Auxiliary hospital space design method and device based on building energy consumption model

Abstract

The present invention provides an auxiliary hospital space design method and device based on a building energy consumption model, which belongs to the field of energy-saving building technology. The auxiliary hospital space design method based on a building energy consumption model of the present invention can more comprehensively evaluate the building energy consumption by acquiring basic data of surrounding target hospitals, comprehensively considering the hardware and personnel configuration, patient flow and energy consumption data of the target hospital, and combining the design plan data of the hospital to be built. A building energy consumption model can be established based on actual data, and a building energy consumption model for the specific situation of the hospital to be built can be established, which can more accurately reflect the energy consumption characteristics and needs of the hospital, realize data-driven design optimization decisions, thereby reducing energy consumption on the basis of making more reasonable spatial layout adjustments and optimizations, improving energy utilization efficiency, and reducing resource waste.

Description

Technical Field

[0001] The present invention relates to the technical field of energy-saving buildings, and in particular to an auxiliary hospital space design method and device based on a building energy consumption model. Background Art

[0002] With the development of society, energy consumption is also increasing rapidly. In the context of carbon peak and carbon neutrality, hospitals, as public buildings with large populations, have a large demand for energy consumption. How to optimize hospital design and reduce energy consumption from the beginning of design is an important direction for future design work.

[0003] In the building energy consumption prediction model, existing cases often have extensive phenomena in data input, only considering the impact of seasonal time factors on energy consumption, which has a certain impact on the accuracy of the energy consumption prediction results and cannot accurately guide the energy-saving design of hospital buildings. Summary of the invention

[0004] The present invention provides an auxiliary hospital space design method and device based on a building energy consumption model, which is used to solve the defect in the prior art that hospital buildings cannot accurately consider energy-saving issues in the design stage, and achieve the effect of guiding the energy-saving design of hospital buildings according to energy consumption prediction.

[0005] The present invention provides an auxiliary hospital space design method based on a building energy consumption model, comprising:

[0006] Obtain basic data of target hospitals in the surrounding area of ​​the hospital to be built; the basic data includes hospital hardware and personnel configuration data, patient flow data, and energy consumption data;

[0007] Based on the initial design scheme data of the hospital to be built and the basic data, a building energy consumption model of the hospital to be built is obtained; the building energy consumption model is used to represent the energy consumption data of different design areas of the hospital to be built at different time periods;

[0008] Based on the building energy consumption model of the hospital to be built and the spatial layout information in the initial design plan data of the hospital to be built, updated building design plan data are obtained.

[0009] According to an auxiliary hospital space design method based on a building energy consumption model provided by the present invention, the building energy consumption model of the hospital to be built is obtained based on the initial design scheme data of the hospital to be built and the basic data, including:

[0010] Based on the basic data of the target hospital, the patient tidal characteristics of the target hospital are obtained; the patient tidal characteristics are used to represent the fluctuation and regularity of the number of patients in different areas of the hospital in different time periods;

[0011] Based on the patient tidal characteristics of the target hospital and the initial design plan data of the hospital to be built, obtaining predicted patient tidal characteristics of the hospital to be built;

[0012] Based on the predicted patient tide characteristics of the hospital to be built, a predicted behavior pattern of the hospital to be built is obtained; the predicted behavior pattern includes the use of medical staff and the turnover rate of inpatients;

[0013] Based on the predicted behavior pattern of the hospital to be built, the energy consumption data of the medical staff and inpatients of the hospital to be built in different design areas corresponding to the hospital to be built in different time periods are obtained to construct a building energy consumption model of the hospital to be built.

[0014] According to an auxiliary hospital space design method based on a building energy consumption model provided by the present invention, the building energy consumption model of the hospital to be built is obtained based on the initial design scheme data of the hospital to be built and the basic data, and further includes:

[0015] Obtain historical usage data of the target hospital's air conditioning and heating systems;

[0016] Associating the historical usage data with the temperature data and the patient tidal characteristics to obtain an energy consumption model of the air conditioning and heating system of the target hospital;

[0017] The energy consumption model of the air conditioning and heating systems of the target hospital is superimposed on the existing building energy consumption model to obtain an updated building energy consumption model.

[0018] According to an auxiliary hospital space design method based on a building energy consumption model provided by the present invention, the updated building design scheme data is obtained based on the building energy consumption model of the hospital to be built and the space layout information in the initial design scheme data of the hospital to be built, including:

[0019] Based on the building energy consumption model of the hospital to be built, obtaining energy consumption analysis results of the hospital to be built under different spatial layouts;

[0020] Based on the energy consumption analysis result, at least one of the spatial layout, HVAC equipment layout plan and energy consumption equipment control plan of the hospital to be built is adjusted to obtain updated architectural design plan data.

