Medical building energy-saving system
By designing environmental collection devices and building energy-saving devices in the medical rescue training base, and optimizing and controlling energy consumption equipment based on user characteristics, the problem of poor energy saving effect of existing medical energy-saving systems is solved, and more efficient energy utilization and optimized energy saving effect is achieved.
Patent Information
- Application Number
- CN202510195987.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-21
- Publication Date
- 2025-05-30
AI Technical Summary
The energy-saving system of the existing medical rescue training base fails to effectively combine user characteristics and the diversified needs of special groups, resulting in poor energy-saving effects.
A medical building energy-saving system is designed, including environmental acquisition devices and building energy-saving devices. The environmental acquisition device collects environmental data through a temperature sensor, a light illuminance sensor, a carbon dioxide concentration meter and a pressure collector, and sends the data to the building energy-saving device through a data processing and transmission module. The building energy-saving device uses parameter processing modules to optimize the energy consumption equipment in combination with user characteristics, and optimizes and controls it through the energy equipment status intelligent control module.
Through the synergy between multiple modules, it can meet users' special needs and energy-saving needs at the same time, achieve more efficient energy utilization and optimized energy-saving effects, meet multiple needs such as teaching, practical training, emergency rescue in medical buildings, and conform to the concept of green environmental protection and sustainable development.
Smart Images
Figure CN120065730A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of building energy conservation, and particularly to a medical building energy conservation system. Background Art
[0002] With the increasingly severe global climate change and environmental problems, energy conservation and emission reduction have become an important trend in the development of all industries. In the field of medical rescue training, medical rescue training bases are important places to improve the professional skills of medical rescue personnel and enhance their ability to respond to emergencies. These bases usually include simulated first-aid scenes, simulated operating rooms, medical simulation teaching systems, etc., enabling medical rescue personnel to make quick and accurate judgments and responses in a real environment. Their building systems not only need to meet the needs of teaching, training, and emergency rescue, but also need to actively respond to the call for energy conservation and emission reduction, contributing to the construction of a green, low-carbon, and sustainable society.
[0003] However, there are still some challenges in the construction of medical rescue training bases at present: how to further improve the energy conservation effect and reduce the operating cost; how to ensure that the normal progress of teaching and training is not affected while saving energy and reducing emissions. Existing patent documents have made corresponding solutions to the challenges faced in the construction of the bases. For example, the patent document with the publication number C108984298 discloses a building energy conservation system including a building energy conservation device and an environment acquisition device. The environment acquisition device is arranged in the building to collect the environmental parameters in the building, and can control the energy-consuming devices in the building according to the mathematical model of the acquired environmental parameters and state parameters and the algorithm relationship. However, the characteristics of users and the diverse needs of special groups are not combined in this solution, and the energy conservation effect of medical rescue training bases is poor.
[0004] Therefore, it is necessary to provide a medical building energy conservation system that can solve the problems that the existing medical energy conservation system does not combine the characteristics of users and the diverse needs of special groups and has a poor energy conservation effect. Summary of the Invention
[0005] The purpose of the present invention is to provide a medical building energy conservation system that can solve the problems that the existing medical energy conservation system does not combine the characteristics of users and the diverse needs of special groups and has a poor energy conservation effect.
[0006] The present invention is implemented as follows:
[0007] A medical building energy-saving system includes an environmental acquisition device and a building energy-saving device; the environmental acquisition device includes an environmental data acquisition module, a data processing module, and a data transmission module; the building energy-saving device includes a signal receiving module, an energy device status monitoring module, a parameter processing module, and an energy device status intelligent control module; the environmental data acquisition module is used to collect the original environmental data information in the medical training base and send the original environmental data information to the data processing module; the data processing module is used to convert the original environmental data information into a digital signal and send it to the signal receiving module through the data transmission module; the signal receiving module is used to receive the original environmental data information after digital processing and send it to the parameter processing module; the energy device status monitoring module is installed on the energy-consuming devices in the medical training base, and after collecting its status parameters, it sends the status parameters to the parameter processing module; the parameter processing module is used to optimize the parameters of the energy-consuming devices in the medical training base in combination with the characteristic requirements of specific users in the medical training base and send the control instructions to the energy device status intelligent control module; the energy device status intelligent control module is connected to the energy-consuming devices in the medical training base and is used to optimize the control of the energy-consuming devices according to the optimized parameters.
