1106 results about "Outdoor temperature" patented technology

The invention provides a BIM-based building energy consumption simulation analysis optimization method and system, and relates to the technical field of building energy consumption, and the method comprises the steps: building a building energy consumption digital twinborn model through integrating a building information model (BIM) and real-time operation data, such as indoor and outdoor temperature, equipment operation, electrical load and personnel density, collected by an Internet of Things sensor. An LSTM and GNN mixed deep learning algorithm is used to predict building energy consumption, and clustering analysis is used to identify an energy consumption abnormal mode and a peak period. And finally, based on a reinforcement learning algorithm, constructing an energy consumption optimization model taking total energy consumption minimization as a target and taking indoor thermal comfort and air quality as constraints, outputting equipment optimization operation parameters such as air conditioner temperature, fresh air volume, illumination brightness and the like, and realizing intelligent optimization control of building energy consumption, so that the building energy consumption is reduced, and the building operation efficiency is improved.

The invention discloses a central air-conditioning system optimization control method oriented to building load prediction, which comprises the following steps: building a building load prediction model based on a long short-term memory network, combining real-time acquired building electrical load, indoor and outdoor temperature, humidity and equipment operation power data to accurately predict building cooling load requirements in a future time period, and on this basis, optimizing a central air-conditioning system. According to the method, time-of-use electricity price information is used for dynamically adjusting a cooling capacity distribution strategy of the central air conditioning system, so that the energy consumption and the operation cost of the system are reduced to the maximum extent while the load requirement is met. Compared with the prior art, the method has the advantages that the problems of insufficient load fluctuation response and insufficient energy consumption optimization are effectively solved, and the operation efficiency and economical efficiency of the central air-conditioning system of the building can be remarkably improved.

The invention provides an air conditioner personalized intelligent control method, system and device and a storage medium, and relates to the technical field of air conditioner control, the method comprises the following steps: combining first people flow data and historical people flow data of a target area within a first preset duration to predict second people flow data within a target duration; determining the reference temperature of the target area within the target duration in combination with the outdoor temperature and the area characteristics of the target area; in combination with the reference temperature and the second visitor flow rate data, temperature adjusting parameters of the target area within the target duration are determined, and an initial operation scheme of an air conditioner of the target area is formulated according to the temperature adjusting parameters; and according to the environment monitoring parameters of the target area, determining an environment load coefficient, and according to the environment load coefficient, generating a target operation scheme. The method has the technical effects that the environment change is predicted in advance, the air conditioner operation parameters are adjusted in time, and it is guaranteed that the indoor environment can reach the comfortable state in time.

The invention relates to the technical field of heat supply system temperature control, and discloses a temperature control method of an air source heat pump heat supply system. The method comprises the following steps: establishing a temperature field model according to temperature-pressure-flow data of the head and tail ends of a building and each region, and obtaining distribution characteristics; analyzing and predicting a thermal load based on the temperature rise and drop rate and the heat storage coefficient; determining a water supply temperature correction coefficient and a valve opening degree through fuzzy control in combination with an outdoor temperature trend; generating a partition start-stop sequence according to the partition start-stop sequence; and finally calculating heat pump operation frequency and water pump rotation speed. According to the method, the partition control strategy based on temperature field modeling is established, the technical means such as unit pressure compensation and partition alternate starting are combined, accurate temperature control over all the heat supply areas is achieved, and the problem of uneven heat supply in the prior art is effectively solved.

An air conditioner load monitoring and anomaly detection method and system. The method comprises: acquiring user power consumption data and meteorological data, the user power consumption data and the meteorological data comprising the total power of an electricity meter, the power of an air conditioner, and the outdoor temperature, preprocessing the data, and computing electrical characteristics of the user power consumption data; on the basis of the electrical characteristics, learning by using a two-tower neural network so as to obtain operating rules of the air conditioner, and extracting an air conditioner operation curve; on the basis of the air conditioner operation curve, computing electrical characteristics and energy consumption characteristics of the air conditioner, and performing cluster analysis by using a K-means clustering algorithm; and, on the basis of clustering results, comparing the clustering results with clustering results of collected electrical data of the air conditioner under normal and abnormal operating conditions to determine whether the air conditioner is in an abnormal state, so as to implement detection of anomalies in the operation of the air conditioner, thereby improving the precision of load decomposition of the air conditioner, reducing application costs, providing a decision-making reference for equipment maintenance personnel, and prolonging the service life of the equipment.