[0021] According to an auxiliary hospital space design method based on a building energy consumption model provided by the present invention, based on the energy consumption analysis result, at least one of the space layout of the hospital to be built, the HVAC equipment layout plan, and the control plan of the energy-consuming equipment is adjusted to obtain updated building design plan data, including:

[0022] Based on the energy consumption analysis results, energy consumption data of different areas are identified to determine areas where the hospital to be built is densely populated for a long period of time;

[0023] In the areas of the hospital to be built where there are dense crowds for long periods of time, the spatial layout is adjusted to increase the lighting area and the accommodation space, the number of HVAC equipment is increased, and the control scheme of the energy-consuming equipment is adjusted to control the HVAC equipment to increase the air output, so as to obtain updated architectural design scheme data.

[0024] According to an auxiliary hospital space design method based on a building energy consumption model provided by the present invention, the updated building design scheme data is obtained based on the building energy consumption model of the hospital to be built and the space layout information in the initial design scheme data of the hospital to be built, including:

[0025] Based on the building energy consumption model of the hospital to be built, determine the energy consumption analysis results of each space layout;

[0026] The initial design scheme data of the hospital to be built is adjusted based on the scheme with the lowest energy consumption in each space layout to obtain updated architectural design scheme data.

[0027] According to an auxiliary hospital space design method based on a building energy consumption model provided by the present invention, the target hospital is a hospital in the surrounding area of ​​the hospital to be built that has at least two of the same scale, grade and main specialty types as the hospital to be built.

[0028] The present invention also provides an auxiliary hospital space design device based on a building energy consumption model, comprising:

[0029] An acquisition module is used to acquire basic data of target hospitals in the surrounding area of ​​the hospital to be built; the basic data includes hardware and personnel configuration data, patient flow data and energy consumption data of the hospital;

[0030] A first processing module is used to obtain a building energy consumption model of the hospital to be built based on the initial design scheme data of the hospital to be built and the basic data; the building energy consumption model is used to represent the energy consumption data of different design areas of the hospital to be built in different time periods;

[0031] The second processing module is used to obtain updated building design plan data based on the building energy consumption model of the hospital to be built and the spatial layout information in the initial design plan data of the hospital to be built.

[0032] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, an auxiliary hospital space design method based on a building energy consumption model as described in any one of the above is implemented.

[0033] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for assisting hospital space design based on a building energy consumption model as described in any one of the above is implemented.

[0034] The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-mentioned auxiliary hospital space design methods based on the building energy consumption model.

[0035] The auxiliary hospital space design method and device based on the building energy consumption model provided by the present invention can more comprehensively evaluate the building energy consumption by acquiring basic data of surrounding target hospitals, comprehensively considering the hardware and personnel configuration, patient flow and energy consumption data of the target hospitals, and combining the design plan data of the hospital to be built. A building energy consumption model can be established based on actual data, and a building energy consumption model for the specific situation of the hospital to be built can be established, which can more accurately reflect the energy consumption characteristics and needs of the hospital and realize data-driven design optimization decisions, thereby reducing energy consumption on the basis of making more reasonable spatial layout adjustments and optimizations, improving energy utilization efficiency, and reducing resource waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0037] Figure 1 It is one of the flow diagrams of the auxiliary hospital space design method based on the building energy consumption model provided by the present invention;

[0038] Figure 2 This is the second flow chart of the auxiliary hospital space design method based on the building energy consumption model provided by the present invention;

[0039] Figure 3 It is a structural schematic diagram of an auxiliary hospital space design device based on a building energy consumption model provided by the present invention;

[0040] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] Combine the following Figure 1-Figure 4 The invention describes the auxiliary hospital space design method and device based on the building energy consumption model.

[0043] like Figure 1 As shown, the auxiliary hospital space design method based on the building energy consumption model of the embodiment of the present invention mainly includes step 110, step 120 and step 130.

[0044] Step 110, obtaining basic data of target hospitals in the surrounding areas of the location of the hospital to be built.

[0045] It is understandable that in response to the high energy consumption of hospitals, targeted optimization measures can be proposed starting from the architectural layout.

[0046] On this basis, it is necessary to analyze the energy consumption and behavior patterns of hospital buildings. By inputting information such as hospital usage behavior data, energy consumption data, and regional usage data obtained through monitoring, we can obtain energy consumption forecast analysis results to guide the generation of design plans.

[0047] The data-driven building energy consumption forecast analysis is supported by the input of data information from the surrounding areas. In the context of big data, the energy consumption monitoring data of surrounding hospital buildings and the data of building energy consumption management are mined. Through data processing, a better energy consumption treatment strategy can be obtained.

[0048] Basic data include the hospital's hardware and staffing data, patient flow data, and energy consumption data.

[0049] The hospital's hardware and staffing data, patient flow data, and energy consumption data are important inputs to the building energy consumption prediction model. By analyzing and processing these data, we can more accurately predict the hospital's energy consumption, optimize hospital design, and reduce energy consumption.

[0050] Hardware and staffing data include the hospital's building structure, equipment and facilities, parameters and configuration information of heating, ventilation, air conditioning and other systems, as well as the number of hospital staff, patients and other personnel, activity areas, etc. These data can help analyze the distribution of energy consumption within the building and estimate the energy consumption demand in different areas, thereby optimizing the design and operation of the building and reducing energy consumption.

