Building thermal environment and building energy-saving control methods to achieve demand-side response

Abstract

The present invention discloses a building thermal environment and building energy-saving control method for realizing demand-side response, and relates to the field of building energy-saving technology. In order to solve the problem that the influence of the thermal environment is ignored in the prior art, resulting in limited control accuracy and comfort, different regions or different users may have different requirements for the thermal environment, and the prior art does not take into account personalized needs, which may cause some users to feel dissatisfied; the building thermal environment and building energy-saving control method for realizing demand-side response includes the following steps: step one: energy assessment; step two: formulating a control strategy; step three: terminal control monitoring; by comprehensively considering multiple factors such as building energy use, indoor environment and personnel activities, an effective energy-saving control strategy is formulated, and real-time monitoring and optimization are realized through an intelligent control system, thereby improving the energy utilization efficiency of the building, reducing energy consumption costs, and creating a more comfortable and healthy indoor environment for users.

Description

Technical Field

[0001] The present invention relates to the technical field of building energy conservation, and in particular to a building thermal environment and building energy conservation control method that realizes demand-side response. Background Art

[0002] As people pursue a higher quality of life and improve their environmental awareness, the requirements for building thermal environment and energy-saving control are becoming higher and higher. Traditional building thermal environment regulation and energy-saving control methods often have problems such as slow response speed, low control accuracy, and high energy consumption, which cannot meet the needs of modern buildings. Regarding the control method related to building thermal environment and building energy saving, a Chinese patent with publication number CN116659034A discloses a building thermal environment and building energy-saving control method and system in an air-conditioned building. By dividing the air-conditioned building into regions, the cold air with a temperature lower than the set temperature in the nearby areas of the qualified areas is collected, and the flow rate to other areas is determined according to the flow of people in the air-conditioned building, so that the cold air is transported to other areas, making full use of the cooling capacity of the air conditioner, reducing the air conditioning energy consumption in the building, and achieving the effect of energy saving.

[0003] However, although the above patent achieves the effect of energy saving, it ignores the influence of the thermal environment, resulting in limited control accuracy and comfort. Different regions or different users may have different requirements for the thermal environment. The existing technology does not take into account personalized needs, which may cause some users to feel dissatisfied. Summary of the invention

[0004] The purpose of the present invention is to provide a building thermal environment and building energy-saving control method that realizes demand-side response. By comprehensively considering multiple factors such as building energy use, indoor environment and human activities, an effective energy-saving control strategy is formulated, and real-time monitoring and optimization are achieved through an intelligent control system, thereby improving the energy utilization efficiency of the building, reducing energy consumption costs, and creating a more comfortable and healthier indoor environment for users, so as to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] The method for controlling building thermal environment and building energy conservation to realize demand-side response includes the following steps:

[0007] Step 1: Energy assessment: Before the energy-saving renovation of the building project, an energy assessment is conducted to collect the building's assessment data, including the building type, area, orientation, and surrounding environment data. Based on the collected assessment data, the building's energy usage is analyzed and the various areas of energy consumption are identified;

[0008] Step 2: Formulate control strategies: formulate corresponding energy-saving control strategies for various energy consumption areas based on the analysis results, build a virtual model of the building project based on the evaluation data, simulate and deduce the energy-saving control strategies, and optimize the energy-saving measures of the energy-saving control strategies based on the simulation results;

[0009] Step 3: Terminal control and monitoring: Integrate intelligent control systems, including partition control, location sensing, time series control, and light sensing control, collect actual operation data, analyze energy usage, and conduct real-time monitoring and evaluation based on optimized energy-saving measures;

[0010] The control strategy formulated in step 2 also includes:

[0011] Real-time data collection time interval of temperature sensor, humidity sensor and light sensor;

