117 results about "Environment controlled" patented technology

The invention discloses a method and a system for adjusting the internal environment of a mobile laboratory cabin, particularly relates to the technical field of environment control, and aims to solve the problem that the existing environment adjusting method adopts a fixed control target and cannot adapt to differentiated environment requirements in a multi-task scene of a mobile laboratory. The method comprises the following steps: acquiring a current task identifier of a mobile laboratory, identifying a corresponding experiment task execution stage, and dynamically generating an inter-parameter collaborative constraint relation matrix based on a fuzzy inference rule base; a regulation and control demand vector is generated by collecting a multi-dimensional environmental parameter measurement value and combining a pre-stored environmental parameter expected value; calculating a regulation and control conflict risk entropy value based on the matrix and the vector, and performing risk judgment; when the risk tolerance is exceeded, a roundabout regulation and control strategy is generated as an optimization guide parameter; finally, an environment control instruction is generated in a coordinated mode according to the optimized guiding parameters and sent to an executing mechanism; the dynamic adaptation of the environmental parameter regulation and control strategy and the experiment task is realized, and the precision and reliability of multi-parameter cooperative control are improved.

The invention provides a PID-based clean room intelligent regulation and control system and method. The system comprises a multi-parameter sensing module used for monitoring real-time environment data in a clean room in real time; the data processing module is used for preprocessing the real-time environment data to obtain monitoring data; the PID control module is used for determining the deviation between the monitoring data and a preset target parameter value, and determining an environment control signal based on the deviation; the environment regulation and control execution module is used for regulating the operation state of corresponding environment regulation equipment in the clean room according to the environment control signal; the multi-factor coupling prediction model is used for predicting a change trend of cleanliness according to the real-time environment data and historical environment data in the clean room, and optimizing control parameters of the PID control module based on the change trend; and the human-computer interaction interface is used for displaying real-time environment data, an operation state and a change trend, so that high-precision and high-stability dynamic cooperative control and intelligent prediction of various environment parameters in the clean room are realized.

The invention relates to the technical field of laboratory environment control, and discloses an environment parameter control method and system for a complex laboratory, and the method comprises the steps: obtaining environment index data, and carrying out the time sequence processing, and obtaining a real-time change trend; according to the real-time change trend, predicting a future offset by using a prediction model, and performing data fusion when the offset exceeds a threshold value to obtain an accurate environment state estimated value; according to the accurate environmental state estimation value, quantifying the mutual influence among the environmental indexes to obtain the mutual influence relationship of the environmental indexes; determining an environment index priority sequence according to the mutual influence relationship; generating and executing a control instruction according to the priority sequence; and when continuous deviation exists, the prediction model and the mutual influence relation are updated through feedback circulation. According to the method, the dynamic mutual influence among the environmental indexes can be quantified, and accurate and stable cooperative control of multiple parameters in a complex dynamic environment is realized.

The invention discloses a paint spraying room temperature and humidity control system based on the Internet of Things, and relates to the technical field of industrial coating environment control. Accurate perception and disturbance pre-judgment of gate opening and closing behaviors are realized by means of cooperation of a gate state detection module and an environment monitoring module; the predictive sub-module dynamically evaluates the disturbance risk level by analyzing the door opening and closing frequency, the duration time and the environment difference, so that the control action is converted into beforehand intervention from post-event compensation; humiture sudden change caused by opening of the gate is effectively inhibited, and the overshoot phenomenon caused by response delay is reduced; meanwhile, an Internet of Things architecture is introduced, and the decision dimension of the system is expanded; the cloud collaborative management module optimizes control parameter distribution by summarizing operation data of a plurality of spray booths and utilizing a consistency algorithm, so that mutual interference caused by coupling of ventilation systems of adjacent spray booths is avoided; and the local intelligent control unit can be automatically degraded to a cache strategy when the cloud is unavailable, so that the control continuity is ensured.