The invention relates to the technical field of intelligent control, and particularly discloses a linkage control method for energy-saving ventilation equipment, which comprises the following steps of: acquiring indoor and outdoor temperature, indoor carbon dioxide concentration and personnel occupancy state data in real time; according to the method, deep collaborative analysis is carried out on the indoor personnel occupancy state and the deviation between the carbon dioxide concentration and a target set value, so that joint characterization of the current indoor fresh air volume regulation and control requirement is achieved, control parameters of a fresh air volume PI D controller are dynamically optimized accordingly, and a basic fresh air volume regulation instruction is calculated. On the basis, thermal disturbance introduced by fresh air is further quantified based on the outdoor and indoor temperature difference, and the thermal disturbance serves as a feedforward signal to be compensated to an air conditioner load adjusting loop, so that dynamic adjustment of the air conditioner load is achieved. In this way, cooperative control over ventilation and air conditioning systems can be achieved, the fresh air-air conditioning equipment energy consumption coupling conflict in traditional control is restrained, and therefore the building energy consumption is reduced while the indoor environment quality is guaranteed.

The invention relates to the technical field of intelligent building energy management, and particularly discloses an air conditioner load cluster optimization regulation and control method and system based on building thermal inertia modeling, and the method comprises the steps: collecting building structure parameters, building material thermophysical parameters, indoor and outdoor temperature and humidity historical data, air conditioner operation data and real-time electricity price data of a building; building a building thermal inertia model based on the collected data; inputting the collected air conditioner operation data, indoor and outdoor temperature and humidity historical data into a building thermal inertia model, and predicting air conditioner loads under different working conditions; constructing an optimized objective function, and solving the optimized objective function by adopting a genetic algorithm to obtain an optimal air conditioner load regulation and control strategy; and according to the optimal air conditioner load regulation and control strategy, the air conditioner load cluster is regulated and controlled in real time. The energy utilization efficiency can be effectively improved, the operation cost is reduced, and intelligent and refined regulation and control of the air conditioner load cluster are achieved.

The invention relates to the technical field of air-cooled air conditioner control, in particular to an air-cooled air conditioner control method and system based on deep learning, and the method comprises the following steps: obtaining sensor readings of indoor temperature, outdoor temperature and humidity and Wi-Fi channel state information, judging the position number and the activity state of personnel, calculating the position distribution of the personnel in combination with a time window, and calculating the position distribution of the personnel. And integrating to obtain a multi-dimensional environment and load state vector. According to the method, indoor and outdoor temperature, humidity, Wi-Fi channel state information and personnel position distribution and activity states are integrated through a multi-dimensional environment and load state vector, the personnel density change trend is dynamically calculated through a time window, the comprehensiveness and real-time performance of environment perception are enhanced, and high-dimensional data support is provided for control decision making. And a basic comfort degree deviation index is constructed based on the temperature deviation value and the humidity deviation value, and a multi-target performance index set is generated in combination with the wind speed value, the compressor start-stop frequency and the energy consumption power.

The invention relates to the technical field of air conditioner energy-saving systems, and discloses a central air conditioner energy-saving automatic control system and method.The central air conditioner energy-saving automatic control system comprises a sensor module, a control module, a communication module, an intelligent control algorithm module, a dynamic adjusting module and an energy-saving optimization module; the sensor module comprises a temperature sensor, a humidity sensor, a CO2 sensor, an illumination sensor and an occupation sensor, the temperature sensor is used for monitoring indoor and outdoor temperatures and providing real-time data for decision making of a control system, and an NTC (negative temperature coefficient thermistor), a PTC (positive temperature coefficient thermistor) or a DS18B20 digital temperature sensor is adopted. The environment parameters are monitored in real time, the operation state of the air conditioning equipment is dynamically adjusted, the high-energy-consumption operation mode of a traditional air conditioning system is avoided, cooling / heating according to needs is achieved, energy consumption is effectively reduced, the mode is automatically switched to the energy-saving mode in the state that the number of personnel activities is small or no one exists, and therefore the effect of remarkably reducing the operation load and energy consumption can be achieved.