[0012] According to the change of the data collection time interval of the temperature sensor, the humidity sensor and the light sensor, the first sensor time interval coefficient is obtained; wherein the first sensor time interval coefficient is obtained by the following formula: Among them, F 01 represents the first sensor time interval coefficient; f 01 、f 02 and f 03 Respectively represent the time interval coefficients corresponding to the temperature sensor, humidity sensor and light sensor; F n represents f 01 、f 02 and f 03 The coefficient values ​​corresponding to the non-maximum and non-minimum values ​​in; F0 represents the preset coefficient reference value; wherein the time interval coefficients corresponding to the temperature sensor, humidity sensor and light sensor are obtained by the following formula: Where n, m and k represent the number of data collection time intervals included in the operation of the temperature sensor, humidity sensor and light sensor respectively; G 01i , G 02i and G 03i Respectively represent the time length of the data collection time interval corresponding to the i-th temperature sensor, humidity sensor and light sensor; G c Indicates the preset time interval reference value; G 01max , G 02max and G 03max Respectively represent the maximum time length of the data collection time interval corresponding to the temperature sensor, humidity sensor and light sensor;

[0013] comparing the first sensor time interval coefficient with a preset time interval coefficient threshold;

[0014] When the time interval coefficient of the first sensor exceeds a preset time interval coefficient threshold, the data collection time interval of the human body infrared sensor is adjusted.

[0015] Furthermore, the energy assessment in step 1 specifically includes:

[0016] Data collection: Based on the construction project, obtain the type and area of ​​the building, determine the orientation of the building and the layout of each functional area, and collect information about the surrounding environment of the building, including the height, distance and vegetation of adjacent buildings;

[0017] Energy situation analysis: Obtain the historical energy data of the building, analyze the energy consumption data of different time periods, identify the peak and off-peak periods, and obtain the operating status of each energy-using system in the building;

[0018] Determination of energy consumption areas: Divide the building into at least one area according to its functional layout and energy consumption characteristics, label each area, and process and analyze the acquired source consumption data based on the label type of each area;

[0019] Energy consumption area assessment: Based on the processing and analysis results of each area, the energy consumption levels of the areas are compared to determine the key areas with high energy consumption. At the same time, based on the surrounding environment information obtained, the building's shading and the impact of the heat island effect are evaluated.

[0020] Furthermore, in step 2, a control strategy is formulated, specifically:

[0021] Formulate energy-saving control plans: integrate regions based on the tag types and energy consumption levels of each region, formulate corresponding energy-saving control strategies based on the integration results, and match the energy-saving control strategies with each region one by one;

[0022] Scheme simulation: Build a virtual building model based on the acquired building assessment data, apply the formulated energy-saving control strategy to the virtual building model, simulate the operation status and energy consumption of the building under different conditions, predict the energy-saving effect after the implementation of the strategy, and discover potential problems;

[0023] Adaptive adjustment and optimization: Optimize the energy-saving control strategy according to the simulation results, apply the optimized strategy to the actual building, and obtain feedback data in real time.

[0024] Furthermore, the control strategy formulated in step 2 also includes:

[0025] A sensor network is deployed in each area of ​​the building, including a temperature sensor, a humidity sensor, a light sensor, and a human infrared sensor, and indoor environment and personnel activity data are monitored in real time based on the sensor network;

[0026] Based on the acquired indoor environment data, the current indoor light intensity and indoor temperature and humidity levels are determined. The brightness and color temperature of the lighting terminal are adjusted based on the time information and outdoor weather. The indoor temperature and humidity change trend is inferred based on the personnel activity data and outdoor temperature data. The air conditioning system is adjusted based on the inferred results.

[0027] Establish a wireless signal transmission channel with each device inside the building, control the control module of each device based on the control instructions corresponding to the received energy-saving control solution, adjust the indoor environment, and the sensor network continuously monitors changes in the indoor environment and feeds back new data.

