be emphasized that due to the large macroscopic volume of building spaces, the internal thermodynamic and fluid dynamic evolution exhibits extremely significant thermal inertia and conduction time delay effects. Simply issuing commands in open-loop control can easily lead to overshoot (such as the room temperature dropping too low) or the adjustment falling short of expectations. Therefore, within the overlapping time window during which the aforementioned mechanical components continuously output power, the underlying system must still force the temperature and humidity transmitters and air quality probe arrays deployed at indoor measuring points to remain in a high-frequency active polling state. This continuously detects and tracks the instantaneous decay or rise trajectory of real-time dry and wet bulb temperatures, absolute relative humidity, and gaseous pollutant indicators when the environment changes, thereby completing the action of "real-time acquisition of indoor three constant state monitoring parameters". Through this concurrent mechanism of "executing commands while collecting data", the system successfully constructs a rigorous effectiveness verification feedback link during this period, providing a crucial dynamic reference system for judging whether the current environment has approached the preset target of "three constants" and whether it is necessary to stop or fine-tune the energy supply distribution in time.

[0040] Optionally, the step of performing constant temperature regulation, constant humidity regulation, and constant oxygen regulation according to the energy allocation command includes: performing signal decoding processing on the energy allocation command to extract the constant temperature control target value, constant humidity control target value, and constant oxygen control target value; performing data classification and analysis on the indoor environmental parameters to separate the indoor real-time temperature value, indoor real-time humidity value, and indoor real-time oxygen concentration value; calculating the difference between the constant temperature control target value and the indoor real-time temperature value to obtain a temperature deviation adjustment amount, and controlling a pre-configured variable frequency heat pump host to perform the constant temperature regulation according to the temperature deviation adjustment amount; calculating the difference between the constant humidity control target value and the indoor real-time humidity value to obtain a humidity deviation adjustment amount, and triggering a pre-set steam generator to perform the constant humidity regulation according to the humidity deviation adjustment amount; calculating the difference between the constant oxygen control target value and the indoor real-time oxygen concentration value to obtain a fresh air supply deviation amount, and driving a pre-set total heat exchange exhaust device to perform the constant oxygen regulation according to the fresh air supply deviation amount.

[0041] Specifically, the energy allocation command undergoes signal decoding. The controller parses the received command communication message into data frames, extracting the expected constant temperature control target values ​​(e.g., user-set 24℃), constant humidity control target values ​​(e.g., set 50%RH), and constant oxygen control target values ​​(e.g., set upper limit of CO2 concentration) from its data payload. Simultaneously, the collected indoor environmental parameters are classified and analyzed. Through digital filtering and multi-channel data separation technology, the mixed sensor data streams reported at the lower level are demultiplexed to accurately extract the real-time indoor temperature, humidity, and oxygen concentration values ​​reflecting the current physical space's objective state.

[0042] After obtaining the target and real-time values, constant temperature regulation is performed. The difference between the target constant temperature control value and the real-time indoor temperature value is calculated to obtain the temperature deviation adjustment amount. Based on the temperature deviation adjustment amount, the pre-configured variable frequency heat pump unit is controlled to perform constant temperature regulation. Specific technical solutions for implementing this control include: the first solution is direct frequency control, where the system uses a PID algorithm to convert the temperature deviation adjustment amount into an analog control signal, directly changing the operating frequency (Hz) of the variable frequency heat pump unit compressor; the larger the temperature difference, the higher the operating frequency. The second solution is water-refrigerant linkage control, where, in addition to adjusting the compressor speed, the system also synchronously adjusts the frequency of the circulating water pump in the hot and cold water system or the opening of the electronic two-way water valve at the radiant capillary network end based on the temperature deviation adjustment amount, precisely matching the hot and cold output.

[0043] In terms of humidity control, the difference between the target humidity control value and the real-time indoor humidity value is calculated to obtain the humidity deviation adjustment amount. Based on the humidity deviation adjustment amount, the associated preset steam generator is triggered to perform the humidity control. Specific implementation schemes include: the first is a stepless power adjustment mode, where when the environment is dry and the humidity deviation is small, the deviation is converted into a pulse-width modulation (PWM) signal to control the conduction angle of the internal thyristor, precisely changing the stepless output power of the heating electrode and smoothly releasing water vapor; the second is a step mode, where when the humidity deviation exceeds a preset threshold (e.g., for rapid humidification), the system determines to close the contactor, causing the steam generator to directly switch to full-power, full-load boiling state, rapidly injecting a large amount of water vapor into the air supply system.