[0008] The environmental data acquisition module described above includes a temperature sensor, an illuminance sensor, a carbon dioxide concentration meter, and a barometric pressure collector installed in the medical training base.
[0009] The parameter processing module is equipped with an intelligent control algorithm and a user characteristic analysis module. The intelligent control algorithm is used to establish a mathematical model through neural network control technology, calculate the relationship between the original environmental data information after digital processing and the status parameters of the energy-consuming devices in the medical training base, and based on this relationship, combined with the environmental indicators of human comfort, analyze the characteristic requirements of specific special users in the medical training base through the user characteristic analysis module, calculate the optimized parameters of the energy-consuming devices, and generate control instructions, so as to be able to optimize the control of the energy-consuming devices in the medical training base through the energy device status intelligent control module based on the control instructions.
[0010] The specific special users described above include the user's age, condition (i.e., health status), and activity ability. The characteristic requirements of specific special users include the specific requirements of this user for environmental comfort.
[0011] The control method of the medical building energy-saving system includes the following steps:
[0012] Step 1: The environmental acquisition device continuously monitors the environmental parameters, and the building energy-saving device continuously monitors the operating status of the energy-consuming devices.
[0013] Step 2: The parameter processing module collects the acquired data, including the original environmental data information collected by temperature sensors, illuminance sensors, carbon dioxide concentration meters, and barometric pressure collectors and digitized by the data processing module, as well as the status parameters of energy-consuming devices collected by the energy device status monitoring module;
[0014] Step 3: The parameter processing module periodically analyzes the collected data and generates control instructions. The energy device status intelligent control module optimally controls the energy-consuming devices in the medical training base through the control instructions;
[0015] Step 4: Evaluate the energy-saving effect of the medical building energy-saving system and the compliance of the environmental comfort level;
[0016] Step 5: Analyze whether the original environmental data information meets the comfort and safety requirements of special users such as patients. If so, execute Step 6; if not, return to Step 2;
[0017] Step 6: Output the comfort performance and energy-saving effect of the medical building energy-saving system.
[0018] The mathematical model for the energy device status intelligent control module to analyze the energy-saving effect of the medical building energy-saving system is a medical energy-saving control model based on intelligent control algorithms and mechanism analysis. The algorithm relationship based on intelligent control is:
[0019]
[0020] Among them, E is the output of the energy consumption control model, representing the required energy consumption quality value; ΔP is the parameter change amount, reflecting the change of environmental parameters or device status; α is the time factor, considering the influence of time on energy consumption and reflecting the change of energy consumption demand in different time periods; N is the total number of people in the base, affecting the energy consumption demand; S is the area of the base, affecting the energy distribution and utilization; θ is the user characteristic parameter value, considering the personalized needs of special users; δ is the adjustment factor, used to adjust the energy consumption quality value according to the actual situation; k1 and k2 are the weight factors.
[0021] Compared with the prior art, the present invention has the following beneficial effects:
[0022] 1. Since the present invention is provided with an environment collection device and a building energy-saving device, it can continuously collect the environmental parameters in the medical training base through the environment collection device, and through the building energy-saving device, intelligently control the operation mode and parameter settings of the energy-consuming equipment in the medical training base in combination with the characteristic needs of users and the diverse needs of special groups. Through the collaborative action of multiple modules, it can simultaneously meet the special needs of users and the need for energy conservation, provide the optimal medical building energy-saving optimization plan for the medical training base, achieve more efficient energy utilization and optimized energy-saving effects, and thus meet multiple needs such as teaching, training, and emergency rescue in medical buildings, conforming to the concepts of green environmental protection and sustainable development.
