Load management operation method for comprehensive energy optimization configuration

Abstract

The invention discloses a load management operation method for comprehensive energy optimal configuration, and relates to the technical field of energy management, and the method comprises the following specific steps: microclimate partition division: carrying out the comprehensive field exploration of a target region, collecting the landform, building layout and vegetation coverage data, analyzing the influence of each factor on the microclimate formation, and carrying out the calculation of the microclimate; according to the method, a partition division basis is determined according to the difference between airflow and heat caused by topographic relief, the influence of a building on sunlight and ventilation and local microclimate characteristics of vegetation construction, and a linkage model comprehensively considering the relationship among a microclimate partition state, a building adjustment behavior and an energy load is established; the complex relation among microclimate parameter changes, building adjustment action changes and energy load changes is accurately reflected, meanwhile, according to state changes after building adjustment, the energy management system can dynamically optimize an energy configuration scheme, unnecessary energy transmission and conversion links are reduced, and the energy utilization rate is improved. And deep optimization configuration of comprehensive energy of the whole area from generation, transportation to use is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of energy management, and in particular to a load management operation method for comprehensive energy optimization configuration. Background Art

[0002] In today's society, with the acceleration of urbanization and the rapid development of various large-scale parks, communities and buildings, energy management has become an important factor affecting the sustainable development of society. These areas usually integrate multiple functions such as living, office, business, and leisure. The energy demand is complex and huge. Microclimate is one of the key factors affecting building energy consumption. Its zoning control technology has gradually become an important means to improve energy efficiency. At the same time, the continuous advancement of building adaptation technology has made it possible to achieve refined energy management. By real-time monitoring of the internal and external environmental parameters of the building and dynamically adjusting the building operation strategy, energy consumption can be effectively reduced and energy efficiency can be improved.

[0003] However, the traditional energy management model seems to be unable to cope with complex demands. On the one hand, the existing management model ignores the refined regulation of microclimate zoning when managing energy loads, which often leads to irrational energy allocation and serious waste. Traditional energy management is mostly based on macro-regional or overall building regulation, and fails to fully consider the specific impact of microclimate differences on energy consumption. On the other hand, traditional technology ignores the dynamic adaptation ability of the building itself and its adaptability to the energy load, making it impossible for the building to flexibly adjust according to its actual state, further affecting the efficiency and rationality of energy utilization. Therefore, the traditional energy management model cannot meet the current needs for refined energy management, efficient utilization and comprehensive optimization configuration.

[0004] In view of the above problems, it is necessary to optimize the existing load management operation method. By combining microclimate zoning control, dynamic adjustment of the building itself, and establishing a linkage mechanism with the energy load, all-round and refined management of energy consumption load and in-depth optimization configuration of the comprehensive energy of the entire region can be achieved. Therefore, it is of great significance to develop a load management operation method with comprehensive energy optimization configuration that can comprehensively realize the above characteristics. Summary of the invention

[0005] The purpose of the present invention is to make up for the shortcomings of the prior art and provide a load management operation method with comprehensive energy optimization configuration. By utilizing GIS technology to divide the target area into microclimate zones, and rationally deploying intelligent meteorological monitoring and control equipment in each zone, microclimate parameters are collected in real time. At the same time, IoT sensors are installed inside the building and at key parts of the enclosure structure to continuously monitor the building status. Based on these real-time data, through big data analysis technology and machine learning algorithms, a linkage model is established that comprehensively considers the relationship between the microclimate zone status, building adaptation behavior and energy load. The model can accurately reflect the complex relationship between various factors, and according to the current parameters and preset energy optimization goals, the corresponding control instructions are calculated and sent to the microclimate control equipment and building adaptation-related equipment in the zone, thereby minimizing energy waste and significantly improving energy utilization efficiency.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a load management operation method for comprehensive energy optimization configuration, the method comprising the following specific steps:

[0007] Microclimate zoning: Conduct a comprehensive field survey of the target area, collect data on topography, building layout and vegetation coverage, analyze the impact of various factors on the formation of microclimate, determine the basis for zoning based on the airflow and heat differences caused by terrain undulations, the impact of buildings on sunlight and ventilation, and the local microclimate characteristics created by vegetation, and use geographic information system technology to digitize the field survey data and import it into the software platform. Perform microclimate zoning through cluster analysis, generate zoning boundaries and numbers to identify each zoning, and form a microclimate zoning map to display the zoning range and location relationship;

[0008] Installation and layout of equipment in microclimate zones: In each microclimate zone, the installation location and quantity of intelligent meteorological monitoring equipment are planned according to the area, shape and spatial layout characteristics of the zone. At the same time, small spray cooling systems, adjustable ventilation corridors, shading facilities and small heating devices are arranged according to the activities of people, heat sources, sunshine and wind direction in the zone to ensure that each device can play an effective role and coordinately regulate the microclimate in the zone;

[0009] Building adaptation monitoring and strategy formulation: Install heat flow sensors at key locations of building envelope structures to accurately measure their thermal performance parameters, arrange light intensity sensors at different locations in different functional areas of the building to accurately monitor lighting conditions, install personnel activity sensors and space occupancy monitoring equipment in each functional space to grasp the space usage status in real time, and integrate the collected real-time data into the building information model. Use big data analysis technology to pre-process and deeply mine the data, and formulate variable sunshade curtain opening and closing angles, adjustable ventilation window openings, and indoor partition layout adjustment strategies based on the analysis results to optimize the building's internal environment and energy utilization;

[0010] Establishment of linkage model: historical microclimate data is obtained from intelligent meteorological monitoring equipment in each microclimate zone, historical records of building adaptation are obtained from building-related records, and energy consumption data is obtained and integrated from building energy metering equipment. A machine learning algorithm is used to build a linkage model, with microclimate parameters and building adaptation-related data as input variables, and energy consumption load data as output variables. The model is trained by dividing the training set and the validation set, and the model performance is verified using the validation set. If the accuracy requirements are not met, the model is optimized until it can accurately reflect the complex relationship between various related factors and energy load.

[0011] Operation of control strategy: The intelligent meteorological monitoring equipment in each microclimate zone and the Internet of Things sensors of each building collect microclimate parameters and building-related status data in real time at a set frequency, and transmit them to the regional energy management control center server through the wireless communication network. After receiving the data, the server runs the linkage model and generates control instructions based on the preset energy optimization goals using the model's built-in algorithm. During the generation process, special control instructions can be generated to ensure energy supply in extreme weather conditions or sudden functional changes of the building, and the instructions are sent to the corresponding device end through the communication network. The device executes the action according to the instructions to achieve dynamic matching and control of microclimate zoning, building adaptation and energy load.