The invention discloses an air conditioner control method and system, electronic equipment and a storage medium, and relates to the field of air conditioner control. The method comprises the following steps: determining an energy-saving award coefficient and a comfort award coefficient according to a current time period and a current season; constructing an energy-saving award function according to the energy-saving award coefficient, constructing a comfort award function according to the comfort award coefficient, and constructing an instant award function according to the energy-saving award function, the comfort award function and a punishment mechanism; state data and action data of operation of the air conditioner are obtained, the state data comprise the indoor temperature, the outdoor temperature and the temperature, the mode and the air speed set by a user, and the action data comprise air speed adjustment, mode adjustment and temperature adjustment; and the optimal action of the next state is determined according to the state data, the action data and the instant reward function, and the operation parameters of the air conditioner are adjusted according to the optimal action. By implementing the technical scheme provided by the invention, a more efficient and environment-friendly air conditioner control method is provided.

The invention relates to the field of factory intelligent cooling, and discloses an MPC-based large factory intelligent cooling system and a cooling control method, the system comprises a data acquisition module, an AI control module, a cooling tower control module, a cooling water pump control module and a cooling-water machine control module; the data acquisition module acquires outdoor environment temperature and humidity, cooling tower outlet water temperature, cooling water pump inlet and outlet water temperature difference and flow and water chiller operation state data in real time. The AI control module constructs a system model through real-time data, predicts and optimizes by using an MPC algorithm, and calculates optimal values of the running frequency of a cooling tower fan, the running frequency of a cooling water pump and the power of a cooling-water machine compressor by adopting sequential quadratic programming, so as to realize cooperative dynamic control of equipment in the system; the overall operation efficiency of the cooling system under the outdoor temperature and humidity change condition is effectively improved, and the overall energy consumption of the system is minimized in real time.

The invention relates to the field of smart home, and discloses a smart home environment sensing and energy-saving control system based on the Internet of Things, and the system comprises a sensing module which comprises an environment sensor unit and a human body sensor unit, and the environment sensor unit is used for collecting the indoor temperature, humidity, illumination intensity and air quality in real time; the human body sensor unit is used for detecting existence and activity conditions of indoor personnel; the Internet of Things communication module transmits data collected by the sensing module to the control module through Internet of Things communication; the energy-saving analysis module receives the data acquired by the sensing module, analyzes and processes the data, and judges whether to adjust the energy-saving strategy of each smart home according to the analysis result; the control module controls the operation state of each smart home according to the energy-saving strategy; the energy-saving strategy comprises the steps of automatically switching on and off light and air conditioning equipment according to the personnel activity condition, automatically adjusting the indoor illumination brightness according to the illumination intensity and adjusting the air conditioner operation parameters according to the indoor and outdoor temperature difference.

The invention relates to the technical field of photovoltaic inverter regulation and control, in particular to a photovoltaic inverter intelligent regulation and control method and system based on the Internet of Things, and the method comprises the following steps: setting a time window based on an illumination prediction value of a photovoltaic inverter and a real-time voltage measurement value of a grid-connected point, and carrying out the serialized calculation of the voltage in the window, and establishing an out-of-limit risk early warning. According to the invention, the time window is set based on the illumination prediction value and the grid-connected point voltage measurement value, serialized calculation is carried out on the voltage in the window, and point-by-point comparison with the voltage threshold is carried out, so that an out-of-limit risk time point can be identified in advance, and the pre-warning capability of local voltage abnormity is improved. On the basis, a voltage out-of-limit amplitude value is extracted by combining indoor and outdoor temperature information of a building and is converted into a voltage regulation requirement, and a quantifiable voltage consumption index is further formed, so that power load regulation is changed from traditional static setting to dynamic quantifiable regulation, and the accuracy of regulation response is effectively improved.

