12results about How to "Minimize energy consumption" patented technology

The invention provides a water plant raw water and clear water lifting pump station joint optimization energy-saving dispatching method and system for solving the problems that traditional pump station dispatching depends on artificial experience, global optimization is lacked, and energy waste is serious. Comprising the steps that a flow-lift and flow-efficiency relation model is established, and a variable frequency pump deduces a performance formula under any frequency based on the similarity law; in the first-stage optimization scheduling, the optimal flow of a water intake pumping station and the optimal water storage level of a clean water tank in each time period are determined by adopting a dynamic programming algorithm and taking the minimum total work of the system as a target, and the conditions of flow balance, water level constraint and the like are met; and in the second-stage optimization scheduling, the genetic algorithm is adopted to optimize the combination and operation frequency of the water pumps in each time period by taking the minimum total power of the pump set as a target, and a flow and lift deviation penalty term is introduced. According to the method, water taking, water storage and water supply whole-process collaborative optimization is achieved, the energy saving rate exceeds 10%, the operation cost is reduced, the method adapts to dynamic changes of the water source tide level and the water demand, and the dispatching intelligent level is improved.

The invention relates to the technical field of shield tunnel engineering, and discloses an intelligent energy management method and system for a shield tunneling machine, and the method comprises the steps: S1, sensor deployment and data collection: respectively installing sensors in a cutterhead driving system, a duct piece installation system, a propulsion system and a grouting system of the shield tunneling machine, the extraction module is used for extracting energy consumption and construction state parameters of each subsystem of the shield tunneling machine; s2, data preprocessing is carried out on the collected real-time tunnel face geological parameters and corresponding subsystem energy consumption parameters, and a'geological condition-equipment working condition-energy consumption 'multi-dimensional mapping model is constructed based on a machine learning algorithm and used for outputting theoretical optimal energy consumption intervals under different working conditions; and S3, based on the progress of the construction task and the energy consumption efficiency of each subsystem, combining the model constructed in the S2, and dynamically adjusting the energy distribution priority of each subsystem through a multi-objective optimization algorithm. According to the method, collaborative optimization of construction efficiency and energy consumption is facilitated, the total energy consumption of the shield tunneling machine can be reduced, and the energy-saving effect is more remarkable.

The invention discloses a wireless federated learning energy consumption optimization method and a medium, and belongs to the technical field of wireless communication, and the method comprises the steps: building a bidirectional model compression frame based on a wireless federated learning system model, and building a joint optimization problem with the minimization of the total energy consumption of the system as a target and a model convergence condition as a constraint; solving the joint optimization problem by adopting an alternating iterative optimization algorithm, and solving a sub-problem of optimal bandwidth allocation and a sub-problem of optimal bidirectional sparseness parameters; and executing compressed global model issuing and local model uploading between the central server and the client according to the solved optimal bandwidth allocation and the optimal bidirectional sparseness parameter. According to the method, the minimization of the total energy consumption of the system is realized on the premise of ensuring the model precision by constructing the bidirectional model compression framework and the bandwidth joint optimization, the method is particularly suitable for large-scale deployment, the communication overhead can be reduced, the model performance of federal learning can be maintained, and the collaborative optimization of the energy efficiency and the precision can be realized.

The application relates to the technical field of clean room air conditioner air outlet design, in particular to a clean room air conditioner air outlet optimization design method based on fluid dynamics; through construction of a multi-physical field coupling simulation model based on a fluid dynamics model, accurate prediction of a temperature field, a flow velocity field and a pollutant concentration field in the clean room is realized; the method takes Reynolds average NS equations and a discrete phase model as cores, combines a Standard k-epsilon turbulent flow model and a wall surface function method, effectively captures complex air flow organization and particle diffusion behavior in the clean room, provides a high-precision data basis for subsequent multi-target optimization, minimizes energy consumption under the premise of guaranteeing air quality, and has important engineering application value; and the technical problem that existing clean room air conditioner air outlet design methods mainly depend on experience and industry standards or focus on optimization of a single parameter and fail to fully consider the action of multiple factors is solved.