[0012] Furthermore, in the microclimate zoning, cluster analysis is used to perform microclimate zoning, and the algorithm formula is: Among them, S ij represents the microclimate similarity score between the i-th region and the j-th region, n represents the number of factors affecting the microclimate, and w k is the weight coefficient of the kth influencing factor, f kij is the characteristic similarity function value of the kth influencing factor between the i-th region and the j-th region. After calculating the microclimate similarity scores between different regions, the similarity threshold S is set. X , and the areas with scores above this threshold are divided into the same microclimate zone.

[0013] Furthermore, in the installation and layout of the microclimate zoning equipment, a small spray cooling system, an adjustable ventilation corridor, a sunshade facility and a small heating device are arranged according to the activities of people, heat sources, sunshine and wind direction in the zone. For the layout of the small spray cooling system, the calculation formula for the number of nozzles is: Where N represents the number of small spray cooling system nozzles that need to be arranged in the microclimate zone, S is the target area that needs spray cooling, and ρ heat is the heat accumulation density in the target area, ΔT targetrepresents the desired cooling temperature difference, η is the heat exchange efficiency coefficient of the spray cooling system, Q is the spray flow rate of a single nozzle, ε is the spray coverage overlap coefficient, and for the adjustable ventilation corridor, its size design formula is: Among them, A v Represents the effective ventilation area of ​​the adjustable ventilation gallery vents, V vent is the ventilation volume that the ventilation corridor needs to achieve, T in and T out are the indoor temperature and outdoor temperature respectively, k is the ventilation resistance coefficient, v avg The expected average wind speed in the ventilation corridor and the installation location of the sunshade facilities are determined according to the orientation of the buildings in the zone, the pattern of sunshine, and the activities and lighting needs of personnel in the zone. According to the low temperature conditions in the zone in winter and the insulation needs, a small heating device is installed. For the entrances and exits of buildings, near the vents, and areas with frequent human activities and rapid heat loss, a small heating device is selected for installation, and it is coordinated with other microclimate control equipment in the zone to jointly maintain the microclimate conditions in the zone.

[0014] Furthermore, in the building adaptation monitoring and strategy formulation, in each microclimate zone, the installation location and quantity of the intelligent meteorological monitoring equipment are planned according to the zone area, shape and spatial layout characteristics. The temperature sensors are installed at different height levels and different directions in the zone to obtain the temperature distribution at different positions in the zone. The humidity sensor and the temperature sensor are installed in a similar position to ensure the correlation and synchronization of the collected temperature and humidity data. The wind speed sensor is installed in the open area, the top of the building and the entrance and exit of the ventilation corridor in the zone. The installation height is determined according to the height of the highest building in the zone and the surrounding terrain conditions to ensure accurate capture of the wind speed and wind direction changes at different positions in the zone. The light sensor is installed in the outdoor open space of different functional areas in the zone and the main indoor lighting surface. The outdoor installation ensures that it is not blocked by surrounding buildings and trees. The indoor installation fits the window orientation and the actual lighting conditions to monitor the light intensity, light duration and light angle of different spaces in the zone.

[0015] Furthermore, in the building adaptation monitoring and strategy formulation, variable sunshade curtain opening and closing angles, adjustable ventilation window openings, and indoor partition layout adjustment strategies are formulated based on the analysis results. For the variable sunshade curtain opening and closing angle, the formula Calculate, where θ opt represents the optimal opening and closing angle of the variable sunshade curtain, M is the number of indoor lighting monitoring points, and I m is the light intensity value collected by the mth lighting monitoring point, α m is the incident angle of light corresponding to the mth lighting monitoring point, k mis the lighting weight coefficient of the mth lighting monitoring point, λ is the thermal comfort weight coefficient, ΔT represents the indoor and outdoor temperature difference, and for the adjustable ventilation window opening, the formula Calculate, where O v Indicates the optimal opening of the adjustable ventilation window, V req is the required ventilation volume in the room, ρ is the air density, C p is the specific heat capacity of air at constant pressure, and T out represent the indoor temperature and outdoor temperature respectively, L is the number of ventilation zones that the ventilation window can be divided into, v l is the wind speed at the lth ventilation zone, A l is the ventilation area of ​​the lth ventilation zone, ΔT l It represents the expected change of air temperature after entering the room through the lth ventilation zone, β l is the ventilation efficiency weight coefficient of the lth ventilation zone. For the indoor partition layout adjustment, the formula Adjust, where Q transfer represents the amount of heat transferred per unit time through the layout of indoor partitions, P is the number of different types of indoor partitions, Q represents the number of different layout directions of indoor partitions in space, and k pq is the thermal conductivity of the pth type of partition in the qth arrangement direction, A pq is the effective heat transfer area of ​​the pth type of partition in the qth arrangement direction, ΔT pq represents the temperature difference between the two sides of the p-th type of partition in the q-th layout direction, δ pq is the thickness of the p-th type of partition in the q-th arrangement direction.

[0016] Furthermore, in the establishment of the linkage model, a machine learning algorithm is selected to construct the linkage model, and the model formula is: Where E t represents the predicted energy load at time t, I is the number of microclimate zones, J is the number of categories of building adaptation strategies, and a ij is the energy impact coefficient of the i-th microclimate zone for the j-th building adaptation strategy, ΔM ijt is the change in parameters related to microclimate in the i-th microclimate zone at time t, b ij is the microclimate interaction coefficient of the i-th microclimate zone with respect to the j-th building adaptation strategy, ΔB ijt represents the change in the implementation degree of the jth building adaptation strategy in the i-th microclimate zone at time t, c ij is the hysteresis effect coefficient of the i-th microclimate zone on the j-th building adaptation strategy, ΔC ijtIt is the change in relevant parameters corresponding to the lag time after the implementation of the h-th building adaptation strategy in the i-th microclimate zone at time t.