The invention relates to the technical field of environment control, in particular to a cold and heat source environment control method and device with an air purification function, and the method comprises the steps: collecting various parameters through a sensor network, and carrying out the data fusion based on a decision rule base to select a dominant working mode; corresponding air treatment operation is executed, and a composite energy-saving strategy including precooling optimization and phase change latent heat assistance is triggered under the refrigeration working condition; fuzzy control and machine learning are applied to optimize system output and predict load, and a decision rule base and algorithm parameters are updated through self-learning; air supply and exhaust power is controlled to maintain the negative pressure gradient of the key area, and an air path distribution mechanism is adjusted to organize a one-way air flow line; the device comprises an intelligent control module, a sensor group, a fresh air module, a purification module, a cold and heat source module, a bypass pipeline and an air path distribution mechanism. The problems that an existing system is poor in function collaboration, low in energy efficiency and unreasonable in airflow organization are solved, and intelligent decision making, deep energy saving and accurate environment control are achieved.

The invention discloses an environment control method, system and device for a mobile high-voltage chamber and a medium, and belongs to the technical field of high-voltage chamber environment regulation and control, and the method comprises the following steps: dividing the mobile high-voltage chamber into A analysis regions, and setting a temperature control intelligent agent in each analysis region; the method comprises the following steps: acquiring equipment state data of an analysis area through a temperature control intelligent body, and performing reconstruction analysis on the equipment state data by using an auto-encoder to obtain a state label; combining the temperature control intelligent agent with the state label, and calculating equipment state data to obtain a health state matrix; environment data of each analysis area is collected in real time, a microclimate situation map is formed in combination with the health state matrix, and an optimal partition temperature control instruction is generated; and adjusting the environment of each analysis area through the optimal partition temperature control instruction. The method has the beneficial effects that the mobile high-voltage chamber is divided into a plurality of analysis areas, and the temperature control intelligent agent is arranged in each area, so that the fundamental conversion from the traditional centralized control to the distributed cooperative control is realized.

The invention discloses a green building energy consumption adaptive regulation and control system based on dynamic environment parameters, and relates to the technical field of building energy consumption regulation and control, and the system comprises a multi-source environment sensing module which comprises a plurality of environment parameter collection devices which are arranged at different spatial positions of a building atrium area and are used for collecting various kinds of environment parameter information, generating a structured data packet; and the control analysis module is used for receiving the structured environment data packet, performing field analysis, generating a control intention set based on a preset atrium environment control rule, identifying an environment parameter conflict relationship caused by vertical spatial characteristics of the atrium, and outputting the control intention set with a conflict identifier. According to the invention, multi-point synchronous acquisition of parameters such as temperature, humidity, air quality and illumination intensity in a building atrium area is realized through environment parameter acquisition devices arranged at different spatial levels, and a comprehensive credibility weight is generated in combination with personnel quantity information to construct a structured data packet.

The invention relates to the technical field of green building environment monitoring, and discloses a green building environment monitoring system and method and a storage medium. The method comprises the steps that environmental parameters such as thermodynamic parameters, humidity parameters and gas concentration parameters are continuously collected through intelligent sensing nodes at multiple positions in a green building; the environment parameters are transmitted to a central processing unit, and the central processing unit combines a pre-stored environment standard value and a real-time data stream and generates an environment control command by adopting a self-adaptive learning algorithm; the environment execution device carries out an environment regulation activity according to the command; and monitoring and adjusting an activity execution sequence in real time, calculating a performance evaluation index, generating a normal or abnormal performance state signal, and automatically triggering an alarm process when the performance state signal is abnormal. According to the method, a complete environment management and control closed loop is constructed, all-directional dynamic monitoring and accurate adjustment of the environment of the green building are achieved, the core requirements for environment protection and comfort of the green building are met, and it is guaranteed that the internal environment of the building is in a proper state.

The invention relates to the technical field of cold chain transportation environment control, and discloses a temperature and humidity control system for cold chain transportation, and the system comprises an environment modeling module which is used for constructing a heat conduction model of a cold chain space based on a random field theory and a finite element method, and outputting a stiffness matrix containing random parameters; the self-adaptive sensing network module is used for receiving the characteristic information of the stiffness matrix, dynamically optimizing sensor distribution positions, collecting multi-node temperature and humidity data and adding space-time labels; and the distributed data processing module is used for receiving the sensing data. According to the invention, through random field theoretical modeling and parameter-state joint estimation, the temperature field prediction precision is significantly improved and the system environment adaptability is enhanced; a distributed sensing network architecture and a heterogeneous calculation acceleration technology are combined, so that the cooperative control with optimal energy efficiency is realized while millisecond-level real-time response is ensured, and the performance bottleneck of a traditional cold chain temperature control system is comprehensively broken through.