[0044] It should be noted that the triggering logic of the steam generator is based on the directional judgment of the humidity deviation adjustment amount: when the constant humidity control target value is greater than the real-time indoor humidity value (humidity deviation adjustment amount is positive, the indoor environment is dry, and humidification is needed), the controller determines that moisture needs to be added to the room and activates the steam generator to perform humidification operation; when the real-time indoor humidity value is not lower than the constant humidity control target value (humidity deviation adjustment amount is zero or negative, the indoor humidity has reached the standard or is too high, and there is no need for humidification), the controller determines that humidification is not needed, and the steam generator remains in standby off state and does not perform any action. In the case of high indoor humidity requiring dehumidification, the active reduction of humidity is achieved through the variable frequency heat pump unit in cooling mode, via the physical effect of low-temperature condensation and water precipitation on the surface of the evaporator coil, thus forming a two-way collaborative and complementary constant humidity control mechanism with the steam generator for both low and high humidity conditions, jointly ensuring the achievement of the constant humidity target under all operating conditions. The above directional triggering judgment is automatically executed by the controller's built-in sign judgment module based on the positive or negative sign of the humidity deviation adjustment amount, without additional manual intervention.

[0045] Regarding constant oxygen regulation, the target value for constant oxygen control is compared and the difference is calculated with the real-time indoor oxygen concentration value to obtain the fresh air supply deviation. (The real-time indoor oxygen concentration value is obtained by inversely converting the CO2 concentration collected by the CO2 sensor: when the CO2 concentration increases, the oxygen concentration decreases accordingly. The two are converted one-to-one through the standard atmospheric component ratio relationship. The target value for constant oxygen control corresponds to the inverse conversion result of the upper limit of CO2 concentration. The two are equivalent and interchangeable at the numerical level. In engineering implementation, the CO2 probe value can be used as the calculation input.) Based on this, the preset total heat exchange exhaust device is driven to perform the constant oxygen regulation. Specific drive control schemes include: The first scheme is variable frequency speed control, where the controller independently adjusts the speed of the supply and exhaust fans within the total heat exchanger based on the magnitude of the deviation, dynamically increasing or decreasing the replacement air volume; the second scheme is bypass control, where when the fresh air supply deviation is extremely large and the outdoor temperature is detected to be suitable, not only is the fan speed increased, but the bypass valve inside the total heat exchanger is also fully opened, allowing the introduced fresh air to bypass the air resistance of the heat exchange core and rapidly supply clean air to the room at maximum airflow. Through the above-mentioned independent calculation and execution chain based on specific deviations, decoupled operation of the three environmental elements is achieved.

[0046] S205. Based on the indoor constant state monitoring parameters, determine the target working process that is currently running, and trigger the waste heat and cold recovery operation for the target working process, and return the recovered waste heat and cold medium to the preset feedback heat exchanger. Specifically, the system determines the target working process currently in operation based on the real-time indoor constant state monitoring parameters (such as indoor temperature drop rate, real-time relative humidity, and exhaust volume), and triggers the corresponding residual energy recovery and fluid guidance operations accordingly. In a first specific implementation scheme, when the monitoring parameters indicate that the system is in the "exhaust and ventilation" target working stage with large air volume replacement, the controller triggers the opening of the diversion valve on the return air duct to perform energy recovery operation. The turbid exhaust carrying the original indoor air conditioning cooling or heating capacity is used as the waste heat and cooling medium. The exhaust fan uses negative pressure to draw it back and pass through the preset cross-flow total heat exchange core (i.e., the feedback heat exchanger). Before being discharged outdoors, it undergoes full exchange of sensible and latent heat with the outdoor fresh air introduced in the opposite direction. As a second alternative specific implementation scheme, when the monitoring parameters show extremely high humidity and the system is in the "dehumidification and cooling" target working stage with continuous depth, the controller triggers the liquid cooling capacity recovery operation. Specifically, by opening the guide solenoid valve at the bottom of the evaporator water tray, the low-temperature condensate liquid water (e.g., usually between 10℃ and 15℃) precipitated during the dehumidification process is collected as the waste cooling medium for this stage. The preset return power booster pump drives the condensate liquid water to be transported back to the feedback heat exchanger along the preset guide pipeline. Inside the feedback heat exchanger, the condensed liquid water receives heat energy compensation from the heat storage side of the buffer water tank through the internal heat exchange channel, or receives heat input from the waste heat side of the heat pump unit under heating conditions, so that the outlet temperature of the medium is increased in stages to reach a temperature level suitable for distribution to the heating network for heat exchange and dissipation operation or distribution to the humidification network for water evaporation and spraying operation. Under the transitional season conditions where only dehumidification is required, if there is no surplus heat to compensate on the energy storage side, the system will mainly guide the liquid medium after it has been homogenized by the feedback heat exchanger to the humidification network, and use the liquid storage of the medium to perform water evaporation and spraying to achieve the humidification target, thereby realizing the cascade reuse of the waste cooling medium. The heat compensation source and outlet temperature control parameters of the aforementioned medium in the feedback heat exchanger are determined by the controller based on the real-time medium temperature value and system load demand data. The medium distribution path at the outlet of the feedback heat exchanger is switched by the three-way diverter valve according to the distribution opening parameter command. The opening of the recovery valve and the flow rate parameters of the return power booster pump can be dynamically adjusted by the system according to the feedback load demand under different operating conditions, which is not limited here.