[0028] Further, when the time interval coefficient of the first sensor exceeds a preset time interval coefficient threshold, the data collection time interval of the human body infrared sensor is adjusted, including:

[0029] When the time interval coefficient of the first sensor exceeds a preset time interval coefficient threshold, extracting the data collection time interval of the human body infrared sensor;

[0030] The data collection time interval of the human infrared sensor is used to obtain the second sensor time interval coefficient, wherein the second sensor time interval coefficient is obtained by the following formula: Among them, F 02 represents the time interval coefficient of the second sensor; F0 represents the preset coefficient reference value; f 01 、f 02 and f 03 Respectively represent the time interval coefficients corresponding to the temperature sensor, humidity sensor and light sensor; f 04 represents the time interval coefficient corresponding to the human infrared sensor, and the time interval coefficient corresponding to the human infrared sensor is obtained by the following formula: Where r represents the number of data collection time intervals included in the operation of the human infrared sensor; G 04max Indicates the maximum time length of the data collection time interval corresponding to the human infrared sensor; G 04i G represents the length of the data collection time interval corresponding to the i-th human infrared sensor; c Indicates the preset time interval reference value;

[0031] Comparing the first sensor time interval coefficient with the second sensor time interval coefficient to obtain a comparison result;

[0032] When the comparison result shows that the time interval coefficient of the first sensor exceeds the time interval coefficient of the second sensor, the data collection time interval range of the human infrared sensor is adjusted to obtain an adjusted data collection time interval range, and the adjusted data collection time interval range is obtained by the following formula: Among them, G up and G down Respectively represent the upper and lower limits of the adjusted data collection time interval range; G p It represents the average value of the data collection time interval contained in the data collection process of the human infrared sensor; F 01 Indicates the time interval coefficient of the first sensor; F 02 represents the time interval coefficient of the second sensor;

[0033] The human body infrared sensor is controlled to collect data according to the adjusted data collection time interval.

[0034] Furthermore, the terminal control monitoring in step 3 is specifically as follows:

[0035] Based on the deployed sensor network and established wireless signal transmission channel, the energy usage data and equipment operation data collected from various areas and equipment in the building are monitored in real time;

[0036] Monitor and evaluate the energy usage in the building based on the optimized energy-saving measures, and determine the energy-saving efficiency of each area and equipment in the building based on the obtained feedback data and the preset threshold;

[0037] Establish a user feedback mechanism to collect opinions and suggestions from people in the building on energy use and environmental comfort, and adjust and optimize the parameters and settings of various equipment in the building based on user feedback results.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] By conducting energy assessment on buildings, we can accurately identify key areas and time periods of energy consumption, so as to formulate targeted energy-saving control strategies, which will help reduce unnecessary energy waste, significantly improve energy utilization efficiency, and reduce building operating costs. Through sensors and intelligent algorithms, we can realize automatic adjustment and optimization of lighting, air-conditioning and other systems. Using intelligent sensing technology and adaptive control algorithms, we can automatically adjust indoor temperature and humidity according to personnel activities and outdoor environment. After implementing energy-saving control measures, we will carry out continuous monitoring and evaluation to ensure the effectiveness and efficiency of various measures. We will regularly conduct energy audits on buildings to identify new energy-saving opportunities and improvement points. By implementing energy-saving control strategies, we can reduce energy consumption and emissions, help reduce negative impacts on the environment, and achieve harmonious coexistence between buildings and the environment. We will adjust equipment parameters and settings in real time according to actual operating data and user feedback to ensure that energy-saving goals are achieved while meeting user comfort needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A flow chart of a building thermal environment and building energy-saving control method for realizing demand-side response according to the present invention;

[0041] Figure 2 is the energy assessment flow chart of the present invention;

[0042] Figure 3 The control strategy flow chart of the present invention is formulated. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0044] In order to solve the problem of ignoring the influence of thermal environment, resulting in limited control accuracy and comfort, different areas or different users may have different requirements for thermal environment, and the existing technology does not take into account personalized needs, which may cause some users to feel dissatisfied. Figure 1-3 , this embodiment provides the following technical solutions:

[0045] The method for controlling building thermal environment and building energy conservation to realize demand-side response includes the following steps:

[0046] Step 1: Energy assessment: Before the energy-saving renovation of the building project, an energy assessment is conducted to collect the building's assessment data, including building type, area, orientation, and surrounding environment data. Based on the collected assessment data, the building's energy usage is analyzed and the various areas of energy consumption are determined, including:

[0047] Data collection: Based on the construction project, obtain the type and area of ​​the building, such as residential, commercial, industrial, etc., and determine the orientation of the building and the layout of each functional area, such as north-south orientation, east-west orientation, etc. At the same time, collect the surrounding environment information of the building, including the height, distance and vegetation conditions of adjacent buildings;