[0017] Furthermore, in the establishment of the linkage model, the model performance is verified using the validation set. If the accuracy requirement is not met, the model is optimized until it can accurately reflect the complex relationship between various related factors and energy loads. The model parameter adjustment formula is: Among them, C ijt is the dynamic adjustment coefficient of energy load for the jth building adaptation strategy in the i-th microclimate zone at time t, ΔM ijt is the change in parameters related to microclimate in the i-th microclimate zone at time t, is the historical average level of microclimate-related parameters in the i-th microclimate zone, ΔB ijt represents the change in the implementation degree of the jth building adaptation strategy in the i-th microclimate zone at time t, is the historical average implementation degree of the jth building adaptation strategy, L is the number of influencing factors of the synergy between microclimate and building adaptation, γ h is the weight coefficient of the lth synergistic influencing factor, ΔD ijtl is the synergistic variation between the jth building adaptation strategy and the lth synergistic influencing factor in the i-th microclimate zone at time t, It is the historical average synergy level of the j-th building adaptation strategy and each synergistic influencing factor in the i-th microclimate zone.

[0018] Furthermore, during the operation of the control strategy, the control instructions are generated by the model's built-in algorithm in combination with the preset energy optimization goals. During the process of generating the control instructions, when extreme weather conditions or sudden functional changes of the building occur, the control strategy algorithm built into the linkage model has an emergency response mechanism. According to the preset extreme situation response rules and the temporarily adjusted energy optimization goals, it prioritizes the microclimate stability and reasonable energy supply in key areas, and generates corresponding special control instructions.

[0019] Compared with the prior art, this load management operation method of comprehensive energy optimization configuration has the following beneficial effects:

[0020] 1. The present invention establishes a linkage model that comprehensively considers the relationship between microclimate zoning status, building adaptation behavior and energy load, accurately reflecting the complex relationship between changes in microclimate parameters, changes in building adaptation actions and changes in energy load. At the same time, according to the changes in the state of the building after adjustment, the energy management system can dynamically optimize the energy configuration plan, reduce unnecessary energy transmission and conversion links, and realize the deep optimization configuration of the entire regional comprehensive energy from generation, transmission to use.

[0021] 2. The present invention comprehensively considers the two factors of microclimate zoning and building self-adaptation, and conducts multi-dimensional and all-round refined management of energy load. By collecting microclimate parameters and building status data in real time and using a linkage model to dynamically adjust microclimate control equipment and building adaptation equipment, the internal and external environment of the building is maintained in a better state, thereby significantly reducing the additional energy consumption caused by unreasonable microclimate environment and building layout.

[0022] Other advantages, objectives and features of the present invention will be set forth in part in the following description and, in part, will be apparent to those skilled in the art based on an examination of the following or may be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 A flow chart of a load management operation method for comprehensive energy optimization configuration;

[0025] Figure 2 A flow chart of a load management operation method for comprehensive energy optimization configuration. DETAILED DESCRIPTION

[0026] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation mode, structure, characteristics and effects of the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments.

[0027] Embodiment 1

[0028] This embodiment describes in detail the specific application of a load management operation method with comprehensive energy optimization configuration in a large commercial plaza scenario. Through the present invention, while ensuring the comfortable activities of people in the commercial plaza and the normal operation of various commercial functions, the comprehensive energy configuration of the entire commercial plaza is significantly optimized and energy waste is reduced.

[0029] A large commercial plaza covers an area of ​​about 50,000 square meters and includes multiple commercial buildings. The functions of the buildings include retail stores, catering areas, entertainment venues and leisure plazas. The terrain of the plaza is relatively flat overall, but it is surrounded by some small green hills. The building layout is staggered and the buildings face different directions. The vegetation coverage in the plaza includes concentrated landscape tree belts, scattered flower beds and lawns, forming a relatively complex microclimate environment. The geographic information system (GIS) technology is used for operation. First, relevant data is collected. The terrain data is clarified through professional measurement tools and field survey records. For example, it is measured that the highest altitude of the small green hills around the plaza is about 10-15 meters higher than the ground of the plaza, and the drainage direction is basically from the hills to the low-lying area in the center of the plaza. With the help of architectural drawings combined with field measurements, the building layout data is sorted out. For example, the height of each commercial building varies from 3 to 6 floors, the minimum distance between buildings is about 8 meters, and the maximum is 30 meters. The vegetation coverage is counted by on-site survey and reference to satellite images. Based on the data, it is determined that the landscape tree belt is mainly distributed on the east and west sides of the square, with a width of about 5-10 meters. The flower beds and lawns are scattered around the buildings and beside the square passages. Based on these data, the influence of various factors on the microclimate is analyzed to determine the basis for zoning. Considering the topography, the air flow around the hills is relatively complex and the temperature is affected by the terrain differently, which is used as a reference for zoning. In terms of building layout, the height and density of buildings lead to different sunshine and ventilation conditions. For example, the shady side of high-rise buildings has short sunshine time and obstructed ventilation, while the open areas between buildings have good ventilation. In terms of vegetation coverage, the landscape tree belt has obvious effects on shading, cooling and regulating humidity in the surrounding areas. Based on this, the commercial square is divided into 8 microclimate zones through GIS methods such as cluster analysis and buffer zone analysis. For example, the area with hills and dense buildings on the east side is one zone, and the area with open space and sufficient sunshine in the center of the square is divided into another zone. Corresponding microclimate zone maps are generated, and each zone is numbered and marked.