[0047] Optionally, the step of determining the currently operating target working process based on the indoor constant-temperature, constant-state monitoring parameters and triggering a waste heat and cold recovery operation for the target working process, and returning the recovered waste heat and cold medium to a preset feedback heat exchanger, includes: performing a condition feature extraction operation on the indoor constant-temperature, constant-state monitoring parameters to generate a real-time condition feature vector; matching and comparing the real-time condition feature vector with a preset system process feature library to determine the currently operating target working process; generating a corresponding recovery trigger command based on the target working process, and opening a preset medium recovery valve based on the recovery trigger command; performing the waste heat and cold recovery operation on the target working process through the medium recovery valve to extract the waste heat and cold medium; and driving a preset return power booster pump to rotate and transport the waste heat and cold medium along a preset guide pipeline to the feedback heat exchanger.

[0048] Specifically, the system's main control unit receives the indoor constant-temperature, constant-humidity, and constant-temperature monitoring parameters from the underlying layer (these parameters typically include temperature change rate, humidity maintenance level, real-time equipment operating power readings, and pipeline pressure, etc.) and performs operating condition feature extraction operations on them. Specifically, the controller extracts multi-dimensional values ​​to form a structured array or tensor, thereby generating a real-time operating condition feature vector representing the current physical state (e.g., it can be represented as [temperature drop, dehumidification rate, compressor frequency, return air pressure]). Subsequently, the controller performs feature matching and comparison between the generated real-time operating condition feature vector and a preset system component feature library stored in the local ROM (Read-Only Memory) medium. In practical applications, the feature library pre-loads reference template vectors for various standard working states. The system can find the state template with the highest similarity by calculating the Euclidean distance or cosine similarity between the real-time feature vector and each reference template vector (the first matching scheme), or by using a pre-configured decision tree model for classification and discrimination (the second matching scheme). This allows the system to accurately determine and identify the target working stage that it is currently operating in, such as determining that the system is currently in the "continuous deep dehumidification stage" or the "full-load fresh air pre-cooling stage".

[0049] After identifying the specific working stage, the system generates a corresponding recovery trigger command at the logic layer based on the determined target working stage. This trigger command is sent to the corresponding actuator via the communication bus, and the "preset media recovery valve" on the corresponding matching cross-pipe is opened based on the recovery trigger command. In terms of hardware implementation, taking the current stage as "continuous deep dehumidification" as an example, the recovery command will convert the control voltage and open the electric proportional solenoid valve set at the bottom of the condensate water receiving pan as the recovery valve; if it is determined to be "full-load fresh air exchange stage", the electric deflector valve set on the exhaust main duct will be driven to open. By opening the media recovery valve, the system physically intervenes in the current target working stage, physically cutting or bypassing the material flow with residual energy, thereby performing the waste heat and cold recovery operation and actually extracting the required waste heat and cold medium (such as low-temperature condensate water at 10℃-15℃, or exhaust waste air with indoor 24℃ ambient cooling capacity).

[0050] To overcome the physical potential energy resistance and pipeline flow resistance during the recovery process, the system sends an electrical signal to drive a pre-installed reflux booster pump on the pipeline after successful extraction of the medium. For cases where the extracted waste heat and cold medium is liquid (condensate), the booster pump is specifically a small variable frequency centrifugal water pump; if the medium is gaseous (exhaust), the booster pump is a booster duct fan. Under the continuous pressurization of the booster pump, the waste heat and cold medium is forced to undergo reverse or bypass cyclic transport along a pre-installed guide pipeline with a heat-insulating and cold-resistant outer protective layer, and is ultimately forced into the corresponding flow channel of the feedback heat exchanger. Inside this feedback heat exchanger (specifically, a water / fluorine plate heat exchanger or an air total heat exchange interface connected to the heat dissipation side of the heat pump unit), the input high-efficiency recovery medium performs physical heat / cold exchange pretreatment on the circulating refrigerant in the main system circulation or the newly introduced high-temperature and high-humidity fresh air. After the circulation feedback, it is finally discharged to the outside of the building through the lower-level sewage pipe or exhaust vent, thus forming a closed and tight energy cycle recovery link.

[0051] Optionally, the step of matching and comparing the real-time operating condition feature vector with a preset system component feature library to determine the currently running target operating component includes: retrieving multiple sets of pre-stored benchmark component feature vectors and associated component identification tags from the preset system component feature library; calculating the vector distance between the real-time operating condition feature vector and the multiple sets of benchmark component feature vectors to obtain multiple sets of feature distance values; sorting the multiple sets of feature distance values ​​according to an increasing numerical rule to select the candidate feature distance value with the smallest value; extracting the component identification tag associated with the candidate feature distance value, and confirming the component identification tag as the target operating component.

[0052] Specifically, the system's microprocessor, through addressing instructions, retrieves multiple pre-stored sets of benchmark feature vectors and their associated identifiers from a non-volatile storage medium (such as an EEPROM or flash memory chip embedded in the control motherboard) containing a preset system feature library. In this embodiment, the benchmark feature vectors can be understood as standard templates of multi-dimensional parameter arrays measured by the system under various standard operating conditions in a laboratory or historical optimal state; while the identifiers are unique classification IDs or state names corresponding to these templates. For example, the retrieved feature library data may include: benchmark vector A (representing high air volume and high pressure difference) and its associated label "fresh air replacement link"; benchmark vector B (representing high-frequency cooling and high dehumidification rate) and its associated label "deep dehumidification link," etc. By retrieving these preset data in batches at once, a complete reference benchmark is provided for subsequent comparisons.