[0023] 2. Since the present invention is provided with a building energy-saving device, it can accurately calculate the relationship between environmental parameters and the operating state of energy-consuming equipment through the intelligent control algorithm of the parameter processing module and the mathematical model of the energy equipment state intelligent control module, so as to realize the refined control and optimized scheduling of energy-consuming equipment. Moreover, the parameter processing module introduces a user characteristic analysis module, which can optimize and adjust the energy-consuming equipment according to the specific user characteristics and special needs in the medical training base, and achieve effective and accurate control of illumination, temperature, gas concentration, etc., to achieve the comprehensive goals of energy conservation, comfort, safety, and environmental protection.
[0024] 3. The present invention performs real-time optimized scheduling of energy-consuming equipment through continuous monitoring of environmental parameters and the operating state of energy-consuming equipment, can significantly improve the efficient utilization rate of energy, and dynamically adjusts the operation mode and energy consumption of energy-consuming equipment in combination with environmental parameters and user characteristics, so as to minimize energy consumption and optimize the energy-saving effect to the greatest extent.
[0025] 4. The present invention not only applies intelligent control technology to the field of building energy conservation, but also collects environmental parameters and energy-consuming equipment state parameters in the medical training base, and combines mathematical modeling, intelligent control algorithms, and user characteristic analysis according to the special needs of the medical building base to achieve more efficient energy utilization and optimized energy-saving effects, so as to provide more reliable and lasting support for medical work. BRIEF DESCRIPTION OF THE DRAWINGS
[0026] Figure 1 is the structural block diagram of the medical building energy-saving system of the present invention;
[0027] Figure 2 is the structural block diagram of the environment collection device in the medical building energy-saving system of the present invention;
[0028] Figure 3 is the flow chart of the control method of the medical building energy-saving system of the present invention.
[0029] In the figure, 1 is an environmental acquisition device, 11 is an environmental data acquisition module, 111 is a temperature sensor, 112 is a light intensity sensor, 113 is a carbon dioxide concentration meter, 114 is a barometric pressure collector, 12 is a data processing module, 13 is a data transmission module, 2 is a building energy saving device, 21 is a signal receiving module, 22 is an energy equipment status monitoring module, 23 is a parameter processing module, 24 is an energy equipment status intelligent control module, and 3 is an energy consumption equipment. Detailed implementation mode
[0030] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.
[0031] Please refer to the attached Figure 1 As shown in the figure, a medical building energy saving system includes an environmental acquisition device 1 and a building energy saving device 2; the environmental acquisition device 1 includes an environmental data acquisition module 11, a data processing module 12 and a data transmission module 13; the building energy saving device 2 includes a signal receiving module 21, an energy equipment status monitoring module 22, a parameter processing module 23 and an energy equipment status intelligent control module 24; the environmental data acquisition module 11 is used to collect the original environmental data information in the medical training base and send the original environmental data information to the data processing module 12; the data processing module 12 is used to convert the original environmental data information into a digital signal and send it to the signal receiving module 21 through the data transmission module 13; the signal receiving module 21 is used to receive the original environmental data information after digital processing and send it to the parameter processing module 23; the energy equipment status monitoring module 22 is installed on the energy consumption equipment 3 in the medical training base, and after collecting its status parameters, sends the status parameters to the parameter processing module 23; the parameter processing module 23 is used to optimize the parameters of the energy consumption equipment 3 in the medical training base in combination with the specific user's characteristic requirements in the medical training base and send a control instruction to the energy equipment status intelligent control module 24; the energy equipment status intelligent control module 24 is connected to the energy consumption equipment 3 in the medical training base and is used to optimize the control of the energy consumption equipment 3 according to the optimized parameters.