[0030] Intelligent meteorological monitoring equipment is installed in each microclimate zone. Temperature sensors are installed at different heights of 1.5 meters, 5 meters, 10 meters from the ground and in the east, south, west, north and middle areas within the zone to ensure that temperature changes can be fully monitored. Humidity sensors are installed at locations where air circulation is relatively stable and not easily disturbed by local water vapor, such as slightly higher corners of buildings. Wind speed sensors are installed on the top of buildings and in open areas of each zone, at the entrance and exit of ventilation corridors, and the installation direction is calibrated and aligned with the north direction. Light sensors are arranged in open areas of outdoor squares and near the main lighting surfaces of indoor commercial shops, catering areas, etc. to ensure accurate light data collection. At the same time, microclimate control equipment is arranged. For small-scale spray cooling systems, the number and location of sprinklers are reasonably arranged based on the gathering of people in each zone (such as frequent activities of people in the leisure square, high density of people in the waiting area outside the catering area, etc.), heat source distribution (such as heat dissipation in the kitchen of the catering area, heat dissipation of large electronic display screens, etc.) and sunlight intensity distribution. Taking the zone where the leisure square in the center of the square is located as an example, according to the formula Calculation, where the target area S to be cooled is about 2000 square meters, the heat accumulation density ρ heat By counting the heat dissipation of personnel and equipment in this area, it is estimated to be 50 watts per square meter, and the expected cooling temperature difference ΔT target The temperature is set to 3℃. The heat exchange efficiency coefficient η of the spray cooling system is tested to be 0.6. The spray flow rate Q of a single nozzle is 0.01 cubic meters per second. The spray coverage overlap coefficient ε is 0.2. It is calculated that the number of nozzles N is about 28. The nozzle layout is carried out accordingly, and the water supply pipeline is well protected from the sun and heat-insulated. The control valve is installed for easy operation and maintenance. The adjustable ventilation corridor is set according to the building layout and wind direction characteristics. For example, a ventilation corridor is reserved between two rows of buildings running north and south. The size of the vent is based on the formula Design, the ventilation volume V that the ventilation corridor in this area needs to achieve vent According to the volume of indoor commercial space, personnel density and air quality requirements, it is converted to 10 cubic meters per second, and the indoor temperature T in The average outdoor temperature is 25℃. out The average temperature is 20℃. The ventilation resistance coefficient k is determined to be 0.8 through fluid mechanics simulation analysis of the corridor's wind duct roughness, bend conditions, etc. The expected average wind speed v avg Set it to 2 meters per second and calculate the effective ventilation area A of the vent vIt is about 6.25 square meters, and the size of the vent is designed accordingly. Electric adjustment devices are installed in the ventilation corridor to facilitate the adjustment of ventilation volume and direction according to real-time wind direction and wind speed. In terms of sunshade facilities, electric awnings are installed above the windows and on the top of the balcony on the south facade, west facade and other facades of each building where direct sunlight lasts for a long time. The extension length and shading angle can be automatically adjusted according to changes in the angle and intensity of sunlight. Large parasols are set up in the outdoor leisure square to cover the public rest area to protect people from direct sunlight during activities. In addition, in winter, according to the low temperature in the zone and the position of the air vents, small electric heating devices are installed near the entrances and exits of the buildings and the vents to maintain suitable microclimate conditions in the area.

[0031] Heat flow sensors are installed at key locations of the envelope structures of buildings in the commercial plaza, such as evenly installed on the inner and outer surfaces of the walls and the upper and lower surfaces of the roof to ensure a close fit with the envelope structure and measure heat transfer in real time. Light intensity sensors are arranged at different locations in various functional areas (retail stores, dining areas, entertainment venues, etc.) inside the building to fully grasp the indoor lighting conditions. Personnel activity sensors and space occupancy monitoring equipment are installed in meeting rooms, activity areas and other spaces to monitor changes in space usage functions in real time, and the collected data is transmitted to the building information model. Based on the lighting and thermal comfort requirements, variable sunshade curtains for each store and indoor public area are calculated through the formula Calculate the optimal opening and closing angle. For example, there are 5 lighting monitoring points in a retail store, and the light intensity value I collected at each lighting monitoring point is m According to the sunshine conditions at different times, the incident angle of light α m The lighting weight coefficient k is calculated based on the sun position, window orientation and monitoring point position. m According to the importance of lighting in different areas of the store (such as high weight for display area and low weight for warehouse area), the thermal comfort weight coefficient λ is set to 0.8 in summer. The indoor and outdoor temperature difference ΔT is obtained through indoor and outdoor temperature sensors, and the opening and closing angles of the sunshade curtains are calculated and adjusted in real time. While ensuring that the indoor lighting meets the needs of product display, the solar radiation heat entering the room is reduced, and the indoor thermal environment is optimized. For adjustable ventilation windows, according to the ventilation efficiency and indoor environmental quality requirements, according to the formula Determine the best opening, for example, the kitchen area of ​​the dining area, according to the required ventilation volume V in the room req (15 cubic meters per second is determined based on the kitchen area, number of stoves and relevant hygiene standards), combined with the local air density ρ, the constant pressure specific heat capacity of air C p and indoor and outdoor temperature T in 、T out , wind speed v in each zone of the ventilation window l , Ventilation area A l , Expected change in air temperature ΔTl and ventilation efficiency weight coefficient β l , etc. (determined through field measurement and analysis), calculate the optimal opening of the ventilation window, achieve natural ventilation, exhaust smoke and heat, maintain a good indoor environment, reduce the use time of ventilation equipment, and reduce energy consumption. For indoor partition layout, according to the changes in space usage functions, such as entertainment venues according to different activity needs (such as holding small performances, setting up children's play areas, etc.), use the formula After evaluating the impact of heat transfer, the position and form of partitions are adjusted to control indoor heat transfer and optimize energy efficiency while meeting the flexible changes of activity space.

[0032] The historical microclimate data of each microclimate zone (including temperature, humidity, wind speed, light intensity and other parameter records at different times of the past year), the historical records of building adaptation (such as changes in the opening and closing angles of sunshade curtains, changes in the opening of ventilation windows, changes in the layout of indoor partitions, etc.) and the energy consumption data of different functional buildings and equipment in each zone under the corresponding microclimate and building adaptation status (the power consumption and heat consumption in different time periods are obtained through metering equipment such as electric meters and heat meters) are collected to build a linkage model. The microclimate parameters and building adaptation related data are used as input variables, and the energy consumption load data is used as the output variable. The training set and the validation set are divided according to 70% of the data for training and 30% of the data for validation. During the training process, the model parameters are optimized so that the model can learn the correlation between the changes in different microclimate parameters, building adaptation actions and energy load changes. The difference between the energy load results predicted by the model and the actual energy consumption data is verified through the validation set. If it does not meet the accuracy requirements, the model is retrained and optimized by increasing the amount of training data, adjusting the network structure, optimizing parameters, etc. until the model can accurately reflect the relationship between various related factors and energy load.

