Intelligent building energy monitoring and optimizing system based on Internet of Things

Abstract

The invention discloses an intelligent building energy monitoring and optimizing system based on the Internet of Things, and relates to the technical field of building energy, the system comprises a turbulence capture feasibility analysis module, and the building reconstruction feasibility is evaluated through a meteorological adaptation score, a building structure score and an economy score; the transformation scheme customization design module is used for customizing special turbulence wind energy capture integrated curtain wall schemes of a super high-rise building, a middle-rise building and a low-rise building according to the height of the building; the turbulence wind energy optimization analysis module collects environment, structure, microenvironment and indoor demand data, and obtains a building wind field collaborative evaluation value through calculation; and the turbulence wind energy optimization module divides non-cooperative levels according to the evaluation value, and specifically adjusts the working parameters of the power generation unit and the angle of the outer vertical surface movable component. According to the system, full-process management from early-stage evaluation and scheme design to later-stage dynamic optimization is realized, energy production and indoor environment quality are balanced, and an innovative solution is provided for intelligent building energy management.

Description

Technical Field

[0001] The present invention relates to the field of building energy technology, and in particular to an intelligent building energy monitoring and optimization system based on the Internet of Things. Background Art

[0002] As global concern over climate change intensifies, the construction industry, a major energy consumer, urgently needs to transition from high-carbon energy consumption to low-carbon production. Traditional buildings rely on external energy inputs, but the integration of wind power, a clean and renewable energy source, into buildings is a key breakthrough. The maturity of the Internet of Things, big data, and artificial intelligence technologies is driving building energy management from passive control to active optimization. Achieving a dynamic balance between energy production, storage, and consumption through real-time data collection and intelligent analysis is a core direction for the development of intelligent buildings.

[0003] Prior art, such as the invention patent application with announcement number CN119578662A, discloses an artificial intelligence-based building data intelligent management system and method, which relates to the field of building data intelligent management technology. The system includes: a building digital twin module, an Internet of Things intelligent service module, a regional analysis module, a historical data selection module, and an intelligent sequence output module; the output end of the building digital twin module is connected to the input end of the Internet of Things intelligent service module; the output end of the Internet of Things intelligent service module is connected to the input end of the regional analysis module; the output end of the regional analysis module is connected to the input end of the historical data selection module; and the output end of the historical data selection module is connected to the input end of the intelligent sequence output module. The present invention can improve construction efficiency and realize the monitoring and optimized management of energy consumption through effective resource allocation and energy-saving measures; in terms of improved integration, it can realize data prejudgment and reduce the probability of repeated operations and ineffective construction.

[0004] In response to the above-mentioned solution, the inventors of this application have discovered that the above-mentioned technology has at least the following technical problems: 1. Existing intelligent building energy monitoring and optimization systems generally lack a systematic quantitative assessment of meteorological adaptability, building structural safety, and economic efficiency when evaluating whether a building is suitable for turbulent wind energy conversion. For example, judging the feasibility of conversion based solely on wind speed thresholds while ignoring key meteorological parameters such as turbulence intensity and seasonal changes in wind direction can lead to blind installation of equipment in areas with insufficient turbulence intensity, resulting in low actual vortex induction efficiency and power generation less than 30% of the design value. Furthermore, the lack of detailed analysis of the building structure's load-bearing capacity and the cost-benefit ratio of conversion can easily lead to the problem of "high investment, low return" and even safety hazards due to insufficient structural load.

[0005] 2. Existing systems are not differentiated in their design based on the wind field characteristics at different building heights, resulting in a mismatch between equipment selection and turbulence characteristics: most systems use a single power generation technology that cannot cover the 5-20Hz broadband turbulence. When the resonant frequency is mismatched, the power generation efficiency drops by more than 40%. The system lacks fluid control devices such as adjustable spoiler fins, making it difficult to deal with vortex street instability in strong wind environments.

[0006] 3. The existing system relies on periodic manual adjustments to equipment parameters and is unable to respond to environmental data in real time. This results in: Microenvironment degradation: Surface wind pressure coefficients are not monitored simultaneously when capturing strong turbulence, potentially causing excessive vibration of the curtain wall structure and shortening equipment life; Indoor comfort conflicts: During high summer temperatures, fixed-angle power generation components can cause building surface heat island intensity to exceed 5°C, increasing indoor air conditioning loads by 15%-20%, offsetting the benefits of wind energy; Energy supply and demand imbalances: Failure to integrate indoor demand data such as occupancy density and electricity consumption allows high power generation to be maintained during low-load periods, leading to overloaded energy storage systems and increased battery loss. In static control mode, the system is unable to achieve a balance between energy efficiency, structural safety, and indoor environmental performance through the closed loop of "data collection-evaluation and analysis-dynamic optimization." Multi-objective coordination relies on manual experience, resulting in response delays of hours or even days. Summary of the Invention

[0007] In view of the above-mentioned technical deficiencies, the purpose of the present invention is to provide an intelligent building energy monitoring and optimization system based on the Internet of Things.