[0053] After data loading is complete, the processor calls its internal Arithmetic and Logic Unit (ALU) to calculate the vector distance in a multidimensional feature space between the previously acquired real-time operating condition feature vector and the extracted multiple sets of reference link feature vectors. This yields a series of results reflecting the degree of difference between the current state and each standard state, i.e., multiple sets of feature distance values. The specific technical solutions for implementing this vector distance calculation cover various mathematical metrics: The first solution uses the Euclidean distance algorithm to directly calculate the absolute straight-line distance between the real-time vector point and each reference vector point in multidimensional space as the feature distance value. This method is extremely sensitive to absolute differences in parameters such as temperature and humidity, making it highly suitable for three-constant systems with extremely high requirements for environmental stability. As a second alternative, the Manhattan distance or cosine distance algorithm can also be used. For example, using cosine distance to calculate the multidimensional angle and converting it into a distance scalar, this method focuses more on evaluating the proportional synergistic relationship between multiple environmental parameters (such as cooling and dehumidification trends), and has stronger robustness when the sensor may have overall hardware temperature drift errors. The specific algorithm selection and its calculation accuracy and bit width can be flexibly configured according to the computing power resources of the controller, and are not limited here.

[0054] After calculating all distance results, the controller's sorting logic module (using algorithms such as quicksort or bubble sort) strictly follows the numerical increment rule (i.e., ascending order from smallest to largest) to sort the generated sets of feature distance values. Then, the first element of this ordered sequence is extracted to quickly and uniquely select the candidate feature distance value with the smallest value. In the multidimensional space comparison logic, the smaller the feature distance, the closer the objectively measured temporal state is to the standard operating condition, and the higher the similarity. Finally, the controller extracts the associated stage identifier tag in the original feature library for the candidate feature distance value through a lookup table, and formally confirms the retrieved stage identifier tag as the target operating stage currently running in the system. Through the above specific mechanism of transforming fuzzy state determination into multidimensional vector distance optimization, the system can accurately and resiliently lock onto the actual operating condition of the system, ensuring that the opening of the subsequent recovery valve and the operation of the water pump perfectly match the thermal physical characteristics of the operating stage, maximizing the energy efficiency benefits of waste heat and cold recovery.

[0055] S206. Based on the state of the waste heat and cold medium in the feedback heat exchanger and combined with the system load demand data, the waste heat and cold medium is allocated to the preset heating network and preset humidification network as needed for reuse.

[0056] Specifically, after the waste heat and cold medium is successfully fed back to the system, the system will collect and determine the physical state of the waste heat and cold medium in real time (specifically including the real-time outlet temperature, phase state, available storage capacity, or flow parameters of the medium) based on the high-precision sensor network (such as temperature probes, level switches, and bypass flow meters) installed inside or at the outlet of the feedback heat exchanger. At the same time, it will read the system load demand data in real time (such as the difference between the current indoor temperature and humidity and the set target, i.e., the heating gap and humidification gap) in conjunction with the underlying communication bus. Based on this, dynamic diversion control parameters will be generated, and the waste heat and cold medium will be distributed to the preset heating network and preset humidification network as needed to perform reuse operations by driving the proportional regulating valve or multi-way diversion valve set at the pipe gallery intersection node.

[0057] Before performing on-demand allocation, the controller determines the temperature range of the thermodynamic grade of the medium in the feedback heat exchanger based on the real-time medium temperature value to ensure that the medium is allocated to a network that matches its temperature properties. The specific determination rule is as follows: When the real-time medium temperature value is higher than the preset lower limit threshold of the applicable heating temperature (e.g., 35°C, which can be determined according to the type of heating terminal: underfloor heating coils are usually 35°C to 45°C, and capillary radiant terminals are usually 28°C to 32°C, which is not limited here), the system determines that the current medium is in a waste heat applicable state, and a larger proportion or even the entire amount can be allocated. The medium is allocated to the heating network for heat exchange and dissipation. When the real-time medium temperature is below the lower limit of the applicable heating temperature but still above the minimum inlet water temperature required by the atomizing terminal (e.g., above 15°C), the system determines that the current sensible heat grade of the medium is insufficient to directly meet the heating terminal demand. The medium is then primarily allocated to the humidification network, utilizing the liquid volume of the medium for water evaporation and spraying, thus achieving humidification and reuse of the remaining water. When the real-time medium temperature is in the intermediate temperature range suitable for both heating and humidification, the system performs a proportional coordination allocation based on the relative weights of the heating and humidification target demands. The specific values ​​of the thresholds for each temperature range can be calibrated according to the building type and the parameters of the three constant temperature terminal equipment; these are not limited here.