The invention discloses an energy-saving ground source heat pump control method and system, and the method comprises the steps: building a ground source heat pump system dynamic model which comprises an indoor heat balance model, a ground source heat pump unit model and a soil heat exchange model, obtaining a topological network through coupling, designing a distributed control and fault-tolerant operation strategy according to the topological network structure, and carrying out the control of the ground source heat pump system. Each node is locally controlled according to the position and adjacent node information, a state space model is constructed, an optimal control action sequence is solved through quadratic programming to balance energy consumption and an indoor and outdoor temperature deviation objective function, the optimal operation state is obtained, and the mapping relation between the optimal operation state and environment parameters is learned through a neural network; a ground source circulation flow control algorithm is designed, and circulation pump flow distribution and unit working parameter automatic adjustment are achieved. According to the method, the control precision and stability of the ground source heat pump system can be effectively improved, reliable operation of the ground source heat pump system under complex working conditions is ensured, the energy utilization efficiency is remarkably improved, energy conservation and consumption reduction are achieved, and meanwhile good interpretability is achieved.

According to the chicken coop temperature prediction algorithm based on the TCN-Transform, the temperature, the humidity and the ventilation quantity in the chicken coop are automatically adjusted in a mode of combining real-time monitoring and a prediction model, so that the growth environment of broiler chickens is optimized; a sensor is used for collecting internal and external environment data of a henhouse, and in combination with a prediction model based on TCN and Transformer, a future temperature change trend is estimated; a PID controller is adopted, the ventilation requirement is calculated in real time according to the target temperature, the current temperature, the predicted temperature and the outdoor temperature, the starting number and starting time of fans are output so that it can be ensured that the temperature of the henhouse can be kept within the target range all the time, PID control parameters are dynamically adjusted through the growth data of chickens, and the ventilation strategy is optimized so that the requirements of different growth stages can be met. By using the chicken coop temperature prediction algorithm based on TCN-Transformer, the prediction precision and the reaction speed can be improved, dynamic adjustment is performed according to the actual chicken coop environment, and the production benefits of a farm are improved.

The invention relates to the technical field of constructional engineering, and discloses an intelligent ventilation and purification method and system for constructional engineering, and the method comprises the steps: 1, determining the concentration of pollutants in a building based on real-time air quality data, and calculating the required ventilation quantity meeting a preset standard; secondly, the fresh air introduction proportion is adjusted according to the indoor and outdoor temperature and humidity difference value so as to optimize energy consumption and thermal comfort balance; 3, according to the personnel distribution density, the local area air supply intensity is set, and the air circulation uniformity is ensured; fourthly, the system operation mode is regulated and controlled based on the working state of the air purification equipment, so that energy consumption is reduced, and the service life of the equipment is prolonged; the fresh air introduction proportion is intelligently adjusted by comparing indoor and outdoor temperature and humidity differences. For example, when the outdoor temperature and humidity are close to the indoor comfortable interval, the fresh air volume is increased to utilize natural cold and heat sources; when the outdoor environment is extreme, the fresh air volume is reduced, the heat recovery device is started, the air conditioner load is reduced, and energy waste is reduced.

The invention relates to the technical field of building energy conservation, in particular to an edge computing cooperative communication method for multiple heat pumps and a photovoltaic system, which comprises an edge server, a cloud server, multiple heat pumps, a variable frequency pump and an indoor and outdoor heat supply device, and is characterized in that the edge server realizes time synchronization of equipment through an OPC UA over TCSN protocol, a multi-level energy topology network is established, and the multi-level energy topology network is connected with the cloud server; in combination with physical energy flow and information flow, based on a building heat balance equation, an edge server controls a heat pump to work at an energy-saving operation point according to indoor and outdoor temperatures and user requirements, and the flow of a variable frequency pump is adjusted. In addition, multi-mode state sensing is achieved through the distributed sensor network, a layered self-adaptive control strategy is executed, photo-thermal collaborative optimization and heat pump group collaborative control are achieved, the system collaborative control precision is remarkably improved through the method, the time synchronization error is reduced by three orders of magnitude, and the system response speed reaches the millisecond level and is 10 times faster than that of a traditional system.