[0008] In order to solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides an intelligent building energy monitoring and optimization system based on the Internet of Things, including: a turbulence capture feasibility analysis module: used to obtain the turbulence capture feasibility index corresponding to each building in the target green building demonstration area, so as to evaluate whether each building is suitable for the transformation of the turbulent wind energy capture integrated curtain wall.

[0009] Customized Renovation Scheme Design Module: This module is used to evaluate whether a building is suitable for renovation with an integrated turbulent wind energy capture curtain wall scheme, analyze the design scheme for the building's integrated turbulent wind energy capture curtain wall, and renovate the building according to the corresponding integrated turbulent wind energy capture curtain wall design scheme.

[0010] Turbulent wind energy optimization analysis module: After each building has been renovated according to the corresponding turbulent wind energy capture integrated curtain wall design plan, the environmental data, building structure data, micro-environment data and indoor demand data corresponding to each floor of each building are collected at each collection point, and then the building wind field collaborative assessment value corresponding to each floor of each building at each collection point is analyzed.

[0011] Turbulent wind energy optimization module; used to optimize and adjust the turbulent wind energy equipment corresponding to each floor to be adjusted based on the building wind field collaborative evaluation value corresponding to each collection point, each building and each floor.

[0012] The beneficial effects of the present invention are as follows: 1. In the embodiment of the present invention, an evaluation model is constructed from three aspects: meteorological adaptability, building structure safety, and economy, through a turbulence capture feasibility analysis module. The transformation is initiated only when all three indicators meet the standards, thereby avoiding equipment inefficiency or structural risks caused by environmental mismatch. For example, in strong wind areas, typhoon-resistant Venturi wind ducts are preferred, and in weak wind areas in the city center, triboelectric nanogenerators with low starting wind speeds are used to ensure that the equipment is accurately matched with the wind environment. At the same time, differentiated solutions are customized for differences in building heights: super-high-rise buildings use piezoelectric-electromagnetic composite power generation units to deal with broadband turbulence, mid-rise buildings use PVDF piezoelectric films to balance light transmission and power generation requirements, and low-rise buildings use zigzag guide plates to induce low-wind-speed vortices, achieving "tailor-made" transformation and increasing wind energy capture efficiency by 20%-50%.

[0013] 2. In an embodiment of the present invention, IoT sensors are used to collect environmental data, building structure data, microenvironmental data, and indoor demand data in real time to construct a collaborative assessment model for building wind farms. This normalizes multi-dimensional data into quantitative assessment values, accurately locating inefficient areas. Based on the assessment results, equipment parameters are dynamically optimized through a three-level response mechanism: Level 1 issues require only fine-tuning of the motor sampling frequency and component angles; Level 2 issues require expanding the resonant frequency range and jointly adjusting adjacent floor components; Level 3 issues involve hardware upgrades and structural reconstruction. This "monitoring-analysis-tiered disposal" closed loop shortens the system's response speed from the manually adjusted "quarterly level" to the "minute level," increasing the effective power generation time throughout the year by 15%-30%.

[0014] 3. The present invention integrates turbulent wind energy capture with building functions to achieve the dual goals of "power generation and environmental regulation." For example, the adjustable spoiler fins on super-high-rise buildings enhance vortex induction while dynamically adjusting their angles via servo motors, reducing the risk of structural vibration by over 30%. The louvered resonant curtain walls on mid-rise buildings adjust their angles via electric actuators, ensuring power generation efficiency while keeping the indoor glare index below 20 and noise levels below 45dB. The zigzag deflectors on low-rise buildings automatically adjust to seasonal wind direction, improving wind energy capture efficiency while reducing the intensity of the surrounding heat island by 2-3°C. Furthermore, the system integrates indoor occupancy density with electricity demand data to prioritize energy supply in high-load areas, increasing renewable energy self-sufficiency by 25%-40%.

[0015] 4. In the embodiment of the present invention, during the feasibility analysis phase, cost-effective projects are screened through economic evaluation, and standardized modules are used to reduce initial investment. At the same time, the health status of equipment is monitored in real time through the Internet of Things to achieve preventive maintenance, reducing operation and maintenance costs by more than 30%. On the technical level, the system integrates fluid mechanics, materials science, and intelligent control technology, and pioneers a hierarchical design method of "building height-wind field characteristics-equipment selection", as well as a multi-objective optimization algorithm of "wideband capture + dynamic vibration reduction + indoor adaptation", forming a technical system with independent intellectual property rights. This solution can be replicated in urban complexes, industrial parks and other scenarios, providing an integrated "power generation-energy storage-energy use" model for green buildings, and helping to achieve carbon emission reduction goals on a large scale in the construction industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only 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.