[0058] Specifically, the technical solutions for implementing this on-demand allocation and reuse operation include: Firstly, in the preferred scheme, when the system load demand data indicates that the current period is a cold winter season, the heating demand on the supply side is at its peak, and the waste heat medium in the heat exchanger is detected to carry a large amount of usable sensible enthalpy, the microprocessor outputs a control level to switch the main channel of the electric three-way reversing valve to the heating side, directing most or even all of the heat fluid to the preset heating network (such as concealed underfloor heating coils or capillary radiant terminals), directly compensating for the indoor heat load through physical heat conduction, and performing an operation primarily based on direct heat reuse; Secondly, as an alternative scheme, if the system load combined with a seasonal algorithm detects that the current indoor relative humidity is below a preset lower threshold (i.e., the existing heat is below the threshold value), the system load is adjusted accordingly. When there is an extremely high demand for humidification, and the processor detects that the medium condensed in the heat exchanger's water collection pan and slightly heated by the waste heat from the outdoor unit of the heat pump is liquid warm water, the processor drives the variable frequency diversion pump according to the calculated water pressure to pump the medium preferentially or at a set proportional flow rate into the preset humidification network (e.g., the water distribution pipe of the wet film humidifier in the centralized air supply duct, or the high-frequency ultrasonic water tank). The warm water is quickly vaporized and dispersed into the indoor airflow, performing a closed-loop reuse operation of water for on-site humidification. It should be noted that the specific valve opening ratio, diversion cut threshold, and other parameters used to balance the two networks can be dynamically and steplessly configured by the PID self-tuning control logic according to the small disturbance requirements of the actual indoor constant environment, and are not limited here.

[0059] Optionally, the step of allocating the waste heat and cold medium to a preset heating network and a preset humidification network for reuse based on the state of the waste heat and cold medium stored in the feedback heat exchanger and the system load demand data includes: acquiring the real-time storage value and real-time medium temperature value inside the feedback heat exchanger through preset level sensors and temperature sensors, and combining the real-time storage value and the real-time medium temperature value to determine the state of the waste heat and cold medium; performing data parsing and extraction on the system load demand data to separate the target heating demand and the target humidification demand; and further... Based on the target heating demand, the target humidification demand, and the real-time inventory value, an allocation calculation is performed to generate heating pipeline allocation opening parameters and humidification pipeline allocation opening parameters. According to these parameters, a preset three-way diverter valve is adjusted to form corresponding heating and humidification channels. The waste heat and cold medium is introduced through the heating channel into the radiator coil of the heating network for heat exchange and dissipation, and through the humidification channel into the atomizing terminal of the humidification network for water evaporation and spraying, thus performing the reuse operation.

[0060] Specifically, the system's main controller senses the available energy status in real time through sensing components deployed within the feedback heat exchanger cavity. Specifically, it acquires the real-time fluid volume (e.g., calculating the current available liters or milliliters) using a level sensor pre-placed at the bottom of the accumulator tank, and simultaneously acquires the real-time medium temperature using a temperature sensor array pre-placed on the medium outlet pipe wall. Regarding the selection of these sensing components, the first option is to use an ultrasonic reflective level probe combined with a PT100 high-precision thermistor to achieve high-frequency, non-contact, precise data acquisition; the second alternative is to use a traditional float potentiometer combined with an NTC thermistor to meet the requirements of high cost-effectiveness and anti-condensation sealing. Subsequently, the controller concatenates the real-time fluid volume (representing the "quantity" of the resource) and the real-time medium temperature (representing the "quality" of the resource) into a data structure in memory, combining them to determine the global state variable of the waste heat and waste cold medium.

[0061] At the data processing layer, the central processing unit of the system motherboard synchronously performs message decomposition and data parsing to extract the system load demand data from the thermostats in each room. Through field stripping, the system decouples and separates from the total demand the target heating demand (e.g., the calculated heat compensation kWh) specifically used to characterize the room temperature gap, and the target humidification demand (e.g., the calculated air humidity replenishment grams) specifically used to characterize the humidity difference. Next, the processor calls the allocation decision algorithm in the internal flash memory, and performs multivariate linear or nonlinear allocation calculations based on the aforementioned target heating demand, target humidification demand, and the underlying real-time inventory values. This outputs digital heating pipe allocation opening parameters and humidification pipe allocation opening parameters (e.g., analog duty cycle signals existing in the form of 0-100%). The specific technical solutions for performing this matching operation include: the first solution is the on-demand weighted proportional method, which directly calculates the opening commands of the two valves proportionally based on the set heat / humidity gap weights and the current water volume; the second solution is the priority threshold lookup table method, which prioritizes assigning the opening to the humidification pipeline to meet the basic indoor comfort level when the real-time water volume is detected to be at an extremely low set threshold, and then allocates the remaining amount to the heating. The specific values ​​of the judgment thresholds and weights can be configured according to the actual calibration requirements of the three constant operating conditions, and are not limited here.

[0062] At the physical execution end, the microcontroller converts digital parameters into drive current. Based on the opening parameters of the heating pipeline and the humidification pipeline, it controls the rotation of the valve core in a pre-set three-way diversion valve (such as a V-type proportional regulating valve driven by a servo motor) located at the pipeline branch point. By changing the cross-sectional area, corresponding physically isolated heating and humidification channels are directly formed according to the set diversion ratio.