The invention discloses a hospital public building temperature refined energy-saving regulation and control method, which comprises the following steps: establishing a refined hierarchical management architecture based on use requirements and energy use purposes of different wards; for a conventional inpatient ward, door and window opening and closing state data and ward heat state data are collected, and air conditioner operation control and door and window opening and closing state adjustment are executed based on a window magnetic control air conditioner operation model and by adopting a multi-step prediction control method; for different types of special wards, regulating and optimizing corresponding thermal equipment by adopting a multi-step prediction control method under an MPC model prediction control framework according to thermal parameters required to be controlled by the current type of ward; for outpatient wards, outpatient air conditioner output operation is optimized by adopting a multi-step prediction control method based on a cooling load prediction model according to the flow density, the temperature and the indoor and outdoor temperature difference; according to the invention, monitoring and accurate prediction of the thermal condition in the ward are realized based on the model prediction control MPC method in combination with the window magnetic switch.

An implementation of the disclosed technology provides a method that includes receiving a setpoint temperature for the building, determining an average outdoor temperature over a first predetermined time period for a location of the building, measuring a total central heating energy consumption for the building over the first predetermined time period, adding the determined average outdoor temperature and measured total central heating energy consumption to a first data set including a plurality of average outdoor temperatures and corresponding total central heating energy consumptions over a plurality of predetermined time periods having durations substantially the same as the first predetermined time period, estimating a weather independent normalized heating energy consumption for maintaining the setpoint temperature in the building based on a predetermined reference outdoor temperature and the first data set, and characterizing the heating energy consumption for heating the building based on the normalized heating energy consumption and a base temperature wherein the base temperature is the outdoor temperature at which heating is required to keep an indoor temperature minimally at the setpoint temperature and wherein the base temperature is selectively obtained by way of optimization and / or linear fit and / or distribution based approach. (1)

The invention discloses an air conditioner automatic control method and system based on a cold and heat source machine room, and relates to the technical field of air conditioner automatic control. Calculating a cold and heat source switching index K1 according to the deviation between the outdoor temperature T1 and the target temperature T0 in combination with the change trend of the relative humidity H1; when the cold and heat source switching index K1 exceeds a preset threshold value, a load prediction module is started, and a load prediction value P1 is generated; and according to the load predicted value P1, the rotating speed of the water pump is controlled in a gradient adjustment mode, and the valve opening V1 is dynamically adjusted through the temperature difference between the water supply temperature T2 and the water return temperature T3. The system operation accuracy, the energy utilization efficiency and the adjustment flexibility are remarkably improved, the rotating speed of the water pump and the opening degree of the valve can be accurately adjusted dynamically in real time according to outdoor temperature and humidity changes and equipment operation characteristics, and the technical problems that an air conditioning system is inaccurate in control and large in energy consumption fluctuation are effectively solved.

The invention discloses a dynamic building thermal load simulation method and device, heat supply equipment and a medium, and relates to the technical field of load prediction.The method comprises the steps that when the environment temperature changes, the first building unit area thermal load before change is determined, and the second building unit area thermal load after change is determined; determining a first heat change of the building external envelope structure and a second heat change of the building internal envelope structure caused by the environment temperature change; according to the difference value of the unit area thermal load of the first building and the unit area thermal load of the second building, the delay time is determined in combination with the heat change of the building envelope; and based on the delay time, the outdoor temperature before the delay time and the current indoor temperature are utilized to correct the unit area thermal load of the second building. By adopting the method, the calculation complexity of dynamic building thermal load simulation can be simplified, and the calculation of the delay time is more practical and operable.

The invention provides a heterogeneous building air conditioner group quick response control method based on physical information deep learning, and the method comprises the steps: 1, obtaining a real-time discrete step scheduling instruction issued by a power grid, obtaining the thermodynamic parameters and equipment inertia time constants of all building units in a heterogeneous building group, obtaining the outdoor temperature, and carrying out the real-time discrete step scheduling instruction; the solar radiation intensity and the indoor air temperature of each building unit; step 2, extracting spatial-temporal characteristics of each building unit based on a multi-head self-attention mechanism, and generating initial distribution target power of the air conditioner; 3, inputting the initial allocation target power into a pre-trained cascaded physical information neural network (PINN), and predicting power and temperature evolution tracks in a future scheduling period; 4, calculating an out-of-limit risk index of each unit, judging whether to execute a quantile risk migration strategy or not, and generating a final distribution target power of the air conditioner; and 5, calculating the transient climbing deviation between the actual aggregation power and the target power of the power grid, and carrying out deviation compensation.