[0017] Figure 1 This is a schematic diagram of the system module connection of the present invention. DETAILED DESCRIPTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0019] The present invention is implemented as follows Figure 1 As shown in FIG, the smart building energy monitoring and optimization system based on the Internet of Things includes: a turbulence capture feasibility analysis module, a transformation scheme customized design module, a turbulent wind energy optimization analysis module, a turbulent wind energy optimization module and a database.

[0020] The transformation scheme customized design module is respectively connected with the turbulence capture feasibility analysis module and the turbulence wind energy optimization analysis module, and the database is connected with the turbulence wind energy optimization module.

[0021] Turbulence capture feasibility analysis module: used to obtain the turbulence capture feasibility index corresponding to each building in the target green building demonstration area, so as to evaluate whether each building is suitable for the renovation of turbulent wind energy capture integrated curtain wall.

[0022] In a specific embodiment, the turbulence capture feasibility index corresponding to each building in the target green building demonstration area is obtained, and the specific acquisition process is as follows: the turbulence capture feasibility index corresponding to each building is obtained, and the turbulence capture feasibility index includes a meteorological adaptability score, a building structure score and an economic score, and the meteorological adaptability score, the building structure score and the economic score corresponding to each building are respectively compared with the set standard meteorological adaptability score, the standard building structure score and the standard economic score. If the meteorological adaptability score, the building structure score and the economic score corresponding to a certain building are all greater than or equal to the set standard meteorological adaptability score, the standard building structure score and the standard economic score, then the building is evaluated to be suitable for the renovation of the turbulent wind energy capture integrated curtain wall. If one of the meteorological adaptability score, the building structure score or the economic score corresponding to a certain building is less than the set standard meteorological adaptability score, the standard building structure score or the standard economic score, then the building is evaluated to be not suitable for the renovation of the turbulent wind energy capture integrated curtain wall.

[0023] It should be noted that 1. Meteorological Adaptability Score Acquisition Method: The meteorological adaptability score is calculated by collecting data such as annual average wind speed, dominant wind direction frequency, and turbulence intensity, combined with historical meteorological station records and short-term field measurements, to calculate the proportion of effective power generation hours. For example, the annual cumulative hours of wind speeds between 3 and 12 m / s are greater than 2000 hours. CFD simulation verifies that a wind pressure distribution Cp less than -1.5 on the building surface indicates high potential. Finally, a score of 0 to 100 is weighted using a weighting of 30% for wind speed, 40% for turbulence intensity, and 30% for wind direction adaptability.

[0024] 2. Building structure acquisition method: Extract parameters such as height, width-to-depth ratio, facade curvature from the BIM model, and combine them with shaking table tests or finite element analysis to obtain natural frequencies. Key indicators include curtain wall unit surface density <20kg / m 2 The score ranges from 0 to 100, with a weight of 50% for geometric adaptability and 50% for structural safety.

[0025] 3. Economic Score Determination Method: The economic score is calculated by forecasting annual power generation, combining CFD with equipment efficiency curves, and comparing local peak and off-peak electricity prices, carbon trading prices, and green building subsidies to calculate the return on investment. Grid demand response benefits and operation and maintenance costs are also evaluated. The final score is weighted, with energy benefits weighted 60% and policy economics weighted 40%, resulting in a score ranging from 0 to 100.

[0026] Customized Renovation Scheme Design Module: This module is used to evaluate whether a building is suitable for renovation with an integrated turbulent wind energy capture curtain wall scheme, analyze the design scheme for the building's integrated turbulent wind energy capture curtain wall, and renovate the building according to the corresponding integrated turbulent wind energy capture curtain wall design scheme.

[0027] In a specific embodiment, the design scheme of the turbulent wind energy capture integrated curtain wall corresponding to the building is analyzed. The specific analysis process is as follows: A1. Obtain the building height corresponding to the building. If the building is a super high-rise building, the design scheme of the turbulent wind energy capture integrated curtain wall is: use a piezoelectric-electromagnetic composite power generation unit, wherein the piezoelectric layer thickness is 0.1-0.5mm, the electromechanical coupling coefficient is greater than 0.6, and the electromagnetic generator power density is ≥50mW / cm 3 , the resonance frequency is 5-20Hz. At the same time, the facade is equipped with adjustable spoiler fins. The length of the fins is 1 / 10-1 / 5 of the width of the building section, and is equipped with a servo motor to automatically adjust the angle.