[0048] Energy situation analysis: Obtain the historical energy data of the building, analyze the energy consumption data of different time periods, such as seasons, weekdays and weekends, identify peak and off-peak hours, and obtain the operating status of each energy-using system in the building, such as lighting, air conditioning, elevators, etc., to understand their usage patterns and energy consumption characteristics;

[0049] Determination of energy consumption areas: Divide the building into at least one area according to its functional layout and energy consumption characteristics, and label each area, such as office area, rest area, public area, etc. Process and analyze the acquired source consumption data based on the label type of each area;

[0050] Energy consumption area assessment: compare the energy consumption levels of each area based on the processing and analysis results of each area, determine the key areas with high energy consumption, and at the same time, evaluate the building's shading and the impact of the heat island effect based on the surrounding environment information obtained;

[0051] Step 2: Formulate control strategies: Based on the analysis results, formulate corresponding energy-saving control strategies for each area of ​​energy consumption, and build a virtual model of the building project based on the evaluation data. Simulate and deduce the energy-saving control strategy, and optimize the energy-saving measures of the energy-saving control strategy based on the deduction results. Specifically:

[0052] Formulate energy-saving control plans: integrate regions based on the tag types and energy consumption levels of each region, formulate corresponding energy-saving control strategies based on the integration results, and match the energy-saving control strategies with each region one by one;

[0053] Scheme simulation: Build a virtual building model based on the acquired building assessment data, apply the formulated energy-saving control strategy to the virtual building model, simulate the operation status and energy consumption of the building under different conditions, predict the energy-saving effect after the implementation of the strategy, and discover potential problems;

[0054] Adaptive adjustment and optimization: Optimize energy-saving control strategies based on simulation results, apply the optimized strategies to actual buildings, and obtain feedback data in real time;

[0055] Step 3: Terminal control monitoring: Integrate intelligent control systems, including partition control, location sensing, time series control and light sensing control, collect actual operation data, analyze energy usage, and conduct real-time monitoring and evaluation based on optimized energy-saving measures, specifically:

[0056] Based on the deployed sensor network and established wireless signal transmission channel, the energy usage data and equipment operation data collected from various areas and equipment in the building are monitored in real time;

[0057] Monitor and evaluate the energy usage in the building based on the optimized energy-saving measures, and determine the energy-saving efficiency of each area and equipment in the building based on the obtained feedback data and the preset threshold;

[0058] Establish a user feedback mechanism to collect opinions and suggestions from people in the building on energy use and environmental comfort, adjust and optimize the parameters and settings of various equipment in the building based on user feedback, and improve user satisfaction and energy-saving effects.

[0059] In this embodiment, by conducting energy assessment on the building, it is possible to accurately identify key areas and time periods of energy consumption, so as to formulate targeted energy-saving control strategies, which helps to reduce unnecessary energy waste, significantly improve energy utilization efficiency, and reduce building operating costs. Through sensors and intelligent algorithms, automatic adjustment and optimization of lighting, air-conditioning and other systems are achieved. By using intelligent sensing technology and adaptive control algorithms, indoor temperature and humidity are automatically adjusted according to personnel activities and outdoor environment. After implementing energy-saving control measures, continuous monitoring and evaluation are carried out to ensure the effectiveness and efficiency of various measures. Energy audits are conducted on buildings regularly to identify new energy-saving opportunities and improvement points. By implementing energy-saving control strategies, energy consumption and emissions are reduced, which helps to reduce negative impacts on the environment and achieve harmonious coexistence between buildings and the environment. Equipment parameters and settings are adjusted in real time according to actual operating data and user feedback to ensure that energy-saving goals are achieved while meeting user comfort needs.