[0051] Patient flow data includes information such as patient flow, visit type, and visit duration in different time periods in the hospital. These data can help analyze the flow of people in different areas within the hospital and predict the impact of personnel activities on building energy consumption, thereby optimizing the design and operation of the building and saving energy consumption.

[0052] Energy consumption data includes information such as electricity consumption, water consumption, air conditioning cooling capacity, heating heat, etc. in different time periods of the hospital. These data can help analyze the energy consumption trend within the hospital and predict energy consumption needs in different time periods, thereby optimizing the design and operation of the building and reducing energy consumption.

[0053] It is understandable that through comprehensive analysis and processing of these basic data, the hospital's energy consumption can be predicted more accurately, providing a scientific basis for the hospital to save energy and reduce costs.

[0054] The embodiments of the present invention collect and analyze these data in order to improve the comfort level of building space use and reduce energy consumption from the perspective of engineering design. Therefore, the basic data sampling selected by the present invention comes from a statistical stratified sampling model, and data of hospital buildings of the same type are selected for comparative analysis. The meaning of the same type includes hospital characteristics such as similar geographical locations, similar scales, similar hospital grades, and similar hospital specialty types. In order to ensure a certain number of samples, the above hospital characteristics meet three of the following items, including being located in similar regions, among which being located in similar regions is a necessary option. In other words, the target hospital is a hospital in the area surrounding the hospital to be built that has at least two of the same scale, grade, and main specialty types as the hospital to be built.

[0055] According to the stratified sampling mode, select similar hospitals of the same type in the surrounding area of ​​the hospital to be built with similar scale, grade and major specialty types as sample data. Ensure that the selected hospitals meet at least three similar characteristics, among which the geographical proximity is a necessary condition. Collect energy consumption data, building structure data and other relevant information of these hospitals as the basic data for model construction.

[0056] Step 120, based on the initial design data and basic data of the hospital to be built, obtain a building energy consumption model of the hospital to be built.

[0057] The building energy consumption model is used to represent the energy consumption data of different design areas of the hospital to be built at different times.

[0058] The collected basic data can be analyzed to extract characteristic variables related to building energy consumption, such as building structure parameters, functional areas, personnel activity patterns, etc., for building energy consumption models. According to the characteristic variables and sample data, a suitable modeling method is selected to establish an energy consumption model for hospital buildings. For example, regression analysis, time series analysis, machine learning and other methods can be used for modeling.

[0059] The established energy consumption model can be trained using sample data and verified through methods such as cross-validation to ensure the accuracy and stability of the model. The trained energy consumption model can be applied to the design of the hospital to be built, evaluate the energy consumption of different design schemes at different times, and put forward optimization suggestions to reduce energy consumption and improve space comfort.

[0060] In this implementation, a model that can predict the energy consumption of the hospital to be built can be constructed based on the data of similar hospitals in the surrounding area, providing a scientific basis for the design team to achieve efficient use of energy and improvement of comfort in hospital buildings.

[0061] Through the comprehensive implementation of the above steps, an accurate and reliable energy consumption model of the hospital building to be built can be constructed, providing a scientific basis for the hospital design team and achieving efficient utilization and sustainable development of hospital energy.

[0062] Specifically, the energy consumption data obtained through analysis and prediction can be associated with the building model to ensure that the correspondence between the data and the building model is correct. According to the range and distribution of the energy consumption data, the data is processed and normalized for subsequent visualization.

[0063] You can choose a suitable visualization method to display energy consumption data according to design requirements and goals. You can use bar charts, heat maps, contour maps and other forms to express energy consumption and spatial distribution. According to the numerical value of energy consumption data, design corresponding color mapping rules to convert data size into color depth and difference in visualization effect.

[0064] The processed and mapped energy consumption data can be combined with the building model to display the energy consumption data model in three-dimensional or two-dimensional form. This can be achieved using building information model (BIM) software or data visualization tools. Based on the visualization results, the energy consumption data model is interpreted and analyzed to understand the energy consumption distribution of hospital buildings, high energy consumption areas, low energy consumption areas and other information.

[0065] Step 130, obtaining updated building design plan data based on the building energy consumption model of the hospital to be built and the spatial layout information in the initial design plan data of the hospital to be built.

[0066] It is understandable that the results of the building energy consumption model can be analyzed in detail to understand the degree of influence of each parameter on energy consumption and the main energy consumption hotspots.

[0067] Based on the results of the energy consumption model, possible energy consumption problems can be identified, such as high energy consumption areas and energy waste.

[0068] Based on the results of the energy consumption model and the problems identified, the parameters of the initial design solution are gradually adjusted. For example, the building's orientation, shape, window design, insulation materials, building energy-saving equipment, etc. can be adjusted.

[0069] On this basis, the energy consumption model can be used to re-simulate the updated design and evaluate its improvement in energy consumption. The simulation results are compared with the initial design to analyze the difference in energy consumption and the extent of improvement. Based on the simulation and evaluation results, iterative optimization can be performed, repeatedly adjusting the design parameters and re-simulating until the expected energy consumption reduction target is achieved.

[0070] When adjusting the design plan, other factors can also be considered comprehensively, such as building functional requirements, safety requirements, economic costs, etc. Ensure that the optimized design plan can not only reduce energy consumption, but also meet other key requirements.