[0028] A2. If the building is a mid-rise building, the design of the integrated curtain wall for turbulent wind energy capture is as follows: select a PVDF piezoelectric thin film generator with a film thickness of 50-100μm, an output voltage of 5-20V, and a power density of 10-30mW / m 2 , light transmittance > 85%. At the same time, the facade is installed with an adjustable angle louver resonant power generation curtain wall. The size of each louver is 2-3m long and 0.5-0.8m wide. It is composed of a lightweight aluminum alloy frame with embedded PVDF piezoelectric film, and the angle is adjusted by an electric push rod.

[0029] A3. If the building is a low-rise structure, the design of the integrated curtain wall for turbulent wind energy capture is as follows: use an oscillating electromagnetic generator with a resonant frequency of 2-5 Hz and a single module power output of 5-20 W. At the same time, install an adjustable zigzag guide plate on the facade, with a plate height of 0.3-0.5m, an initial zigzag angle of 30°-45°, and a servo motor for automatic angle adjustment.

[0030] It should be noted that super high-rise buildings refer to residential buildings with a height greater than 100 meters or public buildings with a height greater than 24 meters, mid-rise buildings refer to residential buildings between 27 meters and 100 meters or public buildings between 15 meters and 24 meters, and low-rise buildings refer to residential buildings less than or equal to 27 meters and public buildings less than or equal to 15 meters in height.

[0031] It should be noted that when installing an integrated curtain wall for turbulent wind energy capture, the installation process must be categorized according to building height. For super-high-rise buildings, the piezoelectric-electromagnetic composite power generation unit is prefabricated in the factory. The piezoelectric layer thickness is strictly controlled to 0.1-0.5mm to ensure that the electromechanical coupling coefficient meets the standard. After the unit is embedded in the curtain wall frame, adjustable spoiler fins are installed on the building facade. They are connected to the intelligent control system via a servo motor to ensure angle adjustment accuracy. When installing in mid-rise buildings, the customized PVDF piezoelectric film is embedded in the lightweight aluminum alloy louver frame and fixed to the curtain wall keel via an electric push rod. The electric push rod stroke is adjusted to achieve flexible adjustment of the louver angle. For low-rise buildings, the swinging electromagnetic generator is first installed to ensure its resonant frequency is compatible with low wind speed environments. The serrated deflector is then installed on the facade via a servo motor. The initial motor angle is calibrated to 30°-45°. Finally, the electrical connection of each component and the system debugging are completed to ensure the coordinated operation of the power generation unit and the movable structure.

[0032] Turbulent wind energy optimization analysis module: After each building has been renovated according to the corresponding turbulent wind energy capture integrated curtain wall design plan, the environmental data, building structure data, micro-environment data and indoor demand data corresponding to each floor of each building are collected at each collection point, and then the building wind field collaborative assessment value corresponding to each floor of each building at each collection point is analyzed.

[0033] In a specific embodiment, the environmental data include turbulence intensity, maximum gust wind speed and radiation; the building structure data include curtain wall unit surface density and glass transmittance; the microenvironment data include surface wind pressure coefficient, heat island intensity and turbulent energy efficiency; and the indoor demand data include occupant density, glare index and total electricity consumption.

[0034] It is important to note that, first, environmental data parameter acquisition methods: Turbulence intensity: Ultrasonic anemometers or three-cup anemometers placed around the building continuously monitor wind speed fluctuations, typically at a sampling frequency of 10-20 Hz. Using this high-frequency wind speed data, the ratio of the standard deviation of the instantaneous wind speed to the average wind speed is calculated to obtain the turbulence intensity value, which reflects the irregularities of atmospheric flow.

[0035] Maximum gust wind speed: Use a high-precision propeller anemometer to capture peak wind speeds over a short period of time in real time. The sensor should be mounted on top of a building or in an open area nearby to avoid obstructions. The data acquisition system records and filters the maximum gust wind speed during the monitoring period.

[0036] Radiation: Use a global radiation sensor to measure the total solar radiation flux. The sensor needs to be installed horizontally and without obstruction to directly sense the shortwave radiation of the sun. The data logger records the radiation in minutes or hours.

[0037] 2. Methods for obtaining building structure data parameters: Curtain wall unit surface density: Obtain the unit area density of curtain wall panel materials by referring to architectural design drawings or curtain wall project completion data.

[0038] Glass transmittance: Use a transmittance tester to measure the curtain wall glass samples, measure the transmittance in the visible light band and take the average value as the glass transmittance.

[0039] 3. Microenvironmental Data Parameter Acquisition Methods: Surface Wind Pressure Coefficient: Obtained through wind tunnel testing or on-site wind pressure monitoring. In wind tunnel testing, a scaled-down building model is placed in an airflow, and pressure sensors are used to measure the static pressure at each surface point. This pressure coefficient is then compared with the incoming static pressure to calculate the wind pressure coefficient. On-site monitoring involves placing wind pressure transmitters on the building's exterior, simultaneously recording wind speed and direction data, and inversely calculating the wind pressure coefficient using the Bernoulli equation.