[0032] Preferably, the data transmission module 13 and the signal receiving module 21 can adopt a wired data transmission and receiving module or a wireless data transmission and receiving module, and the data transmission method can be adaptively selected according to the actual use requirements to ensure the complete and safe transmission of data. The data processing module 12 can adopt an analog-to-digital conversion module, which is used to convert the collected analog signal into a unified digital signal to facilitate the signal processing of the building energy saving device 2.
[0033] Preferably, the building energy-saving device 2 is used to control the energy-consuming devices 3 in the medical training base to automatically adjust the operation modes and parameters of the energy-consuming devices 3. During the optimization and adjustment, water and electricity should be separated to ensure its environmental protection and safety, and potential safety accidents such as fires, explosions, and electric shocks should be prevented; the monitoring accuracy of the main operation parameters of each energy-consuming device 3, such as temperature, pressure, flow rate, electricity consumption, and energy, by the energy device status monitoring module 22 is ≤2%; the energy device status intelligent control module 24 realizes automatic optimization adjustment and control according to the comfort of the human body and the special user needs of patients, etc., to avoid unnecessary energy consumption.
[0034] Preferably, the energy-consuming devices 3 in the medical training base include devices that require energy consumption and energy-saving optimization, such as air conditioners and lighting equipment. The energy device status monitoring module 22 and the energy device status intelligent control module 24 can be installed and connected to the controllers of the energy-consuming devices 3, which is convenient for the energy device status monitoring module 22 to collect status parameters such as temperature, humidity, pressure, brightness, flow rate, and electricity consumption of the energy-consuming devices 3. For different energy-consuming devices 3, the status parameters characterizing energy consumption are also different, and corresponding status parameters can be collected according to different energy-consuming devices 3, which is also convenient for the energy device status intelligent control module 24 to optimize the control of the energy-consuming devices 3.
[0035] In addition, for special situations or emergencies, failures of energy-consuming devices 3, and extreme weather, the medical building energy-saving system can be configured with corresponding emergency treatment mechanisms according to actual needs to ensure the comfort and safety of users. The emergency treatment mechanism does not fall within the protection scope of the present invention and will not be elaborated here.
[0036] Please refer to the appendix Figure 2 , the described environmental data acquisition module 11 includes a temperature sensor 111, a light intensity sensor 112, a carbon dioxide concentration meter 113, and a barometric pressure collector 114 installed in the medical training base.
[0037] The installation positions and quantities of the temperature sensor 111, the light intensity sensor 112, the carbon dioxide concentration meter 113, and the barometric pressure collector 114 can be adaptively selected according to actual acquisition needs to meet multiple needs such as teaching, training, and emergency rescue in the medical training base.
[0038] Preset the parameters of the acquisition frequency and acquisition range for the temperature sensor 111, the light intensity collector 112, the carbon dioxide concentration meter 113, and the barometric pressure collector 114, so that the temperature sensor 111 can regularly collect the environmental stability in the medical training base, the light intensity collector 112 can regularly collect the environmental light intensity in the medical training base, the carbon dioxide concentration meter 113 can regularly collect the carbon dioxide concentration in the air in the medical training base, and the barometric pressure collector 114 can regularly collect the environmental barometric pressure in the medical training base.
[0039] A temperature sensor with a corresponding model and specification can be selected according to the ambient temperature requirement. The key performance indicators of the temperature sensor 111 include: measurement range, accuracy, and response time. Preferably, the measurement range of the temperature sensor 111 is: -40°C to +125°C; accuracy: ±0.5°C; response time: usually between 50 milliseconds and 85 milliseconds.
[0040] A light intensity sensor with a corresponding model and specification can be selected according to the ambient light intensity requirement. The key performance indicators of the light intensity collector 112 include: measurement range, spectral response, and accuracy. Preferably, the measurement range of the light intensity collector 112 is: from 5 Lux to 10,000 Lux. Spectral response: Usually calibrated according to light of different wavelengths to meet the requirements of specific applications. Accuracy: The typical accuracy reaches 3% under low light.