The invention relates to the technical field of air conditioners, and provides a compressor frequency control method and device of an air conditioner and an air conditioning system.The control method comprises the steps that the current indoor temperature, the current compressor frequency and the current outdoor temperature are obtained; based on the current indoor temperature, the current compressor frequency and the current outdoor temperature, the next indoor temperature corresponding to the next operation stage is determined; the temperature difference value between the next indoor temperature and the preset target temperature is determined; and under the condition that the temperature difference value is larger than a preset threshold value, the operation frequency of the compressor is adjusted based on the temperature difference value and a preset temperature difference, so that the next compressor frequency is obtained. According to the method, the next indoor temperature of the next operation stage is predicted, the temperature change trend is predicted in advance, then the frequency of the compressor is dynamically adjusted by calculating the temperature difference value between the next indoor temperature and the preset target temperature, fluctuation of the indoor temperature is effectively reduced, and the comfort of a user is improved; and by optimizing the operation frequency of the compressor, the energy utilization efficiency is remarkably improved.

The utility model belongs to the technical field of heat dissipation and cooling, and particularly relates to an active balance type gravity assisted heat pipe, which comprises a condenser, an evaporator and a plurality of liquid storage tanks, the condenser is respectively connected with inlets of the plurality of liquid storage tanks through a first liquid downcomer, outlets of the plurality of liquid storage tanks are respectively connected with the evaporator through a second liquid downcomer, and the second liquid downcomer is connected with the evaporator. The evaporator is connected with the condenser through a gas ascending pipe, the gas ascending pipe is connected with the liquid storage tanks through bypass pipelines, and when the temperature difference T between the user heat dissipation end temperature T and the environment temperature T is smaller than or equal to the threshold value T, different liquid storage tanks are alternately used for liquid storage and liquid supply. The liquid storage tank for liquid supply is communicated with the evaporator and the gas ascending pipe, and the liquid storage tank for liquid storage is communicated with the condenser; according to the active balance type gravity assisted heat pipe, the gravity assisted heat pipe can be started smoothly when the indoor and outdoor temperature difference is small; and meanwhile, liquid supply and refrigeration working medium circulation can be promoted, and the heat exchange / heat dissipation effect is improved.

The invention discloses a building air conditioning system partition control method based on the KNX technology, and relates to the related technical field of building air conditioning systems.The method comprises the steps that building structure information and air conditioning system topological information are obtained based on the KNX protocol, and an air conditioning control partition set is divided; a target temperature interval is set, and global optimization of partition target temperature is carried out; according to real-time data collected by indoor and outdoor temperature sensors, the reference personnel density and a partition control target are combined, and partition control parameters of all air conditioner control partitions are initialized; and based on the personnel flow data, the air conditioner operation parameters of all the air conditioner control subareas are dynamically adjusted, and the personnel flow direction is predicted to execute prospective regulation and control. The technical problems that in the prior art, fine regulation and control are difficult to conduct according to actual requirements of different functional areas in a building, consequently, energy of an air conditioning system is wasted, and the comfort degree of a user is poor are solved, and the technical effects of reducing air conditioner energy consumption and improving the comfort degree of the user are achieved.

The invention discloses an energy-saving self-control and intelligent monitoring system for a central air conditioner, relates to the technical field of energy-saving air conditioners, and aims to solve the technical problem of high energy consumption caused by incapability of precise regulation and control in the prior art. Comprising a touch screen, a display unit and a remote mobile terminal interaction interface. The data acquisition module is used for acquiring indoor and outdoor parameter information in real time, including indoor and outdoor temperature, humidity, air volume, air outlet temperature, pressure and time information; the data processing module is used for calculating the cold load capacity of each area according to the indoor and outdoor parameter information, generating the change rate of the air outlet temperature difference based on the cold load capacity and the air outlet temperature difference, and obtaining a cold load capacity change signal according to the change rate of the air outlet temperature difference of each area; and a data storage module. The method has the advantages that the air outlet cooling load capacity of each area is dynamically adjusted, energy waste is avoided, and the energy-saving effect is achieved.