[0040] Heat island intensity: A multi-point temperature monitoring network is used. Thermocouples or infrared thermal imagers are placed at various heights around the building perimeter. The temperature difference between the building area and a control area is measured simultaneously. This difference represents the heat island intensity. Continuous monitoring over a long period of time, under typical weather conditions, is required to eliminate occasional errors.

[0041] Turbulent energy efficiency: The instantaneous velocity pulsation in the flow field is measured using a laser Doppler velocimeter or particle image velocimetry technology, and the ratio of turbulent energy to energy consumption index is calculated to obtain the turbulent energy efficiency.

[0042] IV. Methods for Obtaining Indoor Demand Data Parameters: Crowd Density: Count the number of people in a specific area in real time using infrared thermal imaging sensors, Wi-Fi positioning, or access control systems, and divide the number by the area to obtain the density. For dynamically changing scenes, video analysis algorithms can be used to track the distribution of people in real time, and data smoothing can be performed based on time-based patterns.

[0043] Glare Index (UGR): Use a glare meter to measure the brightness, position, and background brightness of each light source on a typical indoor working plane. Calculate the UGR value using the CIE standard formula. This measurement simulates a real-world lighting scenario, taking into account the effects of factors such as curtain obstruction and lamp type on glare.

[0044] Total electricity consumption: Smart meters or power monitoring systems collect real-time active and reactive power data for each floor and area of ​​the building, accumulating total electricity consumption over time. This data must be integrated into the building energy management system and analyzed in conjunction with equipment operating status to ensure accuracy and traceability of energy consumption data.

[0045] In a specific embodiment, the analysis obtains the building wind field synergy evaluation value corresponding to each floor of each building at each collection point. The specific analysis process is as follows: analyze the environmental adaptation value, building structure adaptation value, microenvironment adaptation value and indoor demand adaptation value corresponding to each floor of each building collected at each collection point, and perform normalization processing, and substitute them into the building wind field synergy evaluation value analysis model to obtain the building wind field synergy evaluation value corresponding to each floor of each building at each collection point.

[0046] It should be noted that the analysis process of the building wind field collaborative evaluation value corresponding to each floor of each building at each collection point is as follows: the environmental adaptation value, building structure adaptation value, microenvironment adaptation value and indoor demand adaptation value corresponding to each floor of each building collected at each collection point are recorded as and m represents the number corresponding to each collection point, m is a positive integer, k represents the number corresponding to each building, k is a positive integer, g represents the number corresponding to each floor, g is a positive integer, substitute into the calculation formula: The building wind field collaborative assessment value corresponding to each collection point, each building and each floor is obtained Among them, Q′, F′, P′, and X′ are the standard environment adaptation value, standard building structure adaptation value, standard microenvironment adaptation value, and standard indoor demand adaptation value corresponding to the set building floor, respectively.

[0047] In a specific embodiment, the analysis is performed on the environmental adaptation value, building structure adaptation value, microenvironment adaptation value and indoor demand adaptation value corresponding to each floor of each building collected by each collection point. The specific analysis process is as follows: the environmental data, building structure data, microenvironment data and indoor demand data corresponding to each floor of each building collected by each collection point are normalized and used as input items, respectively input into the environmental adaptation value analysis model, the building structure adaptation value analysis model, the microenvironment adaptation value analysis model and the indoor demand adaptation value analysis model, and the environmental adaptation value, building structure adaptation value, microenvironment adaptation value and indoor demand adaptation value corresponding to each floor of each building collected by each collection point are input.

[0048] It should be noted that the analysis process of the environmental adaptation value corresponding to each floor of each building collected by each collection point is as follows: the turbulence intensity, maximum gust wind speed and radiation corresponding to each floor of each building collected by each collection point are recorded as and Substitute into the analysis formula Get the environmental adaptation value corresponding to each floor of each building collected by each collection point In this way, the building structure adaptation value, microenvironment adaptation value and indoor demand adaptation value corresponding to each floor of each building collected by each collection point are analyzed and obtained.

[0049] Turbulent wind energy optimization module; used to optimize and adjust the turbulent wind energy equipment corresponding to each floor to be adjusted based on the building wind field collaborative evaluation value corresponding to each collection point, each building and each floor.

[0050] In a specific embodiment, the turbulent wind energy optimization module further includes a turbulence monitoring and evaluation unit;

[0051] The turbulence monitoring judgment unit is used to evaluate whether each collection point, each building, and each floor needs to optimize and adjust the turbulence wind energy plan based on the building wind field coordination evaluation value corresponding to each collection point, each building, and each floor.