[0033] In daily operation, each intelligent meteorological monitoring device and IoT sensor collects microclimate parameters and building-related status data at a set frequency. For example, temperature and humidity sensors collect data every 5 minutes, and light intensity sensors collect data every 1-2 minutes according to the change of sunshine. The collected data is transmitted to the regional energy management control center server through the wireless communication network (according to the square network coverage and data transmission requirements, some areas use ZigBee technology for short-distance and low-power transmission, and LoRa technology for long-distance transmission. Key equipment and areas with large data transmission volume are combined with 5G network to ensure real-time and high-speed transmission). After receiving the data, the server runs the linkage model and combines it with the preset energy optimization goals (such as the overall power consumption during the summer peak period is reduced by 15% compared with the same period last year, and the heat of each zone is reduced by 15% during the summer peak period). The control strategy algorithm built into the model generates control instructions and sends them to the corresponding equipment. For example, in the afternoon in summer, the temperature in the area where the leisure square in the center of the square is located rises, the light is strong, and there are frequent activities. The linkage model generates instructions based on real-time data to control the sunshade facilities in the area to expand to the appropriate angle for shading, start the spray cooling system for spray cooling, and adjust the opening of the ventilation windows of the surrounding buildings to increase natural ventilation. The angle of the variable sunshade curtains is adjusted according to the indoor lighting conditions. Each device (such as awning drive motor, spray cooling system nozzle control valve, ventilation window electric window opener, sunshade curtain electric track device, etc.) executes actions according to the instructions to achieve dynamic matching and control of microclimate zoning, building adaptation and energy load, optimize the energy configuration of the entire commercial square, and reduce energy waste.

[0034] In summary, through the present invention, while ensuring the comfortable activities of people in the commercial plaza and the normal operation of various commercial functions, the comprehensive energy configuration of the entire commercial plaza is significantly optimized, energy waste is reduced, and good practical application effects and economic and environmental benefits are demonstrated, which fully verifies the feasibility and advancement of the present invention in such application fields.

[0035] Embodiment 2

[0036] This embodiment describes in detail the specific application of a load management operation method with comprehensive energy optimization configuration in a large industrial park scenario. Through the present invention, it can be flexibly and effectively controlled according to actual conditions to ensure that various production activities in the industrial park can be carried out smoothly in an energy-saving, comfortable and safety-compliant environment.

[0037] A large industrial park covers an area of ​​about 100,000 square meters. It has different types of industrial plants, office buildings, storage facilities, large green areas, roads, etc. The terrain of the park is undulating. There is a low-lying area for rainwater collection, and several small high slopes are distributed on the edge of the park. The building layout is planned according to the functional needs of different industries. The plants are divided into single-story tall plants and multi-story plants. The office buildings are distributed near the entrance of the park and the main production areas. The storage facilities are concentrated in areas with convenient logistics and transportation. In terms of vegetation coverage, in addition to the roadside trees on both sides of the road, there are also large areas of concentrated green forests. The belt is used for environmental beautification and air purification in the park. The overall microclimate is significantly affected by factors such as terrain, buildings and vegetation. Work is carried out through geographic information system (GIS) technology. First, various data are collected. For topographic data, professional measuring instruments are used to accurately measure the height and slope of each place. It is clear that the highest point of the small high slope is about 20-30 meters higher than the low-lying area. Detailed records are recorded on the direction of drainage from high slopes to low-lying areas. Building layout data is obtained based on architectural drawings, field measurements and spatial positioning technology. For example, the height of a single-story tall factory building is 15 meters, and the number of floors of a multi-story factory building is not less than 3-5 floors. The distance between different buildings varies between 10 and 30 meters according to production safety and logistics requirements. With the help of on-site surveys combined with satellite imagery to count vegetation coverage data, it is determined that the green belts are mainly distributed in the middle and southern parts of the park, with a width of about 10 to 20 meters. Street trees are planted on both sides of the roads in the park. Based on these data, the influence of various factors on the formation of microclimate is analyzed to determine the basis for zoning. From the perspective of topography, high slopes are well ventilated but heat dissipates quickly, while low-lying areas have relatively slow air circulation and are prone to heat accumulation. This is used as a reference for zoning. In terms of building layout, tall factories have a great impact on the surrounding areas. Sunlight blocking, ventilation obstruction and heat radiation have a great impact. The microclimates around buildings with different functions are different. For example, the temperature around the production workshop is affected by the heat dissipation of equipment. These influencing factors are taken into consideration. In terms of vegetation coverage, the green belt has a significant effect on regulating the surrounding humidity and reducing the temperature. Based on this, the zones are divided and the cluster analysis method is used to divide the industrial park into 10 microclimate zones. For example, the area around the green belt in the southern part of the park and where the factory buildings are relatively sparse is one zone, and the area in the middle of the park where the factory buildings are concentrated and the terrain is low is divided into another zone, etc. A clear microclimate zoning map is generated, and each zone is numbered and labeled.

[0038] Intelligent meteorological monitoring equipment is installed in each microclimate zone, and temperature sensors are installed at different heights (such as 2 meters, 8 meters, 12 meters from the ground) and in different directions to fully capture the temperature changes in the zone. Humidity sensors are installed at locations where the relative humidity of the air is more representative and less susceptible to local interference, such as places close to vents but away from the direct influence of vents. Wind speed sensors are installed at key locations such as the top of the building, the entrance and exit of the ventilation corridor, and open areas to ensure that they are calibrated and aligned with the north direction to accurately measure the wind direction and wind speed. Light sensors are arranged in outdoor open spaces and near the main lighting surfaces of factories, office buildings and other buildings to ensure that accurate light data is collected. When laying out microclimate control equipment, the small spray cooling system is based on the distribution of heat sources in the zone (such as equipment heat dissipation in the production workshop, heat generated by accumulation of goods in the storage area during high temperatures in summer), personnel activities (such as office areas for office buildings, worker operation areas in factories, etc.) and sunshine intensity. The number and layout of sprinklers are reasonably determined. Taking the zone where a production workshop is located as an example, according to the formula Calculate the number of nozzles. The target area S to be cooled in the workshop is about 3,000 square meters, and the heat accumulation density ρ heat By calculating the heat dissipation power of equipment and the heat generated by personnel activities, it is estimated to be 80 watts per square meter. The expected cooling temperature difference ΔT target The temperature is set to 4℃. The heat exchange efficiency coefficient η of the spray cooling system is tested to be 0.7. The spray flow rate Q of a single nozzle is 0.012 cubic meters per second. The spray coverage overlap coefficient ε is 0.15. The number of nozzles N is calculated to be about 43. The nozzle layout is carried out according to the calculation results. At the same time, the water supply pipes are insulated, sun-proofed, and the control valves are reasonably installed to facilitate operation and maintenance. The adjustable ventilation corridor is designed according to the building layout and wind direction characteristics in the park. Reasonable ventilation corridor space is reserved between the factory and the office building, and between the factory and the storage facilities. The vent size is based on the formula Calculate and determine, for example, the ventilation volume V required for a ventilation corridor between two rows of factory buildings vent According to the plant volume, personnel density and ventilation requirements, it is converted to 12 cubic meters per second, and the indoor temperature T in The average outdoor temperature is 28℃. out The average temperature is 22℃. The ventilation resistance coefficient k is determined to be 0.9 by analyzing the roughness of the air duct, the number of bends and the resistance characteristics of the ventilation equipment in the corridor. The expected average wind speed v avg Set it to 2.5 meters per second and calculate the effective ventilation area A of the vent vIt is about 5.8 square meters. The size of the vent is designed accordingly, and adjustable vents, ventilation fans and other equipment and control devices are installed to achieve precise adjustment of ventilation volume and direction, improve air circulation in the partition, reduce indoor stuffiness, and reduce energy consumption of ventilation and cooling equipment. In terms of shading facilities, electric awnings and sunshades are installed on the south facades, west facades and other direct sunlight surfaces of each factory building and office building. The shading angle and extension length are automatically adjusted according to changes in sunlight angle and intensity to reduce solar radiation heat entering the room; awnings are set up in public rest areas, logistics loading and unloading areas and other areas in the park to provide a shade environment for personnel and goods. In winter, small water heating devices are installed in areas with low temperatures and wind outlets in the park, such as entrances and exits of storage facilities and near vents of some factory buildings, to ensure suitable microclimate conditions in the area and avoid affecting production operations and cargo storage safety due to low temperatures.