[0063] Furthermore, driven by the hydrostatic pressure of the system's return pump, a portion of the waste heat and cold medium (such as warm water), which has been proportionally cut, is continuously introduced into various terminal heat dissipation coils of the heating network through the opened heating channel. Specifically, the terminal can be a capillary constant-temperature radiant network pre-embedded in the ceiling, or a traditional underfloor heating coil. The medium flows along the wall, performing heat exchange and dissipation operations on the indoor air or building envelope. Simultaneously, the remaining portion of the waste heat and cold medium is smoothly introduced into the atomization terminal of the humidification network through the opened humidification channel. For water atomization conversion, specific implementation schemes can include dripping the medium into a high-frequency ultrasonic oscillating water tank to disperse it into micron-level cold mist, or using a micro diaphragm pump to pressurize the medium and directly spray it into the air supply duct through a ruby ​​microporous nozzle, thereby performing a water evaporation spraying operation. Based on the aforementioned data-analysis-based servo splitting and dual-network terminal collaboration, not only are the waste products generated during system operation consumed and the aforementioned reuse operations performed, but the heat output of the original host equipment under extreme stress and the cost of separately purchased pure water humidifier consumables are also effectively shared.

[0064] Optionally, the step of performing allocation calculations based on the target heating demand, the target humidification demand, and the real-time inventory value to generate heating pipeline allocation opening parameters and humidification pipeline allocation opening parameters includes: summing the target heating demand and the target humidification demand to obtain a total load demand value; dividing the real-time inventory value by the total load demand value to calculate a medium allocation ratio coefficient; multiplying the target heating demand and the target humidification demand by the medium allocation ratio coefficient respectively to obtain a corrected heating volume value and a corrected humidification volume value; converting the corrected heating volume value into a corresponding heating diversion angle value and the corrected humidification volume value into a corresponding humidification diversion angle value through a preset flow angle mapping table; setting the heating diversion angle value as the heating pipeline allocation opening parameter and the humidification diversion angle value as the humidification pipeline allocation opening parameter.

[0065] Specifically, the system's ALU will resolve the target heating demand and the target humidification demand (before summation, the system's built-in thermal conversion module has converted both to medium consumption in mL / min units before addition: the target heating demand is converted from thermal power units to volumetric flow rate using the formula Q=P×1000÷[ρ×c×ΔT×(1 / 60)], where Q is the converted medium volumetric flow rate (mL / min), P is the target heating thermal power (W), and ρ is the medium density (g / min). mL (1.00 for room temperature water), c is the specific heat capacity of the medium (J / (g·℃), 4.18 for room temperature water), ΔT is the design inlet and outlet temperature difference of the medium (℃); the target humidification demand is converted from mass flow rate to volumetric flow rate using the formula V=m÷60÷ρ, where V is the converted medium volumetric flow rate (mL / min), m is the target humidification mass flow rate (g / h), and ρ is the same as above. This is loaded into the accumulator register for summation, calculating the upper limit of the overall water intake or heat absorption capacity of the system, thus obtaining the total load demand value. Subsequently, the processor calls the hardware divider to divide the real-time inventory value fed back by the sensor by the previously obtained total load demand value, calculating the medium allocation ratio coefficient characterizing the current sufficiency of physical resources. There are two specific technical solutions for implementing mathematical operations here: The first solution is to use single-precision floating-point numbers according to the IEEE 754 standard for direct division calculations to retain the highest precision decimal places and accurately handle extremely small changes in demand; as a second alternative technical solution, to match the extremely low cost of basic microcontrollers without floating-point units, the existing values ​​can be pre-shifted and amplified thousands of times to the left before using integer fixed-point numbers to perform division operations to improve system response time. This media allocation ratio coefficient is essentially a dynamic scaling factor reflecting the "supply-demand ratio".

[0066] Furthermore, after extracting the scaling reference, the microprocessor continues to perform item-by-item allocation calculations. Specifically, the original target heating demand and target humidification demand are fed into a multiplier in parallel and multiplied by the media allocation ratio coefficient, respectively. The physical significance of this step is that when the total media storage is insufficient to meet 100% of the demand, a strict proportional "reduction" is performed according to the relative weight ratio of the two initial demands, thereby calculating the theoretically actual quantity of physical fluid that the system can supply to both pipelines, and thus obtaining the corrected heating volume value and corrected humidification volume value.