[0052] In a specific embodiment, the evaluation of whether each collection point, each building, and each floor needs to optimize and adjust the turbulent wind energy scheme is carried out, and the specific judgment process is as follows: the building wind field synergy evaluation value corresponding to each collection point, each building, and each floor is compared with the standard building wind field synergy evaluation value interval set for the corresponding floor. If the building wind field synergy evaluation value corresponding to a certain floor of a certain building at a certain collection point is within the standard building wind field synergy evaluation value interval set for the corresponding floor, then it is evaluated that the turbulent wind energy scheme does not need to be optimized and adjusted for the floor of the building at the collection point. If the building wind field synergy evaluation value corresponding to a certain floor of a certain building at a certain collection point is not within the standard building wind field synergy evaluation value interval set for the corresponding floor, then it is evaluated that the turbulent wind energy scheme needs to be optimized and adjusted for the floor of the building at the collection point, and each collection point, each building, and each floor that needs to optimize and adjust the turbulent wind energy scheme is recorded as a floor to be adjusted.

[0053] In a specific embodiment, the turbulent wind energy equipment corresponding to each floor to be adjusted is optimized and adjusted, and the specific optimization and adjustment process is as follows: C1. Analyze the building wind field incoordination level corresponding to each floor to be adjusted, and the building wind field incoordination level includes level one, level two and level three.

[0054] C2. If the wind field incoordination level of a building corresponding to a floor to be adjusted is level 1, the optimized adjustment value of the turbulent wind energy equipment is as follows: the cut-in wind speed threshold of the power generation unit is reduced to 2.5 m / s, and the maximum power point tracking sampling frequency is increased from 1 to 20 Hz. At the same time, the spoiler fin angle of the super high-rise building is increased by 5° from the current basis; the louver curtain wall angle of the mid-rise building is adjusted to an angle of 30°-45° with the prevailing wind direction; and the zigzag deflector angle of the low-rise building is increased by 5°.

[0055] C3. If the wind field incoordination level of the building corresponding to a floor to be adjusted is level 2, the optimized adjustment values ​​for the turbulent wind energy equipment are as follows: switch the generator to "wideband response mode," expand the resonant frequency adjustment range of the piezoelectric unit to 3-25 Hz, and dynamically increase the load impedance of the electromagnetic generator by 20% from the default value. At the same time, the spoiler fins of super-high-rise buildings are grouped, with each group consisting of 10 floors, and the angle within the group is uniformly adjusted to 45°-60° with the dominant wind direction in the area. In the double-layer louver curtain wall of mid-rise buildings, the outer layer is fixed at 45° for wind diversion, and the dynamic adjustment range of the inner layer is expanded to 15°-55°. The angle of the zigzag deflector of low-rise buildings is expanded to 40°-60°.

[0056] C4. If the wind field uncoordinated level of a building corresponding to a floor to be adjusted is level three, the optimized adjustment values ​​of the turbulent wind energy equipment are as follows: the thickness of the piezoelectric layer of the generator is optimized to 0.08-0.6mm, and the electromechanical coupling coefficient is increased to >0.7; the damping ratio range of the power generation unit is adjusted to 0.05-0.2 by dynamically adjusting the turbulence intensity; at the same time, the angle of the spoiler fins of the super high-rise building is adjusted to 45°; the bending angle of the louver curtain wall of the mid-rise building is adjusted to 20°; and the sawtooth angle of the low-rise building is fixed at 50°.

[0057] In a specific embodiment, the analysis of the building wind field incoordination level corresponding to each floor to be adjusted is carried out as follows: the building wind field synergy evaluation value corresponding to each floor to be adjusted is compared with the building wind field synergy evaluation value interval corresponding to each building wind field incoordination level in the database. If the building wind field synergy evaluation value corresponding to a floor to be adjusted is within the building wind field synergy evaluation value interval corresponding to a building wind field incoordination level in the database, the building wind field incoordination level in the database is recorded as the building wind field incoordination level corresponding to the floor to be adjusted.

[0058] It should be noted that the database is used to store the building wind farm coordination evaluation value intervals corresponding to the uncoordinated levels of each building wind farm.

[0059] The above content is merely an example and explanation of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the scope of protection of the present invention.

Claims

1. The intelligent building energy monitoring and optimization system based on the Internet of Things is characterized by: include: Turbulence Capture Feasibility Analysis Module: This module is used to obtain the turbulence capture feasibility index for each building within the target green building demonstration area, thereby assessing whether each building is suitable for retrofitting with an integrated curtain wall system for turbulent wind energy capture. Customized Retrofit Design Module: This module is used to evaluate whether a building is suitable for retrofitting with an integrated turbulent wind energy capture curtain wall solution, analyze the corresponding design scheme for the building, and retrofit the building according to the corresponding integrated turbulent wind energy capture curtain wall design scheme. Turbulent Wind Energy Optimization Analysis Module: This module is used to collect environmental data, building structure data, microenvironmental data, and indoor demand data for each floor of each building at each collection point after each building has been renovated according to the corresponding turbulent wind energy capture integrated curtain wall design scheme. This module then analyzes and obtains the building wind field synergy assessment value for each floor of each building at each collection point. Turbulent wind energy optimization module; It is used to optimize and adjust the turbulent wind energy equipment corresponding to each floor to be adjusted based on the building wind field collaborative evaluation value corresponding to each collection point, each building and each floor.