[0071] When adjusting the initial design plan data of the hospital to be built, consideration may be given to adjusting dimensions such as energy efficiency improvement, lighting and ventilation design, intelligent control systems, renewable energy applications, green vegetation coverage, and equipment updates and optimization in the initial design plan data.

[0072] Specifically, energy efficiency improvements can improve the energy efficiency of buildings and reduce energy losses by optimizing building facade design, improving thermal insulation performance, and adding insulation materials.

[0073] Lighting and ventilation design can consider optimizing the internal layout and window design of the building, increasing natural lighting and ventilation, reducing dependence on artificial lighting and air-conditioning systems, and reducing energy consumption.

[0074] In this embodiment, an intelligent building management system can also be introduced to achieve dynamic adjustment and optimization of energy consumption through sensors and control systems to improve energy utilization efficiency.

[0075] Understandably, it is possible to consider installing renewable energy facilities such as solar photovoltaic panels and wind power generation equipment in buildings to reduce dependence on traditional energy and reduce building energy consumption.

[0076] Regarding green vegetation coverage, the green vegetation coverage on the roof or walls of the building can be increased to improve the building's thermal insulation performance and cooling effect and reduce air-conditioning energy consumption.

[0077] For equipment renewal and optimization, you can consider using more energy-efficient equipment and technologies, such as LED lighting, high-efficiency air conditioning, etc., to replace old equipment to reduce energy consumption.

[0078] It is understandable that through the analysis of the building energy consumption model and the application of the above-mentioned optimization measures, the design plan data of the hospital to be built can be adjusted and an updated building design plan can be proposed, thereby reducing building energy consumption, improving energy efficiency, and achieving the goal of sustainable development.

[0079] In some embodiments, based on the building energy consumption model of the hospital to be built and the spatial layout information in the initial design plan data of the hospital to be built, an updated number of building design plans is obtained, including determining the energy consumption analysis results of each spatial layout based on the building energy consumption model of the hospital to be built, adjusting the initial design plan data of the hospital to be built based on the plan with the lowest energy consumption in each spatial layout, and obtaining updated building design plan data.

[0080] It is understandable that, based on the building energy consumption model of the hospital to be built, energy consumption analysis can be performed on different space layout designs to obtain the energy consumption under different space layout designs.

[0081] In this case, the initial design scheme data of the hospital to be built can be adjusted based on the scheme with the lowest energy consumption among various space layouts, that is, the space layout design with the lowest energy consumption can be used as the updated building design scheme data.

[0082] According to the auxiliary hospital space design method based on the building energy consumption model provided by the embodiment of the present invention, by acquiring the basic data of the surrounding target hospitals, comprehensively considering the hardware and personnel configuration, patient flow and energy consumption data of the target hospitals, and combining the design plan data of the hospital to be built, it is possible to more comprehensively evaluate the building energy consumption situation, and establish a building energy consumption model based on actual data. Establishing a building energy consumption model for the specific situation of the hospital to be built can more accurately reflect the energy consumption characteristics and needs of the hospital, and realize data-driven design optimization decisions, thereby reducing energy consumption on the basis of making more reasonable spatial layout adjustments and optimizations, improving energy utilization efficiency, and reducing resource waste.

[0083] like Figure 2 As shown, in some embodiments, based on the initial design plan data and basic data of the hospital to be built, a building energy consumption model of the hospital to be built is obtained, including step 121, step 122, step 123 and step 124.

[0084] Step 121, based on the basic data of the target hospital, obtain the patient tidal characteristics of the target hospital.

[0085] Patient tide characteristics are used to represent the fluctuation and regularity of the number of patients in different areas of a hospital during different time periods.

[0086] It is understandable that relevant hardware and personnel configuration data can be obtained from the target hospital, including the number of hospital beds, medical equipment, medical staff configuration, etc. At the same time, patient flow data is collected, including the number of patients per day, the distribution of the number of patients in different time periods, etc.

[0087] Analyze the collected patient flow data to explore the changes in the number of patients in different areas during different periods of time. Statistical methods, time series analysis and other techniques can be used to identify the periodicity of patient tides, peak moments, and the changing patterns between high and low peaks.

[0088] According to the data analysis results, a patient tide model of the target hospital is established. This model can describe the fluctuation of the number of patients in each area of ​​the hospital in different time periods and reflect its regularity.

[0089] The established patient tidal model is used to validate the collected patient flow data to check the accuracy and adaptability of the model. Based on the validation results, the model can be adjusted and optimized to more accurately represent the patient tidal characteristics of the target hospital.

[0090] Step 122, based on the patient tidal characteristics of the target hospital and the initial design plan data of the hospital to be built, obtain the predicted patient tidal characteristics of the hospital to be built.

[0091] Time series analysis, machine learning models and other methods can be used to establish a prediction model, which can predict the patient tidal characteristics of the hospital to be built through correlation analysis of the patient tidal characteristics of the target hospital and the design plan data of the hospital to be built.