[0041] A carbon dioxide concentration meter with a corresponding model and specification can be selected according to the carbon dioxide concentration requirement. The key performance indicators of the carbon dioxide concentration meter 113 include: measurement range, accuracy, and response time. Preferably, the measurement range of the carbon dioxide concentration meter 113 is: from 100 ppm (parts per million) to 5,000 ppm; accuracy: typically between 3 ppm and 85 ppm; response time: within 30 s.
[0042] A barometric pressure collector with a corresponding model and specification can be selected according to the ambient barometric pressure requirement. The key performance indicators of the barometric pressure collector 114 include: measurement range, accuracy, and temperature influence. Preferably, the measurement range of the barometric pressure collector 114 is: from 100 hPa to 2,000 hPa; accuracy: in the range of 1 hPa; the accuracy of the barometric pressure collector is usually affected by temperature changes, and temperature compensation is performed to improve accuracy.
[0043] Preferably, the environmental data acquisition module 11 can also be set with a humidity sensor, a wind speed sensor, etc. according to actual usage requirements to collect parameters such as environmental humidity and wind speed in the medical training base.
[0044] Preferably, a preset digital algorithm is installed in the data processing module 12, and the digital algorithm is used to convert the collected temperature parameters, light intensity parameters, carbon dioxide concentration parameters, and barometric pressure parameters into digital signals.
[0045] The parameter processing module 23 is equipped with an intelligent control algorithm and a user feature analysis module. The intelligent control algorithm is used to establish a mathematical model through technologies such as neural network control, calculate statistical values, means, variances, etc. of environmental parameters, and based on this, calculate the relationship between the original environmental data information after digital processing and the state parameters of the energy-consuming equipment 3 in the medical training base. According to this relationship, combined with the environmental indicators of human comfort, the user feature analysis module conducts feature demand analysis on specific special users in the medical training base. According to the relationship between the characteristics of the energy-consuming equipment 3 and the environmental parameters, the features with the greatest impact on energy consumption are selected and extracted, the optimized parameters of the energy-consuming equipment 3 are calculated, and a control instruction is generated, so that the energy-consuming equipment 3 in the medical training base can be optimized and controlled based on the control instruction through the energy equipment status intelligent control module 24.
[0046] Preferably, historical data can be used to train the mathematical model and adjust the parameters of the mathematical model to improve the prediction accuracy. Verify and optimize the mathematical model: Use the verification set data to verify the prediction ability of the mathematical model, and evaluate the accuracy and generalization ability of the mathematical model. Adjust the structure and parameters of the mathematical model according to the verification results to optimize the performance of the mathematical model. Apply the optimized mathematical model to real-time data to predict the best operation mode and parameter settings of the energy-consuming equipment 3. According to the prediction results, automatically adjust the operation of the energy-consuming equipment 3 through the energy equipment status intelligent control module 24. By continuously monitoring the prediction effect of the mathematical model and the operation status of the energy-consuming equipment 3, and according to the actual situation and user feedback, regularly adjust and optimize the mathematical model.
[0047] Using neural network technology to build a mathematical model is a conventional processing method in this field. The input of the mathematical model is the original environmental data information received by the signal receiving module 21 and the state parameters of the energy-consuming equipment 3 collected by the energy equipment status monitoring module 22, and the output of the mathematical model is the control instruction for the energy-consuming equipment 3.
[0048] The specific special users mentioned above include the user's age, condition (i.e., health status), activity ability, etc. The feature demands of specific special users include the specific demands of this user for environmental comfort. For example: For the elderly, they need a relatively higher environmental temperature, a relatively lower carbon dioxide concentration in the air, a relatively higher illuminance, etc.
[0049] Please refer to Appendix Figure 1 to Appendix Figure 3 , and the control method of the medical building energy-saving system includes the following steps:
[0050] Step 1: The environmental acquisition device 1 continuously monitors environmental parameters, and the building energy-saving device 2 continuously monitors the operation status of the energy-consuming equipment 3.