The invention belongs to the technical field of environmental engineering, and particularly relates to a contaminated soil micro-foam leaching device and method based on the ATP forming principle, a supporting table is fixedly provided with a large crossed roller bearing, the large crossed roller bearing is provided with three high-frequency vibration tables, the three high-frequency vibration tables are each provided with a reaction tank, and the reaction tanks are arranged on the supporting table; the three reaction tanks are sequentially arranged in a clockwise mode to be a filling station, a leaching station and a discharging station, a discharging component is arranged on the filling station, a micro-foam generating module is arranged on one side of the leaching station and arranged on a supporting table, an anti-leakage collecting barrel is arranged below the discharging station, and a discharging component is arranged on the discharging station. The technical scheme is innovated from the aspect of mass transfer principle, continuous physical conveying of soil can be achieved, targeted transfer of pollutants from the soil to a leaching medium can be actively driven through an ATP bionic mechanism, and three core challenges of mass transfer efficiency, operation cost and secondary pollution are systematically solved.

This invention provides an economical operation system and control method for CAES (Compressed Air Storage) units after load shedding, belonging to the field of compressed air energy storage. The method first executes a load shedding process after the unit is disconnected from the grid, causing the speed to drop back to a preset value. Then, by acquiring energy consumption data for three strategies—continuous operation of the single-stage expander, intermittent control, and restart after shutdown—and combining the intersection of energy consumption curves, an energy consumption threshold is determined. Finally, based on the comparison between the unit's real-time energy consumption and the energy consumption threshold, the optimal operating strategy is dynamically selected. This method solves the problem of high air consumption during traditional continuous operation and avoids the drawback of long downtime and reconnection time, minimizing total energy consumption during the disconnection and reconnection period. Furthermore, the intermediate-stage expander in the system is equipped with an independent intake regulating valve and intake pipe, enabling control of the single-stage expander. The solution of this invention solves the problems of low operating efficiency and wasted air resources in existing technologies, improving the system's economy.

The invention discloses an automatic ammonia water concentration intelligent adjustment and safety control system, and relates to the technical field of ammonia water concentration automatic control and safety protection, and the system comprises a concentration detection module which adopts a high-precision sensor and a temperature compensation unit, and transmits the processed data to an intelligent control module; the intelligent control module carries a processor and a self-adaptive algorithm and compares data to calculate deviation; the medicament conveying module is used for controlling the conveying flow proportion according to an instruction to form closed-loop control; the stirring and mixing module consists of a variable frequency motor and a stirring paddle, and dynamically adjusts the rotating speed according to deviation, volume and specification; the safety monitoring module integrates multiple types of sensors and monitors multi-dimensional parameters; the data storage and communication module adopts a double-storage architecture and stores various data; and the man-machine interaction module is provided with a touch screen and keys, displays information and supports operation. The concentration adjustment is accurate, and the temperature compensation and closed-loop control guarantee the concentration stability; remote control is safe and traceable, and various use requirements are met.

The application provides an industrial facility energy control method and system based on big data, relates to the technical field of big data, and comprises the following steps: obtaining the running state and energy consumption data of an energy consumption unit and extracting an energy consumption time sequence feature vector; identifying an energy consumption correlation mode through correlation rule mining; constructing a dynamic energy consumption prediction model; predicting an energy consumption value in a to-be-predicted period; and generating a collaborative control strategy through a multi-objective optimization algorithm and issuing a control instruction based on the coupling strength in an energy consumption correlation relationship diagram. The application realizes collaborative optimization control of multiple energy consumption units, reduces overall energy consumption, and improves energy utilization efficiency.