[0092] After establishing the prediction model, the model needs to be verified. For example, historical data can be used for verification to check the accuracy and stability of the model and ensure the reliability of the prediction results.

[0093] On this basis, the model can be applied to the design plan data of the hospital to be built to obtain the predicted patient tidal characteristics of the hospital to be built, which will help optimize the design plan of the hospital to be built, including appropriate adjustments to the planning, staffing, equipment layout, etc. of the diagnosis and treatment area to better adapt to future patient tidal conditions.

[0094] Step 123, based on the predicted patient tidal characteristics of the hospital to be built, obtain the predicted behavior pattern of the hospital to be built.

[0095] Predicted behavioral patterns included healthcare staff utilization and inpatient turnover.

[0096] According to the predicted patient tide characteristics of the hospital to be built, combined with the target hospital's medical staff usage data, a forecasting model for medical staff demand is established. Regression analysis, time series analysis and other methods can be used to predict the demand for medical staff in different time periods based on changes in the number of patients and related factors.

[0097] Based on the predicted demand for medical staff, a scheduling plan for medical staff can be formulated. Taking into account the tidal characteristics of patients and the volatility of patient flow, the working hours and shift arrangements of medical staff can be reasonably arranged to ensure sufficient staffing during peak hours while avoiding excess during low hours.

[0098] By using the predicted patient tide characteristics of the hospital to be built and combining the inpatient turnover rate data of the target hospital, a prediction model for inpatient turnover rate is established. Time series analysis, survival analysis and other methods can be used to predict the average length of stay and the speed of admission and discharge of patients.

[0099] According to the predicted inpatient turnover rate, bed management and resource allocation should be arranged reasonably. Increase bed supply during peak hours, adjust bed utilization rate and referral policy in a timely manner to meet the needs of patients in different time periods and optimize the utilization efficiency of inpatient resources.

[0100] Through the above steps, we can obtain the predicted behavior patterns of medical staff utilization and inpatient turnover rate based on the predicted patient tide characteristics of the hospital to be built. These patterns will help to rationally plan and manage hospital personnel and resources and improve the service quality and efficiency of the hospital.

[0101] Step 124, based on the predicted behavior pattern of the hospital to be built, obtain the energy consumption data of the medical staff and inpatients of the hospital to be built in different design areas corresponding to the hospital to be built at different time periods, and construct a building energy consumption model of the hospital to be built.

[0102] Based on the predicted behavior patterns of medical staff in the hospital to be built, the energy consumption of medical staff in different design areas is predicted. Considering the energy consumption of lighting, air conditioning, ventilation, etc. required by medical staff during work, and combining factors such as working hours and work intensity, the energy consumption of medical staff in each area is calculated.

[0103] Based on the inpatient turnover rate in the predicted behavior pattern of the hospital to be built, the energy consumption of inpatients is predicted in different design areas. Considering the energy consumption of lighting, air conditioning, elevator use in the ward, and the energy consumption required for patients' living and eating, the energy consumption of inpatients in each area is calculated.

[0104] In this embodiment, a building energy consumption model of the hospital to be built can be constructed based on the energy consumption data of medical staff and inpatients in different design areas, combined with relevant building energy consumption models and algorithms, to further reflect factors such as energy consumption in each area, equipment operation status, indoor temperature and humidity, so as to predict the overall energy consumption of the hospital to be built.

[0105] In some embodiments, based on the initial design plan data and basic data of the hospital to be built, a building energy consumption model of the hospital to be built is obtained, which also includes the following process.

[0106] The historical usage data of the target hospital's air conditioning and heating systems can be obtained; the historical usage data can be associated with the temperature data and the patient's tidal characteristics to obtain the energy consumption model of the target hospital's air conditioning and heating systems; the energy consumption model of the target hospital's air conditioning and heating systems can be superimposed on the existing building energy consumption model to obtain an updated building energy consumption model.

[0107] For example, the year can be taken as a periodic unit, and the annual air conditioning and heating usage patterns can be digitized and then superimposed into the energy consumption model in the previous step.

[0108] For the hospital's air conditioning and heating systems, historical data is collected and analyzed to understand the demand for air conditioning and heating due to temperature changes in different seasons or months, personnel activity patterns, etc. Based on these data, certain usage patterns can be obtained, such as a certain season where the daytime activity area requires a stronger air conditioning supply, while the night is relatively low; or a certain month where more heating is required in the morning and evening, but less during the day.

[0109] These air conditioning and heating usage patterns are converted into numerical data and combined with other existing basic data. Statistical analysis methods such as regression analysis and time series analysis can be used to quantify and correlate various factors to form a mathematical model that can reflect the energy consumption characteristics of the hospital.

[0110] The obtained data on air conditioning and heating usage patterns are added to the existing energy consumption model, combined with other factors (such as lighting, equipment use, etc.), to comprehensively consider the overall energy consumption of the hospital. Through the operation and calculation of the model, the energy consumption forecast results of the hospital to be built in different seasons or months, as well as the corresponding energy consumption characteristics, can be obtained.