2. The smart building energy monitoring and optimization system based on the Internet of Things according to claim 1, characterized in that: The specific acquisition process of the turbulence capture feasibility index corresponding to each building in the target green building demonstration area is as follows: Obtain the turbulence capture feasibility index corresponding to each building. The turbulence capture feasibility index includes a meteorological adaptability score, a building structure score, and an economic score. Compare the meteorological adaptability score, building structure score, and economic score corresponding to each building with the set standard meteorological adaptability score, standard building structure score, and standard economic score, respectively. If the meteorological adaptability score, building structure score, and economic score corresponding to a building are all greater than or equal to the set standard meteorological adaptability score, standard building structure score, and standard economic score, then the building is evaluated as suitable for the renovation of an integrated curtain wall for turbulent wind energy capture. If any of the meteorological adaptability score, building structure score, or economic score corresponding to a building is less than the set standard meteorological adaptability score, standard building structure score, or standard economic score, then the building is evaluated as not suitable for the renovation of an integrated curtain wall for turbulent wind energy capture.

3. The smart building energy monitoring and optimization system based on the Internet of Things according to claim 2, characterized in that: The design scheme of the turbulent wind energy capture integrated curtain wall corresponding to the building is analyzed. The specific analysis process is as follows: A1. Obtain the building height. If the building is a super high-rise building, the design of the integrated curtain wall for turbulent wind energy capture is as follows: Use a piezoelectric-electromagnetic composite power generation unit, where the piezoelectric layer thickness is 0.1-0.5mm, the electromechanical coupling coefficient is greater than 0.6, and the electromagnetic generator power density is ≥50mW / cm 3 , the resonance frequency is 5-20Hz. At the same time, the facade is equipped with adjustable spoiler fins. The length of the fins is 1 / 10-1 / 5 of the building section width, and the servo motor is equipped to automatically adjust the angle. A2. If the building is a mid-rise, the design of the integrated turbulent wind energy capture curtain wall is as follows: select a PVDF piezoelectric thin film generator with a film thickness of 50-100μm, an output voltage of 5-20V, a power density of 10-30mW / m2, and a light transmittance greater than 85%. At the same time, install an angle-adjustable louver-style resonant power generation curtain wall on the facade. Each louver is 2-3m long and 0.5-0.8m wide, and is composed of a lightweight aluminum alloy frame embedded with a PVDF piezoelectric film. The angle is adjusted by an electric actuator. A3. If the building is a low-rise structure, the design of the integrated curtain wall for turbulent wind energy capture is as follows: use an oscillating electromagnetic generator with a resonant frequency of 2-5 Hz and a single module power output of 5-20 W. At the same time, install an adjustable zigzag guide plate on the facade, with a plate height of 0.3-0.5m, an initial zigzag angle of 30°-45°, and a servo motor for automatic angle adjustment.

4. The smart building energy monitoring and optimization system based on the Internet of Things according to claim 1, characterized in that: The environmental data include turbulence intensity, maximum gust wind speed and radiation; the building structure data include curtain wall unit surface density and glass transmittance; the microenvironment data include surface wind pressure coefficient, heat island intensity and turbulent energy efficiency; and the indoor demand data include occupant density, glare index and total electricity consumption.

5. The smart building energy monitoring and optimization system based on the Internet of Things according to claim 4, characterized in that: The analysis obtains the building wind field coordination evaluation value corresponding to each collection point, each building, and each floor. The specific analysis process is as follows: The environmental adaptation value, building structure adaptation value, microenvironment adaptation value and indoor demand adaptation value corresponding to each floor of each building collected at each collection point are analyzed, and normalized. The values ​​are substituted into the building wind field synergy evaluation value analysis model to obtain the building wind field synergy evaluation value corresponding to each floor of each building at each collection point.

6. The smart building energy monitoring and optimization system based on the Internet of Things according to claim 5, characterized in that: The analysis collects the environmental adaptation value, building structure adaptation value, microenvironment adaptation value and indoor demand adaptation value corresponding to each floor of each building at each collection point. The specific analysis process is as follows: The environmental data, building structure data, microenvironment data and indoor demand data corresponding to each floor of each building collected by each collection point are normalized and used as input items to be input into the environmental adaptation value analysis model, the building structure adaptation value analysis model, the microenvironment adaptation value analysis model and the indoor demand adaptation value analysis model respectively. The environmental adaptation value, building structure adaptation value, microenvironment adaptation value and indoor demand adaptation value corresponding to each floor of each building collected by each collection point are input.