[0067] Furthermore, to bridge the control gap between the fluid volume in the digital domain and the electromechanical angle in the physical domain, the main control chip calls the addressing and table lookup subroutine in the ROM. By consulting a preset flow-angle mapping table, it converts the corrected heating volume value into a corresponding heating diversion angle value that the controller can recognize, and converts the corrected humidification volume value into a corresponding humidification diversion angle value. The technical solutions for implementing this table lookup mapping include: the first solution is a one-dimensional discrete piecewise mapping table based on an arithmetic sequence. The processor directly retrieves the nearest neighbor calibration angle using a step-by-step comparison method, suitable for ordinary valves where response speed is more important than accuracy; the second preferred solution uses a two-dimensional continuous mapping table with a linear interpolation algorithm. This table can automatically calculate a smoothly compensated intermediate angle value between two discrete calibration points based on volume differences, thereby avoiding the nonlinear error of the "mechanical dead zone" in three-way valves at low flow rates. It should be noted that the specific constant sequence corresponding to flow rate and angle within the above mapping table can be obtained and written into the configuration through factory calibration on a fluid dynamics test bench for the selected specific model of regulating valve; this is not limited here.

[0068] Furthermore, through assignment statements, the microprocessor directly sets and confirms the final mapped heating diversion angle value as the heating pipeline allocation opening parameter, and simultaneously sets the humidification diversion angle value as the humidification pipeline allocation opening parameter. Utilizing the aforementioned closed-loop logic circuit—from demand-driven, dynamic proportional coefficient segmentation to nonlinear lookup table correction—the system seamlessly transforms abstract macroscopic load demands into specific servo actuator position duty cycles, ensuring that limited waste heat and waste water resources can be strictly and accurately pushed into the reuse pipeline network.

[0069] It should be noted that the above embodiments of the apparatus are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0070] This embodiment also discloses an electronic device, as shown in the reference. Figure 3 The electronic device may include: at least one processor 301, at least one communication bus 302, user interface 303, network interface 304, and at least one memory 305.

[0071] The communication bus 302 is used to enable communication between these components.

[0072] The user interface 303 may include a display screen and a camera. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0073] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0074] The processor 301 may include one or more processing cores. The processor 301 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 305, and by calling data stored in memory 305. Optionally, the processor 301 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 301 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 301 and may be implemented as a separate chip.

[0075] The memory 305 may include random access memory (RAM) or read-only memory. Optionally, the memory 305 may include a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 305 may also be at least one storage device located remotely from the aforementioned processor 301. Figure 3As shown, the memory 305, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for a photoelectric and thermal co-driven three-constant environment regulation method.

[0076] exist Figure 3 In the electronic device shown, the user interface 303 is mainly used to provide an input interface for the user and to obtain the user input data; while the processor 301 can be used to call the application program stored in the memory 305, which is a photoelectric and photothermal co-driven three constant environment regulation method. When executed by one or more processors 301, the electronic device executes one or more methods as described in the above embodiments.

[0077] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0078] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings or direct couplings or communication connections may be through some service interfaces; indirect couplings or communication connections between apparatuses or units may be electrical or other forms.

[0079] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0080] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory 305 and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods in the various embodiments of this application. The aforementioned memory 305 includes various media capable of storing program code, such as a USB flash drive, external hard drive, magnetic disk, or optical disk.