[0111] In some embodiments, based on the building energy consumption model of the hospital to be built and the spatial layout information in the initial design plan data of the hospital to be built, updated building design plan data are obtained, including: based on the building energy consumption model of the hospital to be built, obtaining energy consumption analysis results of the hospital to be built under different spatial layouts; based on the energy consumption analysis results, adjusting at least one of the spatial layout of the hospital to be built, the HVAC equipment layout plan, and the control plan of the energy consuming equipment, to obtain updated building design plan data.

[0112] It is understandable that energy consumption analysis can be conducted based on the building energy consumption model of the hospital to be built to obtain the energy consumption and energy consumption proportion of each area under different space design methods. Through the analysis of energy consumption, it is determined which areas and HVAC equipment need to be optimized.

[0113] According to the results of energy consumption analysis, the spatial layout of the hospital to be built can be optimized in a targeted manner to reduce unnecessary energy consumption as much as possible while meeting functional requirements. For example, the layout of beds and furniture in the ward area can be adjusted, ventilation and lighting design can be optimized, and indoor lighting can be improved.

[0114] According to the results of energy consumption analysis, the HVAC equipment layout of the hospital to be built can be optimized, the type of HVAC equipment can be reasonably selected, and factors such as high efficiency, energy saving, and convenient maintenance can be considered. For example, insulation layers and thermal insulation materials can be added in high-energy consumption areas, intelligent control systems can be installed, and air circulation plans can be optimized.

[0115] According to the results of energy consumption analysis, the energy consumption equipment control plan of the hospital to be built can be optimized to reduce operating costs and environmental pollution by improving equipment utilization efficiency and reducing unnecessary energy consumption. For example, energy-saving lamps can be used in lighting equipment, and induction switches and timer switches can be installed.

[0116] In some embodiments, based on the energy consumption analysis results, at least one of the spatial layout of the hospital to be built, the HVAC equipment layout plan, and the control plan of the energy-consuming equipment is adjusted to obtain updated building design plan data, including: based on the energy consumption analysis results, identifying energy consumption data of different areas, and determining areas where the hospital to be built is densely populated for a long period of time; adjusting the spatial layout in areas where the hospital to be built is densely populated for a long period of time to increase the lighting area and accommodation space, increase the number of HVAC equipment, adjust the control plan of the energy-consuming equipment to control the HVAC equipment to increase the air output, and obtain updated building design plan data.

[0117] For crowded areas, we can consider adjusting the spatial layout, increasing the lighting area and accommodation space to improve comfort and reduce energy consumption. For example, we can increase the number and size of windows, optimize the window position, introduce natural light, and reduce dependence on artificial lighting; adjust the seating arrangement, ensure good ventilation, and improve space utilization.

[0118] For places with dense patient populations, such as waiting halls and waiting areas for patients, their needs are to increase the daylighting area, and an open design that blends with nature can help relieve patients’ anxiety. The establishment of an energy consumption model can help architects provide data support for the location of open spaces, how to arrange open areas in areas such as waiting halls where patients stay for a long time and are relatively dense, and the layout of inner courtyards, etc., and can help architects achieve a trade-off between energy saving and space quality creation through multiple feedback and adjustments.

[0119] During the use of hospitals, there will be uneven distribution of personnel, uneven daily time periods, and uneven number of people using the hospital during the week. Establishing a building energy consumption model can help architects define the size of the main space and the space design in most cases. According to the model data, multiple landscape nodes can be arranged around the hospital to provide waiting space for patients during peak hours.

[0120] For public spaces such as outpatient and inpatient halls, architects usually arrange tall spaces according to the needs of personnel, which leads to uneven temperature in the upper part of the space, which is not conducive to energy saving. Low energy consumption requires a lower space height. The building energy consumption model can help architects coordinate the relationship between space height and reduce energy consumption by reducing the height of multiple small halls. The building energy consumption model can help architects balance the relationship between energy saving and space height without reducing the quality of the space.

[0121] For crowded areas, you can consider increasing the number of HVAC equipment to ensure indoor air quality and temperature comfort. You can increase the number and layout of vents and air outlets to optimize air circulation and improve indoor air quality.

[0122] For the additional HVAC equipment, the control scheme of energy-consuming equipment needs to be adjusted to control the increased air volume of HVAC equipment and avoid energy waste. Intelligent control systems can be used to adjust the equipment operation mode and parameters according to actual needs to achieve energy efficiency optimization and energy saving and emission reduction.

[0123] In this embodiment, the indoor microclimate is fundamentally improved by means of architectural design. By guiding the layout of the air conditioning and ventilation system, etc., the layout points of the air conditioning system that can be adjusted and the layout points of the conventional air conditioning that can be used with less changes are defined.

[0124] Specifically, in areas where people gather for long periods of time, we can increase semi-outdoor gray spaces in buildings and partially open skylights in indoor spaces. This can not only improve the adverse effects on patients caused by dense crowds, but also utilize outdoor natural ventilation in seasons such as spring and autumn to reduce the use of air conditioning.

[0125] According to the conclusions of energy consumption analysis, the layout of HVAC equipment can be adjusted. For example, the number of ventilation and heating vents can be increased in places with concentrated population density, and the air volume can be increased to increase patient comfort.