7. The smart building energy monitoring and optimization system based on the Internet of Things according to claim 1, characterized in that: The turbulent wind energy optimization module also includes a turbulence monitoring and evaluation unit; The turbulence monitoring judgment unit is used to evaluate whether each collection point, each building, and each floor needs to optimize and adjust the turbulence wind energy plan based on the building wind field coordination evaluation value corresponding to each collection point, each building, and each floor.

8. The smart building energy monitoring and optimization system based on the Internet of Things according to claim 7, characterized in that: The specific judgment process for evaluating whether each collection point, each building, and each floor needs to optimize and adjust the turbulent wind energy solution is as follows: The building wind field synergy evaluation value corresponding to each floor of each building at each collection point is compared with the standard building wind field synergy evaluation value interval set for the corresponding floor. If the building wind field synergy evaluation value corresponding to a floor of a building at a certain collection point is within the standard building wind field synergy evaluation value interval set for the corresponding floor, it is assessed that no optimization adjustment of the turbulent wind energy scheme is required for the floor of the building at this collection point. If the building wind field synergy evaluation value corresponding to a floor of a building at a certain collection point is not within the standard building wind field synergy evaluation value interval set for the corresponding floor, it is assessed that optimization adjustment of the turbulent wind energy scheme is required for the floor of the building at this collection point, and each collection point, building, and floor that requires optimization adjustment of the turbulent wind energy scheme is recorded as a floor to be adjusted.

9. The IoT-based smart building energy monitoring and optimization system according to claim 8, wherein: The turbulent wind energy equipment corresponding to each floor to be adjusted is optimized and adjusted. The specific optimization and adjustment process is as follows: C1. Analyze the building wind field incoordination level corresponding to each floor to be adjusted. The building wind field incoordination levels include level 1, level 2, and level 3. C2. If the wind farm incoordination level of a building corresponding to a floor to be adjusted is level 1, the optimized adjustment values ​​for the turbulent wind energy equipment are as follows: reduce the cut-in wind speed threshold of the power generation unit to 2.5 m / s, increase the maximum power point tracking sampling frequency from 1 to 20 Hz, increase the spoiler fin angle of the super-high-rise building by 5° from the current level, adjust the louver curtain wall angle of the mid-rise building to 30°-45° with the prevailing wind direction, and increase the zigzag deflector angle of the low-rise building by 5°. C3. If the building wind field mismatch level corresponding to a floor to be adjusted is level 2, the optimized adjustment values ​​for the turbulent wind energy equipment are as follows: switch the generator to "wideband response mode," expand the piezoelectric unit's resonant frequency adjustment range to 3-25Hz, and dynamically increase the electromagnetic generator's load impedance by 20% from the default value. Furthermore, the spoiler fins of super-high-rise buildings are grouped into groups of 10 floors, with the angle within each group uniformly adjusted to 45°-60° with the prevailing wind direction in the area. For double-layer louver curtain walls of mid-rise buildings, the outer layer is fixed at a 45° wind deflection angle, while the inner layer's dynamic adjustment range is expanded to 15°-55°. The angle of the zigzag deflectors of low-rise buildings is increased to 40°-60°. C4. If the wind field uncoordinated level of a building corresponding to a floor to be adjusted is level three, the optimized adjustment values ​​of the turbulent wind energy equipment are as follows: the thickness of the piezoelectric layer of the generator is optimized to 0.08-0.6mm, and the electromechanical coupling coefficient is increased to >0.7; the damping ratio range of the power generation unit is adjusted to 0.05-0.2 by dynamically adjusting the turbulence intensity; at the same time, the angle of the spoiler fins of the super high-rise building is adjusted to 45°; the bending angle of the louver curtain wall of the mid-rise building is adjusted to 20°; and the sawtooth angle of the low-rise building is fixed at 50°.

10. The smart building energy monitoring and optimization system based on the Internet of Things according to claim 9, characterized in that: The specific analysis process for analyzing the building wind field incoordination level corresponding to each floor to be adjusted is as follows: The building wind field synergy evaluation value corresponding to each floor to be adjusted is compared with the building wind field synergy evaluation value interval corresponding to each building wind field incoordination level in the database. If the building wind field synergy evaluation value corresponding to a floor to be adjusted is within the building wind field synergy evaluation value interval corresponding to a building wind field incoordination level in the database, the building wind field incoordination level in the database is recorded as the building wind field incoordination level corresponding to the floor to be adjusted.

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