[0051] Among them, the continuous monitoring of environmental parameters is achieved through the continuous monitoring of the temperature sensor 111, the illuminance sensor 112, the carbon dioxide concentration meter 113, and the air pressure collector 114. The continuous monitoring of the operating status of the energy-consuming device 3 is achieved through the continuous monitoring of the energy device status monitoring module 22, and its monitoring period can be adaptively set according to actual needs.
[0052] Step 2: The parameter processing module 23 collects the collected data, including the original environmental data information collected by the temperature sensor 111, the illuminance sensor 112, the carbon dioxide concentration meter 113, and the air pressure collector 114 and digitized by the data processing module 12, and the status parameters of the energy-consuming device 3 collected by the energy device status monitoring module 22.
[0053] After the parameter processing module 23 collects the collected data, it preprocesses the data, cleans the collected data, and removes outliers and noise. Removing outliers and noise is a conventional means of data preprocessing in this field and will not be elaborated here. Then, it performs format conversion on the data, converting the data into a format suitable for input into the mathematical model for convenient standardization processing.
[0054] Step 3: The parameter processing module 23 regularly analyzes the collected data and generates control instructions. The energy device status intelligent control module 24 optimally controls the energy-consuming device 3 in the medical training base through the control instructions.
[0055] Combining the environmental indicators of human comfort (for example: the environmental temperature range for human comfort is 22 - 26 °C, the humidity range is 50 - 60%, etc.) and the characteristic requirements of users (the condition of patients, activity ability, etc.), comparing them with the original environmental data information is used to evaluate the compliance of the environmental comfort in the medical training base, so that the parameter processing module 23 can generate control instructions for the energy-consuming device 3 according to the compliance situation.
[0056] For example: when the collected original environmental temperature is lower than the environmental temperature requirement for human comfort, the environmental comfort in the medical training base does not meet the standard. The parameter processing module 23 generates a control instruction to increase the temperature and sends it to the energy device status intelligent control module 24 installed on the air conditioner controller, so that the energy device status intelligent control module 24 controls the air conditioner to increase the temperature and lower the wind speed, etc., and adjusts the actual environmental temperature to within the environmental temperature requirement range for human comfort, thereby realizing the optimization of the environmental temperature. Furthermore, different environmental optimization functions can be realized according to different environmental parameter requirements to ensure energy conservation while meeting the user's needs for environmental comfort.
[0057] Step 4: Evaluate the energy-saving effect and the compliance of environmental comfort of the medical building energy-saving system.
[0058] The compliance of the environmental comfort level can be obtained through the analysis of the parameter processing module 23, and the energy-saving effect of the medical building energy-saving system can be obtained through the analysis of the energy equipment status intelligent control module 24.
[0059] The energy equipment status intelligent control module 24 first preprocesses the data, including removing outliers, scaling the data to the interval [0,1], and extracting features that have a significant impact on energy consumption; feature selection, using correlation analysis and recursive feature elimination (RFE) methods to select important features; constructing new features, including the moving average of environmental parameters and the operating duration of energy-consuming equipment.
[0060] The mathematical model for the energy equipment status intelligent control module 24 to analyze the energy-saving effect of the medical building energy-saving system is a medical energy-saving control model based on intelligent control algorithms and mechanism analysis. The algorithm relationship based on intelligent control is:
[0061]
[0062] Among them, E is the output of the energy consumption control model, representing the required energy consumption quality value; ΔP is the parameter change amount, reflecting the changes in environmental parameters or equipment status; α is the time factor, considering the impact of time on energy consumption and reflecting the changes in energy consumption demand in different time periods; N is the total number of people in the base, affecting energy consumption demand; S is the area of the base, affecting energy distribution and utilization; θ is the user characteristic parameter value, considering the personalized needs of special users; δ is the adjustment factor, used to adjust the energy consumption quality value according to the actual situation; k1 and k2 are weight factors, adjusted according to specific usage scenarios and system requirements.