[0081] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the disclosure in this specification. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for regulating a three-constant environment through direct drive of photoelectric and photothermal synergy, characterized in that, The method includes: The photovoltaic power data and solar thermal collection data at the current moment are collected synchronously by the pre-configured photovoltaic solar thermal panel. The photovoltaic power data is input into the preset battery module to perform fluctuation smoothing processing to obtain the electrical energy storage status parameters. The solar thermal collection data is input into the preset buffer water tank to perform buffer thermal storage processing to obtain the thermal energy storage status parameters. Real-time indoor environmental parameters are collected by temperature sensors, humidity sensors, and air quality sensors distributed in the target indoor area and at the return air vent. The indoor environmental parameters are then compared with preset target constant parameters to generate the current system load demand data. Based on the electrical energy storage status parameters, the thermal energy storage status parameters, and the system load demand data, an energy dispatch command is generated. According to the energy allocation command, constant temperature regulation, constant humidity regulation and constant oxygen regulation are executed respectively, and indoor constant three state monitoring parameters are collected in real time during the execution of constant temperature regulation, constant humidity regulation and constant oxygen regulation; Based on the indoor constant state monitoring parameters, the target working process currently in operation is determined, and the waste heat and cold recovery operation for the target working process is triggered, and the recovered waste heat and cold medium is returned to the preset feedback heat exchanger. Based on the state of the waste heat and cold medium in the feedback heat exchanger, and combined with the system load demand data, the waste heat and cold medium is allocated to the preset heating network and preset humidification network as needed for reuse. The step of determining the currently operating target process based on the indoor constant-state monitoring parameters and triggering a waste heat and cold recovery operation for the target process, and returning the recovered waste heat and cold medium to a preset feedback heat exchanger, includes: The operating condition feature extraction operation is performed on the indoor constant three state monitoring parameters to generate a real-time operating condition feature vector; The real-time operating condition feature vector is matched and compared with the preset system link feature library to determine the target working link that is currently running; Generate a corresponding recovery trigger command based on the target working step, and open a preset medium recovery valve based on the recovery trigger command; The waste heat and cold recovery operation is performed on the target working process through the medium recovery valve to extract the waste heat and cold medium. Drive the preset reflux booster pump to rotate and transport the waste heat and waste cooling medium along the preset guide pipeline to the feedback heat exchanger; The step of matching and comparing the real-time operating condition feature vector with a preset system component feature library to determine the currently running target operating component includes: Retrieve multiple pre-stored benchmark feature vectors and associated feature labels from the preset system feature library; The real-time operating condition feature vector is compared with multiple sets of reference link feature vectors to calculate the vector distance, resulting in multiple sets of feature distance values. The multiple sets of feature distance values ​​are sorted according to the numerical increment rule, and the candidate feature distance value with the smallest value is selected. Extract the process identification label associated with the distance value of the candidate feature, and confirm the process identification label as the target working process; The step of allocating the waste heat and cold medium to a preset heating network and a preset humidification network for reuse, based on the state of the waste heat and cold medium stored in the feedback heat exchanger and in conjunction with the system load demand data, includes: The real-time inventory value and real-time medium temperature value inside the feedback heat exchanger are obtained by pre-set liquid level sensor and temperature sensor respectively, and the real-time inventory value and the real-time medium temperature value are combined to determine the state of the waste heat and waste cold medium. The system load demand data is parsed and extracted to separate the target heating demand and the target humidification demand. Based on the target heating demand, the target humidification demand, and the real-time inventory value, an allocation calculation is performed to generate heating pipeline allocation opening parameters and humidification pipeline allocation opening parameters. According to the opening parameters of the heating pipeline and the opening parameters of the humidification pipeline, the preset three-way diversion valve is adjusted to form the corresponding heating flow channel and humidification flow channel; The waste heat and cold medium is introduced into the heat dissipation coil of the heating network through the heating channel to perform heat exchange and dissipation operation, and the waste heat and cold medium is introduced into the atomizing terminal of the humidification network through the humidification channel to perform water evaporation and spraying operation, so as to perform the reuse operation. The step of performing allocation calculations based on the target heating demand, the target humidification demand, and the real-time inventory value to generate heating pipeline allocation opening parameters and humidification pipeline allocation opening parameters includes: The total load demand is obtained by summing the target heating demand and the target humidification demand. Divide the real-time inventory value by the total load demand value to calculate the medium allocation ratio coefficient. The target heating demand and the target humidification demand are respectively multiplied by the medium distribution ratio coefficient to obtain the corrected heating volume value and the corrected humidification volume value. The corrected heating volume value is converted into the corresponding heating diversion angle value by using a preset flow angle mapping table, and the corrected humidification volume value is converted into the corresponding humidification diversion angle value. The heating diversion angle value is set as the opening parameter of the heating pipeline, and the humidification diversion angle value is set as the opening parameter of the humidification pipeline. The generation of energy dispatch instructions based on the electrical energy storage status parameters, the thermal energy storage status parameters, and the system load demand data includes: The energy storage state parameters are compared with a preset power safety judgment threshold, and the overflow power data exceeding the power safety judgment threshold is extracted. The thermal energy storage state parameters are compared with a preset thermal safety judgment threshold, and the overflow heat data exceeding the thermal safety judgment threshold is extracted. The system load demand data is decomposed into constant temperature load demand parameters, constant humidity load demand parameters, and constant oxygen load demand parameters. The overflow power data, the overflow heat data, the constant temperature load demand parameters, the constant humidity load demand parameters, and the constant oxygen load demand parameters are input into a preset energy allocation decision model, and the corresponding energy allocation weight coefficients are output through the energy allocation decision model. The energy allocation command is generated by performing instruction encoding operation based on the energy allocation weight coefficient. The process of performing constant temperature regulation, constant humidity regulation, and constant oxygen regulation according to the energy allocation command includes: The energy allocation command is processed by signal decoding to extract the target values ​​for constant temperature control, constant humidity control, and constant oxygen control. The indoor environmental parameters are classified and analyzed to separate the real-time indoor temperature, real-time indoor humidity, and real-time indoor oxygen concentration. The difference between the constant temperature control target value and the real-time indoor temperature value is calculated to obtain the temperature deviation adjustment amount, and the pre-configured variable frequency heat pump host is controlled to perform the constant temperature adjustment according to the temperature deviation adjustment amount. The difference between the constant humidity control target value and the real-time indoor humidity value is calculated to obtain the humidity deviation adjustment amount, and the preset steam generator is triggered to perform the constant humidity adjustment according to the humidity deviation adjustment amount. The difference between the constant oxygen control target value and the real-time indoor oxygen concentration value is calculated to obtain the fresh air supply deviation, and the preset total heat exchange exhaust device is driven to perform the constant oxygen regulation according to the fresh air supply deviation.

2. An electronic device, characterized in that, It includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions. The user interface and the network interface are both used to communicate with other devices. The processor is used to execute the instructions stored in the memory so that the electronic device performs the photoelectric and photothermal synergistic direct drive three-constant environment regulation method as described in claim 1.

3. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed, perform the photoelectric and photothermal synergistic direct drive three-constant environment regulation method as described in claim 1.

4. A computer program product, characterized in that, When the computer program product is run on an electronic device, the electronic device performs the photoelectric and photothermal synergistic direct drive three-constant environment regulation method as described in claim 1.

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