The invention discloses a cluster temperature control and energy consumption balance optimization control system for group air conditioners, and relates to the technical field of intelligent control, the system comprises a data acquisition module, temperature data of each indoor area and outdoor temperature change information are acquired in real time through a sensor network, and a preset temperature threshold value interval is combined to determine the temperature of each indoor area; analyzing heterogeneity characteristics of indoor temperature distribution to obtain a temperature distribution state of each area; according to the air conditioner cluster temperature control and energy consumption balance optimization control system, the operation efficiency of an air conditioner system and the comfort degree of a user can be effectively improved, and intelligent temperature management is achieved.

The invention relates to the field of household appliances, and provides a control method and device for a fresh air ventilator air conditioner and an air conditioner. The method comprises the steps that indoor and outdoor environment data and air conditioner power are obtained, and the indoor and outdoor environment data comprise indoor and outdoor air quality data and indoor and outdoor temperature data; according to the indoor and outdoor environment data and the power of the air conditioner, the optimal control power of the fresh air ventilator and the optimal control power of the air conditioner are determined in combination with a multi-target optimization model; and according to the optimal control power of the fresh air ventilator and the optimal control power of the air conditioner, the corresponding fresh air ventilator and the air conditioner are controlled to operate. According to the method, the problem that multiple environmental factors cannot be synthesized for dynamic adjustment based on control of a fixed threshold value and a single parameter is solved, the energy efficiency and the indoor comfort degree are considered at the same time by integrating the environmental data, the lowest energy consumption scheme meeting the requirements of environmental health and room temperature change is found out, and cooperative control of the fresh air ventilator and the air conditioner is achieved.

The invention discloses heat supply equipment based on computing power and a control method, and belongs to the technical field of heat supply control. The method comprises the following steps: acquiring heat supply data, and performing anomaly detection on the heat supply data; when the heat supply data is not abnormal, the distribution condition of the hot water in the heat supply pipe network is analyzed, and a flow analysis result and a pressure analysis result are obtained; optimizing the operation parameters of the heat supply network, and calculating the heat recovery efficiency of the heat supply network; constructing and training an autoregressive integral moving average model, inputting current power utilization related data and heat recovery efficiency, and outputting a thermal load demand prediction value; influence weights of the indoor temperature and the outdoor temperature on the thermal load demand are determined, a temperature difference is calculated, a temperature correction coefficient is calculated according to the temperature difference, and a thermal load demand prediction value is adjusted by using the temperature correction coefficient; setting a power corresponding relation, and adjusting the power of the electric boiler by stages; the operation time and the stop time of the electric boiler are calculated according to the operation state data of the electric boiler, and the electric boiler is set according to the operation time and the stop time obtained through calculation.

The invention discloses a subway tunnel piston air valve control method and device, electronic equipment and a storage medium, and the method comprises the steps: monitoring indoor and outdoor air indexes of each section of a subway tunnel, judging whether a triggering condition is satisfied or not according to at least one of the temperature and humidity in the indoor and outdoor air indexes, and determining a target control mode, so as to control the opening degree of a piston air valve, when the outdoor temperature is higher than the tunnel temperature or the outdoor humidity is too high, the opening degree of the piston air valve is reduced or even the piston air valve is closed, so that the tunnel is kept at low temperature and humidity, a low-temperature environment is provided for air conditioners of running trains in the tunnel and air conditioners in stations, and energy consumption of the air conditioners is reduced; when the outdoor temperature is lower than the tunnel temperature, the opening degree of the piston air valve is controlled to be increased; tunnel cold storage or heat storage and air conditioner energy conservation are achieved through asymmetric piston air ventilation, and the tunnel can learn to breathe; in addition, influence on electronic equipment, line safety and driver sight caused by condensation or fog due to too high humidity is avoided, safety risks and hidden dangers are reduced, and safe operation is ensured.