[0063] The mathematical model of the energy equipment status intelligent control module 24 selects the deep learning model LSTM to process time series data and selects the ensemble learning method random forest to process non-time series data. The mathematical model is trained using historical data, and the parameters of the mathematical model are adjusted through cross-validation. The prediction results of the mathematical model are integrated using stacking to improve prediction accuracy.
[0064] The mathematical model of the energy equipment status intelligent control module 24 implements an online learning mechanism, enabling the mathematical model to be continuously updated according to new data. An adaptive learning rate adjustment strategy is introduced, including learning rate decay and early stopping. Multiple optimization goals are defined, such as minimizing energy consumption, maximizing comfort, and extending equipment life. The multi-objective optimization algorithm, NSGA-II (Non-dominated Sorting Genetic Algorithm II), is used to find the optimal solution.
[0065] Finally, the energy consumption control system of the medical training base is modeled as a Markov decision process (MDP). The deep reinforcement learning algorithm A3C is used to learn the optimal energy consumption control strategy. A simulation environment is constructed to simulate different environmental conditions and user requirements, and the performance and robustness of the mathematical model of the intelligent control module 24 for the energy equipment status are verified. At the same time, a user feedback mechanism is designed to collect the comfort feedback of users in the medical training base, and the parameters of the mathematical model and the control strategy are adjusted according to the user feedback. A monitoring system is implemented to regularly evaluate the performance and effectiveness of the mathematical model. The mathematical model is maintained and updated according to the monitoring results.
[0066] Based on the analysis results of the environmental comfort compliance of the parameter processing module 23 and the feedback of the user characteristics module, the intelligent control module 24 for the energy equipment status performs intelligent control on the operation mode and parameter settings of the energy consumption equipment 3 through the mathematical model. The mathematical model of the intelligent control module 24 for the energy equipment status is a conventional analysis and control model method in the medical building energy-saving system, and the energy-saving optimization control process is not described in detail here.
[0067] According to the analysis of the energy-saving effect and the environmental comfort compliance, the intelligent control algorithm of the parameter processing module 23 and the mathematical model of the intelligent control module 24 for the energy equipment status can be optimized and adjusted to improve the performance and energy-saving effect of the medical building energy-saving system.
[0068] Step 5: Analyze whether the original environmental data information meets the comfort and safety requirements of special users such as patients. If so, execute Step 6; if not, return to Step 2.
[0069] If the environmental parameters still do not meet the standards after the optimized control of the intelligent control module 24 for the energy equipment status, return to Step 2 and repeat the intelligent optimization control until the environmental parameters meet the standards. If the environmental parameters meet the standards after the optimized control of the intelligent control module 24 for the energy equipment status, exit and wait for the parameter collection in the next cycle for the next optimization control.
[0070] Step 6: Output the comfort performance and energy-saving effect of the medical building energy-saving system.
[0071] The output comfort performance may include the compliance of the environmental temperature, the compliance of the carbon dioxide concentration, etc., and the energy-saving effect may include a 5% reduction in energy consumption, etc. The output content can be adaptively set according to the actual usage requirements.
[0072] The above are only the preferred embodiments of the present invention and are not used to limit the protection scope of the invention. Therefore, any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.