[0060] In this embodiment, the control strategy is formulated in step 2, further comprising:

[0061] A sensor network is deployed in each area of ​​the building, including temperature sensors, humidity sensors, light sensors, and human infrared sensors. Based on the sensor network, the indoor environment and personnel activity data are monitored in real time. The indoor environment data includes the temperature, humidity, light intensity and other data of the indoor environment and the indoor personnel activities. The personnel activity data includes the number of people, location, density, etc.;

[0062] Based on the acquired indoor environment data, the current indoor light intensity and indoor temperature and humidity levels are determined. The brightness and color temperature of the lighting terminal are adjusted based on the time information and outdoor weather. The indoor temperature and humidity change trend is inferred based on the personnel activity data and outdoor temperature data. The air conditioning system is adjusted based on the inferred results.

[0063] Establish a wireless signal transmission channel with each device inside the building, control the control module of each device based on the control instructions corresponding to the received energy-saving control solution, adjust the indoor environment, and the sensor network continuously monitors changes in the indoor environment and feeds back new data.

[0064] In this embodiment, by real-time monitoring of indoor environmental data and personnel activity data through the sensor network, the indoor light intensity, temperature and humidity levels, and personnel activities can be accurately judged, so as to perform precise control and adjustment to ensure the comfort of the indoor environment, adjust the operating status of the equipment according to actual needs, avoid energy waste, predict the trend of indoor temperature and humidity changes, and adjust the operating status of the equipment in advance according to the prediction results, which helps to avoid energy consumption peaks and reduce unnecessary energy consumption, thereby achieving significant energy-saving effects. By establishing a wireless signal transmission channel and an integrated intelligent control system, remote control and intelligent management of various equipment inside the building can be achieved, which improves the operating efficiency of the equipment and reduces management costs. By optimizing control instructions and adjustment parameters, it is possible to flexibly respond to various complex situations and ensure the stability and reliability of the system.

[0065] Specifically, the control strategy formulated in step 2 also includes:

[0066] Real-time data collection time interval of temperature sensor, humidity sensor and light sensor;

[0067] According to the change of the data collection time interval of the temperature sensor, the humidity sensor and the light sensor, the first sensor time interval coefficient is obtained; wherein the first sensor time interval coefficient is obtained by the following formula: Among them, F 01 represents the first sensor time interval coefficient; f 01 、f 02 and f 03 Respectively represent the time interval coefficients corresponding to the temperature sensor, humidity sensor and light sensor; F n represents f 01 、f 02 and f 03 The coefficient values ​​corresponding to the non-maximum and non-minimum values ​​in; F0 represents the preset coefficient reference value; wherein the time interval coefficients corresponding to the temperature sensor, humidity sensor and light sensor are obtained by the following formula: Where n, m and k represent the number of data collection time intervals included in the operation of the temperature sensor, humidity sensor and light sensor respectively; G 01i , G 02i and G 03i Respectively represent the time length of the data collection time interval corresponding to the i-th temperature sensor, humidity sensor and light sensor; G c Indicates the preset time interval reference value; G 01max , G 02max and G 03max Respectively represent the maximum time length of the data collection time interval corresponding to the temperature sensor, humidity sensor and light sensor;

[0068] comparing the first sensor time interval coefficient with a preset time interval coefficient threshold;

[0069] When the time interval coefficient of the first sensor exceeds a preset time interval coefficient threshold, the data collection time interval of the human body infrared sensor is adjusted.

[0070] The technical effect of the above technical solution is: by real-time acquisition of the data acquisition time intervals of the temperature sensor, humidity sensor and light sensor, and dynamically calculating the first sensor time interval coefficient (F01) according to the changes in these time intervals, the technology can realize intelligent adjustment of the sensor data acquisition frequency. When the environmental parameters (such as temperature, humidity, light) change frequently or drastically, the sensor data acquisition time interval can be shortened accordingly to more accurately capture environmental changes; otherwise, the data collection time interval can be appropriately extended to reduce unnecessary resource consumption.

[0071] By dynamically adjusting the data collection time interval, this technology can improve the overall efficiency and response speed of the system while ensuring the accuracy of data collection. Especially in the case of large environmental changes, fast data collection and response can ensure that the system can make timely adjustments to meet the needs of the control strategy.