This invention provides a warehouse management method for emergency supplies in smart facilities. It obtains production date, shelf life, and initial environmental parameters by parsing electronic tags on emergency supplies. A dynamic suitable temperature range is generated based on a nonlinear mapping between shelf life and initial temperature value, and a dynamic suitable humidity range is generated based on a correlation model between production date and initial humidity value. The overlap between the remaining shelf life and the suitable temperature range is calculated as a first priority factor, combined with the real-time warehouse load rate to generate a second dynamic allocation factor. A priority fusion algorithm is used to integrate and generate a material allocation matrix. The target warehouse environmental parameters are monitored in real time. When parameters exceed the suitable range, a multi-level adjustment strategy is triggered. If verification fails, a parameter self-learning engine is activated, achieving intelligent control and optimization of the warehouse environment, improving the safety and management efficiency of emergency supplies storage. This application can dynamically adapt to changes in material characteristics and optimize the precision of warehouse environment control.

The invention relates to an energy storage system state adjusting method and device, an energy storage system and related products. The method comprises the following steps: acquiring environment data acquired by an environment sensor of at least one bin in the energy storage system, and acquiring an environment data threshold value of the bin; determining an environment control mode required by the bin according to the environment data of the bin and an environment data threshold value; determining at least one target unit in a plurality of working units of the environment adjusting equipment according to the environment control mode required by the bin, and controlling the environment control mode required by the target unit for the operation of the bin; different working units are used for operating different environment control modes; the energy storage system comprises environment adjusting equipment and a plurality of bins, the environment adjusting equipment comprises a plurality of working units, an environment sensor is arranged in each bin, and each bin is connected with the corresponding working unit through a pipeline; according to the method, the flexibility of adjusting different bin environment states in the energy storage system is improved.

The present application relates to the technical field of building ventilation and environmental control, and provides a differential pressure gradient control method, device, equipment and storage medium for a multi-room laboratory, wherein current differential pressure data and interference source state signals of the room are acquired, and interference source state signals of other rooms are received through a communication connection; feedback air volume adjustment instructions are generated based on the differential pressure data through a feedback algorithm; interference source state signals of the room and / or other rooms are input into a feedforward model to generate feedforward air volume adjustment instructions; feedback and feedforward instructions are superimposed to generate total air volume adjustment instructions to adjust air supply or exhaust volume; and the interference source state signals of the room are sent to other rooms when an interference event is detected. Through feedforward-feedback composite control and inter-room collaborative early warning, the present application realizes rapid response, global stability and flexible deployment of the differential pressure gradient.

The invention is suitable for the technical field of storage regulation and control, and provides an irradiation storage environment regulation and control method based on multi-modal data fusion, and the method comprises the steps: obtaining a voice instruction inputted by a user and image data of a to-be-irradiated object, and determining a storage environment parameter value; collecting environment data of a storage area where the to-be-irradiated article is located and performing fusion estimation to obtain an environment state vector and an equipment state vector; performing environment state prediction based on the storage environment parameter value, the historical environment state vector and the historical equipment state vector to obtain an environment state prediction value and a comprehensive risk assessment value; and processing the current environment state vector, the current equipment state vector, the environment state prediction value, the comprehensive risk assessment value and the storage environment parameter value by using a deep reinforcement learning network to obtain control parameters of the environment control equipment. The perception-prediction-decision regulation and control mode designed by the invention can improve the regulation and control precision of the storage environment and reduce the influence of fluctuations such as temperature and humidity on the quality of articles to be irradiated.

The utility model discloses a micro-pressure oxygen-enriched cabin environment temperature regulation system, belonging to the technical field of special environment control equipment, which includes a control center module, a temperature sensing module, an actuator module and a safety protection module. The control center module is electrically connected to the temperature sensing module. The safety protection module is installed on the actuator module, and the safety protection module and the actuator module are respectively electrically connected to the control center module. Under the conditions of maintaining micro-pressure (usually 1.1 to 1.3 atmospheres) and oxygen enrichment (oxygen concentration of 21% to 30%), it ensures that the temperature inside the cabin is stable within a comfortable range, and the temperature can be set arbitrarily, usually 20 to 26 °C. It automatically controls the start and stop of the environment temperature regulation system according to the change of temperature, realizes the linkage control of the micro-pressure oxygen-enriched cabin and the environment temperature regulation system, and is convenient to operate and use.