[0039] Heat flow sensors are installed at key locations of the enclosure structures of buildings in the industrial park, such as the walls and roofs of factories, and the inner and outer walls of office buildings, so that they fit closely to the enclosure structures, accurately measure the heat transfer conditions, and grasp the thermal performance of the enclosure structures in real time; light intensity sensors are reasonably arranged in different functional spaces inside the building, such as the production workshops and warehouses of factories, and the offices and conference rooms of office buildings, to understand the indoor lighting conditions in detail; personnel activity sensors and space occupancy monitoring equipment are installed in conference rooms, activity rooms, and different operating areas in factories to monitor the changes in space usage functions in real time. For example, when an area in the workshop was originally used for temporary storage of materials and was later changed into a new processing area due to adjustments in the production process, these devices can capture the corresponding changes in time and transmit the collected data to the building information model (BIM). Based on the lighting and thermal comfort requirements, for the variable sunshade curtains in factories and office buildings, the formula is used to calculate the temperature of the variable sunshade curtains in the factory and office buildings. To calculate the optimal opening and closing angle, take an office in an office building as an example. There are 4 lighting monitoring points in the office. The light intensity value I collected by each lighting monitoring point is m It will change with time and weather, and the incident angle of light α m The lighting weight coefficient k is calculated based on the sun position, window orientation and monitoring point location. m The thermal comfort weight coefficient λ is set to 0.7 in summer according to the degree of demand for lighting in different locations of the office area (such as high weight for the location of desks and chairs, low weight for the corner equipment placement area, etc.). The indoor and outdoor temperature difference ΔT is obtained by the indoor and outdoor temperature sensors. Based on these parameters, the optimal opening and closing angle of the sunshade curtains is calculated in real time, which can not only ensure that there is enough light in the room to meet the visual needs of the office, but also reduce the solar radiation heat entering the room, reduce the air conditioning refrigeration load, and optimize the indoor thermal environment. For adjustable ventilation windows, according to the ventilation efficiency and indoor environmental quality requirements, according to the formula Determine the optimal opening, for example, in a production workshop, according to the required indoor ventilation volume V req (According to the exhaust gas emissions generated by the operation of equipment in the workshop, the air quality required for work by personnel and relevant safety regulations, it is determined to be 20 cubic meters per second), combined with the local air density ρ, the constant pressure specific heat capacity of air C p and indoor and outdoor temperature T in , T out , wind speed v in each zone of the ventilation window l , Ventilation area A l , Expected change in air temperature ΔT l and ventilation efficiency weight coefficient β l (determined through field measurements, simulation analysis and the degree of influence of ventilation in each partition on the overall air quality) and other parameters, calculate the optimal opening of the ventilation window, realize natural ventilation, timely discharge harmful gases and heat in the workshop, maintain a good indoor production environment, reduce the operating time of mechanical ventilation equipment, and thus reduce energy consumption. For the layout of indoor partitions, taking into account the functional changes of building spaces in the industrial park, such as the need to flexibly adjust the layout of operation areas and material storage areas according to the development of different production projects in the factory, the formula is used After evaluating the impact of heat transfer, adjust the location and form of the partition. For example, when adjusting the production layout of a new product, if two small spaces originally separated by partitions are merged into a large space for the installation of new equipment, it is necessary to analyze the thermal conductivity k of different types of partitions (such as metal partitions, fireproof partitions, etc., i.e. P types) in different layout directions (east-west, north-south, etc., i.e. Q directions). pq , effective heat transfer area A pq , temperature difference between the two sides ΔT pq and the partition thickness δ pq The heat transfer changes are calculated through formulas, and partitions are adjusted appropriately to optimize the indoor thermal environment and reduce the energy load for heating or cooling while meeting production process requirements and flexible use of space.

[0040] Collect historical microclimate data of each microclimate zone (covering detailed parameter records such as temperature, humidity, wind speed, light intensity, etc. at different times in the past two years, ensuring that data under different seasons and weather conditions are included), historical records of building adaptation (such as the history of changes in the opening and closing angles of sunshade curtains in various factories, office buildings, etc., historical adjustments to the opening of ventilation windows, changes in the layout of indoor partitions, etc., record the specific time of each adjustment, the values ​​of relevant parameters, and the corresponding zone, specific location of the building, etc.) and energy consumption data of different functional buildings and equipment in each zone under the corresponding microclimate and building adaptation status (obtain the power consumption and heat consumption corresponding to different time periods through energy metering equipment such as electric meters and heat meters installed in each building, and clearly record the time and date of the microclimate data and building adaptation records). The time of energy consumption, the corresponding buildings and partitions, the specific energy consumption values ​​and other details are recorded), and a linkage model is constructed. The collected microclimate parameter data and building adaptation related data are used as input variables, and the energy consumption load data are used as output variables. The training set and the validation set are divided according to 70% of the data for training and 30% of the data for validation. During the training process, the optimization strategy is used to continuously optimize the model so that the model can learn the correlation between the changes in different microclimate parameters, the changes in building adaptation actions and the changes in energy load. The validation set is used to verify the difference between the energy load results predicted by the model and the actual energy consumption data. If it does not meet the expected accuracy requirements, the model is retrained and optimized until the model can accurately reflect the complex relationship between the relevant factors and the energy load, providing a reliable basis for subsequent operation and regulation.