[0072] This technology calculates the time interval coefficient (Fn) of non-maximum and non-minimum values ​​and introduces a preset coefficient reference value (F0) for weighted calculation, making the adjustment process smoother and more reasonable. This helps to avoid resource waste or shortage caused by extreme changes in the time interval of individual sensor data collection, thereby achieving optimal resource utilization.

[0073] The calculated first sensor time interval coefficient is compared with the preset time interval coefficient threshold, and the data collection time interval of the human infrared sensor is adjusted according to the comparison result. This step enhances the stability and reliability of the system. Through the preset threshold control, excessive adjustment of the data collection time interval can be prevented, ensuring that the system can operate stably in various environments.

[0074] By intelligently adjusting the sensor data collection time interval, the technology can more accurately reflect environmental changes and provide more accurate data support for the formulation of control strategies. This not only helps to improve the overall performance of the system, but also provides users with a more comfortable and convenient experience. For example, in a smart home system, by accurately controlling environmental parameters such as indoor temperature, humidity and light, a more comfortable living environment can be created for users.

[0075] Specifically, when the time interval coefficient of the first sensor exceeds a preset time interval coefficient threshold, the data collection time interval of the human infrared sensor is adjusted, including:

[0076] When the time interval coefficient of the first sensor exceeds a preset time interval coefficient threshold, extracting the data collection time interval of the human body infrared sensor;

[0077] The data collection time interval of the human infrared sensor is used to obtain the second sensor time interval coefficient, wherein the second sensor time interval coefficient is obtained by the following formula: Among them, F 02 represents the time interval coefficient of the second sensor; F0 represents the preset coefficient reference value; f 01 、f 02 and f 03 Respectively represent the time interval coefficients corresponding to the temperature sensor, humidity sensor and light sensor; f 04 represents the time interval coefficient corresponding to the human infrared sensor, and the time interval coefficient corresponding to the human infrared sensor is obtained by the following formula: Where r represents the number of data collection time intervals included in the operation of the human infrared sensor; G 04max Indicates the maximum time length of the data collection time interval corresponding to the human infrared sensor; G 04i G represents the length of the data collection time interval corresponding to the i-th human infrared sensor; c Indicates the preset time interval reference value;

[0078] Comparing the first sensor time interval coefficient with the second sensor time interval coefficient to obtain a comparison result;

[0079] When the comparison result shows that the time interval coefficient of the first sensor exceeds the time interval coefficient of the second sensor, the data collection time interval range of the human infrared sensor is adjusted to obtain an adjusted data collection time interval range, and the adjusted data collection time interval range is obtained by the following formula: Among them, G up and G down Respectively represent the upper and lower limits of the adjusted data collection time interval range; G p It represents the average value of the data collection time interval contained in the data collection process of the human infrared sensor; F 01 Indicates the time interval coefficient of the first sensor; F 02 represents the time interval coefficient of the second sensor;

[0080] The human body infrared sensor is controlled to collect data according to the adjusted data collection time interval.

[0081] The technical effect of the above technical solution is: by real-time acquisition of the data acquisition time intervals of the temperature sensor, humidity sensor and light sensor, and dynamically calculating the first sensor time interval coefficient (F01) according to the changes in these time intervals, the technology can realize intelligent adjustment of the sensor data acquisition frequency. When the environmental parameters (such as temperature, humidity, light) change frequently or drastically, the sensor data acquisition time interval can be shortened accordingly to more accurately capture environmental changes; otherwise, the data collection time interval can be appropriately extended to reduce unnecessary resource consumption.

[0082] By dynamically adjusting the data collection time interval, this technology can improve the overall efficiency and response speed of the system while ensuring the accuracy of data collection. Especially in the case of large environmental changes, fast data collection and response can ensure that the system can make timely adjustments to meet the needs of the control strategy.

[0083] This technology calculates the time interval coefficient (Fn) of non-maximum and non-minimum values ​​and introduces a preset coefficient reference value (F0) for weighted calculation, making the adjustment process smoother and more reasonable. This helps to avoid resource waste or shortage caused by extreme changes in the time interval of individual sensor data collection, thereby achieving optimal resource utilization.