The invention discloses an evaluation method of an environment control system. The evaluation method comprises the following steps: acquiring operation data, a first-dimension evaluation standard and a second-dimension evaluation standard of the environment control system; wherein the first dimension evaluation standard and the second dimension evaluation standard are evaluation standards of different dimensions corresponding to different subsystems or devices in the environment control system; performing first-dimension evaluation according to the first-dimension evaluation standard and the operation data to obtain a first-dimension score; performing second-dimension evaluation according to the second-dimension evaluation standard and the operation data to obtain a second-dimension score; and obtaining operation evaluation according to the first dimension score and the second dimension score. According to the evaluation method of the environment control system, evaluation of different dimensions corresponding to different subsystems or devices in the environment control system can be taken into consideration for multi-dimensional fault evaluation analysis, the problems of low-efficiency work, improper control functions and the like of the environment control system can be found in time, and therefore operation and maintenance work can be effectively guided according to operation evaluation.

This invention discloses an intelligent constant temperature and pressure control system for a cleanroom, comprising: a data acquisition module for deploying sensors to collect data and transmit it to a control unit; a data processing module for calibrating, filtering, and synchronizing data, and inputting it into an MLP network to extract features; a coupling prediction module for establishing a prediction model, calculating deviations, and generating a control error vector; a process control module for executing control strategies based on the error vector and determining equipment operating parameters; an execution control module for transmitting adjustment commands and driving synchronous adjustment of the equipment; and a closed-loop feedback module for collecting adjusted data and feeding it back to the control unit to achieve closed-loop regulation. This invention, through an intelligent control system, adjusts the temperature, pressure, and airflow of the cleanroom in real time, improving environmental control accuracy, energy efficiency, and stability, and ensuring the efficient and reliable operation of the experimental environment.

The invention relates to the technical field of advanced manufacturing, in particular to a high-temperature and high-pressure metal three-dimensional component laser printing forming cabin which comprises a high-pressure welding and monitoring system used for providing a high-temperature and high-pressure environment for the workpiece forming process, monitoring a molten pool in real time and capturing the dynamic behavior of the molten pool; the environment control system is used for controlling the temperature and the pressure in the hyperbaric cabin assembly and simulating environment parameters of different working conditions; the electric control system is used for accurately controlling and adjusting power supply, signal transmission and operation parameters of the high-pressure welding and monitoring system and the environment control system to realize preset functions of the electric control system; the integrated cabinet body is used for installing the high-pressure welding and monitoring system, the electric control system and the environment control system and guaranteeing the safety of operators; the high-temperature and high-pressure environment can be simulated, and a multi-parameter in-situ monitoring function is integrated.

The invention provides a GIS room environment control method and system, and the method comprises the steps: collecting GIS room environment parameter data, and when the GIS room environment parameter data does not meet a preset environment condition, closing an access control, the GIS room environment parameter data comprising GIS room SF6 gas concentration; obtaining a GIS room work task and a priority thereof, and according to the GIS room work task and the priority thereof and a preset target SF6 gas concentration, determining a GIS room ventilation duration; according to the ventilation duration of the GIS chamber, driving GIS chamber air exchange equipment to ventilate through wireless communication, and after an instruction for indicating that ventilation of the GIS chamber air exchange equipment is finished is received, collecting environmental parameter data of the GIS chamber after ventilation; and if the environmental parameter data of the ventilated GIS room does not meet the preset environmental condition, triggering air conditioning equipment of the GIS room to carry out supplementary adjustment until the preset environmental condition is met, and opening an access control. Therefore, the operation preparation time is greatly shortened.

The present application relates to the field of reagent environment control, and particularly relates to a reagent storage environment control system for multi-classification reagent kits and a reagent kit, the control system comprising an initial-to-bin module, an environment pre-adjustment module, an opening and closing management module, a door closing recovery module, an execution action module and a database, and is matched with the classification information of the reagent kit in the database through a scanning mode, automatically outputs a reagent cabinet number and generates an opening cabinet signal, and constructs an internal and external environment difference vector, combines a digital twin model to simulate a candidate control strategy, and outputs an optimal control parameter vector through a comprehensive cost function to select the optimal output, realizes intelligent pre-adjustment of the internal environment of the cabinet before opening the door, and combines periodical convergence verification and maximum pre-processing time length double constraints to issue an automatic opening door instruction when all the environment parameters are compliant and there is a safety margin, and real-time monitoring of the cabinet door closing state is realized, convergence and fluctuation double determination is completed to realize steady state recovery, a suboptimal event is recorded when the time is up, and an alarm is triggered when the limit is exceeded.