Claims
1. A medical building energy-saving system, characterized by: The invention comprises an environment collection device (1) and a building energy-saving device (2); the environment collection device (1) comprises an environment data collection module (11), a data processing module (12) and a data transmission module (13); the building energy-saving device (2) comprises a signal receiving module (21), an energy equipment status monitoring module (22), a parameter processing module (23) and an energy equipment status intelligent control module (24); the environment data collection module (11) is used to collect original environment data information in the medical training base, and send the original environment data information to the data processing module (12); the data processing module (12) is used to convert the original environment data information into a digital signal, and send it to the signal receiving module (21) through the data transmission module (13); The signal receiving module (21) is used to receive the original environmental data information after digital processing, and send it to the parameter processing module (23); the energy equipment status monitoring module (22) is installed on the energy consumption equipment (3) in the medical training base, and collects its status parameters and sends the status parameters to the parameter processing module (23); the parameter processing module (23) is used to optimize the parameters of the energy consumption equipment (3) in the medical training base in combination with the characteristic requirements of specific users in the medical training base, and send the control instructions to the energy equipment status intelligent control module (24); the energy equipment status intelligent control module (24) is connected to the energy consumption equipment (3) in the medical training base, and is used to optimize the energy consumption equipment (3) according to the optimized parameters.
2. The medical building energy saving system according to claim 1 is characterized in that: The environmental data acquisition module (11) comprises a temperature sensor (111), a light intensity sensor (112), a carbon dioxide concentration meter (113) and an air pressure collector (114) installed in the medical training base.
3. The medical building energy saving system according to claim 2 is characterized in that: The parameter processing module (23) is equipped with an intelligent control algorithm and a user characteristic analysis module. The intelligent control algorithm is used to establish a mathematical model through a neural network control technology to calculate the relationship between the original environmental data information after digital processing and the state parameters of the energy-consuming equipment (3) in the medical training base. Based on this relationship and in combination with the environmental index of human comfort, the user characteristic analysis module performs characteristic demand analysis on specific special users in the medical training base, calculates the optimized parameters of the energy-consuming equipment (3), and generates control instructions, so that the energy-consuming equipment (3) in the medical training base can be optimized and controlled based on the control instructions through the energy equipment state intelligent control module (24).
4. The medical building energy saving system according to claim 3 is characterized by: The specific special user includes the user's age, condition, ie, health status, and mobility. The characteristic needs of the specific special user include the user's specific needs for environmental comfort.
5. The medical building energy saving system according to claim 4 is characterized in that: The control method of the medical building energy-saving system comprises the following steps: Step 1: The environmental collection device (1) continuously monitors environmental parameters, and the building energy-saving device (2) continuously monitors the operating status of the energy-consuming equipment (3); Step 2: The parameter processing module (23) collects data, including the original environmental data information collected by the temperature sensor (111), the light intensity sensor (112), the carbon dioxide concentration meter (113) and the air pressure collector (114) and digitized by the data processing module (12), and the state parameters of the energy consumption equipment (3) collected by the energy equipment state monitoring module (22); Step 3: The parameter processing module (23) regularly analyzes the collected data and generates control instructions, and the energy equipment state intelligent control module (24) optimizes and controls the energy consumption equipment (3) in the medical training base through the control instructions; Step 4: Evaluate the energy-saving effect and environmental comfort level of the medical building energy-saving system; Step 5: Analyze whether the original environmental data information meets the comfort and safety requirements of special users such as patients. If so, execute step 6; if not, return to step 2; Step 6: Output the comfort performance and energy-saving effect of the medical building energy-saving system.
6. The medical building energy saving system according to claim 5 is characterized in that: The mathematical model used by the energy equipment status intelligent control module (24) to analyze the energy-saving effect of the medical building energy-saving system is a medical energy-saving control model based on intelligent control algorithms and mechanism analysis. The algorithm relationship based on intelligent control is: Among them, E is the output of the energy consumption control model, representing the required energy consumption quality value; ΔP is the parameter change, reflecting the change of environmental parameters or equipment status; α is the time factor, considering the impact of time on energy consumption, reflecting the change of energy consumption demand in different time periods; N is the total number of people in the base, affecting the energy consumption demand; S is the area of the base, affecting energy distribution and utilization; θ is the user characteristic parameter value, considering the personalized needs of special users; δ is the adjustment factor, used to adjust the energy consumption quality value according to actual conditions; k1 and k2 are weight factors.