[0084] The calculated first sensor time interval coefficient is compared with the preset time interval coefficient threshold, and the data collection time interval of the human infrared sensor is adjusted according to the comparison result. This step enhances the stability and reliability of the system. Through the preset threshold control, excessive adjustment of the data collection time interval can be prevented, ensuring that the system can operate stably in various environments.

[0085] By intelligently adjusting the sensor data collection time interval, the technology can more accurately reflect environmental changes and provide more accurate data support for the formulation of control strategies. This not only helps to improve the overall performance of the system, but also provides users with a more comfortable and convenient experience. For example, in a smart home system, by accurately controlling environmental parameters such as indoor temperature, humidity and light, a more comfortable living environment can be created for users.

[0086] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A building thermal environment and building energy-saving control method for realizing demand-side response, characterized in that: The following steps are involved: Step 1: Energy assessment: Before the energy-saving renovation of the building project, an energy assessment is conducted to collect the building's assessment data, including the building type, area, orientation, and surrounding environment data. Based on the collected assessment data, the building's energy usage is analyzed and the various areas of energy consumption are identified; Step 2: Formulate control strategies: formulate corresponding energy-saving control strategies for various energy consumption areas based on the analysis results, build a virtual model of the building project based on the evaluation data, simulate and deduce the energy-saving control strategies, and optimize the energy-saving measures of the energy-saving control strategies based on the simulation results; Step 3: Terminal control and monitoring: Integrate intelligent control systems, including partition control, location sensing, time series control, and light sensing control, collect actual operation data, analyze energy usage, and conduct real-time monitoring and evaluation based on optimized energy-saving measures; The control strategy formulated in step 2 also includes: Real-time data collection time interval of temperature sensor, humidity sensor and light sensor; According to the change of the data collection time interval of the temperature sensor, the humidity sensor and the light sensor, the first sensor time interval coefficient is obtained; wherein the first sensor time interval coefficient is obtained by the following formula: Among them, F 01 represents the first sensor time interval coefficient; f 01 、f 02 and f 03 Respectively represent the time interval coefficients corresponding to the temperature sensor, humidity sensor and light sensor; F n represents f 01 、f 02 and f 03 The coefficient values ​​corresponding to the non-maximum and non-minimum values ​​in; F0 represents the preset coefficient reference value; wherein the time interval coefficients corresponding to the temperature sensor, humidity sensor and light sensor are obtained by the following formula: Where n, m and k represent the number of data collection time intervals included in the operation of the temperature sensor, humidity sensor and light sensor respectively; G 01i , G 02i and G 03i Respectively represent the time length of the data collection time interval corresponding to the i-th temperature sensor, humidity sensor and light sensor; G c Indicates the preset time interval reference value; G 01max , G 02max and G 03max Respectively represent the maximum time length of the data collection time interval corresponding to the temperature sensor, humidity sensor and light sensor; comparing the first sensor time interval coefficient with a preset time interval coefficient threshold; When the time interval coefficient of the first sensor exceeds a preset time interval coefficient threshold, the data collection time interval of the human body infrared sensor is adjusted.

2. The method for controlling building thermal environment and building energy saving by realizing demand-side response according to claim 1, characterized in that: The energy assessment in step 1 specifically includes: Data collection: Based on the construction project, obtain the type and area of ​​the building, determine the orientation of the building and the layout of each functional area, and collect information about the surrounding environment of the building, including the height, distance and vegetation of adjacent buildings; Energy situation analysis: Obtain the historical energy data of the building, analyze the energy consumption data of different time periods, identify the peak and off-peak periods, and obtain the operating status of each energy-using system in the building; Determination of energy consumption areas: Divide the building into at least one area according to its functional layout and energy consumption characteristics, label each area, and process and analyze the acquired energy consumption data based on the label type of each area; Energy consumption area assessment: Based on the processing and analysis results of each area, the energy consumption levels of the areas are compared to determine the key areas with high energy consumption. At the same time, based on the surrounding environment information obtained, the building's shading and the impact of the heat island effect are evaluated.