[0126] According to the patient's behavior pattern, the operation of the equipment inside the building is precisely controlled. For example, when the patient's tide changes and the crowd is at its lowest point, the energy consumption can be reduced by reducing the air volume and lighting density.

[0127] According to the above adjustments, the design plan data of the hospital to be built will be updated, including adjustments to the spatial layout, increase in the number of HVAC equipment, and adjustments to the control plan for energy-consuming equipment, and evaluation and verification will be carried out to ensure the feasibility and effectiveness of the design plan.

[0128] In some embodiments, based on the energy consumption analysis results, at least one of the spatial layout of the hospital to be built, the HVAC equipment layout plan, and the control plan of the energy-consuming equipment is adjusted to obtain updated architectural design plan data, including: based on the energy consumption analysis results, identifying the energy consumption data of the peripheral area of ​​the hospital building, reducing the window area of ​​the peripheral area of ​​the building, and obtaining updated architectural design plan data.

[0129] It is understandable that improving the performance of the building's exterior insulation structure can reduce indoor energy loss. For buildings, the thermal insulation performance of glass is lower than that of the exterior wall, which means that reducing the window area can reduce energy loss.

[0130] The following is a description of the auxiliary hospital space design device based on the building energy consumption model provided by the present invention. The auxiliary hospital space design device based on the building energy consumption model described below and the auxiliary hospital space design method based on the building energy consumption model described above can be referenced to each other.

[0131] like Figure 3 As shown, the auxiliary hospital space design device based on the building energy consumption model of the embodiment of the present invention mainly includes an acquisition module 310, a first processing module 320 and a second processing module 330.

[0132] The acquisition module 310 is used to acquire basic data of target hospitals in the surrounding area of ​​the hospital to be built; the basic data includes the hospital's hardware and personnel configuration data, patient flow data, and energy consumption data;

[0133] The first processing module 320 is used to obtain a building energy consumption model of the hospital to be built based on the initial design scheme data and basic data of the hospital to be built; the building energy consumption model is used to represent the energy consumption data of different design areas of the hospital to be built at different time periods;

[0134] The second processing module 330 is used to obtain updated building design plan data based on the building energy consumption model of the hospital to be built and the spatial layout information in the initial design plan data of the hospital to be built.

[0135] According to the auxiliary hospital space design device based on the building energy consumption model provided by the embodiment of the present invention, by acquiring the basic data of the surrounding target hospitals, comprehensively considering the hardware and personnel configuration, patient flow and energy consumption data of the target hospitals, and combining the design plan data of the hospital to be built, it is possible to more comprehensively evaluate the building energy consumption situation, and establish a building energy consumption model based on actual data. Establishing a building energy consumption model for the specific situation of the hospital to be built can more accurately reflect the energy consumption characteristics and needs of the hospital, and realize data-driven design optimization decisions, thereby reducing energy consumption on the basis of making more reasonable spatial layout adjustments and optimizations, improving energy utilization efficiency, and reducing resource waste.

[0136] Figure 4 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430 and a communication bus 440, wherein the processor 410, the communication interface 420 and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute the auxiliary hospital space design method based on the building energy consumption model, the method comprising: obtaining the basic data of the target hospital in the surrounding area of ​​the hospital to be built; the basic data includes the hardware and personnel configuration data, the patient flow data and the energy consumption data of the hospital; based on the initial design scheme data of the hospital to be built and the basic data, obtaining the building energy consumption model of the hospital to be built; the building energy consumption model is used to represent the energy consumption data of different design areas of the hospital to be built at different time periods; based on the building energy consumption model of the hospital to be built and the spatial layout information in the initial design scheme data of the hospital to be built, obtaining the updated building design scheme data.

[0137] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0138] On the other hand, the present invention also provides a computer program product, which includes a computer program, and the computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the auxiliary hospital space design method based on the building energy consumption model provided by the above-mentioned methods, and the method includes: obtaining basic data of a target hospital in the surrounding area of ​​the hospital to be built; the basic data includes the hospital's hardware and personnel configuration data, patient flow data and energy consumption data; based on the initial design plan data of the hospital to be built and the basic data, obtaining the building energy consumption model of the hospital to be built; the building energy consumption model is used to represent the energy consumption data of different design areas of the hospital to be built at different time periods; based on the building energy consumption model of the hospital to be built and the spatial layout information in the initial design plan data of the hospital to be built, obtaining updated building design plan data.

[0139] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the auxiliary hospital space design method based on the building energy consumption model provided by the above-mentioned methods, the method comprising: obtaining basic data of a target hospital in the surrounding area of ​​the hospital to be built; the basic data includes the hospital's hardware and personnel configuration data, patient flow data and energy consumption data; based on the initial design plan data of the hospital to be built and the basic data, obtaining a building energy consumption model of the hospital to be built; the building energy consumption model is used to represent the energy consumption data of different design areas of the hospital to be built at different time periods; based on the building energy consumption model of the hospital to be built and the spatial layout information in the initial design plan data of the hospital to be built, obtaining updated building design plan data.