This application discloses a method, device, and medium for temperature control of electronic devices using a thermal field coordination mechanism. The method includes: acquiring temperature data collected from multiple temperature control points of the electronic device under test (DUT), and normalizing the temperature data; determining the weight values ​​corresponding to each temperature control point; obtaining a dimensionless weighted average temperature corresponding to the DUT based on the normalized temperature data and weight values; adjusting the speed of multiple preset cooling fans using a multi-fan simultaneous speed control method based on the temperature control target of the DUT; identifying the temperature control points that do not meet the preset device temperature conditions, and adjusting the speed of the preset cooling fans corresponding to the temperature control points using a target-oriented multi-fan speed monotonic power consumption optimization control method until the temperature data corresponding to the temperature control points meets the preset device temperature conditions, thereby obtaining the adjusted fan temperature control parameters. This method improves heat dissipation efficiency.

This invention discloses an energy-saving control method for new energy substations based on digital management, belonging to the field of power system automation and energy management technology. The method includes: constructing a multi-source data fusion sensing layer to collect data such as main transformer operating parameters, reactive power compensation status, auxiliary system load, and ambient temperature and humidity; establishing a dynamic energy efficiency evaluation model with the goal of minimizing comprehensive energy consumption, integrating main transformer losses, reactive power switching losses, auxiliary system energy efficiency, and ambient temperature correction factors; generating a coordinated control strategy for main transformer tap positions, reactive power switching, and cooling system start / stop using a rolling optimization algorithm, and verifying safety boundaries and action frequency constraints; executing closed-loop control and online correction strategies based on deviation feedback; and adaptively updating model parameters using the recursive least squares method, combined with an energy efficiency knowledge base to improve response speed. This invention achieves accurate modeling of the entire substation's energy consumption and multi-factor coordinated optimization, significantly reducing the substation's electricity consumption while ensuring safety and new energy consumption.

This invention relates to a method of operating a wireless logger device at least prior to placing the logger device in a transport mode where the logger device is configured to monitor an environmental related parameter of an asset while the asset is transported from an origin location to a destination location. The method includes setting the logger device in a first low-power mode where the environmental related parameter is measured by the sensing device and where the resulting environmental related data is stored in the storage medium, where in the low-power mode the logger device communicates with an external data processing device with at least one first-time frequency where the logger device is temporarily set to a first higher-energy mode during the communication with the external data processing device. The invention further includes identifying if there is a deviation in the measured environmental related data, where in case a detected deviation exceeds a pre-defined deviation target, adjusting the logger device to a second higher energy mode and: checking if the logger device is to be set to a transport mode, where in case the checking results in that the logger device is to be set to a transport mode, adjusting the communication frequency with the external data processing device to a second-time frequency, the second-timer frequency being larger than the first-time frequency, where in case the checking results in that the logger device is not to be set to a transport mode, adjusting the logger device to a second low-power mode and adjusting the communication frequency with the external data processing device to at least one third-time frequency, at least one third-time frequency being lower than the second-time frequency

The invention relates to the technical field of temperature and humidity control, in particular to an intelligent temperature and humidity regulation and control method and system for aviation food cold chain transportation. According to the method, firstly, data cleaning is completed through space-time dimension verification of multi-node data, and high-confidence-coefficient feature parameters are generated; then synchronizing a flight profile and a destination weather forecast, and extracting a multi-dimensional environment factor containing thermal radiation intensity; on the basis, a heat exchange prediction model coupled with air pressure correction is constructed, and a full-voyage heat profit and loss curve is deduced; the electric quantity of the storage battery is further combined, and the pre-cooling triggering moment and the target deviation temperature are reversely optimized with food safety as a constraint; and finally, the frequency conversion compressor and the fan are cooperatively executed, and dynamic deviation correction is conducted in the falling stage according to the temperature change rate deviation. The technical problem that traditional aviation cold chain equipment is poor in resistance to extreme thermal shock on the ground is solved, accurate space-time transfer of cold energy from the high altitude to the ground is achieved, and the energy utilization efficiency is remarkably improved while food safety is guaranteed.