The application discloses a biological sample storage integrated equipment and belongs to the technical field of biological sample storage. The biological sample storage integrated equipment comprises a storage cabin, an operation cabin is arranged on one side of the storage cabin, a plurality of groups of storage devices are arranged in the storage cabin, a plurality of groups of multimodal acquisition units and a plurality of groups of miniature parameter adjustment units are independently arranged on the lower middle area of the inner side wall of the storage cabin, the position close to the top of the operation cabin on the top of the operation table, the outer side wall of the docking transfer assembly and the docking assembly of the transfer frame, and a control system is arranged in a controller. The application solves the problems of lack of personalized environment control mechanism, slow response, easy to cause environmental out of control and sample damage, and low data management security in the prior art, guarantees the stability of sample storage, ensures uninterrupted environment control instruction, data transmission and execution mechanism control, realizes full-process parameter tamper-proof and traceability, and reduces the sample damage risk.

The application discloses a kind of mine local ventilation and cooling system methods based on liquid air, it is related to mine environment control technical field, including intelligent conveying pipeline, intelligent multi-mode release device, air purification and energy recovery device and mine environment adaptive monitoring and control system;The intelligent conveying pipeline includes multilayer composite insulation structure and intelligent control module, the intelligent control module includes temperature sensor, pressure sensor and flow sensor, for real-time monitoring and adjusting the delivery state of liquid air;The intelligent multi-mode release device includes the intelligent release device of plasma vaporization, ultrasonic nanometer atomization and vortex synergistic function, the efficient conversion and accurate distribution of liquid air from storage to working face are realized by the steps of the application through intelligent multi-mode release device, according to mine environment parameter real-time adjustment air velocity and direction, ensure the uniform distribution and local cooling effect of fresh air, improve the air quality of work area.

The invention discloses a safety cabin air exchange control method based on artificial intelligence, and belongs to the technical field of environment control, and the method comprises the steps: collecting internal and external multi-mode environment data of a safety cabin in real time, processing time sequence data through a recurrent neural network, constructing a state space representing a dynamic change rule, and carrying out the control of the air exchange of the safety cabin based on the state space. And generating an optimal air exchange control strategy through the reinforcement learning model. The complex relation between the environment and the equipment is dynamically learned through the artificial intelligence model, conversion from fixed threshold value control to target-oriented self-adaptive control is achieved, the problem of response lag of traditional timing or fixed threshold value control is solved, and on the premise that the oxygen content and the air cleanliness in the cabin are absolutely guaranteed, the target-oriented self-adaptive control can be achieved. External pollution is intelligently avoided, a ventilation strategy is dynamically adjusted, and finally the balance between safety and energy consumption optimization is achieved.

This invention discloses a multidimensional mechanical fatigue testing system based on high-temperature environments, specifically relating to the field of testing machine technology. The system includes: a torsional fatigue testing module, a tensile-compressive fatigue testing module, a high-temperature environment control module, a servo-hydraulic control module, and a temperature influence correction unit. This multidimensional mechanical fatigue testing system based on high-temperature environments integrates torsional fatigue testing and tensile-compressive fatigue testing modules, enabling the simultaneous application of multidimensional alternating loads such as torsion and tension / compression. Simultaneously, the high-temperature environment control module dynamically adjusts the temperature, and combined with the temperature influence correction unit and a series of accuracy correction formulas, effectively eliminates the interference of high temperatures on material properties and sensor accuracy. It avoids data distortion caused by the lack of a systematic temperature correction mechanism, making the test results closer to actual service conditions and providing more reliable performance data for engineering applications.