[0041] In daily operation, each intelligent meteorological monitoring device and IoT sensor collects microclimate parameters and building-related status data at the set collection frequency. For example, temperature and humidity sensors collect data every 6 minutes, and light intensity sensors collect data every 1-2 minutes according to the changes in sunshine, to ensure that real-time information can be captured in a timely and accurate manner. The collected data is transmitted to the regional energy management control center server through the wireless communication network. According to the network coverage of the park and the data transmission requirements of different regions, ZigBee technology is used for short-distance and low-power data transmission requirements (such as short-distance communication between equipment in some factories), and LoRa technology is used for medium- and long-distance and low-power data transmission (such as transmitting data from the edge of the park to the central server). For some key equipment with high real-time requirements and large data volumes (such as production safety monitoring, key energy consumption monitoring areas, etc.), 5G networks are used for transmission. During the transmission process, data verification, encryption and other technologies are used to ensure the integrity and accuracy of the data. At the same time, a real-time monitoring mechanism is set up to alarm in time in case of communication failure, and automatically switch to the backup communication link or take corresponding repair measures to ensure the continuity of data transmission.

[0042] After receiving the real-time data, the regional energy management control center server runs the pre-built linkage model, and uses the current microclimate parameter data of each zone and the actual adjustment data of each building (such as the current opening and closing angle of the sunshade curtains, the current opening of the ventilation windows, the current layout of the interior partitions, etc.) as the model input. Combined with the preset energy optimization goals (for example, the overall energy consumption is reduced by 12% throughout the year compared with the previous year, and the power load and thermal load fluctuations of each zone are controlled within a certain reasonable range, etc., and these specific quantitative indicators are set to reflect the optimization direction and target requirements), the model's built-in control strategy algorithm performs calculations and analysis to generate control instructions for the microclimate control equipment in each microclimate zone and the building adjustment-related equipment.

[0043] In summary, the present invention can achieve reasonable allocation and optimal utilization of energy through effective control means, while meeting the complex and diverse production operations and environmental requirements of large industrial parks, and significantly reducing overall energy consumption.

[0044] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A load management operation method for comprehensive energy optimization configuration, characterized in that: The method comprises the following specific steps: Microclimate zoning: Conduct a comprehensive field survey of the target area, collect data on topography, building layout and vegetation coverage, analyze the impact of various factors on the formation of microclimate, determine the basis for zoning based on the airflow and heat differences caused by terrain undulations, the impact of buildings on sunlight and ventilation, and the local microclimate characteristics created by vegetation, and use geographic information system technology to digitize the field survey data and import it into the software platform. Perform microclimate zoning through cluster analysis, generate zoning boundaries and numbers to identify each zoning, and form a microclimate zoning map to display the zoning range and location relationship; Installation and layout of equipment in microclimate zones: In each microclimate zone, the installation location and quantity of intelligent meteorological monitoring equipment are planned according to the area, shape and spatial layout characteristics of the zone. At the same time, small spray cooling systems, adjustable ventilation corridors, shading facilities and small heating devices are arranged according to the activities of people, heat sources, sunshine and wind direction in the zone to ensure that each device can play an effective role and coordinately regulate the microclimate in the zone; Building adaptation monitoring and strategy formulation: Install heat flow sensors at key locations of building envelope structures to accurately measure their thermal performance parameters, arrange light intensity sensors at different locations in different functional areas of the building to accurately monitor lighting conditions, install personnel activity sensors and space occupancy monitoring equipment in each functional space to grasp the space usage status in real time, and integrate the collected real-time data into the building information model. Use big data analysis technology to pre-process and deeply mine the data, and formulate variable sunshade curtain opening and closing angles, adjustable ventilation window openings, and indoor partition layout adjustment strategies based on the analysis results to optimize the building's internal environment and energy utilization; Establishment of linkage model: historical microclimate data is obtained from intelligent meteorological monitoring equipment in each microclimate zone, historical records of building adaptation are obtained from building-related records, and energy consumption data is obtained and integrated from building energy metering equipment. A machine learning algorithm is used to build a linkage model, with microclimate parameters and building adaptation-related data as input variables, and energy consumption load data as output variables. The model is trained by dividing the training set and the validation set, and the model performance is verified using the validation set. If the accuracy requirements are not met, the model is optimized until it can accurately reflect the complex relationship between various related factors and energy load. Operation of control strategy: The intelligent meteorological monitoring equipment in each microclimate zone and the Internet of Things sensors of each building collect microclimate parameters and building-related status data in real time at a set frequency, and transmit them to the regional energy management control center server through the wireless communication network. After receiving the data, the server runs the linkage model and generates control instructions based on the preset energy optimization goals using the model's built-in algorithm. During the generation process, special control instructions can be generated to ensure energy supply in extreme weather conditions or sudden functional changes of the building, and the instructions are sent to the corresponding device end through the communication network. The device executes the action according to the instructions to achieve dynamic matching and control of microclimate zoning, building adaptation and energy load.

2. The load management operation method of comprehensive energy optimization configuration according to claim 1 is characterized in that: In the microclimate zoning, cluster analysis is used to perform microclimate zoning, and the algorithm formula is: Among them, S ij represents the microclimate similarity score between the i-th region and the j-th region, n represents the number of factors affecting the microclimate, and w k is the weight coefficient of the kth influencing factor, f kij is the characteristic similarity function value of the jth influencing factor between the i-th region and the j-th region. After calculating the microclimate similarity scores between different regions, the similarity threshold S is set. X , and the areas with scores above this threshold are divided into the same microclimate zone.