3. The method for controlling building thermal environment and building energy saving by realizing demand-side response according to claim 2, characterized in that: The control strategy is formulated in step 2, specifically: Formulate energy-saving control plans: integrate regions based on the tag types and energy consumption levels of each region, formulate corresponding energy-saving control strategies based on the integration results, and match the energy-saving control strategies with each region one by one; Scheme simulation: Build a virtual building model based on the acquired building assessment data, apply the formulated energy-saving control strategy to the virtual building model, simulate the operation status and energy consumption of the building under different conditions, predict the energy-saving effect after the implementation of the strategy, and discover potential problems; Adaptive adjustment and optimization: Optimize the energy-saving control strategy according to the simulation results, apply the optimized strategy to the actual building, and obtain feedback data in real time.

4. The method for controlling building thermal environment and building energy saving by realizing demand-side response according to claim 3, characterized in that: The control strategy formulated in step 2 also includes: A sensor network is deployed in each area of ​​the building, including a temperature sensor, a humidity sensor, a light sensor, and a human infrared sensor, and indoor environment and personnel activity data are monitored in real time based on the sensor network; Based on the acquired indoor environment data, the current indoor light intensity and indoor temperature and humidity levels are determined. The brightness and color temperature of the lighting terminal are adjusted based on the time information and outdoor weather. The indoor temperature and humidity change trend is inferred based on the personnel activity data and outdoor temperature data. The air conditioning system is adjusted based on the inferred results. Establish a wireless signal transmission channel with each device inside the building, control the control module of each device based on the control instructions corresponding to the received energy-saving control solution, adjust the indoor environment, and the sensor network continuously monitors changes in the indoor environment and feeds back new data.

5. The method for controlling building thermal environment and building energy saving by realizing demand-side response according to claim 4, characterized in that: When the time interval coefficient of the first sensor exceeds a preset time interval coefficient threshold, the data collection time interval of the human body infrared sensor is adjusted, including: When the time interval coefficient of the first sensor exceeds a preset time interval coefficient threshold, extracting the data collection time interval of the human body infrared sensor; The data collection time interval of the human infrared sensor is used to obtain the second sensor time interval coefficient, wherein the second sensor time interval coefficient is obtained by the following formula: Among them, F 02 represents the time interval coefficient of the second sensor; F0 represents the preset coefficient reference value; f 01 、f 02 and f 03 Respectively represent the time interval coefficients corresponding to the temperature sensor, humidity sensor and light sensor; f 04 represents the time interval coefficient corresponding to the human infrared sensor, and the time interval coefficient corresponding to the human infrared sensor is obtained by the following formula: Where r represents the number of data collection time intervals included in the operation of the human infrared sensor; G 04max Indicates the maximum time length of the data collection time interval corresponding to the human infrared sensor; G 04i G represents the length of the data collection time interval corresponding to the i-th human infrared sensor; c Indicates the preset time interval reference value; Comparing the first sensor time interval coefficient with the second sensor time interval coefficient to obtain a comparison result; When the comparison result shows that the time interval coefficient of the first sensor exceeds the time interval coefficient of the second sensor, the data collection time interval range of the human infrared sensor is adjusted to obtain an adjusted data collection time interval range, and the adjusted data collection time interval range is obtained by the following formula: Among them, G up and G down Respectively represent the upper and lower limits of the adjusted data collection time interval range; G p It represents the average value of the data collection time interval contained in the data collection process of the human infrared sensor; F 01 Indicates the time interval coefficient of the first sensor; F 02 represents the time interval coefficient of the second sensor; The human body infrared sensor is controlled to collect data according to the adjusted data collection time interval.

6. The method for controlling building thermal environment and building energy saving by realizing demand-side response according to claim 5, characterized in that: The terminal control monitoring in step 3 is specifically as follows: Based on the deployed sensor network and established wireless signal transmission channel, the energy usage data and equipment operation data collected from various areas and equipment in the building are monitored in real time; Monitor and evaluate the energy usage in the building based on the optimized energy-saving measures, and determine the energy-saving efficiency of each area and equipment in the building based on the obtained feedback data and the preset threshold; Establish a user feedback mechanism to collect opinions and suggestions from people in the building on energy use and environmental comfort, and adjust and optimize the parameters and settings of various equipment in the building based on user feedback results.

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