The invention discloses a building environment self-adaptive regulation and control method and system based on a space-time attention mechanism, and the method comprises the steps: collecting environment data, such as temperature, flow density, humidity and air pressure, and constructing a three-dimensional thermodynamic model through a dynamic weighted Bayesian collaborative fusion algorithm; the method comprises the following steps: processing environment data by virtue of a space-time cross attention network, and generating a regulation and control priority map with a dynamic space-time weight through operations of dynamic multi-feature embedding, parallel space-time self-attention, cross attention fusion and the like; and the fuzzy-PMV decision engine fuzzifies the atlas and PMV comfort indexes, outputs an equipment regulation and control instruction set through expert rule matching and defuzzification, and realizes closed-loop control from environmental data to equipment actions. Compared with the prior art, the method can accurately analyze the space-time correlation of building environment parameters, adaptively regulate and control equipment, improve the environment comfort and regulation and control efficiency, has the advantages of energy conservation and intelligence, and is suitable for the field of intelligent building environment control.

The invention provides a GIS installation intelligent integrated environment control method and system, and the method comprises the steps: obtaining multi-mode real-time data; based on the multi-modal real-time data, obtaining an installation process stage; inputting the multi-modal real-time data and the installation process stage into an environment prediction and decision-making model to generate an optimization regulation and control instruction; wherein the environment prediction and decision model is obtained based on data training of a historical database; and controlling an execution module according to the optimization regulation and control instruction so as to dynamically adjust the installation environment. The technical problems that in the prior art, differentiation and dynamic requirements of different installation process stages for environmental conditions are difficult to perceive and adapt, regulation and control are lagged and not accurate enough, and therefore the risk of equipment quality defects and even operation faults caused by the fact that the environment does not reach the standard in the installation process is increased are solved.

The invention discloses an indoor environment control system, method and device and a storage medium, and relates to the technical field of environment control, and the system comprises a multi-mode sensor array which is used for obtaining data of a physical field, a physiological field and a behavior field in an indoor environment at the same time; the digital twin engine is used for generating three-dimensional transient environment-human body coupling prediction within second-level time; the multi-agent deep reinforcement learning controller is used for outputting an optimal action sequence of the equipment under the condition of meeting a'comfort-health-energy consumption 'combined constraint condition; the safety correction module is used for ensuring that the system action meets a preset safety boundary through a Lyapunov function; and the communication interface is used for interacting with a local device, an edge node or a cloud platform. The invention further provides a control method, various indoor environment parameters can be comprehensively, intelligently and efficiently adjusted, and the energy-saving, comfortable and personalized indoor environment control target is achieved.

The invention relates to an indoor environment control system and method, a centralized control device and air conditioning devices. The system comprises the centralized control device, a plurality of indoor environment sensing devices and a plurality of air conditioning devices. Wherein the plurality of indoor environment sensing devices are arranged at different positions of the inner wall of the spherical building, the plurality of indoor environment sensing devices are electrically connected with the centralized control device, and the plurality of indoor environment sensing devices are used for collecting indoor environment parameters corresponding to different positions of the spherical building; the multiple air conditioning devices are annularly arranged at different edge positions of the bottom face of the spherical building, electrically connected with the centralized control device and used for determining respective target air outlet angles according to control instructions or indoor environment parameters sent by the centralized control device. And the respective air outlet angles are adjusted according to the target air outlet angle. In this way, the uniformity of the indoor temperature of the spherical building is effectively improved, and then the purpose of improving the indoor environment control effect is achieved.

A data storage device may include a sealed inner enclosure, wherein a gaseous environment inside the sealed inner enclosure differs from a standard air environment; an outer cover arranged over and coupled to at least one section of the sealed inner enclosure; and an environment-controlling substance located between the sealed inner enclosure and the outer cover. The sealed inner enclosure has at least one membrane to allow the environment-controlling substance to influence the gaseous environment inside the sealed inner enclosure.A method for manufacturing a data storage device may include: sealing an inner enclosure of the data storage device; attaching an outer cover to the data storage device; enclosing an environment-regulating substance between the inner enclosure and the outer cover; and creating a non-standard air environment inside the inner enclosure of the data storage device.

An optimal environment control model for an AIoT-based heating and cooling energy saving service is disclosed. The optimal environment control model for an AIoT-based heating and cooling energy saving service according to the present invention includes: an image-based store environment detection model that collects images within a store to detect the environment of the store; an optimal control plan model that creates a plan to maintain the indoor temperature at a target temperature by controlling the operation of the heating and cooling unit in consideration of the detected environment; and a power consumption prediction model that predicts the amount of power consumed during a set period by controlling the operation of the heating and cooling unit according to the plan.