3. The load management operation method of comprehensive energy optimization configuration according to claim 1 is characterized in that: In the installation and layout of the microclimate zoning equipment, a small spray cooling system, an adjustable ventilation corridor, shading facilities and a small heating device are arranged according to the personnel activities, heat sources, sunshine and wind direction in the zone. For the layout of the small spray cooling system, the calculation formula for the number of nozzles is: Where N represents the number of small spray cooling system nozzles that need to be arranged in the microclimate zone, S is the target area that needs spray cooling, and ρ heat is the heat accumulation density in the target area, ΔT target represents the desired cooling temperature difference, η is the heat exchange efficiency coefficient of the spray cooling system, Q is the spray flow rate of a single nozzle, ε is the spray coverage overlap coefficient, and for the adjustable ventilation corridor, its size design formula is: Among them, A v Represents the effective ventilation area of ​​the adjustable ventilation gallery vents, V vent is the ventilation volume that the ventilation corridor needs to achieve, T in and T out are the indoor temperature and outdoor temperature respectively, k is the ventilation resistance coefficient, v avg The expected average wind speed in the ventilation corridor and the installation location of the sunshade facilities are determined according to the orientation of the buildings in the zone, the pattern of sunshine, and the activities and lighting needs of personnel in the zone. According to the low temperature conditions in the zone in winter and the insulation needs, a small heating device is installed. For the entrances and exits of buildings, near the vents, and areas with frequent human activities and rapid heat loss, a small heating device is selected for installation, and it is coordinated with other microclimate control equipment in the zone to jointly maintain the microclimate conditions in the zone.

4. The load management operation method of comprehensive energy optimization configuration according to claim 1 is characterized in that: In the building adaptation monitoring and strategy formulation, in each microclimate zone, the installation location and quantity of the intelligent meteorological monitoring equipment are planned according to the zone area, shape and spatial layout characteristics. The temperature sensors are installed at different height levels and different directions in the zone to obtain the temperature distribution at different positions in the zone. The humidity sensor and the temperature sensor are installed in a similar position to ensure the correlation and synchronization of the collected temperature and humidity data. The wind speed sensor is installed in the open area, the top of the building and the entrance and exit of the ventilation corridor in the zone. The installation height is determined according to the height of the highest building in the zone and the surrounding terrain conditions to ensure accurate capture of the wind speed and wind direction changes at different positions in the zone. The light sensor is installed in the outdoor open space of different functional areas in the zone and the main indoor lighting surface. The outdoor installation ensures that it is not blocked by surrounding buildings and trees. The indoor installation fits the window orientation and the actual lighting conditions to monitor the light intensity, light duration and light angle of different spaces in the zone.

5. The load management operation method of comprehensive energy optimization configuration according to claim 1 is characterized in that: In the building adaptation monitoring and strategy formulation, variable sunshade curtain opening and closing angles, adjustable ventilation window openings, and indoor partition layout adjustment strategies are formulated based on the analysis results. For the variable sunshade curtain opening and closing angle, the formula Calculate, where θ opt represents the optimal opening and closing angle of the variable sunshade curtain, M is the number of indoor lighting monitoring points, and I m is the light intensity value collected by the mth lighting monitoring point, α m is the incident angle of light corresponding to the mth lighting monitoring point, k m is the lighting weight coefficient of the mth lighting monitoring point, λ is the thermal comfort weight coefficient, ΔT represents the indoor and outdoor temperature difference, and for the adjustable ventilation window opening, the formula Calculate, where O v Indicates the optimal opening of the adjustable ventilation window, V req is the required indoor ventilation volume, ρ is the air density, C p is the specific heat capacity of air at constant pressure, and T out represent the indoor temperature and outdoor temperature respectively, L is the number of ventilation zones that the ventilation window can be divided into, v l is the wind speed at the lth ventilation zone, A l is the ventilation area of ​​the lth ventilation zone, ΔT l It represents the expected change of air temperature after entering the room through the lth ventilation zone, β l is the ventilation efficiency weight coefficient of the lth ventilation zone. For the indoor partition layout adjustment, the formula Adjust, where Q transfer represents the amount of heat transferred per unit time through the layout of indoor partitions, P is the number of different types of indoor partitions, Q represents the number of different layout directions of indoor partitions in space, and k pq is the thermal conductivity of the pth type of partition in the qth arrangement direction, A pq is the effective heat transfer area of ​​the pth type of partition in the qth arrangement direction, ΔT pq represents the temperature difference on both sides of the p-th type of partition in the q-th arrangement direction, δ pq is the thickness of the p-th type of partition in the q-th arrangement direction.

6. The load management operation method of comprehensive energy optimization configuration according to claim 1 is characterized in that: In establishing the linkage model, a machine learning algorithm is used to construct the linkage model, and the model formula is: Where E t represents the predicted energy load at time t, I is the number of microclimate zones, J is the number of categories of building adaptation strategies, and a ij is the energy impact coefficient of the i-th microclimate zone for the j-th building adaptation strategy, ΔM ijt is the change in parameters related to microclimate in the i-th microclimate zone at time t, b ij is the microclimate interaction coefficient of the i-th microclimate zone with respect to the j-th building adaptation strategy, ΔB ijt represents the change in the implementation degree of the jth building adaptation strategy in the i-th microclimate zone at time t, c ij is the hysteresis effect coefficient of the i-th microclimate zone on the j-th building adaptation strategy, ΔC ijt It is the change in relevant parameters corresponding to the lag time after the implementation of the j-th building adaptation strategy in the i-th microclimate zone at time t.

7. The load management operation method of comprehensive energy optimization configuration according to claim 1 is characterized in that: In the establishment of the linkage model, the model performance is verified using the validation set. If the accuracy requirement is not met, the model is optimized until it can accurately reflect the complex relationship between various related factors and energy loads. The model parameter adjustment formula is: Among them, C ijt is the dynamic adjustment coefficient of energy load for the jth building adaptation strategy in the i-th microclimate zone at time t, ΔM ijt is the change in parameters related to microclimate in the i-th microclimate zone at time t, is the historical average level of microclimate-related parameters in the i-th microclimate zone, ΔB ijt represents the change in the implementation degree of the jth building adaptation strategy in the i-th microclimate zone at time t, is the historical average implementation degree of the jth building adaptation strategy, L is the number of influencing factors of the synergy between microclimate and building adaptation, γ h is the weight coefficient of the lth synergistic influencing factor, ΔD ijtl is the synergistic variation between the jth building adaptation strategy and the lth synergistic influencing factor in the i-th microclimate zone at time t, It is the historical average synergy level of the j-th building adaptation strategy and various synergistic influencing factors in the i-th microclimate zone.

8. The load management operation method of comprehensive energy optimization configuration according to claim 1 is characterized in that: During the operation of the control strategy, the control instructions are generated by the model's built-in algorithm in combination with the preset energy optimization goals. During the process of generating the control instructions, when extreme weather conditions or sudden functional changes of the building occur, the control strategy algorithm built into the linkage model has an emergency response mechanism. According to the preset extreme situation response rules and the temporarily adjusted energy optimization goals, it prioritizes the microclimate stability and reasonable energy supply in key areas, and generates corresponding special control instructions.

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