[0140] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0141] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0142] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for auxiliary hospital space design based on building energy consumption model, characterized in that: include: Obtain basic data of target hospitals in the surrounding area of ​​the hospital to be built; the basic data includes hospital hardware and personnel configuration data, patient flow data, and energy consumption data; Based on the initial design scheme data of the hospital to be built and the basic data, a building energy consumption model of the hospital to be built is obtained; The building energy consumption model is used to represent the energy consumption data of different design areas of the hospital to be built at different time periods; Based on the building energy consumption model of the hospital to be built and the spatial layout information in the initial design plan data of the hospital to be built, obtaining updated building design plan data; The building energy consumption model of the hospital to be built is obtained based on the initial design scheme data of the hospital to be built and the basic data, including: Based on the basic data of the target hospital, the patient tidal characteristics of the target hospital are obtained; the patient tidal characteristics are used to represent the fluctuation and regularity of the number of patients in different areas of the hospital in different time periods; Based on the patient tidal characteristics of the target hospital and the initial design plan data of the hospital to be built, obtaining predicted patient tidal characteristics of the hospital to be built; Based on the predicted patient tide characteristics of the hospital to be built, a predicted behavior pattern of the hospital to be built is obtained; the predicted behavior pattern includes the use of medical staff and the turnover rate of inpatients; Based on the predicted behavior pattern of the hospital to be built, the energy consumption data of the medical staff and inpatients of the hospital to be built in different design areas corresponding to the hospital to be built in different time periods are obtained to construct a building energy consumption model of the hospital to be built.

2. The auxiliary hospital space design method based on building energy consumption model according to claim 1 is characterized in that: The step of obtaining a building energy consumption model of the hospital to be built based on the initial design scheme data of the hospital to be built and the basic data further includes: Obtain historical usage data of the target hospital's air conditioning and heating systems; Associating the historical usage data with the temperature data and the patient tidal characteristics to obtain an energy consumption model of the air conditioning and heating system of the target hospital; The energy consumption model of the air conditioning and heating systems of the target hospital is superimposed on the existing building energy consumption model to obtain an updated building energy consumption model.

3. The auxiliary hospital space design method based on building energy consumption model according to claim 1 is characterized in that: The updated building design scheme data is obtained based on the building energy consumption model of the hospital to be built and the spatial layout information in the initial design scheme data of the hospital to be built, including: Based on the building energy consumption model of the hospital to be built, obtaining energy consumption analysis results of the hospital to be built under different spatial layouts; Based on the energy consumption analysis result, at least one of the spatial layout, HVAC equipment layout plan and energy consumption equipment control plan of the hospital to be built is adjusted to obtain updated architectural design plan data.

4. The auxiliary hospital space design method based on building energy consumption model according to claim 3 is characterized in that: The step of adjusting at least one of the spatial layout, HVAC equipment layout plan, and energy consumption equipment control plan of the hospital to be built based on the energy consumption analysis result to obtain updated building design plan data includes: Based on the energy consumption analysis results, energy consumption data of different areas are identified to determine areas where the hospital to be built is densely populated for a long period of time; In the areas of the hospital to be built where there are dense crowds for long periods of time, the spatial layout is adjusted to increase the lighting area and the accommodation space, the number of HVAC equipment is increased, and the control scheme of the energy-consuming equipment is adjusted to control the HVAC equipment to increase the air output, so as to obtain updated architectural design scheme data.

5. The auxiliary hospital space design method based on building energy consumption model according to claim 1 is characterized in that: The updated building design scheme data is obtained based on the building energy consumption model of the hospital to be built and the spatial layout information in the initial design scheme data of the hospital to be built, including: Based on the building energy consumption model of the hospital to be built, determine the energy consumption analysis results of each space layout; The initial design scheme data of the hospital to be built is adjusted based on the scheme with the lowest energy consumption in each space layout to obtain updated architectural design scheme data.

6. The auxiliary hospital space design method based on building energy consumption model according to claim 1 is characterized in that: The target hospital is a hospital in the surrounding area of ​​the hospital to be built that has at least two of the same scale, grade and main specialty types as the hospital to be built.

7. A device for assisting hospital space design based on a building energy consumption model, characterized in that: The auxiliary hospital space design device based on the building energy consumption model adopts the auxiliary hospital space design method based on the building energy consumption model as claimed in claim 1 to perform auxiliary hospital space design. The auxiliary hospital space design device based on the building energy consumption model includes: An acquisition module is used to acquire basic data of target hospitals in the surrounding area of ​​the hospital to be built; the basic data includes hardware and personnel configuration data, patient flow data and energy consumption data of the hospital; A first processing module is used to obtain a building energy consumption model of the hospital to be built based on the initial design scheme data of the hospital to be built and the basic data; the building energy consumption model is used to represent the energy consumption data of different design areas of the hospital to be built in different time periods; The second processing module is used to obtain updated building design plan data based on the building energy consumption model of the hospital to be built and the spatial layout information in the initial design plan data of the hospital to be built.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the auxiliary hospital space design method based on the building energy consumption model as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the auxiliary hospital space design method based on the building energy consumption model as described in any one of claims 1 to 6 is implemented.

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